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high-performance computing resources, available on the cloud through |DesignSafe|, to enable parallel workflows for non-trivial large-scale NHE problems; - uncertainty quantification capabilities using `Dakota `_, which allows users to introduce input uncertainties that are propagated through the workflow with random variables; - - streamlined interfaces between existing software applications and datasets that are widely used by the NHE community, such as `OpenFOAM `_, `OpenSees `_, `ADCIRC `_, and `PEER Strong Ground Motion Databases `_. To do this, the SimCenter develops pre- and post-processors for these existing applications and utilizes web technologies for accessing online services; + - streamlined interfaces between existing software applications and datasets that are widely used by the NHE community, such as `OpenFOAM `_, |OpenSeesLink|, `ADCIRC `_, and `PEER Strong Ground Motion Databases `_. To do this, the SimCenter develops pre- and post-processors for these existing applications and utilizes web technologies for accessing online services; - additional custom software applications produced by the SimCenter. Among these are applications that automate the acquisition of building inventory data (`BRAILS `_), applications that simulate hazard events and generate corresponding input files for passing through the workflow system (RegionalEvent Applications), applications for damage and loss assessment (`pelicun `_), and more. - a modular framework that allows developers to incorporate their own software applications as components to the workflow system, so long as it meets the input-output structure at component interfaces. diff --git a/docs/_sources/common/developer_manual/architecture/desktop/c4model.rst.txt b/docs/_sources/common/developer_manual/architecture/desktop/c4model.rst.txt index be991c49..c6967f07 100644 --- a/docs/_sources/common/developer_manual/architecture/desktop/c4model.rst.txt +++ b/docs/_sources/common/developer_manual/architecture/desktop/c4model.rst.txt @@ -10,14 +10,14 @@ The SimCenter workflow systems are aimed at facilitating the use, reuse and exte Level 1: Context Diagram ------------------------ -A Level 1 diagram in :numref:`figContext` shows the system context for the SimCenter applications, i.e. how it fits in the world. In the diagram: +A Level 1 diagram in :numref:`c4model_figContext` shows the system context for the SimCenter applications, i.e. how it fits in the world. In the diagram: - the SimCenter computational applications (EE-UQ, WE-UQ, PBE, R2D) are shown in the center surrounded by the user and the systems it interacts with. - input data for the SimCenter applications can be obtained either from NHERI datasets accessible on the DesignSafe `Data Depot `_, shown to the right, or from web-based databases, shown to the left. - the SimCenter applications can then be run in conjunction with open-source software applications (such as Dakota, FEAP, OpenSees, Python, OpenFOAM, etc.) either on a local desktop, shown below, or using HPC resources on |DesignSafe|, shown to the right. .. figure:: figures/context.png - :name: figContext + :name: c4model_figContext :align: center :width: 800 :figclass: align-center @@ -28,10 +28,10 @@ A Level 1 diagram in :numref:`figContext` shows the system context for the SimCe Level 2: Container Diagram -------------------------- -A Level 2 diagram in :numref:`figContainer` demonstrates how the SimCenter applications are broken into high-level containers (applications, databases, etc.). Each of the SimCenter applications is broken into two components: A front-end UI and a back-end application that runs the workflow. The front-end is a desktop application written using the cross-platform `Qt framework `_. The back-end is an application that processes the input from the front-end, which comes in the form of a JSON file, creates a workflow and runs it. The workflow applications, written in Python, C, or C++, utilize existing applications where possible and run on either the local desktop machine or on an HPC utilizing resources made available to NHE community through DesignSafe. +A Level 2 diagram in :numref:`c4model_figContainer` demonstrates how the SimCenter applications are broken into high-level containers (applications, databases, etc.). Each of the SimCenter applications is broken into two components: A front-end UI and a back-end application that runs the workflow. The front-end is a desktop application written using the cross-platform `Qt framework `_. The back-end is an application that processes the input from the front-end, which comes in the form of a JSON file, creates a workflow and runs it. The workflow applications, written in Python, C, or C++, utilize existing applications where possible and run on either the local desktop machine or on an HPC utilizing resources made available to NHE community through DesignSafe. .. figure:: figures/container.png - :name: figContainer + :name: c4model_figContainer :align: center :width: 800 :figclass: align-center @@ -42,10 +42,11 @@ A Level 2 diagram in :numref:`figContainer` demonstrates how the SimCenter appli Level 3: Component Diagram -------------------------- -Two level 3 diagrams are now presented which break up the two containers into the major building blocks or components in C4 terminology. In :numref:`figComponentFront` the component diagram for the front-end UI is presented. It outlines the interaction between the user and the individual graphical elements (widgets) of the UI. Given the analogy of a jigsaw puzzle, the user selects which piece of the jigsaw puzzle they are working on in the component selection widget. The widget for the jigsaw piece will then be displayed on the desktop. The user for each jigsaw piece then selects which application to run for that piece, and for the chosen application, they provide the inputs. When the inputs are all provided, the user can select to run the simulations locally or remotely. For jobs that run remotely, the user can download and review previously run simulations. As seen the widgets may subsequently interact with web services through HTTPS requests, or with DesignSafe utilizing TAPIS Restful API through the RemoteService container. +Two level 3 diagrams are now presented which break up the two containers into the major building blocks or +components in C4 terminology. In :numref:`c4model_figComponentFront` the component diagram for the front-end UI is presented. It outlines the interaction between the user and the individual graphical elements (widgets) of the UI. Given the analogy of a jigsaw puzzle, the user selects which piece of the jigsaw puzzle they are working on in the component selection widget. The widget for the jigsaw piece will then be displayed on the desktop. The user for each jigsaw piece then selects which application to run for that piece, and for the chosen application, they provide the inputs. When the inputs are all provided, the user can select to run the simulations locally or remotely. For jobs that run remotely, the user can download and review previously run simulations. As seen the widgets may subsequently interact with web services through HTTPS requests, or with DesignSafe utilizing TAPIS Restful API through the RemoteService container. .. figure:: figures/componentFront.png - :name: figComponentFront + :name: c4model_figComponentFront :align: center :width: 800 :figclass: align-center @@ -53,11 +54,11 @@ Two level 3 diagrams are now presented which break up the two containers into th Component diagram for front end UI. -The component diagram for the backend application shown in :numref:`figComponentBack`, shows that the backend is made up of a number of component applications. The application ``femUQ.py`` is the application that parses the input from the front end, sets up the workflow by creating a ``workflow_driver`` script and then launches the UQ engine. Which UQ Engine and which applications to run in the workflow, is determined from the data passed from the UI and information contained in a file, ``WorkflowApplication.json``. The ``WorkflowApplication.json`` file is a file that maps the applications specified in the output from the UI with a specific application contained on the user's local machine or at the remote HPC resource, as such it allows the researchers to modify the applications that may be run in the workflow w/o the need to recompile the application. Once the ``workflow_driver`` file is created, control is passed to a UQ engine, which repeatedly runs the ``workflow_driver`` to generate the results. In running the workflow some of the applications will invoke applications not developed to meet the API. For such applications, pre- and post-processors are provided. The figure shows the backend application running locally or remotely on an HPC at DesignSafe. +The component diagram for the backend application shown in :numref:`c4model_figComponentBack`, shows that the backend is made up of a number of component applications. The application ``femUQ.py`` is the application that parses the input from the front end, sets up the workflow by creating a ``workflow_driver`` script and then launches the UQ engine. Which UQ Engine and which applications to run in the workflow, is determined from the data passed from the UI and information contained in a file, ``WorkflowApplication.json``. The ``WorkflowApplication.json`` file is a file that maps the applications specified in the output from the UI with a specific application contained on the user's local machine or at the remote HPC resource, as such it allows the researchers to modify the applications that may be run in the workflow w/o the need to recompile the application. Once the ``workflow_driver`` file is created, control is passed to a UQ engine, which repeatedly runs the ``workflow_driver`` to generate the results. In running the workflow some of the applications will invoke applications not developed to meet the API. For such applications, pre- and post-processors are provided. The figure shows the backend application running locally or remotely on an HPC at DesignSafe. .. figure:: figures/componentBack.png - :name: figComponentBack + :name: c4model_figComponentBack :align: center :width: 800 :figclass: align-center @@ -128,7 +129,7 @@ Now that the UI has been handed over to the backend application, the backend app .. figure:: figures/sequenceLocal.png - :name: figSequenceLocal + :name: c4model_figSequenceLocal :align: center :width: 800 :figclass: align-center @@ -136,11 +137,14 @@ Now that the UI has been handed over to the backend application, the backend app Sequence diagram showing what happens when a workflow runs locally. -That is for the case where the computations are performed on the local computer. When the computations are performed remotely the steps are different. The first 8 steps are the same. But now the UQwrapper will not start the UQ engine. Instead, control is returned to the UI. The UI will, as shown in the following: (11) Compress the temporary folder. (12) Send the compressed folder to the remote HPC, shown in :numref:`figSequenceRemote`. (13) Start an application to perform the computations. All the remote data transfer and application invocation is down through a cloud service. The `TACC tapis `_ interface is used to provide SimCenter users with access to the TACC HPC resources through the DesignSafe portal. +That is for the case where the computations are performed on the local computer. When the computations are +performed remotely the steps are different. The first 8 steps are the same. But now the UQwrapper will not +start the UQ engine. Instead, control is returned to the UI. The UI will, as shown in the following: (11) +Compress the temporary folder. (12) Send the compressed folder to the remote HPC, shown in :numref:`c4model_figSequenceRemote`. (13) Start an application to perform the computations. All the remote data transfer and application invocation is down through a cloud service. The `TACC tapis `_ interface is used to provide SimCenter users with access to the TACC HPC resources through the DesignSafe portal. .. figure:: figures/sequenceRemote.png - :name: figSequenceRemote + :name: c4model_figSequenceRemote :align: center :width: 800 :figclass: align-center diff --git a/docs/_sources/common/developer_manual/architecture/desktop/file-types/Inputs.rst.txt b/docs/_sources/common/developer_manual/architecture/desktop/file-types/Inputs.rst.txt index 8a5c1fc9..27e13c57 100644 --- a/docs/_sources/common/developer_manual/architecture/desktop/file-types/Inputs.rst.txt +++ b/docs/_sources/common/developer_manual/architecture/desktop/file-types/Inputs.rst.txt @@ -17,6 +17,42 @@ The header schema, followed by an example input, is provided. Definitions for th :header-rows: 2 :align: center +.. _lblTransportationInputOption1: + +.. jsonschema:: File_Schema.json#/properties/Inputs/transportationSourceFile1 + +A JSON file containing highway transportation roadways, bridges, and tunnels for the response simulation and damage/loss estimation steps of the workflow. This file contains all the information necessary for constructing AIM files for each bridge, tunnel, and roadway. The JSON file must contain the "nodes" object and at lease one of the "hwy_bridges", "hwy_tunnels", and "roadways" object. Involved key-item pairs are: + +* "hwy_bridges": A JSON array of JSON Objects, each containing the following key/item pairs + +.. csv-table:: InputDataSchemaBridge.csv + :file: files/InputDataSchemaBridge.csv + :header-rows: 2 + :align: center + + +* "hwy_tunnels": A JSON array of JSON Objects, each containing the following key/item pairs + +.. csv-table:: InputDataSchemaTunnel.csv + :file: files/InputDataSchemaTunnel.csv + :header-rows: 2 + :align: center + + +* "roadways": A JSON array of JSON Objects, each containing the following key/item pairs + +.. csv-table:: InputDataSchemaRoadway.csv + :file: files/InputDataSchemaRoadway.csv + :header-rows: 2 + :align: center + + +* "nodes": A long JSON Objects containing the following key/item pairs + +.. csv-table:: InputDataSchemaTransportNode.csv + :file: files/InputDataSchemaTransportNode.csv + :header-rows: 1 + :align: center .. jsonschema:: File_Schema.json#/properties/Inputs/modelFile @@ -26,3 +62,5 @@ The header schema, followed by an example input, is provided. Definitions for th .. jsonschema:: File_Schema.json#/properties/Inputs/eventFiles + + diff --git a/docs/_sources/common/developer_manual/architecture/desktop/run-manually/runRemote.rst.txt b/docs/_sources/common/developer_manual/architecture/desktop/run-manually/runRemote.rst.txt index 450c8666..d9ddc5dc 100644 --- a/docs/_sources/common/developer_manual/architecture/desktop/run-manually/runRemote.rst.txt +++ b/docs/_sources/common/developer_manual/architecture/desktop/run-manually/runRemote.rst.txt @@ -49,7 +49,7 @@ This method uses Jupyter Notebook to run the job, accessing Tapis CLI in the bac :figclass: align-center -6. Specify settings for running the job on Stampede2. Submit the job by running all cells in the Jupyter Notebook (Cell > Run All). +6. Specify settings for running the job on Frontera. Submit the job by running all cells in the Jupyter Notebook (Cell > Run All). .. .. jsonschema:: App_Schema.json#/properties/runRemote @@ -151,7 +151,7 @@ You will see an output in the Ubuntu window similar to the following. ``vim job.json`` -9. Edit the job.json file to specify settings for running the job on Stampede2. To make edits in the VIM Editor, type ``Ctrl+I``. To exit out of the editor, type ``:wq``. +9. Edit the job.json file to specify settings for running the job on Frontera. To make edits in the VIM Editor, type ``Ctrl+I``. To exit out of the editor, type ``:wq``. 10. Once the job.json file is prepared, submit the job by running the command: diff --git a/docs/_sources/common/developer_manual/architecture/desktop/workflows.rst.txt b/docs/_sources/common/developer_manual/architecture/desktop/workflows.rst.txt index de89e39c..1cf3af21 100644 --- a/docs/_sources/common/developer_manual/architecture/desktop/workflows.rst.txt +++ b/docs/_sources/common/developer_manual/architecture/desktop/workflows.rst.txt @@ -3,7 +3,7 @@ Creating Workflows ********************** -In the |app|, users may create a custom workflow to perform regional loss assessment for earthquake, wind, and storm surge hazards at varying levels of fidelity. Components of the workflow must be chosen to match a user's particular hazard type and available data on the hazard. +In the |app|, users may create a custom workflow, named rWHALE, to perform regional loss assessment for earthquake, wind, and storm surge hazards at varying levels of fidelity. Components of the workflow must be chosen to match a user's particular hazard type and available data on the hazard. For a guide on preparing a workflow, refer to the following pages: diff --git a/docs/_sources/common/developer_manual/how_to_build/desktop/how_to_build.rst.txt b/docs/_sources/common/developer_manual/how_to_build/desktop/how_to_build.rst.txt index 0933af28..5fb906f5 100644 --- a/docs/_sources/common/developer_manual/how_to_build/desktop/how_to_build.rst.txt +++ b/docs/_sources/common/developer_manual/how_to_build/desktop/how_to_build.rst.txt @@ -25,7 +25,13 @@ First, ensure the following dependencies are installed: * **Python**: The workflow requires at least Python 3.7. -* **Conan**: This repository uses `Conan `_ for dependency management. Conan is a python library and can be installed using the following `instructions `_. Version 1.25 or later is recommended. +* **Conan**: This repository uses `Conan `_, a python library, for dependency management. **Install conan version 1.60.2**, for example, through + + .. code:: console + + pip install conan==1.60.2 + + | See the `instructions `_ if alternative installation methods are needed * **CMake**: This repository uses `CMake `_ for managing the build process. Version 3.15 or later is recommended. @@ -183,7 +189,7 @@ You now have two ways to build the application: (1) using the **Qt Creator** des Build using Qt Creator ----------------------- +======================== 1. Start Qt Creator, then open the |short tool id|.pro file located in the |short tool id| directory that was downloaded in the previous step. 2. Setup the development kit in Qt Creator. This is usually done by selecting the Qt version, compiler, and configuration and following the onscreen dialog. @@ -191,7 +197,7 @@ Build using Qt Creator Build from the Terminal ------------------------ +======================== The operations are similar to what was done when building the backend applications. In the terminal application, starting inside the directory of the cloned application again, you will create a build directory, cd into that build directory, run **qmake**, and finally make (or on Windows nmake) to create the application. @@ -247,12 +253,10 @@ Once built, the tool **Preferences** needs to be modified. To do this, open the #. Custom Local Application: Here, select the checkbox to the left, and then provide the path to the SimCenterBackendApplications directory. The code assumes that the folder **applications**, which you created when building the backend applications, exists. + .. _figPreferences: .. only:: notQuoFEM - - .. _figPreferences: - .. figure:: figures/Preferences.png :align: center :figclass: align-center @@ -261,11 +265,9 @@ Once built, the tool **Preferences** needs to be modified. To do this, open the .. only:: quoFEM_app - - .. _figPreferences: - .. figure:: figures/Preferences_qfem.png :align: center :figclass: align-center Preferences Dialog + diff --git a/docs/_sources/common/front-matter/cite.rst.txt b/docs/_sources/common/front-matter/cite.rst.txt index 23236b96..e6848e5c 100644 --- a/docs/_sources/common/front-matter/cite.rst.txt +++ b/docs/_sources/common/front-matter/cite.rst.txt @@ -6,10 +6,8 @@ How To Cite .. only:: R2D_app - 1. Frank McKenna, Stevan Gavrilovic, Adam Zsarnoczay, Kuanshi Zhong, Wael Elhaddad, and - Pedro Arduino (2022). - NHERI-SimCenter/R2DTool: Version 2.1.0. - Zenodo. `DOI 10.5281/zenodo.6404528 `_ + 1. Frank McKenna, Stevan Gavrilovic, Zsarnoczay, A., Zhao, J., Zhong, K., Barbaros Cetiner, Yi, S.-. ri ., Elhaddad, W., & Arduino, P. (2024). + NHERI-SimCenter/R2DTool: Version 4.0.0 (v4.0.0). Zenodo. `DOI 10.5281/zenodo.4483614 `_ .. only:: PBE_app @@ -27,15 +25,15 @@ How To Cite .. only:: WEUQ_app 1. Frank McKenna, Abiy F. Melaku, Fei Ding, Jiawei Wan, Peter Mackenzie-Helnwein, Wael Elhaddad, & - Michael Gardner. (2023). NHERI-SimCenter/WE-UQ: Version 3.0.0 (v3.0.0). - Zenodo. `DOI: 10.5281/zenodo.8133017 `_ + Michael Gardner. (2023). NHERI-SimCenter/WE-UQ: Version 3.1.0 (v3.1.0). + Zenodo. `DOI: 10.5281/zenodo.8396121 `_ .. only:: quoFEM_app - 1. Frank McKenna, Sang-ri Yi, Aakash Bangalore Satish, Kuanshi Zhong, Adam Zsarnoczay, & Wael Elhaddad. (2023). - NHERI-SimCenter/quoFEM: Version 3.3.0 (v3.3.0). - Zenodo. `DOI: 10.5281/zenodo.6404498 `_ + 1. Frank McKenna, Sang-ri Yi, Aakash Bangalore Satish, Adam Zsarnoczay, Kuanshi Zhong, Michael Gardner, & Wael Elhaddad. (2023). + NHERI-SimCenter/quoFEM: Version 3.5.0 (v3.5.0). + Zenodo. `DOI: 10.5281/zenodo.10443180 `_ 2. Gregory G. Deierlein, Frank McKenna, Adam Zsarnóczay, Tracy Kijewski-Correa, Ahsan Kareem, diff --git a/docs/_sources/common/front-matter/desktop/ack_pbe.rst.txt b/docs/_sources/common/front-matter/desktop/ack_pbe.rst.txt index 41355410..fddbc39b 100644 --- a/docs/_sources/common/front-matter/desktop/ack_pbe.rst.txt +++ b/docs/_sources/common/front-matter/desktop/ack_pbe.rst.txt @@ -1,4 +1,4 @@ -.. _lblAcknowledgements: +.. _lblPBEAcknowledgements: *************** Acknowledgments diff --git a/docs/_sources/common/technical_manual/desktop/HazardSimulationTool_useCase.rst.txt b/docs/_sources/common/technical_manual/desktop/HazardSimulationTool_useCase.rst.txt new file mode 100644 index 00000000..cb7d7be0 --- /dev/null +++ b/docs/_sources/common/technical_manual/desktop/HazardSimulationTool_useCase.rst.txt @@ -0,0 +1,131 @@ +.. _lblEQSimulationUseCases: +Regional Earthquake Hazard Use Cases +==================================================== +The major use cases of Regional Earthquake Hazard in R2D can be divided +into Scenario-specific or Probabilistic Seismic Hazard Analysis. + +.. _fig-R2DScenarioOrPSHA: + +.. figure:: figures/R2DScenarioOrPSHA.png + :align: center + :figclass: align-center + + Specific Earthquake Scenario or Probabilistic Hazard Analysis. + +Scenario-specific Earthquake +----------------------------- +This option is to analyze an earthquake scenario that consists of one or more ruptures +based on an earthquake description of a past or hypothetical event. Some use cases +for which this option are: + #. Analysis of a single rupture. For example, running the "Hayward-Rodgers Creek; HN+HS" segment, which is a specific rupture location, length, characteristics, etc. + #. Broader analysis of a scenario. For example, running "an M7 earthquake on the San Andreas Fault." This would include realizations with different ruptures, that all describe an M7 on the San Andreas. + #. Multiple specified ruptures. This would be used in the case in which a user already has a defined set of ruptures they are interested in studying. This option does not fully capture the probabilistic seismic hazard of a region. + #. A past earthquake. For example, recreating the Loma Prieta earthquake. + +:numref:`fig-R2DScenarioSpecificUseCases` shows typical scenario-specific use cases in R2D. +All the use cases in :numref:`fig-R2DScenarioSpecificUseCases` can be achieved with R2D. The first two options are loading predefined +ground motion records or intensity measures in the region, and are described in +:ref:`User-specified Ground Motions `. The functionality to +interface with some physics-based earthquake simulation databases is also under development in R2D. +The third to fifty use cases in :numref:`fig-R2DScenarioSpecificUseCases` requires +the :ref:`earthquake hazard simulation tool `, and the last option +can be achieved as described in :ref:`ShakeMap Earthquake Scenarios `). + +The functions in the earthquake hazard simulation tool required for +scenario-specific use cases are Site Definition, +Earthquake Rupture Forecasting, Intensity Measure Definition, Ground Motion Prediction +Equations, Spatial Correlations and Ground Motion Record Selection (optional). +The "Scenario-specific" option should be selected in the "Scenario Selection" tool tab. +More details of the use cases, required inputs, and some benefits/limitations are +summarised in :numref:`tab-R2DScenarioSpecificUseCases`. + + +.. _fig-R2DScenarioSpecificUseCases: + +.. figure:: figures/R2DScenarioSpecificUseCases.png + :align: center + :figclass: align-center + + Scenario-specific earthquake hazard use cases. + +.. _tab-R2DScenarioSpecificUseCases: + +.. list-table:: Typical Scenario-specific Earthquake Hazard Use Cases + :widths: 25 60 60 60 + :header-rows: 1 + + * - Use Case + - Recommended Uses + - Required Inputs + - Benefits/Limitations + * - Predefined GM + - User already has ground motion time histories they are interested in. + - Describe any specific file type/folder structure required. + - + * - Predefined IM + - User already has an IM field they are interested in. GM selection can be done. + - Describe any specific file type/folder structure required. + - + * - OpenSHA/UCERF + - Recommended where UCERF ruptures are available (maybe we can show a map). Recommended because it requires no additional inputs other than selections using the R2D interface (source models are openly available). + - No external files are required and all selection can be done in R2D. + - Users can select out of several choices of GMM and correlation models to use through the R2D interface. Limited in that it only has information available about ruptures in certain locations. + * - OpenQuake + - Recommended to describe distributed and background seismicity. Also recommended for use where rupture information is unavailable through UCERF. + - External source model file required. The format of source models can be found :ref:`here `, and a database of global earthquake sources can be found at the `GEM's Global Active Faults Database `_ [Styron2020]_ + - Can be used to describe distributed and background seismicity where information on the faults is unavailable. + * - Point Source + - For educational and/or academic use only. The point source option does not accurately reflect real faults. + - No external files are required and all selection can be done in R2D. + - Not representative of real faults/scenarios. + * - ShakeMap + - Re-creation of a past earthquake event by obtaining seismic intensity measures sufficiently representative of the event. + - Inputs are USGS ShakeMap files for a given earthquake scenario. These files must be located in a folder in which at least must be a grid.xml file. These files contain ShakeMaps that include the intensity measures for a given earthquake event as spectral ordinate values (Those can be given as PGA, PGV, PGD and spectral ordinates at different periods). These files can be obtained from `USGS's ShakeMap archives `_ for real past earthquake events. + - ShakeMap intensity measures (as spectral ordinates) for past earthquakes might not be an accurate representation of this event in locations far from the grid control points (usually recording stations where GMM predictions are adjusted to match real recorded ground motion spectra). Moreover, the set of scenarios is limited. + + +Regional Probabilistic Seismic Hazard Analysis +---------------------------------------------- +The regional probabilistic seismic hazard analysis (PSHA) characterizes the probability +of certain levels of intensity are exceeded in a region considering all nearby +earthquake sources. +:numref:`fig-R2DScenarioSpecificUseCases` shows two typical use cases in regional PSHA. +Both use cases can be achieved in R2D with the :ref:`earthquake hazard simulation tool `. +The functions in the earthquake hazard simulation tool required for +regional PSHA are Site Definition, +Earthquake Rupture Forecasting, Intensity Measure Definition, Ground Motion Prediction +Equations, Spatial Correlations, Ground Motion Record Selection (optional), and hazard consistent +downsamping (optional). The "Conventional Monte Carlo" or "Hazard consistent downsampling" option +should be selected in the "Scenario Selection" tool tab. More details of the use cases, +required inputs, and some benefits/limitations are summarised in :numref:`tab-R2DRegionalPSHAUseCases`. + +.. _fig-R2DRegionalPSHAUseCases: + +.. figure:: figures/R2DRegionalPSHAUseCases.png + :align: center + :figclass: align-center + + Regional probabilistic seismic hazard analysis use cases. + +.. _tab-R2DRegionalPSHAUseCases: + +.. list-table:: Typical Regional Probabilistic Seismic Hazard Analysis Use Cases + :widths: 25 60 60 60 + :header-rows: 1 + + * - Use Case + - Recommended Uses + - Required Inputs + - Benefits/Limitations + * - OpenSHA/UCERF + - Recommended where UCERF ruptures are available (maybe we can show a map). Recommended because it requires no additional inputs other than selections using the R2D interface (source models are openly available). + - No external files are required, and all selections can be done in R2D. + - Only available for California. + * - OpenQuake + - Recommended for use where UCERF ruptures are unavailable. + - External files required. The format of source models can be found :ref:`here `, and a database of global earthquake sources can be found at the `GEM's Global Active Faults Database `_ [Styron2020]_ + - Users need to prepare their earthquake source model. + + +.. [Styron2020] + Styron, Richard, and Marco Pagani. “The GEM Global Active Faults Database.” Earthquake Spectra, vol. 36, no. 1_suppl, Oct. 2020, pp. 160–180, doi:10.1177/8755293020944182. diff --git a/docs/_sources/common/technical_manual/desktop/SimCenterUQTechnical.rst.txt b/docs/_sources/common/technical_manual/desktop/SimCenterUQTechnical.rst.txt index 551a8ea3..e757cd5a 100644 --- a/docs/_sources/common/technical_manual/desktop/SimCenterUQTechnical.rst.txt +++ b/docs/_sources/common/technical_manual/desktop/SimCenterUQTechnical.rst.txt @@ -3,6 +3,8 @@ Methods in SimCenterUQ Engine ***************************** +.. _lbluqSimTechnical_Nataf: + Nataf transformation ==================== @@ -34,6 +36,22 @@ For the Nataf transformation, the SimCenterUQ engine borrows a part of the distr Global sensitivity analysis =========================== +Video Resources +------------------ +Global Sensitivity Analysis: why, what, and how. + +.. raw:: html + +
+ +
+ +.. raw:: html + +


Click to replay the video from 2:14.

+ + + Variance-based global sensitivity indices ----------------------------------- Global sensitivity analysis (GSA) is performed to quantify the contribution of each input variable to the uncertainty in QoI. Using the global sensitivity indices, users can set preferences between random variables considering both inherent randomness and its propagation through the model. GSA helps users to understand the overall impact of different sources of uncertainties, as well as accelerate UQ computations by focusing on dominant dimensions or screening out trivial input variables. diff --git a/docs/_sources/common/technical_manual/desktop/UCSDUQTechnical.rst.txt b/docs/_sources/common/technical_manual/desktop/UCSDUQTechnical.rst.txt index e5e4191a..27dd19f9 100644 --- a/docs/_sources/common/technical_manual/desktop/UCSDUQTechnical.rst.txt +++ b/docs/_sources/common/technical_manual/desktop/UCSDUQTechnical.rst.txt @@ -3,8 +3,10 @@ Methods in UCSD UQ Engine ************************* -Transtitional Markov chain Monte Carlo -====================================== +.. _lbluqUCSD_TMCMC: + +Transitional Markov chain Monte Carlo +===================================== TMCMC is a numerical method used to obtain samples of the target posterior PDF. This algorithm is flexible, applicable in general settings, and parallelizable. Thus, it can be used to effectively sample the posterior PDF, when the likelihood function involves a computationally expensive FE model evaluation, using high-performance computing (HPC) resources. @@ -22,7 +24,7 @@ but to sample from a series of simpler intermediate probability distributions th p(\theta|y)_j \propto p(y | \theta)^{\beta_j} \times p(\theta); \quad j = 0, 1, \ldots, m; \quad 0 = \beta_0 < \beta_1 < \ldots < \beta_m = 1 Index :math:`j` denotes the stage number, :math:`m` denotes the total number of stages, and :math:`p (\mathbf{\theta \ | \ y})_j` is the tempered posterior PDF at stage :math:`j` controlled by the parameter :math:`\beta_j`. At the initial stage :math:`(j = 0)`, parameter :math:`\beta_0 = 0`, the tempered distribution :math:`p(\mathbf{\theta \ | \ y})_{j=0}` is just the -prior joint PDF :math:`p(\theta)`. The TMCMC sampler progresses by monotonically increasing the value of :math:`\beta_j` , at each stage :math:`j`, until it reaches the value of 1. At the final stage :math:`(j = m)`, parameter :math:`\beta_m = 1`, the tempered distribution :math:`p(\mathbf{\theta \ | \ y})_{j = m}` is the target posterior joint PDF :math:`p(\mathbf{\theta \ | \ y})`. +prior joint PDF :math:`p(\theta)`. The TMCMC sampler progresses by monotonically increasing the value of :math:`\beta_j`, at each stage :math:`j`, until it reaches the value of 1. At the final stage :math:`(j = m)`, parameter :math:`\beta_m = 1`, the tempered distribution :math:`p(\mathbf{\theta \ | \ y})_{j = m}` is the target posterior joint PDF :math:`p(\mathbf{\theta \ | \ y})`. TMCMC represents the tempered posterior PDF at every stage by a set of weighted samples (known as particles). TMCMC approximates the :math:`j^{th}` stage tempered posterior PDF :math:`p(\mathbf{\theta \ | \ y})_j` by weighing, resampling, and perturbing the particles of the :math:`j-1^{th}` stage intermediate joint PDF :math:`p(\mathbf{\theta \ | \ y})_{j-1}` . For details about the TMCMC algorithm, the interested reader is referred to Ching and Chen [Ching2007]_, Minson et. al. [Minson2013]_. @@ -32,4 +34,196 @@ TMCMC represents the tempered posterior PDF at every stage by a set of weighted J. Ching and Y.-C. Chen, “Transitional Markov Chain Monte Carlo Method for Bayesian Model Updating, Model Class Selection, and Model Averaging”, *Journal of Engineering Mechanics*, 133(7), 816-832, 2007. .. [Minson2013] - S. E. Minson, M. Simons, and J. L. Beck, “Bayesian Inversion for Finite Fault Earthquake Source Models I-Theory and Algorithm”, *Geophysical Journal International*, 194(3), 1701- 1726, 2013. \ No newline at end of file + S. E. Minson, M. Simons, and J. L. Beck, “Bayesian Inversion for Finite Fault Earthquake Source Models I-Theory and Algorithm”, *Geophysical Journal International*, 194(3), 1701- 1726, 2013. + + +.. _lbluqUCSD_hierarchical: + +Bayesian Inference of Hierarchical Models +========================================= + +Consider for model calibration a dataset consisting of experimental results on test specimens of the same kind. Let :math:`\mathbf{y}_i` denote the measured output response of the :math:`i^{th}` specimen in the dataset :math:`\mathbf{Y} = \{\mathbf{y}_1, \mathbf{y}_2, ..., \mathbf{y}_{N_s}\}` where :math:`N_s` designates the number of specimens. Let :math:`\theta_i` be the model parameter vector corresponding to the :math:`i^{th}` specimen, where :math:`n_\theta` denotes the number of model parameters. For the :math:`i^{th}` specimen, the output response :math:`\mathbf{y}_i` can be viewed as a function of :math:`\theta_i` through the model :math:`\mathbf{h}` and the following measurement equation: + +.. math:: \mathbf{y}_i = \mathbf{h}(\theta_i) + \mathbf{w}_i + :label: measurement_equation + +where :math:`\mathbf{w}_i` denotes the discrepancy between the response predicted by the model parameterized with :math:`\theta_i`, i.e., :math:`\mathbf{h}(\theta_i)`, and the experimental output response :math:`\mathbf{y}_i`; :math:`\mathbf{w}_i` is termed the prediction error. With the measurement equation in :math:numref:`measurement_equation`, the sources of real-world uncertainties such as the measurement noise during data collection and model form error are lumped and accounted for in the prediction error (also called noise) term :math:`\mathbf{w}_i` (i.e., :math:`\mathbf{w}_i` is also a proxy for model form error). In quoFEM, it is assumed that the prediction error is a zero-mean Gaussian white noise, thus, + +.. math:: \mathbf{w}_i \sim N(0, (\sigma_i^w)^2 \times I_{n_{\mathbf{y}_i} \times n_{\mathbf{y}_i}}) + :label: gaussian_white_noise_prediction_error + +where :math:`\sigma_i^2` denotes the variance of the prediction error :math:`\mathbf{w}_i`. + + +With the assumptions made in :math:numref:`measurement_equation` and :math:numref:`gaussian_white_noise_prediction_error`, :math:`\mathbf{y}_i` is Gaussian and centered at the model response :math:`\mathbf{h}(\theta_i)`, with a diagonal covariance matrix equal to :math:`\sigma_i^2 \times \mathbf{I}_{n_{\mathbf{y}_i} \times n_{\mathbf{y}_i}}` i.e., + +.. math:: p(\mathbf{y}_i | \theta_i, \sigma_i^2) = N(h(\theta_i), \sigma_i^2 \times \mathbf{I}_{n_{\mathbf{y}_i} \times n_{\mathbf{y}_i}}) + :label: likelihood_for_one_dataset + +In the UCSD_UQ engine, hierarchical Bayesian modeling is used to account for specimen-to-specimen variability in the parameter estimates. In the hierarchical Bayesian modeling realm, the parameter vectors :math:`\theta_1, \theta_2, \ldots, \theta_{N_s}` are considered as mutually statistically independent and identically distributed (s.i.i.d) random variables following a PDF :math:`p(\theta | \eta)`. This is the PDF of the parent distribution, which represents the aleatory specimen-to-specimen variability. + +The objective of hierarchical Bayesian inference is to jointly estimate the model parameters :math:`\theta_i` for each specimen i (along with its prediction error variance :math:`\sigma_i^2`) as well as the hyperparameters :math:`\eta` of the parent distribution of the set :math:`\theta_i (i = 1, \ldots, N_s)`. + + +Making use of the experimental results for a single specimen, :math:`\mathbf{y}_i`, Bayes’ theorem for all parameters to be inferred from this specimen can be written as + +.. math:: + p(\theta_i, \sigma_i^2, \eta | \mathbf{y}_i) \propto p(\mathbf{y}_i | \theta_i, \sigma_i^2, \eta) p(\theta_i, \sigma_i^2, \eta) + :label: bayes_rule_for_one_coupon + +The specimen response :math:`\mathbf{y}_i` depends solely on the model parameters :math:`\theta_i` and the prediction error variance for that specimen, :math:`\sigma_i^2`, and is independent of the hyperparameters :math:`\eta`. Consequently, the conditional PDF :math:`p(\mathbf{y}_i | \theta_i, \sigma_i^2, \eta)` reduces to :math:`p(\mathbf{y}_i | \theta_i, \sigma_i^2)`. + +Assuming :math:`\sigma_i^2` to be statistically independent of :math:`\theta_i` and :math:`\eta` in the joint prior PDF of :math:`\theta_i`, :math:`\sigma_i^2`, and :math:`\eta`, :math:numref:`bayes_rule_for_one_coupon` becomes + +.. math:: + p(\theta_i, \sigma_i^2, \eta | \mathbf{y}_i) \propto p(\mathbf{y}_i | \theta_i, \sigma_i^2) p(\sigma_i^2) p(\theta_i | \eta) p(\eta) + :label: bayes_rule_for_one_coupon_after_assumptions + +In the context of hierarchical Bayesian modeling, the entire experimental dataset from multiple specimens of the same kind, :math:`\mathbf{Y} = \{\mathbf{y}_1, \mathbf{y}_2, ..., \mathbf{y}_{N_s}\}`, is considered. The model parameters and the prediction error variances for all specimens are assumed to be mutually statistically independent, while the set of the model parameter estimates are assumed to be samples from a parent distribution. The figure :numref:`figHierarchicalModel` shows the structure of the hierarchical model. + +.. _figHierarchicalModel: + +.. figure:: figures/UQ/ProbabilisticGraphicalModel.png + :align: center + :figclass: align-center + + Structure of the hierarchical model + +Under these assumptions, the equation for Bayesian updating of all unknown quantities in the hierarchical model, including the model parameters :math:`\Theta = \{\theta_1, \theta_2, \ldots, \theta_{N_s}\}`, measurement noise variances :math:`\mathbf{s} = \{\sigma_1^2, \sigma_2^2, \ldots, \sigma_{N_s}^2\}`, and hyperparameters :math:`\eta` is given by + +.. math:: + p(\Theta, \mathbf{s}, \eta | \mathbf{Y}) \propto p(\eta) \prod_{i=1}^{N_s}[p(\mathbf{y}_i | \theta_i, \sigma_i^2) p( \sigma_i^2) p(\theta_i | \eta) ] + :label: bayes_rule_for_hierarchical_model + +The marginal posterior distribution of the hyperparameters, :math:`p(\eta | \mathbf{Y})` , is obtained by marginalizing out :math:`\mathbf{\Theta}` and :math:`\mathbf{s}` from :math:`p(\Theta, \mathbf{s}, \eta | \mathbf{Y})` as + +.. math:: + p(\eta | \mathbf{Y}) = \int_{\Theta, \mathbf{s}} p(\Theta, \mathbf{s}, \eta | \mathbf{Y}) d\Theta d\mathbf{s} + :label: marginal_posterior_of_hyperparameters + +The distribution :math:`p(\eta | \mathbf{Y})` describes the epistemic uncertainty in the value of the hyperparameters :math:`\eta` due to the finite number of specimens :math:`N_s` in the experimental dataset. + +In the hierarchical approach, the probability distribution of the model parameters conditioned on the entire measurement dataset, :math:`p(\theta | \mathbf{Y})`, is given by + +.. math:: + p(\theta | \mathbf{Y}) = \int_\eta p(\theta | \eta) p(\eta | \mathbf{Y}) d\eta + :label: posterior_predictive_distribution_of_theta + + +The conditional distribution :math:`p(\theta | \eta)` models the aleatory specimen-to-specimen variability. Therefore, the probability distribution :math:`p(\theta | \mathbf{Y})`, referred to as the posterior predictive distribution of the model parameters :math:`\theta`, encompasses both the aleatory specimen-to-specimen uncertainty and the epistemic estimation uncertainty (due to the finite number of specimens :math:`N_s` in the experimental dataset and the finite length of the experimental data corresponding to each specimen). It can be utilized for uncertainty quantification and propagation in reliability and risk analyses. + + +.. _lbluqUCSD_hierarchical_normal: + +Special Case: Normal Population Distribution +++++++++++++++++++++++++++++++++++++++++++++ +The hierarchical modeling approach discussed above captures the specimen-to-specimen aleatory variability by modeling the model parameters corresponding to each experiment as a realization from a population distribution. In the UCSD_UQ engine, a multivariate normal distribution :math:`\theta | \eta \sim N (\mu_\theta, \Sigma_\theta)` is adopted (i.e., :math:`\eta = (\mu_\theta, \Sigma_\theta)`) as: + +.. math:: + \theta_i & \stackrel{s.i.i.d}{\sim} N (\mu_\theta, \Sigma_\theta), \quad i = 1, \ldots, N_s \\ + \mu_\theta = \begin{bmatrix} \mu_{\theta_1} \\ \mu_{\theta_2} \\ \vdots \\ \mu_{\theta_{n_\theta}}\end{bmatrix}; \quad \Sigma_\theta &= \begin{bmatrix} \sigma_{\theta_1}^2 & cov(\theta_1, \theta_2) & \cdots & cov(\theta_1, \theta_{n_\theta}) \\ + cov(\theta_2, \theta_1) & \sigma_{\theta_2}^2 & \cdots & cov(\theta_2, \theta_{n_\theta}) \\ \vdots & \vdots & \ddots & \vdots \\ + cov(\theta_{n_\theta}, \theta_1) & cov(\theta_{n_\theta}, \theta_2) & \cdots & \sigma_{n_\theta}^2 \end{bmatrix} + :label: normal_population_distribution + + +In the Bayesian inference process, the hyperparameters characterizing the population probability distribution, the hypermean vector :math:`\mu_\theta` and the hypercovariance matrix :math:`\Sigma_\theta` are jointly estimated with all the :math:`\theta_i` s and :math:`\sigma_i^2` s. + +So, for this special case, :math:numref:`bayes_rule_for_hierarchical_model` becomes + +.. math:: + p(\Theta, \mathbf{s}, \mu_\theta, \Sigma_\theta | \mathbf{Y}) \propto p(\mu_\theta, \Sigma_\theta) \prod_{i=1}^{N_s}[p(\mathbf{y}_i | \theta_i, \sigma_i^2) p(\sigma_i^2) p(\theta_i | \mu_\theta, \Sigma_\theta) ] + :label: bayes_rule_for_hierarchical_model_with_normal_population + +with :math:`\Theta`, :math:`\mathbf{Y}`, and :math:`\mathbf{s}` as defined above. + + +In the UCSD_UQ engine, the sampling algorithm operates in the standard normal space i.e., + +.. math:: + \theta_i & \stackrel{s.i.i.d}{\sim} N (\mu_\theta, \Sigma_\theta), \quad i = 1, \ldots, N_s \\ + \mu_\theta & = \begin{bmatrix} 0 \\ 0 \\ \vdots \\ 0\end{bmatrix}; \quad \Sigma_\theta = \begin{bmatrix} 1 & 0 & \cdots & 0 \\ + 0 & 1 & \cdots & 0 \\ \vdots & \vdots & \ddots & \vdots \\ + 0 & 0 & \cdots & 1 \end{bmatrix} + :label: standard_normal_population_distribution + +and the :ref:`Nataf transform ` is utilized to map the values provided by the sampling algorithm to the physical space of the model parameters before the model is evaluated. + + +.. _lbluqUCSD_hierarchical_sampling_algorithm: + +Sampling the Posterior Probability Distribution of the Parameters of the Hierarchical Model ++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++ +Due to the high dimensionality (:math:`n_\theta \times n_s + n_s + n_\theta + n_\theta \times \frac{(n_\theta+1)}{2}`, corresponding to the dimensions of the :math:`\theta_i` of each dataset, :math:`\sigma_i^2` for each dataset, :math:`\mu_\theta` and :math:`\Sigma_\theta`, respectively) of the posterior joint PDF shown in :math:numref:`bayes_rule_for_hierarchical_model_with_normal_population`, the Metropolis within Gibbs algorithm is used to generate samples from the posterior probability distribution. To do this, conditional posterior distributions are derived for blocks of parameters from the joint posterior distribution :math:numref:`bayes_rule_for_hierarchical_model_with_normal_population` of all the parameters of the hierarchical model. The Gibbs sampler generates values from these conditional posterior distributions iteratively. The conditional posterior distributions are lower dimensional than the joint distribution. The assumptions made next result in a few of the conditional posterior distributions being of a form that can be easily sampled from, thereby making it feasible to draw samples from the high-dimensional joint posterior PDF of the hierarchical model. + +The prior distributions for each :math:`\sigma_i^2` are selected as the inverse gamma (IG) distribution: + +.. math:: + p(\sigma_i^2) = IG(\alpha_0, \beta_0) + :label: conjugate_prior_pdf_for_sigma_i + + +The prior probability distribution for :math:`(\mu_\theta, \Sigma_\theta)` is chosen to be the normal-inverse-Wishart (NIW) distribution: + +.. math:: + p(\mu_\theta, \Sigma_\theta) = N(\mu_\theta | \mu_0, \frac{\Sigma_\theta}{\nu_0}) IW(\Sigma_\theta | \Sigma_0, m_0) + :label: conjugate_prior_pdf_for_hyperparameters + +With these assumptions, the conditional posterior distributions are the following: + +.. math:: + p(\Sigma_\theta &| \mathbf{Y}, \Theta, \mathbf{s}, \mu_\theta) \propto IW(\Sigma_\theta | \Sigma_n, m_n) \\ + p(\mu_\theta &| \mathbf{Y}, \Theta, \mathbf{s}, \Sigma_\theta) \propto N(\mu_\theta | \mu_n, \frac{\Sigma_\theta}{\nu_n}) \\ + p(\sigma_i^2 &| \mathbf{Y}, \Theta, \mu_\theta, \Sigma_\theta) \propto IG(\alpha_{n_i}, \beta_{n_i})\\ + p(\theta_i &| \mathbf{Y}, \mathbf{s}, \mu_\theta, \Sigma_\theta ) \propto p(\mathbf{y}_i | \theta_i, \sigma_i^2) p(\theta_i | \mu_\theta, \Sigma_\theta) + :label: conditional_posterior_distributions + +where: + +.. math:: + \nu_n &= \nu_0 + N_s \\ + \mu_n &= \frac{(\mu_0 * \lambda_0 + N_s * \bar{\theta})}{\nu_n} \\ + \Sigma_n &= \Sigma_0 + S + \frac{\nu_0 * N_s}{\nu_n} \times ((\bar{\theta} - \mu_0)(\bar{\theta} - \mu_0)^T) \\ + m_n &= m_0 + N_s \\ + \alpha_{n_i} &= \alpha_0 + \frac{n_{\mathbf{y}_i}}{2}\\ + \beta_{n_i} &= \beta_0 + \frac{{sse}_i}{2} + +and, + +.. math:: + \bar{\theta} &= \frac{1}{N_s}\sum_{i=1}^{N_s} \theta_i \\ + S &= \sum_{i=1}^{N_s} {(\bar{\theta} - \mu_0)(\bar{\theta} - \mu_0)^T} \\ + {sse}_i &= \sum_{k=1}^{n_{\mathbf{y}_i}}(\mathbf{y}_i^{(k)} - \mathbf{h}(\theta_i)^{(k)})^2 + + +The Metropolis within Gibbs sampler generates values from the posterior joint PDF shown in :math:numref:`bayes_rule_for_hierarchical_model_with_normal_population` using the posterior conditional distributions :math:numref:`conditional_posterior_distributions` through the following steps: + +#. Select appropriate initial values for each of the :math:`\theta_i`. + +#. Based on the :math:`k^{th}` sample value, the :math:`(k+1)^{th}` sample value is obtained using the following steps: + + #. Generate a sample value of :math:`\Sigma_{\theta}^{(k+1)}` from the conditional posterior distribution :math:`IW(\Sigma_n, m_n)` + + #. Generate a sample value of :math:`\mu_\theta^{(k+1)}` from the conditional posterior distribution :math:`N(\mu_n, \frac{\Sigma_\theta}{\nu_n})` + + #. For each dataset, generate independently a sample value of :math:`\sigma_i^{2(k+1)}` from the conditional posterior distribution of each :math:`\sigma_i^2`: :math:`IG(\alpha_n, \beta_n)` + + #. For each dataset, generate a sample value of the model parameters :math:`\theta_i` from the conditional posterior :math:`p(\mathbf{y}_i | \theta_i, \sigma_i^2) p(\theta_i | \mu_\theta, \Sigma_\theta)` with a Metropolis-Hastings step as follows: + + a. Generate a candidate sample :math:`\theta_{i(c)}` from a local random walk proposal density :math:`\theta_{i(c)} \sim N(\theta_i^{(k)}, \Sigma_i^{(k)})` where :math:`\Sigma_i^{(k)}` is the proposal covariance matrix of the random walk. + + b. Calculate the acceptance ratio + + .. math:: + a_c = \frac{p(\mathbf{y}_i | \theta_{i(c)}, \sigma_i^{2(k+1)}) p(\theta_{i(c)} | \mu_\theta^{(k+1)}, \Sigma_{\theta}^{(k+1)})}{p(\mathbf{y}_i | \theta_i^{(k)}, \sigma_i^{2(k+1)}) p(\theta_i^{(k)}| \mu_\theta^{(k+1)}, \Sigma_{\theta}^{(k+1)})} + + c. Generate a random value :math:`u` from a uniform distribution on [0, 1] and set + + .. math:: + \theta_i^{(k+1)} = \quad &\theta_{i(c)} \quad \text{if} \quad u < a_c \\ + &\theta_i^{(k)} \quad \text{otherwise} + :label: Metropolis_Hastings_criteria + + +After an initial burn-in period, the sample values generated by this algorithm converge to the target density. The proposal covariance matrix of the random walk :math:`\Sigma_i^{(k)}` is selected to facilitate proper mixing of the random walks used to generate sample values of the :math:`\theta_i`. Within the adaptation duration, a scaled version of the covariance matrix of the sample values of the last :math:`N_{cov}` samples (defined as the adaptation frequency in the UCSD_UQ engine) is used, to keep the acceptance rate in the range of 0.2 to 0.5. + diff --git a/docs/_sources/common/technical_manual/desktop/damping.rst.txt b/docs/_sources/common/technical_manual/desktop/damping.rst.txt index 2d3a6d6d..2e2f47cc 100644 --- a/docs/_sources/common/technical_manual/desktop/damping.rst.txt +++ b/docs/_sources/common/technical_manual/desktop/damping.rst.txt @@ -10,7 +10,7 @@ The standard equations that are solved in the nonlinear analysis of structures s where :math:`U(t), \dot{U}(t), \ddot{U}(t)` are the vectors of displacements, velocities, and accelerations for the degrees of freedom, :math:`M` and :math:`C` are the mass and damping matrices, respectively, and the vector :math:`Fs(U)` represents the nonlinear relation between resisting forces and deformations, which includes both material and geometric nonlinearities, and :math:`P(t)` the time-varying applied load due to the event of interest. -Energy is dissipated by the structure as it deforms, which is why it to come to rest when the force is removed. The :math:`Fs(U(t))` term captures the **hysteretic** energy dissipated through the nonlinear behavior of the structural members. The :math:`C \dot{U}(t)` term, the **viscous** damping term, attempts to capture energy dissipated through other mechanisms present in the structure, e.g. thermal effects from repeated elastic straining of structural materials, repeated straining of nonstructural elements—partition walls, mechanical equipment, fire proofing, and so on—friction at steel connections, opening and closing of microcracks in concrete, friction between the structure itself and nonstructural elements, and other mechanisms, some of which are even difficult to identify. Damping for such is often quantified in terms of **modal** damping ratios, and are typically of the order of 1% (steel buildings) to 5% (concrete buildings). These the values have been obtained from field testing and system identification, albeit they have mostly been obtained from buildings undergoing low levels of vibration. +Energy is dissipated by the structure as it deforms, which is why it comes to rest when the force is removed. The :math:`Fs(U(t))` term captures the **hysteretic** energy dissipated through the nonlinear behavior of the structural members. The :math:`C \dot{U}(t)` term, the **viscous** damping term, attempts to capture energy dissipated through other mechanisms present in the structure, e.g. thermal effects from repeated elastic straining of structural materials, repeated straining of nonstructural elements—partition walls, mechanical equipment, fireproofing, and so on—friction at steel connections, opening and closing of microcracks in concrete, friction between the structure itself and nonstructural elements, and other mechanisms, some of which are even difficult to identify. Damping for such is often quantified in terms of **modal** damping ratios, and are typically of the order of 1% (steel buildings) to 5% (concrete buildings). These values have been obtained from field testing and system identification, albeit they have mostly been obtained from buildings undergoing low levels of vibration. It is the formulation of the :math:`C` matrix that is of interest here. There are two damping options presented to the user as inputs to the :ref:`FEM ` panel: 1) Rayleigh Damping Options and 2) Modal Damping options. This is a brief overview of the theory behind both. diff --git a/docs/_sources/common/technical_manual/desktop/spatial_correlation.rst.txt b/docs/_sources/common/technical_manual/desktop/spatial_correlation.rst.txt index df3c8a01..dc833555 100644 --- a/docs/_sources/common/technical_manual/desktop/spatial_correlation.rst.txt +++ b/docs/_sources/common/technical_manual/desktop/spatial_correlation.rst.txt @@ -1,3 +1,4 @@ + .. _lblCorrelation: Ground Motion Intensity Spatial Correlation Model Options @@ -16,6 +17,9 @@ where :math:`Y_{ij}` is the intensity measure (e.g., :math:`Sa(T)`), :math:`\bar 1. **Intra-event residual** quantifies the deviation of intensities at different sites given a specific earthquake realization. 2. **Inter-event residual** quantifies the deviation of intensities at a specific site given different earthquake realizations. +Intra-event Correlation Model Options +------------------------------------- + [Jayaram08]_ found that the spatially distributed intra-event residuals :math:`\epsilon_j = (\epsilon_{1j}, \epsilon_{2j}, ..., \epsilon_{dj})` follows a multivariate normal distribution. This multivariate normal distribution can be defined by the mean, variance, and correlation (between :math:`\epsilon_{i_1j}` and :math:`\epsilon_{i_2j}`). The mean is zero (as discussed previously) and the variance can be predicted by ground motion models, but the correlation between residuals at two different sites needs to be described. The semivariogram :math:`\gamma(u,u^\prime)` is used to describe the expected squared difference between two locations :math:`u` and :math:`u^\prime`. Because it is very difficult to obtain several observations of a random variable at a given pair of sites, the stationarity assumption is usually applied to simplify it to a more trackable problem. It is typically assumed that the semivariogram only depends on the distance :math:`h` - the stationary semivariogram :math:`\gamma(h)` can be obtained from data as follows: .. math:: @@ -43,7 +47,7 @@ Similarly, the correlation coefficient is defined as: Given the semivariogram is often preferred in geostatistical practice (because it does not require a prior estimation of the mean), many studies were carried to find the semivariogram models to derive the correlation :math:`rho(h)` of ground motion intensities. The available models in the current |short tool name| are briefly summarized in following sections. Jayaram and Baker (2009) ------------------------- +^^^^^^^^^^^^^^^^^^^^^^^^ [Jayaram09]_ adopted a exponential model for the semivariogram function with a isotropic hypothesis (i.e., the distance :math:`h` is the separation length): @@ -78,7 +82,7 @@ where T is the period. If the :math:`V_{S30}` values are very close in the given Earthquakes that were considered in the development: Anza earthquake, Alum Rock earthquake, Parkfield earthquake, Chi-Chi earthquake, Northridge earthquake, Big Bear City earthquake, and Chino Hills earthquake. Loth and Baker (2013) ----------------------- +^^^^^^^^^^^^^^^^^^^^^ Note that the cross-semivariograms between different pairs of intensity measures can be different, for instance, :math:`\rho_{Sa(T=0.1s),Sa(T=0.2s)}(h)` might be greater than :math:`\rho_{Sa(T=0.1s),Sa(T=1s)}(h)`. This means one needs to repeat a calibration process many times to develop semivariogram functions and correlation models that have higher resolutions (i.e., direct semivariogram fit). Instead of fitting each semivariogram independently, [Loth13]_ proposed a predictive model for spatial covariance of spectral accelerations at different periods: @@ -168,7 +172,7 @@ where :math:`I_{h=0}` is the indicator function equal to 1 at :math:`h = 0` and Markhvida et al. (2017) ------------------------ +^^^^^^^^^^^^^^^^^^^^^^^ [Markhvida17]_ proposed to use Principal Component Analysis (PCA) to develop the predictive model for cross-correlograms. In theorem, PCA performs a linear transformation of the variables of interests to an orthogonal basis, where the resulting projections onto the new basis are uncorrelated: @@ -258,3 +262,29 @@ The general idea is to include more degrees of freedom in the predictive model i .. [Markhvida17] Markhvida, M., Ceferino, L., & Baker, J. W. (2018). Modeling spatially correlated spectral accelerations at multiple periods using principal component analysis and geostatistics. Earthquake Engineering & Structural Dynamics, 47(5), 1107-1123. + +Inter-event Correlation Model Options +------------------------------------- +[Baker08]_ presented equations to predict the inter-event residual correlations of spectral acceleration values, +using the Next Generation Attenuation (NGA) ground motion library and the new NGA +ground motion models (GMMs). A predictive equation was presented that provides +correlations between logarithmic spectral accelerations at two periods. This equation was observed to be valid for +a variety of definitions of spectral acceleration (i.e., spectral acceleration of +an individual component, the geometric mean of spectral accelerations from two orthogonal +components, and the orientation-independent GMRotI definition used by the NGA modelers) + +The correlation equations are applicable for use with any of the NGA ground motion +models at periods between 0.01 and 10 seconds. When the periods of interest are less +than 5 seconds, correlation coefficients from all considered models are essentially identical. If one period is greater than 5 seconds and the second period is significantly less +than 5 seconds, correlations vary slightly among models. These variations are likely due +to a lack of empirical data, and these widely-spaced period pairs are also of less engineering interest, so separate correlation equations were not developed for each model. +The similarity of correlations from the various GMMs occurs because the correlations +are dominated by the large record-to-record variability in observed spectral values from +similar events. While slight differences in mean predicted values from the GMMs may +be important for some applications, they do not affect computed values to a large +enough extent that correlations change noticeably. The predictive equations (Eq. 5 and Eq. 6 in [Baker08]_) +are implemented in R2D. + +.. [Baker08] + + Baker, J. W., & Jayaram, N. (2008). Correlation of spectral acceleration values from NGA ground motion models. Earthquake Spectra, 24(1), 299-317. \ No newline at end of file diff --git a/docs/_sources/common/technical_manual/desktop/technical_manual.rst.txt b/docs/_sources/common/technical_manual/desktop/technical_manual.rst.txt index 7adc4b1d..38699610 100644 --- a/docs/_sources/common/technical_manual/desktop/technical_manual.rst.txt +++ b/docs/_sources/common/technical_manual/desktop/technical_manual.rst.txt @@ -17,10 +17,13 @@ Technical Manual :WEUQ:WEUQ/scalingWindTunnelData :WEUQ:WEUQ/TinF :WEUQ:WEUQ/dataInformedStochasticWind - -.. :WEUQ:WEUQ/computationalWindLoadEvaluation :EEUQ:spatial_correlation :PBE:spatial_correlation + :R2D:HazardSimulationTool_useCase :R2D:spatial_correlation :R2D:hazard_occurrence + +.. :WEUQ:WEUQ/computationalWindLoadEvaluation + + diff --git a/docs/_sources/common/testbeds/atlantic_city/example_outputs.rst.txt b/docs/_sources/common/testbeds/atlantic_city/example_outputs.rst.txt index c3db84f1..05ddce73 100644 --- a/docs/_sources/common/testbeds/atlantic_city/example_outputs.rst.txt +++ b/docs/_sources/common/testbeds/atlantic_city/example_outputs.rst.txt @@ -105,11 +105,11 @@ the app would direct you to the **RES** panel (:numref:`r2d_res`) where you coul R2D RES panel. For simulating the damage and loss for a large region of interest (please remember to reset the building IDs in **ASD**), it would be efficient to submit and run the job -to `DesignSafe `_ on `Stampede2 `_. +to `DesignSafe `_ on `Frontera `_. This can be done in R2D by clicking **RUN at DesignSafe** (one would need to have a valid `DesignSafe account `_ for login and access the computing resource). :numref:`r2d_run_ds` provides an example configuration to run the analysis (and please see `R2D User Guide `_ for detailed descriptions). -The individual building simulations are paralleled when being conducted on Stampede2 which accelerate the process. It is suggested for the entire building +The individual building simulations are paralleled when being conducted on Frontera which accelerate the process. It is suggested for the entire building inventory in this testbed to use 20 minutes with 96 Skylake (SKX) cores (e.g., 2 nodes with 48 processors per node) to complete the simulation. One would receive a job failure message if the specified CPU hours are not sufficient to complete the run. Note that the product of node number, processor number per node, and buildings per task should be greater than the diff --git a/docs/_sources/common/testbeds/atlantic_city/index.rst.txt b/docs/_sources/common/testbeds/atlantic_city/index.rst.txt index dc225d5f..1209d96e 100644 --- a/docs/_sources/common/testbeds/atlantic_city/index.rst.txt +++ b/docs/_sources/common/testbeds/atlantic_city/index.rst.txt @@ -70,7 +70,7 @@ and the versions of all applications and rulesets of the current version of the The software descriptions and results herein were generated by executing the R2D application using the versions of this application and associated SimCenter software as listed in :numref:`software_version_AC` and :numref:`brails_version_AC`. With the software versions listed, the testbed is currently estimated -to execute in 40 minutes using five Skylake (SKX) nodes (240 cores) on `Stampede2 `_. +to execute in 40 minutes using five Skylake (SKX) nodes (240 cores) on `Frontera `_. .. list-table:: Software and Supporting Files :name: software_version_AC diff --git a/docs/_sources/common/testbeds/lake_charles/example_outputs.rst.txt b/docs/_sources/common/testbeds/lake_charles/example_outputs.rst.txt index 66b64f28..f0f3ccfa 100644 --- a/docs/_sources/common/testbeds/lake_charles/example_outputs.rst.txt +++ b/docs/_sources/common/testbeds/lake_charles/example_outputs.rst.txt @@ -109,11 +109,11 @@ the app would direct you to the **RES** panel (:numref:`r2d_res`) where you coul R2D RES panel. For simulating the damage and loss for a large region of interest (please remember to reset the building IDs in **ASD**), it would be efficient to submit and run the job -to `DesignSafe `_ on `Stampede2 `_. +to `DesignSafe `_ on `Frontera `_. This can be done in R2D by clicking **RUN at DesignSafe** (one would need to have a valid `DesignSafe account `_ for login and access the computing resource). :numref:`r2d_run_ds` provides an example configuration to run the analysis (and please see `R2D User Guide `_ for detailed descriptions). -The individual building simulations are paralleled when being conducted on Stampede2 which accelerate the process. It is suggested for the entire building +The individual building simulations are paralleled when being conducted on Frontera which accelerate the process. It is suggested for the entire building inventory in this testbed to use 15 minutes with 96 Skylake (SKX) cores (e.g., 2 nodes with 48 processors per node) to complete the simulation. One would receive a job failure message if the specified CPU hours are not sufficient to complete the run. Note that the product of node number, processor number per node, and buildings per task should be greater than the diff --git a/docs/_sources/common/testbeds/lake_charles/index.rst.txt b/docs/_sources/common/testbeds/lake_charles/index.rst.txt index 67bbac02..9a003e19 100644 --- a/docs/_sources/common/testbeds/lake_charles/index.rst.txt +++ b/docs/_sources/common/testbeds/lake_charles/index.rst.txt @@ -68,7 +68,7 @@ Note when accessing the project in DesignSafe, please check that the version dro The software descriptions and results herein were generated by executing the R2D application using the versions of this application and associated SimCenter software as listed in :numref:`software_version_LC` and :numref:`brails_version_LC`. With the software versions listed, the testbed is currently estimated -to execute in 15 minutes using five Skylake (SKX) nodes (96 cores) on `Stampede2 `_. +to execute in 15 minutes using five Skylake (SKX) nodes (96 cores) on `Frontera `_. .. list-table:: Software and Supporting Files :name: software_version_LC diff --git a/docs/_sources/common/user_manual/about/EEUQ/about.rst.txt b/docs/_sources/common/user_manual/about/EEUQ/about.rst.txt index 4eace21c..2c50cc46 100644 --- a/docs/_sources/common/user_manual/about/EEUQ/about.rst.txt +++ b/docs/_sources/common/user_manual/about/EEUQ/about.rst.txt @@ -7,17 +7,17 @@ About This open-source research application, which is available at |tool github link|, is released under a **3-Clause BSD** license (see :ref:`lblLicense`). The |app| can be used to predict the response of a building subjected to earthquake events. The application is focused on quantifying the uncertainties in the predicted response, -given the that the properties of the buildings and the earthquake -events are not known exactly, and that both the simulation software -and the user make simplifying assumptions in the numerical modeling of +given that the properties of the buildings and the earthquake +events are not known exactly, and both the simulation software +and the user makes simplifying assumptions in the numerical modeling of that structure. In this application, the user is required to characterize the uncertainties in the input. The application will, -after utilizing the users selected sampling method, provide +after utilizing the user-selected sampling method, provide information that characterizes the uncertainties in the computed response measures. As the computations to make these determinations can be prohibitively expensive to perform on a user's local computer, the user has the option to perform the computations remotely on the -Stampede2 supercomputer. Stampede2 is located at the Texas Advanced +Frontera supercomputer. Frontera is located at the Texas Advanced Computing Center (TACC) and made available to the user through NHERI DesignSafe, the cyberinfrastructure provider for the distributed NSF funded Natural Hazards in Engineering Research Infrastructure (NHERI) @@ -26,15 +26,15 @@ facility. Whether running locally or remotely, the computations are performed, as will be discussed in :ref:`lbl-technical-manual`, in a workflow -application. That is, the numerical simulations are actually performed -by a number of different applications. The |app| backend software runs +application. That is, the numerical simulations are performed +by several different applications. The |app| backend software runs these different applications for the user, taking the outputs from some programs and providing them as inputs to others. The design of -the |app| is such that researchers are able to modify the -backend application to utilize their own application in the workflow +the |app| is such that researchers can modify the +backend application to utilize their application in the workflow computations. This will ensure researchers are not limited to using the default applications we provide and will be enthused to provide -their own applications for others to use. +their applications for others to use. This document covers Version |tool version| of the tool. Users are encouraged to comment on what additional features and capabilities they would like to see in this application. These requests and feedback can be submitted through the |messageBoard| we greatly appreciate any input you have. If there are features you want, chances are many of your colleagues also would benefit from them. Users are encouraged to review |app requirements| to see what features are planned for this application. diff --git a/docs/_sources/common/user_manual/examples/desktop/examples.rst.txt b/docs/_sources/common/user_manual/examples/desktop/examples.rst.txt index dce72bbd..5790abc6 100644 --- a/docs/_sources/common/user_manual/examples/desktop/examples.rst.txt +++ b/docs/_sources/common/user_manual/examples/desktop/examples.rst.txt @@ -30,13 +30,13 @@ Examples .. only:: PBE_app - The following are a few examples showing the usage of PBE. The files for the examples are available on Github. The scope of these examples is limited to damage and loss assessment. The usage of the tool for response estimation is identical to that of the EE-UQ application. Examples on those features are available in the `EE-UQ Documentation `_. + The following are a few examples showing the usage of PBE. The files for the examples are available on Github. The scope of these examples is limited to damage and loss assessment. The usage of the tool for response estimation is identical to that of the EE-UQ application. Examples of those features are available in the `EE-UQ Documentation `_. All examples come with input files that are available in the `PBE Github repository `_. .. only:: PBE1_app - The following examples demonstrate the usage of the PBE application. The scope of these examples is limited to damage and loss assessment. The usage of the tool for response estimation is identical to that of the EE-UQ application. Examples on those features are available in the `EE-UQ Documentation `_. + The following examples demonstrate the usage of the PBE application. The scope of these examples is limited to damage and loss assessment. The usage of the tool for response estimation is identical to that of the EE-UQ application. Examples of those features are available in the `EE-UQ Documentation `_. All examples come with input files that are available in the `PBE Github repository `_. diff --git a/docs/_sources/common/user_manual/installation/desktop/downloadOther.rst.txt b/docs/_sources/common/user_manual/installation/desktop/downloadOther.rst.txt index c741b825..57a57b89 100644 --- a/docs/_sources/common/user_manual/installation/desktop/downloadOther.rst.txt +++ b/docs/_sources/common/user_manual/installation/desktop/downloadOther.rst.txt @@ -3,7 +3,7 @@ Install Additional Applications =============================== -Additional software is needed by the |app|. This software, which as is discussed in :ref:`lblArchitecture`, is used by the application to perform the computations in the backend workflow. The software required is dependent on your operating system. +Additional software is needed by the |app|. This software, which is discussed in :ref:`lblArchitecture`, is used by the application to perform the computations in the backend workflow. The software required is dependent on your operating system. .. toctree-filt:: :maxdepth: 1 diff --git a/docs/_sources/common/user_manual/installation/desktop/downloadOtherMAC.rst.txt b/docs/_sources/common/user_manual/installation/desktop/downloadOtherMAC.rst.txt index ff53ee70..f3d41285 100644 --- a/docs/_sources/common/user_manual/installation/desktop/downloadOtherMAC.rst.txt +++ b/docs/_sources/common/user_manual/installation/desktop/downloadOtherMAC.rst.txt @@ -10,7 +10,7 @@ The following set of instructions assumes all files will be placed in the **bin* .. note:: - Placement of terminal applications in your home **bin** folder is common practice for the terminal applications on a **MacOS** system. It is legacy practice from the operating systems Linux heritage. + Placement of terminal applications in your home **bin** folder is common practice for the terminal applications on a **MacOS** system. It is a legacy practice from the operating system's Linux heritage. Python ^^^^^^ @@ -20,8 +20,8 @@ dated version 2.7. We recommend installing Python 3.7 from `Python.org `_ and in that window type the following instructions: @@ -53,21 +53,21 @@ Once Python is installed, you need to extend it by installing the following pack Dakota ^^^^^^ -|DakotaLink| is the default UQ engine used by the |app| that is publicly available from the |DakotaDownload| page. The download page offers an extensive list of downloadable files. You can narrow this down to the file to be selected by selecting **Windows** in the `Platform`, **6.10** (**6.10** was latest at time of writing, select newer of course if available) in the `Release`, and **Command Line Only** for the `interface type`. In the `Public` area you should now only have a single option, click on the link to download |Dakota|. When you extract the files that you download, they will all be contained in a single folder, we suggest renaming it **dakota-6.10.0** (the last **.0** was the number in the download, sometimes developers issue minor updates and identify them through the last number). When you have renamed the folder move that folder to the **C:\\SimCenter\\dakota\\** folder. +|DakotaLink| is the default UQ engine used by the |app| that is publicly available from the |DakotaDownload| page. The download page offers an extensive list of downloadable files. You can narrow this down to the file to be selected by selecting **Windows** in the `Platform`, **6.10** (**6.10** was the latest at the time of writing, select newer of course if available) in the `Release`, and **Command Line Only** for the `interface type`. In the `Public` area you should now only have a single option, click on the link to download |Dakota|. When you extract the files that you download, they will all be contained in a single folder, we suggest renaming it **dakota-6.10.0** (the last **.0** was the number in the download, sometimes developers issue minor updates and identify them through the last number). When you have renamed the folder move that folder to the **C:\\SimCenter\\dakota\\** folder. .. note:: - We place **dakota-6.10.0** inside **dakota** folder to be able to have multiple versions installed. This is a useful practice, as software developers make tweaks that can effect the results of past simulations. It is useful to be able to compare different versions of an application to ensure results stay the same. + We place **dakota-6.10.0** inside **dakota** folder to be able to have multiple versions installed. This is a useful practice, as software developers make tweaks that can affect the results of past simulations. It is useful to be able to compare different versions of an application to ensure results stay the same. OpenSees ^^^^^^^^ -|OpenSeesLink| is the default FEM engine used by the |app| that is publicly available from the |OpenSeesDownload| page. To download the **OpenSees** you have to enter your email address, which may also require you to register (that requirement is going away and may be gone by time you read this). At the bottom of the page, under section **Windows Version** is the download link for the current executable, currently **3.2.2** Follow the link to download the application. It is in the form of a **.zip** file. The zip file contains a folder and in the bin directory is the **OpenSees.exe** application. The other files and folders are needed by the application and must be kept. Rename the folder to **OpenSees-3.2.2** and move the folder to the **C:\\SimCenter\\OpenSees** folder. +|OpenSeesLink| is the default FEM engine used by the |app| that is publicly available from the |OpenSeesDownload| page. To download the **OpenSees** you have to enter your email address, which may also require you to register (that requirement is going away and may be gone by the time you read this). At the bottom of the page, under section **Windows Version** is the download link for the current executable, currently **3.2.2** Follow the link to download the application. It is in the form of a **.zip** file. The zip file contains a folder and in the bin directory is the **OpenSees.exe** application. The other files and folders are needed by the application and must be kept. Rename the folder to **OpenSees-3.2.2** and move the folder to the **C:\\SimCenter\\OpenSees** folder. Modify the Environment Variables ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ -You now need to make some changes to your environment variables as neither OpenSees or Dakota includes an installer which typically performs this task. +You now need to make some changes to your environment variables as neither OpenSees or Dakota includes an installer that typically performs this task. 1. Open the Start Search, type in “env”, and choose “Edit the system environment variables” 2. Click the **Environment Variables…** button at the bottom right of the application that pop up. @@ -88,7 +88,7 @@ You now need to make some changes to your environment variables as neither OpenS C:\\SimCenter\\dakota\\share\\dakota\\Python 9. Press the **OK** button. -10. Press now the **Apply** button and exit the SystemProperties application +10. Now press the **Apply** button and exit the SystemProperties application Test the Install of Python, OpenSees & Dakota @@ -97,7 +97,7 @@ Test the Install of Python, OpenSees & Dakota Steps to Test: 1. Open a command window window(type `cmd` in search) 2. Type `python3` in the application that starts (this should bring up python interpreter) - 3. Enter the following to test the install of the modules and quit the application: + 3. Enter the following to test the installation of the modules and quit the application: .. code-block:: python diff --git a/docs/_sources/common/user_manual/installation/desktop/install_Windows.rst.txt b/docs/_sources/common/user_manual/installation/desktop/install_Windows.rst.txt index 8b88785a..354fd1e4 100644 --- a/docs/_sources/common/user_manual/installation/desktop/install_Windows.rst.txt +++ b/docs/_sources/common/user_manual/installation/desktop/install_Windows.rst.txt @@ -11,8 +11,8 @@ Install on Windows 10 .. note:: Java is needed to use OpenSHA to characterize the regional seismic hazard (see :ref:`ground_motion_tool`). If you do not plan to use that feature, you can skip this step of the installation. - If you have not yet installed Java, please download the latest installer from `java.com `_ , run it, and follow the on-screen instructions to install Java. - + If you have not yet installed Java, please download the installer from Java website. The version `16.0.2 `_ has been tested to be working with the latest |app|. Follow the on-screen instructions to install Java. If you run into a JVM error that suggests setting JAVA_HOME environment variable, you can do so per this `link `_ + .. note:: The Java website should automatically detect your operating system and offer the corresponding installer for you to download. Make sure you see "64-bit Java for Windows" at the top of the page before downloading the installer. @@ -34,15 +34,15 @@ Install on Windows 10 #. Open WSL from the start menu and run the following commands on the opened terminal window. -.. code:: bash + .. code:: bash - sudo sh -c "wget -O - http://dl.openfoam.org/gpg.key | apt-key add -" - sudo add-apt-repository http://dl.openfoam.org/ubuntu - sudo apt-get update - sudo apt-get install openfoam10 + sudo sh -c "wget -O - http://dl.openfoam.org/gpg.key | apt-key add -" + sudo add-apt-repository http://dl.openfoam.org/ubuntu + sudo apt-get update + sudo apt-get install openfoam10 -Further instructions can be found in `OpenFOAM.org `_. + Further instructions can be found in `OpenFOAM.org `_. Download the Application @@ -117,7 +117,7 @@ To download the |app|, navigate to the |appLink| page which should resemble |fig Click on the file with a name ending with **Windows_Download.zip** to download the |app|. In the pop-up window, click on the **Download** button in the bottom right corner. -After the download is completed, extract the zip archive to a location in your filesystem. We suggest extracting to the **C:/SimCenter/** folder. You can create a shortcut that points to the |short tool id|.exe executable of the application and move this shortcut to your Desktop for easy access. +After the download is completed, extract the zip archive to a location in your filesystem. We suggest extracting it to the **C:/SimCenter/** folder. You can create a shortcut that points to the |short tool id|.exe executable of the application and move this shortcut to your Desktop for easy access. .. tip:: Using an external compressor program, such as `7-Zip `_, can significantly reduce the zip archive extraction time compared to the Windows default extraction function. diff --git a/docs/_sources/common/user_manual/installation/desktop/install_macOS.rst.txt b/docs/_sources/common/user_manual/installation/desktop/install_macOS.rst.txt index a10d543a..d3621f82 100644 --- a/docs/_sources/common/user_manual/installation/desktop/install_macOS.rst.txt +++ b/docs/_sources/common/user_manual/installation/desktop/install_macOS.rst.txt @@ -8,7 +8,7 @@ Install Python 3.9 SimCenter tools require an x86-based version of Python 3.9 to run properly. If you have a different version of Python installed, you will need to add a Python 3.9 x86 version to your system. Below, we will demonstrate the process for installing Python 3.9 using the official distributor of Python, **python.org**. -To see if you have python installed and whether it is compatable with SimCenter tools, issue the following in a terminal window. +To see if you have python installed and whether it is compatible with SimCenter tools, issue the following in a terminal window. .. code:: @@ -17,7 +17,7 @@ To see if you have python installed and whether it is compatable with SimCenter platform.uname() exit() -As shown in screenshot below, you should see a Python 3.9 version after issuing the python3 command and the machine='x86_64' in the last line of output from the platform.uname() command. If you see another Python version or machine='arm64', you will need to install an x86 Python 3.9 on your computer. +As shown in the screenshot below, you should see a Python 3.9 version after issuing the python3 command and the machine='x86_64' in the last line of output from the platform.uname() command. If you see another Python version or machine='arm64', you will need to install an x86 Python 3.9 on your computer. .. figure:: figures/pythonKernel.png :align: center @@ -35,7 +35,7 @@ As shown in screenshot below, you should see a Python 3.9 version after issuing Python: python.org MacOS Download Page -**2.** After running yhe Python.org installer, a pop up directory window will appear containing a number of files, as shown in the figure below. Two of these files, ``Update Shell Profile.command.sh`` and ``Install CertificateCommand.sh`` are script files. You need to execute both script files to get Python set up correctly so that it can be invoked from the terminal application. To execute the files, double click on the files individually with your mouse. +**2.** After running the Python.org installer, a pop-up directory window will appear containing several files, as shown in the figure below. Two of these files, ``Update Shell Profile.command.sh`` and ``Install CertificateCommand.sh`` are script files. You need to execute both script files to get Python set up correctly so that it can be invoked from the terminal application. To execute the files, double-click on the files individually with your mouse. .. figure:: figures/pythonInstallShell.png :align: center @@ -60,9 +60,9 @@ Make sure you see a message that confirms the successful installation of the nhe 1. If you forget to invoke the ``UpdateShellProfile.command.sh`` script at the end of the install, you can always execute the correct shell file later to update the ``PATH`` variable to point to the Python application. - On Linux systems, the shell is the program that takes commands from the keyboard that you enter in the terminal window and passes them to the operating system to perform by invoking applications and passing data between applications. In the good old days, it was the only interface available to the user, i.e., there was no such thing as Finder! There are a number of shell programs that can be installed and made available to you. The most popular is the **bash** shell, the up and coming one is the **Z** shell. Power MacOS users will write shell scripts to do many many useful things. By default the applications that the shell program will invoke are limited to applications in a few specific directories that are defined in the users ``PATH``. Users can modify this path by editing files that the shell program will read from everytime the program is started. + On Linux systems, the shell is the program that takes commands from the keyboard that you enter in the terminal window and passes them to the operating system to perform by invoking applications and passing data between applications. In the good old days, it was the only interface available to the user, i.e., there was no such thing as Finder! There are a number of shell programs that can be installed and made available to you. The most popular is the **bash** shell, and the up-and-coming one is the **Z** shell. Power MacOS users will write shell scripts to do many many useful things. By default, the applications that the shell program will invoke are limited to applications in a few specific directories that are defined in the user's ``PATH``. Users can modify this path by editing files that the shell program will read from every time the program is started. - When the frontend application is running the computations it is actually running a backend application using the shell program. As a consequence the shell program must be made aware of the locations of some of the external applications that you have installed as **OpenSees** and **Dakota** do not provide installers that automatically do this when they are installed. Other applications, like **Tcl** provide scripts that you invoke to do it. In short you have to edit the file appropriate to the shell you are using. + When the frontend application is running the computations it is actually running a backend application using the shell program. As a consequence the shell program must be made aware of the locations of some of the external applications that you have installed as **OpenSees** and **Dakota** do not provide installers that automatically do this when they are installed. Other applications, like **Tcl** provide scripts that you invoke to do it. In short, you have to edit the file appropriate to the shell you are using. To find which shell program you are using when you issue commands inside the terminal window, type the following: @@ -72,7 +72,7 @@ Make sure you see a message that confirms the successful installation of the nhe If the result is ``/bin/bash`` you will need to edit the ``.bashrc`` file or the ``bash_profile`` file. If the result is ``/bin/zsh`` you will need to edit the ``.zshrc`` or ``.zprofile``. Typically, the ``.bash_profile`` or the ``.zprofile`` file is the one to edit as by design these will invoke the ``.bashrc`` or ``.zshrc`` file. If in doubt, look for these files in your home directory and see which of these other installers have modified. - 2. Python 3.10 from python.org will also work, though there is no x86 installer. The reason we do not recommend it's usage is that there is additional settings that need to be modified in the application under the Preferences tab as that python package has a different mechanism for invoking the x86 version, specifically **python3-intel64**. + 2. Python 3.10 from python.org will also work, though there is no x86 installer. The reason we do not recommend its usage is that there are additional settings that need to be modified in the application under the Preferences tab as that python package has a different mechanism for invoking the x86 version, specifically **python3-intel64**. .. only:: R2D_app @@ -173,7 +173,7 @@ To download the |app|, navigate to the |appLink| page which should resemble |fig HydroUQ tool download page. -Click on the file with a name ending with **Mac_Download.dmg** to download the |app|. In the pop-up window, click on the **Download** button in the bottom right corner. After the download has completed, open the dmg file and copy the |short tool name| application to a location in your filesystem. +Click on the file with a name ending with **Mac_Download.dmg** to download the |app|. In the pop-up window, click on the **Download** button in the bottom right corner. After the download is completed, open the dmg file and copy the |short tool name| application to a location in your filesystem. .. note:: @@ -186,16 +186,16 @@ Once the installation procedure has been completed, it is a good practice to run .. note:: - SimCenter apps are code-signed and notarized, but because they are not downloaded from the operating system's app store, they may not be recognized as safe applications. Depending on your security settings, when you start a SimCenter app for the first time, your operating system may show a dialog box indicating it is unsafe. If this dialog appears, choose the cancel button. Try to start the app again, this time by right clicking on it and selecting open. + SimCenter apps are code-signed and notarized, but because they are not downloaded from the operating system's app store, they may not be recognized as safe applications. Depending on your security settings, when you start a SimCenter app for the first time, your operating system may show a dialog box indicating it is unsafe. If this dialog appears, choose the cancel button. Try to start the app again, this time by right-clicking on it and selecting open. - If the app still fails to open. You need to go to System Settings->Privacy and Security. Under the Security section you need to at least temprarily select the option to allow applications downloaded from the **App Store and Identified Developers**. With this schecked try again. If it fails again, go back to System Settings->Privacy and Security. Just below the section you just checked, there should be some text about why the app was stopped and an option to **Open Anayway" , as shown in figure below. Click on the button and the app should start. + If the app still fails to open. You need to go to System Settings->Privacy and Security. Under the Security section you need to at least temporarily select the option to allow applications downloaded from the **App Store and Identified Developers**. With this checked try again. If it fails again, go back to System Settings->Privacy and Security. Just below the section you just checked, there should be some text about why the app was stopped and an option to **Open Anayway" , as shown in figure below. Click on the button and the app should start. .. figure:: figures/AppleSecurity.png :align: center :figclass: align-center -Once the application started, you should see the user interface shown in |figUI|. We recommend running the example problem |test example| to test the application. +Once the application starts, you should see the user interface shown in |figUI|. We recommend running the example problem |test example| to test the application. .. only:: R2D_app @@ -262,9 +262,12 @@ Once the application started, you should see the user interface shown in |figUI| When the |app| is running, open the app/preferences or File/Preferences and make sure that python3 appears under **External Applications:Python**, as shown in the figure below. If you used older versions of SimCenter tools this was not the default. The exact location of python3 that you installed can be found by opening the terminal application and executing the **which python3** command. Enter the path shown as a response to the Preferences panel under Python and then press the **Save** button. - .. figure:: figures/pythonPreferences.png + .. _figUI-preferences: + + .. figure:: figures/pythonPreferences.png :align: center :figclass: align-center - Set Python Preferences. + Set Python Preferences. + diff --git a/docs/_sources/common/user_manual/releases/eePlans.rst.txt b/docs/_sources/common/user_manual/releases/eePlans.rst.txt index 5717cd5b..040fe747 100644 --- a/docs/_sources/common/user_manual/releases/eePlans.rst.txt +++ b/docs/_sources/common/user_manual/releases/eePlans.rst.txt @@ -8,11 +8,6 @@ Release Plans The following features are planned to be developed for upcoming releases of |app|. We are actively working on the features in the next release. Farther development priorities may change depending on feedback from the community. If you have any suggestions, we encourage you to contribute and contact us through the SimCenter Forum. -December 2023 ---------- - #. Train and export surrogates for regional simulations (1.3.6.1) - Surrogates developed in EE_UQ can be exported, shared, and directly used to represent structural behavior in large regional seismic risk assessments in R2D. - - March 2024 ---------- #. Automatic access to physics-based ground motion simulation results (1.1.1.3) diff --git a/docs/_sources/common/user_manual/releases/quoCapabilities.rst.txt b/docs/_sources/common/user_manual/releases/quoCapabilities.rst.txt index 810d48df..655df607 100644 --- a/docs/_sources/common/user_manual/releases/quoCapabilities.rst.txt +++ b/docs/_sources/common/user_manual/releases/quoCapabilities.rst.txt @@ -5,7 +5,7 @@ Capabilities ************ -Version |tool version| of the |app| was released on **October 2, 2023**. The following lists the functionality available in this current version. (Note: New features and fixes in this release are marked :blue:`blue` in the following list of features.) +Version |tool version| of the |app| was released on **December 29, 2023**. The following lists the functionality available in this current version. (Note: New features and fixes in this release are marked :blue:`blue` in the following list of features.) UQ (Uncertainty Quantification and Optimization Options) @@ -26,7 +26,7 @@ UQ (Uncertainty Quantification and Optimization Options) a. Resample from the existing correlated dataset of samples - #. :blue:`Multi-fidelity Monte Calro` + #. Multi-fidelity Monte Carlo #. Global Sensitivity Analysis @@ -60,13 +60,19 @@ UQ (Uncertainty Quantification and Optimization Options) #. DREAM - B. :ref:`UCSD_UQ` + B. :ref:`TMCMC ` #. Transitional Markov Chain Monte Carlo (TMCMC) for Bayesian estimation a. Override default log-likelihood function b. Override default error covariance structure c. Calibrate multipliers on error covariance structure + + C. :ref:`Hierarchical Models ` + + #. :blue:`Bayesian updating of parameters of a hierarchical model` + + a. Quantify aleatory uncertainty in the parameter values of a computational model #. Deterministic Calibration @@ -96,7 +102,7 @@ UQ (Uncertainty Quantification and Optimization Options) .. note:: - Support for the running computation to be preformed on TACC's high performance computer, Frontera, is provided through DesignSafe for all but the methods indicated with a star (*). + Support for the running computation to be performed on TACC's high-performance computer, Frontera, is provided through DesignSafe for all but the methods indicated with a star (*). FEM (Computational Model Specification) @@ -132,7 +138,7 @@ RV (Random Variable Options) .. note:: - :sup:`1`: For SimCentreUQ and UCSD algorithms only, the RVs can be defined by any of parameters, moments, or a dataset. + :sup:`1`: For SimCenterUQ and UCSD algorithms only, the RVs can be defined through any of these options - parameters, moments, or a dataset. :sup:`2`: Available for Optimization routines in Dakota only. :sup:`3`: Available in SimCenterUQ and UCSD only. @@ -149,11 +155,11 @@ RES (Summary and Visualization of UQ Analysis Results) A. Mean B. Standard deviation - -#. All output values presented in spreadsheet + +#. All output values presented in the spreadsheet A. Update the chart by clicking on spreadsheet columns - + #. Output values visualized in the interactive chart A. Scatter plot diff --git a/docs/_sources/common/user_manual/releases/quoPlans.rst.txt b/docs/_sources/common/user_manual/releases/quoPlans.rst.txt index b4ae1bb7..c62ee57f 100644 --- a/docs/_sources/common/user_manual/releases/quoPlans.rst.txt +++ b/docs/_sources/common/user_manual/releases/quoPlans.rst.txt @@ -9,17 +9,11 @@ Release Plans The following features are planned to be developed for upcoming releases of |app|. We are actively working on the features in the next release. Farther development priorities may change depending on feedback from the community. If you have any suggestions, we encourage you to contribute and contact us through the SimCenter Forum. -October 2023 ---------- - #. Bayesian model selection and averaging (1.2.4.1) - Define weights for each model candidate and propagate epistemic uncertainty by randomly selecting a model for each realization according to these weights. - #. Accelerate Bayesian calibration using advanced Markov Chain Monte Carlo methods (1.2.3.3) - Build a surrogate model iteratively that will replace the original model in MCMC sampling. In each iteration, use a batch of data generated by evaluating the original model at carefully selected points to improve the surrogate model approximation of the target probability density. This is especially helpful when the original model is expensive to run and conventional MCMC is not feasible. +October 2024 +------------ + #. Accelerate Bayesian calibration using advanced Markov Chain Monte Carlo methods (1.2.3.4) - Build a surrogate model iteratively that will replace the original model in MCMC sampling. In each iteration, use a batch of data generated by evaluating the original model at carefully selected points to improve the surrogate model approximation of the target probability density. This is especially helpful when the original model is expensive to run and conventional MCMC is not feasible. #. Additional calibration examples developed with researchers running projects at NHERI experimental facilities (1.2.5.3) - These examples demonstrate real-world application of |app| and they can also serve as templates for future users of NHERI facilities. - -March 2024 ----------- - #. Advanced model calibration methods using recursive stochastic filters and particle filters (1.2.3.4) - .. note:: diff --git a/docs/_sources/common/user_manual/releases/quoReleaseNotes.rst.txt b/docs/_sources/common/user_manual/releases/quoReleaseNotes.rst.txt index 919f39dc..41eef07f 100644 --- a/docs/_sources/common/user_manual/releases/quoReleaseNotes.rst.txt +++ b/docs/_sources/common/user_manual/releases/quoReleaseNotes.rst.txt @@ -14,15 +14,22 @@ Major Version 3 The major version number was increased from 2 to 3 as changes were made to the input and output formats of |app|. This means old examples will not be loaded in this version of the tool. - .. dropdown:: Version 3.4 (:blue:`Current`) + .. dropdown:: Version 3.5 (:blue:`Current`) :open: + **Release date:** December. 2023 + + **Highlights** + #. Bayesian calibration of a **hierarchical model** + + .. dropdown:: Version 3.4 + **Release date:** October. 2023 **Highlights** #. **Multi-fidelity** Monte Carlo Simulation - .. dropdown:: Version 3.3 + .. dropdown:: Version 3.3 **Release date:** March. 2023 @@ -32,7 +39,7 @@ Major Version 3 #. Display of correlation coefficients within the input/output dataset #. Switching the display order of the UQ method and UQ engine - .. dropdown:: Version 3.2 + .. dropdown:: Version 3.2 **Release date:** September. 2022 @@ -51,7 +58,7 @@ Major Version 3 * Inverse problem → **Bayesian calibration** - .. dropdown:: Version 3.1 + .. dropdown:: Version 3.1 **Release date:** June. 2022 @@ -59,7 +66,7 @@ Major Version 3 #. New efficient global sensitivity analysis method for high-dimensional output (GSA-PCA) - #. "Save RVs" and "Save QoIs" buttons added to the results tab spreadsheet + #. "Save RVs" and "Save QoIs" buttons were added to the results tab spreadsheet #. “NaN” handling option added to SimCenterUQ engine @@ -68,7 +75,7 @@ Major Version 3 #. Minor bug fixes in the user interface, surrogate modeling, and sensitivity analysis scripts - .. dropdown:: Version 3.0 + .. dropdown:: Version 3.0 **Release date:** March. 2022 @@ -91,7 +98,7 @@ Major Version 3 Major Version 2 ================= - .. dropdown:: Version 2.4.1 + .. dropdown:: Version 2.4.1 **Release date:** Dec. 2021 @@ -101,7 +108,7 @@ Major Version 2 #. SimCenterUQ RV tab - preventing path strings from being deleted when "choose" is clicked (dataset inputs) - #. SimCenterUQ checks if python packages are missing in the environment and shows an error message if needed + #. SimCenterUQ checks if Python packages are missing in the environment and shows an error message if needed #. Minor fixes in surrogate UI (nugget values option should not show up by default, RVs should be uniform by default) @@ -110,13 +117,13 @@ Major Version 2 #. Parameter values are passed to the log-likelihood script when using the UCSD_UQ engine - .. dropdown:: Version 2.4.0 + .. dropdown:: Version 2.4.0 **Release date:** Oct. 2021 Highlights - #. New forward propagation method in SimCenterUQ to import existing sample sets (eg. samples obtained by MCMC) + #. New forward propagation method in SimCenterUQ to import existing sample sets (e.g. samples obtained by MCMC) #. New multi-fidelity surrogate modeling option in SimCenterUQ @@ -130,7 +137,7 @@ Major Version 2 #. Minor improvements and bug fixes - .. dropdown:: Version 2.3 + .. dropdown:: Version 2.3 **Release date:** May 2021 @@ -145,7 +152,7 @@ Major Version 2 #. Log-likelihood function specification made optional for TMCMC - .. dropdown:: Version 2.2 + .. dropdown:: Version 2.2 **Release date:** Oct. 2020 @@ -161,7 +168,7 @@ Major Version 2 #. Changes to UI to reduce wasted space - .. dropdown:: Version 2.0 + .. dropdown:: Version 2.0 **Release date:** Sept. 2019 diff --git a/docs/_sources/common/user_manual/releases/r2dCapabilities.rst.txt b/docs/_sources/common/user_manual/releases/r2dCapabilities.rst.txt index ca715c88..f531046f 100644 --- a/docs/_sources/common/user_manual/releases/r2dCapabilities.rst.txt +++ b/docs/_sources/common/user_manual/releases/r2dCapabilities.rst.txt @@ -6,18 +6,19 @@ Capabilities ************ -**Version 3.0** of |app| was released **May 2023**. The following lists the functionality available in this current version. (Note: New features and fixes in this release are marked :blue:`blue` in the following list of features.) Note the version introduced major changes in how tool is used. Some of existing **Haz** options were moved to a new **Tool** main menu option. +**Version** |tool version| of |app| was released **Jan 2024**. The following is the functionality available in this current version. (Note: New features and fixes in this release are marked :blue:`blue` in the following list of features.) +The major update from Version 3.0 is adding the analysis capability for :blue:`regional transportation infrastructure`. Note that since version 3.0, most **Haz** options were moved to the **Tool** main menu. -**Release date:** May, 2023 +**Release date:** Dec, 2023 #. **Hazard Types**: * :ref:`User specified earthquakes `. * :ref:`User specified hurricanes `. - * :ref:`ShakeMap Scenarios `, which suports importing the following ShakeMap outputs: + * :ref:`ShakeMap Scenarios `, which supports importing the following ShakeMap outputs: a. ShakeMap ground motion grid in .xml format. b. PGA contours in .json format. c. Fault rupture in .json format. @@ -26,17 +27,24 @@ Capabilities -#. **Asset Types**: +#. **Asset Types**: + * :ref:`Buildings `: - a. Building database in a ``.csv`` format. - b. Building database in a ``.gis`` format. + a. Load building database in a ``.csv`` format. + b. Load building database in a ``.gis`` format. + * :ref:`Transportation infrastructure `: + a. :blue:`Load transportation infrastructure database in SimCenter's` ``.geojson`` :blue:`format.` + b. :blue:`Load transportation infrastructure database in common` ``.gis`` :blue:`format.` + #. **Asset Modeling**: * :ref:`Buildings `: a. MDOF-LU (MDOF shear building model) b. OpenSeesPy script building generator - c. IMasEDP, i.e., no analysis as the IM is considered the EDP + c. IMasEDP, i.e., no structural modeling, and the Intensity Measures (IMs) are considered the Engineering Demand Parameters (EDPs) d. CustomPy + * :ref:`Transportation infrastructure `: + a. IMasEDP, i.e., no structural modeling, and the Intensity Measures (IMs) are considered the Engineering Demand Parameters (EDPs) #. **Asset Analysis**: * :ref:`Buildings `: @@ -44,14 +52,19 @@ Capabilities b. OpenSeesPy c. IMasEDP, i.e., no analysis as the IM is considered the EDP d. CustomPy for CustomPy in Asset Modeling - d. None for IMasEDP option in Modeling. + e. None for IMasEDP option in Modeling. + * :ref:`Transportation infrastructure `: + a. None for IMasEDP option in Modeling. #. **Damage and Loss**: - * Buildings: - * :ref:`Pelicun ` + * :ref:`Buildings `: + * Pelicun a. HAZUS MH EQ b. HAZUS MH EQ IM c. HAZUS MH HU + * :ref:`Transportation infrastructure ` + a. HAZUS MH EQ + b. HAZUS MH EQ IM #. **Uncertainty Quantification**: * :ref:`Dakota `: @@ -64,13 +77,12 @@ Capabilities * Site definition: a. Grid b. Point - c. Scattered sites (user defined sites in .csv format) + c. Scattered sites (user-defined sites in .csv format) * Rupture forecast models: a. OpenSHA UCERF rupture forecast models - b. OpenSHA Point source user defined - c. OpenQuake Scenario Based - d. OpenQuake Classical PSHA - e. :blue:`Hazard Occurrence Model` + b. OpenSHA Point source user-defined + c. OpenQuake rupture forecast + d. Hazard Occurrence Model * Inter-event correlation: a. Baker and Jayaram (2008) * Intra-event correlation: @@ -86,25 +98,24 @@ Capabilities c. Campbell & Bozorgnia (2014) d. Chiou & Youngs (2014) * Intensity Measures: - a. Spectral accelertion (SA) + a. Spectral acceleration (SA) b. Peak ground acceleraation (PGA) * Vs30 Model: a. CGS/Wills Vs30 (Wills et al., 2015) - b. Peak ground acceleraation (PGA) - c. Thompson California Vs30 (Thompson et al., 2018) - d. Global Vs30 (Heath et al., 2020) - e. User Defined` + b. Thompson California Vs30 (Thompson et al., 2018) + c. Global Vs30 (Heath et al., 2020) + d. User Defined * :ref:`Hurricane Scenario Simulation ` (hurricane wind field generation) * Site definition: a. Grid * Hurricane track definition: - a. User defined sites in .csv format - b. Select from database of historical hurricanes + a. User-defined sites in .csv format + b. Select from a database of historical hurricanes c. Truncate hurricane track functionality * Landfall location and parameters: - a. User select on GIS map - b. Manual user entry in input box + a. User selects on GIS map + b. Manual user entry in the input box * Wind field generation model: a. Snaiki and Wu (2017) diff --git a/docs/_sources/common/user_manual/releases/r2dPlans.rst.txt b/docs/_sources/common/user_manual/releases/r2dPlans.rst.txt index aa40fe13..75d5ce01 100644 --- a/docs/_sources/common/user_manual/releases/r2dPlans.rst.txt +++ b/docs/_sources/common/user_manual/releases/r2dPlans.rst.txt @@ -9,26 +9,18 @@ Release Plans The following features are planned to be developed for upcoming releases of |app|. We are actively working on the features in the next release. Farther development priorities may change depending on feedback from the community. If you have any suggestions, we encourage you to contribute and contact us through the SimCenter Forum. -June 2023 +March 2024 ---------- #. Water Distribution Network, buried pipelines.(1.3.4.3) - -Sept 2023 ----------- - #. Efficient forward propagation using Multi-Fidelity Monte-Carlo (1.2.3.1) - Use a few realizations of the output calculated with expensive, high-fidelity models to evaluate and correct the bias in efficient, approximate models, such as surrogates. With little extra computational demands, this method provides a substantial improvement in surrogate model performance if you have the high-fidelity models available that were used to train the surrogates. -#. Support transportation networks hazus level analysis (1.3.4.3) and provide corresponding Examples (1.3.4.7) - Extend the scope of tool with transportation networks and add examples that can serve as templates. - #. Add datasets to simulate subassembly damage and losses under wind demands (1.3.5.1) - Data from recent publications in the Performance-Based Wind Engineering literature is collected to enable high-resolution performance assessment under wind hazard, add data to DB-DamegeAndLoss. -#. Incorprate surrogate models created by other SimCenter tools in regional assesments (1.3.6.1) - Other tools can export models in a standard format that can be imported directly in R2D for use in regional simulations. - #. Probabilistic asset inventories (1.3.6.2) - Calibrate, store, and propagate uncertainties in building features at the regional scale. For example, we have some but not all information for all buildings in an area, fill in the gaps using information we do know. -March 2024 +June 2024 ---------- #. Automatic access to physics-based ground motion simulation results (1.1.1.3) @@ -45,7 +37,7 @@ Sept 2024 #. Develop and implement metrics and their visualization to inform recovery and community resilience (1.4.3.2) -#. Look at aspects related to recovery. Housholds (1.4.3.2), Infrastructure )1.4.2.4), Business operations (1.4.2.5) +#. Look at aspects related to recovery. Housholds (1.4.3.2), Infrastructure (1.4.2.4), Business operations (1.4.2.5) Sept 2025 diff --git a/docs/_sources/common/user_manual/releases/r2dReleaseNotes.rst.txt b/docs/_sources/common/user_manual/releases/r2dReleaseNotes.rst.txt index dcef0483..09ffbabf 100644 --- a/docs/_sources/common/user_manual/releases/r2dReleaseNotes.rst.txt +++ b/docs/_sources/common/user_manual/releases/r2dReleaseNotes.rst.txt @@ -6,7 +6,20 @@ Release Notes *************************** -Version 3.0.0 (Current) +Version 4.0.1 (Current) +----------------------- + +**Release date:** Jan. 2024 + +**Highlights** + +#. Support the assessment of transportation infrastructure. +#. Revised interface for earthquake scenario simulation tool. +#. Added Brails-Transportation tool to generate transportation infrastructure inventory. +#. Allow using PreTrained Surrogate Models from EE-UQ as structural analysis models. + + +Version 3.0.0 ----------------------- **Release date:** May. 2023 diff --git a/docs/_sources/common/user_manual/releases/weCapabilities.rst.txt b/docs/_sources/common/user_manual/releases/weCapabilities.rst.txt index 8fd1c98f..8eed8c6b 100644 --- a/docs/_sources/common/user_manual/releases/weCapabilities.rst.txt +++ b/docs/_sources/common/user_manual/releases/weCapabilities.rst.txt @@ -5,13 +5,13 @@ Capabilities ************ -**Version 3.3.0** of |app| was released **September 2023**. The following lists the functionality available in this current version. (Note: New features and fixes in this release are marked :blue:`blue` in the following list of features.) +**Version 3.1.0** of |app| was released **October 2023**. The following lists the functionality available in this current version. (Note: New features and fixes in this release are marked :blue:`blue` in the following list of features.) Structural Information Model ============================ -Applications used to specify/select the structural model to be used in the analysis. +Applications are used to specify/select the structural model to be used in the analysis. #. MDOF: creating idealized multi-degree-of-freedom models #. MDOF-LU: auto-generated multi-degree-of-freedom model @@ -26,7 +26,7 @@ Applications used to specify/select wind loading for the structure. #. Stochastic Wind: simulating stochastic wind speed using spectral method #. CFD-Digital Wind Tunnel: CFD simulation of boundary layer wind tunnel -#. :blue:`CFD-Wind Load on Isolated Buildings: CFD-based wind load simulation for isolated buildings` +#. :blue:`CFD-Wind Load on Isolated Buildings: CFD-based wind load simulation for isolated buildings with complex geometry` #. DEDM_HRP: database-enabled design framework based on wind-tunnel data for high-rise buildings #. LowRiseTPU: extracting aerodynamics loads based on TPU database for low-rise buildings #. Wind Tunnel Experiment: uses pressure tap measurements from building in wind tunnel experiment diff --git a/docs/_sources/common/user_manual/releases/weReleaseNotes.rst.txt b/docs/_sources/common/user_manual/releases/weReleaseNotes.rst.txt index a74b3f61..8f51b666 100644 --- a/docs/_sources/common/user_manual/releases/weReleaseNotes.rst.txt +++ b/docs/_sources/common/user_manual/releases/weReleaseNotes.rst.txt @@ -5,20 +5,20 @@ Release Notes ************* -Version 3.3 (Current) +Version 3.1 (Current) ----------------------- -**Release date:** Sept. 2023 +**Release date:** Oct. 2023 **Highlights** #. Added capability to simulate wind load on building with arbitrary shape -#. Added options to import and transform STL geometry of the building. -#. Fixed bugs in prior release +#. Added options to import and transform the STL geometry of the building. +#. Fixed bugs in the prior release #. Created a new CFD example to demonstrate the recently added features. -Version 3.0 +Version 3.0.0 --------------- **Release date:** July. 2023 diff --git a/docs/_sources/common/user_manual/usage/desktop/DakotaBayesianCalibration.rst.txt b/docs/_sources/common/user_manual/usage/desktop/DakotaBayesianCalibration.rst.txt index 3a5988ec..fb13a782 100644 --- a/docs/_sources/common/user_manual/usage/desktop/DakotaBayesianCalibration.rst.txt +++ b/docs/_sources/common/user_manual/usage/desktop/DakotaBayesianCalibration.rst.txt @@ -4,7 +4,7 @@ Bayesian Calibration ******************** -The methods in the Bayesian calibration category are concerned with estimation of the probability distribution of the parameter values given observational measurements. Unlike deterministic parameter estimation methods, in which the user provides a range and an initial starting point for the input random variables, when using the methods in this category, the user has some idea about the probability distribution of the parameter values. This information is provided in the form of the prior distributions in the **RV** panel. The Bayesian calibration methods take this prior information and combine it with information from the observed data provided in the **UQ** panel, to infer posterior distributions of the parameter values. A Bayesian updating paradigm is followed, the prior distribution on a parameter is updated through a Bayesian framework involving experimental data and a likelihood function. The likelihood function specifies the likelihood that a particular parameter value of the model produced the observed data. Dakota uses a Gaussian likelihood function. The algorithms that generate the samples to characterize the posterior distributions are typically based on some Markov Chain Monte Carlo (MCMC) methods. Currently, |appName| provides access to the DREAM algorithm implemented in Dakota. +The methods in the Bayesian calibration category are concerned with the estimation of the probability distribution of the parameter values given observational measurements. Unlike deterministic parameter estimation methods, in which the user provides a range and an initial starting point for the input random variables, when using the methods in this category, the user has some idea about the probability distribution of the parameter values. This information is provided in the form of the prior distributions in the **RV** panel. The Bayesian calibration methods take this prior information and combine it with information from the observed data provided in the **UQ** panel, to infer posterior distributions of the parameter values. A Bayesian updating paradigm is followed, the prior distribution on a parameter is updated through a Bayesian framework involving experimental data and a likelihood function. The likelihood function specifies the likelihood that a particular parameter value of the model produced the observed data. Dakota uses a Gaussian likelihood function. The algorithms that generate the samples to characterize the posterior distributions are typically based on some Markov Chain Monte Carlo (MCMC) methods. Currently, |appName| provides access to the DREAM algorithm implemented in Dakota. .. diff --git a/docs/_sources/common/user_manual/usage/desktop/DakotaDeterministicCalibration.rst.txt b/docs/_sources/common/user_manual/usage/desktop/DakotaDeterministicCalibration.rst.txt index c190d27d..4937965d 100644 --- a/docs/_sources/common/user_manual/usage/desktop/DakotaDeterministicCalibration.rst.txt +++ b/docs/_sources/common/user_manual/usage/desktop/DakotaDeterministicCalibration.rst.txt @@ -4,7 +4,7 @@ Deterministic Calibration ************************* -Deterministic calibration methods (also known as non-linear least squares methods or deterministic parameter estimation methods) are used to fit a set of m observations (provided in the calibration data file defined in the **UQ** panel) with a model (defined in the **FEM** panel) that is non-linear with n unknown parameters. The unknown parameters of this model are defined in the **RV** panel. The bounds of the domain within which the optimal values of the parameters need to be searched for are also specified in the **RV** panel, along with the initial point at which the search will begin. No prior specification of the distribution associated with the random variables is necessary. The output quantities from the model are defined in the **QOI** panel. For each evaluation of the computational model, the processing scripts should write the values of the simulated response quantities of interest in a file called ``results.out``. The algorithms employed will find a set of parameter values that **minimizes** the sum of the squared differences between the measured values of the QoIs and the predicted values of the QoIs from the computational model. The algorithms themselves are general functional minimization algorithms seeking to minimize: +Deterministic calibration methods (also known as non-linear least squares methods or deterministic parameter estimation methods) are used to fit a set of m observations (provided in the calibration data file defined in the **UQ** panel) with a model (defined in the **FEM** panel) that is non-linear with n unknown parameters. The unknown parameters of this model are defined in the **RV** panel. The bounds of the domain within which the optimal values of the parameters need to be searched for are also specified in the **RV** panel, along with the initial point at which the search will begin. No prior specification of the distribution associated with the random variables is necessary. The output quantities from the model are defined in the **QOI** panel. For each evaluation of the computational model, the processing scripts should write the values of the simulated response quantities of interest in a file called ``results.out``. The algorithms employed will find a set of parameter values that **minimizes** the sum of the squared differences between the measured values of the QoIs and the predicted values of the QoIs from the computational model. The algorithms themselves are general functional minimization algorithms seeking to minimize: .. math:: @@ -20,10 +20,10 @@ The panel that is presented to the user when this Dakota Category is chosen, is :align: center :figclass: align-center - Dakota determinstic calibration input panel. + Dakota deterministic calibration input panel. -For determinstic calibration two different optimization algorithms are currently provided under the Method drop down menu, namely OPT++GaussNewton and NL2SOL. For both methods three input parameters need to be specified as shown in the figure: +For deterministic calibration two different optimization algorithms are currently provided under the Method drop-down menu, namely OPT++GaussNewton and NL2SOL. For both methods three input parameters need to be specified as shown in the figure: 1. the maximum number of iterations for the optimization algorithm 2. the convergence tolerance @@ -37,7 +37,7 @@ OPT++ provides a Gauss-Newton least squares capability which, on zero-residual t NL2SOL ^^^^^^ -The NL2SOL method is based on an adaptive nonlinear least-squares algorithm, devised by Dennis and colleagues ([Dennis81a]_, [Dennis81b]_). NL2SOL uses a trust region method and adaptively switches between two Hessian approximations, the Gauss-Newton approximation alone and the Gauss-Newton approximation plus a quasi-Newton approximation to the rest of the Hessian. This latter approximation being useful when the starting guess is far from solution. For problems with large residuals, this algorithm is known to be more reliable than Gauss-Newton. +The NL2SOL method is based on an adaptive nonlinear least-squares algorithm, devised by Dennis and colleagues ([Dennis81a]_, [Dennis81b]_). NL2SOL uses a trust region method and adaptively switches between two Hessian approximations, the Gauss-Newton approximation alone and the Gauss-Newton approximation plus a quasi-Newton approximation to the rest of the Hessian. This latter approximation is useful when the starting guess is far from the solution. For problems with large residuals, this algorithm is known to be more reliable than Gauss-Newton. .. note:: diff --git a/docs/_sources/common/user_manual/usage/desktop/DakotaGradientFreeOptimization.rst.txt b/docs/_sources/common/user_manual/usage/desktop/DakotaGradientFreeOptimization.rst.txt index cbc433cf..c776db36 100644 --- a/docs/_sources/common/user_manual/usage/desktop/DakotaGradientFreeOptimization.rst.txt +++ b/docs/_sources/common/user_manual/usage/desktop/DakotaGradientFreeOptimization.rst.txt @@ -6,11 +6,11 @@ Gradient-free Parameter Estimation It is not uncommon for engineering problems that the gradient of a computational model with respect to the model parameters is not reliably estimated. Sometimes, the objective function for deterministic calibration is not differentiable. In such situations, a gradient-based local search algorithm might fail to locate the optimum parameter values that provide the best fit of the model predictions to the data. A gradient-free local search method can be employed for deterministic calibration instead of a gradient-based algorithm in such scenarios. -Gradient-free optimization methods are used to minimize an objective function based solely on evaluation of the objective function values without the use of any derivative information or any approximation of the derivatives. When concerned with parameter estimation, the objective function is typically the sum of the squared differences between the predictions from a model and the calibration data. However, any objective function that the user desires can be employed. When performing grdient-free parameter estimation, the model (or the post-processing script, if any), should be defined in a way that returns the objective function value (a single scalar quantity) in a file called ``results.out``. +Gradient-free optimization methods are used to minimize an objective function based solely on an evaluation of the objective function values without the use of any derivative information or any approximation of the derivatives. When concerned with parameter estimation, the objective function is typically the sum of the squared differences between the predictions from a model and the calibration data. However, any objective function that the user desires can be employed. When performing gradient-free parameter estimation, the model (or the post-processing script, if any), should be defined in a way that returns the objective function value (a single scalar quantity) in a file called ``results.out``. The parameters of the model (which is defined in the **FEM** panel) are defined in the **RV** panel. The bounds of the domain within which the optimal values of the parameters need to be searched for are also specified in the **RV** panel, along with the initial point at which the search will start. No prior specification of the distribution associated with the random variables is necessary. -The output from the model is the objective function value, and this can be given a name which is defined in the **EDP** panel. The length must be set equal to 1. +The output from the model is the objective function value, and this can be given a name that is defined in the **EDP** panel. The length must be set equal to 1. The algorithms employed will find a set of parameter values that **minimizes** the objective function. @@ -31,14 +31,14 @@ Gradient-free parameter estimation uses the pattern search algorithm that is ava 1. Initial step size: this defines the initial size of the offsets used in the pattern search algorithm 2. Contraction factor: this specifies the ratio of the reduction in the offset size used in the pattern search algorithm -3. Max # model evals: This is a termination criterion. This specifies the maximum number of model evaluations allowed during the search for the optimum parameter values. This sets the total compuational budget for the pattern search algorithm. +3. Max # model evals: This is a termination criterion. This specifies the maximum number of model evaluations allowed during the search for the optimum parameter values. This sets the total computational budget for the pattern search algorithm. 4. Max # iterations: This is a termination criterion. This specifies the maximum number of iterations allowed in the optimization algorithm. During each iteration of the algorithm, several model evaluations occur in parallel. -5. Variable tolerance: This is a terminiation criterion. This specifies the maximum permitted change in the value of the parameters being estimated from one iteration to the next. -6. Convergence tolerance: This is a termination criterion. This soecifies the maximum permitted change in the value of the objective function from one iteration to the next. +5. Variable tolerance: This is a termination criterion. This specifies the maximum permitted change in the value of the parameters being estimated from one iteration to the next. +6. Convergence tolerance: This is a termination criterion. This specifies the maximum permitted change in the value of the objective function from one iteration to the next. The search for the optimum parameter value will terminate once any of the four available termination criteria are met. .. [Torczon] - Virginia Torczon. On the convergence of pattern search algortihms. SIAM J. Optim. Vol. 7, No. 1, pp. 1–25, February 1997. + Virginia Torczon. On the convergence of pattern search algorithms. SIAM J. Optim. Vol. 7, No. 1, pp. 1–25, February 1997. diff --git a/docs/_sources/common/user_manual/usage/desktop/DakotaReliability.rst.txt b/docs/_sources/common/user_manual/usage/desktop/DakotaReliability.rst.txt index 6f78cb2d..12623eb4 100644 --- a/docs/_sources/common/user_manual/usage/desktop/DakotaReliability.rst.txt +++ b/docs/_sources/common/user_manual/usage/desktop/DakotaReliability.rst.txt @@ -6,7 +6,7 @@ Reliability Analysis Reliability methods are another class of probabilistic algorithms used for quantifying the effect of uncertainties in simulation input on response metrics of interest. These methods, unlike forward propagation analysis, provide the probability of response exceeding the user-provided threshold levels, i.e. given a set of uncertain input variables, it estimates the probability of system 'failure' defined as an excessive response. For reliability analysis, it is often more efficient to concentrate samples around the tail region of the response distributions, i.e. generating more events having low occurrence probability but high consequence, since often the number of samples required by naive sampling approach to resolve a low probability can be prohibitive. -Reliability methods can be split into local and global reliability methods and importance sampling-based method, as elaborated in the following sections. +Reliability methods can be split into local and global reliability methods and importance sampling-based methods, as elaborated in the following sections. Problem Formulation @@ -35,7 +35,7 @@ where :math:`q(\mathbf{x})` is the computed value of QoI for given :math:`\mathb Local Reliability Methods ---------------------------- -Local reliability methods introduces first/second-order local approximation of the response or :math:`g(\mathbf{x})` around either "Mean Value" or "Design point (also known as the most probable point, MPP)". Each of these methods involves gradient-based local optimization. The local reliability methods can also be used for "inverse reliability problems" which aims to idenitify the unknown parameter (random variables) combination that produces prescribed probability levels. The user selects the local method using the pull down menu. +Local reliability methods introduce a first/second-order local approximation of the response or :math:`g(\mathbf{x})` around either "Mean Value" or "Design point (also known as the most probable point, MPP)". Each of these methods involves gradient-based local optimization. The local reliability methods can also be used for "inverse reliability problems" which aim to identify the unknown parameter (random variables) combination that produces prescribed probability levels. The user selects the local method using the pull-down menu. The default local reliability method is inverse reliability using the first-order reliability approximation (FORM) method. For the FORM method the user provides the following inputs: @@ -48,7 +48,7 @@ The default local reliability method is inverse reliability using the first-orde Local reliability analysis using the MPP option. -1. The first input involves selection of the MPP search method from the following options: +1. The first input involves a selection of the MPP search method from the following options: - ``no_approx``: the MPP search on the original response functions without the use of any approximations. Combining this option with first-order and second-order integration approaches (see next section) results in the traditional first-order and second-order reliability methods (FORM and SORM). @@ -62,17 +62,17 @@ The default local reliability method is inverse reliability using the first-orde 2. The second input involves the user selecting the integration approach for computing probabilities at the MPP. These can be selected to be first-order or second-order integration. -3. Finally the user selects either response levels (for forward reliability analysis) or probability level (for inverse reliability analysis) from a drop down menu. The user then provides these levels in the line edit to the right of the pull down menu. +3. Finally the user selects either response levels (for forward reliability analysis) or probability level (for inverse reliability analysis) from a drop-down menu. The user then provides these levels in the line edit to the right of the pull-down menu. .. warning:: - Only a single quantity of interest (QoI) is allowed to be specified when using most probable point searching. Mean Value search method works for multiple QoIs. + Only a single quantity of interest (QoI) is allowed to be specified when using most probable point searching. The Mean Value search method works for multiple QoIs. .. [EldredBichonAdams2006]: - Eldred, M.S., Bichon, B.J., and Adams, B.M., "Overview of Reliability Analysis and Design Capabilities in DAKOTA,Proceedings of the NSF Workshop on Reliable Engineering Computing (REC 2006), Savannah, GA, February 22-24, 2006. + Eldred, M.S., Bichon, B.J., and Adams, B.M., "Overview of Reliability Analysis and Design Capabilities in DAKOTA, Proceedings of the NSF Workshop on Reliable Engineering Computing (REC 2006), Savannah, GA, February 22-24, 2006. -The second local reliability method available is the Mean Value method (also known as MVFOSM). It is the simplest and least-expensive reliability method because it estimates the response means, response standard deviations, and all response-probability levels from a single evaluation of the response functions and their gradients at the uncertain variable means. This approximation can have acceptable accuracy when the response functions are nearly linear and their distributions are approximately Gaussian, but **can have poor accuracy in other situations**. +The second local reliability method available is the Mean Value method (also known as MVFOSM). It is the simplest and least-expensive reliability method because it estimates the response means, response standard deviations, and all response probability levels from a single evaluation of the response functions and their gradients at the uncertain variable means. This approximation can have acceptable accuracy when the response functions are nearly linear and their distributions are approximately Gaussian, but **can have poor accuracy in other situations**. As shown in the figure below the user selects either to use response levels or probability levels. The user then inputs the levels. @@ -122,7 +122,7 @@ For problems where one is interested in the rare events rather than the whole di :numref:`figIS` shows the input panel for IS scheme. Similar to MCS and LHS, IS requires both the number of samples to be executed and the corresponding seed for generating such random samples. In addition, IS algorithm can be performed via three different approaches, as specified by the third input method: -1. **Basic Sampling**: A sampling density is constructed in the failure region based on an initial LHS sampling, followed by generation of importance samples and weights and evaluation of the Cumulative Distribution Function. +1. **Basic Sampling**: A sampling density is constructed in the failure region based on an initial LHS sampling, followed by the generation of importance samples and weights and evaluation of the Cumulative Distribution Function. 2. **Adaptive Sampling**: The basic sampling procedure is repeated iteratively until a convergence in failure probability is achieved. 3. **Multimodal Adaptive Sampling**: A multimodal sampling density is constructed based on samples in the failure and the adaptive sampling procedure is used. diff --git a/docs/_sources/common/user_manual/usage/desktop/DakotaSampling.rst.txt b/docs/_sources/common/user_manual/usage/desktop/DakotaSampling.rst.txt index 618cc7fc..c1d526a5 100644 --- a/docs/_sources/common/user_manual/usage/desktop/DakotaSampling.rst.txt +++ b/docs/_sources/common/user_manual/usage/desktop/DakotaSampling.rst.txt @@ -4,7 +4,7 @@ Forward Propagation ********************************************** -The forward propagation analysis provides probabilistic understanding of output variables by producing sample realizations and statistical moments (mean, standard deviation, skewness, and kurtosis) of the quantities of interest. Currently four sampling methods are available: +The forward propagation analysis provides a probabilistic understanding of output variables by producing sample realizations and statistical moments (mean, standard deviation, skewness, and kurtosis) of the quantities of interest. Currently, four sampling methods are available: 1. **Monte Carlo Sampling (MCS)** 2. **Latin Hypercube Sampling (LHS)** @@ -35,7 +35,7 @@ MCS is among the most robust and universally applicable sampling methods. Moreov Latin Hypercube Sampling (LHS) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ -Conventional Monte Carlo method generates each sample independently, which may produce undesired clusters and gaps between the samples arising from the sampling variability. On the other hand, Latin hypercube sampling (LHS) aims to prevent those gaps and clusters by 'evenly' spreading out the samples throughout the whole input domain. This can significantly reduce the sampling variability and facilitate faster convergence of the probabilistic statistics. In particular, LHS divides the input domain of each variable into N intervals with equal probability and locates the samples such that only one sample lies on each interval. This strategy enforces the samples to be more uniformly spread across the domain. In general, LHS encouraged over MCS as it provides unbiased estimation with smaller standard error. For example, `this article `_ suggests that the convergence rate of a sample mean is about quadratically faster with LHS than with Monte Carlo simulation. However, it is noted that one drawback of LHS is that there is no closed-form expression to quantify the error level of the estimators. This means that the user may need to perform the multiple batch samplings to quantify the error from the sample variability +Conventional Monte Carlo method generates each sample independently, which may produce undesired clusters and gaps between the samples arising from the sampling variability. On the other hand, Latin hypercube sampling (LHS) aims to prevent those gaps and clusters by 'evenly' spreading out the samples throughout the whole input domain. This can significantly reduce the sampling variability and facilitate faster convergence of the probabilistic statistics. In particular, LHS divides the input domain of each variable into N intervals with equal probability and locates the samples such that only one sample lies on each interval. This strategy forces the samples to be more uniformly spread across the domain. In general, LHS is encouraged over MCS as it provides unbiased estimation with a smaller standard error. For example, `this article `_ suggests that the convergence rate of a sample mean is about quadratically faster with LHS than with Monte Carlo simulation. However, it is noted that one drawback of LHS is that there is no closed-form expression to quantify the error level of the estimators. This means that the user may need to perform multiple batch samplings to quantify the error from the sample variability .. _figLHS1: @@ -63,7 +63,7 @@ Conventional Monte Carlo method generates each sample independently, which may p Gaussian Process Regression (GPR) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ -For the problems in which computationally expensive models are involved, conventional sampling schemes such as LHS and MCS can be extremely time-consuming. In such case, a surrogate model can be constructed based on a smaller number of simulation runs, and then the surrogate model can be used to efficiently generate a larger number of samples replacing the expensive simulations. +For the problems in which computationally expensive models are involved, conventional sampling schemes such as LHS and MCS can be extremely time-consuming. In this case, a surrogate model can be constructed based on a smaller number of simulation runs, and then the surrogate model can be used to efficiently generate a larger number of samples replacing the expensive simulations. Gaussian Process Regression (GPR), also known as Kriging is one of the well-established surrogate techniques, which constructs an approximated response surface based on Gaussian process modeling and covariance matrix optimizations. :numref:`figGPR` shows the input panel for the GPR model that consists of training and sampling panels. @@ -76,9 +76,9 @@ Gaussian Process Regression (GPR), also known as Kriging is one of the well-esta GPR forward propagation input panel. -In the **Surrogate Training Data** panel, the users specify the number of samples of the output of the computationally expensive model to be select either Monte Carlo Sampling or Latin Hypercube Sampling to generate sample output values from the computationally expensive model, which, along with the corresponding input values are used to train the surrogate models. +In the **Surrogate Training Data** panel, the users specify the number of samples of the output of the computationally expensive model to be either Monte Carlo Sampling or Latin Hypercube Sampling to generate sample output values from the computationally expensive model, which, along with the corresponding input values are used to train the surrogate models. -Other surrogate models, different from Gaussian process regression are also available in the drop-down menu titled **Surface Fitting Method**. All thse surrogate models utilize either Monte Carlo Sampling or Latin Hypercube Sampling to generate sample output values, which, along with the corresponding input values are used to train the surrogate models. +Other surrogate models, different from Gaussian process regression are also available in the drop-down menu titled **Surface Fitting Method**. All these surrogate models utilize either Monte Carlo Sampling or Latin Hypercube Sampling to generate sample output values, which, along with the corresponding input values are used to train the surrogate models. Polynomial Chaos Expansion (PCE) diff --git a/docs/_sources/common/user_manual/usage/desktop/DakotaSensitivity.rst.txt b/docs/_sources/common/user_manual/usage/desktop/DakotaSensitivity.rst.txt index eee50164..9d0eb7c3 100644 --- a/docs/_sources/common/user_manual/usage/desktop/DakotaSensitivity.rst.txt +++ b/docs/_sources/common/user_manual/usage/desktop/DakotaSensitivity.rst.txt @@ -4,11 +4,11 @@ Global Sensitivity Analysis ********************************************** -Global sensitivity analysis is used to quantify contribution of each input variable to the uncertainty in the output quantity of interest (QoI). In particular, by calculating the global sensitivity indices, users can set preferences between random variables considering both inherent randomness and its propagation through the model. Global sensitivity analysis helps users to understand the overall impact of different sources of uncertainties and their interactions, as well as to accelerate UQ computations by focusing on dominant dimensions or screening out trivial input variables. Sensitivity index can also be used to identify the input variables for which extra experimentation/research may be useful in reducing the uncertainty in the initial specification. +Global sensitivity analysis is used to quantify the contribution of each input variable to the uncertainty in the output quantity of interest (QoI). In particular, by calculating the global sensitivity indices, users can set preferences between random variables considering both inherent randomness and its propagation through the model. Global sensitivity analysis helps users to understand the overall impact of different sources of uncertainties and their interactions, as well as to accelerate UQ computations by focusing on dominant dimensions or screening out trivial input variables. The sensitivity index can also be used to identify the input variables for which extra experimentation/research may be useful in reducing the uncertainty in the initial specification. -**Sobol indices** are widely used variance-based global sensitivity measures which have two types: main effect and total effect sensitivity indices. The **main effect index** quantifies the fraction of variance in QoI that can be attributed to specific input random variable(s) but without considering interactive effect with other input variables. The **total effect index**, on the other hand, additionally takes the interactions into account. **Please read** :ref:`HERE` **for more details on the equations.** +**Sobol indices** are widely used variance-based global sensitivity measures which have two types: main effect and total effect sensitivity indices. The **main effect index** quantifies the fraction of variance in QoI that can be attributed to specific input random variable(s) but without considering the interactive effect with other input variables. The **total effect index**, on the other hand, additionally takes the interactions into account. **Please read** :ref:`HERE` **for more details on the equations.** -**Dakota Sensitivity Analysis** is based on efficient Monte Carlo method (See Eqs. (8) and (9) in [Weirs12]_ which is referred in Dakota Technical manual [Adams20]_), and the user has two options to generate the samples on which the statistics are created: Monte Carlo, and Latin Hypercube Sampling (LHS). For both, they are required, as shown in figure below, to specify the number of samples and a seed. +**Dakota Sensitivity Analysis** is based on the efficient Monte Carlo method (See Eqs. (8) and (9) in [Weirs12]_ which is referenced in the Dakota Technical manual [Adams20]_), and the user has two options to generate the samples on which the statistics are created: Monte Carlo, and Latin Hypercube Sampling (LHS). For both, they are required, as shown in the figure below, to specify the number of samples and a seed. The results of the Sensitivity analysis will show both the main effect and total effect `Sobol indices `_ for each random variable (RV) for each of the quantity of interest (QoI). @@ -26,7 +26,7 @@ The results of the Sensitivity analysis will show both the main effect and total When the associated FEM model is computationally expensive, the user should consider that the actual number of the simulation runs is larger than the number of samples specified in the input panel. The actual number of simulation runs are NS*(2+NRV) - - NS = number of samples specified by user + - NS = number of samples specified by the user - NRV = number of random variables diff --git a/docs/_sources/common/user_manual/usage/desktop/RV.rst.txt b/docs/_sources/common/user_manual/usage/desktop/RV.rst.txt index ffe03200..3144b8ba 100644 --- a/docs/_sources/common/user_manual/usage/desktop/RV.rst.txt +++ b/docs/_sources/common/user_manual/usage/desktop/RV.rst.txt @@ -31,13 +31,13 @@ The following six distribution classes are supported for Dakota engine. 2. `Lognormal `_ + User provides the mean (:math:`\mu`) and standard deviation (:math:`\sigma`) of the lognormal distribution. The density function of the lognormal distribution, as a function of :math:`\mu` and :math:`\sigma` is: .. math:: f(x) = \frac{1}{\sqrt{2 \pi} \zeta x} \exp \left( -{\frac{1}{2} \left( \frac{\ln x - \lambda}{\zeta} \right)^2} \right) - where :math:`\zeta^2 = \ln \left( \frac{\sigma^2}{\mu^2} + 1 \right)` and :math:`\lambda = \ln(\mu) - \frac{\zeta^2}{2}` diff --git a/docs/_sources/common/user_manual/usage/desktop/SimCenterUQSurrogate.rst.txt b/docs/_sources/common/user_manual/usage/desktop/SimCenterUQSurrogate.rst.txt index 0f3e5e14..00d709e6 100644 --- a/docs/_sources/common/user_manual/usage/desktop/SimCenterUQSurrogate.rst.txt +++ b/docs/_sources/common/user_manual/usage/desktop/SimCenterUQSurrogate.rst.txt @@ -8,7 +8,37 @@ Gaussian Process (GP) Surrogate Modeling .. Note:: Surrogate modeling functionality of |short tool id| is built upon `GPy `_ library (available under BSD 3-clause license), an opensource python framework for Gaussian process modeling developed in the Sheffield machine learning group. -.. only:: quoFEM +.. Warning:: + Update: 01.04.2024 + + **Only on Mac**, the GPy module (v.1.12 or lower) has a dependency version compatibility issue with other python packages SimCenter uses. + To run GPy on SimCenter tools, one needs to install the latest developer release of GPy. Below is the error message you get. + + .. code:: console + + Surrogate modeling module uses GPy python package which is facing a version compatibility issue at this moment (01.05.2024). + To use the surrogate module, one needs to update manually the GPy version to 1.13. The instructions can be found in the documentation: + https://nheri-simcenter.github.io/quoFEM-Documentation/common/user_manual/usage/desktop/SimCenterUQSurrogate.html#lblsimsurrogate + + Until the GPy version v1.13 is available on pip, one can install the `developer release of GPy v1.13 `_ by typing the following commands one by one in the terminal + + .. code:: console + + git clone https://github.com/SheffieldML/GPy.git + cd GPy + {$PathToPythonExe} -m pip uninstall GPy + {$PathToPythonExe} setup.py install + + where ``{$PathToPythonExe}`` should be replaced with the python path found in the File-Preference window. After the third line, they will ask for the confirmation (type Y and enter). Check the installation status by typing + + .. code:: console + + {$PathToPythonExe} -m pip show GPy + + and confirming that the version appears as 1.13.x. For any questions and bug reports, please contact us through `user forum `_. + + +.. only:: quoFEM_app The ``Train GP Surrogate Model`` module is used to construct a Gaussian process (GP) based **surrogate model** that substitutes expensive computational **simulation models** or physical experiments. Consider a simulation model, with input random variables (or parameters) :math:`\boldsymbol{x}` and output quantity of interests, denoted as :math:`\boldsymbol{y}=f(\boldsymbol{x})`. A surrogate model for the corresponding simulation model can be built by different user-provided information types (RV-random variables, QoI-quantities of interest): @@ -220,7 +250,7 @@ Note that the results from the parallel and serial run may not be exactly the sa The user can select intensity measures (IMs) that will be used as auxiliary inputs of the surrogate model, in addition to those specified in the RV tab. If ground motions have more than one directional component, either each component's IM can be added as a separate surrogate input parameter, or they can be aggregated by using their geometric mean. The latter can be selected by checking 'Use geometric mean when 2 or more ground motion components are given'. -.. only:: quoFEM +.. only:: quoFEM_app Case 2: Import RV Dataset and run Simulation ---------------------------------------------- @@ -338,7 +368,7 @@ Note that the results from the parallel and serial run may not be exactly the sa RV (Random Variables) Tab -------------------------- -.. only:: quoFEM +.. only:: quoFEM_app **Case 1 and 2**: @@ -353,7 +383,7 @@ The bounds of RVs need to cover the domain of interest in future applications, w Example of RV tab -.. only:: quoFEM +.. only:: quoFEM_app **Case 3**: **RV data tab** will be populated automatically as soon as the dataset is imported. diff --git a/docs/_sources/common/user_manual/usage/desktop/UCSD_UQ_Hierarchical.rst.txt b/docs/_sources/common/user_manual/usage/desktop/UCSD_UQ_Hierarchical.rst.txt new file mode 100644 index 00000000..9b8358d3 --- /dev/null +++ b/docs/_sources/common/user_manual/usage/desktop/UCSD_UQ_Hierarchical.rst.txt @@ -0,0 +1,46 @@ +.. _lblUCSDHierarchical: + + +Calibration of Hierarchical Model +********************************* + +Introduction +============ +Bayesian calibration of a hierarchical model is performed using the Adaptive Metropolis-within-Gibbs sampling algorithm in quoFEM. Adaptive Metropolis-within-Gibbs is an advanced Markov chain Monte Carlo (MCMC) method that is designed to efficiently sample from complex, high-dimensional distributions, especially when direct sampling of these distributions is impractical. + +The sampler is initialized with a set of reasonable values for the variables (i.e., parameters of the hierarchical model). The hierarchical model that is used in the UCSD_UQ engine (refer the :ref:`Technical Manual ` for more details) results in a structure where the variables can be grouped into blocks. For example, the parameters of the computational model for each dataset have strong interactions/dependencies among themselves, while they are independent of the parameters of the model for other datasets or the hyperparameters or the prediction error variances that are also part of the variables calibrated in the hierarchical model. After the variables have been grouped into blocks, Gibbs sampling involves updating the variables within each block sequentially, conditioned on the current values of variables in other blocks, and generating a sample from the updated distribution. For all the blocks where it is not possible to directly generate a sample from the updated distribution, adaptive Metropolis steps are used. In this step, a new state is proposed for all the variables within the block based on the current values using an adaptive proposal distribution. The acceptance probability for the proposed state is computed using the Metropolis-Hastings criterion and the proposed state is accepted or rejected based on this probability. The proposal distributions are adapted based on the accept/reject decisions made during the previous adaptive Metropolis steps. The adaptation is performed to improve the efficiency of the sampling process by adjusting the proposal distributions to better match the target distribution. This process is repeated for a large number of iterations, after which the sampler generates values from the updated distributions of the parameters of the hierarchical model. + + +Usage +===== +To use the Adaptive Metropolis-within-Gibbs algorithm, select the **UCSD-UQ** engine in the **UQ** panel and select the **Hierarchical** Model. + +The required inputs to perform Bayesian calibration of a hierarchical model in quoFEM are **Sample Size**, **Random State**, **Calibration Data File Name**, and **Calibration Datasets Directory**. + +The optional inputs are **Restart File Name**, **Adaptation Duration**, and **Adaptation Frequency**. Figure :numref:`figHierarchicalPanel` shows the input panel that is presented when the Hierarchical model is selected. Each of the options on this panel will be explained next. + +.. _figHierarchicalPanel: + +.. figure:: figures/UCSD_Hierarchical.png + :align: center + :figclass: align-center + + Input panel for Bayesian calibration of a hierarchical model. + +1. **Sample Size** defines the number of values to be sampled from the posterior probability distribution of the parameters of the computational model. + +2. **Random State** is an integer that is used to specify the seed value of the pseudorandom number generator used in the Bayesian updating algorithm. Setting the same seed as in a previous analysis ensures that the same result is reproduced if the analysis is run again with the same inputs used in the previous analysis. + +3. **Restart File Name** is the name of a JSON file containing the results from a previous Bayesian calibration of the same hierarchical model using quoFEM. The restart option allows users to resume the MCMC sampling from a previously obtained sample value. + +4. **Adaptation Duration** is an integer that specifies the initial number of steps of the sampler during which the characteristics of the proposal distribution are adjusted to increase the efficiency of the sampling. + +5. **Adaptation Frequency** is an integer that defines the number of steps within the adaptation duration after which the proposal distribution is adapted. + +6. **Calibration Data File Name** is the name of a text file that contains the data of the measured values of the output quantity of interest. + +7. **Calibration Datasets Directory** is the path to the directory that contains the datasets from multiple measurements. + + + + diff --git a/docs/_sources/common/user_manual/usage/desktop/UCSD_UQ_TMCMC.rst.txt b/docs/_sources/common/user_manual/usage/desktop/UCSD_UQ_TMCMC.rst.txt index e943a5a5..1a0a6533 100644 --- a/docs/_sources/common/user_manual/usage/desktop/UCSD_UQ_TMCMC.rst.txt +++ b/docs/_sources/common/user_manual/usage/desktop/UCSD_UQ_TMCMC.rst.txt @@ -1,31 +1,33 @@ .. _lblUCSDTMCMC: -Transitional Markov chain Monte Carlo (TMCMC) algorithm -******************************************************* +Calibration of Non-hierarchical Model +************************************* Introduction ============ -TMCMC is an algorithm which is used to draw samples from the posterior probability distribution of random variables when performing Bayesian estimation. Bayesian estimation is a probabilistic inverse problem where the objective is to estimate the probability distribution of the parameters of a computational model, given data. The data consist of numbers which are typically obtained from measurements of a physical phenomenon being studied. In quoFEM, the data are provided in a text file, whose path is defined in the **UQ** panel. The computational model (defined in the **FEM** panel) is an approximation of the real process that generated the data and the outputs of this model (defined in the **QoI** panel) are the same quantities of interest for which we have measured data. The model has several parameters that influence the output predicted by the model when it is evaluated at a set of inputs. In the inverse problem, the values of these parameters are unknown, and in the Bayesian setting, they are treated as random variables, with specified prior probability distribution functions (defined in the **RV** panel). To complete the definition of the Bayesian inverse problem, the probability model for the data needs to be specified, which is done by the log-likelihood function in the **UQ** panel. +Bayesian calibration of a non-hierarchical model is a probabilistic inverse problem where the objective is to estimate the probability distribution of the parameters of a computational model, using all the available data. The data consist of numbers which are typically obtained from measurements of a physical phenomenon being studied. In quoFEM, the data are provided in a text file, whose path is defined in the **UQ** panel. The computational model (defined in the **FEM** panel) is an approximation of the real process that generated the data and the outputs of this model (defined in the **QoI** panel) are the same quantities of interest for which we have measured data. The model has several parameters that influence the output predicted by the model when it is evaluated at a set of inputs. In the inverse problem, the values of these parameters are unknown, and in the Bayesian setting, they are treated as random variables, with specified prior probability distribution functions (defined in the **RV** panel). To complete the definition of the Bayesian inverse problem, the probability model for the data needs to be specified, which is done by the log-likelihood function in the **UQ** panel. Usage ===== +Transitional Markov chain Monte Carlo (TMCMC) is an algorithm that is used to draw samples from the posterior probability distribution of the parameters of a computational model when performing Bayesian calibration using a non-hierarchical model. + To use the TMCMC algorithm, select the **UCSD-UQ** engine in the **UQ** panel. Currently, only the TMCMC method is available with the **UCSD-UQ** engine. The required inputs to perform Bayesian calibration in quoFEM using the TMCMC algorithm are **# Samples**, **Seed**, and **Calibration Data File**. Specifying **Log Likelihood Script** is optional. Figure :numref:`figTMCMCPanel` shows the input panel that is presented when the TMCMC method is selected. Each of the options on this panel will be explained next. .. _figTMCMCPanel: -.. figure:: figures/UCSD_UQ_Engine.png +.. figure:: figures/UCSD_Non-hierarchical.png :align: center :figclass: align-center TMCMC algorithm input panel. -1. **# Samples** defines the number of values to be sampled from the posterior probability distribution of the parameters of the computational model. This number is not the same as the number of times the computational model is evaluated. In order to sample from the posterior probability distribution of the inputs, the TMCMC algorithm relies on gradually changing the target distribution from the prior to posterior in a number of stages. The number of stages is not known apriori. In every stage, the Markov chain is propagated for a number of steps (which varies betwen 2-5) for each sample, which requires the computational model to be evaluated. So, if **# Samples** is set to a number denoted as :math:`N_{samples}`, the total number of times that the computational model is evaluated is given by :math:`N_{eval} = \sum_{i=1}^{N_{stages}} N_{samples}*N_{steps}^{(i)}`. +1. **# Samples** defines the number of values to be sampled from the posterior probability distribution of the parameters of the computational model. This number is not the same as the number of times the computational model is evaluated. To sample from the posterior probability distribution of the inputs, the TMCMC algorithm relies on gradually changing the target distribution from the prior to the posterior in several stages. The number of stages is not known in advance. In every stage, the Markov chain is propagated for several steps (which vary between 2-5) for each sample, which requires the computational model to be evaluated. So, if **# Samples** is set to a number denoted as :math:`N_{samples}`, the total number of times that the computational model is evaluated is given by :math:`N_{eval} = \sum_{i=1}^{N_{stages}} N_{samples}*N_{steps}^{(i)}`. -2. **Seed** is an integer that specifies the seed value of the psuedo-random number generator. If the same Bayesian estimation problem is run multiple times without having the same seed, a different set of samples produced in each run. Setting the same seed as a previous TMCMC sampling run ensures that the the same result is reproduced if the TMCMC sampling is run again. +2. **Seed** is an integer that specifies the seed value of the pseudorandom number generator. If the same Bayesian estimation problem is run multiple times without having the same seed, a different set of samples is produced in each run. Setting the same seed as a previous TMCMC sampling run ensures that the same result is reproduced if the TMCMC sampling is run again. 3. **Calibration Data File** is the path to a text file that contains the data of the measured values of the quantities of interest. @@ -35,7 +37,7 @@ The required inputs to perform Bayesian calibration in quoFEM using the TMCMC al 1. Each row of the calibration data file contains data from one experiment. The individual entries in every row of this file can be separated by spaces, tabs, or commas. 2. The number of entries in each row must equal the sum of the length of all outputs defined in the **QoI** panel. - 3. The order of the entries in each row of the calibration data file must match the order in which the outputs are defined in the **QoI** panel, and must correspond to the output from the computational model in the ``results.out`` file. + 3. The order of the entries in each row of the calibration data file must match the order in which the outputs are defined in the **QoI** panel and must correspond to the output from the computational model in the ``results.out`` file. For example, if there are data from two experiments, and there are 2 response quantities, of length 2 and 1 respectively, then, there must be two rows of values in the calibration data file, the length of each row must be 3, the first two values in each row correspond to the first response quantity and the third value in each row corresponds to the second response quantity. @@ -47,12 +49,12 @@ Defining the log-likelihood function ==================================== .. warning:: - This feature is meant for advanced users, and users must exercise care if defining their own log-likelihood function. + This feature is meant for advanced users, and users must exercise care if defining their log-likelihood function. -In the **Log Likelihood Script** field, users can provide the path to a Python script which contains a function called ``log_likelihood`` that returns the log-likelihood value. +In the **Log Likelihood Script** field, users can provide the path to a Python script that contains a function called ``log_likelihood`` that returns the log-likelihood value. By allowing users to define a ``log_likelihood`` function in the **Log Likelihood Script**, the workflow provides users full control in defining the log-likelihood model they desire to use. -The ``log_likelihood`` function is called internally during the execution of the TMCMC algorithm, and this function must compute and return the log-likelihood value at a point in the parameter space. The function must take the arguments as shown below in signature of the `default log-likelihood script `_. Within this function, users can define their own log-likelihood function. +The ``log_likelihood`` function is called internally during the execution of the TMCMC algorithm, and this function must compute and return the log-likelihood value at a point in the parameter space. The function must take the arguments as shown below in the signature of the `default log-likelihood script `_. Within this function, users can define their log-likelihood function. .. literalinclude:: defaultLogLikeScript.py :linenos: @@ -64,7 +66,7 @@ Default error covariance structure ================================== The likelihood is a function of the difference between the predicted and the measured values of the response quantities of interest. These differences are also called **residuals** or **errors**. The likelihood function assumes a structure of the covariance matrix for these error terms. -By default, quoFEM assumes a block-diagonal error covariance structure. An example of the block-diagonal covariance structure is shown in :numref:`figDefaultCovarianceStructure`. In this figure, the number of experiments is denoted as :math:`N_{exp}`. The number of response quantities of interest is denoted as :math:`N_{q}`, and :math:`q_1, q_2, ..., q5` are the names of the quantities of interest in this example (these will be defined in the **QoI** panel when using quoFEM). Of these, :math:`q_1` and :math:`q_2` are scalar response quantities (i.e., they have a length of 1), while :math:`q_3`, :math:`q_4`, and :math:`q_5` are response quantities whose length > 1 (referred to as vector/field quantities). The length of each of the :math:`N_q` quantities of interest is denoted by :math:`l_i`. So, :math:`N`, the total number of calibration data terms, which is the same as the total number of terms in the ``results.out`` file output from the model, and is also equal to the total number of error/residual terms, is given by: +By default, quoFEM assumes a block-diagonal error covariance structure. An example of the block-diagonal covariance structure is shown in :numref:`figDefaultCovarianceStructure`. In this figure, the number of experiments is denoted as :math:`N_{exp}`. The number of response quantities of interest is denoted as :math:`N_{q}`, and :math:`q_1, q_2, ..., q5` are the names of the quantities of interest in this example (these will be defined in the **QoI** panel when using quoFEM). Of these, :math:`q_1` and :math:`q_2` are scalar response quantities (i.e., they have a length of 1), while :math:`q_3` ,:math:`q_4`, and :math:`q_5` are response quantities whose length > 1 (referred to as vector/field quantities). The length of each of the :math:`N_q` quantities of interest is denoted by :math:`l_i`. So, :math:`N`, the total number of calibration data terms, which is the same as the total number of terms in the ``results.out`` file output from the model, and is also equal to the total number of error/residual terms, is given by: .. math:: N = N_{exp} \times \sum_{i=1}^{N_q} l_i @@ -75,7 +77,7 @@ Note that quoFEM requires that the calibration data be provided in a text file s The error-covariance matrix is a block-diagonal square matrix of size :math:`N \times N`. There are :math:`N_{exp} \times N_q` blocks on the diagonal. For each of these blocks, if it corresponds to a scalar response quantity, then a scalar variance value is used by default else, a scalar matrix (i.e., an identity matrix of size :math:`l_i \times l_i` multiplied by a scalar value) is used by default. .. note:: - For numerical convenience, during execution, a transformation is applied to the calibration data and model prediction corresponding to each response quantity. The calibration data and model prediction for each response quantity are first shifted (a scalar value is added to the data and prediction) and then scaled (the data and prediction is divided by a positive scalar value). + For numerical convenience, during execution, a transformation is applied to the calibration data and model prediction corresponding to each response quantity. The calibration data and model prediction for each response quantity are first shifted (a scalar value is added to the data and prediction) and then scaled (the data and prediction are divided by a positive scalar value). Currently, the shift factors are set to 0.0 for all response quantities by default. The scale factors used are the absolute maximum of the data for each response variable. If the absolute maximum of the data for any response variable is 0.0, then the scale factor is set to 1.0, and the shift factor is set to 1.0. @@ -99,11 +101,11 @@ The block-diagonal structure implies that there is no correlation among the erro User-defined covariance structure ================================= -quoFEM provides users the option to supply error covariance matrices per response quantity per experiment, i.e., users can define each block of the diagonal error-covariance structure which will be utilized in the calculation of the log-likelihood. To do so, users must provide a separate text file for each block containing the values for that block. The names of these text files are expected to follow the convention of "{QoIName}.{ExpNum}.sigma". Examples of the names of the files that contain values which will be used instead of the default values are shown for each block in :numref:`figUserDefinedCovarianceStructure`. +quoFEM provides users the option to supply error covariance matrices per response quantity per experiment, i.e., users can define each block of the diagonal error-covariance structure which will be utilized in the calculation of the log-likelihood. To do so, users must provide a separate text file for each block containing the values for that block. The names of these text files are expected to follow the convention of "{QoIName}.{ExpNum}.sigma". Examples of the names of the files that contain values that will be used instead of the default values are shown for each block in :numref:`figUserDefinedCovarianceStructure`. Within these files, the entries can be separated by either commas, spaces, or tabs. Users can provide a scalar variance value for scalar response quantities, which will be used instead of the default value. For vector/field response quantities, users can supply in the files either -#. a scalar value, in which case the block corresponding to this response variable and this experiment will be an identity matrix of size :math:`l_i \times l_i` multipled by this scalar value, or +#. a scalar value, in which case the block corresponding to this response variable and this experiment will be an identity matrix of size :math:`l_i \times l_i` multiplied by this scalar value, or #. a row/column of :math:`l_i` values, in which case, these will be treated as the elements of the diagonal of the block, or #. a matrix of values of size :math:`l_i \times l_i`, which implies that the error/residual terms corresponding to this block are correlated. @@ -120,7 +122,7 @@ Within these files, the entries can be separated by either commas, spaces, or ta Additional calibration parameters ================================= -In Bayesian calibration problems, the value of the variance/covariances of the error/residual terms is also typically unknown. The residuals include not only measurement errors, but also errors caused due to the inability of the model to prefectly represent the behavior being modeled. Hence, by default, quoFEM also calibrates the values of multipliers on the block-diagonal terms in the error covariance matrix. Therefore, the total number of parameters being calibrated is given by the sum of the number of parameters of the computational model and the number of response quantities of interest. +In Bayesian calibration problems, the value of the variance/covariances of the error/residual terms is also typically unknown. The residuals include not only measurement errors but also errors caused due to the inability of the model to perfectly represent the behavior being modeled. Hence, by default, quoFEM also calibrates the values of multipliers on the block-diagonal terms in the error covariance matrix. Therefore, the total number of parameters being calibrated is given by the sum of the number of parameters of the computational model and the number of response quantities of interest. In quoFEM, the parameters of the model are defined in the **RV** panel, and the response quantities are specified in the **QoI** panel. Hence the total number of parameters being calibrated is equal to the sum of the number of RVs and the number of QoIs. There is one multiplier per response quantity, irrespective of it being either a scalar or a vector/field quantity. Also, the same multiplier per response quantity is used on the blocks of the error covariance matrix across experiments. diff --git a/docs/_sources/common/user_manual/usage/desktop/UQ.rst.txt b/docs/_sources/common/user_manual/usage/desktop/UQ.rst.txt index b1282553..e61892c8 100644 --- a/docs/_sources/common/user_manual/usage/desktop/UQ.rst.txt +++ b/docs/_sources/common/user_manual/usage/desktop/UQ.rst.txt @@ -213,17 +213,19 @@ The following categories are available: UCSD-UQ engine and category selection. - This module currently offers support for Bayesian estimation using the Transitional Markov chain Monte Carlo (TMCMC) algorithm: + This module currently offers support for Bayesian estimation of the parameters of a traditional (non-hierarchical) model using the Transitional Markov chain Monte Carlo (TMCMC) algorithm and of a hierarchical model using an adaptive Metropolis-within-Gibbs sampling algorithm. .. toctree-filt:: :maxdepth: 1 UCSD_UQ_TMCMC + UCSD_UQ_Hierarchical Custom UQ Engine ---------------- The **CustomUQ** option enables users to switch out the UQ engine in the |appName| workflow such that different methods and tools can be applied within the SimCenter framework with minimal effort on the part of the user. The CustomUQ option can be accessed as shown below: + .. _figCustomUQ: .. figure:: figures/customUQ.png diff --git a/docs/_sources/common/user_manual/usage/desktop/earthquake/usageS3hark.rst.txt b/docs/_sources/common/user_manual/usage/desktop/earthquake/usageS3hark.rst.txt index 225ae570..20feac6b 100644 --- a/docs/_sources/common/user_manual/usage/desktop/earthquake/usageS3hark.rst.txt +++ b/docs/_sources/common/user_manual/usage/desktop/earthquake/usageS3hark.rst.txt @@ -378,7 +378,7 @@ in-situ data are available. This calibration process can become cumbersome when a parametric study was conducted to establish a correlation among :math:`D_R`, :math:`G_o`, :math:`h_{po}`, and CRR, i.e., :math:`CRR = f(D_R, G_o, h_{po})`. The function, :math:`f`, should be solvable for :math:`h_{po}` when the other variables are known and eventually yield :math:`h_{po} = g(CRR, D_R, G_o)`. This correlation is intended to provide a preliminary estimation of :math:`h_{po}` and simplify the iterative calibration process under selected :math:`D_R`, :math:`G_o`, and CRR, especially when both SPT and :math:`V_s` data are available and the user wants to make :math:`G_o` independent to :math:`D_R`. For this purpose, the Dakota platform, run through the uqFEM (now quoFEM) tool was used in this parametric study. -uqFEM was modified to include UW MixedDriver tool. All the simulations were performed on the Texas Advanced Computing Center (http://www.tacc.utexas.edu) Stampede2 supercomputer made available through DesignSafe-ci. +uqFEM was modified to include UW MixedDriver tool. All the simulations were performed on the Texas Advanced Computing Center (http://www.tacc.utexas.edu) Frontera supercomputer made available through DesignSafe-ci. Using this tool, :math:`D_R`, :math:`G_o`, and :math:`h_{po}` were varied while all the secondary parameters were kept of their default values (predefined by primary parameters and initial stresses). The Latin Hypercube Sampling (LHS) method was used to generate near-random variables. Each of these three variables was assigned an independent uniform distribution between minimum and maximum values. The range of these variables was chosen to cover a reasonable range of scenarios and can be diff --git a/docs/_sources/common/user_manual/usage/desktop/usage.rst.txt b/docs/_sources/common/user_manual/usage/desktop/usage.rst.txt index 88b0315e..0d0e86d1 100644 --- a/docs/_sources/common/user_manual/usage/desktop/usage.rst.txt +++ b/docs/_sources/common/user_manual/usage/desktop/usage.rst.txt @@ -204,7 +204,7 @@ The main window of the UI is made up from the following areas: 6. **Main Menu** - | The main menu, which contains the typical pull down options found in almost all desktop applications, contains three additional options **Examples**, **Tools** and **GIS Map**. The **Examples** pull down provides a way to download and then load the examples described in this manual. The **Tools** pull down provide a number of options for generating inputs and additional attributed for the various input widgets of the tool, e.g. a user can use the Ground motion selection tool to create a set of ground motions using OpenSHA, PEER, etc., which can be subsequently used in the **HAZ** part of the workflow. The **GIS Map** pulldown provides access to the standard **QGIS** options, e.g. adding layers, maps, plugins. + | The main menu, which contains the typical pull down options found in almost all desktop applications, contains three additional options **Examples**, **Tools** and **GIS Map**. The **Examples** pull down provides a way to download and then load the examples described in this manual. The **Tools** (See :ref:`r2d-tools`) pull down provide a number of options for generating inputs and additional attributed for the various input widgets of the tool, e.g. a user can use the Ground motion selection tool to create a set of ground motions using OpenSHA, PEER, etc., which can be subsequently used in the **HAZ** part of the workflow. The **GIS Map** pulldown provides access to the standard **QGIS** options, e.g. adding layers, maps, plugins. .. include:: R2DTool/tools.rst @@ -213,7 +213,6 @@ The main window of the UI is made up from the following areas: .. only:: quoFEM_app - **Overview of User Interface** Recorded in tool training, 2022 (From 21:14 to 26:58) diff --git a/docs/_sources/common/user_manual/user_inputs_documentation/User_Input_Documentation_Tables.rst.txt b/docs/_sources/common/user_manual/user_inputs_documentation/User_Input_Documentation_Tables.rst.txt new file mode 100644 index 00000000..09075273 --- /dev/null +++ b/docs/_sources/common/user_manual/user_inputs_documentation/User_Input_Documentation_Tables.rst.txt @@ -0,0 +1,64 @@ +User Inputs +=========== + +The following pages define the inputs to be provided by users in the graphical interface of SimCenter applications + +.. toctree:: + :maxdepth: 2 + :caption: Definition of User Inputs + + User_Inputs_Documentation_RST_Files/ConcreteBuildingModel.rst + User_Inputs_Documentation_RST_Files/CustomPy.rst + User_Inputs_Documentation_RST_Files/CustomPySimulation.rst + User_Inputs_Documentation_RST_Files/DakotaInputBayesianCalibration.rst + User_Inputs_Documentation_RST_Files/DakotaInputCalibration.rst + User_Inputs_Documentation_RST_Files/DakotaInputOptimization.rst + User_Inputs_Documentation_RST_Files/DakotaInputReliability.rst + User_Inputs_Documentation_RST_Files/DakotaInputSampling.rst + User_Inputs_Documentation_RST_Files/DakotaInputSensitivity.rst + User_Inputs_Documentation_RST_Files/EDP.rst + User_Inputs_Documentation_RST_Files/EDP_EarthquakeSelection.rst + User_Inputs_Documentation_RST_Files/ExampleWidget.rst + User_Inputs_Documentation_RST_Files/ExistingSimCenterEvents.rst + User_Inputs_Documentation_RST_Files/GaussianProcessInputWidget.rst + User_Inputs_Documentation_RST_Files/GlobalReliabilityWidget.rst + User_Inputs_Documentation_RST_Files/ImportanceSamplingInputWidget.rst + User_Inputs_Documentation_RST_Files/ImportSamplesWidget.rst + User_Inputs_Documentation_RST_Files/InputWidgetBIM.rst + User_Inputs_Documentation_RST_Files/InputWidgetExistingEvent.rst + User_Inputs_Documentation_RST_Files/InputWidgetOpenSeesAnalysis.rst + User_Inputs_Documentation_RST_Files/LatinHypercubeInputWidget.rst + User_Inputs_Documentation_RST_Files/LocalReliabilityWidget.rst + User_Inputs_Documentation_RST_Files/MDOF_BuildingModel.rst + User_Inputs_Documentation_RST_Files/MDOF_LU.rst + User_Inputs_Documentation_RST_Files/MonteCarloInputSimWidget.rst + User_Inputs_Documentation_RST_Files/MonteCarloInputWidget.rst + User_Inputs_Documentation_RST_Files/MultiFidelityMonteCarlo.rst + User_Inputs_Documentation_RST_Files/MultiFidelitySimWidget.rst + User_Inputs_Documentation_RST_Files/NoneEngine.rst + User_Inputs_Documentation_RST_Files/OpenSeesBuildingModel.rst + User_Inputs_Documentation_RST_Files/PCEInputWidget.rst + User_Inputs_Documentation_RST_Files/PLoMInputWidget.rst + User_Inputs_Documentation_RST_Files/PLoMSimuWidget.rst + User_Inputs_Documentation_RST_Files/SimCenterIntensityMeasureCombo.rst + User_Inputs_Documentation_RST_Files/SimCenterIntensityMeasureWidget.rst + User_Inputs_Documentation_RST_Files/SimCenterUnitsCombo.rst + User_Inputs_Documentation_RST_Files/SimCenterUQInputPLoM.rst + User_Inputs_Documentation_RST_Files/SimCenterUQInputSampling.rst + User_Inputs_Documentation_RST_Files/SimCenterUQInputSensitivity.rst + User_Inputs_Documentation_RST_Files/SimCenterUQInputSurrogate.rst + User_Inputs_Documentation_RST_Files/StandardEarthquakeEDP.rst + User_Inputs_Documentation_RST_Files/StandardEDP.rst + User_Inputs_Documentation_RST_Files/SteelBuildingModel.rst + User_Inputs_Documentation_RST_Files/SurrogateDoEInputWidget.rst + User_Inputs_Documentation_RST_Files/SurrogateEDP.rst + User_Inputs_Documentation_RST_Files/SurrogateGP.rst + User_Inputs_Documentation_RST_Files/SurrogateMFInputWidget.rst + User_Inputs_Documentation_RST_Files/SurrogateNoDoEInputWidget.rst + User_Inputs_Documentation_RST_Files/SurrogateSimulation.rst + User_Inputs_Documentation_RST_Files/UCSD_InputBayesianCalibration.rst + User_Inputs_Documentation_RST_Files/UCSD_InputHierarchicalBayesian.rst + User_Inputs_Documentation_RST_Files/UCSD_InputTMCMC.rst + User_Inputs_Documentation_RST_Files/UQpyStretch.rst + User_Inputs_Documentation_RST_Files/UQpySubsetSimulation.rst + User_Inputs_Documentation_RST_Files/UserDefinedEDP.rst \ No newline at end of file diff --git a/docs/_sources/common/user_manual/user_inputs_documentation/User_Inputs_Documentation_RST_Files/ConcreteBuildingModel.rst.txt b/docs/_sources/common/user_manual/user_inputs_documentation/User_Inputs_Documentation_RST_Files/ConcreteBuildingModel.rst.txt new file mode 100644 index 00000000..232f88c4 --- /dev/null +++ b/docs/_sources/common/user_manual/user_inputs_documentation/User_Inputs_Documentation_RST_Files/ConcreteBuildingModel.rst.txt @@ -0,0 +1,9 @@ + +.. _ConcreteBuildingModel User Inputs: + +ConcreteBuildingModel +===================== + + + + diff --git a/docs/_sources/common/user_manual/user_inputs_documentation/User_Inputs_Documentation_RST_Files/CustomPy.rst.txt b/docs/_sources/common/user_manual/user_inputs_documentation/User_Inputs_Documentation_RST_Files/CustomPy.rst.txt new file mode 100644 index 00000000..833ceb5c --- /dev/null +++ b/docs/_sources/common/user_manual/user_inputs_documentation/User_Inputs_Documentation_RST_Files/CustomPy.rst.txt @@ -0,0 +1,9 @@ + +.. _CustomPy User Inputs: + +CustomPy +======== + + + + diff --git a/docs/_sources/common/user_manual/user_inputs_documentation/User_Inputs_Documentation_RST_Files/CustomPySimulation.rst.txt b/docs/_sources/common/user_manual/user_inputs_documentation/User_Inputs_Documentation_RST_Files/CustomPySimulation.rst.txt new file mode 100644 index 00000000..873adcbb --- /dev/null +++ b/docs/_sources/common/user_manual/user_inputs_documentation/User_Inputs_Documentation_RST_Files/CustomPySimulation.rst.txt @@ -0,0 +1,9 @@ + +.. _CustomPySimulation User Inputs: + +CustomPySimulation +================== + + + + diff --git a/docs/_sources/common/user_manual/user_inputs_documentation/User_Inputs_Documentation_RST_Files/DakotaInputBayesianCalibration.rst.txt b/docs/_sources/common/user_manual/user_inputs_documentation/User_Inputs_Documentation_RST_Files/DakotaInputBayesianCalibration.rst.txt new file mode 100644 index 00000000..aabca31c --- /dev/null +++ b/docs/_sources/common/user_manual/user_inputs_documentation/User_Inputs_Documentation_RST_Files/DakotaInputBayesianCalibration.rst.txt @@ -0,0 +1,9 @@ + +.. _DakotaInputBayesianCalibration User Inputs: + +DakotaInputBayesianCalibration +============================== + + + + diff --git a/docs/_sources/common/user_manual/user_inputs_documentation/User_Inputs_Documentation_RST_Files/DakotaInputCalibration.rst.txt b/docs/_sources/common/user_manual/user_inputs_documentation/User_Inputs_Documentation_RST_Files/DakotaInputCalibration.rst.txt new file mode 100644 index 00000000..7c0c9052 --- /dev/null +++ b/docs/_sources/common/user_manual/user_inputs_documentation/User_Inputs_Documentation_RST_Files/DakotaInputCalibration.rst.txt @@ -0,0 +1,9 @@ + +.. _DakotaInputCalibration User Inputs: + +DakotaInputCalibration +====================== + + + + diff --git a/docs/_sources/common/user_manual/user_inputs_documentation/User_Inputs_Documentation_RST_Files/DakotaInputOptimization.rst.txt b/docs/_sources/common/user_manual/user_inputs_documentation/User_Inputs_Documentation_RST_Files/DakotaInputOptimization.rst.txt new file mode 100644 index 00000000..87bd0edf --- /dev/null +++ b/docs/_sources/common/user_manual/user_inputs_documentation/User_Inputs_Documentation_RST_Files/DakotaInputOptimization.rst.txt @@ -0,0 +1,9 @@ + +.. _DakotaInputOptimization User Inputs: + +DakotaInputOptimization +======================= + + + + diff --git a/docs/_sources/common/user_manual/user_inputs_documentation/User_Inputs_Documentation_RST_Files/DakotaInputReliability.rst.txt b/docs/_sources/common/user_manual/user_inputs_documentation/User_Inputs_Documentation_RST_Files/DakotaInputReliability.rst.txt new file mode 100644 index 00000000..8f9efdae --- /dev/null +++ b/docs/_sources/common/user_manual/user_inputs_documentation/User_Inputs_Documentation_RST_Files/DakotaInputReliability.rst.txt @@ -0,0 +1,9 @@ + +.. _DakotaInputReliability User Inputs: + +DakotaInputReliability +====================== + + + + diff --git a/docs/_sources/common/user_manual/user_inputs_documentation/User_Inputs_Documentation_RST_Files/DakotaInputSampling.rst.txt b/docs/_sources/common/user_manual/user_inputs_documentation/User_Inputs_Documentation_RST_Files/DakotaInputSampling.rst.txt new file mode 100644 index 00000000..853fafce --- /dev/null +++ b/docs/_sources/common/user_manual/user_inputs_documentation/User_Inputs_Documentation_RST_Files/DakotaInputSampling.rst.txt @@ -0,0 +1,9 @@ + +.. _DakotaInputSampling User Inputs: + +DakotaInputSampling +=================== + + + + diff --git a/docs/_sources/common/user_manual/user_inputs_documentation/User_Inputs_Documentation_RST_Files/DakotaInputSensitivity.rst.txt b/docs/_sources/common/user_manual/user_inputs_documentation/User_Inputs_Documentation_RST_Files/DakotaInputSensitivity.rst.txt new file mode 100644 index 00000000..2a0bbd4f --- /dev/null +++ b/docs/_sources/common/user_manual/user_inputs_documentation/User_Inputs_Documentation_RST_Files/DakotaInputSensitivity.rst.txt @@ -0,0 +1,9 @@ + +.. _DakotaInputSensitivity User Inputs: + +DakotaInputSensitivity +====================== + + + + diff --git a/docs/_sources/common/user_manual/user_inputs_documentation/User_Inputs_Documentation_RST_Files/EDP.rst.txt b/docs/_sources/common/user_manual/user_inputs_documentation/User_Inputs_Documentation_RST_Files/EDP.rst.txt new file mode 100644 index 00000000..9da608b0 --- /dev/null +++ b/docs/_sources/common/user_manual/user_inputs_documentation/User_Inputs_Documentation_RST_Files/EDP.rst.txt @@ -0,0 +1,9 @@ + +.. _EDP User Inputs: + +EDP +=== + + + + diff --git a/docs/_sources/common/user_manual/user_inputs_documentation/User_Inputs_Documentation_RST_Files/EDP_EarthquakeSelection.rst.txt b/docs/_sources/common/user_manual/user_inputs_documentation/User_Inputs_Documentation_RST_Files/EDP_EarthquakeSelection.rst.txt new file mode 100644 index 00000000..cff2fd85 --- /dev/null +++ b/docs/_sources/common/user_manual/user_inputs_documentation/User_Inputs_Documentation_RST_Files/EDP_EarthquakeSelection.rst.txt @@ -0,0 +1,9 @@ + +.. _EDP_EarthquakeSelection User Inputs: + +EDP_EarthquakeSelection +======================= + + + + diff --git a/docs/_sources/common/user_manual/user_inputs_documentation/User_Inputs_Documentation_RST_Files/ExampleWidget.rst.txt b/docs/_sources/common/user_manual/user_inputs_documentation/User_Inputs_Documentation_RST_Files/ExampleWidget.rst.txt new file mode 100644 index 00000000..cc4a602f --- /dev/null +++ b/docs/_sources/common/user_manual/user_inputs_documentation/User_Inputs_Documentation_RST_Files/ExampleWidget.rst.txt @@ -0,0 +1,86 @@ + +.. _ExampleWidget User Inputs: + +ExampleWidget +============= + + +.. _ExampleWidget Compound Widget: + +Compound Widget + Follow the link for a description of the inputs to Compound Widget + + Key in JSON file: compound_widget + + .. seealso:: + + :ref:`Compound Widget ` + User inputs for Compound Widget + + +.. _ExampleWidget Sample Size: + +Sample Size + Number of samples from the posterior probability distribution + + Default: 2000 + + Key in JSON file: sample_size + + +.. _ExampleWidget Seed: + +Seed + State of pseudo-random number generator for reproducibility + + Key in JSON file: seed + + .. seealso:: + + :ref:`seed ` + Compare with this parameter too + + +.. _ExampleWidget Calibration Data File: + +Calibration Data File + Full path to the file containing the calibration data + + Key in JSON file: calibration_data_file + + +.. _ExampleWidget Log Likelihood Script: + +Log Likelihood Script + Full path to the file containing the log-likelihood function + + Default: probability density of multivariate normal with independent components + + Key in JSON file: log_likelihood_script + + .. seealso:: + + :ref:`log_likelihood_script ` + This is also relevant to this parameter and adds some context + + +.. _ExampleWidget Dummy Variable: + +Dummy Variable + This is a dummy variable + + Default: check_default + + Key in JSON file: dummy + + +.. seealso:: + + `Defining the log-likelihood function `_ + Can link to external webpages too + + `Calibration data file `_ + Look at the requirements of how to define the calibration data file + + + diff --git a/docs/_sources/common/user_manual/user_inputs_documentation/User_Inputs_Documentation_RST_Files/ExistingSimCenterEvents.rst.txt b/docs/_sources/common/user_manual/user_inputs_documentation/User_Inputs_Documentation_RST_Files/ExistingSimCenterEvents.rst.txt new file mode 100644 index 00000000..2b4a33c0 --- /dev/null +++ b/docs/_sources/common/user_manual/user_inputs_documentation/User_Inputs_Documentation_RST_Files/ExistingSimCenterEvents.rst.txt @@ -0,0 +1,9 @@ + +.. _ExistingSimCenterEvents User Inputs: + +ExistingSimCenterEvents +======================= + + + + diff --git a/docs/_sources/common/user_manual/user_inputs_documentation/User_Inputs_Documentation_RST_Files/GaussianProcessInputWidget.rst.txt b/docs/_sources/common/user_manual/user_inputs_documentation/User_Inputs_Documentation_RST_Files/GaussianProcessInputWidget.rst.txt new file mode 100644 index 00000000..2d51e32b --- /dev/null +++ b/docs/_sources/common/user_manual/user_inputs_documentation/User_Inputs_Documentation_RST_Files/GaussianProcessInputWidget.rst.txt @@ -0,0 +1,9 @@ + +.. _GaussianProcessInputWidget User Inputs: + +GaussianProcessInputWidget +========================== + + + + diff --git a/docs/_sources/common/user_manual/user_inputs_documentation/User_Inputs_Documentation_RST_Files/GlobalReliabilityWidget.rst.txt b/docs/_sources/common/user_manual/user_inputs_documentation/User_Inputs_Documentation_RST_Files/GlobalReliabilityWidget.rst.txt new file mode 100644 index 00000000..9576ae4d --- /dev/null +++ b/docs/_sources/common/user_manual/user_inputs_documentation/User_Inputs_Documentation_RST_Files/GlobalReliabilityWidget.rst.txt @@ -0,0 +1,9 @@ + +.. _GlobalReliabilityWidget User Inputs: + +GlobalReliabilityWidget +======================= + + + + diff --git a/docs/_sources/common/user_manual/user_inputs_documentation/User_Inputs_Documentation_RST_Files/ImportSamplesWidget.rst.txt b/docs/_sources/common/user_manual/user_inputs_documentation/User_Inputs_Documentation_RST_Files/ImportSamplesWidget.rst.txt new file mode 100644 index 00000000..f8149270 --- /dev/null +++ b/docs/_sources/common/user_manual/user_inputs_documentation/User_Inputs_Documentation_RST_Files/ImportSamplesWidget.rst.txt @@ -0,0 +1,9 @@ + +.. _ImportSamplesWidget User Inputs: + +ImportSamplesWidget +=================== + + + + diff --git a/docs/_sources/common/user_manual/user_inputs_documentation/User_Inputs_Documentation_RST_Files/ImportanceSamplingInputWidget.rst.txt b/docs/_sources/common/user_manual/user_inputs_documentation/User_Inputs_Documentation_RST_Files/ImportanceSamplingInputWidget.rst.txt new file mode 100644 index 00000000..4f7749ae --- /dev/null +++ b/docs/_sources/common/user_manual/user_inputs_documentation/User_Inputs_Documentation_RST_Files/ImportanceSamplingInputWidget.rst.txt @@ -0,0 +1,9 @@ + +.. _ImportanceSamplingInputWidget User Inputs: + +ImportanceSamplingInputWidget +============================= + + + + diff --git a/docs/_sources/common/user_manual/user_inputs_documentation/User_Inputs_Documentation_RST_Files/InputWidgetBIM.rst.txt b/docs/_sources/common/user_manual/user_inputs_documentation/User_Inputs_Documentation_RST_Files/InputWidgetBIM.rst.txt new file mode 100644 index 00000000..984935c4 --- /dev/null +++ b/docs/_sources/common/user_manual/user_inputs_documentation/User_Inputs_Documentation_RST_Files/InputWidgetBIM.rst.txt @@ -0,0 +1,9 @@ + +.. _InputWidgetBIM User Inputs: + +InputWidgetBIM +============== + + + + diff --git a/docs/_sources/common/user_manual/user_inputs_documentation/User_Inputs_Documentation_RST_Files/InputWidgetExistingEvent.rst.txt b/docs/_sources/common/user_manual/user_inputs_documentation/User_Inputs_Documentation_RST_Files/InputWidgetExistingEvent.rst.txt new file mode 100644 index 00000000..d112027a --- /dev/null +++ b/docs/_sources/common/user_manual/user_inputs_documentation/User_Inputs_Documentation_RST_Files/InputWidgetExistingEvent.rst.txt @@ -0,0 +1,9 @@ + +.. _InputWidgetExistingEvent User Inputs: + +InputWidgetExistingEvent +======================== + + + + diff --git a/docs/_sources/common/user_manual/user_inputs_documentation/User_Inputs_Documentation_RST_Files/InputWidgetOpenSeesAnalysis.rst.txt b/docs/_sources/common/user_manual/user_inputs_documentation/User_Inputs_Documentation_RST_Files/InputWidgetOpenSeesAnalysis.rst.txt new file mode 100644 index 00000000..a19ba916 --- /dev/null +++ b/docs/_sources/common/user_manual/user_inputs_documentation/User_Inputs_Documentation_RST_Files/InputWidgetOpenSeesAnalysis.rst.txt @@ -0,0 +1,9 @@ + +.. _InputWidgetOpenSeesAnalysis User Inputs: + +InputWidgetOpenSeesAnalysis +=========================== + + + + diff --git a/docs/_sources/common/user_manual/user_inputs_documentation/User_Inputs_Documentation_RST_Files/LatinHypercubeInputWidget.rst.txt b/docs/_sources/common/user_manual/user_inputs_documentation/User_Inputs_Documentation_RST_Files/LatinHypercubeInputWidget.rst.txt new file mode 100644 index 00000000..0668a03a --- /dev/null +++ b/docs/_sources/common/user_manual/user_inputs_documentation/User_Inputs_Documentation_RST_Files/LatinHypercubeInputWidget.rst.txt @@ -0,0 +1,9 @@ + +.. _LatinHypercubeInputWidget User Inputs: + +LatinHypercubeInputWidget +========================= + + + + diff --git a/docs/_sources/common/user_manual/user_inputs_documentation/User_Inputs_Documentation_RST_Files/LocalReliabilityWidget.rst.txt b/docs/_sources/common/user_manual/user_inputs_documentation/User_Inputs_Documentation_RST_Files/LocalReliabilityWidget.rst.txt new file mode 100644 index 00000000..6a05c4ad --- /dev/null +++ b/docs/_sources/common/user_manual/user_inputs_documentation/User_Inputs_Documentation_RST_Files/LocalReliabilityWidget.rst.txt @@ -0,0 +1,9 @@ + +.. _LocalReliabilityWidget User Inputs: + +LocalReliabilityWidget +====================== + + + + diff --git a/docs/_sources/common/user_manual/user_inputs_documentation/User_Inputs_Documentation_RST_Files/MDOF_BuildingModel.rst.txt b/docs/_sources/common/user_manual/user_inputs_documentation/User_Inputs_Documentation_RST_Files/MDOF_BuildingModel.rst.txt new file mode 100644 index 00000000..ce5da8cc --- /dev/null +++ b/docs/_sources/common/user_manual/user_inputs_documentation/User_Inputs_Documentation_RST_Files/MDOF_BuildingModel.rst.txt @@ -0,0 +1,9 @@ + +.. _MDOF_BuildingModel User Inputs: + +MDOF_BuildingModel +================== + + + + diff --git a/docs/_sources/common/user_manual/user_inputs_documentation/User_Inputs_Documentation_RST_Files/MDOF_LU.rst.txt b/docs/_sources/common/user_manual/user_inputs_documentation/User_Inputs_Documentation_RST_Files/MDOF_LU.rst.txt new file mode 100644 index 00000000..0818c561 --- /dev/null +++ b/docs/_sources/common/user_manual/user_inputs_documentation/User_Inputs_Documentation_RST_Files/MDOF_LU.rst.txt @@ -0,0 +1,9 @@ + +.. _MDOF_LU User Inputs: + +MDOF_LU +======= + + + + diff --git a/docs/_sources/common/user_manual/user_inputs_documentation/User_Inputs_Documentation_RST_Files/MonteCarloInputSimWidget.rst.txt b/docs/_sources/common/user_manual/user_inputs_documentation/User_Inputs_Documentation_RST_Files/MonteCarloInputSimWidget.rst.txt new file mode 100644 index 00000000..1289966a --- /dev/null +++ b/docs/_sources/common/user_manual/user_inputs_documentation/User_Inputs_Documentation_RST_Files/MonteCarloInputSimWidget.rst.txt @@ -0,0 +1,9 @@ + +.. _MonteCarloInputSimWidget User Inputs: + +MonteCarloInputSimWidget +======================== + + + + diff --git a/docs/_sources/common/user_manual/user_inputs_documentation/User_Inputs_Documentation_RST_Files/MonteCarloInputWidget.rst.txt b/docs/_sources/common/user_manual/user_inputs_documentation/User_Inputs_Documentation_RST_Files/MonteCarloInputWidget.rst.txt new file mode 100644 index 00000000..5e3970d6 --- /dev/null +++ b/docs/_sources/common/user_manual/user_inputs_documentation/User_Inputs_Documentation_RST_Files/MonteCarloInputWidget.rst.txt @@ -0,0 +1,9 @@ + +.. _MonteCarloInputWidget User Inputs: + +MonteCarloInputWidget +===================== + + + + diff --git a/docs/_sources/common/user_manual/user_inputs_documentation/User_Inputs_Documentation_RST_Files/MultiFidelityMonteCarlo.rst.txt b/docs/_sources/common/user_manual/user_inputs_documentation/User_Inputs_Documentation_RST_Files/MultiFidelityMonteCarlo.rst.txt new file mode 100644 index 00000000..38fefc7b --- /dev/null +++ b/docs/_sources/common/user_manual/user_inputs_documentation/User_Inputs_Documentation_RST_Files/MultiFidelityMonteCarlo.rst.txt @@ -0,0 +1,9 @@ + +.. _MultiFidelityMonteCarlo User Inputs: + +MultiFidelityMonteCarlo +======================= + + + + diff --git a/docs/_sources/common/user_manual/user_inputs_documentation/User_Inputs_Documentation_RST_Files/MultiFidelitySimWidget.rst.txt b/docs/_sources/common/user_manual/user_inputs_documentation/User_Inputs_Documentation_RST_Files/MultiFidelitySimWidget.rst.txt new file mode 100644 index 00000000..ab674115 --- /dev/null +++ b/docs/_sources/common/user_manual/user_inputs_documentation/User_Inputs_Documentation_RST_Files/MultiFidelitySimWidget.rst.txt @@ -0,0 +1,9 @@ + +.. _MultiFidelitySimWidget User Inputs: + +MultiFidelitySimWidget +====================== + + + + diff --git a/docs/_sources/common/user_manual/user_inputs_documentation/User_Inputs_Documentation_RST_Files/NoneEngine.rst.txt b/docs/_sources/common/user_manual/user_inputs_documentation/User_Inputs_Documentation_RST_Files/NoneEngine.rst.txt new file mode 100644 index 00000000..243b9836 --- /dev/null +++ b/docs/_sources/common/user_manual/user_inputs_documentation/User_Inputs_Documentation_RST_Files/NoneEngine.rst.txt @@ -0,0 +1,9 @@ + +.. _NoneEngine User Inputs: + +NoneEngine +========== + + + + diff --git a/docs/_sources/common/user_manual/user_inputs_documentation/User_Inputs_Documentation_RST_Files/OpenSeesBuildingModel.rst.txt b/docs/_sources/common/user_manual/user_inputs_documentation/User_Inputs_Documentation_RST_Files/OpenSeesBuildingModel.rst.txt new file mode 100644 index 00000000..809188be --- /dev/null +++ b/docs/_sources/common/user_manual/user_inputs_documentation/User_Inputs_Documentation_RST_Files/OpenSeesBuildingModel.rst.txt @@ -0,0 +1,9 @@ + +.. _OpenSeesBuildingModel User Inputs: + +OpenSeesBuildingModel +===================== + + + + diff --git a/docs/_sources/common/user_manual/user_inputs_documentation/User_Inputs_Documentation_RST_Files/PCEInputWidget.rst.txt b/docs/_sources/common/user_manual/user_inputs_documentation/User_Inputs_Documentation_RST_Files/PCEInputWidget.rst.txt new file mode 100644 index 00000000..19c458ff --- /dev/null +++ b/docs/_sources/common/user_manual/user_inputs_documentation/User_Inputs_Documentation_RST_Files/PCEInputWidget.rst.txt @@ -0,0 +1,9 @@ + +.. _PCEInputWidget User Inputs: + +PCEInputWidget +============== + + + + diff --git a/docs/_sources/common/user_manual/user_inputs_documentation/User_Inputs_Documentation_RST_Files/PLoMInputWidget.rst.txt b/docs/_sources/common/user_manual/user_inputs_documentation/User_Inputs_Documentation_RST_Files/PLoMInputWidget.rst.txt new file mode 100644 index 00000000..017c9e97 --- /dev/null +++ b/docs/_sources/common/user_manual/user_inputs_documentation/User_Inputs_Documentation_RST_Files/PLoMInputWidget.rst.txt @@ -0,0 +1,9 @@ + +.. _PLoMInputWidget User Inputs: + +PLoMInputWidget +=============== + + + + diff --git a/docs/_sources/common/user_manual/user_inputs_documentation/User_Inputs_Documentation_RST_Files/PLoMSimuWidget.rst.txt b/docs/_sources/common/user_manual/user_inputs_documentation/User_Inputs_Documentation_RST_Files/PLoMSimuWidget.rst.txt new file mode 100644 index 00000000..778b1b1e --- /dev/null +++ b/docs/_sources/common/user_manual/user_inputs_documentation/User_Inputs_Documentation_RST_Files/PLoMSimuWidget.rst.txt @@ -0,0 +1,9 @@ + +.. _PLoMSimuWidget User Inputs: + +PLoMSimuWidget +============== + + + + diff --git a/docs/_sources/common/user_manual/user_inputs_documentation/User_Inputs_Documentation_RST_Files/SimCenterIntensityMeasureCombo.rst.txt b/docs/_sources/common/user_manual/user_inputs_documentation/User_Inputs_Documentation_RST_Files/SimCenterIntensityMeasureCombo.rst.txt new file mode 100644 index 00000000..ade58e7d --- /dev/null +++ b/docs/_sources/common/user_manual/user_inputs_documentation/User_Inputs_Documentation_RST_Files/SimCenterIntensityMeasureCombo.rst.txt @@ -0,0 +1,9 @@ + +.. _SimCenterIntensityMeasureCombo User Inputs: + +SimCenterIntensityMeasureCombo +============================== + + + + diff --git a/docs/_sources/common/user_manual/user_inputs_documentation/User_Inputs_Documentation_RST_Files/SimCenterIntensityMeasureWidget.rst.txt b/docs/_sources/common/user_manual/user_inputs_documentation/User_Inputs_Documentation_RST_Files/SimCenterIntensityMeasureWidget.rst.txt new file mode 100644 index 00000000..2723270c --- /dev/null +++ b/docs/_sources/common/user_manual/user_inputs_documentation/User_Inputs_Documentation_RST_Files/SimCenterIntensityMeasureWidget.rst.txt @@ -0,0 +1,9 @@ + +.. _SimCenterIntensityMeasureWidget User Inputs: + +SimCenterIntensityMeasureWidget +=============================== + + + + diff --git a/docs/_sources/common/user_manual/user_inputs_documentation/User_Inputs_Documentation_RST_Files/SimCenterUQInputPLoM.rst.txt b/docs/_sources/common/user_manual/user_inputs_documentation/User_Inputs_Documentation_RST_Files/SimCenterUQInputPLoM.rst.txt new file mode 100644 index 00000000..b4bf5980 --- /dev/null +++ b/docs/_sources/common/user_manual/user_inputs_documentation/User_Inputs_Documentation_RST_Files/SimCenterUQInputPLoM.rst.txt @@ -0,0 +1,9 @@ + +.. _SimCenterUQInputPLoM User Inputs: + +SimCenterUQInputPLoM +==================== + + + + diff --git a/docs/_sources/common/user_manual/user_inputs_documentation/User_Inputs_Documentation_RST_Files/SimCenterUQInputSampling.rst.txt b/docs/_sources/common/user_manual/user_inputs_documentation/User_Inputs_Documentation_RST_Files/SimCenterUQInputSampling.rst.txt new file mode 100644 index 00000000..aee7d731 --- /dev/null +++ b/docs/_sources/common/user_manual/user_inputs_documentation/User_Inputs_Documentation_RST_Files/SimCenterUQInputSampling.rst.txt @@ -0,0 +1,9 @@ + +.. _SimCenterUQInputSampling User Inputs: + +SimCenterUQInputSampling +======================== + + + + diff --git a/docs/_sources/common/user_manual/user_inputs_documentation/User_Inputs_Documentation_RST_Files/SimCenterUQInputSensitivity.rst.txt b/docs/_sources/common/user_manual/user_inputs_documentation/User_Inputs_Documentation_RST_Files/SimCenterUQInputSensitivity.rst.txt new file mode 100644 index 00000000..6816ff3e --- /dev/null +++ b/docs/_sources/common/user_manual/user_inputs_documentation/User_Inputs_Documentation_RST_Files/SimCenterUQInputSensitivity.rst.txt @@ -0,0 +1,9 @@ + +.. _SimCenterUQInputSensitivity User Inputs: + +SimCenterUQInputSensitivity +=========================== + + + + diff --git a/docs/_sources/common/user_manual/user_inputs_documentation/User_Inputs_Documentation_RST_Files/SimCenterUQInputSurrogate.rst.txt b/docs/_sources/common/user_manual/user_inputs_documentation/User_Inputs_Documentation_RST_Files/SimCenterUQInputSurrogate.rst.txt new file mode 100644 index 00000000..df66103f --- /dev/null +++ b/docs/_sources/common/user_manual/user_inputs_documentation/User_Inputs_Documentation_RST_Files/SimCenterUQInputSurrogate.rst.txt @@ -0,0 +1,18 @@ + +.. _SimCenterUQInputSurrogate User Inputs: + +SimCenterUQInputSurrogate +========================= + + +.. _SimCenterUQInputSurrogate Training Datase: + +Training Datase + + + Default: Sampling and Simulation + + Key in JSON file: method + + + diff --git a/docs/_sources/common/user_manual/user_inputs_documentation/User_Inputs_Documentation_RST_Files/SimCenterUnitsCombo.rst.txt b/docs/_sources/common/user_manual/user_inputs_documentation/User_Inputs_Documentation_RST_Files/SimCenterUnitsCombo.rst.txt new file mode 100644 index 00000000..6f0a66c9 --- /dev/null +++ b/docs/_sources/common/user_manual/user_inputs_documentation/User_Inputs_Documentation_RST_Files/SimCenterUnitsCombo.rst.txt @@ -0,0 +1,9 @@ + +.. _SimCenterUnitsCombo User Inputs: + +SimCenterUnitsCombo +=================== + + + + diff --git a/docs/_sources/common/user_manual/user_inputs_documentation/User_Inputs_Documentation_RST_Files/StandardEDP.rst.txt b/docs/_sources/common/user_manual/user_inputs_documentation/User_Inputs_Documentation_RST_Files/StandardEDP.rst.txt new file mode 100644 index 00000000..250428f9 --- /dev/null +++ b/docs/_sources/common/user_manual/user_inputs_documentation/User_Inputs_Documentation_RST_Files/StandardEDP.rst.txt @@ -0,0 +1,9 @@ + +.. _StandardEDP User Inputs: + +StandardEDP +=========== + + + + diff --git a/docs/_sources/common/user_manual/user_inputs_documentation/User_Inputs_Documentation_RST_Files/StandardEarthquakeEDP.rst.txt b/docs/_sources/common/user_manual/user_inputs_documentation/User_Inputs_Documentation_RST_Files/StandardEarthquakeEDP.rst.txt new file mode 100644 index 00000000..6a0dd05a --- /dev/null +++ b/docs/_sources/common/user_manual/user_inputs_documentation/User_Inputs_Documentation_RST_Files/StandardEarthquakeEDP.rst.txt @@ -0,0 +1,9 @@ + +.. _StandardEarthquakeEDP User Inputs: + +StandardEarthquakeEDP +===================== + + + + diff --git a/docs/_sources/common/user_manual/user_inputs_documentation/User_Inputs_Documentation_RST_Files/SteelBuildingModel.rst.txt b/docs/_sources/common/user_manual/user_inputs_documentation/User_Inputs_Documentation_RST_Files/SteelBuildingModel.rst.txt new file mode 100644 index 00000000..69ddbc18 --- /dev/null +++ b/docs/_sources/common/user_manual/user_inputs_documentation/User_Inputs_Documentation_RST_Files/SteelBuildingModel.rst.txt @@ -0,0 +1,9 @@ + +.. _SteelBuildingModel User Inputs: + +SteelBuildingModel +================== + + + + diff --git a/docs/_sources/common/user_manual/user_inputs_documentation/User_Inputs_Documentation_RST_Files/SurrogateDoEInputWidget.rst.txt b/docs/_sources/common/user_manual/user_inputs_documentation/User_Inputs_Documentation_RST_Files/SurrogateDoEInputWidget.rst.txt new file mode 100644 index 00000000..eb8ec9fd --- /dev/null +++ b/docs/_sources/common/user_manual/user_inputs_documentation/User_Inputs_Documentation_RST_Files/SurrogateDoEInputWidget.rst.txt @@ -0,0 +1,240 @@ + +.. _SurrogateDoEInputWidget User Inputs: + +SurrogateDoEInputWidget +======================= + + +.. _SurrogateDoEInputWidget Number of Samples: + +Number of Samples + When the number of simulation runs reaches the limit, the analysis will be terminated. + + Default: 150 + + Key in JSON file: samples + + +.. _SurrogateDoEInputWidget Max Computation Time (minutes): + +Max Computation Time (minutes) + When the tolerance limit of the computation time is reached, the analysis will be terminated. There will be a few minutes of error. + + Default: 60 + + Key in JSON file: timeLimit + + +.. _SurrogateDoEInputWidget Target Accuracy (normalized err): + +Target Accuracy (normalized err) + The target accuracy is defined in terms of normalized root-mean-squared error (NRMSE) estimated by leave-out-one cross-validation (LOOCV). + + Default: 0.02 + + Key in JSON file: accuracyLimit + + +.. _SurrogateDoEInputWidget Random Seed: + +Random Seed + Seed of the random number generator + + Default: a random integer + + Key in JSON file: seed + + +.. _SurrogateDoEInputWidget Parallel Execution: + +Parallel Execution + This engine implemented multiprocessing (local) or mpi4py (remote) python packages to run parallel execution. + + Default: checked + + Key in JSON file: parallelExecution + + +.. _SurrogateDoEInputWidget Advanced Options for Gaussian Process Model: + +Advanced Options for Gaussian Process Model + If unchecked, default values will be used + + Default: unchecked + + Key in JSON file: advancedOpt + + +.. _SurrogateDoEInputWidget Kernel Function: + +Kernel Function + Correlation function for Gaussian process regression. Matern5/2 function is the default, and Matern3/2, Radial Basis, and Exponential functions (exponent) are additionally supported. + + Default: Matern5/2 + + Key in JSON file: kernel + + +.. _SurrogateDoEInputWidget Add Linear Trend Function: + +Add Linear Trend Function + When increasing or decreasing trend is expected over the variables domain, a linear trend function may be introduced. + + Default: unchecked + + Key in JSON file: linear + + +.. _SurrogateDoEInputWidget Log-space Transform of QoI: + +Log-space Transform of QoI + When the user can guarantee that the response quantities are always greater than 0, user may want to introduce a surrogate model in log-transformed space of QoI. + + Default: unchecked + + Key in JSON file: logTransform + + +.. _SurrogateDoEInputWidget DoE Options: + +DoE Options + Design of Experiment method + + Default: none + + Key in JSON file: DoEmethod + + +.. _SurrogateDoEInputWidget Initial DoE #: + +Initial DoE # + The number of the initial DoE + + Default: 4 x #RV + + Key in JSON file: initialDoE + + +.. _SurrogateDoEInputWidget Nugget Variances: + +Nugget Variances + User may define nugget variances or bounds of the nugget variances if needed. + + Default: Optimize + + Key in JSON file: nuggetOpt + + +.. _SurrogateDoEInputWidget Nugget Values/Bounds: + +Nugget Values/Bounds + User-defined nugget variances or bounds + + Key in JSON file: nuggetString + + +.. _SurrogateDoEInputWidget # samples to be replicated (A): + +# samples to be replicated (A) + From the number of unique samples specified in the 'Number of Samples' field, decide how many of them will have replications. + + Default: 8 x #RV + + Key in JSON file: numSampToBeRepl + + +.. _SurrogateDoEInputWidget # replications per sample (B): + +# replications per sample (B) + Specify how many replications will be generated for the number of samples specified in A. + + Default: 10 + + Key in JSON file: numRepl + + +.. _SurrogateDoEInputWidget Start with Existing Dataset: + +Start with Existing Dataset + If unchecked, no existing dataset is utilized + + Default: checked + + Key in JSON file: existingDoE + + +.. _SurrogateDoEInputWidget Training Points (Input RV): + +Training Points (Input RV) + Full path to the file containing training points (samples of RV) + + Key in JSON file: inpFile + + .. seealso:: + + `Training Points File Format `_ + + +.. _SurrogateDoEInputWidget System Responses (Output QoI): + +System Responses (Output QoI) + Full path to the file containing system responses (samples of QoI) corresponding to the specified training points + + Key in JSON file: outFile + + .. seealso:: + + `System Responses File Format `_ + + +.. _SurrogateDoEInputWidget Advanced Options (Earthquake specific): + +Advanced Options (Earthquake specific) + If unchecked, default values will be used + + Default: unchecked + + Key in JSON file: none + + +.. _SurrogateDoEInputWidget Input postprocess: + +Input postprocess + Ground motion pre-processing for surrogate model training + + Default: Ground Motion Intensity + + Key in JSON file: none + + +.. _SurrogateDoEInputWidget IM: + +IM + The user can select intensity measures (IMs) that will be used as auxiliary inputs of the surrogate model, in addition to those specified in the RV tab. + + Default: Pseudo Spectral Velocity (in/sec) + + Key in JSON file: IntensityMeasure + + +.. _SurrogateDoEInputWidget Periods: + +Periods + Specify period(s) corresponding to IM + + Default: 0.5 or 0.1,1.0,1.5 + + Key in JSON file: Periods + + +.. _SurrogateDoEInputWidget Geometric mean: + +Geometric mean + If ground motions have more than one directional component, either each component's IM can be added as a separate surrogate input parameter, or they can be aggregated by using their geometric mean. + + Default: checked + + Key in JSON file: useGeoMean + + + diff --git a/docs/_sources/common/user_manual/user_inputs_documentation/User_Inputs_Documentation_RST_Files/SurrogateEDP.rst.txt b/docs/_sources/common/user_manual/user_inputs_documentation/User_Inputs_Documentation_RST_Files/SurrogateEDP.rst.txt new file mode 100644 index 00000000..d73cd8da --- /dev/null +++ b/docs/_sources/common/user_manual/user_inputs_documentation/User_Inputs_Documentation_RST_Files/SurrogateEDP.rst.txt @@ -0,0 +1,9 @@ + +.. _SurrogateEDP User Inputs: + +SurrogateEDP +============ + + + + diff --git a/docs/_sources/common/user_manual/user_inputs_documentation/User_Inputs_Documentation_RST_Files/SurrogateGP.rst.txt b/docs/_sources/common/user_manual/user_inputs_documentation/User_Inputs_Documentation_RST_Files/SurrogateGP.rst.txt new file mode 100644 index 00000000..b6e41108 --- /dev/null +++ b/docs/_sources/common/user_manual/user_inputs_documentation/User_Inputs_Documentation_RST_Files/SurrogateGP.rst.txt @@ -0,0 +1,9 @@ + +.. _SurrogateGP User Inputs: + +SurrogateGP +=========== + + + + diff --git a/docs/_sources/common/user_manual/user_inputs_documentation/User_Inputs_Documentation_RST_Files/SurrogateMFInputWidget.rst.txt b/docs/_sources/common/user_manual/user_inputs_documentation/User_Inputs_Documentation_RST_Files/SurrogateMFInputWidget.rst.txt new file mode 100644 index 00000000..883077d6 --- /dev/null +++ b/docs/_sources/common/user_manual/user_inputs_documentation/User_Inputs_Documentation_RST_Files/SurrogateMFInputWidget.rst.txt @@ -0,0 +1,9 @@ + +.. _SurrogateMFInputWidget User Inputs: + +SurrogateMFInputWidget +====================== + + + + diff --git a/docs/_sources/common/user_manual/user_inputs_documentation/User_Inputs_Documentation_RST_Files/SurrogateNoDoEInputWidget.rst.txt b/docs/_sources/common/user_manual/user_inputs_documentation/User_Inputs_Documentation_RST_Files/SurrogateNoDoEInputWidget.rst.txt new file mode 100644 index 00000000..e9060618 --- /dev/null +++ b/docs/_sources/common/user_manual/user_inputs_documentation/User_Inputs_Documentation_RST_Files/SurrogateNoDoEInputWidget.rst.txt @@ -0,0 +1,9 @@ + +.. _SurrogateNoDoEInputWidget User Inputs: + +SurrogateNoDoEInputWidget +========================= + + + + diff --git a/docs/_sources/common/user_manual/user_inputs_documentation/User_Inputs_Documentation_RST_Files/SurrogateSimulation.rst.txt b/docs/_sources/common/user_manual/user_inputs_documentation/User_Inputs_Documentation_RST_Files/SurrogateSimulation.rst.txt new file mode 100644 index 00000000..d459cc48 --- /dev/null +++ b/docs/_sources/common/user_manual/user_inputs_documentation/User_Inputs_Documentation_RST_Files/SurrogateSimulation.rst.txt @@ -0,0 +1,9 @@ + +.. _SurrogateSimulation User Inputs: + +SurrogateSimulation +=================== + + + + diff --git a/docs/_sources/common/user_manual/user_inputs_documentation/User_Inputs_Documentation_RST_Files/UCSD_InputBayesianCalibration.rst.txt b/docs/_sources/common/user_manual/user_inputs_documentation/User_Inputs_Documentation_RST_Files/UCSD_InputBayesianCalibration.rst.txt new file mode 100644 index 00000000..913d60fd --- /dev/null +++ b/docs/_sources/common/user_manual/user_inputs_documentation/User_Inputs_Documentation_RST_Files/UCSD_InputBayesianCalibration.rst.txt @@ -0,0 +1,9 @@ + +.. _UCSD_InputBayesianCalibration User Inputs: + +UCSD_InputBayesianCalibration +============================= + + + + diff --git a/docs/_sources/common/user_manual/user_inputs_documentation/User_Inputs_Documentation_RST_Files/UCSD_InputHierarchicalBayesian.rst.txt b/docs/_sources/common/user_manual/user_inputs_documentation/User_Inputs_Documentation_RST_Files/UCSD_InputHierarchicalBayesian.rst.txt new file mode 100644 index 00000000..876e565c --- /dev/null +++ b/docs/_sources/common/user_manual/user_inputs_documentation/User_Inputs_Documentation_RST_Files/UCSD_InputHierarchicalBayesian.rst.txt @@ -0,0 +1,9 @@ + +.. _UCSD_InputHierarchicalBayesian User Inputs: + +UCSD_InputHierarchicalBayesian +============================== + + + + diff --git a/docs/_sources/common/user_manual/user_inputs_documentation/User_Inputs_Documentation_RST_Files/UCSD_InputTMCMC.rst.txt b/docs/_sources/common/user_manual/user_inputs_documentation/User_Inputs_Documentation_RST_Files/UCSD_InputTMCMC.rst.txt new file mode 100644 index 00000000..9e1c53f6 --- /dev/null +++ b/docs/_sources/common/user_manual/user_inputs_documentation/User_Inputs_Documentation_RST_Files/UCSD_InputTMCMC.rst.txt @@ -0,0 +1,48 @@ + +.. _UCSD_InputTMCMC User Inputs: + +UCSD_InputTMCMC +=============== + + +.. _UCSD_InputTMCMC Sample Size: + +Sample Size + Number of samples from the posterior probability distribution + + Key in JSON file: sample_size + + +.. _UCSD_InputTMCMC Seed: + +Seed + State of pseudo-random number generator for reproducibility + + Key in JSON file: seed + + +.. _UCSD_InputTMCMC Calibration Data File: + +Calibration Data File + Full path to the file containing the calibration data + + Key in JSON file: calibration_data_file + + .. seealso:: + + `Calibration data file `_ + + +.. _UCSD_InputTMCMC Log Likelihood Script: + +Log Likelihood Script + Full path to the file containing the log-likelihood function + + Key in JSON file: log_likelihood_script + + .. seealso:: + + `Defining the log-likelihood function `_ + + + diff --git a/docs/_sources/common/user_manual/user_inputs_documentation/User_Inputs_Documentation_RST_Files/UQpyStretch.rst.txt b/docs/_sources/common/user_manual/user_inputs_documentation/User_Inputs_Documentation_RST_Files/UQpyStretch.rst.txt new file mode 100644 index 00000000..07803d49 --- /dev/null +++ b/docs/_sources/common/user_manual/user_inputs_documentation/User_Inputs_Documentation_RST_Files/UQpyStretch.rst.txt @@ -0,0 +1,68 @@ + +.. _UQpyStretch User Inputs: + +UQpyStretch +=========== + + +.. _UQpyStretch burn length: + +burn length + Burn length of the Markov Chain Monte Carlo algorithm + + Default: 0 + + Key in JSON file: burn_in + + +.. _UQpyStretch jump: + +jump + Jump parameter of the Markov Chain Monte Carlo sampling + + Default: 1 + + Key in JSON file: jump + + +.. _UQpyStretch method: + +method + String that defines the MCMC algorithm to be used + + Default: ModifiedMetropolisHastings + + Key in JSON file: method + + +.. _UQpyStretch # Chains: + +# Chains + Number of chains to be used in the MCMC sampling algorithm + + Default: 1 + + Key in JSON file: n_chains + + +.. _UQpyStretch # Dimension: + +# Dimension + Number of parameters to be sampled + + Default: 1 + + Key in JSON file: n_dimension + + +.. _UQpyStretch Scale: + +Scale + Parameter specific to the Stretch sampling aglorithm + + Default: 2 + + Key in JSON file: scale + + + diff --git a/docs/_sources/common/user_manual/user_inputs_documentation/User_Inputs_Documentation_RST_Files/UQpySubsetSimulation.rst.txt b/docs/_sources/common/user_manual/user_inputs_documentation/User_Inputs_Documentation_RST_Files/UQpySubsetSimulation.rst.txt new file mode 100644 index 00000000..4ec15b45 --- /dev/null +++ b/docs/_sources/common/user_manual/user_inputs_documentation/User_Inputs_Documentation_RST_Files/UQpySubsetSimulation.rst.txt @@ -0,0 +1,72 @@ + +.. _UQpySubsetSimulation User Inputs: + +UQpySubsetSimulation +==================== + + +.. _UQpySubsetSimulation method: + +method + Reliability analysis method to be used + + Default: SubsetSimulation + + Key in JSON file: method + + +.. _UQpySubsetSimulation Conditional Probabaility: + +Conditional Probabaility + Conditional probability for each conditional level + + Default: 0.1 + + Key in JSON file: conditionalProbability + + +.. _UQpySubsetSimulation Failure Threshold: + +Failure Threshold + Threshold over which it is assume that the simulated system fails + + Default: 0.001 + + Key in JSON file: failureThreshold + + +.. _UQpySubsetSimulation Max. Levels: + +Max. Levels + Maximum number of allowable conditional levels + + Default: 10 + + Key in JSON file: maxLevels + + +.. _UQpySubsetSimulation Initial samples: + +Initial samples + Initial samples to bootstrap the Subset simulation algorithm + + Default: 1000 + + Key in JSON file: initialSamples + + +.. _UQpySubsetSimulation Sampling Method: + +Sampling Method + Specifies the MCMC sampling agorithm to be used + + Default: MetropolisHastings + + Key in JSON file: samplingMethod + + .. seealso:: + + :ref:`MCMC Algorithm ` + + + diff --git a/docs/_sources/common/user_manual/user_inputs_documentation/User_Inputs_Documentation_RST_Files/UserDefinedEDP.rst.txt b/docs/_sources/common/user_manual/user_inputs_documentation/User_Inputs_Documentation_RST_Files/UserDefinedEDP.rst.txt new file mode 100644 index 00000000..93e1f6b1 --- /dev/null +++ b/docs/_sources/common/user_manual/user_inputs_documentation/User_Inputs_Documentation_RST_Files/UserDefinedEDP.rst.txt @@ -0,0 +1,9 @@ + +.. _UserDefinedEDP User Inputs: + +UserDefinedEDP +============== + + + + diff --git a/docs/_static/_sphinx_javascript_frameworks_compat.js b/docs/_static/_sphinx_javascript_frameworks_compat.js new file mode 100644 index 00000000..8549469d --- /dev/null +++ b/docs/_static/_sphinx_javascript_frameworks_compat.js @@ -0,0 +1,134 @@ +/* + * _sphinx_javascript_frameworks_compat.js + * ~~~~~~~~~~ + * + * Compatability shim for jQuery and underscores.js. + * + * WILL BE REMOVED IN Sphinx 6.0 + * xref RemovedInSphinx60Warning + * + */ + +/** + * select a different prefix for underscore + */ +$u = _.noConflict(); + + +/** + * small helper function to urldecode strings + * + * See https://developer.mozilla.org/en-US/docs/Web/JavaScript/Reference/Global_Objects/decodeURIComponent#Decoding_query_parameters_from_a_URL + */ +jQuery.urldecode = function(x) { + if (!x) { + return x + } + return decodeURIComponent(x.replace(/\+/g, ' ')); +}; + +/** + * small helper function to urlencode strings + */ +jQuery.urlencode = encodeURIComponent; + +/** + * This function returns the parsed url parameters of the + * current request. Multiple values per key are supported, + * it will always return arrays of strings for the value parts. + */ +jQuery.getQueryParameters = function(s) { + if (typeof s === 'undefined') + s = document.location.search; + var parts = s.substr(s.indexOf('?') + 1).split('&'); + var result = {}; + for (var i = 0; i < parts.length; i++) { + var tmp = parts[i].split('=', 2); + var key = jQuery.urldecode(tmp[0]); + var value = jQuery.urldecode(tmp[1]); + if (key in result) + result[key].push(value); + else + result[key] = [value]; + } + return result; +}; + +/** + * highlight a given string on a jquery object by wrapping it in + * span elements with the given class name. + */ +jQuery.fn.highlightText = function(text, className) { + function highlight(node, addItems) { + if (node.nodeType === 3) { + var val = node.nodeValue; + var pos = val.toLowerCase().indexOf(text); + if (pos >= 0 && + !jQuery(node.parentNode).hasClass(className) && + !jQuery(node.parentNode).hasClass("nohighlight")) { + var span; + var isInSVG = jQuery(node).closest("body, svg, foreignObject").is("svg"); + if (isInSVG) { + span = document.createElementNS("http://www.w3.org/2000/svg", "tspan"); + } else { + span = document.createElement("span"); + span.className = className; + } + span.appendChild(document.createTextNode(val.substr(pos, text.length))); + node.parentNode.insertBefore(span, node.parentNode.insertBefore( + document.createTextNode(val.substr(pos + text.length)), + node.nextSibling)); + node.nodeValue = val.substr(0, pos); + if (isInSVG) { + var rect = document.createElementNS("http://www.w3.org/2000/svg", "rect"); + var bbox = node.parentElement.getBBox(); + rect.x.baseVal.value = bbox.x; + rect.y.baseVal.value = bbox.y; + rect.width.baseVal.value = bbox.width; + rect.height.baseVal.value = bbox.height; + rect.setAttribute('class', className); + addItems.push({ + "parent": node.parentNode, + "target": rect}); + } + } + } + else if (!jQuery(node).is("button, select, textarea")) { + jQuery.each(node.childNodes, function() { + highlight(this, addItems); + }); + } + } + var addItems = []; + var result = this.each(function() { + highlight(this, addItems); + }); + for (var i = 0; i < addItems.length; ++i) { + jQuery(addItems[i].parent).before(addItems[i].target); + } + return result; +}; + +/* + * backward compatibility for jQuery.browser + * This will be supported until firefox bug is fixed. + */ +if (!jQuery.browser) { + jQuery.uaMatch = function(ua) { + ua = ua.toLowerCase(); + + var match = /(chrome)[ \/]([\w.]+)/.exec(ua) || + /(webkit)[ \/]([\w.]+)/.exec(ua) || + /(opera)(?:.*version|)[ \/]([\w.]+)/.exec(ua) || + /(msie) ([\w.]+)/.exec(ua) || + ua.indexOf("compatible") < 0 && /(mozilla)(?:.*? rv:([\w.]+)|)/.exec(ua) || + []; + + return { + browser: match[ 1 ] || "", + version: match[ 2 ] || "0" + }; + }; + jQuery.browser = {}; + jQuery.browser[jQuery.uaMatch(navigator.userAgent).browser] = true; +} diff --git a/docs/_static/basic.css b/docs/_static/basic.css index 912859b5..7243282d 100644 --- a/docs/_static/basic.css +++ b/docs/_static/basic.css @@ -4,7 +4,7 @@ * * Sphinx stylesheet -- basic theme. * - * :copyright: Copyright 2007-2021 by the Sphinx team, see AUTHORS. + * :copyright: Copyright 2007-2022 by the Sphinx team, see AUTHORS. * :license: BSD, see LICENSE for details. * */ @@ -222,7 +222,7 @@ table.modindextable td { /* -- general body styles --------------------------------------------------- */ div.body { - min-width: 450px; + min-width: 360px; max-width: 800px; } @@ -428,10 +428,6 @@ table.docutils td, table.docutils th { border-bottom: 1px solid #aaa; } -table.footnote td, table.footnote th { - border: 0 !important; -} - th { text-align: left; padding-right: 5px; @@ -615,6 +611,7 @@ ul.simple p { margin-bottom: 0; } +/* Docutils 0.17 and older (footnotes & citations) */ dl.footnote > dt, dl.citation > dt { float: left; @@ -632,6 +629,33 @@ dl.citation > dd:after { clear: both; } +/* Docutils 0.18+ (footnotes & citations) */ +aside.footnote > span, +div.citation > span { + float: left; +} +aside.footnote > span:last-of-type, +div.citation > span:last-of-type { + padding-right: 0.5em; +} +aside.footnote > p { + margin-left: 2em; +} +div.citation > p { + margin-left: 4em; +} +aside.footnote > p:last-of-type, +div.citation > p:last-of-type { + margin-bottom: 0em; +} +aside.footnote > p:last-of-type:after, +div.citation > p:last-of-type:after { + content: ""; + clear: both; +} + +/* Footnotes & citations ends */ + dl.field-list { display: grid; grid-template-columns: fit-content(30%) auto; @@ -731,8 +755,9 @@ dl.glossary dt { .classifier:before { font-style: normal; - margin: 0.5em; + margin: 0 0.5em; content: ":"; + display: inline-block; } abbr, acronym { @@ -756,6 +781,7 @@ span.pre { -ms-hyphens: none; -webkit-hyphens: none; hyphens: none; + white-space: nowrap; } div[class*="highlight-"] { diff --git a/docs/_static/css/custom.css b/docs/_static/css/custom.css index 1bd7d9c4..8a1582d7 100644 --- a/docs/_static/css/custom.css +++ b/docs/_static/css/custom.css @@ -10,6 +10,15 @@ .eqno { float: right; } +.math .headerlink { + display: none; + visibility: hidden; +} +.math:hover .headerlink { + display: inline-block; + visibility: visible; + margin-right: -0.7em; +} table { display: block; diff --git a/docs/_static/custom.css b/docs/_static/custom.css index 1bd7d9c4..8a1582d7 100644 --- a/docs/_static/custom.css +++ b/docs/_static/custom.css @@ -10,6 +10,15 @@ .eqno { float: right; } +.math .headerlink { + display: none; + visibility: hidden; +} +.math:hover .headerlink { + display: inline-block; + visibility: visible; + margin-right: -0.7em; +} table { display: block; diff --git a/docs/_static/doctools.js b/docs/_static/doctools.js index 8cbf1b16..c3db08d1 100644 --- a/docs/_static/doctools.js +++ b/docs/_static/doctools.js @@ -2,322 +2,263 @@ * doctools.js * ~~~~~~~~~~~ * - * Sphinx JavaScript utilities for all documentation. + * Base JavaScript utilities for all Sphinx HTML documentation. * - * :copyright: Copyright 2007-2021 by the Sphinx team, see AUTHORS. + * :copyright: Copyright 2007-2022 by the Sphinx team, see AUTHORS. * :license: BSD, see LICENSE for details. * */ +"use strict"; -/** - * select a different prefix for underscore - */ -$u = _.noConflict(); - -/** - * make the code below compatible with browsers without - * an installed firebug like debugger -if (!window.console || !console.firebug) { - var names = ["log", "debug", "info", "warn", "error", "assert", "dir", - "dirxml", "group", "groupEnd", "time", "timeEnd", "count", "trace", - "profile", "profileEnd"]; - window.console = {}; - for (var i = 0; i < names.length; ++i) - window.console[names[i]] = function() {}; -} - */ - -/** - * small helper function to urldecode strings - * - * See https://developer.mozilla.org/en-US/docs/Web/JavaScript/Reference/Global_Objects/decodeURIComponent#Decoding_query_parameters_from_a_URL - */ -jQuery.urldecode = function(x) { - if (!x) { - return x +const _ready = (callback) => { + if (document.readyState !== "loading") { + callback(); + } else { + document.addEventListener("DOMContentLoaded", callback); } - return decodeURIComponent(x.replace(/\+/g, ' ')); }; /** - * small helper function to urlencode strings + * highlight a given string on a node by wrapping it in + * span elements with the given class name. */ -jQuery.urlencode = encodeURIComponent; +const _highlight = (node, addItems, text, className) => { + if (node.nodeType === Node.TEXT_NODE) { + const val = node.nodeValue; + const parent = node.parentNode; + const pos = val.toLowerCase().indexOf(text); + if ( + pos >= 0 && + !parent.classList.contains(className) && + !parent.classList.contains("nohighlight") + ) { + let span; -/** - * This function returns the parsed url parameters of the - * current request. Multiple values per key are supported, - * it will always return arrays of strings for the value parts. - */ -jQuery.getQueryParameters = function(s) { - if (typeof s === 'undefined') - s = document.location.search; - var parts = s.substr(s.indexOf('?') + 1).split('&'); - var result = {}; - for (var i = 0; i < parts.length; i++) { - var tmp = parts[i].split('=', 2); - var key = jQuery.urldecode(tmp[0]); - var value = jQuery.urldecode(tmp[1]); - if (key in result) - result[key].push(value); - else - result[key] = [value]; - } - return result; -}; + const closestNode = parent.closest("body, svg, foreignObject"); + const isInSVG = closestNode && closestNode.matches("svg"); + if (isInSVG) { + span = document.createElementNS("http://www.w3.org/2000/svg", "tspan"); + } else { + span = document.createElement("span"); + span.classList.add(className); + } -/** - * highlight a given string on a jquery object by wrapping it in - * span elements with the given class name. - */ -jQuery.fn.highlightText = function(text, className) { - function highlight(node, addItems) { - if (node.nodeType === 3) { - var val = node.nodeValue; - var pos = val.toLowerCase().indexOf(text); - if (pos >= 0 && - !jQuery(node.parentNode).hasClass(className) && - !jQuery(node.parentNode).hasClass("nohighlight")) { - var span; - var isInSVG = jQuery(node).closest("body, svg, foreignObject").is("svg"); - if (isInSVG) { - span = document.createElementNS("http://www.w3.org/2000/svg", "tspan"); - } else { - span = document.createElement("span"); - span.className = className; - } - span.appendChild(document.createTextNode(val.substr(pos, text.length))); - node.parentNode.insertBefore(span, node.parentNode.insertBefore( + span.appendChild(document.createTextNode(val.substr(pos, text.length))); + parent.insertBefore( + span, + parent.insertBefore( document.createTextNode(val.substr(pos + text.length)), - node.nextSibling)); - node.nodeValue = val.substr(0, pos); - if (isInSVG) { - var rect = document.createElementNS("http://www.w3.org/2000/svg", "rect"); - var bbox = node.parentElement.getBBox(); - rect.x.baseVal.value = bbox.x; - rect.y.baseVal.value = bbox.y; - rect.width.baseVal.value = bbox.width; - rect.height.baseVal.value = bbox.height; - rect.setAttribute('class', className); - addItems.push({ - "parent": node.parentNode, - "target": rect}); - } + node.nextSibling + ) + ); + node.nodeValue = val.substr(0, pos); + + if (isInSVG) { + const rect = document.createElementNS( + "http://www.w3.org/2000/svg", + "rect" + ); + const bbox = parent.getBBox(); + rect.x.baseVal.value = bbox.x; + rect.y.baseVal.value = bbox.y; + rect.width.baseVal.value = bbox.width; + rect.height.baseVal.value = bbox.height; + rect.setAttribute("class", className); + addItems.push({ parent: parent, target: rect }); } } - else if (!jQuery(node).is("button, select, textarea")) { - jQuery.each(node.childNodes, function() { - highlight(this, addItems); - }); - } + } else if (node.matches && !node.matches("button, select, textarea")) { + node.childNodes.forEach((el) => _highlight(el, addItems, text, className)); } - var addItems = []; - var result = this.each(function() { - highlight(this, addItems); - }); - for (var i = 0; i < addItems.length; ++i) { - jQuery(addItems[i].parent).before(addItems[i].target); - } - return result; }; - -/* - * backward compatibility for jQuery.browser - * This will be supported until firefox bug is fixed. - */ -if (!jQuery.browser) { - jQuery.uaMatch = function(ua) { - ua = ua.toLowerCase(); - - var match = /(chrome)[ \/]([\w.]+)/.exec(ua) || - /(webkit)[ \/]([\w.]+)/.exec(ua) || - /(opera)(?:.*version|)[ \/]([\w.]+)/.exec(ua) || - /(msie) ([\w.]+)/.exec(ua) || - ua.indexOf("compatible") < 0 && /(mozilla)(?:.*? rv:([\w.]+)|)/.exec(ua) || - []; - - return { - browser: match[ 1 ] || "", - version: match[ 2 ] || "0" - }; - }; - jQuery.browser = {}; - jQuery.browser[jQuery.uaMatch(navigator.userAgent).browser] = true; -} +const _highlightText = (thisNode, text, className) => { + let addItems = []; + _highlight(thisNode, addItems, text, className); + addItems.forEach((obj) => + obj.parent.insertAdjacentElement("beforebegin", obj.target) + ); +}; /** * Small JavaScript module for the documentation. */ -var Documentation = { - - init : function() { - this.fixFirefoxAnchorBug(); - this.highlightSearchWords(); - this.initIndexTable(); - if (DOCUMENTATION_OPTIONS.NAVIGATION_WITH_KEYS) { - this.initOnKeyListeners(); - } +const Documentation = { + init: () => { + Documentation.highlightSearchWords(); + Documentation.initDomainIndexTable(); + Documentation.initOnKeyListeners(); }, /** * i18n support */ - TRANSLATIONS : {}, - PLURAL_EXPR : function(n) { return n === 1 ? 0 : 1; }, - LOCALE : 'unknown', + TRANSLATIONS: {}, + PLURAL_EXPR: (n) => (n === 1 ? 0 : 1), + LOCALE: "unknown", // gettext and ngettext don't access this so that the functions // can safely bound to a different name (_ = Documentation.gettext) - gettext : function(string) { - var translated = Documentation.TRANSLATIONS[string]; - if (typeof translated === 'undefined') - return string; - return (typeof translated === 'string') ? translated : translated[0]; - }, - - ngettext : function(singular, plural, n) { - var translated = Documentation.TRANSLATIONS[singular]; - if (typeof translated === 'undefined') - return (n == 1) ? singular : plural; - return translated[Documentation.PLURALEXPR(n)]; - }, - - addTranslations : function(catalog) { - for (var key in catalog.messages) - this.TRANSLATIONS[key] = catalog.messages[key]; - this.PLURAL_EXPR = new Function('n', 'return +(' + catalog.plural_expr + ')'); - this.LOCALE = catalog.locale; + gettext: (string) => { + const translated = Documentation.TRANSLATIONS[string]; + switch (typeof translated) { + case "undefined": + return string; // no translation + case "string": + return translated; // translation exists + default: + return translated[0]; // (singular, plural) translation tuple exists + } }, - /** - * add context elements like header anchor links - */ - addContextElements : function() { - $('div[id] > :header:first').each(function() { - $('\u00B6'). - attr('href', '#' + this.id). - attr('title', _('Permalink to this headline')). - appendTo(this); - }); - $('dt[id]').each(function() { - $('\u00B6'). - attr('href', '#' + this.id). - attr('title', _('Permalink to this definition')). - appendTo(this); - }); + ngettext: (singular, plural, n) => { + const translated = Documentation.TRANSLATIONS[singular]; + if (typeof translated !== "undefined") + return translated[Documentation.PLURAL_EXPR(n)]; + return n === 1 ? singular : plural; }, - /** - * workaround a firefox stupidity - * see: https://bugzilla.mozilla.org/show_bug.cgi?id=645075 - */ - fixFirefoxAnchorBug : function() { - if (document.location.hash && $.browser.mozilla) - window.setTimeout(function() { - document.location.href += ''; - }, 10); + addTranslations: (catalog) => { + Object.assign(Documentation.TRANSLATIONS, catalog.messages); + Documentation.PLURAL_EXPR = new Function( + "n", + `return (${catalog.plural_expr})` + ); + Documentation.LOCALE = catalog.locale; }, /** * highlight the search words provided in the url in the text */ - highlightSearchWords : function() { - var params = $.getQueryParameters(); - var terms = (params.highlight) ? params.highlight[0].split(/\s+/) : []; - if (terms.length) { - var body = $('div.body'); - if (!body.length) { - body = $('body'); - } - window.setTimeout(function() { - $.each(terms, function() { - body.highlightText(this.toLowerCase(), 'highlighted'); - }); - }, 10); - $('') - .appendTo($('#searchbox')); - } - }, + highlightSearchWords: () => { + const highlight = + new URLSearchParams(window.location.search).get("highlight") || ""; + const terms = highlight.toLowerCase().split(/\s+/).filter(x => x); + if (terms.length === 0) return; // nothing to do - /** - * init the domain index toggle buttons - */ - initIndexTable : function() { - var togglers = $('img.toggler').click(function() { - var src = $(this).attr('src'); - var idnum = $(this).attr('id').substr(7); - $('tr.cg-' + idnum).toggle(); - if (src.substr(-9) === 'minus.png') - $(this).attr('src', src.substr(0, src.length-9) + 'plus.png'); - else - $(this).attr('src', src.substr(0, src.length-8) + 'minus.png'); - }).css('display', ''); - if (DOCUMENTATION_OPTIONS.COLLAPSE_INDEX) { - togglers.click(); - } + // There should never be more than one element matching "div.body" + const divBody = document.querySelectorAll("div.body"); + const body = divBody.length ? divBody[0] : document.querySelector("body"); + window.setTimeout(() => { + terms.forEach((term) => _highlightText(body, term, "highlighted")); + }, 10); + + const searchBox = document.getElementById("searchbox"); + if (searchBox === null) return; + searchBox.appendChild( + document + .createRange() + .createContextualFragment( + '" + ) + ); }, /** * helper function to hide the search marks again */ - hideSearchWords : function() { - $('#searchbox .highlight-link').fadeOut(300); - $('span.highlighted').removeClass('highlighted'); + hideSearchWords: () => { + document + .querySelectorAll("#searchbox .highlight-link") + .forEach((el) => el.remove()); + document + .querySelectorAll("span.highlighted") + .forEach((el) => el.classList.remove("highlighted")); + const url = new URL(window.location); + url.searchParams.delete("highlight"); + window.history.replaceState({}, "", url); }, /** - * make the url absolute + * helper function to focus on search bar */ - makeURL : function(relativeURL) { - return DOCUMENTATION_OPTIONS.URL_ROOT + '/' + relativeURL; + focusSearchBar: () => { + document.querySelectorAll("input[name=q]")[0]?.focus(); }, /** - * get the current relative url + * Initialise the domain index toggle buttons */ - getCurrentURL : function() { - var path = document.location.pathname; - var parts = path.split(/\//); - $.each(DOCUMENTATION_OPTIONS.URL_ROOT.split(/\//), function() { - if (this === '..') - parts.pop(); - }); - var url = parts.join('/'); - return path.substring(url.lastIndexOf('/') + 1, path.length - 1); + initDomainIndexTable: () => { + const toggler = (el) => { + const idNumber = el.id.substr(7); + const toggledRows = document.querySelectorAll(`tr.cg-${idNumber}`); + if (el.src.substr(-9) === "minus.png") { + el.src = `${el.src.substr(0, el.src.length - 9)}plus.png`; + toggledRows.forEach((el) => (el.style.display = "none")); + } else { + el.src = `${el.src.substr(0, el.src.length - 8)}minus.png`; + toggledRows.forEach((el) => (el.style.display = "")); + } + }; + + const togglerElements = document.querySelectorAll("img.toggler"); + togglerElements.forEach((el) => + el.addEventListener("click", (event) => toggler(event.currentTarget)) + ); + togglerElements.forEach((el) => (el.style.display = "")); + if (DOCUMENTATION_OPTIONS.COLLAPSE_INDEX) togglerElements.forEach(toggler); }, - initOnKeyListeners: function() { - $(document).keydown(function(event) { - var activeElementType = document.activeElement.tagName; - // don't navigate when in search box, textarea, dropdown or button - if (activeElementType !== 'TEXTAREA' && activeElementType !== 'INPUT' && activeElementType !== 'SELECT' - && activeElementType !== 'BUTTON' && !event.altKey && !event.ctrlKey && !event.metaKey - && !event.shiftKey) { - switch (event.keyCode) { - case 37: // left - var prevHref = $('link[rel="prev"]').prop('href'); - if (prevHref) { - window.location.href = prevHref; - return false; + initOnKeyListeners: () => { + // only install a listener if it is really needed + if ( + !DOCUMENTATION_OPTIONS.NAVIGATION_WITH_KEYS && + !DOCUMENTATION_OPTIONS.ENABLE_SEARCH_SHORTCUTS + ) + return; + + const blacklistedElements = new Set([ + "TEXTAREA", + "INPUT", + "SELECT", + "BUTTON", + ]); + document.addEventListener("keydown", (event) => { + if (blacklistedElements.has(document.activeElement.tagName)) return; // bail for input elements + if (event.altKey || event.ctrlKey || event.metaKey) return; // bail with special keys + + if (!event.shiftKey) { + switch (event.key) { + case "ArrowLeft": + if (!DOCUMENTATION_OPTIONS.NAVIGATION_WITH_KEYS) break; + + const prevLink = document.querySelector('link[rel="prev"]'); + if (prevLink && prevLink.href) { + window.location.href = prevLink.href; + event.preventDefault(); } break; - case 39: // right - var nextHref = $('link[rel="next"]').prop('href'); - if (nextHref) { - window.location.href = nextHref; - return false; + case "ArrowRight": + if (!DOCUMENTATION_OPTIONS.NAVIGATION_WITH_KEYS) break; + + const nextLink = document.querySelector('link[rel="next"]'); + if (nextLink && nextLink.href) { + window.location.href = nextLink.href; + event.preventDefault(); } break; + case "Escape": + if (!DOCUMENTATION_OPTIONS.ENABLE_SEARCH_SHORTCUTS) break; + Documentation.hideSearchWords(); + event.preventDefault(); } } + + // some keyboard layouts may need Shift to get / + switch (event.key) { + case "/": + if (!DOCUMENTATION_OPTIONS.ENABLE_SEARCH_SHORTCUTS) break; + Documentation.focusSearchBar(); + event.preventDefault(); + } }); - } + }, }; // quick alias for translations -_ = Documentation.gettext; +const _ = Documentation.gettext; -$(document).ready(function() { - Documentation.init(); -}); +_ready(Documentation.init); diff --git a/docs/_static/documentation_options.js b/docs/_static/documentation_options.js index 2fa8c97f..a750e4d5 100644 --- a/docs/_static/documentation_options.js +++ b/docs/_static/documentation_options.js @@ -1,12 +1,14 @@ var DOCUMENTATION_OPTIONS = { URL_ROOT: document.getElementById("documentation_options").getAttribute('data-url_root'), VERSION: '', - LANGUAGE: 'None', + LANGUAGE: 'en', COLLAPSE_INDEX: false, BUILDER: 'html', FILE_SUFFIX: '.html', LINK_SUFFIX: '.html', HAS_SOURCE: true, SOURCELINK_SUFFIX: '.txt', - NAVIGATION_WITH_KEYS: false + NAVIGATION_WITH_KEYS: false, + SHOW_SEARCH_SUMMARY: true, + ENABLE_SEARCH_SHORTCUTS: false, }; \ No newline at end of file diff --git a/docs/_static/jquery-3.5.1.js b/docs/_static/jquery-3.6.0.js similarity index 98% rename from docs/_static/jquery-3.5.1.js rename to docs/_static/jquery-3.6.0.js index 50937333..fc6c299b 100644 --- a/docs/_static/jquery-3.5.1.js +++ b/docs/_static/jquery-3.6.0.js @@ -1,15 +1,15 @@ /*! - * jQuery JavaScript Library v3.5.1 + * jQuery JavaScript Library v3.6.0 * https://jquery.com/ * * Includes Sizzle.js * https://sizzlejs.com/ * - * Copyright JS Foundation and other contributors + * Copyright OpenJS Foundation and other contributors * Released under the MIT license * https://jquery.org/license * - * Date: 2020-05-04T22:49Z + * Date: 2021-03-02T17:08Z */ ( function( global, factory ) { @@ -76,12 +76,16 @@ var support = {}; var isFunction = function isFunction( obj ) { - // Support: Chrome <=57, Firefox <=52 - // In some browsers, typeof returns "function" for HTML elements - // (i.e., `typeof document.createElement( "object" ) === "function"`). - // We don't want to classify *any* DOM node as a function. - return typeof obj === "function" && typeof obj.nodeType !== "number"; - }; + // Support: Chrome <=57, Firefox <=52 + // In some browsers, typeof returns "function" for HTML elements + // (i.e., `typeof document.createElement( "object" ) === "function"`). + // We don't want to classify *any* DOM node as a function. + // Support: QtWeb <=3.8.5, WebKit <=534.34, wkhtmltopdf tool <=0.12.5 + // Plus for old WebKit, typeof returns "function" for HTML collections + // (e.g., `typeof document.getElementsByTagName("div") === "function"`). (gh-4756) + return typeof obj === "function" && typeof obj.nodeType !== "number" && + typeof obj.item !== "function"; + }; var isWindow = function isWindow( obj ) { @@ -147,7 +151,7 @@ function toType( obj ) { var - version = "3.5.1", + version = "3.6.0", // Define a local copy of jQuery jQuery = function( selector, context ) { @@ -401,7 +405,7 @@ jQuery.extend( { if ( isArrayLike( Object( arr ) ) ) { jQuery.merge( ret, typeof arr === "string" ? - [ arr ] : arr + [ arr ] : arr ); } else { push.call( ret, arr ); @@ -496,9 +500,9 @@ if ( typeof Symbol === "function" ) { // Populate the class2type map jQuery.each( "Boolean Number String Function Array Date RegExp Object Error Symbol".split( " " ), -function( _i, name ) { - class2type[ "[object " + name + "]" ] = name.toLowerCase(); -} ); + function( _i, name ) { + class2type[ "[object " + name + "]" ] = name.toLowerCase(); + } ); function isArrayLike( obj ) { @@ -518,14 +522,14 @@ function isArrayLike( obj ) { } var Sizzle = /*! - * Sizzle CSS Selector Engine v2.3.5 + * Sizzle CSS Selector Engine v2.3.6 * https://sizzlejs.com/ * * Copyright JS Foundation and other contributors * Released under the MIT license * https://js.foundation/ * - * Date: 2020-03-14 + * Date: 2021-02-16 */ ( function( window ) { var i, @@ -1108,8 +1112,8 @@ support = Sizzle.support = {}; * @returns {Boolean} True iff elem is a non-HTML XML node */ isXML = Sizzle.isXML = function( elem ) { - var namespace = elem.namespaceURI, - docElem = ( elem.ownerDocument || elem ).documentElement; + var namespace = elem && elem.namespaceURI, + docElem = elem && ( elem.ownerDocument || elem ).documentElement; // Support: IE <=8 // Assume HTML when documentElement doesn't yet exist, such as inside loading iframes @@ -3024,9 +3028,9 @@ var rneedsContext = jQuery.expr.match.needsContext; function nodeName( elem, name ) { - return elem.nodeName && elem.nodeName.toLowerCase() === name.toLowerCase(); + return elem.nodeName && elem.nodeName.toLowerCase() === name.toLowerCase(); -}; +} var rsingleTag = ( /^<([a-z][^\/\0>:\x20\t\r\n\f]*)[\x20\t\r\n\f]*\/?>(?:<\/\1>|)$/i ); @@ -3997,8 +4001,8 @@ jQuery.extend( { resolveContexts = Array( i ), resolveValues = slice.call( arguments ), - // the master Deferred - master = jQuery.Deferred(), + // the primary Deferred + primary = jQuery.Deferred(), // subordinate callback factory updateFunc = function( i ) { @@ -4006,30 +4010,30 @@ jQuery.extend( { resolveContexts[ i ] = this; resolveValues[ i ] = arguments.length > 1 ? slice.call( arguments ) : value; if ( !( --remaining ) ) { - master.resolveWith( resolveContexts, resolveValues ); + primary.resolveWith( resolveContexts, resolveValues ); } }; }; // Single- and empty arguments are adopted like Promise.resolve if ( remaining <= 1 ) { - adoptValue( singleValue, master.done( updateFunc( i ) ).resolve, master.reject, + adoptValue( singleValue, primary.done( updateFunc( i ) ).resolve, primary.reject, !remaining ); // Use .then() to unwrap secondary thenables (cf. gh-3000) - if ( master.state() === "pending" || + if ( primary.state() === "pending" || isFunction( resolveValues[ i ] && resolveValues[ i ].then ) ) { - return master.then(); + return primary.then(); } } // Multiple arguments are aggregated like Promise.all array elements while ( i-- ) { - adoptValue( resolveValues[ i ], updateFunc( i ), master.reject ); + adoptValue( resolveValues[ i ], updateFunc( i ), primary.reject ); } - return master.promise(); + return primary.promise(); } } ); @@ -4180,8 +4184,8 @@ var access = function( elems, fn, key, value, chainable, emptyGet, raw ) { for ( ; i < len; i++ ) { fn( elems[ i ], key, raw ? - value : - value.call( elems[ i ], i, fn( elems[ i ], key ) ) + value : + value.call( elems[ i ], i, fn( elems[ i ], key ) ) ); } } @@ -5089,10 +5093,7 @@ function buildFragment( elems, context, scripts, selection, ignored ) { } -var - rkeyEvent = /^key/, - rmouseEvent = /^(?:mouse|pointer|contextmenu|drag|drop)|click/, - rtypenamespace = /^([^.]*)(?:\.(.+)|)/; +var rtypenamespace = /^([^.]*)(?:\.(.+)|)/; function returnTrue() { return true; @@ -5387,8 +5388,8 @@ jQuery.event = { event = jQuery.event.fix( nativeEvent ), handlers = ( - dataPriv.get( this, "events" ) || Object.create( null ) - )[ event.type ] || [], + dataPriv.get( this, "events" ) || Object.create( null ) + )[ event.type ] || [], special = jQuery.event.special[ event.type ] || {}; // Use the fix-ed jQuery.Event rather than the (read-only) native event @@ -5512,12 +5513,12 @@ jQuery.event = { get: isFunction( hook ) ? function() { if ( this.originalEvent ) { - return hook( this.originalEvent ); + return hook( this.originalEvent ); } } : function() { if ( this.originalEvent ) { - return this.originalEvent[ name ]; + return this.originalEvent[ name ]; } }, @@ -5656,7 +5657,13 @@ function leverageNative( el, type, expectSync ) { // Cancel the outer synthetic event event.stopImmediatePropagation(); event.preventDefault(); - return result.value; + + // Support: Chrome 86+ + // In Chrome, if an element having a focusout handler is blurred by + // clicking outside of it, it invokes the handler synchronously. If + // that handler calls `.remove()` on the element, the data is cleared, + // leaving `result` undefined. We need to guard against this. + return result && result.value; } // If this is an inner synthetic event for an event with a bubbling surrogate @@ -5821,34 +5828,7 @@ jQuery.each( { targetTouches: true, toElement: true, touches: true, - - which: function( event ) { - var button = event.button; - - // Add which for key events - if ( event.which == null && rkeyEvent.test( event.type ) ) { - return event.charCode != null ? event.charCode : event.keyCode; - } - - // Add which for click: 1 === left; 2 === middle; 3 === right - if ( !event.which && button !== undefined && rmouseEvent.test( event.type ) ) { - if ( button & 1 ) { - return 1; - } - - if ( button & 2 ) { - return 3; - } - - if ( button & 4 ) { - return 2; - } - - return 0; - } - - return event.which; - } + which: true }, jQuery.event.addProp ); jQuery.each( { focus: "focusin", blur: "focusout" }, function( type, delegateType ) { @@ -5874,6 +5854,12 @@ jQuery.each( { focus: "focusin", blur: "focusout" }, function( type, delegateTyp return true; }, + // Suppress native focus or blur as it's already being fired + // in leverageNative. + _default: function() { + return true; + }, + delegateType: delegateType }; } ); @@ -6541,6 +6527,10 @@ var rboxStyle = new RegExp( cssExpand.join( "|" ), "i" ); // set in CSS while `offset*` properties report correct values. // Behavior in IE 9 is more subtle than in newer versions & it passes // some versions of this test; make sure not to make it pass there! + // + // Support: Firefox 70+ + // Only Firefox includes border widths + // in computed dimensions. (gh-4529) reliableTrDimensions: function() { var table, tr, trChild, trStyle; if ( reliableTrDimensionsVal == null ) { @@ -6548,17 +6538,32 @@ var rboxStyle = new RegExp( cssExpand.join( "|" ), "i" ); tr = document.createElement( "tr" ); trChild = document.createElement( "div" ); - table.style.cssText = "position:absolute;left:-11111px"; + table.style.cssText = "position:absolute;left:-11111px;border-collapse:separate"; + tr.style.cssText = "border:1px solid"; + + // Support: Chrome 86+ + // Height set through cssText does not get applied. + // Computed height then comes back as 0. tr.style.height = "1px"; trChild.style.height = "9px"; + // Support: Android 8 Chrome 86+ + // In our bodyBackground.html iframe, + // display for all div elements is set to "inline", + // which causes a problem only in Android 8 Chrome 86. + // Ensuring the div is display: block + // gets around this issue. + trChild.style.display = "block"; + documentElement .appendChild( table ) .appendChild( tr ) .appendChild( trChild ); trStyle = window.getComputedStyle( tr ); - reliableTrDimensionsVal = parseInt( trStyle.height ) > 3; + reliableTrDimensionsVal = ( parseInt( trStyle.height, 10 ) + + parseInt( trStyle.borderTopWidth, 10 ) + + parseInt( trStyle.borderBottomWidth, 10 ) ) === tr.offsetHeight; documentElement.removeChild( table ); } @@ -7022,10 +7027,10 @@ jQuery.each( [ "height", "width" ], function( _i, dimension ) { // Running getBoundingClientRect on a disconnected node // in IE throws an error. ( !elem.getClientRects().length || !elem.getBoundingClientRect().width ) ? - swap( elem, cssShow, function() { - return getWidthOrHeight( elem, dimension, extra ); - } ) : - getWidthOrHeight( elem, dimension, extra ); + swap( elem, cssShow, function() { + return getWidthOrHeight( elem, dimension, extra ); + } ) : + getWidthOrHeight( elem, dimension, extra ); } }, @@ -7084,7 +7089,7 @@ jQuery.cssHooks.marginLeft = addGetHookIf( support.reliableMarginLeft, swap( elem, { marginLeft: 0 }, function() { return elem.getBoundingClientRect().left; } ) - ) + "px"; + ) + "px"; } } ); @@ -7223,7 +7228,7 @@ Tween.propHooks = { if ( jQuery.fx.step[ tween.prop ] ) { jQuery.fx.step[ tween.prop ]( tween ); } else if ( tween.elem.nodeType === 1 && ( - jQuery.cssHooks[ tween.prop ] || + jQuery.cssHooks[ tween.prop ] || tween.elem.style[ finalPropName( tween.prop ) ] != null ) ) { jQuery.style( tween.elem, tween.prop, tween.now + tween.unit ); } else { @@ -7468,7 +7473,7 @@ function defaultPrefilter( elem, props, opts ) { anim.done( function() { - /* eslint-enable no-loop-func */ + /* eslint-enable no-loop-func */ // The final step of a "hide" animation is actually hiding the element if ( !hidden ) { @@ -7588,7 +7593,7 @@ function Animation( elem, properties, options ) { tweens: [], createTween: function( prop, end ) { var tween = jQuery.Tween( elem, animation.opts, prop, end, - animation.opts.specialEasing[ prop ] || animation.opts.easing ); + animation.opts.specialEasing[ prop ] || animation.opts.easing ); animation.tweens.push( tween ); return tween; }, @@ -7761,7 +7766,8 @@ jQuery.fn.extend( { anim.stop( true ); } }; - doAnimation.finish = doAnimation; + + doAnimation.finish = doAnimation; return empty || optall.queue === false ? this.each( doAnimation ) : @@ -8401,8 +8407,8 @@ jQuery.fn.extend( { if ( this.setAttribute ) { this.setAttribute( "class", className || value === false ? - "" : - dataPriv.get( this, "__className__" ) || "" + "" : + dataPriv.get( this, "__className__" ) || "" ); } } @@ -8417,7 +8423,7 @@ jQuery.fn.extend( { while ( ( elem = this[ i++ ] ) ) { if ( elem.nodeType === 1 && ( " " + stripAndCollapse( getClass( elem ) ) + " " ).indexOf( className ) > -1 ) { - return true; + return true; } } @@ -8707,9 +8713,7 @@ jQuery.extend( jQuery.event, { special.bindType || type; // jQuery handler - handle = ( - dataPriv.get( cur, "events" ) || Object.create( null ) - )[ event.type ] && + handle = ( dataPriv.get( cur, "events" ) || Object.create( null ) )[ event.type ] && dataPriv.get( cur, "handle" ); if ( handle ) { handle.apply( cur, data ); @@ -8856,7 +8860,7 @@ var rquery = ( /\?/ ); // Cross-browser xml parsing jQuery.parseXML = function( data ) { - var xml; + var xml, parserErrorElem; if ( !data || typeof data !== "string" ) { return null; } @@ -8865,12 +8869,17 @@ jQuery.parseXML = function( data ) { // IE throws on parseFromString with invalid input. try { xml = ( new window.DOMParser() ).parseFromString( data, "text/xml" ); - } catch ( e ) { - xml = undefined; - } + } catch ( e ) {} - if ( !xml || xml.getElementsByTagName( "parsererror" ).length ) { - jQuery.error( "Invalid XML: " + data ); + parserErrorElem = xml && xml.getElementsByTagName( "parsererror" )[ 0 ]; + if ( !xml || parserErrorElem ) { + jQuery.error( "Invalid XML: " + ( + parserErrorElem ? + jQuery.map( parserErrorElem.childNodes, function( el ) { + return el.textContent; + } ).join( "\n" ) : + data + ) ); } return xml; }; @@ -8971,16 +8980,14 @@ jQuery.fn.extend( { // Can add propHook for "elements" to filter or add form elements var elements = jQuery.prop( this, "elements" ); return elements ? jQuery.makeArray( elements ) : this; - } ) - .filter( function() { + } ).filter( function() { var type = this.type; // Use .is( ":disabled" ) so that fieldset[disabled] works return this.name && !jQuery( this ).is( ":disabled" ) && rsubmittable.test( this.nodeName ) && !rsubmitterTypes.test( type ) && ( this.checked || !rcheckableType.test( type ) ); - } ) - .map( function( _i, elem ) { + } ).map( function( _i, elem ) { var val = jQuery( this ).val(); if ( val == null ) { @@ -9033,7 +9040,8 @@ var // Anchor tag for parsing the document origin originAnchor = document.createElement( "a" ); - originAnchor.href = location.href; + +originAnchor.href = location.href; // Base "constructor" for jQuery.ajaxPrefilter and jQuery.ajaxTransport function addToPrefiltersOrTransports( structure ) { @@ -9414,8 +9422,8 @@ jQuery.extend( { // Context for global events is callbackContext if it is a DOM node or jQuery collection globalEventContext = s.context && ( callbackContext.nodeType || callbackContext.jquery ) ? - jQuery( callbackContext ) : - jQuery.event, + jQuery( callbackContext ) : + jQuery.event, // Deferreds deferred = jQuery.Deferred(), @@ -9727,8 +9735,10 @@ jQuery.extend( { response = ajaxHandleResponses( s, jqXHR, responses ); } - // Use a noop converter for missing script - if ( !isSuccess && jQuery.inArray( "script", s.dataTypes ) > -1 ) { + // Use a noop converter for missing script but not if jsonp + if ( !isSuccess && + jQuery.inArray( "script", s.dataTypes ) > -1 && + jQuery.inArray( "json", s.dataTypes ) < 0 ) { s.converters[ "text script" ] = function() {}; } @@ -10466,12 +10476,6 @@ jQuery.offset = { options.using.call( elem, props ); } else { - if ( typeof props.top === "number" ) { - props.top += "px"; - } - if ( typeof props.left === "number" ) { - props.left += "px"; - } curElem.css( props ); } } @@ -10640,8 +10644,11 @@ jQuery.each( [ "top", "left" ], function( _i, prop ) { // Create innerHeight, innerWidth, height, width, outerHeight and outerWidth methods jQuery.each( { Height: "height", Width: "width" }, function( name, type ) { - jQuery.each( { padding: "inner" + name, content: type, "": "outer" + name }, - function( defaultExtra, funcName ) { + jQuery.each( { + padding: "inner" + name, + content: type, + "": "outer" + name + }, function( defaultExtra, funcName ) { // Margin is only for outerHeight, outerWidth 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} -if (!splitQuery) { - function splitQuery(query) { - return query.split(/\s+/); +const _removeChildren = (element) => { + while (element && element.lastChild) element.removeChild(element.lastChild); +}; + +/** + * See https://developer.mozilla.org/en-US/docs/Web/JavaScript/Guide/Regular_Expressions#escaping + */ +const _escapeRegExp = (string) => + string.replace(/[.*+\-?^${}()|[\]\\]/g, "\\$&"); // $& means the whole matched string + +const _displayItem = (item, highlightTerms, searchTerms) => { + const docBuilder = DOCUMENTATION_OPTIONS.BUILDER; + const docUrlRoot = DOCUMENTATION_OPTIONS.URL_ROOT; + const docFileSuffix = DOCUMENTATION_OPTIONS.FILE_SUFFIX; + const docLinkSuffix = DOCUMENTATION_OPTIONS.LINK_SUFFIX; + const showSearchSummary = DOCUMENTATION_OPTIONS.SHOW_SEARCH_SUMMARY; + + const [docName, title, anchor, descr] = item; + + let listItem = document.createElement("li"); + let requestUrl; + let linkUrl; + if (docBuilder === "dirhtml") { + // dirhtml builder + let dirname = docName + "/"; + if (dirname.match(/\/index\/$/)) + dirname = dirname.substring(0, dirname.length - 6); + else if (dirname === "index/") dirname = ""; + requestUrl = docUrlRoot + dirname; + linkUrl = requestUrl; + } else { + // normal html builders + requestUrl = docUrlRoot + docName + docFileSuffix; + linkUrl = docName + docLinkSuffix; + } + const params = new URLSearchParams(); + params.set("highlight", [...highlightTerms].join(" ")); + let linkEl = listItem.appendChild(document.createElement("a")); + linkEl.href = linkUrl + "?" + params.toString() + anchor; + linkEl.innerHTML = title; + if (descr) + listItem.appendChild(document.createElement("span")).innerText = + " (" + descr + ")"; + else if (showSearchSummary) + fetch(requestUrl) + .then((responseData) => responseData.text()) + .then((data) => { + if (data) + listItem.appendChild( + Search.makeSearchSummary(data, searchTerms, highlightTerms) + ); + }); + Search.output.appendChild(listItem); +}; +const _finishSearch = (resultCount) => { + Search.stopPulse(); + Search.title.innerText = _("Search Results"); + if (!resultCount) + Search.status.innerText = Documentation.gettext( + "Your search did not match any documents. 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Can be overridden in ``sphinx.search`` with a + * custom function per language. + * + * The regular expression works by splitting the string on consecutive characters + * that are not Unicode letters, numbers, underscores, or emoji characters. + * This is the same as ``\W+`` in Python, preserving the surrogate pair area. + */ +if (typeof splitQuery === "undefined") { + var splitQuery = (query) => query + .split(/[^\p{Letter}\p{Number}_\p{Emoji_Presentation}]+/gu) + .filter(term => term) // remove remaining empty strings } /** * Search Module */ -var Search = { - - _index : null, - _queued_query : null, - _pulse_status : -1, - - htmlToText : function(htmlString) { - var virtualDocument = document.implementation.createHTMLDocument('virtual'); - var htmlElement = $(htmlString, virtualDocument); - htmlElement.find('.headerlink').remove(); - docContent = htmlElement.find('[role=main]')[0]; - if(docContent === undefined) { - console.warn("Content block not found. Sphinx search tries to obtain it " + - "via '[role=main]'. Could you check your theme or template."); - return ""; - } - return docContent.textContent || docContent.innerText; +const Search = { + _index: null, + _queued_query: null, + _pulse_status: -1, + + htmlToText: (htmlString) => { + const htmlElement = document + .createRange() + .createContextualFragment(htmlString); + _removeChildren(htmlElement.querySelectorAll(".headerlink")); + const docContent = htmlElement.querySelector('[role="main"]'); + if (docContent !== undefined) return docContent.textContent; + console.warn( + "Content block not found. Sphinx search tries to obtain it via '[role=main]'. Could you check your theme or template." + ); + return ""; }, - init : function() { - var params = $.getQueryParameters(); - if (params.q) { - var query = params.q[0]; - $('input[name="q"]')[0].value = query; - this.performSearch(query); - } + init: () => { + const query = new URLSearchParams(window.location.search).get("q"); + document + .querySelectorAll('input[name="q"]') + .forEach((el) => (el.value = query)); + if (query) Search.performSearch(query); }, - loadIndex : function(url) { - $.ajax({type: "GET", url: url, data: null, - dataType: "script", cache: true, - complete: function(jqxhr, textstatus) { - if (textstatus != "success") { - document.getElementById("searchindexloader").src = url; - } - }}); - }, + loadIndex: (url) => + (document.body.appendChild(document.createElement("script")).src = url), - setIndex : function(index) { - var q; - this._index = index; - if ((q = this._queued_query) !== null) { - this._queued_query = null; - Search.query(q); + setIndex: (index) => { + Search._index = index; + if (Search._queued_query !== null) { + const query = Search._queued_query; + Search._queued_query = null; + Search.query(query); } }, - hasIndex : function() { - return this._index !== null; - }, + hasIndex: () => Search._index !== null, - deferQuery : function(query) { - this._queued_query = query; - }, + deferQuery: (query) => (Search._queued_query = query), - stopPulse : function() { - this._pulse_status = 0; - }, + stopPulse: () => (Search._pulse_status = -1), - startPulse : function() { - if (this._pulse_status >= 0) - return; - function pulse() { - var i; + startPulse: () => { + if (Search._pulse_status >= 0) return; + + const pulse = () => { Search._pulse_status = (Search._pulse_status + 1) % 4; - var dotString = ''; - for (i = 0; i < Search._pulse_status; i++) - dotString += '.'; - Search.dots.text(dotString); - if (Search._pulse_status > -1) - window.setTimeout(pulse, 500); - } + Search.dots.innerText = ".".repeat(Search._pulse_status); + if (Search._pulse_status >= 0) window.setTimeout(pulse, 500); + }; pulse(); }, /** * perform a search for something (or wait until index is loaded) */ - performSearch : function(query) { + performSearch: (query) => { // create the required interface elements - this.out = $('#search-results'); - this.title = $('

' + _('Searching') + '

').appendTo(this.out); - this.dots = $('').appendTo(this.title); - this.status = $('

 

').appendTo(this.out); - this.output = $(' -

Damage and Loss DB

-

Technical Manual

-

Damage and Loss DB

-

Technical Manual

-

Damage and Loss DB

-

Technical Manual

-

Damage and Loss DB

-

Technical Manual

  • 1. Technical Manual
  • @@ -216,7 +212,7 @@
    -

    2.2.9. DL Applications

    +

    2.2.9. DL Applications

    The DL application performs the damage and loss assessment for the buildings subject to the regional event(s). It takes as input the building properties used for determining damages and losses (e. g. building occupancy, structure type, replacement cost, number of stories), specified in the BIM file, as well as the response simulation output recorded in the EDP file. @@ -238,7 +234,7 @@

    - © Copyright 2023, The Regents of the University of California. + © Copyright 2024, The Regents of the University of California.

    diff --git a/docs/common/developer_manual/architecture/desktop/applications/EDPApps.html b/docs/common/developer_manual/architecture/desktop/applications/EDPApps.html index 0d443bcd..23fab944 100644 --- a/docs/common/developer_manual/architecture/desktop/applications/EDPApps.html +++ b/docs/common/developer_manual/architecture/desktop/applications/EDPApps.html @@ -40,6 +40,7 @@ + @@ -128,11 +129,6 @@
  • 5. Requirements
  • 6. Bugs & Feature Requests
-

Damage and Loss DB

-

Technical Manual

  • 1. Technical Manual
  • @@ -229,7 +225,7 @@
    -

    2.2.5. EDP Applications

    +

    2.2.5. EDP Applications

    The EDP application specifies the types of engineering demand parameters (EDP) expected as output from the response simulation. It determines the EDP type from building properties in the BIM file, the type of event in the EVENT file, and the model information from the SAM file. It writes the type, location, and direction (DOF) of each EDP for a simulation in an EDP.json file, located in its corresponding simulation working directory. @@ -250,7 +246,7 @@

    - © Copyright 2023, The Regents of the University of California. + © Copyright 2024, The Regents of the University of California.

    diff --git a/docs/common/developer_manual/architecture/desktop/applications/UQApps.html b/docs/common/developer_manual/architecture/desktop/applications/UQApps.html index 2f440791..2440377a 100644 --- a/docs/common/developer_manual/architecture/desktop/applications/UQApps.html +++ b/docs/common/developer_manual/architecture/desktop/applications/UQApps.html @@ -40,6 +40,7 @@ + @@ -128,11 +129,6 @@
  • 5. Requirements
  • 6. Bugs & Feature Requests
-

Damage and Loss DB

-

Technical Manual

  • 1. Technical Manual
  • @@ -229,7 +225,7 @@
    -

    2.2.7. UQ Applications

    +

    2.2.7. UQ Applications

    The UQ application is used to sample random variables (RV) specified in any of the workflow steps (Event, Modeling, EDP, Simulation) for uncertainty quantification, then to run commands written in the driver file which call on the backend applications to execute the R2D Workflow. It first populates values for the RVs, sampled from specified probability distributions, in the corresponding files (EVENT.json, SAM.json, EDP.json, SIM.json) for each simulation before executing the workflow. If no RVs are specified, then the UQ application directly runs commands in the driver file without random sampling.

    @@ -249,7 +245,7 @@

    - © Copyright 2023, The Regents of the University of California. + © Copyright 2024, The Regents of the University of California.

    diff --git a/docs/common/developer_manual/architecture/desktop/applications/buildingApps.html b/docs/common/developer_manual/architecture/desktop/applications/buildingApps.html index 9f79bc0d..a96d6815 100644 --- a/docs/common/developer_manual/architecture/desktop/applications/buildingApps.html +++ b/docs/common/developer_manual/architecture/desktop/applications/buildingApps.html @@ -40,6 +40,7 @@ + @@ -128,11 +129,6 @@
  • 5. Requirements
  • 6. Bugs & Feature Requests
-

Damage and Loss DB

-

Technical Manual

  • 1. Technical Manual
  • @@ -216,7 +212,7 @@
    -

    2.2.8. Building Applications

    +

    2.2.8. Building Applications

    The building application creates building information model (BIM) files for each building. It takes as input the range of asset IDs selected for simulation (expressed as “min” and “max” ID, specified in the configuration file) and the building-specific parameters for each simulation (specified in the building source file). The inputs are parsed into #-BIM.json files in the results folder.

    @@ -235,7 +231,7 @@

    - © Copyright 2023, The Regents of the University of California. + © Copyright 2024, The Regents of the University of California.

    diff --git a/docs/common/developer_manual/architecture/desktop/applications/eventApps.html b/docs/common/developer_manual/architecture/desktop/applications/eventApps.html index 3dbb845f..49ac5446 100644 --- a/docs/common/developer_manual/architecture/desktop/applications/eventApps.html +++ b/docs/common/developer_manual/architecture/desktop/applications/eventApps.html @@ -40,6 +40,7 @@ + @@ -128,11 +129,6 @@
  • 5. Requirements
  • 6. Bugs & Feature Requests
-

Damage and Loss DB

-

Technical Manual

  • 1. Technical Manual
  • @@ -229,7 +225,7 @@
    -

    2.2.3. Event Applications

    +

    2.2.3. Event Applications

    The event application takes the event(s) selected for a building site, associates each one with a simulation, and creates EVENT files containing the event intensity measures. It obtains the name of the event from the BIM file and the intensity measure information from the input event files. This input information is saved in an EVENT.json file, located in its corresponding simulation working directory.

    @@ -248,7 +244,7 @@

    - © Copyright 2023, The Regents of the University of California. + © Copyright 2024, The Regents of the University of California.

    diff --git a/docs/common/developer_manual/architecture/desktop/applications/modelingApps.html b/docs/common/developer_manual/architecture/desktop/applications/modelingApps.html index e9fcfa2e..a5643cce 100644 --- a/docs/common/developer_manual/architecture/desktop/applications/modelingApps.html +++ b/docs/common/developer_manual/architecture/desktop/applications/modelingApps.html @@ -40,6 +40,7 @@ + @@ -128,11 +129,6 @@
  • 5. Requirements
  • 6. Bugs & Feature Requests
-

Damage and Loss DB

-

Technical Manual

  • 1. Technical Manual
  • @@ -229,7 +225,7 @@
    -

    2.2.4. Modeling Applications

    +

    2.2.4. Modeling Applications

    The modeling application consolidates information on the structural analysis model (SAM) used to represent the building on each site. It takes as input the BIM file, the EVENT file, and information on the structural model used for response simulation, specified in the configuration file. The input structural model information is parsed into a SAM.json file, located in its corresponding simulation working directory.

    @@ -249,7 +245,7 @@

    - © Copyright 2023, The Regents of the University of California. + © Copyright 2024, The Regents of the University of California.

    diff --git a/docs/common/developer_manual/architecture/desktop/applications/preprocFEM.html b/docs/common/developer_manual/architecture/desktop/applications/preprocFEM.html index 338cd321..10b02ac2 100644 --- a/docs/common/developer_manual/architecture/desktop/applications/preprocFEM.html +++ b/docs/common/developer_manual/architecture/desktop/applications/preprocFEM.html @@ -40,6 +40,7 @@ + @@ -128,11 +129,6 @@
  • 5. Requirements
  • 6. Bugs & Feature Requests
-

Damage and Loss DB

-

Technical Manual

-

Damage and Loss DB

-

Technical Manual

  • 1. Technical Manual
  • @@ -216,7 +212,7 @@
    -

    2.2.2. UQ Pre-processors

    +

    2.2.2. UQ Pre-processors

    @@ -362,7 +358,7 @@

    - © Copyright 2023, The Regents of the University of California. + © Copyright 2024, The Regents of the University of California.

    diff --git a/docs/common/developer_manual/architecture/desktop/applications/regionalMapApps.html b/docs/common/developer_manual/architecture/desktop/applications/regionalMapApps.html index b8f0727c..f8579d28 100644 --- a/docs/common/developer_manual/architecture/desktop/applications/regionalMapApps.html +++ b/docs/common/developer_manual/architecture/desktop/applications/regionalMapApps.html @@ -40,6 +40,7 @@ + @@ -128,11 +129,6 @@
  • 5. Requirements
  • 6. Bugs & Feature Requests
-

Damage and Loss DB

-

Technical Manual

  • 1. Technical Manual
  • @@ -216,7 +212,7 @@
    -

    2.2.10. Regional Mapping Applications

    +

    2.2.10. Regional Mapping Applications

    The regional mapping application selects events for each building site. The number of events is specified by the user in the configuration file under “samples”. For the set of candidate events, event files must be provided by the user in the input_data/records folder. @@ -237,7 +233,7 @@

    - © Copyright 2023, The Regents of the University of California. + © Copyright 2024, The Regents of the University of California.

    diff --git a/docs/common/developer_manual/architecture/desktop/applications/simulationApps.html b/docs/common/developer_manual/architecture/desktop/applications/simulationApps.html index 536c2e1d..ac706672 100644 --- a/docs/common/developer_manual/architecture/desktop/applications/simulationApps.html +++ b/docs/common/developer_manual/architecture/desktop/applications/simulationApps.html @@ -40,6 +40,7 @@ + @@ -128,11 +129,6 @@
  • 5. Requirements
  • 6. Bugs & Feature Requests
-

Damage and Loss DB

-

Technical Manual

  • 1. Technical Manual
  • @@ -229,7 +225,7 @@
    -

    2.2.6. Simulation Applications

    +

    2.2.6. Simulation Applications

    The simulation application specifies parameters and executes the script for the response simulation. These parameters may include the integrator scheme, convergence tolerance, step size, etc. of the numerical analysis. It takes as input the BIM file, the EVENT file, the SAM file, and the EDP file. After response simulation is completed, the EDP.json file is populated with the resulting EDPs and saved in the simulation working directory. Note that the SIM.json file is not saved in the directory.

    @@ -249,7 +245,7 @@

    - © Copyright 2023, The Regents of the University of California. + © Copyright 2024, The Regents of the University of California.

    diff --git a/docs/common/developer_manual/architecture/desktop/architecture.html b/docs/common/developer_manual/architecture/desktop/architecture.html index 2f11c249..2ad791dd 100644 --- a/docs/common/developer_manual/architecture/desktop/architecture.html +++ b/docs/common/developer_manual/architecture/desktop/architecture.html @@ -40,6 +40,7 @@ + @@ -128,11 +129,6 @@
  • 5. Requirements
  • 6. Bugs & Feature Requests
-

Damage and Loss DB

-

Technical Manual

  • 1. Technical Manual
  • @@ -218,13 +214,13 @@
    -

    2. Software Architecture

    +

    2. Software Architecture

    The EE-UQ app is one of the SimCenter’s computational applications, which are scientific workflow systems that execute a sequence of computational tasks specialized for natural hazard engineering (NHE) problems. In contrast to more general-purpose scientific workflow systems (such as Taverna, Kepler, and Pegasus), SimCenter workflow systems include the following features:

    • access to high-performance computing resources, available on the cloud through DesignSafe, to enable parallel workflows for non-trivial large-scale NHE problems;

    • uncertainty quantification capabilities using Dakota, which allows users to introduce input uncertainties that are propagated through the workflow with random variables;

    • -
    • streamlined interfaces between existing software applications and datasets that are widely used by the NHE community, such as OpenFOAM, OpenSees, ADCIRC, and PEER Strong Ground Motion Databases. To do this, the SimCenter develops pre- and post-processors for these existing applications and utilizes web technologies for accessing online services;

    • +
    • streamlined interfaces between existing software applications and datasets that are widely used by the NHE community, such as OpenFOAM, OpenSees, ADCIRC, and PEER Strong Ground Motion Databases. To do this, the SimCenter develops pre- and post-processors for these existing applications and utilizes web technologies for accessing online services;

    • additional custom software applications produced by the SimCenter. Among these are applications that automate the acquisition of building inventory data (BRAILS), applications that simulate hazard events and generate corresponding input files for passing through the workflow system (RegionalEvent Applications), applications for damage and loss assessment (pelicun), and more.

    • a modular framework that allows developers to incorporate their own software applications as components to the workflow system, so long as it meets the input-output structure at component interfaces.

    @@ -246,9 +242,9 @@

    Within the natural hazards engineering community, there exist several widely used open-source applications, e.g., OpenFOAM, and online datasets, e.g., PEER NGA, that researchers are currently using. Consequently, and to avoid duplication, SimCenter applications incorporate many widely used applications, e.g., OpenFOAM. To do this, SimCenter develops pre- and post-processors for these existing applications and utilizes web technologies for accessing online services.

    -
    +
    ../../../../_images/SimCenterFramework.png -

    Fig. 2.9 SimCenter Software Framework

    +

    Fig. 2.9 SimCenter Software Framework

    The SimCenter scientific workflow systems aim to facilitate the use, reuse, and extension of common workflows encountered in NHE by a broad range of natural hazards engineering researchers with varying software skills. This chapter presents the software architecture for the SimCenter framework and EE-UQ app using the C4 model to encourage this use and adoption. The C4 model is a graphical approach for documenting software architecture through diagrams describing and communicating the software architecture at various levels of abstraction. It is a top-down approach that starts at a high level (level 1), showing how a user would interact with the software, and drills down through three more levels, with level 4 containing the typical UML diagrams. The C4 model was chosen to provide NHE researchers with a diverse range of software architecture knowledge to understand the software architecture behind SimCenter applications that fit their skill level. The four levels:

      @@ -270,30 +266,30 @@
    -

    2.4. Overview

    +

    2.4. Overview

    A Level 1 diagram showing the system context for the SimCenter applications, i.e., how it fits in the world, is shown in Fig. 2.4.1. It shows SimCenter applications (EE-UQ, WE-UQ, HydroUQ, PBE, R2D) as a box in the center surrounded by the user and the user’s systems. The SimCenter applications allow a user to create and run scientific workflow applications; the data for the applications may be obtained from the web or DataDepot. The workflow applications are run on either the local desktop or on some HPC at DesignSafe.

    -
    +
    ../../../../_images/context.png -

    Fig. 2.4.1 System context diagram for SimCenter applications.

    +

    Fig. 2.4.1 System context diagram for SimCenter applications.

    Given how SimCenter applications fit in with the environment, a level 2 diagram demonstrates how the SimCenter applications are broken into high-level components. The SimCenter applications are, as shown in Fig. 2.4.2, split into two components: A front-end UI and a back-end application that runs the workflow. The front-end applications are desktop applications written using the cross-platform Qt framework. The back end is an application that processes the input from the front end, which comes in the form of a JSON file, creates a workflow, and runs it. The workflow applications, written in Python, C, or C++, utilize existing applications where possible and run on either the local desktop machine or on an HPC utilizing resources made available to the NHE community through DesignSafe.

    -
    +
    ../../../../_images/container.png -

    Fig. 2.4.2 System container diagram for SimCenter applications.

    +

    Fig. 2.4.2 System container diagram for SimCenter applications.

    Two level 3 diagrams are now presented, which break up the two containers into the major building blocks or components in C4 terminology. In Fig. 2.4.3, the component diagram for the front-end UI is presented. It outlines the interaction between the user and the individual graphical elements (widgets) of the UI. Given the jigsaw puzzle analogy, the user selects which piece of the jigsaw puzzle they are working on in the component selection widget. The widget for the jigsaw piece will then be displayed on the desktop. The user for each jigsaw piece then selects which application to run for that piece. For the chosen application, they provide the inputs. When the inputs are all provided, the user can choose to run the simulations locally or remotely. For jobs that run remotely, the user can download and review previously run simulations. As seen, the widgets may subsequently interact with web services through HTTPS requests or with DesignSafe utilizing TAPIS Restful API through the RemoteService container.

    -
    +
    ../../../../_images/componentFront.png -

    Fig. 2.4.3 Component diagram for front-end UI.

    +

    Fig. 2.4.3 Component diagram for front-end UI.

    The component diagram for the back-end application shown in Fig. 2.4.4, shows that the back-end comprises several component applications. The application femUQ.py is the application that parses the input from the front end, sets up the workflow by creating a workflow_driver script and then launches the UQ engine. The choice of UQ Engine and applications to run in the workflow is determined from the data passed from the UI and information contained in a file, WorkflowApplication.json. The WorkflowApplication.json file is a file that maps the applications specified in the output from the UI with a specific application contained on the users’ local machine or at the remote HPC resource, as such it allows the researchers to modify the applications that may be run in the workflow w/o the need to recompile the application. Once the workflow_driver file is created, control is passed to a UQ engine, which repeatedly runs the workflow_driver to generate the results. In running the workflow, some of the applications will invoke applications not developed to meet the API. For such applications, pre- and post-processors are provided. The figure shows the back-end application running locally or remotely on an HPC at DesignSafe.

    -
    +
    ../../../../_images/componentBack.png -

    Fig. 2.4.4 Component diagram for Backend Application.

    +

    Fig. 2.4.4 Component diagram for Backend Application.

    Note

    @@ -319,18 +315,18 @@

    2.4. Overview

    The femUQ application will notify the UI that it is done.

  • The UI will read the results and present them to the user.

  • -
    +
    ../../../../_images/sequenceLocal.png -

    Fig. 2.4.5 Sequence diagram showing what happens when a Workflow runs Locally

    +

    Fig. 2.4.5 Sequence diagram showing what happens when a Workflow runs Locally

    That is for the case where the computations are performed on the local computer. When the computations are performed remotely, the steps are different. The first 8 steps are the same. But now, the UQwrapper will not start the UQ engine. Instead, control is returned to the UI. The UI will, as shown in the following: (11) Compress the temporary folder. (12) Send the compressed folder to the remote HPC, shown in Fig. 2.4.6. (13) Start an application to perform the computations. All the remote data transfer and application invocation is down through a cloud service. The TACC tapis interface is used to provide SimCenter users with access to the TACC HPC resources through the DesignSafe portal.

    -
    +
    ../../../../_images/sequenceRemote.png -

    Fig. 2.4.6 Sequence diagram showing what happens when a Workflow runs Remotely

    +

    Fig. 2.4.6 Sequence diagram showing what happens when a Workflow runs Remotely

    @@ -345,7 +341,7 @@

    2.4. Overview

    - © Copyright 2023, The Regents of the University of California. + © Copyright 2024, The Regents of the University of California.

    diff --git a/docs/common/developer_manual/architecture/desktop/architectureLevel4.html b/docs/common/developer_manual/architecture/desktop/architectureLevel4.html index 10c832e3..48fb6993 100644 --- a/docs/common/developer_manual/architecture/desktop/architectureLevel4.html +++ b/docs/common/developer_manual/architecture/desktop/architectureLevel4.html @@ -40,6 +40,7 @@ + @@ -126,11 +127,6 @@
  • 5. Requirements
  • 6. Bugs & Feature Requests
-

Damage and Loss DB

-

Technical Manual

  • 1. Technical Manual
  • @@ -210,7 +206,7 @@
    -

    Software Architecture

    +

    Software Architecture

    The SimCenter is developing a software framework for building scientific workflow applications to perform computational; simulations in the field of NHE at both building level scale and regionsl scale. It is releasing a number of applications built using this framework. The EE-UQ app is one of those applications which have been released (EE-UQ, WE-UQ, PBE). Other applications are under development (R2D). The applications that the SimCenter is developing are limited scientific workflow systems. This chapter presents the software architecture for the framework and the EE-UQ app built using it using the C4 model.

    Note

    @@ -221,7 +217,7 @@
    -

    Level 1: A Context for SimCenter Applications

    +

    Level 1: A Context for SimCenter Applications

    A Level 1 diagram showing the system context for the SimCenter applications, i.e. how it fits in the world, is shown in figContext. It shows SimCenter applications (EE-UQ, WE-UQ, PBE, R2D) as a box in the center surrounded by the user and the systems it and the user interact with. The SimCenter applications allow users to create and run scientific workflow applications, the data for the applications may be obtained from the web or DataDepot, and the workflow applications are run on either the local desktop or on some HPC at DesignSafe.

    ../../../../_images/context.png @@ -229,21 +225,21 @@

    Level 1: A Context for SimCenter Applications -

    Level 2: The Components of a SimCenter Application

    -

    Given how SimCenter applications fit in with the environment, a level 2 diagram now demonstrates how the SimCenter applications are broken into high-level components. The SimCenter applications are, as shown in Fig. 2.3.2.2, broken into two components: A front-end UI and a back-end application that runs the workflow. The front-end applications are desktop applications written using the cross-platform Qt framework. The back end is an application that processes the input from the front end, which comes in the form of a JSON file, creates a workflow and runs it. The workflow applications, written in Python, C, or C++, utilize existing applications where possible and run on either the local desktop machine or on an HPC utilizing resources made available to NHE community through DeisignSafe.

    +

    Level 2: The Components of a SimCenter Application

    +

    Given how SimCenter applications fit in with the environment, a level 2 diagram now demonstrates how the SimCenter applications are broken into high-level components. The SimCenter applications are, as shown in figContainer, broken into two components: A front-end UI and a back-end application that runs the workflow. The front-end applications are desktop applications written using the cross-platform Qt framework. The back end is an application that processes the input from the front end, which comes in the form of a JSON file, creates a workflow and runs it. The workflow applications, written in Python, C, or C++, utilize existing applications where possible and run on either the local desktop machine or on an HPC utilizing resources made available to NHE community through DeisignSafe.

    ../../../../_images/container.png

    System container diagram for SimCenter applications.

    -

    Level 3: Container Diagrams for the Front and Back End Components

    -

    Two level 3 diagrams are now presented which break up the two containers into the major building blocks or components in C4 terminology. In Fig. 2.3.3.2 the component diagram for the front-end UI is presented. It outlines the interaction between the user and the individual graphical elements (widgets) of the UI. Given the analogy of a jigsaw puzzle, the user selects which piece of the jigsaw puzzle they are working on in the component selection widget. The widget for the jigsaw piece will then be displayed on the desktop. The user for each jigsaw piece then selects which application to run for that piece, and for the chosen application, they provide the inputs. When the inputs are all provided, the user can select to run the simulations locally or remotely. For jobs that run remotely, the user can download and review previously run simulations. As seen the widgets may subsequently interact with web services through HTTPS requests, or with DesignSafe utilizing TAPIS Restful API through the RemoteService container.

    +

    Level 3: Container Diagrams for the Front and Back End Components

    +

    Two level 3 diagrams are now presented which break up the two containers into the major building blocks or components in C4 terminology. In figComponentFront the component diagram for the front-end UI is presented. It outlines the interaction between the user and the individual graphical elements (widgets) of the UI. Given the analogy of a jigsaw puzzle, the user selects which piece of the jigsaw puzzle they are working on in the component selection widget. The widget for the jigsaw piece will then be displayed on the desktop. The user for each jigsaw piece then selects which application to run for that piece, and for the chosen application, they provide the inputs. When the inputs are all provided, the user can select to run the simulations locally or remotely. For jobs that run remotely, the user can download and review previously run simulations. As seen the widgets may subsequently interact with web services through HTTPS requests, or with DesignSafe utilizing TAPIS Restful API through the RemoteService container.

    ../../../../_images/componentFront.png

    Component diagram for front-end UI.

    -

    The component diagram for the backend application shown in Fig. 2.3.3.3, shows that the backend is made up of several components, all applications. The application femUQ.py is the application that parses the input from the front end, sets up the workflow and launches the UQ engine. Which UQ Engine and which applications to run in the workflow, is determined from the data passed from the UI and information contained in a WorkflowApplication.json file. A file is used to allow the researchers to modify the applications that may be run in the workflow w/o the need to recompile the application. Control is then passed to a UQ Engine, which repeatedly runs the workflow to generate the results. In running the workflow some of the applications will invoke applications not developed to meet the API. For such applications, pre- and post-processors are provided. +

    The component diagram for the backend application shown in figComponentBack, shows that the backend is made up of several components, all applications. The application femUQ.py is the application that parses the input from the front end, sets up the workflow and launches the UQ engine. Which UQ Engine and which applications to run in the workflow, is determined from the data passed from the UI and information contained in a WorkflowApplication.json file. A file is used to allow the researchers to modify the applications that may be run in the workflow w/o the need to recompile the application. Control is then passed to a UQ Engine, which repeatedly runs the workflow to generate the results. In running the workflow some of the applications will invoke applications not developed to meet the API. For such applications, pre- and post-processors are provided. The figure shows the backend application running locally or remotely on an HPC@DesignSafe.

    ../../../../_images/componentBack.png @@ -251,7 +247,7 @@

    Level 3: Container Diagrams for the Front and Back End Components -

    Level 4 UML Diagrams

    +

    Level 4 UML Diagrams

    A number of diagrams are presented for the level 4 diagrams. These are mostly UML diagrams showing how the applications are built. The SimCenter releases a number of front-end applications: EE-UQ shown in figUmlEE, WE-UQ shown in figUmlWE, and PBE shown in figUmlPBE. These applications share code with each other and other SimCenter applications. As a consequence, the common code is bundled into a number of shared packages: EarthquakeEvents shown in figUmlEarthquakeEvents, WindEvents shown in figUmlWindEvents, and SimCenterCommon shown in figUmlCommon. A number of packages were chosen over placing all common code inside a single package to simplify development efforts for outside programmers (whom it is envisioned will mostly be adding new event components) and to reduce the overhead of package management and compile time for SimCenter programmers. UML diagrams are presented for these front-end applications and shared packages. THE UML diagrams that are presented are not exhaustive, in that they do not show all classes used, for it was decided not to for example show the myriad of Line edits, labels, spin boxes, etc. that make up the widgets. What is shown is sufficient to present the SimCenter architecture.

    While there are a number of different types of UML diagrams, those shown in this document will be limited to class diagrams and sequence diagrams. SimCenter applications are object-oriented in nature. An object-oriented program consists of objects interacting with one another, with each object being of a certain type or class. A class diagram shows the classes, their attributes and methods, and the relationships between the classes. A sequence diagram or event diagram shows the order in which objects interact. To understand the SimCenter framework it is useful to first present the main() function for a SImCenter application, in this case, EE-UQ, shown in codeMainCode. The code presented is a stripped-down version of the actual code, code for dealing with style sheets, analytics, etc. is not shown as it is not pertinent to understanding the software architecture.

    int main(int argc, char *argv[]) {
    @@ -304,7 +300,7 @@ 

    Level 4 UML Diagrams

    As was mentioned the Front end UI applications are built using Qt. In a Qt application, the programmer creates a QApplication object, in codeMainCode the object named app and a QMainWindow, in the example named window. As will be shown in figUmlCommon, MainWindowWorkflowApp is a type of QMainWindow that is used in all SimCenter research applications as it deals with all the application menu items, e.g. File open and close, Help cites, etc. The QMainWindowWorkflowApp is a SImCenter class that contains a single QWidget of type WorkflowAppWidget. The WorkflowAppWidget object is passed a RemoteService, the remote cloud service that the application will interact with. This RemoteService is placed in its own QThread object, so that the UI can respond to user requests while communication with the cloud service is underway. Once the window object is shown, control is passed to the QApplication until the user is done.

    -

    UML EE-UQ

    +

    UML EE-UQ

    EE-UQ is an application to determine the response of a building subjected to an earthquake event. As shown in figumlEE it comprises a component selection that presents the user with a number of components, jigsaw pieces, which include: earthquake event (EarthquakeEventSelection), UQ engine (UQ Selection), demand parameters of interns (EDP Selection), building information model (BIM Selection), structural analysis model generator (SAM Selection), finite element application (FEM Selection), and RandomVariableContainer. RandomVariableContainer is a widget allowing user to specify distributions associated with the random variables created by a user. As will be seen in figUmlEarthquakeEvents and figUmlCommon each component offers the user a number of applications to choose from for that component. Other classes corresponding to widgets presented in the Front end UI include: UQ Result for displaying the results, Local and Remote Services for running the job locally or remotely, Remote job Manager for monitoring job status and retrieving old jobs, and Login for obtaining credentials from DesignSafe to access and run jobs on the HPC resources. All communication between the applications and DesignSafe-ci is through the Application Service. This is done to allow the applications to switch to other cloud service providers, possibly allowing applications to run at DesignSafe, on Amazon EC-2, IBM’s Azure or elsewhere.

    ../../../../_images/umlEE.png @@ -312,7 +308,7 @@

    Level 4 UML Diagrams

    -

    UML WE-UQ

    +

    UML WE-UQ

    Similar in construction to EE-UQ is WE-UQ, as shown in figure figumlWE. In fact, the only difference is that Wind Event Selection is present in the component selection, instead of Earthquake Events. The wind event applications, as will be shown in figWindEvents include stochastic wind models, wind loading from online services such as Vortex-Winds, applications that take online wind tunnel experimental datasets such as those from Tokyo Polytechnic.

    @@ -322,7 +318,7 @@

    Level 4 UML Diagrams

    -

    UML PBE

    +

    UML PBE

    PBE is a tool for performance-based engineering. Given a building and an event, it will calculate downtime and loss estimates. As can be seen in figumlPBE, it adds a LossModelSelection to the component Selections available in EE-UQ. The Loss Model applications currently available for selection include a P58 Loss Model and a HAZUS Loss Model. Depending on selection, different widgets are presented for the user to input the different input arguments needed for the different loss model calculations. Presently the calculations for both loss models are performed by the same Python script, CalculateDL.py, in the collection of backend applications.

    @@ -331,7 +327,7 @@

    Level 4 UML Diagrams

    -

    UML EarthquakeEvents

    +

    UML EarthquakeEvents

    The Earthquake Events package, as shown in figumlEarthquakeEvents, contains an Earthquake Event selector with several Earthquake Event selections available. The selections include options that interface with the NGA west server directly and options that will collect inputs for stochastic input models of Vlachos et Al or Dabahi and DerKiuerghian, peer NGA records, site response and our SimCenterEvent format. Each of these widgets corresponds to one application in the backend, e.g. RockOutcrop corresponds to SiteResponse, and it is this application that will run when the workflow runs.

    ../../../../_images/umlEarthquakeEvents.png @@ -339,7 +335,7 @@

    Level 4 UML Diagrams

    -

    UML WindEvents

    +

    UML WindEvents

    Similar to the Earthquake Events package, the wind events package shown in figumlWindEvents, contains a WInd Event Selector with a number of Wnd Event selections available. The selections include options for stochastically generated wind events, events that obtain wind loading from the vortex-winds server, and options to obtain forces from wind tunnel events, either from the Tokyo Polytechnic University database or a user-supplied file.

    ../../../../_images/umlWindEvents.png @@ -347,7 +343,7 @@

    Level 4 UML Diagrams

    -

    SimCenterCommon

    +

    SimCenterCommon

    SimCenter common shown in figUmlCommon contains a number of component selections, BIM selection, EDP Selection, SAM Selection, FEM Selection and UQ Engine Selection. Each contains a number of options. The components and their options are all subclasses of the SImCenterAppWidget class, The SImCenterAppWidget has methods to output and input from a JSON object. SimCenterCommon also contains the RandomVariablesContainer class, each object being a container for several RandomVariables. Each RansomVariable has a name and a RandomVariable Distribution associated with it. Types of RandomVariableDistributions include for example Normal, Lognormal, Uniform, Beta, and Gumbel.

    ../../../../_images/umlCommon.png @@ -355,7 +351,7 @@

    Level 4 UML Diagrams

    -

    SimCenter Backend Applications

    +

    SimCenter Backend Applications

    The BackendApplications are currently all in a single package. These are the applications that perform the numerical computations when the workflow runs. Some of these applications rely on external applications, websites, and external packages. The external applications, web services, and libraries are as shown in figAppDiagramBackend.

    diff --git a/docs/common/developer_manual/architecture/desktop/backendApplications.html b/docs/common/developer_manual/architecture/desktop/backendApplications.html index e44eb13f..6bf7acdb 100644 --- a/docs/common/developer_manual/architecture/desktop/backendApplications.html +++ b/docs/common/developer_manual/architecture/desktop/backendApplications.html @@ -40,6 +40,7 @@ + @@ -128,11 +129,6 @@
  • 5. Requirements
  • 6. Bugs & Feature Requests
-

Damage and Loss DB

-

Technical Manual

-

Damage and Loss DB

-

Technical Manual

  • 1. Technical Manual
  • @@ -226,42 +222,43 @@
    -

    2.3. C4 Model of Software Architecture

    +

    2.3. C4 Model of Software Architecture

    The SimCenter workflow systems are aimed at facilitating the use, reuse and extension of common workflows encountered in NHE by a broad range of natural hazards engineering researchers with varying levels of software skills. In order to encourage this use and adoption, this chapter presents the software architecture for the SimCenter framework and EE-UQ app using the C4 model. The C4 model is a graphical approach for documenting software architecture through diagrams that describe and communicate the software architecture at different levels of abstraction. It is a top-down approach that starts at a high level (level 1) showing how a user would interact with the software and drills down through three more levels, with level 4 containing the typical UML diagrams. The choice of the C4 model was made to provide NHE researchers with a diverse range of software architecture knowledge and an understanding of the software architecture behind SimCenter applications that fit their skill level. The four levels:

    -

    2.3.1. Level 1: Context Diagram

    -

    A Level 1 diagram in figContext shows the system context for the SimCenter applications, i.e. how it fits in the world. In the diagram: +

    2.3.1. Level 1: Context Diagram

    +

    A Level 1 diagram in Fig. 2.3.1.2 shows the system context for the SimCenter applications, i.e. how it fits in the world. In the diagram: - the SimCenter computational applications (EE-UQ, WE-UQ, PBE, R2D) are shown in the center surrounded by the user and the systems it interacts with. - input data for the SimCenter applications can be obtained either from NHERI datasets accessible on the DesignSafe Data Depot, shown to the right, or from web-based databases, shown to the left. - the SimCenter applications can then be run in conjunction with open-source software applications (such as Dakota, FEAP, OpenSees, Python, OpenFOAM, etc.) either on a local desktop, shown below, or using HPC resources on DesignSafe, shown to the right.

    -
    +
    ../../../../_images/context.png -

    Fig. 2.3.1.2 System context diagram for SimCenter applications.

    +

    Fig. 2.3.1.2 System context diagram for SimCenter applications.

    -

    2.3.2. Level 2: Container Diagram

    -

    A Level 2 diagram in Fig. 2.3.2.2 demonstrates how the SimCenter applications are broken into high-level containers (applications, databases, etc.). Each of the SimCenter applications is broken into two components: A front-end UI and a back-end application that runs the workflow. The front-end is a desktop application written using the cross-platform Qt framework. The back-end is an application that processes the input from the front-end, which comes in the form of a JSON file, creates a workflow and runs it. The workflow applications, written in Python, C, or C++, utilize existing applications where possible and run on either the local desktop machine or on an HPC utilizing resources made available to NHE community through DesignSafe.

    -
    +

    2.3.2. Level 2: Container Diagram

    +

    A Level 2 diagram in Fig. 2.3.2.2 demonstrates how the SimCenter applications are broken into high-level containers (applications, databases, etc.). Each of the SimCenter applications is broken into two components: A front-end UI and a back-end application that runs the workflow. The front-end is a desktop application written using the cross-platform Qt framework. The back-end is an application that processes the input from the front-end, which comes in the form of a JSON file, creates a workflow and runs it. The workflow applications, written in Python, C, or C++, utilize existing applications where possible and run on either the local desktop machine or on an HPC utilizing resources made available to NHE community through DesignSafe.

    +
    ../../../../_images/container.png -

    Fig. 2.3.2.2 System container diagram for SimCenter applications.

    +

    Fig. 2.3.2.2 System container diagram for SimCenter applications.

    -

    2.3.3. Level 3: Component Diagram

    -

    Two level 3 diagrams are now presented which break up the two containers into the major building blocks or components in C4 terminology. In Fig. 2.3.3.2 the component diagram for the front-end UI is presented. It outlines the interaction between the user and the individual graphical elements (widgets) of the UI. Given the analogy of a jigsaw puzzle, the user selects which piece of the jigsaw puzzle they are working on in the component selection widget. The widget for the jigsaw piece will then be displayed on the desktop. The user for each jigsaw piece then selects which application to run for that piece, and for the chosen application, they provide the inputs. When the inputs are all provided, the user can select to run the simulations locally or remotely. For jobs that run remotely, the user can download and review previously run simulations. As seen the widgets may subsequently interact with web services through HTTPS requests, or with DesignSafe utilizing TAPIS Restful API through the RemoteService container.

    -
    +

    2.3.3. Level 3: Component Diagram

    +

    Two level 3 diagrams are now presented which break up the two containers into the major building blocks or +components in C4 terminology. In Fig. 2.3.3.2 the component diagram for the front-end UI is presented. It outlines the interaction between the user and the individual graphical elements (widgets) of the UI. Given the analogy of a jigsaw puzzle, the user selects which piece of the jigsaw puzzle they are working on in the component selection widget. The widget for the jigsaw piece will then be displayed on the desktop. The user for each jigsaw piece then selects which application to run for that piece, and for the chosen application, they provide the inputs. When the inputs are all provided, the user can select to run the simulations locally or remotely. For jobs that run remotely, the user can download and review previously run simulations. As seen the widgets may subsequently interact with web services through HTTPS requests, or with DesignSafe utilizing TAPIS Restful API through the RemoteService container.

    +
    ../../../../_images/componentFront.png -

    Fig. 2.3.3.2 Component diagram for front end UI.

    +

    Fig. 2.3.3.2 Component diagram for front end UI.

    -

    The component diagram for the backend application shown in Fig. 2.3.3.3, shows that the backend is made up of a number of component applications. The application femUQ.py is the application that parses the input from the front end, sets up the workflow by creating a workflow_driver script and then launches the UQ engine. Which UQ Engine and which applications to run in the workflow, is determined from the data passed from the UI and information contained in a file, WorkflowApplication.json. The WorkflowApplication.json file is a file that maps the applications specified in the output from the UI with a specific application contained on the user’s local machine or at the remote HPC resource, as such it allows the researchers to modify the applications that may be run in the workflow w/o the need to recompile the application. Once the workflow_driver file is created, control is passed to a UQ engine, which repeatedly runs the workflow_driver to generate the results. In running the workflow some of the applications will invoke applications not developed to meet the API. For such applications, pre- and post-processors are provided. The figure shows the backend application running locally or remotely on an HPC at DesignSafe.

    -
    +

    The component diagram for the backend application shown in Fig. 2.3.3.3, shows that the backend is made up of a number of component applications. The application femUQ.py is the application that parses the input from the front end, sets up the workflow by creating a workflow_driver script and then launches the UQ engine. Which UQ Engine and which applications to run in the workflow, is determined from the data passed from the UI and information contained in a file, WorkflowApplication.json. The WorkflowApplication.json file is a file that maps the applications specified in the output from the UI with a specific application contained on the user’s local machine or at the remote HPC resource, as such it allows the researchers to modify the applications that may be run in the workflow w/o the need to recompile the application. Once the workflow_driver file is created, control is passed to a UQ engine, which repeatedly runs the workflow_driver to generate the results. In running the workflow some of the applications will invoke applications not developed to meet the API. For such applications, pre- and post-processors are provided. The figure shows the backend application running locally or remotely on an HPC at DesignSafe.

    +
    ../../../../_images/componentBack.png -

    Fig. 2.3.3.3 Component diagram for Backend Application.

    +

    Fig. 2.3.3.3 Component diagram for Backend Application.

    -

    2.3.4. Level 4: Code Diagram

    +

    2.3.4. Level 4: Code Diagram

    To facilitate the development of the different SimCenter applications and to encourage their reuse and extension by other NHE researchers, the SimCenter is providing the NHE community with a software framework for building such applications. From this framework, the SimCenter is building the applications, of which EE-UQ app is but one, that it releases. These individual applications are built from the components of the framework. The components of the SimCenter are grouped, as shown in the figure below, into the following components:

    1. Cloud: applications/libraries for communicating with remote web services to launch and monitor applications on HPC resources and to upload and download files from the filesystems of such resources.

    2. @@ -296,14 +293,17 @@

      2.3.4. Level 4: Code Diagram +
      ../../../../_images/sequenceLocal.png -

      Fig. 2.3.4.2 Sequence diagram showing what happens when a workflow runs locally.

      +

      Fig. 2.3.4.2 Sequence diagram showing what happens when a workflow runs locally.

      -

      That is for the case where the computations are performed on the local computer. When the computations are performed remotely the steps are different. The first 8 steps are the same. But now the UQwrapper will not start the UQ engine. Instead, control is returned to the UI. The UI will, as shown in the following: (11) Compress the temporary folder. (12) Send the compressed folder to the remote HPC, shown in Fig. 2.3.4.3. (13) Start an application to perform the computations. All the remote data transfer and application invocation is down through a cloud service. The TACC tapis interface is used to provide SimCenter users with access to the TACC HPC resources through the DesignSafe portal.

      -
      +

      That is for the case where the computations are performed on the local computer. When the computations are +performed remotely the steps are different. The first 8 steps are the same. But now the UQwrapper will not +start the UQ engine. Instead, control is returned to the UI. The UI will, as shown in the following: (11) +Compress the temporary folder. (12) Send the compressed folder to the remote HPC, shown in Fig. 2.3.4.3. (13) Start an application to perform the computations. All the remote data transfer and application invocation is down through a cloud service. The TACC tapis interface is used to provide SimCenter users with access to the TACC HPC resources through the DesignSafe portal.

      +
      ../../../../_images/sequenceRemote.png -

      Fig. 2.3.4.3 Sequence diagram showing what happens when a workflow runs remotely.

      +

      Fig. 2.3.4.3 Sequence diagram showing what happens when a workflow runs remotely.

    @@ -318,7 +318,7 @@

    2.3.4. Level 4: Code Diagram

    - © Copyright 2023, The Regents of the University of California. + © Copyright 2024, The Regents of the University of California.

    diff --git a/docs/common/developer_manual/architecture/desktop/dynamicDiagrams.html b/docs/common/developer_manual/architecture/desktop/dynamicDiagrams.html index f13376fc..e42feb28 100644 --- a/docs/common/developer_manual/architecture/desktop/dynamicDiagrams.html +++ b/docs/common/developer_manual/architecture/desktop/dynamicDiagrams.html @@ -40,6 +40,7 @@ + @@ -126,11 +127,6 @@
  • 5. Requirements
  • 6. Bugs & Feature Requests
-

Damage and Loss DB

-

Technical Manual

  • 1. Technical Manual
  • @@ -210,7 +206,7 @@
    -

    Level 4 Dynamic Diagrams

    +

    Level 4 Dynamic Diagrams

    To understand better the interactions between the components we will present some C4 dynamic diagrams. The dynamic diagram is similar to a UML communication diagram, which again is similar to a UML sequence diagram although it allows a free-form arrangement of diagram elements with numbered interactions to indicate ordering.

    @@ -224,7 +220,7 @@

    - © Copyright 2023, The Regents of the University of California. + © Copyright 2024, The Regents of the University of California.

    diff --git a/docs/common/developer_manual/architecture/desktop/file-types.html b/docs/common/developer_manual/architecture/desktop/file-types.html index 79566bd7..40394e02 100644 --- a/docs/common/developer_manual/architecture/desktop/file-types.html +++ b/docs/common/developer_manual/architecture/desktop/file-types.html @@ -40,6 +40,7 @@ + @@ -128,11 +129,6 @@
  • 5. Requirements
  • 6. Bugs & Feature Requests
-

Damage and Loss DB

-

Technical Manual

-

Damage and Loss DB

-

Technical Manual

-

Damage and Loss DB

-

Technical Manual

  • 1. Technical Manual
  • @@ -210,7 +206,7 @@
    -

    General Requirements

    +

    General Requirements

    key:
    Source: GC=Needed for Grand Challenges, SP=Senior Personnel, UF=User Feedback
    @@ -222,9 +218,9 @@

    General Requirements

    -

    Loading Requirements

    - - +

    Loading Requirements

    +
    Requirements - Earthquake Loading
    +@@ -401,7 +397,660 @@

    Loading Requirements
    -

    UQ Requirements

    +

    UQ Requirements

    +

    Requirements - Earthquake Loading
    + ++++++++ + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + +
    Requirements - Uncertainty Quantification Methods and Variables

    #

    Description

    Source

    Priority

    Status

    Implementation

    UF.1

    +

    “Ability to use basic Monte Carlo and LHS methods”

    +
    +

    SP

    +

    “M”

    +
    +
    +

    “Implemented”

    +
    +

    _

    UF.2

    +

    “Ability to use Gaussian Process Regression”

    +
    +

    SP

    +

    “M”

    +
    +
    +

    “Implemented”

    +
    +

    _

    UF.3

    +

    “Ability to use Own External UQ Engine”

    +
    +

    SP

    +

    “M”

    +
    +

    _

    _

    UF.4

    +

    “Ability to use Multi-Scale Monte Carlo”

    +
    +

    SP

    +

    “M”

    +
    +

    _

    _

    UF.5

    +

    “Ability to use Multi-Fidelity Models”

    +
    +

    SP

    +

    “M”

    +
    +
    +

    “InProgress”

    +
    +

    _

    UR.1

    +

    “Ability to use First Order Reliability method”

    +
    +

    SP

    +

    “M”

    +
    +
    +

    “Implemented”

    +
    +

    _

    UR.2

    +

    “Ability to use Second Order Reliability method”

    +
    +

    SP

    +

    “M”

    +
    +
    +

    “Implemented”

    +
    +

    _

    UR.3

    +

    “Ability to use Surrogate Based Reliability”

    +
    +

    SP

    +

    “M”

    +
    +
    +

    “Implemented”

    +
    +

    _

    UR.4

    +

    “Ability to use Importance Sampling”

    +
    +

    SP

    +

    “M”

    +
    +
    +

    “Implemented”

    +
    +

    _

    UG.1

    +

    “Ability to obtain Global Sensitivity Sobol indices”

    +
    +

    UF

    +

    “M”

    +
    +
    +

    “Implemented”

    +
    +

    _

    UG.2

    +

    “Ability to use probability model-based global sensitivity analysis (PM-GSA)”

    +
    +

    SP

    +

    “M”

    +
    +
    +

    “Implemented”

    +
    +

    _

    US.1

    +

    “Ability to Construct Gaussian Process (GP) Regression Model from a Simulation Model”

    +
    +

    SP

    +

    “M”

    +
    +
    +

    “InProgress”

    +
    +

    _

    US.2

    +

    “Ability to Construct GP Regression Model from Input-output Dataset”

    +
    +

    SP

    +

    “M”

    +
    +
    +

    “InProgress”

    +
    +

    _

    US.3

    +

    “Ability to use Surrogate Model for UQ Analysis”

    +
    +

    SP

    +

    “M”

    +
    +
    +

    “InProgress”

    +
    +

    _

    US.4

    +

    “Ability to Save the Surrogate Model”

    +
    +

    SP

    +

    “M”

    +
    +
    +

    “InProgress”

    +
    +

    _

    US.5

    +

    “Ability to Use Adaptive Design of Experiments”

    +
    +

    SP

    +

    “M”

    +
    +
    +

    “InProgress”

    +
    +

    _

    US.6

    +

    “Ability to Asses Reliability of Surrogate Model”

    +
    +

    SP

    +

    “M”

    +
    +
    +

    “Implemented”

    +
    +

    _

    US.7

    +

    “Ability to Build Surrogate Under Stochastic Excitation”

    +
    +

    SP

    +

    “M”

    +
    +
    +

    “InProgress”

    +
    +

    _

    US.8

    +

    “Ability to Use Physics-Informed Machine Learning”

    +
    +

    SP

    +

    “M”

    +
    +

    _

    _

    UN.1

    +

    “Ability to use Gauss-Newton solvers for parameter estimation”

    +
    +

    SP

    +

    “M”

    +
    +
    +

    “Implemented”

    +
    +

    _

    UN.2

    +

    “Ability to read calibration data from file”

    +
    +

    UF

    +

    “M”

    +
    +
    +

    “Implemented”

    +
    +

    _

    UN.3

    +

    “Ability to handle non-scalar response quantities”

    +
    +

    UF

    +

    “M”

    +
    +
    +

    “Implemented”

    +
    +

    _

    UB.1

    +

    “Ability to use DREAM algorithm for Bayesian inference”

    +
    +

    SP

    +

    “M”

    +
    +
    +

    “Implemented”

    +
    +

    _

    UB.2

    +

    “Ability to use TMCMC algorithm for Bayesian inference”

    +
    +

    SP

    +

    “M”

    +
    +
    +

    “Implemented”

    +
    +

    _

    UB.3

    +

    “Ability to read calibration data from file”

    +
    +

    UF

    +

    “M”

    +
    +
    +

    “Implemented”

    +
    +

    _

    UB.4

    +

    “Ability to handle non-scalar response quantities”

    +
    +

    UF

    +

    “M”

    +
    +
    +

    “Implemented”

    +
    +

    _

    UB.5

    +

    “Ability to calibrate multipliers on error covariance”

    +
    +

    UF

    +

    “M”

    +
    +
    +

    “Implemented”

    +
    +

    _

    UB.6

    +

    “Ability to use a default log-likelihood function”

    +
    +

    UF

    +

    “M”

    +
    +
    +

    “Implemented”

    +
    +

    _

    UB.7

    +

    “Ability to use Kalman Filtering”

    +
    +

    UF

    +

    “M”

    +
    +

    _

    _

    UB.8

    +

    “Ability to use Particle Filtering”

    +
    +

    UF

    +

    “M”

    +
    +

    _

    _

    UH.1

    +

    “Ability to sample from manifold”

    +
    +

    SP

    +

    “M”

    +
    +
    +

    “Implemented”

    +
    +

    _

    UH.2

    +

    “Ability to build Reduced Order Model”

    +
    +

    SP

    +

    “M”

    +
    +

    _

    _

    UO.1

    +

    “Ability to use User-Specified External UQ Engine”

    +
    +

    SP

    +

    “M”

    +
    +
    +

    “Implemented”

    +
    +

    _

    UO.2

    +

    “Ability to use Own External FEM Application”

    +
    +

    UF

    +

    “M”

    +
    +
    +

    “Implemented”

    +
    +

    _

    UM.1

    +

    Ability to use various Reliability Methods

    +
    +
    +

    _

    +
    +
    +

    _

    +
    +
    +

    _

    +
    +
    +

    _

    +
    +

    UM.1.1

    +

    “Ability to use First Order Reliability method”

    +
    +

    UF

    +

    “M”

    +
    +
    +

    “Implemented”

    +
    +

    _

    UM.1.2

    +

    “Ability to use Surrogate Based Reliability”

    +
    +

    UF

    +

    “M”

    +
    +

    _

    _

    UM.1.3

    +

    “Ability to use Own External Application to generate Results”

    +
    +

    UF

    +

    “M”

    +
    +
    +

    “Implemented”

    +
    +

    _

    UM.2

    +

    Ability to user various Sensitivity Methods

    +
    +
    +

    _

    +
    +
    +

    _

    +
    +
    +

    _

    +
    +
    +

    _

    +
    +

    UM.2.1

    +

    “Ability to obtain Global Sensitivity Sobol’s indices”

    +
    +

    UF

    +

    “M”

    +
    +
    +

    “Implemented”

    +
    +

    _

    key:
    Source: GC=Needed for Grand Challenges, SP=Senior Personnel, UF=User Feedback
    @@ -413,9 +1062,9 @@

    UQ Requirements -

    Modeling Requirements

    - - +

    Modeling Requirements

    +
    Requirements - Modeling
    +@@ -503,9 +1152,9 @@

    Modeling Requirements

    Requirements - Modeling
    - +

    Analysis Requirements

    +
    Requirements - Analysis
    +@@ -614,9 +1263,9 @@

    Analysis Requirements

    Requirements - Analysis
    - +

    RV Requirements

    +
    Requirements - Random Variables
    +@@ -725,7 +1374,455 @@

    RV Requirements -

    Common Research Application Requirements

    +

    Common Research Application Requirements

    +
    Requirements - Random Variables
    + ++++++++ + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + +
    Requirements - CR

    #

    Description

    Source

    Priority

    Status

    Implementation

    CR.1

    +

    Open-source software where developers can test new data and develop algorithms

    +
    +
    +

    _

    +
    +
    +

    _

    +
    +
    +

    _

    +
    +
    +

    _

    +
    +

    CR.1.1

    +

    “Provide open-source applications utilizing code hosting platforms

    +
    +
    +

    e.g. GitHub”

    +
    +

    SP

    +

    “M”

    +
    +
    +

    link

    +
    +

    CR.1.2

    +

    “Assign an open-source licensce that allows free use.”

    +
    +

    SP

    +

    “M”

    +
    +
    +

    “Implemented”

    +
    +
    +

    link

    +
    +

    CR.2

    +

    **Ability of Practicing Engineers to use multiple coupled resources (applications

    +
    +

    databases

    +

    viz tools) in engineering practice**”

    +
    +
    +

    _

    +
    +
    +

    _

    +
    +

    CR.2.1

    +

    “Allow users to launch scientific workflows”

    +
    +

    SP

    +

    “M”

    +
    +
    +

    “Implemented”

    +
    +

    _

    CR.3

    +

    Ability to utilize resources beyond the desktop including HPC

    +
    +
    +

    _

    +
    +
    +

    _

    +
    +
    +

    _

    +
    +
    +

    _

    +
    +

    CR.3.1

    +

    “Allow users to utilize HPC resources at TACC through DesignSafe”

    +
    +

    SP

    +

    “M”

    +
    +
    +

    “Implemented”

    +
    +

    _

    CR.4

    +

    **Efficient use of multiple coupled and linked models requiring sharing and inter-operability of databases

    +
    +

    computing environments

    networks

    visualization tools

    +

    _

    +
    +

    CR.4.1

    +

    “Identify and include external analysis systems”

    +
    +

    SP

    +

    “M”

    +
    +
    +

    “InProgress”

    +
    +

    _

    CR.4.2

    +

    “Identify and include external databases”

    +
    +

    SP

    +

    “M”

    +
    +
    +

    “InProgress”

    +
    +

    _

    CR.4.3

    +

    “Identify and include external viz tools”

    +
    +

    SP

    +

    “M”

    +
    +
    +

    “InProgress”

    +
    +

    _

    CR.4.4

    +

    “Identify and include external computing env”

    +
    +

    SP

    +

    “M”

    +
    +
    +

    “Inprogress”

    +
    +

    _

    CR.5

    +

    Tool available for download from web

    +
    +
    +

    _

    +
    +
    +

    _

    +
    +
    +

    _

    +
    +
    +

    _

    +
    +

    CR.5.1

    +

    “Tool downloadable from DesignSafe website”

    +
    +

    GC

    +

    “M”

    +
    +
    +

    “Implemented”

    +
    +
    +

    link

    +
    +

    CR.6

    +

    Ability to benefit from programs that move research results into practice and obtain training

    +
    +
    +

    _

    +
    +
    +

    _

    +
    +
    +

    _

    +
    +
    +

    _

    +
    +

    CR.6.1

    +

    “Ability to use educational provisions to gain interdisclipinary education so as to gain expertise in earth sciences and physics

    +
    +

    engineering mechanics

    geotechnical engineering

    +

    and structural engineering in order to be qualified to perform these simulations”

    +
    +
    +

    “D”

    +
    +

    CR.6.2

    +

    “Documentation exists demonstrainting application usage”

    +
    +

    SP

    +

    “M”

    +
    +
    +

    “Implemented”

    +
    +

    _

    CR.6.3

    +

    “Video Exists demonstrating application usage”

    +
    +

    SP

    +

    “M”

    +
    +
    +

    “Implemented”

    +
    +

    _

    CR.6.4

    +

    “Tool Training through online and in person training events”

    +
    +

    SP

    +

    “M”

    +
    +
    +

    “Implemented”

    +
    +

    _

    CR.7

    +

    “Verification Examples Exist”

    +
    +

    SP

    +

    “M”

    +
    +
    +

    “Implemented”

    +
    +

    _

    CR.8

    +

    validation of proposed analytical models against existing empirical datasets

    +
    +
    +

    _

    +
    +
    +

    _

    +
    +
    +

    _

    +
    +
    +

    _

    +
    +

    CR.8.1

    +

    “Validation Examples Exist

    +
    +
    +

    validated against tests or other software”

    +
    +

    GC

    +

    “M”

    +
    +
    +

    link

    +
    +

    CR.9

    +

    “Tool to allow user to load and save user inputs”

    +
    +

    SP

    +

    “M”

    +
    +
    +

    “Implemented”

    +
    +

    core

    CR.10

    +

    “Installer which installs application and all needed software”

    +
    +

    UF

    +

    “D”

    +
    +

    _

    +

    link

    +
    +
    key:
    Source: GC=Needed for Grand Challenges, SP=Senior Personnel, UF=User Feedback
    @@ -747,7 +1844,7 @@

    Common Research Application Requirements

    - © Copyright 2023, The Regents of the University of California. + © Copyright 2024, The Regents of the University of California.

    diff --git a/docs/common/reqments/EE-UQ.html b/docs/common/reqments/EE-UQ.html index 3788845c..73829e0e 100644 --- a/docs/common/reqments/EE-UQ.html +++ b/docs/common/reqments/EE-UQ.html @@ -40,6 +40,7 @@ + @@ -126,11 +127,6 @@
  • 5. Requirements
  • 6. Bugs & Feature Requests
-

Damage and Loss DB

-

Technical Manual

  • 1. Technical Manual
  • @@ -210,12 +206,12 @@
    -

    Response of Building to Earthquake

    +

    Response of Building to Earthquake

    The following are the requirements for response of single structure to earthquake hazards. The requirements are being met by the EE-UQ application. AAll requirements in this section are related to work in WBS 1.3.8. These requirements are broken down into a number of groups, general, earthquake loading, building description, analysis, and UQ.

    -

    General Requirements

    +

    General Requirements

    key:
    Source: GC=Needed for Grand Challenges, SP=Senior Personnel, UF=User Feedback
    @@ -227,9 +223,9 @@

    General Requirements

    -

    Loading Requirements

    - - +

    Loading Requirements

    +
    Requirements - Earthquake Loading
    +@@ -406,7 +402,660 @@

    Loading Requirements
    -

    UQ Requirements

    +

    UQ Requirements

    +

    Requirements - Earthquake Loading
    + ++++++++ + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + +
    Requirements - Uncertainty Quantification Methods and Variables

    #

    Description

    Source

    Priority

    Status

    Implementation

    UF.1

    +

    “Ability to use basic Monte Carlo and LHS methods”

    +
    +

    SP

    +

    “M”

    +
    +
    +

    “Implemented”

    +
    +

    _

    UF.2

    +

    “Ability to use Gaussian Process Regression”

    +
    +

    SP

    +

    “M”

    +
    +
    +

    “Implemented”

    +
    +

    _

    UF.3

    +

    “Ability to use Own External UQ Engine”

    +
    +

    SP

    +

    “M”

    +
    +

    _

    _

    UF.4

    +

    “Ability to use Multi-Scale Monte Carlo”

    +
    +

    SP

    +

    “M”

    +
    +

    _

    _

    UF.5

    +

    “Ability to use Multi-Fidelity Models”

    +
    +

    SP

    +

    “M”

    +
    +
    +

    “InProgress”

    +
    +

    _

    UR.1

    +

    “Ability to use First Order Reliability method”

    +
    +

    SP

    +

    “M”

    +
    +
    +

    “Implemented”

    +
    +

    _

    UR.2

    +

    “Ability to use Second Order Reliability method”

    +
    +

    SP

    +

    “M”

    +
    +
    +

    “Implemented”

    +
    +

    _

    UR.3

    +

    “Ability to use Surrogate Based Reliability”

    +
    +

    SP

    +

    “M”

    +
    +
    +

    “Implemented”

    +
    +

    _

    UR.4

    +

    “Ability to use Importance Sampling”

    +
    +

    SP

    +

    “M”

    +
    +
    +

    “Implemented”

    +
    +

    _

    UG.1

    +

    “Ability to obtain Global Sensitivity Sobol indices”

    +
    +

    UF

    +

    “M”

    +
    +
    +

    “Implemented”

    +
    +

    _

    UG.2

    +

    “Ability to use probability model-based global sensitivity analysis (PM-GSA)”

    +
    +

    SP

    +

    “M”

    +
    +
    +

    “Implemented”

    +
    +

    _

    US.1

    +

    “Ability to Construct Gaussian Process (GP) Regression Model from a Simulation Model”

    +
    +

    SP

    +

    “M”

    +
    +
    +

    “InProgress”

    +
    +

    _

    US.2

    +

    “Ability to Construct GP Regression Model from Input-output Dataset”

    +
    +

    SP

    +

    “M”

    +
    +
    +

    “InProgress”

    +
    +

    _

    US.3

    +

    “Ability to use Surrogate Model for UQ Analysis”

    +
    +

    SP

    +

    “M”

    +
    +
    +

    “InProgress”

    +
    +

    _

    US.4

    +

    “Ability to Save the Surrogate Model”

    +
    +

    SP

    +

    “M”

    +
    +
    +

    “InProgress”

    +
    +

    _

    US.5

    +

    “Ability to Use Adaptive Design of Experiments”

    +
    +

    SP

    +

    “M”

    +
    +
    +

    “InProgress”

    +
    +

    _

    US.6

    +

    “Ability to Asses Reliability of Surrogate Model”

    +
    +

    SP

    +

    “M”

    +
    +
    +

    “Implemented”

    +
    +

    _

    US.7

    +

    “Ability to Build Surrogate Under Stochastic Excitation”

    +
    +

    SP

    +

    “M”

    +
    +
    +

    “InProgress”

    +
    +

    _

    US.8

    +

    “Ability to Use Physics-Informed Machine Learning”

    +
    +

    SP

    +

    “M”

    +
    +

    _

    _

    UN.1

    +

    “Ability to use Gauss-Newton solvers for parameter estimation”

    +
    +

    SP

    +

    “M”

    +
    +
    +

    “Implemented”

    +
    +

    _

    UN.2

    +

    “Ability to read calibration data from file”

    +
    +

    UF

    +

    “M”

    +
    +
    +

    “Implemented”

    +
    +

    _

    UN.3

    +

    “Ability to handle non-scalar response quantities”

    +
    +

    UF

    +

    “M”

    +
    +
    +

    “Implemented”

    +
    +

    _

    UB.1

    +

    “Ability to use DREAM algorithm for Bayesian inference”

    +
    +

    SP

    +

    “M”

    +
    +
    +

    “Implemented”

    +
    +

    _

    UB.2

    +

    “Ability to use TMCMC algorithm for Bayesian inference”

    +
    +

    SP

    +

    “M”

    +
    +
    +

    “Implemented”

    +
    +

    _

    UB.3

    +

    “Ability to read calibration data from file”

    +
    +

    UF

    +

    “M”

    +
    +
    +

    “Implemented”

    +
    +

    _

    UB.4

    +

    “Ability to handle non-scalar response quantities”

    +
    +

    UF

    +

    “M”

    +
    +
    +

    “Implemented”

    +
    +

    _

    UB.5

    +

    “Ability to calibrate multipliers on error covariance”

    +
    +

    UF

    +

    “M”

    +
    +
    +

    “Implemented”

    +
    +

    _

    UB.6

    +

    “Ability to use a default log-likelihood function”

    +
    +

    UF

    +

    “M”

    +
    +
    +

    “Implemented”

    +
    +

    _

    UB.7

    +

    “Ability to use Kalman Filtering”

    +
    +

    UF

    +

    “M”

    +
    +

    _

    _

    UB.8

    +

    “Ability to use Particle Filtering”

    +
    +

    UF

    +

    “M”

    +
    +

    _

    _

    UH.1

    +

    “Ability to sample from manifold”

    +
    +

    SP

    +

    “M”

    +
    +
    +

    “Implemented”

    +
    +

    _

    UH.2

    +

    “Ability to build Reduced Order Model”

    +
    +

    SP

    +

    “M”

    +
    +

    _

    _

    UO.1

    +

    “Ability to use User-Specified External UQ Engine”

    +
    +

    SP

    +

    “M”

    +
    +
    +

    “Implemented”

    +
    +

    _

    UO.2

    +

    “Ability to use Own External FEM Application”

    +
    +

    UF

    +

    “M”

    +
    +
    +

    “Implemented”

    +
    +

    _

    UM.1

    +

    Ability to use various Reliability Methods

    +
    +
    +

    _

    +
    +
    +

    _

    +
    +
    +

    _

    +
    +
    +

    _

    +
    +

    UM.1.1

    +

    “Ability to use First Order Reliability method”

    +
    +

    UF

    +

    “M”

    +
    +
    +

    “Implemented”

    +
    +

    _

    UM.1.2

    +

    “Ability to use Surrogate Based Reliability”

    +
    +

    UF

    +

    “M”

    +
    +

    _

    _

    UM.1.3

    +

    “Ability to use Own External Application to generate Results”

    +
    +

    UF

    +

    “M”

    +
    +
    +

    “Implemented”

    +
    +

    _

    UM.2

    +

    Ability to user various Sensitivity Methods

    +
    +
    +

    _

    +
    +
    +

    _

    +
    +
    +

    _

    +
    +
    +

    _

    +
    +

    UM.2.1

    +

    “Ability to obtain Global Sensitivity Sobol’s indices”

    +
    +

    UF

    +

    “M”

    +
    +
    +

    “Implemented”

    +
    +

    _

    key:
    Source: GC=Needed for Grand Challenges, SP=Senior Personnel, UF=User Feedback
    @@ -418,9 +1067,9 @@

    UQ Requirements -

    Modeling Requirements

    - - +

    Modeling Requirements

    +
    Requirements - Modeling
    +@@ -508,9 +1157,9 @@

    Modeling Requirements

    Requirements - Modeling
    - +

    Analysis Requirements

    +
    Requirements - Analysis
    +@@ -619,9 +1268,9 @@

    Analysis Requirements

    Requirements - Analysis
    - +

    RV Requirements

    +
    Requirements - Random Variables
    +@@ -730,7 +1379,455 @@

    RV Requirements -

    Common Research Application Requirements

    +

    Common Research Application Requirements

    +
    Requirements - Random Variables
    + ++++++++ + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + +
    Requirements - CR

    #

    Description

    Source

    Priority

    Status

    Implementation

    CR.1

    +

    Open-source software where developers can test new data and develop algorithms

    +
    +
    +

    _

    +
    +
    +

    _

    +
    +
    +

    _

    +
    +
    +

    _

    +
    +

    CR.1.1

    +

    “Provide open-source applications utilizing code hosting platforms

    +
    +
    +

    e.g. GitHub”

    +
    +

    SP

    +

    “M”

    +
    +
    +

    link

    +
    +

    CR.1.2

    +

    “Assign an open-source licensce that allows free use.”

    +
    +

    SP

    +

    “M”

    +
    +
    +

    “Implemented”

    +
    +
    +

    link

    +
    +

    CR.2

    +

    **Ability of Practicing Engineers to use multiple coupled resources (applications

    +
    +

    databases

    +

    viz tools) in engineering practice**”

    +
    +
    +

    _

    +
    +
    +

    _

    +
    +

    CR.2.1

    +

    “Allow users to launch scientific workflows”

    +
    +

    SP

    +

    “M”

    +
    +
    +

    “Implemented”

    +
    +

    _

    CR.3

    +

    Ability to utilize resources beyond the desktop including HPC

    +
    +
    +

    _

    +
    +
    +

    _

    +
    +
    +

    _

    +
    +
    +

    _

    +
    +

    CR.3.1

    +

    “Allow users to utilize HPC resources at TACC through DesignSafe”

    +
    +

    SP

    +

    “M”

    +
    +
    +

    “Implemented”

    +
    +

    _

    CR.4

    +

    **Efficient use of multiple coupled and linked models requiring sharing and inter-operability of databases

    +
    +

    computing environments

    networks

    visualization tools

    +

    _

    +
    +

    CR.4.1

    +

    “Identify and include external analysis systems”

    +
    +

    SP

    +

    “M”

    +
    +
    +

    “InProgress”

    +
    +

    _

    CR.4.2

    +

    “Identify and include external databases”

    +
    +

    SP

    +

    “M”

    +
    +
    +

    “InProgress”

    +
    +

    _

    CR.4.3

    +

    “Identify and include external viz tools”

    +
    +

    SP

    +

    “M”

    +
    +
    +

    “InProgress”

    +
    +

    _

    CR.4.4

    +

    “Identify and include external computing env”

    +
    +

    SP

    +

    “M”

    +
    +
    +

    “Inprogress”

    +
    +

    _

    CR.5

    +

    Tool available for download from web

    +
    +
    +

    _

    +
    +
    +

    _

    +
    +
    +

    _

    +
    +
    +

    _

    +
    +

    CR.5.1

    +

    “Tool downloadable from DesignSafe website”

    +
    +

    GC

    +

    “M”

    +
    +
    +

    “Implemented”

    +
    +
    +

    link

    +
    +

    CR.6

    +

    Ability to benefit from programs that move research results into practice and obtain training

    +
    +
    +

    _

    +
    +
    +

    _

    +
    +
    +

    _

    +
    +
    +

    _

    +
    +

    CR.6.1

    +

    “Ability to use educational provisions to gain interdisclipinary education so as to gain expertise in earth sciences and physics

    +
    +

    engineering mechanics

    geotechnical engineering

    +

    and structural engineering in order to be qualified to perform these simulations”

    +
    +
    +

    “D”

    +
    +

    CR.6.2

    +

    “Documentation exists demonstrainting application usage”

    +
    +

    SP

    +

    “M”

    +
    +
    +

    “Implemented”

    +
    +

    _

    CR.6.3

    +

    “Video Exists demonstrating application usage”

    +
    +

    SP

    +

    “M”

    +
    +
    +

    “Implemented”

    +
    +

    _

    CR.6.4

    +

    “Tool Training through online and in person training events”

    +
    +

    SP

    +

    “M”

    +
    +
    +

    “Implemented”

    +
    +

    _

    CR.7

    +

    “Verification Examples Exist”

    +
    +

    SP

    +

    “M”

    +
    +
    +

    “Implemented”

    +
    +

    _

    CR.8

    +

    validation of proposed analytical models against existing empirical datasets

    +
    +
    +

    _

    +
    +
    +

    _

    +
    +
    +

    _

    +
    +
    +

    _

    +
    +

    CR.8.1

    +

    “Validation Examples Exist

    +
    +
    +

    validated against tests or other software”

    +
    +

    GC

    +

    “M”

    +
    +
    +

    link

    +
    +

    CR.9

    +

    “Tool to allow user to load and save user inputs”

    +
    +

    SP

    +

    “M”

    +
    +
    +

    “Implemented”

    +
    +

    core

    CR.10

    +

    “Installer which installs application and all needed software”

    +
    +

    UF

    +

    “D”

    +
    +

    _

    +

    link

    +
    +
    key:
    Source: GC=Needed for Grand Challenges, SP=Senior Personnel, UF=User Feedback
    @@ -753,7 +1850,7 @@

    Common Research Application Requirements

    - © Copyright 2023, The Regents of the University of California. + © Copyright 2024, The Regents of the University of California.

    diff --git a/docs/common/reqments/EEUQ.html b/docs/common/reqments/EEUQ.html index 043ebed3..a22dadd7 100644 --- a/docs/common/reqments/EEUQ.html +++ b/docs/common/reqments/EEUQ.html @@ -40,6 +40,7 @@ + @@ -137,11 +138,6 @@
  • 6. Bugs & Feature Requests
-

Damage and Loss DB

-

Technical Manual

  • 1. Technical Manual
  • @@ -221,11 +217,11 @@
    -

    5. Requirements

    +

    5. Requirements

    The following contains the functional requirements for the EE-UQ application. These requirements are broken down into a number of groups, general, earthquake loading, building description, analysis, and UQ.

    The purpose of presenting these requirements is to inform the community on the present capabilities of the EE-UQ application and features that could be added. The original set of requirements have come from a set of grand challenge reports, GC. These original requirements have been broken into a smaller set of deliverable features by the senior faculty associated with the project, SP. Additional requirements have come from users through the User Forum, UF. See section features if you have additional features you would like to see.

    -

    5.1. General Requirements

    +

    5.1. General Requirements

    key:
    Source: GC=Needed for Grand Challenges, SP=Senior Personnel, UF=User Feedback
    @@ -237,9 +233,9 @@

    5.1. General Requirements -

    5.2. Loading Requirements

    - - +

    5.2. Loading Requirements

    +
    Table 5.2.1 Requirements - Earthquake Loading
    +@@ -416,7 +412,660 @@

    5.2. Loading Requirements -

    5.3. UQ Requirements

    +

    5.3. UQ Requirements

    +
    Table 5.2.1 Requirements - Earthquake Loading
    + ++++++++ + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + +
    Table 5.3.1 Requirements - Uncertainty Quantification Methods and Variables

    #

    Description

    Source

    Priority

    Status

    Implementation

    UF.1

    +

    “Ability to use basic Monte Carlo and LHS methods”

    +
    +

    SP

    +

    “M”

    +
    +
    +

    “Implemented”

    +
    +

    _

    UF.2

    +

    “Ability to use Gaussian Process Regression”

    +
    +

    SP

    +

    “M”

    +
    +
    +

    “Implemented”

    +
    +

    _

    UF.3

    +

    “Ability to use Own External UQ Engine”

    +
    +

    SP

    +

    “M”

    +
    +

    _

    _

    UF.4

    +

    “Ability to use Multi-Scale Monte Carlo”

    +
    +

    SP

    +

    “M”

    +
    +

    _

    _

    UF.5

    +

    “Ability to use Multi-Fidelity Models”

    +
    +

    SP

    +

    “M”

    +
    +
    +

    “InProgress”

    +
    +

    _

    UR.1

    +

    “Ability to use First Order Reliability method”

    +
    +

    SP

    +

    “M”

    +
    +
    +

    “Implemented”

    +
    +

    _

    UR.2

    +

    “Ability to use Second Order Reliability method”

    +
    +

    SP

    +

    “M”

    +
    +
    +

    “Implemented”

    +
    +

    _

    UR.3

    +

    “Ability to use Surrogate Based Reliability”

    +
    +

    SP

    +

    “M”

    +
    +
    +

    “Implemented”

    +
    +

    _

    UR.4

    +

    “Ability to use Importance Sampling”

    +
    +

    SP

    +

    “M”

    +
    +
    +

    “Implemented”

    +
    +

    _

    UG.1

    +

    “Ability to obtain Global Sensitivity Sobol indices”

    +
    +

    UF

    +

    “M”

    +
    +
    +

    “Implemented”

    +
    +

    _

    UG.2

    +

    “Ability to use probability model-based global sensitivity analysis (PM-GSA)”

    +
    +

    SP

    +

    “M”

    +
    +
    +

    “Implemented”

    +
    +

    _

    US.1

    +

    “Ability to Construct Gaussian Process (GP) Regression Model from a Simulation Model”

    +
    +

    SP

    +

    “M”

    +
    +
    +

    “InProgress”

    +
    +

    _

    US.2

    +

    “Ability to Construct GP Regression Model from Input-output Dataset”

    +
    +

    SP

    +

    “M”

    +
    +
    +

    “InProgress”

    +
    +

    _

    US.3

    +

    “Ability to use Surrogate Model for UQ Analysis”

    +
    +

    SP

    +

    “M”

    +
    +
    +

    “InProgress”

    +
    +

    _

    US.4

    +

    “Ability to Save the Surrogate Model”

    +
    +

    SP

    +

    “M”

    +
    +
    +

    “InProgress”

    +
    +

    _

    US.5

    +

    “Ability to Use Adaptive Design of Experiments”

    +
    +

    SP

    +

    “M”

    +
    +
    +

    “InProgress”

    +
    +

    _

    US.6

    +

    “Ability to Asses Reliability of Surrogate Model”

    +
    +

    SP

    +

    “M”

    +
    +
    +

    “Implemented”

    +
    +

    _

    US.7

    +

    “Ability to Build Surrogate Under Stochastic Excitation”

    +
    +

    SP

    +

    “M”

    +
    +
    +

    “InProgress”

    +
    +

    _

    US.8

    +

    “Ability to Use Physics-Informed Machine Learning”

    +
    +

    SP

    +

    “M”

    +
    +

    _

    _

    UN.1

    +

    “Ability to use Gauss-Newton solvers for parameter estimation”

    +
    +

    SP

    +

    “M”

    +
    +
    +

    “Implemented”

    +
    +

    _

    UN.2

    +

    “Ability to read calibration data from file”

    +
    +

    UF

    +

    “M”

    +
    +
    +

    “Implemented”

    +
    +

    _

    UN.3

    +

    “Ability to handle non-scalar response quantities”

    +
    +

    UF

    +

    “M”

    +
    +
    +

    “Implemented”

    +
    +

    _

    UB.1

    +

    “Ability to use DREAM algorithm for Bayesian inference”

    +
    +

    SP

    +

    “M”

    +
    +
    +

    “Implemented”

    +
    +

    _

    UB.2

    +

    “Ability to use TMCMC algorithm for Bayesian inference”

    +
    +

    SP

    +

    “M”

    +
    +
    +

    “Implemented”

    +
    +

    _

    UB.3

    +

    “Ability to read calibration data from file”

    +
    +

    UF

    +

    “M”

    +
    +
    +

    “Implemented”

    +
    +

    _

    UB.4

    +

    “Ability to handle non-scalar response quantities”

    +
    +

    UF

    +

    “M”

    +
    +
    +

    “Implemented”

    +
    +

    _

    UB.5

    +

    “Ability to calibrate multipliers on error covariance”

    +
    +

    UF

    +

    “M”

    +
    +
    +

    “Implemented”

    +
    +

    _

    UB.6

    +

    “Ability to use a default log-likelihood function”

    +
    +

    UF

    +

    “M”

    +
    +
    +

    “Implemented”

    +
    +

    _

    UB.7

    +

    “Ability to use Kalman Filtering”

    +
    +

    UF

    +

    “M”

    +
    +

    _

    _

    UB.8

    +

    “Ability to use Particle Filtering”

    +
    +

    UF

    +

    “M”

    +
    +

    _

    _

    UH.1

    +

    “Ability to sample from manifold”

    +
    +

    SP

    +

    “M”

    +
    +
    +

    “Implemented”

    +
    +

    _

    UH.2

    +

    “Ability to build Reduced Order Model”

    +
    +

    SP

    +

    “M”

    +
    +

    _

    _

    UO.1

    +

    “Ability to use User-Specified External UQ Engine”

    +
    +

    SP

    +

    “M”

    +
    +
    +

    “Implemented”

    +
    +

    _

    UO.2

    +

    “Ability to use Own External FEM Application”

    +
    +

    UF

    +

    “M”

    +
    +
    +

    “Implemented”

    +
    +

    _

    UM.1

    +

    Ability to use various Reliability Methods

    +
    +
    +

    _

    +
    +
    +

    _

    +
    +
    +

    _

    +
    +
    +

    _

    +
    +

    UM.1.1

    +

    “Ability to use First Order Reliability method”

    +
    +

    UF

    +

    “M”

    +
    +
    +

    “Implemented”

    +
    +

    _

    UM.1.2

    +

    “Ability to use Surrogate Based Reliability”

    +
    +

    UF

    +

    “M”

    +
    +

    _

    _

    UM.1.3

    +

    “Ability to use Own External Application to generate Results”

    +
    +

    UF

    +

    “M”

    +
    +
    +

    “Implemented”

    +
    +

    _

    UM.2

    +

    Ability to user various Sensitivity Methods

    +
    +
    +

    _

    +
    +
    +

    _

    +
    +
    +

    _

    +
    +
    +

    _

    +
    +

    UM.2.1

    +

    “Ability to obtain Global Sensitivity Sobol’s indices”

    +
    +

    UF

    +

    “M”

    +
    +
    +

    “Implemented”

    +
    +

    _

    key:
    Source: GC=Needed for Grand Challenges, SP=Senior Personnel, UF=User Feedback
    @@ -428,9 +1077,9 @@

    5.3. UQ Requirements -

    5.4. Modeling Requirements

    - - +

    5.4. Modeling Requirements

    +
    Table 5.4.1 Requirements - Modeling
    +@@ -518,9 +1167,9 @@

    5.4. Modeling Requirements -

    5.5. Analysis Requirements

    -

    Table 5.4.1 Requirements - Modeling
    - +

    5.5. Analysis Requirements

    +
    Table 5.5.1 Requirements - Analysis
    +@@ -629,9 +1278,9 @@

    5.5. Analysis Requirements -

    5.6. RV Requirements

    -

    Table 5.5.1 Requirements - Analysis
    - +

    5.6. RV Requirements

    +
    Table 5.6.1 Requirements - Random Variables
    +@@ -740,7 +1389,455 @@

    5.6. RV Requirements -

    5.7. Common Research Application Requirements

    +

    5.7. Common Research Application Requirements

    +
    Table 5.6.1 Requirements - Random Variables
    + ++++++++ + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + +
    Table 5.7.1 Requirements - CR

    #

    Description

    Source

    Priority

    Status

    Implementation

    CR.1

    +

    Open-source software where developers can test new data and develop algorithms

    +
    +
    +

    _

    +
    +
    +

    _

    +
    +
    +

    _

    +
    +
    +

    _

    +
    +

    CR.1.1

    +

    “Provide open-source applications utilizing code hosting platforms

    +
    +
    +

    e.g. GitHub”

    +
    +

    SP

    +

    “M”

    +
    +
    +

    link

    +
    +

    CR.1.2

    +

    “Assign an open-source licensce that allows free use.”

    +
    +

    SP

    +

    “M”

    +
    +
    +

    “Implemented”

    +
    +
    +

    link

    +
    +

    CR.2

    +

    **Ability of Practicing Engineers to use multiple coupled resources (applications

    +
    +

    databases

    +

    viz tools) in engineering practice**”

    +
    +
    +

    _

    +
    +
    +

    _

    +
    +

    CR.2.1

    +

    “Allow users to launch scientific workflows”

    +
    +

    SP

    +

    “M”

    +
    +
    +

    “Implemented”

    +
    +

    _

    CR.3

    +

    Ability to utilize resources beyond the desktop including HPC

    +
    +
    +

    _

    +
    +
    +

    _

    +
    +
    +

    _

    +
    +
    +

    _

    +
    +

    CR.3.1

    +

    “Allow users to utilize HPC resources at TACC through DesignSafe”

    +
    +

    SP

    +

    “M”

    +
    +
    +

    “Implemented”

    +
    +

    _

    CR.4

    +

    **Efficient use of multiple coupled and linked models requiring sharing and inter-operability of databases

    +
    +

    computing environments

    networks

    visualization tools

    +

    _

    +
    +

    CR.4.1

    +

    “Identify and include external analysis systems”

    +
    +

    SP

    +

    “M”

    +
    +
    +

    “InProgress”

    +
    +

    _

    CR.4.2

    +

    “Identify and include external databases”

    +
    +

    SP

    +

    “M”

    +
    +
    +

    “InProgress”

    +
    +

    _

    CR.4.3

    +

    “Identify and include external viz tools”

    +
    +

    SP

    +

    “M”

    +
    +
    +

    “InProgress”

    +
    +

    _

    CR.4.4

    +

    “Identify and include external computing env”

    +
    +

    SP

    +

    “M”

    +
    +
    +

    “Inprogress”

    +
    +

    _

    CR.5

    +

    Tool available for download from web

    +
    +
    +

    _

    +
    +
    +

    _

    +
    +
    +

    _

    +
    +
    +

    _

    +
    +

    CR.5.1

    +

    “Tool downloadable from DesignSafe website”

    +
    +

    GC

    +

    “M”

    +
    +
    +

    “Implemented”

    +
    +
    +

    link

    +
    +

    CR.6

    +

    Ability to benefit from programs that move research results into practice and obtain training

    +
    +
    +

    _

    +
    +
    +

    _

    +
    +
    +

    _

    +
    +
    +

    _

    +
    +

    CR.6.1

    +

    “Ability to use educational provisions to gain interdisclipinary education so as to gain expertise in earth sciences and physics

    +
    +

    engineering mechanics

    geotechnical engineering

    +

    and structural engineering in order to be qualified to perform these simulations”

    +
    +
    +

    “D”

    +
    +

    CR.6.2

    +

    “Documentation exists demonstrainting application usage”

    +
    +

    SP

    +

    “M”

    +
    +
    +

    “Implemented”

    +
    +

    _

    CR.6.3

    +

    “Video Exists demonstrating application usage”

    +
    +

    SP

    +

    “M”

    +
    +
    +

    “Implemented”

    +
    +

    _

    CR.6.4

    +

    “Tool Training through online and in person training events”

    +
    +

    SP

    +

    “M”

    +
    +
    +

    “Implemented”

    +
    +

    _

    CR.7

    +

    “Verification Examples Exist”

    +
    +

    SP

    +

    “M”

    +
    +
    +

    “Implemented”

    +
    +

    _

    CR.8

    +

    validation of proposed analytical models against existing empirical datasets

    +
    +
    +

    _

    +
    +
    +

    _

    +
    +
    +

    _

    +
    +
    +

    _

    +
    +

    CR.8.1

    +

    “Validation Examples Exist

    +
    +
    +

    validated against tests or other software”

    +
    +

    GC

    +

    “M”

    +
    +
    +

    link

    +
    +

    CR.9

    +

    “Tool to allow user to load and save user inputs”

    +
    +

    SP

    +

    “M”

    +
    +
    +

    “Implemented”

    +
    +

    core

    CR.10

    +

    “Installer which installs application and all needed software”

    +
    +

    UF

    +

    “D”

    +
    +

    _

    +

    link

    +
    +
    key:
    Source: GC=Needed for Grand Challenges, SP=Senior Personnel, UF=User Feedback
    @@ -763,7 +1860,7 @@

    5.7. Common Research Application Require

    - © Copyright 2023, The Regents of the University of California. + © Copyright 2024, The Regents of the University of California.

    diff --git a/docs/common/reqments/key.html b/docs/common/reqments/key.html index 08ff2d87..80d98c90 100644 --- a/docs/common/reqments/key.html +++ b/docs/common/reqments/key.html @@ -40,6 +40,7 @@ + @@ -126,11 +127,6 @@
  • 5. Requirements
  • 6. Bugs & Feature Requests
-

Damage and Loss DB

-

Technical Manual

  • 1. Technical Manual
  • @@ -229,7 +225,7 @@

    - © Copyright 2023, The Regents of the University of California. + © Copyright 2024, The Regents of the University of California.

    diff --git a/docs/common/reqments/reqPelicun.html b/docs/common/reqments/reqPelicun.html index b5117ae8..6d5184b8 100644 --- a/docs/common/reqments/reqPelicun.html +++ b/docs/common/reqments/reqPelicun.html @@ -40,6 +40,7 @@ + @@ -126,11 +127,6 @@
  • 5. Requirements
  • 6. Bugs & Feature Requests
-

Damage and Loss DB

-

Technical Manual

  • 1. Technical Manual
  • @@ -210,9 +206,9 @@
    -

    Requirements

    +

    Requirements

    -

    General

    +

    General

    @@ -946,7 +942,7 @@

    General -

    Databases & Files

    +

    Databases & Files

    Requirements - General
    @@ -1215,7 +1211,7 @@

    Databases & Files

    - © Copyright 2023, The Regents of the University of California. + © Copyright 2024, The Regents of the University of California.

    diff --git a/docs/common/reqments/reqQUOFE.html b/docs/common/reqments/reqQUOFE.html index b2a9a333..93eed6fa 100644 --- a/docs/common/reqments/reqQUOFE.html +++ b/docs/common/reqments/reqQUOFE.html @@ -40,6 +40,7 @@ + @@ -126,11 +127,6 @@
  • 5. Requirements
  • 6. Bugs & Feature Requests
  • -

    Damage and Loss DB

    -

    Technical Manual

    • 1. Technical Manual
    • @@ -210,12 +206,12 @@
      -

      Requirements

      +

      Requirements

      The purpose of presenting these requirements is to inform the community on the present capabilities of the EE-UQ app and features that could be added. The original set of requirements have come from a set of grand challenge reports, GC. These original requirements have been broken into a smaller set of deliverable features by the senior faculty associated with the project, SP. Additional requirements have come from users, U See section features if you have additional features you would like to see.

      -

      quoFEM Requirements

      -

    Requirements - Databases & Files
    - +

    quoFEM Requirements

    +
    Requirements - QF
    +@@ -350,7 +346,660 @@

    quoFEM Requirements -

    UQ Requirements

    +

    UQ Requirements

    +
    Requirements - QF
    + ++++++++ + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + +
    Requirements - Uncertainty Quantification Methods and Variables

    #

    Description

    Source

    Priority

    Status

    Implementation

    UF.1

    +

    “Ability to use basic Monte Carlo and LHS methods”

    +
    +

    SP

    +

    “M”

    +
    +
    +

    “Implemented”

    +
    +

    _

    UF.2

    +

    “Ability to use Gaussian Process Regression”

    +
    +

    SP

    +

    “M”

    +
    +
    +

    “Implemented”

    +
    +

    _

    UF.3

    +

    “Ability to use Own External UQ Engine”

    +
    +

    SP

    +

    “M”

    +
    +

    _

    _

    UF.4

    +

    “Ability to use Multi-Scale Monte Carlo”

    +
    +

    SP

    +

    “M”

    +
    +

    _

    _

    UF.5

    +

    “Ability to use Multi-Fidelity Models”

    +
    +

    SP

    +

    “M”

    +
    +
    +

    “InProgress”

    +
    +

    _

    UR.1

    +

    “Ability to use First Order Reliability method”

    +
    +

    SP

    +

    “M”

    +
    +
    +

    “Implemented”

    +
    +

    _

    UR.2

    +

    “Ability to use Second Order Reliability method”

    +
    +

    SP

    +

    “M”

    +
    +
    +

    “Implemented”

    +
    +

    _

    UR.3

    +

    “Ability to use Surrogate Based Reliability”

    +
    +

    SP

    +

    “M”

    +
    +
    +

    “Implemented”

    +
    +

    _

    UR.4

    +

    “Ability to use Importance Sampling”

    +
    +

    SP

    +

    “M”

    +
    +
    +

    “Implemented”

    +
    +

    _

    UG.1

    +

    “Ability to obtain Global Sensitivity Sobol indices”

    +
    +

    UF

    +

    “M”

    +
    +
    +

    “Implemented”

    +
    +

    _

    UG.2

    +

    “Ability to use probability model-based global sensitivity analysis (PM-GSA)”

    +
    +

    SP

    +

    “M”

    +
    +
    +

    “Implemented”

    +
    +

    _

    US.1

    +

    “Ability to Construct Gaussian Process (GP) Regression Model from a Simulation Model”

    +
    +

    SP

    +

    “M”

    +
    +
    +

    “InProgress”

    +
    +

    _

    US.2

    +

    “Ability to Construct GP Regression Model from Input-output Dataset”

    +
    +

    SP

    +

    “M”

    +
    +
    +

    “InProgress”

    +
    +

    _

    US.3

    +

    “Ability to use Surrogate Model for UQ Analysis”

    +
    +

    SP

    +

    “M”

    +
    +
    +

    “InProgress”

    +
    +

    _

    US.4

    +

    “Ability to Save the Surrogate Model”

    +
    +

    SP

    +

    “M”

    +
    +
    +

    “InProgress”

    +
    +

    _

    US.5

    +

    “Ability to Use Adaptive Design of Experiments”

    +
    +

    SP

    +

    “M”

    +
    +
    +

    “InProgress”

    +
    +

    _

    US.6

    +

    “Ability to Asses Reliability of Surrogate Model”

    +
    +

    SP

    +

    “M”

    +
    +
    +

    “Implemented”

    +
    +

    _

    US.7

    +

    “Ability to Build Surrogate Under Stochastic Excitation”

    +
    +

    SP

    +

    “M”

    +
    +
    +

    “InProgress”

    +
    +

    _

    US.8

    +

    “Ability to Use Physics-Informed Machine Learning”

    +
    +

    SP

    +

    “M”

    +
    +

    _

    _

    UN.1

    +

    “Ability to use Gauss-Newton solvers for parameter estimation”

    +
    +

    SP

    +

    “M”

    +
    +
    +

    “Implemented”

    +
    +

    _

    UN.2

    +

    “Ability to read calibration data from file”

    +
    +

    UF

    +

    “M”

    +
    +
    +

    “Implemented”

    +
    +

    _

    UN.3

    +

    “Ability to handle non-scalar response quantities”

    +
    +

    UF

    +

    “M”

    +
    +
    +

    “Implemented”

    +
    +

    _

    UB.1

    +

    “Ability to use DREAM algorithm for Bayesian inference”

    +
    +

    SP

    +

    “M”

    +
    +
    +

    “Implemented”

    +
    +

    _

    UB.2

    +

    “Ability to use TMCMC algorithm for Bayesian inference”

    +
    +

    SP

    +

    “M”

    +
    +
    +

    “Implemented”

    +
    +

    _

    UB.3

    +

    “Ability to read calibration data from file”

    +
    +

    UF

    +

    “M”

    +
    +
    +

    “Implemented”

    +
    +

    _

    UB.4

    +

    “Ability to handle non-scalar response quantities”

    +
    +

    UF

    +

    “M”

    +
    +
    +

    “Implemented”

    +
    +

    _

    UB.5

    +

    “Ability to calibrate multipliers on error covariance”

    +
    +

    UF

    +

    “M”

    +
    +
    +

    “Implemented”

    +
    +

    _

    UB.6

    +

    “Ability to use a default log-likelihood function”

    +
    +

    UF

    +

    “M”

    +
    +
    +

    “Implemented”

    +
    +

    _

    UB.7

    +

    “Ability to use Kalman Filtering”

    +
    +

    UF

    +

    “M”

    +
    +

    _

    _

    UB.8

    +

    “Ability to use Particle Filtering”

    +
    +

    UF

    +

    “M”

    +
    +

    _

    _

    UH.1

    +

    “Ability to sample from manifold”

    +
    +

    SP

    +

    “M”

    +
    +
    +

    “Implemented”

    +
    +

    _

    UH.2

    +

    “Ability to build Reduced Order Model”

    +
    +

    SP

    +

    “M”

    +
    +

    _

    _

    UO.1

    +

    “Ability to use User-Specified External UQ Engine”

    +
    +

    SP

    +

    “M”

    +
    +
    +

    “Implemented”

    +
    +

    _

    UO.2

    +

    “Ability to use Own External FEM Application”

    +
    +

    UF

    +

    “M”

    +
    +
    +

    “Implemented”

    +
    +

    _

    UM.1

    +

    Ability to use various Reliability Methods

    +
    +
    +

    _

    +
    +
    +

    _

    +
    +
    +

    _

    +
    +
    +

    _

    +
    +

    UM.1.1

    +

    “Ability to use First Order Reliability method”

    +
    +

    UF

    +

    “M”

    +
    +
    +

    “Implemented”

    +
    +

    _

    UM.1.2

    +

    “Ability to use Surrogate Based Reliability”

    +
    +

    UF

    +

    “M”

    +
    +

    _

    _

    UM.1.3

    +

    “Ability to use Own External Application to generate Results”

    +
    +

    UF

    +

    “M”

    +
    +
    +

    “Implemented”

    +
    +

    _

    UM.2

    +

    Ability to user various Sensitivity Methods

    +
    +
    +

    _

    +
    +
    +

    _

    +
    +
    +

    _

    +
    +
    +

    _

    +
    +

    UM.2.1

    +

    “Ability to obtain Global Sensitivity Sobol’s indices”

    +
    +

    UF

    +

    “M”

    +
    +
    +

    “Implemented”

    +
    +

    _

    key:
    Source: GC=Needed for Grand Challenges, SP=Senior Personnel, UF=User Feedback
    @@ -362,9 +1011,9 @@

    UQ Requirements -

    RV Requirements

    - - +

    RV Requirements

    +
    Requirements - CR
    +@@ -473,7 +1122,449 @@

    RV Requirements -

    Common Research Application Requirements

    +

    Common Research Application Requirements

    +
    Requirements - CR
    + ++++++++ + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + +
    Requirements - CR

    #

    Description

    Source

    Priority

    Status

    Implementation

    CR.1

    +

    Open-source software where developers can test new data and develop algorithms

    +
    +
    +

    _

    +
    +
    +

    _

    +
    +
    +

    _

    +
    +
    +

    _

    +
    +

    CR.1.1

    +

    “Provide open-source applications utilizing code hosting platforms

    +
    +
    +

    e.g. GitHub”

    +
    +

    SP

    +

    “M”

    +
    +
    +

    “Implemented”

    +
    +

    CR.1.2

    +

    “Assign an open-source licensce that allows free use.”

    +
    +

    SP

    +

    “M”

    +
    +
    +

    “Implemented”

    +
    +
    +

    link

    +
    +

    CR.2

    +

    **Ability of Practicing Engineers to use multiple coupled resources (applications

    +
    +

    databases

    +

    viz tools) in engineering practice**”

    +
    +
    +

    _

    +
    +
    +

    _

    +
    +

    CR.2.1

    +

    “Allow users to launch scientific workflows”

    +
    +

    SP

    +

    “M”

    +
    +
    +

    “Implemented”

    +
    +

    _

    CR.3

    +

    Ability to utilize resources beyond the desktop including HPC

    +
    +
    +

    _

    +
    +
    +

    _

    +
    +
    +

    _

    +
    +
    +

    _

    +
    +

    CR.3.1

    +

    “Allow users to utilize HPC resources at TACC through DesignSafe”

    +
    +

    SP

    +

    “M”

    +
    +
    +

    “Implemented”

    +
    +

    _

    CR.4

    +

    **Efficient use of multiple coupled and linked models requiring sharing and inter-operability of databases

    +
    +

    computing environments

    networks

    visualization tools

    +

    and analysis systems**”

    +
    +

    CR.4.1

    +

    “Identify and include external analysis systems”

    +
    +

    SP

    +

    “M”

    +
    +
    +

    “InProgress”

    +
    +

    _

    CR.4.2

    +

    “Identify and include external databases”

    +
    +

    SP

    +

    “M”

    +
    +
    +

    “InProgress”

    +
    +

    _

    CR.4.3

    +

    “Identify and include external viz tools”

    +
    +

    SP

    +

    “M”

    +
    +
    +

    “InProgress”

    +
    +

    _

    CR.4.4

    +

    “Identify and include external computing env”

    +
    +

    SP

    +

    “M”

    +
    +
    +

    “Inprogress”

    +
    +

    _

    CR.5

    +

    Tool available for download from web

    +
    +
    +

    _

    +
    +
    +

    _

    +
    +
    +

    _

    +
    +
    +

    _

    +
    +

    CR.5.1

    +

    “Tool downloadable from DesignSafe website”

    +
    +

    GC

    +

    “M”

    +
    +
    +

    “Implemented”

    +
    +
    +

    link

    +
    +

    CR.6

    +

    Ability to benefit from programs that move research results into practice and obtain training

    +
    +
    +

    _

    +
    +
    +

    _

    +
    +
    +

    _

    +
    +
    +

    _

    +
    +

    CR.6.1

    +

    “Ability to use educational provisions to gain interdisclipinary education so as to gain expertise in earth sciences and physics

    +
    +

    engineering mechanics

    geotechnical engineering

    +

    and structural engineering in order to be qualified to perform these simulations”

    +
    +

    GC

    CR.6.2

    +

    “Documentation exists demonstrainting application usage”

    +
    +

    SP

    +

    “M”

    +
    +
    +

    “Implemented”

    +
    +

    _

    CR.6.3

    +

    “Video Exists demonstrating application usage”

    +
    +

    SP

    +

    “M”

    +
    +
    +

    “Implemented”

    +
    +

    _

    CR.6.4

    +

    “Tool Training through online and in person training events”

    +
    +

    SP

    +

    “M”

    +
    +
    +

    “Implemented”

    +
    +

    _

    CR.7

    +

    “Verification Examples Exist”

    +
    +

    SP

    +

    “M”

    +
    +
    +

    “Implemented”

    +
    +

    _

    CR.8

    +

    validation of proposed analytical models against existing empirical datasets

    +
    +
    +

    _

    +
    +
    +

    _

    +
    +
    +

    _

    +
    +
    +

    _

    +
    +

    CR.8.1

    +

    “Validation Examples Exist

    +
    +
    +

    validated against tests or other software”

    +
    +

    GC

    +

    “M”

    +
    +

    _

    CR.9

    +

    “Tool to allow user to load and save user inputs”

    +
    +

    SP

    +

    “M”

    +
    +
    +

    “Implemented”

    +
    +

    core

    CR.10

    +

    “Installer which installs application and all needed software”

    +
    +

    UF

    +

    “D”

    +
    +

    _

    +

    link

    +
    +
    key:
    Source: GC=Needed for Grand Challenges, SP=Senior Personnel, UF=User Feedback
    @@ -496,7 +1587,7 @@

    Common Research Application Requirements

    - © Copyright 2023, The Regents of the University of California. + © Copyright 2024, The Regents of the University of California.

    diff --git a/docs/common/technical_manual/desktop/HazardSimulationTool_useCase.html b/docs/common/technical_manual/desktop/HazardSimulationTool_useCase.html new file mode 100644 index 00000000..6482182c --- /dev/null +++ b/docs/common/technical_manual/desktop/HazardSimulationTool_useCase.html @@ -0,0 +1,454 @@ + + + + + + + + + + Regional Earthquake Hazard Use Cases — Earthquake Engineering with Uncertainty Quantification documentation + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + +
    + + + +
    + + + + + +
    + +
    + + + + + + + + + + + + + + + + + + + +
    + +
      + +
    • »
    • + +
    • Regional Earthquake Hazard Use Cases
    • + + +
    • + + + View page source + + +
    • + +
    + + +
    +
    +
    +
    + +
    +

    Regional Earthquake Hazard Use Cases

    +

    The major use cases of Regional Earthquake Hazard in R2D can be divided +into Scenario-specific or Probabilistic Seismic Hazard Analysis.

    +
    +../../../_images/R2DScenarioOrPSHA.png +

    Specific Earthquake Scenario or Probabilistic Hazard Analysis.

    +
    +
    +

    Scenario-specific Earthquake

    +

    This option is to analyze an earthquake scenario that consists of one or more ruptures +based on an earthquake description of a past or hypothetical event. Some use cases +for which this option are:

    +
    +
      +
    1. Analysis of a single rupture. For example, running the “Hayward-Rodgers Creek; HN+HS” segment, which is a specific rupture location, length, characteristics, etc.

    2. +
    3. Broader analysis of a scenario. For example, running “an M7 earthquake on the San Andreas Fault.” This would include realizations with different ruptures, that all describe an M7 on the San Andreas.

    4. +
    5. Multiple specified ruptures. This would be used in the case in which a user already has a defined set of ruptures they are interested in studying. This option does not fully capture the probabilistic seismic hazard of a region.

    6. +
    7. A past earthquake. For example, recreating the Loma Prieta earthquake.

    8. +
    +
    +

    fig-R2DScenarioSpecificUseCases shows typical scenario-specific use cases in R2D. +All the use cases in fig-R2DScenarioSpecificUseCases can be achieved with R2D. The first two options are loading predefined +ground motion records or intensity measures in the region, and are described in +User-specified Ground Motions. The functionality to +interface with some physics-based earthquake simulation databases is also under development in R2D. +The third to fifty use cases in fig-R2DScenarioSpecificUseCases requires +the earthquake hazard simulation tool, and the last option +can be achieved as described in ShakeMap Earthquake Scenarios).

    +

    The functions in the earthquake hazard simulation tool required for +scenario-specific use cases are Site Definition, +Earthquake Rupture Forecasting, Intensity Measure Definition, Ground Motion Prediction +Equations, Spatial Correlations and Ground Motion Record Selection (optional). +The “Scenario-specific” option should be selected in the “Scenario Selection” tool tab. +More details of the use cases, required inputs, and some benefits/limitations are +summarised in tab-R2DScenarioSpecificUseCases.

    +
    +../../../_images/R2DScenarioSpecificUseCases.png +

    Scenario-specific earthquake hazard use cases.

    +
    + + ++++++ + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + +
    Typical Scenario-specific Earthquake Hazard Use Cases

    Use Case

    Recommended Uses

    Required Inputs

    Benefits/Limitations

    Predefined GM

    User already has ground motion time histories they are interested in.

    Describe any specific file type/folder structure required.

    Predefined IM

    User already has an IM field they are interested in. GM selection can be done.

    Describe any specific file type/folder structure required.

    OpenSHA/UCERF

    Recommended where UCERF ruptures are available (maybe we can show a map). Recommended because it requires no additional inputs other than selections using the R2D interface (source models are openly available).

    No external files are required and all selection can be done in R2D.

    Users can select out of several choices of GMM and correlation models to use through the R2D interface. Limited in that it only has information available about ruptures in certain locations.

    OpenQuake

    Recommended to describe distributed and background seismicity. Also recommended for use where rupture information is unavailable through UCERF.

    External source model file required. The format of source models can be found here, and a database of global earthquake sources can be found at the GEM’s Global Active Faults Database [Styron2020]

    Can be used to describe distributed and background seismicity where information on the faults is unavailable.

    Point Source

    For educational and/or academic use only. The point source option does not accurately reflect real faults.

    No external files are required and all selection can be done in R2D.

    Not representative of real faults/scenarios.

    ShakeMap

    Re-creation of a past earthquake event by obtaining seismic intensity measures sufficiently representative of the event.

    Inputs are USGS ShakeMap files for a given earthquake scenario. These files must be located in a folder in which at least must be a grid.xml file. These files contain ShakeMaps that include the intensity measures for a given earthquake event as spectral ordinate values (Those can be given as PGA, PGV, PGD and spectral ordinates at different periods). These files can be obtained from USGS’s ShakeMap archives for real past earthquake events.

    ShakeMap intensity measures (as spectral ordinates) for past earthquakes might not be an accurate representation of this event in locations far from the grid control points (usually recording stations where GMM predictions are adjusted to match real recorded ground motion spectra). Moreover, the set of scenarios is limited.

    +
    +
    +

    Regional Probabilistic Seismic Hazard Analysis

    +

    The regional probabilistic seismic hazard analysis (PSHA) characterizes the probability +of certain levels of intensity are exceeded in a region considering all nearby +earthquake sources. +fig-R2DScenarioSpecificUseCases shows two typical use cases in regional PSHA. +Both use cases can be achieved in R2D with the earthquake hazard simulation tool. +The functions in the earthquake hazard simulation tool required for +regional PSHA are Site Definition, +Earthquake Rupture Forecasting, Intensity Measure Definition, Ground Motion Prediction +Equations, Spatial Correlations, Ground Motion Record Selection (optional), and hazard consistent +downsamping (optional). The “Conventional Monte Carlo” or “Hazard consistent downsampling” option +should be selected in the “Scenario Selection” tool tab. More details of the use cases, +required inputs, and some benefits/limitations are summarised in tab-R2DRegionalPSHAUseCases.

    +
    +../../../_images/R2DRegionalPSHAUseCases.png +

    Regional probabilistic seismic hazard analysis use cases.

    +
    + + ++++++ + + + + + + + + + + + + + + + + + + + +
    Typical Regional Probabilistic Seismic Hazard Analysis Use Cases

    Use Case

    Recommended Uses

    Required Inputs

    Benefits/Limitations

    OpenSHA/UCERF

    Recommended where UCERF ruptures are available (maybe we can show a map). Recommended because it requires no additional inputs other than selections using the R2D interface (source models are openly available).

    No external files are required, and all selections can be done in R2D.

    Only available for California.

    OpenQuake

    Recommended for use where UCERF ruptures are unavailable.

    External files required. The format of source models can be found here, and a database of global earthquake sources can be found at the GEM’s Global Active Faults Database [Styron2020]

    Users need to prepare their earthquake source model.

    +
    +
    Styron2020(1,2)
    +

    Styron, Richard, and Marco Pagani. “The GEM Global Active Faults Database.” Earthquake Spectra, vol. 36, no. 1_suppl, Oct. 2020, pp. 160–180, doi:10.1177/8755293020944182.

    +
    +
    +
    +
    + + +
    + +
    +
    + +
    + +
    +

    + © Copyright 2024, The Regents of the University of California. + +

    +
    + + + + Built with Sphinx using a + + theme + + provided by Read the Docs. + +
    +
    +
    + +
    + +
    + + + + + + + + + + + + + + + + + + + + \ No newline at end of file diff --git a/docs/common/technical_manual/desktop/SimCenterUQTechnical.html b/docs/common/technical_manual/desktop/SimCenterUQTechnical.html index ddcf5282..47250a61 100644 --- a/docs/common/technical_manual/desktop/SimCenterUQTechnical.html +++ b/docs/common/technical_manual/desktop/SimCenterUQTechnical.html @@ -40,6 +40,7 @@ + @@ -129,11 +130,6 @@
  • 5. Requirements
  • 6. Bugs & Feature Requests
-

Damage and Loss DB

-

Technical Manual

  • 1. Technical Manual @@ -245,9 +243,9 @@
    -

    1.2. Methods in SimCenterUQ Engine

    +

    1.2. Methods in SimCenterUQ Engine

    -

    Nataf transformation

    +

    Nataf transformation

    Nataf transformation is introduced to standardize the interface between UQ methods and Simulation models. Nataf converts the samples in the physical space (X-space) into the standard normal samples (U-space), \(T:\rm{X} \rightarrow \rm{U}\), and vice versa, during UQ computations [Liu1986]. Specifically, the latter transformation, called inverse Nataf \(T^{-1}\), is performed each time when UQ engine generates sample points and calls external workflow applications, so that the main UQ algorithms would face only the standard normal random variables. Among various standardization transformations, Nataf is one of the most popular methods which exploits marginal distributions of each physical variables and their correlation coefficients.

    ../../../_images/SimCenterNataf1.png @@ -265,9 +263,15 @@

    Nataf transformation

    -

    Global sensitivity analysis

    +

    Global sensitivity analysis

    +
    +

    Video Resources

    +

    Global Sensitivity Analysis: why, what, and how.

    +
    + +


    Click to replay the video from 2:14.

    -

    Variance-based global sensitivity indices

    +

    Variance-based global sensitivity indices

    Global sensitivity analysis (GSA) is performed to quantify the contribution of each input variable to the uncertainty in QoI. Using the global sensitivity indices, users can set preferences between random variables considering both inherent randomness and its propagation through the model. GSA helps users to understand the overall impact of different sources of uncertainties, as well as accelerate UQ computations by focusing on dominant dimensions or screening out trivial input variables.

    ../../../_images/SimCenterSensitivity1.png @@ -294,7 +298,7 @@

    Variance-based global sensitivity indices -

    Estimation of Sobol indices using Probabilistic model-based global sensitivity analysis (PM-GSA)

    +

    Estimation of Sobol indices using Probabilistic model-based global sensitivity analysis (PM-GSA)

    GSA is typically computationally expensive. High computation cost attributes to the multiple integrations (\(d\)-dimensional) associated with the variance and expectation operations shown in Eqs. (1.2.1) and (1.2.2). To reduce the computational cost, efficient Monte Carlo methods, stochastic expansion methods, or meta-model-based methods can be employed. Among different approaches, the SimCenterUQ engine supports the probability model-based GSA (PM-GSA) framework developed by [Hu2019].

    The framework first conducts ordinary MCS to obtain input-output data pairs. Then by extracting only a subset dimension of the dataset, the probability distribution of a reduced dimension can be approximated and used for estimating the Sobol index. Among different probability distribution models introduced in [Hu2019] the Gaussian mixture model is implemented in this engine to approximate this lower dimension distribution. For example, to identify 1st order main Sobol index for a variable \(x_i\), a bivariate Gaussian mixture model is fitted for the joint probability distribution of \(x_i\) and \(y\), i.e.

    @@ -311,7 +315,7 @@

    Estimation of Sobol indices using Probabilistic model-based global sensitivi

    -

    Dealing with high-dimensional responses with PCA-PSA

    +

    Dealing with high-dimensional responses with PCA-PSA

    When the number of the quantities of interest (QoI) is very large, it is computationally cumbersome to perform above Gaussian fitting independently for each QoI. To promote efficient global sensitivity analysis for such cases, SimCenterUQ provides the ‘principal component analysis-based PM-GSA’ module, which is referred to as PCA-PSA [Jung2022]. In this method, the dimension of QoI is first reduced by principal component analysis (PCA), and the conditional variance required to calculate the Sobol indices (the numerators in (1.2.1) and (1.2.2)) is approximately reconstructed from those of the conditional variance/covariance information of the reduced dimension variables. If the high-dimensional QoI has a linear data structure that be reconstructed with a small number of principal components, the computational gain of this approach can be significant. For example, suppose QoI can be reconstructed using 10 principal components. In that case, the Gaussian mixture fitting, which is the most time-consuming step of PM-GSA apart from FEM analysis, needs to be repeated only 10 times per random variable or group of random variables regardless of the actual dimension of QoI. This example shows how PCA-PSA can facilitate efficient global sensitivity analysis for a field (time series) QoI.

    Jung2022
    @@ -320,7 +324,7 @@

    Dealing with high-dimensional responses with PCA-PSA

    -

    Aggregated sensitivity index

    +

    Aggregated sensitivity index

    When the quantities of interest (QoI) are given as a vector or field variable, an aggregated sensitivity index can provide insight into the system’s overall sensitivity characteristics. The aggregated sensitivity index achieves this by calculating the weighted average of the sensitivity indices of each QoI component, where the weights are proportional to the variances of the components [Jung2022]. Component sensitivity indices are useful for visualization, while the aggregated sensitivity index gives instant intuition on how much each variable influences the system response overall. See this example.

    Jung2022
    @@ -330,9 +334,9 @@

    Aggregated sensitivity index -

    Global surrogate modeling

    +

    Global surrogate modeling

    -

    Introduction to Gaussian process regression (Kriging)

    +

    Introduction to Gaussian process regression (Kriging)

    Global surrogate modeling aims to build a regression model that reproduces the outcomes of computationally expensive high fidelity simulations.

    (1.2.9)\[\boldsymbol{y}=g^{\rm{ex}} (\boldsymbol{x}) \simeq g^{\rm{sur}} (\boldsymbol{x})\]
    @@ -350,7 +354,7 @@

    Introduction to Gaussian process regression (Kriging)

    -

    Dealing with noisy measurements

    +

    Dealing with noisy measurements

    In natural hazard applications, often the exact observations of \(\boldsymbol{y}\) are not available and only the noisy observations \(\boldsymbol{y^{obs}}\) are available:
    @@ -389,9 +393,9 @@

    Dealing with noisy measurements -

    Construction of surrogate model

    +

    Construction of surrogate model

    -

    Input-Output settings

    +

    Input-Output settings

    @@ -422,7 +426,7 @@

    Input-Output settings
    -

    Kernel and basis functions

    +

    Kernel and basis functions

    The covariance kernel of the outcome process is unknown in most practical applications. Therefore, the mathematical form of the kernel is first assumed, and its parameters are calibrated based on the observation data. Following are some of the popular stationary covariance kernels.

    -

    Verification of surrogate model

    +

    Verification of surrogate model

    Once the training is completed, the following three verification measures are presented based on leave-one-out cross-validation (LOOCV) error estimation.

    • Leave-one-out cross-validation (LOOCV)

      @@ -589,9 +593,9 @@

      Verification of surrogate model -

      Multi-fidelity Monte Carlo (MFMC)

      +

      Multi-fidelity Monte Carlo (MFMC)

      -

      Models with different infidelities

      +

      Models with different infidelities

      When one has multiple models of a target system with different fidelities, they can introduce multi-fidelity Monte Carlo (MFMC) methods. MFMC helps us to reduce the high-fidelity simulation runs by leveraging a large number of low-fidelity simulations. The high-fidelity and low-fidelity models are defined as the following.

        @@ -619,7 +623,7 @@

        Models with different infidelities -

        Pre-execution checklist for MFMC

        +

        Pre-execution checklist for MFMC

        Before running the MFMC simulation model, the users are advised to check the validity and effectiveness of MFMC for their problem. Only when the below conditions are satisfied, the users are expected to gain meaningful benefit by using MFMC compared to only HF simulations:

        -

        Damage and Loss DB

        -

        Technical Manual

        • 1. Technical Manual
        • @@ -211,9 +207,9 @@
          -

          Methods in UCSD UQ Engine

          -
          -

          Transtitional Markov chain Monte Carlo

          +

          Methods in UCSD UQ Engine

          +
          +

          Transitional Markov chain Monte Carlo

          TMCMC is a numerical method used to obtain samples of the target posterior PDF. This algorithm is flexible, applicable in general settings, and parallelizable. Thus, it can be used to effectively sample the posterior PDF, when the likelihood function involves a computationally expensive FE model evaluation, using high-performance computing (HPC) resources.

          In Bayesian inference, the posterior probability distribution of the unknown quantities, represented by the vector \(\mathbf{\theta}\), is obtained by applying Bayes’ rule as follows:

          @@ -223,7 +219,7 @@

          Transtitional Markov chain Monte Carlo ()\[p(\theta|y)_j \propto p(y | \theta)^{\beta_j} \times p(\theta); \quad j = 0, 1, \ldots, m; \quad 0 = \beta_0 < \beta_1 < \ldots < \beta_m = 1\]

          Index \(j\) denotes the stage number, \(m\) denotes the total number of stages, and \(p (\mathbf{\theta \ | \ y})_j\) is the tempered posterior PDF at stage \(j\) controlled by the parameter \(\beta_j\). At the initial stage \((j = 0)\), parameter \(\beta_0 = 0\), the tempered distribution \(p(\mathbf{\theta \ | \ y})_{j=0}\) is just the -prior joint PDF \(p(\theta)\). The TMCMC sampler progresses by monotonically increasing the value of \(\beta_j\) , at each stage \(j\), until it reaches the value of 1. At the final stage \((j = m)\), parameter \(\beta_m = 1\), the tempered distribution \(p(\mathbf{\theta \ | \ y})_{j = m}\) is the target posterior joint PDF \(p(\mathbf{\theta \ | \ y})\).

          +prior joint PDF \(p(\theta)\). The TMCMC sampler progresses by monotonically increasing the value of \(\beta_j\), at each stage \(j\), until it reaches the value of 1. At the final stage \((j = m)\), parameter \(\beta_m = 1\), the tempered distribution \(p(\mathbf{\theta \ | \ y})_{j = m}\) is the target posterior joint PDF \(p(\mathbf{\theta \ | \ y})\).

          TMCMC represents the tempered posterior PDF at every stage by a set of weighted samples (known as particles). TMCMC approximates the \(j^{th}\) stage tempered posterior PDF \(p(\mathbf{\theta \ | \ y})_j\) by weighing, resampling, and perturbing the particles of the \(j-1^{th}\) stage intermediate joint PDF \(p(\mathbf{\theta \ | \ y})_{j-1}\) . For details about the TMCMC algorithm, the interested reader is referred to Ching and Chen [Ching2007], Minson et. al. [Minson2013].

          Ching2007
          @@ -241,6 +237,120 @@

          Transtitional Markov chain Monte Carlo +

          Bayesian Inference of Hierarchical Models

          +

          Consider for model calibration a dataset consisting of experimental results on test specimens of the same kind. Let \(\mathbf{y}_i\) denote the measured output response of the \(i^{th}\) specimen in the dataset \(\mathbf{Y} = \{\mathbf{y}_1, \mathbf{y}_2, ..., \mathbf{y}_{N_s}\}\) where \(N_s\) designates the number of specimens. Let \(\theta_i\) be the model parameter vector corresponding to the \(i^{th}\) specimen, where \(n_\theta\) denotes the number of model parameters. For the \(i^{th}\) specimen, the output response \(\mathbf{y}_i\) can be viewed as a function of \(\theta_i\) through the model \(\mathbf{h}\) and the following measurement equation:

          +
          +()\[\mathbf{y}_i = \mathbf{h}(\theta_i) + \mathbf{w}_i\]
          +

          where \(\mathbf{w}_i\) denotes the discrepancy between the response predicted by the model parameterized with \(\theta_i\), i.e., \(\mathbf{h}(\theta_i)\), and the experimental output response \(\mathbf{y}_i\); \(\mathbf{w}_i\) is termed the prediction error. With the measurement equation in (), the sources of real-world uncertainties such as the measurement noise during data collection and model form error are lumped and accounted for in the prediction error (also called noise) term \(\mathbf{w}_i\) (i.e., \(\mathbf{w}_i\) is also a proxy for model form error). In quoFEM, it is assumed that the prediction error is a zero-mean Gaussian white noise, thus,

          +
          +()\[\mathbf{w}_i \sim N(0, (\sigma_i^w)^2 \times I_{n_{\mathbf{y}_i} \times n_{\mathbf{y}_i}})\]
          +

          where \(\sigma_i^2\) denotes the variance of the prediction error \(\mathbf{w}_i\).

          +

          With the assumptions made in () and (), \(\mathbf{y}_i\) is Gaussian and centered at the model response \(\mathbf{h}(\theta_i)\), with a diagonal covariance matrix equal to \(\sigma_i^2 \times \mathbf{I}_{n_{\mathbf{y}_i} \times n_{\mathbf{y}_i}}\) i.e.,

          +
          +()\[p(\mathbf{y}_i | \theta_i, \sigma_i^2) = N(h(\theta_i), \sigma_i^2 \times \mathbf{I}_{n_{\mathbf{y}_i} \times n_{\mathbf{y}_i}})\]
          +

          In the UCSD_UQ engine, hierarchical Bayesian modeling is used to account for specimen-to-specimen variability in the parameter estimates. In the hierarchical Bayesian modeling realm, the parameter vectors \(\theta_1, \theta_2, \ldots, \theta_{N_s}\) are considered as mutually statistically independent and identically distributed (s.i.i.d) random variables following a PDF \(p(\theta | \eta)\). This is the PDF of the parent distribution, which represents the aleatory specimen-to-specimen variability.

          +

          The objective of hierarchical Bayesian inference is to jointly estimate the model parameters \(\theta_i\) for each specimen i (along with its prediction error variance \(\sigma_i^2\)) as well as the hyperparameters \(\eta\) of the parent distribution of the set \(\theta_i (i = 1, \ldots, N_s)\).

          +

          Making use of the experimental results for a single specimen, \(\mathbf{y}_i\), Bayes’ theorem for all parameters to be inferred from this specimen can be written as

          +
          +()\[p(\theta_i, \sigma_i^2, \eta | \mathbf{y}_i) \propto p(\mathbf{y}_i | \theta_i, \sigma_i^2, \eta) p(\theta_i, \sigma_i^2, \eta)\]
          +

          The specimen response \(\mathbf{y}_i\) depends solely on the model parameters \(\theta_i\) and the prediction error variance for that specimen, \(\sigma_i^2\), and is independent of the hyperparameters \(\eta\). Consequently, the conditional PDF \(p(\mathbf{y}_i | \theta_i, \sigma_i^2, \eta)\) reduces to \(p(\mathbf{y}_i | \theta_i, \sigma_i^2)\).

          +

          Assuming \(\sigma_i^2\) to be statistically independent of \(\theta_i\) and \(\eta\) in the joint prior PDF of \(\theta_i\), \(\sigma_i^2\), and \(\eta\), () becomes

          +
          +()\[p(\theta_i, \sigma_i^2, \eta | \mathbf{y}_i) \propto p(\mathbf{y}_i | \theta_i, \sigma_i^2) p(\sigma_i^2) p(\theta_i | \eta) p(\eta)\]
          +

          In the context of hierarchical Bayesian modeling, the entire experimental dataset from multiple specimens of the same kind, \(\mathbf{Y} = \{\mathbf{y}_1, \mathbf{y}_2, ..., \mathbf{y}_{N_s}\}\), is considered. The model parameters and the prediction error variances for all specimens are assumed to be mutually statistically independent, while the set of the model parameter estimates are assumed to be samples from a parent distribution. The figure figHierarchicalModel shows the structure of the hierarchical model.

          +
          +../../../_images/ProbabilisticGraphicalModel.png +

          Structure of the hierarchical model

          +
          +

          Under these assumptions, the equation for Bayesian updating of all unknown quantities in the hierarchical model, including the model parameters \(\Theta = \{\theta_1, \theta_2, \ldots, \theta_{N_s}\}\), measurement noise variances \(\mathbf{s} = \{\sigma_1^2, \sigma_2^2, \ldots, \sigma_{N_s}^2\}\), and hyperparameters \(\eta\) is given by

          +
          +()\[p(\Theta, \mathbf{s}, \eta | \mathbf{Y}) \propto p(\eta) \prod_{i=1}^{N_s}[p(\mathbf{y}_i | \theta_i, \sigma_i^2) p( \sigma_i^2) p(\theta_i | \eta) ]\]
          +

          The marginal posterior distribution of the hyperparameters, \(p(\eta | \mathbf{Y})\) , is obtained by marginalizing out \(\mathbf{\Theta}\) and \(\mathbf{s}\) from \(p(\Theta, \mathbf{s}, \eta | \mathbf{Y})\) as

          +
          +()\[p(\eta | \mathbf{Y}) = \int_{\Theta, \mathbf{s}} p(\Theta, \mathbf{s}, \eta | \mathbf{Y}) d\Theta d\mathbf{s}\]
          +

          The distribution \(p(\eta | \mathbf{Y})\) describes the epistemic uncertainty in the value of the hyperparameters \(\eta\) due to the finite number of specimens \(N_s\) in the experimental dataset.

          +

          In the hierarchical approach, the probability distribution of the model parameters conditioned on the entire measurement dataset, \(p(\theta | \mathbf{Y})\), is given by

          +
          +()\[p(\theta | \mathbf{Y}) = \int_\eta p(\theta | \eta) p(\eta | \mathbf{Y}) d\eta\]
          +

          The conditional distribution \(p(\theta | \eta)\) models the aleatory specimen-to-specimen variability. Therefore, the probability distribution \(p(\theta | \mathbf{Y})\), referred to as the posterior predictive distribution of the model parameters \(\theta\), encompasses both the aleatory specimen-to-specimen uncertainty and the epistemic estimation uncertainty (due to the finite number of specimens \(N_s\) in the experimental dataset and the finite length of the experimental data corresponding to each specimen). It can be utilized for uncertainty quantification and propagation in reliability and risk analyses.

          +
          +

          Special Case: Normal Population Distribution

          +

          The hierarchical modeling approach discussed above captures the specimen-to-specimen aleatory variability by modeling the model parameters corresponding to each experiment as a realization from a population distribution. In the UCSD_UQ engine, a multivariate normal distribution \(\theta | \eta \sim N (\mu_\theta, \Sigma_\theta)\) is adopted (i.e., \(\eta = (\mu_\theta, \Sigma_\theta)\)) as:

          +
          +()\[\begin{split}\theta_i & \stackrel{s.i.i.d}{\sim} N (\mu_\theta, \Sigma_\theta), \quad i = 1, \ldots, N_s \\ +\mu_\theta = \begin{bmatrix} \mu_{\theta_1} \\ \mu_{\theta_2} \\ \vdots \\ \mu_{\theta_{n_\theta}}\end{bmatrix}; \quad \Sigma_\theta &= \begin{bmatrix} \sigma_{\theta_1}^2 & cov(\theta_1, \theta_2) & \cdots & cov(\theta_1, \theta_{n_\theta}) \\ +cov(\theta_2, \theta_1) & \sigma_{\theta_2}^2 & \cdots & cov(\theta_2, \theta_{n_\theta}) \\ \vdots & \vdots & \ddots & \vdots \\ +cov(\theta_{n_\theta}, \theta_1) & cov(\theta_{n_\theta}, \theta_2) & \cdots & \sigma_{n_\theta}^2 \end{bmatrix}\end{split}\]
          +

          In the Bayesian inference process, the hyperparameters characterizing the population probability distribution, the hypermean vector \(\mu_\theta\) and the hypercovariance matrix \(\Sigma_\theta\) are jointly estimated with all the \(\theta_i\) s and \(\sigma_i^2\) s.

          +

          So, for this special case, () becomes

          +
          +()\[p(\Theta, \mathbf{s}, \mu_\theta, \Sigma_\theta | \mathbf{Y}) \propto p(\mu_\theta, \Sigma_\theta) \prod_{i=1}^{N_s}[p(\mathbf{y}_i | \theta_i, \sigma_i^2) p(\sigma_i^2) p(\theta_i | \mu_\theta, \Sigma_\theta) ]\]
          +

          with \(\Theta\), \(\mathbf{Y}\), and \(\mathbf{s}\) as defined above.

          +

          In the UCSD_UQ engine, the sampling algorithm operates in the standard normal space i.e.,

          +
          +()\[\begin{split}\theta_i & \stackrel{s.i.i.d}{\sim} N (\mu_\theta, \Sigma_\theta), \quad i = 1, \ldots, N_s \\ +\mu_\theta & = \begin{bmatrix} 0 \\ 0 \\ \vdots \\ 0\end{bmatrix}; \quad \Sigma_\theta = \begin{bmatrix} 1 & 0 & \cdots & 0 \\ +0 & 1 & \cdots & 0 \\ \vdots & \vdots & \ddots & \vdots \\ +0 & 0 & \cdots & 1 \end{bmatrix}\end{split}\]
          +

          and the Nataf transform is utilized to map the values provided by the sampling algorithm to the physical space of the model parameters before the model is evaluated.

          +
          +
          +

          Sampling the Posterior Probability Distribution of the Parameters of the Hierarchical Model

          +

          Due to the high dimensionality (\(n_\theta \times n_s + n_s + n_\theta + n_\theta \times \frac{(n_\theta+1)}{2}\), corresponding to the dimensions of the \(\theta_i\) of each dataset, \(\sigma_i^2\) for each dataset, \(\mu_\theta\) and \(\Sigma_\theta\), respectively) of the posterior joint PDF shown in (), the Metropolis within Gibbs algorithm is used to generate samples from the posterior probability distribution. To do this, conditional posterior distributions are derived for blocks of parameters from the joint posterior distribution () of all the parameters of the hierarchical model. The Gibbs sampler generates values from these conditional posterior distributions iteratively. The conditional posterior distributions are lower dimensional than the joint distribution. The assumptions made next result in a few of the conditional posterior distributions being of a form that can be easily sampled from, thereby making it feasible to draw samples from the high-dimensional joint posterior PDF of the hierarchical model.

          +

          The prior distributions for each \(\sigma_i^2\) are selected as the inverse gamma (IG) distribution:

          +
          +()\[p(\sigma_i^2) = IG(\alpha_0, \beta_0)\]
          +

          The prior probability distribution for \((\mu_\theta, \Sigma_\theta)\) is chosen to be the normal-inverse-Wishart (NIW) distribution:

          +
          +()\[p(\mu_\theta, \Sigma_\theta) = N(\mu_\theta | \mu_0, \frac{\Sigma_\theta}{\nu_0}) IW(\Sigma_\theta | \Sigma_0, m_0)\]
          +

          With these assumptions, the conditional posterior distributions are the following:

          +
          +()\[\begin{split}p(\Sigma_\theta &| \mathbf{Y}, \Theta, \mathbf{s}, \mu_\theta) \propto IW(\Sigma_\theta | \Sigma_n, m_n) \\ +p(\mu_\theta &| \mathbf{Y}, \Theta, \mathbf{s}, \Sigma_\theta) \propto N(\mu_\theta | \mu_n, \frac{\Sigma_\theta}{\nu_n}) \\ +p(\sigma_i^2 &| \mathbf{Y}, \Theta, \mu_\theta, \Sigma_\theta) \propto IG(\alpha_{n_i}, \beta_{n_i})\\ +p(\theta_i &| \mathbf{Y}, \mathbf{s}, \mu_\theta, \Sigma_\theta ) \propto p(\mathbf{y}_i | \theta_i, \sigma_i^2) p(\theta_i | \mu_\theta, \Sigma_\theta)\end{split}\]
          +

          where:

          +
          +()\[\begin{split}\nu_n &= \nu_0 + N_s \\ +\mu_n &= \frac{(\mu_0 * \lambda_0 + N_s * \bar{\theta})}{\nu_n} \\ +\Sigma_n &= \Sigma_0 + S + \frac{\nu_0 * N_s}{\nu_n} \times ((\bar{\theta} - \mu_0)(\bar{\theta} - \mu_0)^T) \\ +m_n &= m_0 + N_s \\ +\alpha_{n_i} &= \alpha_0 + \frac{n_{\mathbf{y}_i}}{2}\\ +\beta_{n_i} &= \beta_0 + \frac{{sse}_i}{2}\end{split}\]
          +

          and,

          +
          +()\[\begin{split}\bar{\theta} &= \frac{1}{N_s}\sum_{i=1}^{N_s} \theta_i \\ +S &= \sum_{i=1}^{N_s} {(\bar{\theta} - \mu_0)(\bar{\theta} - \mu_0)^T} \\ +{sse}_i &= \sum_{k=1}^{n_{\mathbf{y}_i}}(\mathbf{y}_i^{(k)} - \mathbf{h}(\theta_i)^{(k)})^2\end{split}\]
          +

          The Metropolis within Gibbs sampler generates values from the posterior joint PDF shown in () using the posterior conditional distributions () through the following steps:

          +
            +
          1. Select appropriate initial values for each of the \(\theta_i\).

          2. +
          3. Based on the \(k^{th}\) sample value, the \((k+1)^{th}\) sample value is obtained using the following steps:

            +
              +
            1. Generate a sample value of \(\Sigma_{\theta}^{(k+1)}\) from the conditional posterior distribution \(IW(\Sigma_n, m_n)\)

            2. +
            3. Generate a sample value of \(\mu_\theta^{(k+1)}\) from the conditional posterior distribution \(N(\mu_n, \frac{\Sigma_\theta}{\nu_n})\)

            4. +
            5. For each dataset, generate independently a sample value of \(\sigma_i^{2(k+1)}\) from the conditional posterior distribution of each \(\sigma_i^2\): \(IG(\alpha_n, \beta_n)\)

            6. +
            7. For each dataset, generate a sample value of the model parameters \(\theta_i\) from the conditional posterior \(p(\mathbf{y}_i | \theta_i, \sigma_i^2) p(\theta_i | \mu_\theta, \Sigma_\theta)\) with a Metropolis-Hastings step as follows:

              +
                +
              1. Generate a candidate sample \(\theta_{i(c)}\) from a local random walk proposal density \(\theta_{i(c)} \sim N(\theta_i^{(k)}, \Sigma_i^{(k)})\) where \(\Sigma_i^{(k)}\) is the proposal covariance matrix of the random walk.

              2. +
              3. Calculate the acceptance ratio

              4. +
              +
              +()\[a_c = \frac{p(\mathbf{y}_i | \theta_{i(c)}, \sigma_i^{2(k+1)}) p(\theta_{i(c)} | \mu_\theta^{(k+1)}, \Sigma_{\theta}^{(k+1)})}{p(\mathbf{y}_i | \theta_i^{(k)}, \sigma_i^{2(k+1)}) p(\theta_i^{(k)}| \mu_\theta^{(k+1)}, \Sigma_{\theta}^{(k+1)})}\]
              +
                +
              1. Generate a random value \(u\) from a uniform distribution on [0, 1] and set

              2. +
              +
              +()\[\begin{split}\theta_i^{(k+1)} = \quad &\theta_{i(c)} \quad \text{if} \quad u < a_c \\ +&\theta_i^{(k)} \quad \text{otherwise}\end{split}\]
              +
            8. +
            +
          4. +
          +

          After an initial burn-in period, the sample values generated by this algorithm converge to the target density. The proposal covariance matrix of the random walk \(\Sigma_i^{(k)}\) is selected to facilitate proper mixing of the random walks used to generate sample values of the \(\theta_i\). Within the adaptation duration, a scaled version of the covariance matrix of the sample values of the last \(N_{cov}\) samples (defined as the adaptation frequency in the UCSD_UQ engine) is used, to keep the acceptance rate in the range of 0.2 to 0.5.

          +
          +

          @@ -253,7 +363,7 @@

          Transtitional Markov chain Monte Carlo

          - © Copyright 2023, The Regents of the University of California. + © Copyright 2024, The Regents of the University of California.

          diff --git a/docs/common/technical_manual/desktop/damping.html b/docs/common/technical_manual/desktop/damping.html index 367439ce..87841e5f 100644 --- a/docs/common/technical_manual/desktop/damping.html +++ b/docs/common/technical_manual/desktop/damping.html @@ -40,6 +40,7 @@ + @@ -50,7 +51,7 @@ - + @@ -129,11 +130,6 @@
        • 5. Requirements
        • 6. Bugs & Feature Requests
        -

        Damage and Loss DB

        -

        Technical Manual

      @@ -224,15 +221,15 @@
      -

      1.3. Damping Options

      +

      1.3. Damping Options

      The standard equations that are solved in the nonlinear analysis of structures subjected to dynamic forces are:

      (1.3.1)\[M \ddot{U}(t) + C \dot{U}(t) + Fs(U(t)) = P(t)\]

      where \(U(t), \dot{U}(t), \ddot{U}(t)\) are the vectors of displacements, velocities, and accelerations for the degrees of freedom, \(M\) and \(C\) are the mass and damping matrices, respectively, and the vector \(Fs(U)\) represents the nonlinear relation between resisting forces and deformations, which includes both material and geometric nonlinearities, and \(P(t)\) the time-varying applied load due to the event of interest.

      -

      Energy is dissipated by the structure as it deforms, which is why it to come to rest when the force is removed. The \(Fs(U(t))\) term captures the hysteretic energy dissipated through the nonlinear behavior of the structural members. The \(C \dot{U}(t)\) term, the viscous damping term, attempts to capture energy dissipated through other mechanisms present in the structure, e.g. thermal effects from repeated elastic straining of structural materials, repeated straining of nonstructural elements—partition walls, mechanical equipment, fire proofing, and so on—friction at steel connections, opening and closing of microcracks in concrete, friction between the structure itself and nonstructural elements, and other mechanisms, some of which are even difficult to identify. Damping for such is often quantified in terms of modal damping ratios, and are typically of the order of 1% (steel buildings) to 5% (concrete buildings). These the values have been obtained from field testing and system identification, albeit they have mostly been obtained from buildings undergoing low levels of vibration.

      +

      Energy is dissipated by the structure as it deforms, which is why it comes to rest when the force is removed. The \(Fs(U(t))\) term captures the hysteretic energy dissipated through the nonlinear behavior of the structural members. The \(C \dot{U}(t)\) term, the viscous damping term, attempts to capture energy dissipated through other mechanisms present in the structure, e.g. thermal effects from repeated elastic straining of structural materials, repeated straining of nonstructural elements—partition walls, mechanical equipment, fireproofing, and so on—friction at steel connections, opening and closing of microcracks in concrete, friction between the structure itself and nonstructural elements, and other mechanisms, some of which are even difficult to identify. Damping for such is often quantified in terms of modal damping ratios, and are typically of the order of 1% (steel buildings) to 5% (concrete buildings). These values have been obtained from field testing and system identification, albeit they have mostly been obtained from buildings undergoing low levels of vibration.

      It is the formulation of the \(C\) matrix that is of interest here. There are two damping options presented to the user as inputs to the FEM panel: 1) Rayleigh Damping Options and 2) Modal Damping options. This is a brief overview of the theory behind both.

      -

      Rayleigh Damping

      +

      Rayleigh Damping

      A classical damping matrix can be assembled as a linear combination of the mass and stiffness matrices:

      (1.3.2)\[C = a_0 M + a_1 K\]
      @@ -281,7 +278,7 @@

      Rayleigh Damping -

      Modal Damping

      +

      Modal Damping

      In modal damping the eigenvectors \(\Phi\) of the \(N\) degree-of-freedom system are used to create the \(C\) matrix.

      (1.3.9)\[C = M \left ( \sum_{m=1}^{N} \frac{2 \zeta_m \omega_m}{M_m} \phi_m \phi_m^TC \dot{U} \right ) M\]
      @@ -313,7 +310,7 @@

      Modal Damping

      - © Copyright 2023, The Regents of the University of California. + © Copyright 2024, The Regents of the University of California.

      diff --git a/docs/common/technical_manual/desktop/hazard_occurrence.html b/docs/common/technical_manual/desktop/hazard_occurrence.html index 3d6cb501..d915a937 100644 --- a/docs/common/technical_manual/desktop/hazard_occurrence.html +++ b/docs/common/technical_manual/desktop/hazard_occurrence.html @@ -40,6 +40,7 @@ + @@ -127,11 +128,6 @@
    • 5. Requirements
    • 6. Bugs & Feature Requests
    -

    Damage and Loss DB

    -

    Technical Manual

    -

    Damage and Loss DB

    -

    Technical Manual

    -
      -
    • 1. Technical Manual
    • +

      Developer Manual

        @@ -191,7 +204,9 @@
      • »
      • -
      • Ground Motion Intensity Spatial Correlation Model Options
      • +
      • 1. Technical Manual »
      • + +
      • 1.4. Ground Motion Intensity Spatial Correlation Model Options
      • @@ -211,10 +226,10 @@
        -

        Ground Motion Intensity Spatial Correlation Model Options

        +

        1.4. Ground Motion Intensity Spatial Correlation Model Options

        The regional seismic risk analysis requires the prediction of ground motion intensities at multiple sites. Such joint predictions need to consider the correlation between ground motion intensities at different sites given a specific earthquake scenario. In general, ground motion models predict intensities at an individual site \(i\) due to an earthquake \(j\) have the following form:

        -()\[ln(Y_{ij}) = ln(\bar{Y}_{ij}) + \epsilon_{ij} + \eta_j\]
        +(1.4.1)\[ln(Y_{ij}) = ln(\bar{Y}_{ij}) + \epsilon_{ij} + \eta_j\]

        where \(Y_{ij}\) is the intensity measure (e.g., \(Sa(T)\)), \(\bar{Y}_{ij}\) is the predicted median intensity (given magnitude, distance, period, and site conditions), \(\epsilon_{ij}\) is the intra-event residual, and \(\eta_j\) is the inter-event residual. It is assumed that \(\epsilon_{ij}\) and \(\eta_j\) are random variables with zero means and standard deviations \(\sigma_{ij}\) and \(\tau_j\).

        Note

        @@ -223,50 +238,52 @@
      • Inter-event residual quantifies the deviation of intensities at a specific site given different earthquake realizations.

    +
    +

    Intra-event Correlation Model Options

    [Jayaram08] found that the spatially distributed intra-event residuals \(\epsilon_j = (\epsilon_{1j}, \epsilon_{2j}, ..., \epsilon_{dj})\) follows a multivariate normal distribution. This multivariate normal distribution can be defined by the mean, variance, and correlation (between \(\epsilon_{i_1j}\) and \(\epsilon_{i_2j}\)). The mean is zero (as discussed previously) and the variance can be predicted by ground motion models, but the correlation between residuals at two different sites needs to be described. The semivariogram \(\gamma(u,u^\prime)\) is used to describe the expected squared difference between two locations \(u\) and \(u^\prime\). Because it is very difficult to obtain several observations of a random variable at a given pair of sites, the stationarity assumption is usually applied to simplify it to a more trackable problem. It is typically assumed that the semivariogram only depends on the distance \(h\) - the stationary semivariogram \(\gamma(h)\) can be obtained from data as follows:

    -()\[\gamma(h) = \frac{1}{2}[E(Z_u - Z_{u+h})^2]\]
    +(1.4.2)\[\gamma(h) = \frac{1}{2}[E(Z_u - Z_{u+h})^2]\]

    where \(Z_u\) and \(Z_{u+h}\) are the random variable realizations at sites with a distance of \(h\). The covariance between \(Z_u\) and \(Z_{u+h}\) are:

    -()\[C(h) = E[(Z_u - \mu_Z)(Z_{u+h} - \mu_Z)]\]
    +(1.4.3)\[C(h) = E[(Z_u - \mu_Z)(Z_{u+h} - \mu_Z)]\]

    where \(\mu_Z\) is the mean (which is zero under the stationarity assumption). Note this spatial covariance can also be related to the semivariogram with:

    -()\[C(h) = C(0) - \gamma(h)\]
    +(1.4.4)\[C(h) = C(0) - \gamma(h)\]

    Similarly, the correlation coefficient is defined as:

    -()\[\rho(h) = \frac{C(h)}{C(0)} = 1 - \frac{\gamma(h)}{C(0)}\]
    +(1.4.5)\[\rho(h) = \frac{C(h)}{C(0)} = 1 - \frac{\gamma(h)}{C(0)}\]

    Given the semivariogram is often preferred in geostatistical practice (because it does not require a prior estimation of the mean), many studies were carried to find the semivariogram models to derive the correlation \(rho(h)\) of ground motion intensities. The available models in the current EE-UQ app are briefly summarized in following sections.

    -

    Jayaram and Baker (2009)

    +

    Jayaram and Baker (2009)

    [Jayaram09] adopted a exponential model for the semivariogram function with a isotropic hypothesis (i.e., the distance \(h\) is the separation length):

    -()\[\gamma(h) = a[1 - exp(-3h / b)]\]
    +(1.4.6)\[\gamma(h) = a[1 - exp(-3h / b)]\]

    where a and b are two modeling coefficients, namely sill and the range of the semivariogram function, respectively. When \(h = 0\), \(\gamma(h=0) = 0\) which leads to \(\rho(h = 0) = 1\). As the distance between two sites increases, i.e., \(h\) increases, \(\gamma(h)\) increases and \(\rho(h)\) decreases, which is consistent with the decaying trend of correlation between the two sites. After calibrating the model to past earthquake recordings, the following model was proposed for predicting the spatial correlation \(\rho(h)\):

    -()\[\rho(h) = exp(-3h / b)\]
    +(1.4.7)\[\rho(h) = exp(-3h / b)\]

    The range of the semivariogram function \(b\) was found to depend on the similarity of \(V_{S30}\) values in the given region. If the \(V_{S30}\) values do not show clustering, the \(b\) is computed by:

    -()\[ \begin{align}\begin{aligned}b = 8.5 + 17.2T, T < 1s\\b = 22.0 + 3.7T, T \leq 1s\end{aligned}\end{align} \]
    +(1.4.8)\[ \begin{align}\begin{aligned}b = 8.5 + 17.2T, T < 1s\\b = 22.0 + 3.7T, T \leq 1s\end{aligned}\end{align} \]

    where T is the period. If the \(V_{S30}\) values are very close in the given region, the \(b\) can be computed by:

    -()\[ \begin{align}\begin{aligned}b = 40.7 - 15.0T, T < 1s\\b = 22.0 + 3.7T, T \leq 1s\end{aligned}\end{align} \]
    +(1.4.9)\[ \begin{align}\begin{aligned}b = 40.7 - 15.0T, T < 1s\\b = 22.0 + 3.7T, T \leq 1s\end{aligned}\end{align} \]

    Note

    Earthquakes that were considered in the development: Anza earthquake, Alum Rock earthquake, Parkfield earthquake, Chi-Chi earthquake, Northridge earthquake, Big Bear City earthquake, and Chino Hills earthquake.

    -

    Loth and Baker (2013)

    +

    Loth and Baker (2013)

    Note that the cross-semivariograms between different pairs of intensity measures can be different, for instance, \(\rho_{Sa(T=0.1s),Sa(T=0.2s)}(h)\) might be greater than \(\rho_{Sa(T=0.1s),Sa(T=1s)}(h)\). This means one needs to repeat a calibration process many times to develop semivariogram functions and correlation models that have higher resolutions (i.e., direct semivariogram fit). Instead of fitting each semivariogram independently, [Loth13] proposed a predictive model for spatial covariance of spectral accelerations at different periods:

    -()\[\textbf{C}(h) = \textbf{B}^1 exp(-3h/20) + \textbf{B}^2 exp(-3h/70) + \textbf{B}^3 I_{h=0}\]
    +(1.4.10)\[\textbf{C}(h) = \textbf{B}^1 exp(-3h/20) + \textbf{B}^2 exp(-3h/70) + \textbf{B}^3 I_{h=0}\]

    where \(I_{h=0}\) is the indicator function equal to 1 at \(h = 0\) and 0 otherwise. And the three coefficient matrices \(\textbf{B}^1\), \(\textbf{B}^2\), and \(\textbf{B}^3\) were calibrated by 2080 recordings from 8 earthquakes.

    -
    +
    ../../../_images/spatial_correlation_1.png -

    Location of recordings from the 8 earthquakes considered by [Loth13]

    +

    Fig. 1.4.1 Location of recordings from the 8 earthquakes considered by [Loth13]

    -

    - +
    Short-range coregionalization matrix, \(\textbf{B}^1\)
    +@@ -392,8 +409,8 @@

    Loth and Baker (2013)

    Table 1.4.1 Short-range coregionalization matrix, \(\textbf{B}^1\)
    - - +
    Short-range coregionalization matrix, \(\textbf{B}^2\)
    +@@ -519,8 +536,8 @@

    Loth and Baker (2013)

    Table 1.4.2 Short-range coregionalization matrix, \(\textbf{B}^2\)
    - - +
    Short-range coregionalization matrix, \(\textbf{B}^3\)
    +@@ -648,19 +665,19 @@

    Loth and Baker (2013)
    -

    Markhvida et al. (2017)

    +

    Markhvida et al. (2017)

    [Markhvida17] proposed to use Principal Component Analysis (PCA) to develop the predictive model for cross-correlograms. In theorem, PCA performs a linear transformation of the variables of interests to an orthogonal basis, where the resulting projections onto the new basis are uncorrelated:

    -()\[\textbf{P} \textbf{Z} = \textbf{Y}\]
    +(1.4.11)\[\textbf{P} \textbf{Z} = \textbf{Y}\]

    where \(\textbf{P}\) is an orthogonal linear transformation matrix, \(\textbf{Z}\) is the original data matrix, and \(\textbf{Y}\) is the transformed variable matrix which contains uncorrelated principal components \(\textbf{Y}_i\). Since \(\textbf{P}\) is orthogonal, so the inversion is easy to compute:

    -()\[\textbf{Z} = \textbf{P}^{-1} \textbf{Y} = \textbf{P}^{T} \textbf{Y}\]
    +(1.4.12)\[\textbf{Z} = \textbf{P}^{-1} \textbf{Y} = \textbf{P}^{T} \textbf{Y}\]

    For each principal component, one covariance model is developed:

    -()\[C_i(h) = c_{0i}I_{h=0} + c_{1i} exp(-3h/a_{1i}) + c_{2i} exp(-3h/a_{2i})\]
    +(1.4.13)\[C_i(h) = c_{0i}I_{h=0} + c_{1i} exp(-3h/a_{1i}) + c_{2i} exp(-3h/a_{2i})\]

    where \(c_{0i}\), \(c_{1i}\), \(c_{2i}\), \(a_{1i}\), and \(a_{2i}\) are modeling coefficients for \(i^{th}\) principal component. Instead of directly simulating the desired intensity measures, this PCA-based method would first simulate uncorrelated variables using \(C_i(h)\) and then transform them back to intensity measures.

    -

    Table 1.4.3 Short-range coregionalization matrix, \(\textbf{B}^3\)
    - +
    Principal component transformation coefficients
    +@@ -1107,9 +1124,9 @@

    Markhvida et al. (2017)

    Table 1.4.4 Principal component transformation coefficients

    The general idea is to include more degrees of freedom in the predictive model if compared to linear models (e.g., [Loth13]). The figure below contrasts the correlation coefficient functions by PCA and the linear model by [Loth13].

    -
    +
    ../../../_images/spatial_correlation_2.png -

    Comparison of principal component analysis (PCA) model and linear model of coregionalization (LMC) correlograms and cross-correlograms ([Loth13]) for different periods

    +

    Fig. 1.4.2 Comparison of principal component analysis (PCA) model and linear model of coregionalization (LMC) correlograms and cross-correlograms ([Loth13]) for different periods

    Jayaram08
    @@ -1126,6 +1143,33 @@

    Markhvida et al. (2017)

    +
    +
    +

    Inter-event Correlation Model Options

    +

    [Baker08] presented equations to predict the inter-event residual correlations of spectral acceleration values, +using the Next Generation Attenuation (NGA) ground motion library and the new NGA +ground motion models (GMMs). A predictive equation was presented that provides +correlations between logarithmic spectral accelerations at two periods. This equation was observed to be valid for +a variety of definitions of spectral acceleration (i.e., spectral acceleration of +an individual component, the geometric mean of spectral accelerations from two orthogonal +components, and the orientation-independent GMRotI definition used by the NGA modelers)

    +

    The correlation equations are applicable for use with any of the NGA ground motion +models at periods between 0.01 and 10 seconds. When the periods of interest are less +than 5 seconds, correlation coefficients from all considered models are essentially identical. If one period is greater than 5 seconds and the second period is significantly less +than 5 seconds, correlations vary slightly among models. These variations are likely due +to a lack of empirical data, and these widely-spaced period pairs are also of less engineering interest, so separate correlation equations were not developed for each model. +The similarity of correlations from the various GMMs occurs because the correlations +are dominated by the large record-to-record variability in observed spectral values from +similar events. While slight differences in mean predicted values from the GMMs may +be important for some applications, they do not affect computed values to a large +enough extent that correlations change noticeably. The predictive equations (Eq. 5 and Eq. 6 in [Baker08]) +are implemented in R2D.

    +
    +
    Baker08(1,2)
    +

    Baker, J. W., & Jayaram, N. (2008). Correlation of spectral acceleration values from NGA ground motion models. Earthquake Spectra, 24(1), 299-317.

    +
    +
    +
    @@ -1138,7 +1182,7 @@

    Markhvida et al. (2017)

    - © Copyright 2023, The Regents of the University of California. + © Copyright 2024, The Regents of the University of California.

    diff --git a/docs/common/technical_manual/desktop/technical_manual.html b/docs/common/technical_manual/desktop/technical_manual.html index f281a49c..938791c0 100644 --- a/docs/common/technical_manual/desktop/technical_manual.html +++ b/docs/common/technical_manual/desktop/technical_manual.html @@ -40,6 +40,7 @@ + @@ -50,7 +51,7 @@ - + @@ -128,17 +129,13 @@
  • 5. Requirements
  • 6. Bugs & Feature Requests
-

Damage and Loss DB

-

Technical Manual

@@ -217,12 +214,13 @@ diff --git a/docs/common/technical_manual/desktop/uqTechnical.html b/docs/common/technical_manual/desktop/uqTechnical.html index 9aec5fa6..badb55d6 100644 --- a/docs/common/technical_manual/desktop/uqTechnical.html +++ b/docs/common/technical_manual/desktop/uqTechnical.html @@ -40,6 +40,7 @@ + @@ -128,17 +129,13 @@
  • 5. Requirements
  • 6. Bugs & Feature Requests
  • -

    Damage and Loss DB

    -

    Technical Manual

    @@ -219,7 +216,7 @@
    -

    1.1. Dakota Methods

    +

    1.1. Dakota Methods

    The methods and theory implemented by the Dakota application are best described by Dakota’s developers. A comprehensive Dakota Theory Manual is available.

    @@ -233,7 +230,7 @@

    - © Copyright 2023, The Regents of the University of California. + © Copyright 2024, The Regents of the University of California.

    diff --git a/docs/common/testbeds/anchorage/anchorage.html b/docs/common/testbeds/anchorage/anchorage.html index 93dd5bb9..46415124 100644 --- a/docs/common/testbeds/anchorage/anchorage.html +++ b/docs/common/testbeds/anchorage/anchorage.html @@ -40,6 +40,7 @@ + @@ -126,11 +127,6 @@
  • 5. Requirements
  • 6. Bugs & Feature Requests
  • -

    Damage and Loss DB

    -

    Technical Manual

    -

    Damage and Loss DB

    -

    Technical Manual

    • 1. Technical Manual
    • @@ -210,14 +206,14 @@
      -

      Asset Description

      +

      Asset Description

      This section describes how a large-scale building inventory was constructed in two phases. The initial phase of this work involved identifying the attributes needed. The second phase comprised obtaining these attributes for each building using machine learning and computer vision techniques to create a core set of attributes. The remaining attributes were then obtained using other data sources as discussed below.

      -

      Phase I: Attribute Definition

      +

      Phase I: Attribute Definition

      All the attributes required for loss estimation were first identified to develop the Building Inventory data model. This Building Inventory data model presented in tab-bldg_inv_data_model_ac provides a set of attributes that are assigned to each asset to form the building inventory file @@ -536,7 +532,7 @@

      Phase I: Attribute Definition -

      Phase II: Inventory Generation

      +

      Phase II: Inventory Generation

      This section describes how the large-scale building inventory was constructed for Atlantic County using a phased approach that used machine learning, computer vision algorithm and data distributions to generate all attributes required for the corresponding loss assessment. It is emphasized that the intent is @@ -546,7 +542,7 @@

      Phase II: Inventory Generationtab-bldg_inv_data_model_ac, a description of the attribute and information on how the data was identified and validated is presented.

      -

      Phase II: Footprint Selection

      +

      Phase II: Footprint Selection

      Inventory development began with the footprint Data generated by the New Jersey Department of Environmental Protection (NJDEP). These NJDEP footprints include flood-exposed properties cataloged in two geodatabases encompassing approximately 453,000 footprints across the entire state:

      @@ -563,14 +559,14 @@

      Phase II: Footprint Selection -

      AI/ML Techniques combined with Computer Vision

      +

      AI/ML Techniques combined with Computer Vision

      Most of the key building attributes were generated using SimCenter’s BRAILS. The following

      is a brief description of how these attributes were obtained and the utilized methods were validated.

      -

      Attribute: NumberOfStories

      +

      Attribute: NumberOfStories

      Number of floors of each building is determined using an object detection procedure implemented in BRAILS. A detection model that can automatically detect rows of building windows was established to generate the image-based detections of visible floor locations from street-level images. The model was trained on the @@ -611,7 +607,7 @@

      Attribute: NumberOfStories -

      Attribute: MeanRoofHt

      +

      Attribute: MeanRoofHt

      The elevation of the bottom plane of the roof (lowest edge of roof line) and elevation of the roof (peak of gable or apex of hip) are estimated with respect to grade (in feet) from street-level imagery. These geometric properties are defined visually for common residential coastal typologies in @@ -663,12 +659,12 @@

      Attribute: NumberOfStories -

      Attribute: FirstFloorElevation

      +

      Attribute: FirstFloorElevation

      FirstFloorElevation is calculated using the distance between the bottom of the facade mask and the bottom of the fron door of the building. The process of obtaining these masks follow the same approach used for roof mean height and is not repeated here.

      -

      Attribute: RoofSlope

      +

      Attribute: RoofSlope

      RoofSlope is calculated as the ratio between the roof height and the roof run. Roof height is obtained by determining the difference between the bottom plane and apex elevations of the roof as defined in the Attribute: MeanRoofHt @@ -681,7 +677,7 @@

      Attribute: RoofSlope

      -

      Attribute: RoofShape

      +

      Attribute: RoofShape

      The RoofShape is obtained by CityBuilder using the BRAILS Roof shape module. The roof shape module determines roof shape based on a satellite image obtained for the building. The module uses machine learning, specifically it utilizes a convolutional neural network that has been trained on satellite @@ -714,7 +710,7 @@

      Attribute: RoofShape

      -

      Attribute: RoofSlope

      +

      Attribute: RoofSlope

      RoofSlope is calculated as the ratio between the roof height and the roof run. Roof height is obtained by determining the difference between the bottom plane and apex elevations of the roof as defined in the Attribute: MeanRoofHt @@ -727,7 +723,7 @@

      Attribute: RoofSlope -

      Attribute: WindowArea

      +

      Attribute: WindowArea

      The proportion of windows to the overall surface area is not available in inventory and

      assessor datasets though required for wind loss modeling. Generally, window area can be assumed based on the building occupancy class given Department of Energy industry databases. @@ -763,7 +759,7 @@

      Attribute: WindowArea

      -

      Phase III: Augmentation Using Third-Party Data

      +

      Phase III: Augmentation Using Third-Party Data

      Attributes were then parsed from third-party data providers to populate all required attributes in the Building Inventory data model. For the Flood-Exposed Inventory, NJDEP had already enriched these footprints with various attributes necessary to conduct standard FEMA risk assessments. Specifically, all footprints included a set of @@ -1049,7 +1045,7 @@

      Phase III: Augmentation Using Third-Party Data -

      Populated Inventories

      +

      Populated Inventories

      Executing this four-phase process resulted in the assignment of all required attributes at the asset description stage of the workflow for both the Atlantic County Inventory and the Flood-Exposed Inventory. bldg_inv_ac and bldg_inv_fei provide respective examples of each of these inventories. @@ -2042,7 +2038,7 @@

      Phase III: Augmentation Using Third-Party Data

      - © Copyright 2023, The Regents of the University of California. + © Copyright 2024, The Regents of the University of California.

      diff --git a/docs/common/testbeds/atlantic_city/asset_representation.html b/docs/common/testbeds/atlantic_city/asset_representation.html index 8cacab42..8e21cf0c 100644 --- a/docs/common/testbeds/atlantic_city/asset_representation.html +++ b/docs/common/testbeds/atlantic_city/asset_representation.html @@ -40,6 +40,7 @@ + @@ -126,11 +127,6 @@
    • 5. Requirements
    • 6. Bugs & Feature Requests
    -

    Damage and Loss DB

    -

    Technical Manual

    -

    Damage and Loss DB

    -

    Technical Manual

    • 1. Technical Manual
    • @@ -210,7 +206,7 @@
      -

      Best Practices

      +

      Best Practices

      The process of constructing the Atlantic County Inventory for footprints beyond those in the Flood-Exposed Inventory underscored a number of tasks/issues that are commonly encountered when constructing an inventory in a location with sparse inventory data. Recommended best practices are summarized as follows:

      @@ -265,7 +261,7 @@

      - © Copyright 2023, The Regents of the University of California. + © Copyright 2024, The Regents of the University of California.

      diff --git a/docs/common/testbeds/atlantic_city/damage_and_loss.html b/docs/common/testbeds/atlantic_city/damage_and_loss.html index 4740adfc..a1067464 100644 --- a/docs/common/testbeds/atlantic_city/damage_and_loss.html +++ b/docs/common/testbeds/atlantic_city/damage_and_loss.html @@ -40,6 +40,7 @@ + @@ -127,11 +128,6 @@
    • 5. Requirements
    • 6. Bugs & Feature Requests
    -

    Damage and Loss DB

    -

    Technical Manual

    • 1. Technical Manual
    • @@ -211,7 +207,7 @@
      -

      Damage and Loss Estimation

      +

      Damage and Loss Estimation

      Damage and loss functions from the HAZUS Hurricane Damage and Loss Model ([FEMA18a], [FEMA18b]) were implemented in PELICUN to support loss assessment for all configurations of buildings currently supported by HAZUS for wind and flood hazards. These @@ -34506,7 +34502,7 @@

      - © Copyright 2023, The Regents of the University of California. + © Copyright 2024, The Regents of the University of California.

      diff --git a/docs/common/testbeds/atlantic_city/example_outputs.html b/docs/common/testbeds/atlantic_city/example_outputs.html index d63708b5..3399784e 100644 --- a/docs/common/testbeds/atlantic_city/example_outputs.html +++ b/docs/common/testbeds/atlantic_city/example_outputs.html @@ -40,6 +40,7 @@ + @@ -126,11 +127,6 @@
    • 5. Requirements
    • 6. Bugs & Feature Requests
    -

    Damage and Loss DB

    -

    Technical Manual

    -

    Damage and Loss DB

    -

    Technical Manual

    • 1. Technical Manual
    • @@ -210,7 +206,7 @@
      -

      Feedback

      +

      Feedback

      If you have any feedback, data requests, or questions, please post on the SimCenter Regional Testbeds. When creating a New Topic it would be helpful if you could place an indication of your post in the Subject area:

        @@ -232,7 +228,7 @@

        - © Copyright 2023, The Regents of the University of California. + © Copyright 2024, The Regents of the University of California.

        diff --git a/docs/common/testbeds/atlantic_city/future_refinements.html b/docs/common/testbeds/atlantic_city/future_refinements.html index 5a77b213..960421fc 100644 --- a/docs/common/testbeds/atlantic_city/future_refinements.html +++ b/docs/common/testbeds/atlantic_city/future_refinements.html @@ -40,6 +40,7 @@ + @@ -126,11 +127,6 @@
      1. 5. Requirements
      2. 6. Bugs & Feature Requests
    -

    Damage and Loss DB

    -

    Technical Manual

    • 1. Technical Manual
    • @@ -210,7 +206,7 @@
      -

      Opportunity Areas for Future Refinements

      +

      Opportunity Areas for Future Refinements

      This testbed and its backing workflows should be viewed as a sandbox and scaffold, respectively, within which the community can explore different scenarios and develop new capabilities. The following list itemizes some areas where contribution from the @@ -275,7 +271,7 @@

      - © Copyright 2023, The Regents of the University of California. + © Copyright 2024, The Regents of the University of California.

      diff --git a/docs/common/testbeds/atlantic_city/hazard_characterization.html b/docs/common/testbeds/atlantic_city/hazard_characterization.html index 9d45c826..6cd0e5a7 100644 --- a/docs/common/testbeds/atlantic_city/hazard_characterization.html +++ b/docs/common/testbeds/atlantic_city/hazard_characterization.html @@ -40,6 +40,7 @@ + @@ -127,11 +128,6 @@
    • 5. Requirements
    • 6. Bugs & Feature Requests
    -

    Damage and Loss DB

    -

    Technical Manual

    • 1. Technical Manual
    • @@ -211,7 +207,7 @@
      -

      Hazard Characterization

      +

      Hazard Characterization

      Both the wind and flood hazards affect the building inventory in this testbed. As the initial implementation of the regional assessment workflow incorporates the HAZUS Hurricane Damage and Loss Assessment methodology, hazards are quantified by two intensity measures: Peak Wind Speed (PWS) and Peak Water Depth (PWD). @@ -223,7 +219,7 @@ Note that as part of the Asset Representation Process (see Asset Representation), the design wind speeds from ASCE 7 are already included for each building footprint for reference.

      -

      Synthetic Storm Scenario

      +

      Synthetic Storm Scenario

      An Atlantic City landfall scenario was generated using the Storm Hazard Projection Tool developed in the NJcoast project ([NJCoast20]). The constructed hazard scenario uses NJcoast’s basic simulation option, which identifies the 25 hurricane tracks from the SHP tool’s surrogate model that match the targeted @@ -233,7 +229,7 @@ to inundate coastal areas in the testbed geography and generate significant wave run-up in some locales. The SHP Tool generates these through the following underlying computational models.

      -

      Wind Modeling

      +

      Wind Modeling

      The SHP Tool generates its wind fields using a highly efficient, linear analytical model for the boundary layer winds of a moving hurricane developed by Snaiki and Wu ([Snaiki17a], [Snaiki17b]). To account for the exposure in each New Jersey county, an effective roughness length (weighted average) @@ -266,7 +262,7 @@

      Wind Modeling -

      Storm Surge Modeling

      +

      Storm Surge Modeling

      Coastal hazard descriptions use the outputs of the aforementioned SHP Tool, which estimates storm surge and total run up due to the breaking of near-shore waves for an arbitrary hurricane scenario using surrogate modeling techniques ([Jia13], [Jia15]). The SHP Tool @@ -297,7 +293,7 @@

      Wind Modeling -

      Multiple Category Analysis (MCA)

      +

      Multiple Category Analysis (MCA)

      Note that the resulting 3s-gust PWS values by this Category-5 hurricane is much higher than the design wind speed specified by ASCE 7-16 ([ASCE16]) for the Atlantic County which ranges from 105 mph to 115 mph. Since this extreme scenario bears a small likelihood, this testbed @@ -359,7 +355,7 @@

      Multiple Category Analysis (MCA) -

      Historical Storm Scenario

      +

      Historical Storm Scenario

      Hindcast simulations of historical storm events are equally valuable, particularly when they are coupled with observations of damage and loss across an inventory. As such this testbed includes the option to use existing hindcast data from established community providers as input to the loss estimation workflow. @@ -371,7 +367,7 @@

      Historical Storm Scenario -

      Wind Modeling

      +

      Wind Modeling

      Hindcast wind fields for this event were made available by Peter Vickery and Applied Research Associates (ARA). Their hurricane model derives wind speeds based on numerically solving the differential equations of a translating storm and iteratively calibrating based on field observations over the weeks following an event. @@ -388,7 +384,7 @@

      Wind ModelingARA_Example.zip.

      -

      Storm Surge Modeling

      +

      Storm Surge Modeling

      ADCIRC hindcast of Superstorm Sandy was generated by the Westerink Group at the University of Notre Dame and made available to the SimCentetr. adcirc_pwd shows the peak storm surge from the hindcast. Note that the scope of the hindcast focused on the heavier-impacted regions of New York and Northern New Jersey, @@ -505,7 +501,7 @@

      Storm Surge Modeling

      - © Copyright 2023, The Regents of the University of California. + © Copyright 2024, The Regents of the University of California.

      diff --git a/docs/common/testbeds/atlantic_city/index.html b/docs/common/testbeds/atlantic_city/index.html index 99e8a4d6..da789f1c 100644 --- a/docs/common/testbeds/atlantic_city/index.html +++ b/docs/common/testbeds/atlantic_city/index.html @@ -40,6 +40,7 @@ + @@ -126,11 +127,6 @@
    • 5. Requirements
    • 6. Bugs & Feature Requests
    -

    Damage and Loss DB

    -

    Technical Manual

    -

    Damage and Loss DB

    -

    Technical Manual

    • 1. Technical Manual
    • @@ -210,7 +206,7 @@
      -

      Best Practices

      +

      Best Practices

      Recommended best practices are summarized as follows:

      1. Inventories are based upon building footprint data which may be sourced from state/local authorities or @@ -264,7 +260,7 @@

        - © Copyright 2023, The Regents of the University of California. + © Copyright 2024, The Regents of the University of California.

        diff --git a/docs/common/testbeds/lake_charles/damage_and_loss.html b/docs/common/testbeds/lake_charles/damage_and_loss.html index 353033fe..316f8024 100644 --- a/docs/common/testbeds/lake_charles/damage_and_loss.html +++ b/docs/common/testbeds/lake_charles/damage_and_loss.html @@ -40,6 +40,7 @@ + @@ -126,11 +127,6 @@
      2. 5. Requirements
      3. 6. Bugs & Feature Requests
    -

    Damage and Loss DB

    -

    Technical Manual

    • 1. Technical Manual
    • @@ -210,7 +206,7 @@
      -

      Damage and Loss Estimation

      +

      Damage and Loss Estimation

      Damage and loss functions from the HAZUS Hurricane Damage and Loss Model ([FEMA18a], [FEMA18b]) were implemented in PELICUN to support loss assessment for all configurations of buildings currently supported by HAZUS for wind and flood hazards.

      @@ -258,7 +254,7 @@

      - © Copyright 2023, The Regents of the University of California. + © Copyright 2024, The Regents of the University of California.

      diff --git a/docs/common/testbeds/lake_charles/example_outputs.html b/docs/common/testbeds/lake_charles/example_outputs.html index a3aae5ad..226bd47b 100644 --- a/docs/common/testbeds/lake_charles/example_outputs.html +++ b/docs/common/testbeds/lake_charles/example_outputs.html @@ -40,6 +40,7 @@ + @@ -126,11 +127,6 @@
    • 5. Requirements
    • 6. Bugs & Feature Requests
    -

    Damage and Loss DB

    -

    Technical Manual

    -

    Damage and Loss DB

    -

    Technical Manual

    • 1. Technical Manual
    • @@ -210,7 +206,7 @@
      -

      Feedback

      +

      Feedback

      If you have any feedback, data requests, or questions, please post on the SimCenter Regional Testbeds. When creating a New Topic it would be helpful if you could place an indication of your post in the Subject area:

        @@ -232,7 +228,7 @@

        - © Copyright 2023, The Regents of the University of California. + © Copyright 2024, The Regents of the University of California.

        diff --git a/docs/common/testbeds/lake_charles/future_refinements.html b/docs/common/testbeds/lake_charles/future_refinements.html index 9aba22f1..67f760dd 100644 --- a/docs/common/testbeds/lake_charles/future_refinements.html +++ b/docs/common/testbeds/lake_charles/future_refinements.html @@ -40,6 +40,7 @@ + @@ -126,11 +127,6 @@
      1. 5. Requirements
      2. 6. Bugs & Feature Requests
    -

    Damage and Loss DB

    -

    Technical Manual

    • 1. Technical Manual
    • @@ -210,7 +206,7 @@
      -

      Research Opportunities

      +

      Research Opportunities

      This testbed and its backing workflows should be viewed as a sandbox and scaffold, respectively, within which the community can explore different scenarios and develop new capabilities. The following list itemizes some areas where contribution from the @@ -286,7 +282,7 @@

      - © Copyright 2023, The Regents of the University of California. + © Copyright 2024, The Regents of the University of California.

      diff --git a/docs/common/testbeds/lake_charles/hazard_characterization.html b/docs/common/testbeds/lake_charles/hazard_characterization.html index 23ec1c78..db52fbf5 100644 --- a/docs/common/testbeds/lake_charles/hazard_characterization.html +++ b/docs/common/testbeds/lake_charles/hazard_characterization.html @@ -40,6 +40,7 @@ + @@ -127,11 +128,6 @@
    • 5. Requirements
    • 6. Bugs & Feature Requests
    -

    Damage and Loss DB

    -

    Technical Manual

    • 1. Technical Manual
    • @@ -211,7 +207,7 @@
      -

      Hazard Characterization

      +

      Hazard Characterization

      This testbed considers the wind hazard and its affect on the building inventory. The National Institute of Standards and Technology (NIST), working with Applied Research Associates, Inc. (ARA), has developed a rapid response estimate of the surface-level wind field for Hurricane Laura in @@ -264,7 +260,7 @@

      - © Copyright 2023, The Regents of the University of California. + © Copyright 2024, The Regents of the University of California.

      diff --git a/docs/common/testbeds/lake_charles/index.html b/docs/common/testbeds/lake_charles/index.html index 4c1feb9f..64692f13 100644 --- a/docs/common/testbeds/lake_charles/index.html +++ b/docs/common/testbeds/lake_charles/index.html @@ -40,6 +40,7 @@ + @@ -126,11 +127,6 @@
    • 5. Requirements
    • 6. Bugs & Feature Requests
    -

    Damage and Loss DB

    -

    Technical Manual

    • 1. Technical Manual
    • @@ -210,7 +206,7 @@
      -

      Lake Charles, LA

      +

      Lake Charles, LA

      Acknowledgements

      A number of members of the SimCenter Team assisted with this testbed’s development and its documentation: Barbaros Cetiner, Adam Zsarnoczay, Kuanshi Zhong, Chaofeng Wang, Sascha Hornauer, and Wael Elhaddad. @@ -274,7 +270,7 @@

      The software descriptions and results herein were generated by executing the R2D application using the versions of this application and associated SimCenter software as listed in software_version_LC and brails_version_LC. With the software versions listed, the testbed is currently estimated -to execute in 15 minutes using five Skylake (SKX) nodes (96 cores) on Stampede2.

      +to execute in 15 minutes using five Skylake (SKX) nodes (96 cores) on Frontera.

      @@ -393,7 +389,7 @@

      - © Copyright 2023, The Regents of the University of California. + © Copyright 2024, The Regents of the University of California.

      diff --git a/docs/common/testbeds/lake_charles/overview.html b/docs/common/testbeds/lake_charles/overview.html index 4b999733..2817cfe3 100644 --- a/docs/common/testbeds/lake_charles/overview.html +++ b/docs/common/testbeds/lake_charles/overview.html @@ -40,6 +40,7 @@ + @@ -127,11 +128,6 @@
    • 5. Requirements
    • 6. Bugs & Feature Requests
    • -

      Damage and Loss DB

      -

      Technical Manual

      -

      Damage and Loss DB

      -

      Technical Manual

      • 1. Technical Manual
      • @@ -210,7 +206,7 @@
        -

        Response Simulation

        +

        Response Simulation

        The initial implementation of the hurricane testbed is limited to consideration of wind damage and losses. More details are introduced in Damage and Loss Estimation.

        @@ -226,7 +222,7 @@

        - © Copyright 2023, The Regents of the University of California. + © Copyright 2024, The Regents of the University of California.

        diff --git a/docs/common/testbeds/lake_charles/sample_results.html b/docs/common/testbeds/lake_charles/sample_results.html index 1a6e9f74..07b13638 100644 --- a/docs/common/testbeds/lake_charles/sample_results.html +++ b/docs/common/testbeds/lake_charles/sample_results.html @@ -40,6 +40,7 @@ + @@ -126,11 +127,6 @@
      • 5. Requirements
      • 6. Bugs & Feature Requests
      -

      Damage and Loss DB

      -

      Technical Manual

      -

      Damage and Loss DB

      -

      Technical Manual

      -

      Damage and Loss DB

      -

      Technical Manual

      • 1. Technical Manual
      • @@ -211,7 +207,7 @@
        -

        Validation Results

        +

        Validation Results

        This section discusses damage and loss results from three comparative and validation studies with different emphases:

        1. The Influence of Year Built (Zillow vs. NSI and Parametric Study) first explores the implications of utilizing year built based on two data resources @@ -229,7 +225,7 @@ needed given uncertainties around the methodology used to generate the FEMA data.

        -

        Influence of Year Built (Zillow vs. NSI and Parametric Study)

        +

        Influence of Year Built (Zillow vs. NSI and Parametric Study)

        The year built is a critical attribute as it triggers attribute assignments by various rulesets. As discussed in Asset Description, different sources of data were used to predict the YearBuilt engaging both the National Structural Inventory (NSI) (with SURF correcting some @@ -260,7 +256,7 @@

        -

        Validation: StEER

        +

        Validation: StEER

        For Hurricane Laura, the Structural Extreme Reconnaissance (StEER) Network has released a dataset of the visual inspection and damage estimation for sample buildings in Lake Charles ([Roueche21], refereed as StEER buildings). There are 99 StEER buildings @@ -338,7 +334,7 @@

        -

        Validation: FEMA Historical Geospatial Damage Assessment

        +

        Validation: FEMA Historical Geospatial Damage Assessment

        FEMA and the Department of Interior lead the development of the Geospatial Platform, an internet-based service environment that provides a suite of well-manged geospatial data, services, applications, and tools. The @@ -944,7 +940,7 @@

        - © Copyright 2023, The Regents of the University of California. + © Copyright 2024, The Regents of the University of California.

        diff --git a/docs/common/testbeds/memphis/asset_description.html b/docs/common/testbeds/memphis/asset_description.html index 36f9ab6a..13f1c9a1 100644 --- a/docs/common/testbeds/memphis/asset_description.html +++ b/docs/common/testbeds/memphis/asset_description.html @@ -40,6 +40,7 @@ + @@ -126,11 +127,6 @@
      • 5. Requirements
      • 6. Bugs & Feature Requests
      -

      Damage and Loss DB

      -

      Technical Manual

      • 1. Technical Manual
      • @@ -210,7 +206,7 @@
        -

        Asset Description

        +

        Asset Description

        […]

        @@ -224,7 +220,7 @@

        - © Copyright 2023, The Regents of the University of California. + © Copyright 2024, The Regents of the University of California.

        diff --git a/docs/common/testbeds/memphis/asset_representation.html b/docs/common/testbeds/memphis/asset_representation.html index a7a184e9..e6d1966c 100644 --- a/docs/common/testbeds/memphis/asset_representation.html +++ b/docs/common/testbeds/memphis/asset_representation.html @@ -40,6 +40,7 @@ + @@ -126,11 +127,6 @@
      • 5. Requirements
      • 6. Bugs & Feature Requests
      -

      Damage and Loss DB

      -

      Technical Manual

      • 1. Technical Manual
      • @@ -210,7 +206,7 @@
        -

        Asset Representation

        +

        Asset Representation

        @@ -223,7 +219,7 @@

        - © Copyright 2023, The Regents of the University of California. + © Copyright 2024, The Regents of the University of California.

        diff --git a/docs/common/testbeds/memphis/damage_and_loss.html b/docs/common/testbeds/memphis/damage_and_loss.html index fd0e8aff..b618d40c 100644 --- a/docs/common/testbeds/memphis/damage_and_loss.html +++ b/docs/common/testbeds/memphis/damage_and_loss.html @@ -40,6 +40,7 @@ + @@ -126,11 +127,6 @@
      • 5. Requirements
      • 6. Bugs & Feature Requests
      -

      Damage and Loss DB

      -

      Technical Manual

      • 1. Technical Manual
      • @@ -210,7 +206,7 @@
        -

        Damage and Loss Estimation

        +

        Damage and Loss Estimation

        […]

        @@ -224,7 +220,7 @@

        - © Copyright 2023, The Regents of the University of California. + © Copyright 2024, The Regents of the University of California.

        diff --git a/docs/common/testbeds/memphis/future_refinements.html b/docs/common/testbeds/memphis/future_refinements.html index 2d48d326..802566f7 100644 --- a/docs/common/testbeds/memphis/future_refinements.html +++ b/docs/common/testbeds/memphis/future_refinements.html @@ -40,6 +40,7 @@ + @@ -126,11 +127,6 @@
      • 5. Requirements
      • 6. Bugs & Feature Requests
      -

      Damage and Loss DB

      -

      Technical Manual

      • 1. Technical Manual
      • @@ -210,7 +206,7 @@
        -

        Opportunity Areas for Future Refinements

        +

        Opportunity Areas for Future Refinements

        […]

        @@ -224,7 +220,7 @@

        - © Copyright 2023, The Regents of the University of California. + © Copyright 2024, The Regents of the University of California.

        diff --git a/docs/common/testbeds/memphis/hazard_characterization.html b/docs/common/testbeds/memphis/hazard_characterization.html index 473addba..5c6e3518 100644 --- a/docs/common/testbeds/memphis/hazard_characterization.html +++ b/docs/common/testbeds/memphis/hazard_characterization.html @@ -40,6 +40,7 @@ + @@ -126,11 +127,6 @@
      • 5. Requirements
      • 6. Bugs & Feature Requests
      -

      Damage and Loss DB

      -

      Technical Manual

      • 1. Technical Manual
      • @@ -210,7 +206,7 @@
        -

        Hazard Characterization

        +

        Hazard Characterization

        […]

        @@ -224,7 +220,7 @@

        - © Copyright 2023, The Regents of the University of California. + © Copyright 2024, The Regents of the University of California.

        diff --git a/docs/common/testbeds/memphis/index.html b/docs/common/testbeds/memphis/index.html index a6359f68..dcef681e 100644 --- a/docs/common/testbeds/memphis/index.html +++ b/docs/common/testbeds/memphis/index.html @@ -40,6 +40,7 @@ + @@ -126,11 +127,6 @@
      • 5. Requirements
      • 6. Bugs & Feature Requests
      -

      Damage and Loss DB

      -

      Technical Manual

      • 1. Technical Manual
      • @@ -210,7 +206,7 @@
        -

        Memphis, TN

        +

        Memphis, TN

        About text […]

          @@ -239,7 +235,7 @@

          - © Copyright 2023, The Regents of the University of California. + © Copyright 2024, The Regents of the University of California.

          diff --git a/docs/common/testbeds/memphis/network_performance.html b/docs/common/testbeds/memphis/network_performance.html index c840d0e4..a7adb7dc 100644 --- a/docs/common/testbeds/memphis/network_performance.html +++ b/docs/common/testbeds/memphis/network_performance.html @@ -40,6 +40,7 @@ + @@ -126,11 +127,6 @@
        • 5. Requirements
        • 6. Bugs & Feature Requests
        -

        Damage and Loss DB

        -

        Technical Manual

        • 1. Technical Manual
        • @@ -210,7 +206,7 @@
          -

          Network Performance Assessment

          +

          Network Performance Assessment

          @@ -223,7 +219,7 @@

          - © Copyright 2023, The Regents of the University of California. + © Copyright 2024, The Regents of the University of California.

          diff --git a/docs/common/testbeds/memphis/overview.html b/docs/common/testbeds/memphis/overview.html index e83d2f7e..433d44a3 100644 --- a/docs/common/testbeds/memphis/overview.html +++ b/docs/common/testbeds/memphis/overview.html @@ -40,6 +40,7 @@ + @@ -126,11 +127,6 @@
        • 5. Requirements
        • 6. Bugs & Feature Requests
        -

        Damage and Loss DB

        -

        Technical Manual

        • 1. Technical Manual
        • @@ -210,7 +206,7 @@
          -

          Overview

          +

          Overview

          […]

          @@ -224,7 +220,7 @@

          - © Copyright 2023, The Regents of the University of California. + © Copyright 2024, The Regents of the University of California.

          diff --git a/docs/common/testbeds/memphis/response_simulation.html b/docs/common/testbeds/memphis/response_simulation.html index d2664857..7f778a75 100644 --- a/docs/common/testbeds/memphis/response_simulation.html +++ b/docs/common/testbeds/memphis/response_simulation.html @@ -40,6 +40,7 @@ + @@ -126,11 +127,6 @@
        • 5. Requirements
        • 6. Bugs & Feature Requests
        -

        Damage and Loss DB

        -

        Technical Manual

        • 1. Technical Manual
        • @@ -210,7 +206,7 @@
          -

          Response Simulation

          +

          Response Simulation

          […]

          @@ -224,7 +220,7 @@

          - © Copyright 2023, The Regents of the University of California. + © Copyright 2024, The Regents of the University of California.

          diff --git a/docs/common/testbeds/memphis/sample_results.html b/docs/common/testbeds/memphis/sample_results.html index 134542ea..c6960cf7 100644 --- a/docs/common/testbeds/memphis/sample_results.html +++ b/docs/common/testbeds/memphis/sample_results.html @@ -40,6 +40,7 @@ + @@ -126,11 +127,6 @@
        • 5. Requirements
        • 6. Bugs & Feature Requests
        -

        Damage and Loss DB

        -

        Technical Manual

        • 1. Technical Manual
        • @@ -210,7 +206,7 @@
          -

          Sample Results

          +

          Sample Results

          […]

          @@ -224,7 +220,7 @@

          - © Copyright 2023, The Regents of the University of California. + © Copyright 2024, The Regents of the University of California.

          diff --git a/docs/common/testbeds/memphis/uncertainty_quantification.html b/docs/common/testbeds/memphis/uncertainty_quantification.html index 62129693..4631be8a 100644 --- a/docs/common/testbeds/memphis/uncertainty_quantification.html +++ b/docs/common/testbeds/memphis/uncertainty_quantification.html @@ -40,6 +40,7 @@ + @@ -126,11 +127,6 @@
        • 5. Requirements
        • 6. Bugs & Feature Requests
        -

        Damage and Loss DB

        -

        Technical Manual

        • 1. Technical Manual
        • @@ -210,7 +206,7 @@
          -

          Uncertainty Quantification

          +

          Uncertainty Quantification

          […]

          @@ -224,7 +220,7 @@

          - © Copyright 2023, The Regents of the University of California. + © Copyright 2024, The Regents of the University of California.

          diff --git a/docs/common/testbeds/sf_bay_area/asset_description.html b/docs/common/testbeds/sf_bay_area/asset_description.html index dd815fa9..e057687a 100644 --- a/docs/common/testbeds/sf_bay_area/asset_description.html +++ b/docs/common/testbeds/sf_bay_area/asset_description.html @@ -40,6 +40,7 @@ + @@ -126,11 +127,6 @@
        • 5. Requirements
        • 6. Bugs & Feature Requests
        -

        Damage and Loss DB

        -

        Technical Manual

        • 1. Technical Manual
        • @@ -210,7 +206,7 @@
          -

          Asset Description

          +

          Asset Description

          This study used a parcel-level inventory of buildings in the Bay Area that was developed by UrbanSim ([Waddell02]) using public resources such as the City and County of San Francisco’s @@ -394,7 +390,7 @@

          - © Copyright 2023, The Regents of the University of California. + © Copyright 2024, The Regents of the University of California.

          diff --git a/docs/common/testbeds/sf_bay_area/damage_and_loss.html b/docs/common/testbeds/sf_bay_area/damage_and_loss.html index aa679d7d..027253ef 100644 --- a/docs/common/testbeds/sf_bay_area/damage_and_loss.html +++ b/docs/common/testbeds/sf_bay_area/damage_and_loss.html @@ -40,6 +40,7 @@ + @@ -126,11 +127,6 @@
        • 5. Requirements
        • 6. Bugs & Feature Requests
        -

        Damage and Loss DB

        -

        Technical Manual

        • 1. Technical Manual
        • @@ -210,7 +206,7 @@
          -

          Damage and Loss Estimation

          +

          Damage and Loss Estimation

          The building performance assessment was performed on a story-level basis using PELICUN ([Zsarnóczay20]), where damage and losses are calculated with storylevel fragility functions based on the peak story drift and @@ -346,7 +342,7 @@

          - © Copyright 2023, The Regents of the University of California. + © Copyright 2024, The Regents of the University of California.

          diff --git a/docs/common/testbeds/sf_bay_area/example_outputs.html b/docs/common/testbeds/sf_bay_area/example_outputs.html index e87c8e20..4df6c3bd 100644 --- a/docs/common/testbeds/sf_bay_area/example_outputs.html +++ b/docs/common/testbeds/sf_bay_area/example_outputs.html @@ -40,6 +40,7 @@ + @@ -126,11 +127,6 @@
        • 5. Requirements
        • 6. Bugs & Feature Requests
        -

        Damage and Loss DB

        -

        Technical Manual

        -

        Damage and Loss DB

        -

        Technical Manual

        • 1. Technical Manual
        • @@ -210,7 +206,7 @@
          -

          Feedback and Data Request

          +

          Feedback and Data Request

          If you have any feedback, data requests, or questions, please post on the Message Board on SimCenter Forum. When creating a New Topic`it would be helpful if you could place an indication of your post in the `Subject area:

            @@ -229,7 +225,7 @@

            - © Copyright 2023, The Regents of the University of California. + © Copyright 2024, The Regents of the University of California.

            diff --git a/docs/common/testbeds/sf_bay_area/future_refinements.html b/docs/common/testbeds/sf_bay_area/future_refinements.html index 5e9e75ab..82e0a6ed 100644 --- a/docs/common/testbeds/sf_bay_area/future_refinements.html +++ b/docs/common/testbeds/sf_bay_area/future_refinements.html @@ -40,6 +40,7 @@ + @@ -126,11 +127,6 @@
          1. 5. Requirements
          2. 6. Bugs & Feature Requests
        -

        Damage and Loss DB

        -

        Technical Manual

        • 1. Technical Manual
        • @@ -210,7 +206,7 @@
          -

          Opportunity Areas for Future Refinements

          +

          Opportunity Areas for Future Refinements

          This testbed and its backing workflows should be viewed as a sandbox and scaffold, respectively, within which the community can explore different scenarios and develop new capabilities. The following list itemizes some areas where contribution from the @@ -251,7 +247,7 @@

          - © Copyright 2023, The Regents of the University of California. + © Copyright 2024, The Regents of the University of California.

          diff --git a/docs/common/testbeds/sf_bay_area/hazard_characterization.html b/docs/common/testbeds/sf_bay_area/hazard_characterization.html index f4529264..97e2d051 100644 --- a/docs/common/testbeds/sf_bay_area/hazard_characterization.html +++ b/docs/common/testbeds/sf_bay_area/hazard_characterization.html @@ -40,6 +40,7 @@ + @@ -126,11 +127,6 @@
        • 5. Requirements
        • 6. Bugs & Feature Requests
        -

        Damage and Loss DB

        -

        Technical Manual

        • 1. Technical Manual
        • @@ -210,7 +206,7 @@
          -

          Hazard Characterization

          +

          Hazard Characterization

          The ground motions for the Mw 7.0 Hayward earthquake were simulated by Rodgers et al. ([Rodgers19]) at the Lawrence Livermore National Lab (LLNL) using the SW4 finite difference code @@ -279,7 +275,7 @@

          - © Copyright 2023, The Regents of the University of California. + © Copyright 2024, The Regents of the University of California.

          diff --git a/docs/common/testbeds/sf_bay_area/index.html b/docs/common/testbeds/sf_bay_area/index.html index 793b096b..8af07d1f 100644 --- a/docs/common/testbeds/sf_bay_area/index.html +++ b/docs/common/testbeds/sf_bay_area/index.html @@ -40,6 +40,7 @@ + @@ -126,11 +127,6 @@
        • 5. Requirements
        • 6. Bugs & Feature Requests
        -

        Damage and Loss DB

        -

        Technical Manual

        • 1. Technical Manual
        • @@ -210,7 +206,7 @@
          -

          San Francisco, CA

          +

          San Francisco, CA

          Acknowledgements

          The SimCenter was financially supported by the National Science Foundation under Grant CMMI-1612843. Any opinions, findings, and conclusions or recommendations expressed in this material are those of the authors and do not necessarily reflect @@ -285,7 +281,7 @@

          - © Copyright 2023, The Regents of the University of California. + © Copyright 2024, The Regents of the University of California.

          diff --git a/docs/common/testbeds/sf_bay_area/overview.html b/docs/common/testbeds/sf_bay_area/overview.html index 9ebe174c..a984ac8b 100644 --- a/docs/common/testbeds/sf_bay_area/overview.html +++ b/docs/common/testbeds/sf_bay_area/overview.html @@ -40,6 +40,7 @@ + @@ -127,11 +128,6 @@
        • 5. Requirements
        • 6. Bugs & Feature Requests
        -

        Damage and Loss DB

        -

        Technical Manual

        -

        Damage and Loss DB

        -

        Technical Manual

        • 1. Technical Manual
        • @@ -210,7 +206,7 @@
          -

          Response Simulation

          +

          Response Simulation

          The non-linear response of buildings to ground shaking is simulated using OpenSees ([OpenSees20]) and an application, MDOF-LU, that generates an idealized structural analysis model @@ -276,7 +272,7 @@

          - © Copyright 2023, The Regents of the University of California. + © Copyright 2024, The Regents of the University of California.

          diff --git a/docs/common/testbeds/sf_bay_area/uncertainty_quantification.html b/docs/common/testbeds/sf_bay_area/uncertainty_quantification.html index 65356f1f..f919f006 100644 --- a/docs/common/testbeds/sf_bay_area/uncertainty_quantification.html +++ b/docs/common/testbeds/sf_bay_area/uncertainty_quantification.html @@ -40,6 +40,7 @@ + @@ -126,11 +127,6 @@
        • 5. Requirements
        • 6. Bugs & Feature Requests
        -

        Damage and Loss DB

        -

        Technical Manual

        -

        Damage and Loss DB

        -

        Technical Manual

        • 1. Technical Manual
        • @@ -212,36 +208,36 @@
          -

          1. About

          +

          1. About

          This open-source research application, which is available at EE-UQ Github page, is released under a 3-Clause BSD license (see Copyright and License). The EE-UQ app can be used to predict the response of a building subjected to earthquake events. The application is focused on quantifying the uncertainties in the predicted response, -given the that the properties of the buildings and the earthquake -events are not known exactly, and that both the simulation software -and the user make simplifying assumptions in the numerical modeling of +given that the properties of the buildings and the earthquake +events are not known exactly, and both the simulation software +and the user makes simplifying assumptions in the numerical modeling of that structure. In this application, the user is required to characterize the uncertainties in the input. The application will, -after utilizing the users selected sampling method, provide +after utilizing the user-selected sampling method, provide information that characterizes the uncertainties in the computed response measures. As the computations to make these determinations can be prohibitively expensive to perform on a user’s local computer, the user has the option to perform the computations remotely on the -Stampede2 supercomputer. Stampede2 is located at the Texas Advanced +Frontera supercomputer. Frontera is located at the Texas Advanced Computing Center (TACC) and made available to the user through NHERI DesignSafe, the cyberinfrastructure provider for the distributed NSF funded Natural Hazards in Engineering Research Infrastructure (NHERI) facility.

          Whether running locally or remotely, the computations are performed, as will be discussed in Technical Manual, in a workflow -application. That is, the numerical simulations are actually performed -by a number of different applications. The EE-UQ app backend software runs +application. That is, the numerical simulations are performed +by several different applications. The EE-UQ app backend software runs these different applications for the user, taking the outputs from some programs and providing them as inputs to others. The design of -the EE-UQ app is such that researchers are able to modify the -backend application to utilize their own application in the workflow +the EE-UQ app is such that researchers can modify the +backend application to utilize their application in the workflow computations. This will ensure researchers are not limited to using the default applications we provide and will be enthused to provide -their own applications for others to use.

          +their applications for others to use.

          This document covers Version 3.4 of the tool. Users are encouraged to comment on what additional features and capabilities they would like to see in this application. These requests and feedback can be submitted through the Message Board we greatly appreciate any input you have. If there are features you want, chances are many of your colleagues also would benefit from them. Users are encouraged to review Requirements to see what features are planned for this application.

          @@ -256,7 +252,7 @@

          - © Copyright 2023, The Regents of the University of California. + © Copyright 2024, The Regents of the University of California.

          diff --git a/docs/common/user_manual/about/HazardSimulation/about.html b/docs/common/user_manual/about/HazardSimulation/about.html index 4c149e52..d098ed8b 100644 --- a/docs/common/user_manual/about/HazardSimulation/about.html +++ b/docs/common/user_manual/about/HazardSimulation/about.html @@ -40,6 +40,7 @@ + @@ -126,11 +127,6 @@
        • 5. Requirements
        • 6. Bugs & Feature Requests
        -

        Damage and Loss DB

        -

        Technical Manual

        • 1. Technical Manual
        • @@ -210,7 +206,7 @@
          -

          About

          +

          About

          This is an open-source research application, EE-UQ Github page, released under a BSD clause 2 license, Copyright and License. The EE-UQ app can be used to simulate regional ground motion intensities given user-defined earthquake scenarios. Users can specify artificial earthquake sources (e.g., point sources) or select from faults in earthquake forecast models (e.g., UCERF3). Users can also specify the site soil velocities in addition to using the default database in |opensha link|. EE-UQ app provides different options for ground motion prediction equations and correlation models to compute spatially correlated intensity measures at user-defined site locations. Users can use EE-UQ app to generate multiple realizations to represent the uncertainty from earthquake sources and soil properties. If the user provide valid account information on |peer nga link|, EE-UQ app will download and parse ground motion accelerograms for running time history analyses.

          This is Version 3.4 of the tool. Users are encouraged to comment on what additional features and capabilities they would like to see in this application. These requests and feedback can be submitted through an anonymous user survey. We greatly appreciate any input you have. If there are features you want, chances are many of your colleagues also would benefit from them. Users are encouraged to review the lbl-requirements to see what features are planned for this application.

          @@ -225,7 +221,7 @@

          - © Copyright 2023, The Regents of the University of California. + © Copyright 2024, The Regents of the University of California.

          diff --git a/docs/common/user_manual/bugs.html b/docs/common/user_manual/bugs.html index efdd4b5f..993a2065 100644 --- a/docs/common/user_manual/bugs.html +++ b/docs/common/user_manual/bugs.html @@ -40,6 +40,7 @@ + @@ -49,7 +50,7 @@ - + @@ -128,11 +129,6 @@
        • 5. Requirements
        • 6. Bugs & Feature Requests
        -

        Damage and Loss DB

        -

        Technical Manual

        • 1. Technical Manual
        • @@ -212,7 +208,7 @@
          -

          6. Bugs & Feature Requests

          +

          6. Bugs & Feature Requests

          If you find bugs, have feature requests, or questions about how to install or use the application, please post on the Message Board. To avoid duplication, try the Search feature before creating a New Topic. When creating a New Topic to report a bug or new feature request it would be helpful if you could place in the Subject area, as shown in Fig. 6.1, an indication of what the post is about:

          @@ -237,7 +233,7 @@

          - © Copyright 2023, The Regents of the University of California. + © Copyright 2024, The Regents of the University of California.

          diff --git a/docs/common/user_manual/examples/desktop/eeuq-0001/README.html b/docs/common/user_manual/examples/desktop/eeuq-0001/README.html index 476cdbed..8b2fffaf 100644 --- a/docs/common/user_manual/examples/desktop/eeuq-0001/README.html +++ b/docs/common/user_manual/examples/desktop/eeuq-0001/README.html @@ -40,6 +40,7 @@ + @@ -148,11 +149,6 @@
        • 5. Requirements
        • 6. Bugs & Feature Requests
        -

        Damage and Loss DB

        -

        Technical Manual

        • 1. Technical Manual
        • @@ -234,7 +230,7 @@
          -

          3.1. Shear Building: Sampling, Reliability and Sensitivity

          +

          3.1. Shear Building: Sampling, Reliability and Sensitivity

          Consider the problem of uncertainty quantification in a three-story shear building

          ../../../../../_images/model.png @@ -313,7 +309,7 @@

          Do not place the file in your root, downloads, or desktop folder as when the application runs it will copy the contents on the directories and subdirectories containing this file multiple times (a copy will be made for each sample specified). If you are like us, your root, Downloads or Documents folders contain and awful lot of files and when the backend workflow runs you will slowly find you will run out of disk space!

          -

          3.1.1. Sampling Analysis with El Centro

          +

          3.1.1. Sampling Analysis with El Centro

          We will first demonstrate the steps to perform a sampling analysis to study the effects of the roof response of models of the building subjected to the El Centro ground motion. We will scale the input motion using a scale factor (which we name factorEC) following a uniform distribution between 1.2 and 1.8, i.e. mean \(\mu_{factorEC} = 1.5\) and a standard deviation of \(\sigma_{factorEC} = 0.1732\), (COV = 12%).

          To perform a Sampling or Forward propagation uncertainty analysis the user would perform the following steps:

            @@ -386,7 +382,7 @@

            3.1.1. Sampling Analysis with El Centro<

          -

          3.1.2. Sampling Analysis with ElCentro and Reduced Output

          +

          3.1.2. Sampling Analysis with ElCentro and Reduced Output

          In the previous example we got the standard output, which can be both a lot and also limited (in the sense you don’t get the information you want). In this example we will present how to obtain results just for the roof displacement, the displacement of node 4 in both the MDOF and OpenSees model generator examples. The examples could be extended to output for example the story shear forces, element forces, element end rotations, …

          For this example you will need two additional file recorderCommands.tcl and postprocess.tcl.

          The recorderCommands.tcl script as shown below will record the envelope displacements in the first two degrees of freedom for nodes 1 through 4.

          @@ -410,7 +406,7 @@

          3.1.2. Sampling Analysis with ElCentro a

          -

          3.1.3. Global Sensitivity

          +

          3.1.3. Global Sensitivity

          In a global sensitivity analysis, the user wishes to understand what is the influence of the individual random variables on the quantities of interest. This is typically done before the user launches large-scale forward uncertainty problems in order to limit the number of random variables used so as to limit the number of simulations performed.

          To perform a reliability analysis the steps above would be repeated with the exception that the user would select a reliability analysis method instead of a Forward Propagation method. To obtain reliability results using the global reliability method for this problem the user would follow the same sequence of steps as previously. The difference would be in the UQ panel in which the user would select a Reliability as the Dakota Method Category and then choose GLobal reliability. In the figure, the user is specifying that they are interested in the probability that the displacement will exceed certain response levels.

          @@ -423,7 +419,7 @@

          3.1.3. Global Sensitivity -

          3.1.4. Reliability Analysis

          +

          3.1.4. Reliability Analysis

          If the user is interested in the probability that certain response measures will be exceeded an alternative strategy is to perform a reliability analysis. To perform a reliability analysis the steps above would be repeated with the exception that the user would select a reliability analysis method instead of a Forward Propagation method. To obtain reliability results using the Global Reliability method presented in Dakota choose the Global Reliability methods from the methods drop-down menu. In the response levels enter a value of 2.5, specifying that we are interested in the value of the CDF for a displacement of the roof of 2.5in, i.e. what is the probability that displacement will be less than 2.5in.

          diff --git a/docs/common/user_manual/examples/desktop/eeuq-0002/README.html b/docs/common/user_manual/examples/desktop/eeuq-0002/README.html index bca3d2e1..b6b1eb36 100644 --- a/docs/common/user_manual/examples/desktop/eeuq-0002/README.html +++ b/docs/common/user_manual/examples/desktop/eeuq-0002/README.html @@ -40,6 +40,7 @@ + @@ -151,11 +152,6 @@
        • 5. Requirements
        • 6. Bugs & Feature Requests
        -

        Damage and Loss DB

        -

        Technical Manual

        • 1. Technical Manual
        • @@ -237,11 +233,11 @@
          -

          3.2. Including Spatial Variability in Site Response Event

          +

          3.2. Including Spatial Variability in Site Response Event

          This page shows two examples of how to incorporate spatial variability into UQ analysis by using various special materials, namely ElasticIsotropic, PM4Sand, and PDMY03, in the Site Response option under the EVENT tab.

          -

          3.2.1. Problem Statement

          +

          3.2.1. Problem Statement

          Site response analysis is commonly performed to analyze the propagation of seismic waves through soil. As shown in Fig. 3.2.1.1, one-dimensional response analyses, as a simplified method, assume that all boundaries are horizontal and that the response of a soil deposit is predominately caused by SH-waves propagating vertically from the underlying bedrock. Ground surface response is usually the major output from @@ -251,7 +247,7 @@

          3.2.1. Problem Statement.

          +These components are illustrated in Fig. 2.4.5.9.1.

          ../../../../../_images/siteResponse1.png

          Fig. 3.2.1.1 Simplified 1D site response analysis (courtesy of Pedro Arduino)

          @@ -277,7 +273,7 @@

          3.2.1. Problem Statement -

          3.2.2. General Workflow for Global Sensitivity Analysis

          +

          3.2.2. General Workflow for Global Sensitivity Analysis

          In a global sensitivity analysis, the user wishes to understand what is the influence of the individual random variables on the quantities of interest. This is typically done before the user launches large-scale forward uncertainty problems in order to limit the number of random variables used so as to limit the number of simulations performed.

          root mean square (RMS) accelerations in 1 and 2 directions, Peak BAse shear and moments in 1 and 2 directions.

          @@ -338,9 +334,9 @@

          3.2.2. General Workflow for Global Sensi

          -

          3.2.3. Adding Spatial Variability

          +

          3.2.3. Adding Spatial Variability

          -

          3.2.3.1. Case 1: using ElasticIsotropic material

          +

          3.2.3.1. Case 1: using ElasticIsotropic material

          For the Elastic_Random material, shear wave velocity (Vs) can be selected to be randomized. Then select the Mean and COV (coefficient of variation \(=\frac{\sigma}{\mu}\)) for shear wave velocity. Correlation length defines how shear wave velocities are vertically correlated. Subsequently, Young’s modulus is calculated based on the stochastic shear velocity profile at the center of each element. No special calibration is required.

          @@ -365,7 +361,7 @@

          3.2.3.1. Case 1: using ElasticIsotropic

          -

          3.2.3.2. Case 2: using PM4Sand material

          +

          3.2.3.2. Case 2: using PM4Sand material

          For the PM4Sand_Random material, relative density (Dr) can be selected to be randomized. Then select the Mean and COV (coefficient of variation \(COV=\frac{\sigma}{\mu}\)) for shear wave velocity. Correlation length defines how shear wave velocities are vertically correlated. In the current calibration procedure, all the other parameters are kept as input except for the contraction rate parameter hpo, which is calibrated based on the empirical triggering model proposed by Idriss and Boulanger 2008.

          @@ -403,7 +399,7 @@

          3.2.3.2. Case 2: using PM4Sand material<

          - © Copyright 2023, The Regents of the University of California. + © Copyright 2024, The Regents of the University of California.

          diff --git a/docs/common/user_manual/examples/desktop/eeuq-0003/README.html b/docs/common/user_manual/examples/desktop/eeuq-0003/README.html index c7c6c0e2..d3bfa9f5 100644 --- a/docs/common/user_manual/examples/desktop/eeuq-0003/README.html +++ b/docs/common/user_manual/examples/desktop/eeuq-0003/README.html @@ -40,6 +40,7 @@ + @@ -147,11 +148,6 @@
        • 5. Requirements
        • 6. Bugs & Feature Requests
        -

        Damage and Loss DB

        -

        Technical Manual

        • 1. Technical Manual
        • @@ -233,7 +229,7 @@
          -

          3.3. Ground Motion Selection and Nonlinear Response Analysis

          +

          3.3. Ground Motion Selection and Nonlinear Response Analysis

          Shown in Fig. 3.3.1 is an OpenSees model sketch of a 2D steel moment frame building. The building has a four-bay lateral frame with gravity system which is modeled by the leaning column in the model. The bottom two stories @@ -248,7 +244,7 @@

          This example shows how to select ground motion records and run nonlinear time history analysis for the OpenSees/tcl model of interest.

          -

          3.3.1. Load OpenSees/tcl model and analysis script

          +

          3.3.1. Load OpenSees/tcl model and analysis script

          1. Navigate to the SIM tab in the left menu. In is panel, select the OpenSees as the Building Model Generator. Use the Choose button to select the @@ -269,7 +265,7 @@

            3.3.1. Load OpenSees/tcl model and analy

          -

          3.3.2. Select and scale ground motion records

          +

          3.3.2. Select and scale ground motion records

          1. Navigate to the EVT panel and select the PEER NGA Records as the Load Generator. We can use the Design Spectrum (ASCE 7-10) as an example target spectrum here. First, please specify the \(S_{DS}\), @@ -296,7 +292,7 @@

            3.3.2. Select and scale ground motion re

          -

          3.3.3. Run the analysis and postprocess results

          +

          3.3.3. Run the analysis and postprocess results

          1. Navigate to the UQ panel, use the default Forward Propagation method with the # Sample same as the number of selected records.

          2. @@ -333,7 +329,7 @@

            3.3.3. Run the analysis and postprocess

            - © Copyright 2023, The Regents of the University of California. + © Copyright 2024, The Regents of the University of California.

            diff --git a/docs/common/user_manual/examples/desktop/eeuq-0004/README.html b/docs/common/user_manual/examples/desktop/eeuq-0004/README.html index 23385f79..5693877f 100644 --- a/docs/common/user_manual/examples/desktop/eeuq-0004/README.html +++ b/docs/common/user_manual/examples/desktop/eeuq-0004/README.html @@ -40,6 +40,7 @@ + @@ -147,11 +148,6 @@
          3. 5. Requirements
          4. 6. Bugs & Feature Requests
        -

        Damage and Loss DB

        -

        Technical Manual

        • 1. Technical Manual
        • @@ -233,11 +229,11 @@
          -

          3.4. AutoSDA and Nonlinear Response Analysis

          +

          3.4. AutoSDA and Nonlinear Response Analysis

          This example demonstrates the use of a Python-based computation platform to automate seismic design and analysis of of steel moment resisting frames (AutoSDA) ([GBS20]).

          -

          3.4.1. Design and create a numerical model

          +

          3.4.1. Design and create a numerical model

          1. Navigate to the SIM tab in the left menu. In this panel, select the Steel Building Model as the Building Model Generator. In the user interface, five major input sections: (1) @@ -289,7 +285,7 @@

            3.4.1. Design and create a numerical mod

          -

          3.4.2. Select and scale ground motion records

          +

          3.4.2. Select and scale ground motion records

          1. Navigate to the EVT panel and select the PEER NGA Records as the Load Generator. We can use the Uniform Hazard Spectrum as an example target spectrum here. We can specify the site location, the @@ -316,7 +312,7 @@

            3.4.2. Select and scale ground motion re

          -

          3.4.3. Run the analysis and post-process results

          +

          3.4.3. Run the analysis and post-process results

          1. Navigate to the UQ panel, use the default Forward Propagation method with the # Sample same as the number of selected records.

          2. @@ -350,7 +346,7 @@

            3.4.3. Run the analysis and post-process

            - © Copyright 2023, The Regents of the University of California. + © Copyright 2024, The Regents of the University of California.

            diff --git a/docs/common/user_manual/examples/desktop/eeuq-0005/README.html b/docs/common/user_manual/examples/desktop/eeuq-0005/README.html index 5132d021..8e9cc357 100644 --- a/docs/common/user_manual/examples/desktop/eeuq-0005/README.html +++ b/docs/common/user_manual/examples/desktop/eeuq-0005/README.html @@ -40,6 +40,7 @@ + @@ -146,11 +147,6 @@
          3. 5. Requirements
          4. 6. Bugs & Feature Requests
        -

        Damage and Loss DB

        -

        Technical Manual

        -

        Damage and Loss DB

        -

        Technical Manual

        • 1. Technical Manual
        • @@ -232,7 +228,7 @@
          -

          3.6. Surrogate Model for Structural Response Prediction (Probabilistic Learning on Manifolds)

          +

          3.6. Surrogate Model for Structural Response Prediction (Probabilistic Learning on Manifolds)

          One essential step in seismic structural performance assessment is evaluating structural responses under earthquake ground motion inputs. The typical workflow is demonstrated in Example 4.3. The trade-off between computational efficiency and accuracy is one of the major challenges in problems that @@ -243,7 +239,7 @@

          3.6. Surrogate Model for Structural Resp

          This example demonstrates using a novel method, Probabilistic Learning on Manifolds (PLoM) [Soize2016], to develop surrogate models for structural responses under earthquake ground motion inputs.

          -

          3.6.1. Configure UQ Engine

          +

          3.6.1. Configure UQ Engine

          1. Navigate to the UQ tab in the left menu. In this panel, select the SimCenterUQ as the UQ Engine. In the SimCenterUQ Method Category, select the PLoM Model method. There are @@ -267,7 +263,7 @@

            3.6.1. Configure UQ Engine -

            3.6.2. Configure Structural Analysis

            +

            3.6.2. Configure Structural Analysis

            1. Navigate to the SIM tab and select the MDOF as the Building Model Generator. In this example we use a simple nonlinear SDOF model (yield displacement is 0.01 inch and hardening ratio is 0.1).

            2. @@ -304,7 +300,7 @@

              3.6.2. Configure Structural Analysis

          -

          3.6.3. Run the analysis and post-process results

          +

          3.6.3. Run the analysis and post-process results

          1. Next click on the Run button. This will call the backend application to launch the analysis. When done the RES panel will first arrive at the Summary panel. Two plots are created to summarize the PLoM training @@ -359,7 +355,7 @@

            3.6.3. Run the analysis and post-process

            - © Copyright 2023, The Regents of the University of California. + © Copyright 2024, The Regents of the University of California.

            diff --git a/docs/common/user_manual/examples/desktop/eeuq-0007/README.html b/docs/common/user_manual/examples/desktop/eeuq-0007/README.html index 63f80e55..443c5915 100644 --- a/docs/common/user_manual/examples/desktop/eeuq-0007/README.html +++ b/docs/common/user_manual/examples/desktop/eeuq-0007/README.html @@ -40,6 +40,7 @@ + @@ -146,11 +147,6 @@
          2. 5. Requirements
          3. 6. Bugs & Feature Requests

        -

        Damage and Loss DB

        -

        Technical Manual

        • 1. Technical Manual
        • @@ -232,12 +228,12 @@
          -

          3.7. Target Spectrum by Surrogate Hazard GP Model

          +

          3.7. Target Spectrum by Surrogate Hazard GP Model

          In some cases, users may want to specify the target response spectrum in ground motion selection using a pre-trained surrogate hazard model. This example demonstrates using quoFEM-trained Gaussian Process hazard model to get a target response spectrum at a specific site location in San Francisco Bay Area given the seismicity from the Hayward Fault.

          -

          3.7.1. Pre-trained Gaussian Process Surrogate Model

          +

          3.7.1. Pre-trained Gaussian Process Surrogate Model

          1. In this example, the Gaussian Process (GP) model is trained on regional earthquake intensity measure maps that are generated for 147 possible Hayward earthquake scenarios in UCERF-2 model. For each scenario, the response spectral accelerations at periods @@ -263,7 +259,7 @@

            3.7.1. Pre-trained Gaussian Process Surr

          -

          3.7.2. Configure Surrogate Target Spectrum

          +

          3.7.2. Configure Surrogate Target Spectrum

          1. Navigate to the EVT tab and select the PEER NGA Records as the Load Generator. In this example we use the Spectrum from Hazard Surrogate as the Target Spectrum (specified in the dropdown list).

          2. @@ -290,7 +286,7 @@

            3.7.2. Configure Surrogate Target Spectr

          -

          3.7.3. Select Ground Motion and Run Analysis

          +

          3.7.3. Select Ground Motion and Run Analysis

          1. Once the target response spectrum is available, users can follow the same procedure as introduced in EE-UQ Example 3 to @@ -335,7 +331,7 @@

            3.7.3. Select Ground Motion and Run Anal

            - © Copyright 2023, The Regents of the University of California. + © Copyright 2024, The Regents of the University of California.

            diff --git a/docs/common/user_manual/examples/desktop/eeuq-0008/README.html b/docs/common/user_manual/examples/desktop/eeuq-0008/README.html index 05d47fc5..ddff759c 100644 --- a/docs/common/user_manual/examples/desktop/eeuq-0008/README.html +++ b/docs/common/user_manual/examples/desktop/eeuq-0008/README.html @@ -40,6 +40,7 @@ + @@ -146,11 +147,6 @@
          2. 5. Requirements
          3. 6. Bugs & Feature Requests
        -

        Damage and Loss DB

        -

        Technical Manual

        • 1. Technical Manual
        • @@ -232,11 +228,11 @@
          -

          3.8. Using Multiple Models and Analysis Options in EE-UQ

          +

          3.8. Using Multiple Models and Analysis Options in EE-UQ

          This example showcases the use of multiple structural models and finite element analysis options to predict structural responses to earthquake ground motion inputs.

          Non-linear time history analysis is conducted using OpenSees, employing a simple model of a 5-story structure, subjected to recorded ground acceleration time history during an earthquake. The response of the model is used to extract commonly used engineering demand parameters while considering uncertainties in the value of story stiffnesses and model formulation. By including or excluding the uncertainty in the story stiffness and using modal or Rayleigh damping, four possible models are obtained, with each model having an equal chance of being randomly picked to predict the response of the structure. The resulting distribution of the engineering demand parameters is that obtained by propagating model form uncertainty as well as uncertainty about the value of a parameter of the model.

          -

          3.8.1. Configure UQ Engine

          +

          3.8.1. Configure UQ Engine

          1. Navigate to the UQ tab in the left menu. In this panel, select Forward Propagation as the UQ Method and Dakota as the UQ Engine. LHS is used as the sampling method. Enter the values needed for the LHS method, as shown in the figure below:

          2. @@ -246,7 +242,7 @@

            3.8.1. Configure UQ Engine -

            3.8.2. Configure Structural Analysis

            +

            3.8.2. Configure Structural Analysis

            1. Navigate to the SIM tab and select the Multi Model option for the Building Model Generator. We will use two simulation models for the 5 story structure in this example. Use the Add or Remove button as appropriate to create two tabs, corresponding to the two models that we will define next. In each of the tabs, choose MDOF as the Building Model Generator. The difference between the two models in this example is that in one of them, we consider the story stiffness in the X and Y directions as being uncertain.

            @@ -281,7 +277,7 @@

            3.8.2. Configure Structural Analysis

          -

          3.8.3. Run the analysis and observe the results

          +

          3.8.3. Run the analysis and observe the results

          1. Next, click on the Run button. This will call the backend application to launch the analysis. When the analysis is finished, the RES panel will be displayed, which shows summary statistics of the output quantities in the Summary tab.

          2. @@ -310,7 +306,7 @@

            3.8.3. Run the analysis and observe the

            - © Copyright 2023, The Regents of the University of California. + © Copyright 2024, The Regents of the University of California.

            diff --git a/docs/common/user_manual/examples/desktop/eeuq-0009/README.html b/docs/common/user_manual/examples/desktop/eeuq-0009/README.html index 6713a637..cea8713a 100644 --- a/docs/common/user_manual/examples/desktop/eeuq-0009/README.html +++ b/docs/common/user_manual/examples/desktop/eeuq-0009/README.html @@ -40,6 +40,7 @@ + @@ -149,11 +150,6 @@
          3. 5. Requirements
          4. 6. Bugs & Feature Requests
        -

        Damage and Loss DB

        -

        Technical Manual

        • 1. Technical Manual
        • @@ -235,14 +231,14 @@
          -

          3.9. Training a Surrogate Model (Gaussian Process)

          +

          3.9. Training a Surrogate Model (Gaussian Process)

          Warning

          To reproduce the result of this example, the user should first click EVT and Select Records, and then click the RUN button. See the below procedure for details.

          -

          3.9.1. Training Gaussian Process Surrogate Model

          -

          This example shows how to train a surrogate model that can be imported into EE-UQ and replace structural dynamic simulations. The training of a surrogate model requires some number of structural dynamic simulations for representative scenarios [i.e. training set]. In this example, these simulations are performed using recorded ground motions selected from the PEER NGA database. The ground motions are selected such that it covers a wide domain of intensity measure (IM) space, as uniform as possible. Three IMs are considered in the example: pseudo-spectral acceleration at period 0.5 sec (PSA), 5-75% duration (D5-75), and SaRatio following the work in [Zhong2023]. We additionally consider the stiffness of the target structure (3 story building) as input for the surrogate model.

          +

          3.9.1. Training Gaussian Process Surrogate Model

          +

          This example shows how to train a surrogate model that can be imported into EE-UQ and replace structural dynamic simulations. The training of a surrogate model requires some number of structural dynamic simulations for representative scenarios [i.e. training set]. In this example, these simulations are performed using recorded ground motions selected from the PEER NGA database. The ground motions are selected such that it covers a wide domain of intensity measure (IM) space, as uniform as possible. Three IMs are considered in the example: pseudo-spectral acceleration at period 0.5 sec (PSA), 5-75% duration (D5-75), and SaRatio following the work in [Zhong2023]. We additionally consider the stiffness of the target structure (3 story building) as input for the surrogate model.

          ../../../../../_images/EE09_main2.png @@ -256,7 +252,7 @@

          3.9.1. Training Gaussian Process Surroga

          -

          3.9.2. Set Up GP Surrogate Modeling Options

          +

          3.9.2. Set Up GP Surrogate Modeling Options

          1. In the UQ tab select the Surrogate Modeling as UQ Method. Then, select the Train GP Surrogate Model.

            @@ -281,7 +277,7 @@

            3.9.2. Set Up GP Surrogate Modeling Opti

            More information can be found in the User Guide.

          -

          3.9.3. Define Target Structure

          +

          3.9.3. Define Target Structure

          1. In GI tab, set the number of stories, 3.

            @@ -302,7 +298,7 @@

            3.9.3. Define Target Structure -

            3.9.4. Select Ground Motions for the Training

            +

            3.9.4. Select Ground Motions for the Training

            1. In EVT tab, the option to retrieve ground motions from PEER NGA records is selected. To allow the surrogate models to cover a wide variety of ground motions (represented as “wide IM domain”), let us select No Spectrum - Uniform IMs for the analysis. Set the Number of samples per bin 1, and add three intensity measures that are specified in the UQ tab as the input of surrogate, i.e. “5-75% Significant Duration”, “Pseudo Spectral Acceleration (with a natural period of 0.5 sec)”, and “SaRatio (at 1.0 sec in range of 0.1-1.5 sec). Set the coverage ranges respectively to [2.5, 30], [0.1, 2.0], and [0.25, 1.2]. For the former two IMs, the number of bins is set as 5, and the SaRatio will have 4 bins. Therefore, the total number of bins (i.e. grid points in 3-dimensional space) is 100.

              @@ -362,7 +358,7 @@

              3.9.4. Select Ground Motions for the Tra

          -

          3.9.5. Set Up Training Domain

          +

          3.9.5. Set Up Training Domain

          1. In RV tab set the range of stiffness to be [50, 150] as shown in the below image. This is equivalent to the range of stiffness of which the response can be predicted using the surrogate. The selected IMs (Sa, D5-75, and SaRatio) in each two horizontal directions will be additional inputs of the surrogate model. Therefore, the total dimension of the surrogate model input is 7.

            @@ -375,7 +371,7 @@

            3.9.5. Set Up Training Domain -

            3.9.6. Run the Analysis and Process Results

            +

            3.9.6. Run the Analysis and Process Results

            1. Click Run button. The analysis may take several minutes to run. The RES tab will be highlighted when the analysis is completed.

              The EDP name consists of the quantity of interest, story number, and the direction of interest - for example:

              @@ -458,7 +454,7 @@

              3.9.6. Run the Analysis and Process Resu

              - © Copyright 2023, The Regents of the University of California. + © Copyright 2024, The Regents of the University of California.

              diff --git a/docs/common/user_manual/examples/desktop/eeuq-0010/README.html b/docs/common/user_manual/examples/desktop/eeuq-0010/README.html index 0bf673f0..bf79041f 100644 --- a/docs/common/user_manual/examples/desktop/eeuq-0010/README.html +++ b/docs/common/user_manual/examples/desktop/eeuq-0010/README.html @@ -40,6 +40,7 @@ + @@ -148,11 +149,6 @@
            2. 5. Requirements
            3. 6. Bugs & Feature Requests
        -

        Damage and Loss DB

        -

        Technical Manual

        • 1. Technical Manual
        • @@ -234,7 +230,7 @@
          -

          3.10. Structural Response Prediction Using a Surrogate Model (Gaussian Process)

          +

          3.10. Structural Response Prediction Using a Surrogate Model (Gaussian Process)

          Warning

          To reproduce the result of this example, the user should first click EVT and Select Records, and then click the RUN button. See the below procedure for details.

          @@ -251,7 +247,7 @@

          This examples uses the surrogate model trained in example 09

          -

          3.10.1. Set Up Forward Propagation Configuration

          +

          3.10.1. Set Up Forward Propagation Configuration

          1. In UQ tab select the Forward modeling as UQ Method. Select Dakota engine.

            @@ -265,7 +261,7 @@

            3.10.1. Set Up Forward Propagation Confi

          -

          3.10.2. Define Target Structure

          +

          3.10.2. Define Target Structure

          1. The GI tab is kept as default. (GI tab is not used when a surrogate model is used in SIM tab)

          2. In SIM tab, the surrogate model (.json) trained in Example 09 is imported as shown in the figure.

            @@ -284,7 +280,7 @@

            3.10.2. Define Target Structure

          -

          3.10.3. Select Ground Motions

          +

          3.10.3. Select Ground Motions

          1. In EVT tab, PEER NGA ground motion records option is selected. Let us consider the site of interest located at (37.8715, -122.273), of which we would like to select ground motions that follow USGS Uniform Hazard Spectrum (2014 v4.2.0) with return period 2475. Vs30 is assumed 760 m/s. Let us select 30 ground motion time histories that match this spectrum by clicking Select records button. The target response spectrum curve and the selected ground motions will be displayed on the right-hand side panel as shown below.

            @@ -335,7 +331,7 @@

            3.10.3. Select Ground Motions -

            3.10.4. Distribution of Random Variables

            +

            3.10.4. Distribution of Random Variables

            1. The RV tab is pre-populated with the random variables that were used to train the surrogate. Change the distribution of the statistical parameters as desired. In this example, the stiffness is assumed to be distributed around 120 with a standard deviation of 5.

              @@ -352,7 +348,7 @@

              3.10.4. Distribution of Random Variables

          -

          3.10.5. Run the Analysis and Process Results

          +

          3.10.5. Run the Analysis and Process Results

          1. Click Run button. The analysis may take several minutes. The RES tab will be highlighted when the analysis is completed

          2. The obtained statistics of responses are shown in the “Summary tab”

            @@ -428,7 +424,7 @@

            3.10.5. Run the Analysis and Process Res

            - © Copyright 2023, The Regents of the University of California. + © Copyright 2024, The Regents of the University of California.

            diff --git a/docs/common/user_manual/examples/desktop/eeuq-0011/README.html b/docs/common/user_manual/examples/desktop/eeuq-0011/README.html index e5e3de93..824a7859 100644 --- a/docs/common/user_manual/examples/desktop/eeuq-0011/README.html +++ b/docs/common/user_manual/examples/desktop/eeuq-0011/README.html @@ -40,6 +40,7 @@ + @@ -148,11 +149,6 @@
          3. 5. Requirements
          4. 6. Bugs & Feature Requests
        -

        Damage and Loss DB

        -

        Technical Manual

        • 1. Technical Manual
        • @@ -234,7 +230,7 @@
          -

          3.11. Multi-fidelity Monte Carlo Simulation

          +

          3.11. Multi-fidelity Monte Carlo Simulation

          This example demonstrates Multi-fidelity Monte Carlo (MFMC) supported in EE-UQ. The high- and low-fidelity building models of a benchmark 9-story steel structure ([Ohtori2004]) are used for the demonstration, following the implementation in ([Patsialis2023]).

          @@ -251,7 +247,7 @@
          -

          3.11.1. Target structure

          +

          3.11.1. Target structure

          The target structure is a nine-story moment-resisting five-bay frame with a total height of 37.19 m and a length of 45.73 m.

          The High-Fidelity model (main script: benchmark_9st_model.tcl) is a nonlinear finite element model developed in OpenSees. Material characteristics are modulus of elasticity E=1.99 105 MPa for both beams and columns, yield stress for the columns 345 MPa and 248 MPa for the beams using values proposed in [Ohtori2004]. For modeling material inelastic behavior, the Giufre’-Menegotto-Pinto model with isotropic strain hardening is chosen for the steel fibers. The fundamental period is 2.274 sec, and under the Rayleigh damping assumption, the damping ratio is selected as 2% for the 1st and 3rd modes.

          @@ -267,7 +263,7 @@

          3.11.1. Target structure -

          3.11.2. Procedure

          +

          3.11.2. Procedure

          1. In UQ tab select the Forward Propagation as UQ Method. Select SimCenterUQ engine. Select Multi-fidelity Monte Carlo method.

            @@ -347,7 +343,7 @@

            3.11.2. Procedure

          -

          3.11.3. Run the Analysis

          +

          3.11.3. Run the Analysis

          1. Click Run button. The analysis may take several minutes. The RES tab will be highlighted when the analysis is completed

            The EDP name consists of the quantity of interest, story number, and the direction of interest - for example:

            @@ -387,7 +383,7 @@

            3.11.3. Run the Analysis -

            3.11.4. Comparison to High-fidelity-only and low-fidelity-only simulations

            +

            3.11.4. Comparison to High-fidelity-only and low-fidelity-only simulations

            Only for validation purposes, high-fidelity simulations are performed 1000 times and the resulting statistics (reference) are compared with the above multifidelity (MF) estimates. Recall that the estimation was based on 32 high-fidelity (HF) simulations and 1027 low-fidelity (LF) simulations.

            @@ -422,7 +418,7 @@

            3.11.4. Comparison to High-fidelity-only

            - © Copyright 2023, The Regents of the University of California. + © Copyright 2024, The Regents of the University of California.

            diff --git a/docs/common/user_manual/examples/desktop/examples.html b/docs/common/user_manual/examples/desktop/examples.html index b00affe4..b34d2b9c 100644 --- a/docs/common/user_manual/examples/desktop/examples.html +++ b/docs/common/user_manual/examples/desktop/examples.html @@ -40,6 +40,7 @@ + @@ -141,11 +142,6 @@
          2. 5. Requirements
          3. 6. Bugs & Feature Requests
        -

        Damage and Loss DB

        -

        Technical Manual

        • 1. Technical Manual
        • @@ -225,7 +221,7 @@
          -

          3. Examples

          +

          3. Examples

          The following are a few examples showing the usage of EE-UQ. Video companions showing these examples are also provided. The files for the examples are available in Github.

          @@ -585,7 +581,7 @@
          Multi-fidelity Monte Carlo Simulation

          - © Copyright 2023, The Regents of the University of California. + © Copyright 2024, The Regents of the University of California.

          diff --git a/docs/common/user_manual/examples/desktop/hdro-0001/README.html b/docs/common/user_manual/examples/desktop/hdro-0001/README.html index 67f334b5..b5975d57 100644 --- a/docs/common/user_manual/examples/desktop/hdro-0001/README.html +++ b/docs/common/user_manual/examples/desktop/hdro-0001/README.html @@ -40,6 +40,7 @@ + @@ -126,11 +127,6 @@
        • 5. Requirements
        • 6. Bugs & Feature Requests
        -

        Damage and Loss DB

        -

        Technical Manual

        • 1. Technical Manual
        • @@ -210,7 +206,7 @@
          -

          Coupled Digital Twin Example

          +

          Coupled Digital Twin Example

          Example to demonstrate how to run a coupled OpenSees-OpenFOAM simulation to determine floor loads on a building and then perform an OpenSees simulation of the building assuming uncertainties in the building properties.

          @@ -228,7 +224,7 @@

          - © Copyright 2023, The Regents of the University of California. + © Copyright 2024, The Regents of the University of California.

          diff --git a/docs/common/user_manual/installation/desktop/downloadOther.html b/docs/common/user_manual/installation/desktop/downloadOther.html index 53807615..158ef248 100644 --- a/docs/common/user_manual/installation/desktop/downloadOther.html +++ b/docs/common/user_manual/installation/desktop/downloadOther.html @@ -40,6 +40,7 @@ + @@ -126,11 +127,6 @@
        • 5. Requirements
        • 6. Bugs & Feature Requests
        -

        Damage and Loss DB

        -

        Technical Manual

        • 1. Technical Manual
        • @@ -210,8 +206,8 @@
          -

          Install Additional Applications

          -

          Additional software is needed by the EE-UQ app. This software, which as is discussed in Software Architecture, is used by the application to perform the computations in the backend workflow. The software required is dependent on your operating system.

          +

          Install Additional Applications

          +

          Additional software is needed by the EE-UQ app. This software, which is discussed in Software Architecture, is used by the application to perform the computations in the backend workflow. The software required is dependent on your operating system.

          • Windows Users
          • @@ -230,7 +226,7 @@

            - © Copyright 2023, The Regents of the University of California. + © Copyright 2024, The Regents of the University of California.

            diff --git a/docs/common/user_manual/installation/desktop/downloadOtherMAC.html b/docs/common/user_manual/installation/desktop/downloadOtherMAC.html index 7b7be38e..d8d9be4c 100644 --- a/docs/common/user_manual/installation/desktop/downloadOtherMAC.html +++ b/docs/common/user_manual/installation/desktop/downloadOtherMAC.html @@ -40,6 +40,7 @@ + @@ -126,11 +127,6 @@
          • 5. Requirements
          • 6. Bugs & Feature Requests
          -

          Damage and Loss DB

          -

          Technical Manual

          -

          Damage and Loss DB

          -

          Technical Manual

          • 1. Technical Manual
          • @@ -210,27 +206,27 @@
            -

            Windows Users

            +

            Windows Users

            -

            Install Location

            +

            Install Location

            The following set of instructions assumes all files will be placed in a C:\SimCenter folder. You can of course place them anywhere you want, you just need to make appropriate changes to the env PATH settings. If you wish to follow our placement strategy, inside the C:\SimCenter folder create 2 additional folders named dakota and OpenSees.

            Note

            -

            The choice of C:\SimCenter was made as opposed to typical C:\Program Files location as there is no uninstallers provided for the different software packages we provide. To remove the software you only need to remove the SimCenter folder.

            +

            The choice of C:\SimCenter was made as opposed to typical C:\Program Files location as there are no uninstallers provided for the different software packages we provide. To remove the software you only need to remove the SimCenter folder.

            -

            Python

            +

            Python

            If you have not yet installed Python 3.7, we recommend installing Python 3.7 from Python.org. We recommend installing using the Windowsx86 64-bit executable installer.

            Note

            -

            Allow the installer to change yur system environment variables so that the directory containing the executable is on your path. This requires checking the small box asking for this when the installer starts. The box is located at bottom of installer application window.

            +

            Allow the installer to change your system environment variables so that the directory containing the executable is on your path. This requires checking the small box asking for this when the installer starts. The box is located at the bottom of the installer application window.

            Warning

            -

            The latest version of Python is 3.8.3 At time of writing Python 3.8.3 was no working with the current numpy package.

            +

            The latest version of Python is 3.8.3 At the time of writing, Python 3.8.3 was not working with the current numpy package.

            Once Python is installed, you need to extend it by installing the following packages: numpy, scipy, and pandas. To install these packages, start a terminal window as an Admin user and in that window type the following instructions:

            pip install numpy
            @@ -249,20 +245,20 @@ 

            Python -

            Dakota

            -

            Dakota is the default UQ engine used by the EE-UQ app that is publicly available from the Dakota Download page. The download page offers an extensive list of downloadable files. You can narrow this down to the file to be selected by selecting Windows in the Platform, 6.10 (6.10 was latest at time of writing, select newer of course if available) in the Release, and Command Line Only for the interface type. In the Public area you should now only have a single option, click on the link to download Dakota. When you extract the files that you download, they will all be contained in a single folder, we suggest renaming it dakota-6.10.0 (the last .0 was the number in the download, sometimes developers issue minor updates and identify them through the last number). When you have renamed the folder move that folder to the C:\SimCenter\dakota\ folder.

            +

            Dakota

            +

            Dakota is the default UQ engine used by the EE-UQ app that is publicly available from the Dakota Download page. The download page offers an extensive list of downloadable files. You can narrow this down to the file to be selected by selecting Windows in the Platform, 6.10 (6.10 was the latest at the time of writing, select newer of course if available) in the Release, and Command Line Only for the interface type. In the Public area you should now only have a single option, click on the link to download Dakota. When you extract the files that you download, they will all be contained in a single folder, we suggest renaming it dakota-6.10.0 (the last .0 was the number in the download, sometimes developers issue minor updates and identify them through the last number). When you have renamed the folder move that folder to the C:\SimCenter\dakota\ folder.

            Note

            -

            We place dakota-6.10.0 inside dakota folder to be able to have multiple versions installed. This is a useful practice, as software developers make tweaks that can effect the results of past simulations. It is useful to be able to compare different versions of an application to ensure results stay the same.

            +

            We place dakota-6.10.0 inside dakota folder to be able to have multiple versions installed. This is a useful practice, as software developers make tweaks that can affect the results of past simulations. It is useful to be able to compare different versions of an application to ensure results stay the same.

            -

            OpenSees

            -

            OpenSees is the default FEM engine used by the EE-UQ app that is publicly available from the OpenSees Download page. To download the OpenSees you have to enter your email address, which may also require you to register (that requirement is going away and may be gone by time you read this). At the bottom of the page, under section Windows Version is the download link for the current executable, currently 3.2.2 Follow the link to download the application. It is in the form of a .zip file. The zip file contains a folder and in the bin directory is the OpenSees.exe application. The other files and folders are needed by the application and must be kept. Rename the folder to OpenSees-3.2.2 and move the folder to the C:\SimCenter\OpenSees folder.

            +

            OpenSees

            +

            OpenSees is the default FEM engine used by the EE-UQ app that is publicly available from the OpenSees Download page. To download the OpenSees you have to enter your email address, which may also require you to register (that requirement is going away and may be gone by the time you read this). At the bottom of the page, under section Windows Version is the download link for the current executable, currently 3.2.2 Follow the link to download the application. It is in the form of a .zip file. The zip file contains a folder and in the bin directory is the OpenSees.exe application. The other files and folders are needed by the application and must be kept. Rename the folder to OpenSees-3.2.2 and move the folder to the C:\SimCenter\OpenSees folder.

            -

            Modify the Environment Variables

            -

            You now need to make some changes to your environment variables as neither OpenSees or Dakota includes an installer which typically performs this task.

            +

            Modify the Environment Variables

            +

            You now need to make some changes to your environment variables as neither OpenSees or Dakota includes an installer that typically performs this task.

            1. Open the Start Search, type in “env”, and choose “Edit the system environment variables”

            2. Click the Environment Variables… button at the bottom right of the application that pop up.

            3. @@ -283,16 +279,16 @@

              Modify the Environment Variables
            4. Press the OK button.

            5. -
            6. Press now the Apply button and exit the SystemProperties application

            7. +
            8. Now press the Apply button and exit the SystemProperties application

            -

            Test the Install of Python, OpenSees & Dakota

            +

            Test the Install of Python, OpenSees & Dakota

            Steps to Test:
            1. Open a command window window(type cmd in search)

            2. Type python3 in the application that starts (this should bring up python interpreter)

            3. -
            4. Enter the following to test the install of the modules and quit the application:

            5. +
            6. Enter the following to test the installation of the modules and quit the application:

          -

          Damage and Loss DB

          -

          Technical Manual

          -

          Damage and Loss DB

          -

          Technical Manual

          -

          Damage and Loss DB

          -

          Technical Manual

          • 1. Technical Manual
          • @@ -216,7 +212,7 @@
            -

            1. Installation

            +

            1. Installation

            All SimCenter applications can be downloaded from the SimCenter Research Tools page. This chapter walks you through the installation process on Windows and macOS operating systems from downloading the application to testing that it has been installed correctly.

              @@ -246,7 +242,7 @@

              - © Copyright 2023, The Regents of the University of California. + © Copyright 2024, The Regents of the University of California.

              diff --git a/docs/common/user_manual/releases/eeCapabilities.html b/docs/common/user_manual/releases/eeCapabilities.html index 2d577fc2..3f553e66 100644 --- a/docs/common/user_manual/releases/eeCapabilities.html +++ b/docs/common/user_manual/releases/eeCapabilities.html @@ -40,6 +40,7 @@ + @@ -135,11 +136,6 @@
            • 5. Requirements
            • 6. Bugs & Feature Requests
            -

            Damage and Loss DB

            -

            Technical Manual

            -

            Damage and Loss DB

            -

            Technical Manual

            -

            Damage and Loss DB

            -

            Technical Manual

            -

            Damage and Loss DB

            -

            Technical Manual

            -

            Damage and Loss DB

            -

            Technical Manual

            -

            Damage and Loss DB

            -

            Technical Manual

            -

            Damage and Loss DB

            -

            Technical Manual

            -

            Damage and Loss DB

            -

            Technical Manual

            • 1. Technical Manual
            • @@ -210,24 +206,15 @@
              -

              Release Plans

              +

              Release Plans

              The following features are planned to be developed for upcoming releases of EE-UQ app. We are actively working on the features in the next release. Farther development priorities may change depending on feedback from the community. If you have any suggestions, we encourage you to contribute and contact us through the SimCenter Forum.

              -
              -

              October 2023

              -
              -
                -
              1. Bayesian model selection and averaging (1.2.4.1) - Define weights for each model candidate and propagate epistemic uncertainty by randomly selecting a model for each realization according to these weights.

              2. -
              3. Accelerate Bayesian calibration using advanced Markov Chain Monte Carlo methods (1.2.3.3) - Build a surrogate model iteratively that will replace the original model in MCMC sampling. In each iteration, use a batch of data generated by evaluating the original model at carefully selected points to improve the surrogate model approximation of the target probability density. This is especially helpful when the original model is expensive to run and conventional MCMC is not feasible.

              4. -
              5. Additional calibration examples developed with researchers running projects at NHERI experimental facilities (1.2.5.3) - These examples demonstrate real-world application of EE-UQ app and they can also serve as templates for future users of NHERI facilities.

              6. -
              -
              -
              -
              -

              March 2024

              +
              +

              October 2024

                -
              1. Advanced model calibration methods using recursive stochastic filters and particle filters (1.2.3.4)

              2. +
              3. Accelerate Bayesian calibration using advanced Markov Chain Monte Carlo methods (1.2.3.4) - Build a surrogate model iteratively that will replace the original model in MCMC sampling. In each iteration, use a batch of data generated by evaluating the original model at carefully selected points to improve the surrogate model approximation of the target probability density. This is especially helpful when the original model is expensive to run and conventional MCMC is not feasible.

              4. +
              5. Additional calibration examples developed with researchers running projects at NHERI experimental facilities (1.2.5.3) - These examples demonstrate real-world application of EE-UQ app and they can also serve as templates for future users of NHERI facilities.

              diff --git a/docs/common/user_manual/releases/quoReleaseNotes.html b/docs/common/user_manual/releases/quoReleaseNotes.html index 09618669..a84cb388 100644 --- a/docs/common/user_manual/releases/quoReleaseNotes.html +++ b/docs/common/user_manual/releases/quoReleaseNotes.html @@ -40,6 +40,7 @@ + @@ -126,11 +127,6 @@
            • 5. Requirements
            • 6. Bugs & Feature Requests
            -

            Damage and Loss DB

            -

            Technical Manual

            -

            Damage and Loss DB

            -

            Technical Manual

            • 1. Technical Manual
            • @@ -210,9 +206,10 @@
              -

              Capabilities

              -

              Version 3.0 of EE-UQ app was released May 2023. The following lists the functionality available in this current version. (Note: New features and fixes in this release are marked blue in the following list of features.) Note the version introduced major changes in how tool is used. Some of existing Haz options were moved to a new Tool main menu option.

              -

              Release date: May, 2023

              +

              Capabilities

              +

              Version 3.4 of EE-UQ app was released Jan 2024. The following is the functionality available in this current version. (Note: New features and fixes in this release are marked blue in the following list of features.) +The major update from Version 3.0 is adding the analysis capability for regional transportation infrastructure. Note that since version 3.0, most Haz options were moved to the Tool main menu.

              +

              Release date: Dec, 2023

              1. Hazard Types:

                @@ -220,7 +217,7 @@
              2. User specified earthquakes.

              3. User specified hurricanes.

              4. -
                ShakeMap Scenarios, which suports importing the following ShakeMap outputs:
                  +
                  ShakeMap Scenarios, which supports importing the following ShakeMap outputs:
                  1. ShakeMap ground motion grid in .xml format.

                  2. PGA contours in .json format.

                  3. Fault rupture in .json format.

                  4. @@ -233,46 +230,68 @@
            -
          • -
            Asset Types:
              +
            • Asset Types:

              +
              +
              • Buildings:
                  -
                1. Building database in a .csv format.

                2. -
                3. Building database in a .gis format.

                4. +
                5. Load building database in a .csv format.

                6. +
                7. Load building database in a .gis format.

              • -
              +
            • +
              Transportation infrastructure:
                +
              1. Load transportation infrastructure database in SimCenter’s .geojson format.

              2. +
              3. Load transportation infrastructure database in common .gis format.

              4. +
            • +
            +
          • +
          • Asset Modeling:
            • Buildings:
              1. MDOF-LU (MDOF shear building model)

              2. OpenSeesPy script building generator

              3. -
              4. IMasEDP, i.e., no analysis as the IM is considered the EDP

              5. +
              6. IMasEDP, i.e., no structural modeling, and the Intensity Measures (IMs) are considered the Engineering Demand Parameters (EDPs)

              7. CustomPy

            • +
            • +
              Transportation infrastructure:
                +
              1. IMasEDP, i.e., no structural modeling, and the Intensity Measures (IMs) are considered the Engineering Demand Parameters (EDPs)

              2. +
              +
              +
              +
          • -
          • -
            Asset Analysis:
              -
            • +
            • +
              Asset Analysis:
                +
              • Buildings:
                1. OpenSees

                2. OpenSeesPy

                3. IMasEDP, i.e., no analysis as the IM is considered the EDP

                4. +
                5. CustomPy for CustomPy in Asset Modeling

                6. +
                7. None for IMasEDP option in Modeling.

                8. +
                +
                +
                +
              • +
              • +
                Transportation infrastructure:
                  +
                1. None for IMasEDP option in Modeling.

                -

                d. CustomPy for CustomPy in Asset Modeling -d. None for IMasEDP option in Modeling.

              • @@ -283,9 +302,9 @@
              • Damage and Loss:
                • -
                  Buildings:
                    +
                    Buildings:
                    • -
                      Pelicun
                        +
                        Pelicun
                        1. HAZUS MH EQ

                        2. HAZUS MH EQ IM

                        3. HAZUS MH HU

                        4. @@ -297,6 +316,14 @@
                    • +
                    • +
                      Transportation infrastructure
                        +
                      1. HAZUS MH EQ

                      2. +
                      3. HAZUS MH EQ IM

                      4. +
                      +
                      +
                      +
                  @@ -323,7 +350,7 @@
                  Site definition:
                  1. Grid

                  2. Point

                  3. -
                  4. Scattered sites (user defined sites in .csv format)

                  5. +
                  6. Scattered sites (user-defined sites in .csv format)

                @@ -331,10 +358,9 @@
              • Rupture forecast models:
                1. OpenSHA UCERF rupture forecast models

                2. -
                3. OpenSHA Point source user defined

                4. -
                5. OpenQuake Scenario Based

                6. -
                7. OpenQuake Classical PSHA

                8. -
                9. Hazard Occurrence Model

                10. +
                11. OpenSHA Point source user-defined

                12. +
                13. OpenQuake rupture forecast

                14. +
                15. Hazard Occurrence Model

                @@ -375,7 +401,7 @@
              • Intensity Measures:
                  -
                1. Spectral accelertion (SA)

                2. +
                3. Spectral acceleration (SA)

                4. Peak ground acceleraation (PGA)

                @@ -384,10 +410,9 @@
              • Vs30 Model:
                1. CGS/Wills Vs30 (Wills et al., 2015)

                2. -
                3. Peak ground acceleraation (PGA)

                4. Thompson California Vs30 (Thompson et al., 2018)

                5. Global Vs30 (Heath et al., 2020)

                6. -
                7. User Defined`

                8. +
                9. User Defined

                @@ -407,8 +432,8 @@
              • Hurricane track definition:
                  -
                1. User defined sites in .csv format

                2. -
                3. Select from database of historical hurricanes

                4. +
                5. User-defined sites in .csv format

                6. +
                7. Select from a database of historical hurricanes

                8. Truncate hurricane track functionality

                @@ -416,8 +441,8 @@
              • Landfall location and parameters:
                  -
                1. User select on GIS map

                2. -
                3. Manual user entry in input box

                4. +
                5. User selects on GIS map

                6. +
                7. Manual user entry in the input box

                @@ -452,7 +477,7 @@

                - © Copyright 2023, The Regents of the University of California. + © Copyright 2024, The Regents of the University of California.

                diff --git a/docs/common/user_manual/releases/r2dPlans.html b/docs/common/user_manual/releases/r2dPlans.html index 17308c28..6b1f91cd 100644 --- a/docs/common/user_manual/releases/r2dPlans.html +++ b/docs/common/user_manual/releases/r2dPlans.html @@ -40,6 +40,7 @@ + @@ -126,11 +127,6 @@
              • 5. Requirements
              • 6. Bugs & Feature Requests
              -

              Damage and Loss DB

              -

              Technical Manual

              • 1. Technical Manual
              • @@ -210,26 +206,19 @@
                -

                Release Plans

                +

                Release Plans

                The following features are planned to be developed for upcoming releases of EE-UQ app. We are actively working on the features in the next release. Farther development priorities may change depending on feedback from the community. If you have any suggestions, we encourage you to contribute and contact us through the SimCenter Forum.

                -
                -

                June 2023

                +
                +

                March 2024

                1. Water Distribution Network, buried pipelines.(1.3.4.3)

                2. -
                -
                -
                -

                Sept 2023

                -
                1. Efficient forward propagation using Multi-Fidelity Monte-Carlo (1.2.3.1) - Use a few realizations of the output calculated with expensive, high-fidelity models to evaluate and correct the bias in efficient, approximate models, such as surrogates. With little extra computational demands, this method provides a substantial improvement in surrogate model performance if you have the high-fidelity models available that were used to train the surrogates.

                2. -
                3. Support transportation networks hazus level analysis (1.3.4.3) and provide corresponding Examples (1.3.4.7) - Extend the scope of tool with transportation networks and add examples that can serve as templates.

                4. Add datasets to simulate subassembly damage and losses under wind demands (1.3.5.1) - Data from recent publications in the Performance-Based Wind Engineering literature is collected to enable high-resolution performance assessment under wind hazard, add data to DB-DamegeAndLoss.

                5. -
                6. Incorprate surrogate models created by other SimCenter tools in regional assesments (1.3.6.1) - Other tools can export models in a standard format that can be imported directly in R2D for use in regional simulations.

                7. Probabilistic asset inventories (1.3.6.2) - Calibrate, store, and propagate uncertainties in building features at the regional scale. For example, we have some but not all information for all buildings in an area, fill in the gaps using information we do know.

                -
                -

                March 2024

                +
                +

                June 2024

                1. Automatic access to physics-based ground motion simulation results (1.1.1.3)

                2. Add datasets to simulate subassembly damage and losses under water demands (1.3.5.2)

                3. @@ -237,16 +226,16 @@

                  March 2024 -

                  Sept 2024

                  +

                  Sept 2024

                  1. Develop methods to model interdependencies between physical components, housing, socio-economic functions, and lifelines (1.3.4.6)

                  2. Add datasets to simulate high-resolution damages and losses in transportation networks (1.3.5.3)

                  3. Develop and implement metrics and their visualization to inform recovery and community resilience (1.4.3.2)

                  4. -
                  5. Look at aspects related to recovery. Housholds (1.4.3.2), Infrastructure )1.4.2.4), Business operations (1.4.2.5)

                  6. +
                  7. Look at aspects related to recovery. Housholds (1.4.3.2), Infrastructure (1.4.2.4), Business operations (1.4.2.5)

                -

                Sept 2025

                +

                Sept 2025

                1. Multi-fidelity models in regional simulations (1.3.3.1)

                2. Multi-scale models for wind and water (1.3.3.2)

                3. @@ -270,7 +259,7 @@

                  Sept 2025

                  - © Copyright 2023, The Regents of the University of California. + © Copyright 2024, The Regents of the University of California.

                diff --git a/docs/common/user_manual/releases/r2dRelaseNotes.html b/docs/common/user_manual/releases/r2dRelaseNotes.html index a72b6b5f..20d3c51d 100644 --- a/docs/common/user_manual/releases/r2dRelaseNotes.html +++ b/docs/common/user_manual/releases/r2dRelaseNotes.html @@ -40,6 +40,7 @@ + @@ -126,11 +127,6 @@
              • 5. Requirements
              • 6. Bugs & Feature Requests
              -

              Damage and Loss DB

              -

              Technical Manual

              -

              Damage and Loss DB

              -

              Technical Manual

              -

              Damage and Loss DB

              -

              Technical Manual

              -

              Damage and Loss DB

              -

              Technical Manual

              -

              Damage and Loss DB

              -

              Technical Manual

              -

              Damage and Loss DB

              -

              Technical Manual

              • 1. Technical Manual
              • @@ -216,7 +212,7 @@
                -

                4. Troubleshooting

                +

                4. Troubleshooting

                • 4.1. Startup Issues
                • @@ -235,7 +231,7 @@

                  - © Copyright 2023, The Regents of the University of California. + © Copyright 2024, The Regents of the University of California.

                  diff --git a/docs/common/user_manual/troubleshooting/desktop/troubleshootingRunning.html b/docs/common/user_manual/troubleshooting/desktop/troubleshootingRunning.html index a4df88a9..d27adb71 100644 --- a/docs/common/user_manual/troubleshooting/desktop/troubleshootingRunning.html +++ b/docs/common/user_manual/troubleshooting/desktop/troubleshootingRunning.html @@ -40,6 +40,7 @@ + @@ -132,11 +133,6 @@
                • 5. Requirements
                • 6. Bugs & Feature Requests
                -

                Damage and Loss DB

                -

                Technical Manual

                • 1. Technical Manual
                • @@ -218,7 +214,7 @@
                  -

                  4.2. Issues While Running

                  +

                  4.2. Issues While Running

                  Common causes of failure include incorrect setup, non-functioning or poorly functioning websites, user error, and possible bugs in the software. To discover the errors, it is useful to understand how the user interface (UI) and the backend work when the user submits to run a job. A number of things occur when the Submit button is clicked:

                  1. The UI creates a tmp.SimCenter folder in the working directory and later creates a templatedir within tmp.SimCenter.

                  2. @@ -258,7 +254,7 @@

                    - © Copyright 2023, The Regents of the University of California. + © Copyright 2024, The Regents of the University of California.

                    diff --git a/docs/common/user_manual/troubleshooting/desktop/troubleshootingStartup.html b/docs/common/user_manual/troubleshooting/desktop/troubleshootingStartup.html index a14aa0d3..a4ec977e 100644 --- a/docs/common/user_manual/troubleshooting/desktop/troubleshootingStartup.html +++ b/docs/common/user_manual/troubleshooting/desktop/troubleshootingStartup.html @@ -40,6 +40,7 @@ + @@ -132,11 +133,6 @@
                  3. 5. Requirements
                  4. 6. Bugs & Feature Requests
                -

                Damage and Loss DB

                -

                Technical Manual

                • 1. Technical Manual
                • @@ -218,7 +214,7 @@
                  -

                  4.1. Startup Issues

                  +

                  4.1. Startup Issues

                  On Windows operating systems, you might receive the error shown in Fig. 4.1.2 when starting the application. This error is caused by a missing Visual C/C++ runtime library. You can fix this by running the installer for the Visual C/C++ redistributable package vc_redist.x64.exe which is included in the folder of every SimCenter desktop application.

                  ../../../../_images/EE-UQ-MissingCRT.png @@ -236,7 +232,7 @@

                  - © Copyright 2023, The Regents of the University of California. + © Copyright 2024, The Regents of the University of California.

                  diff --git a/docs/common/user_manual/usage/desktop/Configuring_CustomUQ.html b/docs/common/user_manual/usage/desktop/Configuring_CustomUQ.html index 271b4f41..7c3e23db 100644 --- a/docs/common/user_manual/usage/desktop/Configuring_CustomUQ.html +++ b/docs/common/user_manual/usage/desktop/Configuring_CustomUQ.html @@ -40,6 +40,7 @@ + @@ -50,7 +51,7 @@ - + @@ -128,11 +129,6 @@
                • 5. Requirements
                • 6. Bugs & Feature Requests
                -

                Damage and Loss DB

                -

                Technical Manual

                -

                Damage and Loss DB

                -

                Technical Manual

                • 1. Technical Manual
                • @@ -210,10 +206,10 @@
                  -

                  Bayesian Calibration

                  -

                  The methods in the Bayesian calibration category are concerned with estimation of the probability distribution of the parameter values given observational measurements. Unlike deterministic parameter estimation methods, in which the user provides a range and an initial starting point for the input random variables, when using the methods in this category, the user has some idea about the probability distribution of the parameter values. This information is provided in the form of the prior distributions in the RV panel. The Bayesian calibration methods take this prior information and combine it with information from the observed data provided in the UQ panel, to infer posterior distributions of the parameter values. A Bayesian updating paradigm is followed, the prior distribution on a parameter is updated through a Bayesian framework involving experimental data and a likelihood function. The likelihood function specifies the likelihood that a particular parameter value of the model produced the observed data. Dakota uses a Gaussian likelihood function. The algorithms that generate the samples to characterize the posterior distributions are typically based on some Markov Chain Monte Carlo (MCMC) methods. Currently, EE-UQ app provides access to the DREAM algorithm implemented in Dakota.

                  +

                  Bayesian Calibration

                  +

                  The methods in the Bayesian calibration category are concerned with the estimation of the probability distribution of the parameter values given observational measurements. Unlike deterministic parameter estimation methods, in which the user provides a range and an initial starting point for the input random variables, when using the methods in this category, the user has some idea about the probability distribution of the parameter values. This information is provided in the form of the prior distributions in the RV panel. The Bayesian calibration methods take this prior information and combine it with information from the observed data provided in the UQ panel, to infer posterior distributions of the parameter values. A Bayesian updating paradigm is followed, the prior distribution on a parameter is updated through a Bayesian framework involving experimental data and a likelihood function. The likelihood function specifies the likelihood that a particular parameter value of the model produced the observed data. Dakota uses a Gaussian likelihood function. The algorithms that generate the samples to characterize the posterior distributions are typically based on some Markov Chain Monte Carlo (MCMC) methods. Currently, EE-UQ app provides access to the DREAM algorithm implemented in Dakota.

                  -

                  DREAM

                  +

                  DREAM

                  The Differential Evolution Adaptive Metropolis ([DREAM]) method runs multiple Markov chains simultaneously for global exploration of the space, and automatically tunes and scales the orientation of the proposal distributions in randomized subspaces during the search. figDREAM shows the input panel corresponding to the DREAM method. The required inputs for this method are:

                  1. # Chains: number of chains in the DREAM algorithm

                  2. @@ -260,7 +256,7 @@

                    DREAM

                    - © Copyright 2023, The Regents of the University of California. + © Copyright 2024, The Regents of the University of California.

                    diff --git a/docs/common/user_manual/usage/desktop/DakotaDeterministicCalibration.html b/docs/common/user_manual/usage/desktop/DakotaDeterministicCalibration.html index 12b7cc98..ae65201b 100644 --- a/docs/common/user_manual/usage/desktop/DakotaDeterministicCalibration.html +++ b/docs/common/user_manual/usage/desktop/DakotaDeterministicCalibration.html @@ -40,6 +40,7 @@ + @@ -127,11 +128,6 @@
                  3. 5. Requirements
                  4. 6. Bugs & Feature Requests
                -

                Damage and Loss DB

                -

                Technical Manual

                • 1. Technical Manual
                • @@ -211,29 +207,29 @@
                  -

                  Deterministic Calibration

                  -

                  Deterministic calibration methods (also known as non-linear least squares methods or deterministic parameter estimation methods) are used to fit a set of m observations (provided in the calibration data file defined in the UQ panel) with a model (defined in the FEM panel) that is non-linear with n unknown parameters. The unknown parameters of this model are defined in the RV panel. The bounds of the domain within which the optimal values of the parameters need to be searched for are also specified in the RV panel, along with the initial point at which the search will begin. No prior specification of the distribution associated with the random variables is necessary. The output quantities from the model are defined in the QOI panel. For each evaluation of the computational model, the processing scripts should write the values of the simulated response quantities of interest in a file called results.out. The algorithms employed will find a set of parameter values that minimizes the sum of the squared differences between the measured values of the QoIs and the predicted values of the QoIs from the computational model. The algorithms themselves are general functional minimization algorithms seeking to minimize:

                  +

                  Deterministic Calibration

                  +

                  Deterministic calibration methods (also known as non-linear least squares methods or deterministic parameter estimation methods) are used to fit a set of m observations (provided in the calibration data file defined in the UQ panel) with a model (defined in the FEM panel) that is non-linear with n unknown parameters. The unknown parameters of this model are defined in the RV panel. The bounds of the domain within which the optimal values of the parameters need to be searched for are also specified in the RV panel, along with the initial point at which the search will begin. No prior specification of the distribution associated with the random variables is necessary. The output quantities from the model are defined in the QOI panel. For each evaluation of the computational model, the processing scripts should write the values of the simulated response quantities of interest in a file called results.out. The algorithms employed will find a set of parameter values that minimizes the sum of the squared differences between the measured values of the QoIs and the predicted values of the QoIs from the computational model. The algorithms themselves are general functional minimization algorithms seeking to minimize:

                  ()\[f(\theta) = \sum_{i=1}^{m} R_i(\theta)^2 = \sum_{i=1}^{m} \left ( y_i(\theta)^{predicted} - y_i^{measured} \right)^2\]

                  where \(R_i(\theta)\), typically called the residuals, are the differences between the measured data \(y_i^{measured}\) provided in the calibration data file, and predictions from the model \(y_i(\theta)^{predicted}\) of the corresponding response quantity, and \(\theta \in \mathbb{R}^n\) the \(n\) model parameters whose values are not precisely known and are being calibrated to match available data.

                  The panel that is presented to the user when this Dakota Category is chosen, is as shown in figParameterEstimation.

                  ../../../../_images/DeterministicCalibration.png -

                  Dakota determinstic calibration input panel.

                  +

                  Dakota deterministic calibration input panel.

                  -

                  For determinstic calibration two different optimization algorithms are currently provided under the Method drop down menu, namely OPT++GaussNewton and NL2SOL. For both methods three input parameters need to be specified as shown in the figure:

                  +

                  For deterministic calibration two different optimization algorithms are currently provided under the Method drop-down menu, namely OPT++GaussNewton and NL2SOL. For both methods three input parameters need to be specified as shown in the figure:

                  1. the maximum number of iterations for the optimization algorithm

                  2. the convergence tolerance

                  3. the path to the file containing the calibration data

                  -

                  OPT++GaussNewton

                  +

                  OPT++GaussNewton

                  OPT++ provides a Gauss-Newton least squares capability which, on zero-residual test problems, can exhibit quadratic convergence rates near the solution. As a consequence, good starting point values for the parameters should be provided. The Hessian is constructed with a Gauss-Newton approximation and the OPT++ Optimization routines are used. ([OPT]).

                  -

                  NL2SOL

                  -

                  The NL2SOL method is based on an adaptive nonlinear least-squares algorithm, devised by Dennis and colleagues ([Dennis81a], [Dennis81b]). NL2SOL uses a trust region method and adaptively switches between two Hessian approximations, the Gauss-Newton approximation alone and the Gauss-Newton approximation plus a quasi-Newton approximation to the rest of the Hessian. This latter approximation being useful when the starting guess is far from solution. For problems with large residuals, this algorithm is known to be more reliable than Gauss-Newton.

                  +

                  NL2SOL

                  +

                  The NL2SOL method is based on an adaptive nonlinear least-squares algorithm, devised by Dennis and colleagues ([Dennis81a], [Dennis81b]). NL2SOL uses a trust region method and adaptively switches between two Hessian approximations, the Gauss-Newton approximation alone and the Gauss-Newton approximation plus a quasi-Newton approximation to the rest of the Hessian. This latter approximation is useful when the starting guess is far from the solution. For problems with large residuals, this algorithm is known to be more reliable than Gauss-Newton.

                  Note

                  The data are provided in the calibration data file, which must fulfill the following requirements:

                  @@ -283,7 +279,7 @@

                  NL2SOL

                  - © Copyright 2023, The Regents of the University of California. + © Copyright 2024, The Regents of the University of California.

                  diff --git a/docs/common/user_manual/usage/desktop/DakotaGradientFreeOptimization.html b/docs/common/user_manual/usage/desktop/DakotaGradientFreeOptimization.html index b3880a03..b0dc7752 100644 --- a/docs/common/user_manual/usage/desktop/DakotaGradientFreeOptimization.html +++ b/docs/common/user_manual/usage/desktop/DakotaGradientFreeOptimization.html @@ -40,6 +40,7 @@ + @@ -126,11 +127,6 @@
                • 5. Requirements
                • 6. Bugs & Feature Requests
                -

                Damage and Loss DB

                -

                Technical Manual

                • 1. Technical Manual
                • @@ -210,11 +206,11 @@
                  -

                  Gradient-free Parameter Estimation

                  +

                  Gradient-free Parameter Estimation

                  It is not uncommon for engineering problems that the gradient of a computational model with respect to the model parameters is not reliably estimated. Sometimes, the objective function for deterministic calibration is not differentiable. In such situations, a gradient-based local search algorithm might fail to locate the optimum parameter values that provide the best fit of the model predictions to the data. A gradient-free local search method can be employed for deterministic calibration instead of a gradient-based algorithm in such scenarios.

                  -

                  Gradient-free optimization methods are used to minimize an objective function based solely on evaluation of the objective function values without the use of any derivative information or any approximation of the derivatives. When concerned with parameter estimation, the objective function is typically the sum of the squared differences between the predictions from a model and the calibration data. However, any objective function that the user desires can be employed. When performing grdient-free parameter estimation, the model (or the post-processing script, if any), should be defined in a way that returns the objective function value (a single scalar quantity) in a file called results.out.

                  +

                  Gradient-free optimization methods are used to minimize an objective function based solely on an evaluation of the objective function values without the use of any derivative information or any approximation of the derivatives. When concerned with parameter estimation, the objective function is typically the sum of the squared differences between the predictions from a model and the calibration data. However, any objective function that the user desires can be employed. When performing gradient-free parameter estimation, the model (or the post-processing script, if any), should be defined in a way that returns the objective function value (a single scalar quantity) in a file called results.out.

                  The parameters of the model (which is defined in the FEM panel) are defined in the RV panel. The bounds of the domain within which the optimal values of the parameters need to be searched for are also specified in the RV panel, along with the initial point at which the search will start. No prior specification of the distribution associated with the random variables is necessary.

                  -

                  The output from the model is the objective function value, and this can be given a name which is defined in the EDP panel. The length must be set equal to 1.

                  +

                  The output from the model is the objective function value, and this can be given a name that is defined in the EDP panel. The length must be set equal to 1.

                  The algorithms employed will find a set of parameter values that minimizes the objective function.

                  The panel that is presented to the user when this Dakota Category is chosen, is as shown in figGradientFreeParameterEstimation.

                  @@ -222,20 +218,20 @@

                  Input panel for gradient-free parameter estimation using Dakota.

                  @@ -251,7 +247,7 @@

                  Pattern Search

                  - © Copyright 2023, The Regents of the University of California. + © Copyright 2024, The Regents of the University of California.

                  diff --git a/docs/common/user_manual/usage/desktop/DakotaReliability.html b/docs/common/user_manual/usage/desktop/DakotaReliability.html index 7179a271..59547c02 100644 --- a/docs/common/user_manual/usage/desktop/DakotaReliability.html +++ b/docs/common/user_manual/usage/desktop/DakotaReliability.html @@ -40,6 +40,7 @@ + @@ -148,11 +149,6 @@
                • 5. Requirements
                • 6. Bugs & Feature Requests
                -

                Damage and Loss DB

                -

                Technical Manual

                • 1. Technical Manual
                • @@ -236,11 +232,11 @@
                  -

                  2.1.2.3. Reliability Analysis

                  +

                  2.1.2.3. Reliability Analysis

                  Reliability methods are another class of probabilistic algorithms used for quantifying the effect of uncertainties in simulation input on response metrics of interest. These methods, unlike forward propagation analysis, provide the probability of response exceeding the user-provided threshold levels, i.e. given a set of uncertain input variables, it estimates the probability of system ‘failure’ defined as an excessive response. For reliability analysis, it is often more efficient to concentrate samples around the tail region of the response distributions, i.e. generating more events having low occurrence probability but high consequence, since often the number of samples required by naive sampling approach to resolve a low probability can be prohibitive.

                  -

                  Reliability methods can be split into local and global reliability methods and importance sampling-based method, as elaborated in the following sections.

                  +

                  Reliability methods can be split into local and global reliability methods and importance sampling-based methods, as elaborated in the following sections.

                  -

                  Problem Formulation

                  +

                  Problem Formulation

                  The probability of failure \(P_f\) is computed by the following integration:

                  @@ -262,15 +258,15 @@

                  Problem Formulation -

                  Local Reliability Methods

                  -

                  Local reliability methods introduces first/second-order local approximation of the response or \(g(\mathbf{x})\) around either “Mean Value” or “Design point (also known as the most probable point, MPP)”. Each of these methods involves gradient-based local optimization. The local reliability methods can also be used for “inverse reliability problems” which aims to idenitify the unknown parameter (random variables) combination that produces prescribed probability levels. The user selects the local method using the pull down menu.

                  +

                  Local Reliability Methods

                  +

                  Local reliability methods introduce a first/second-order local approximation of the response or \(g(\mathbf{x})\) around either “Mean Value” or “Design point (also known as the most probable point, MPP)”. Each of these methods involves gradient-based local optimization. The local reliability methods can also be used for “inverse reliability problems” which aim to identify the unknown parameter (random variables) combination that produces prescribed probability levels. The user selects the local method using the pull-down menu.

                  The default local reliability method is inverse reliability using the first-order reliability approximation (FORM) method. For the FORM method the user provides the following inputs:

                  ../../../../_images/localReliabilityMPP.png

                  Fig. 2.1.2.3.1 Local reliability analysis using the MPP option.

                    -
                  1. The first input involves selection of the MPP search method from the following options:

                  2. +
                  3. The first input involves a selection of the MPP search method from the following options:

                  -

                  Damage and Loss DB

                  -

                  Technical Manual

                  • 1. Technical Manual
                  • @@ -236,8 +232,8 @@
                    -

                    2.1.2.1. Forward Propagation

                    -

                    The forward propagation analysis provides probabilistic understanding of output variables by producing sample realizations and statistical moments (mean, standard deviation, skewness, and kurtosis) of the quantities of interest. Currently four sampling methods are available:

                    +

                    2.1.2.1. Forward Propagation

                    +

                    The forward propagation analysis provides a probabilistic understanding of output variables by producing sample realizations and statistical moments (mean, standard deviation, skewness, and kurtosis) of the quantities of interest. Currently, four sampling methods are available:

                    1. Monte Carlo Sampling (MCS)

                    2. Latin Hypercube Sampling (LHS)

                    3. @@ -249,7 +245,7 @@

                    Depending on the option selected, the user must specify the appropriate input parameters. For instance, for MCS, the number of samples specifies the number of simulations to be performed, and providing a seed value for the pseudo-random number generator will produce the same sequence of random numbers allowing the user to reproduce the sampling results multiple times. The user selects the sampling method from the dropdown Dakota Method Category menu. Additional information regarding sampling techniques offered in Dakota can be found here.

                    -

                    Monte Carlo Sampling (MCS)

                    +

                    Monte Carlo Sampling (MCS)

                    MCS is among the most robust and universally applicable sampling methods. Moreover, the convergence rate of MCS methods are independent of the problem dimensionality, albeit the convergence rate of such MCS methods is relatively slow at \(N^{-1/2}\). In MCS, a sample drawn at any step is independent of all previous samples.

                    Fig. 2.1.2.1.1 shows the input panel corresponding to the Monte Carlo Sampling setting. Two input parameters need to be specified: (1) the number of samples of the output to be produced, which is equal to the number of times the model is evaluated, and (2) the seed for the pseudo-random number generator.

                    @@ -258,8 +254,8 @@

                    Monte Carlo Sampling (MCS) -

                    Latin Hypercube Sampling (LHS)

                    -

                    Conventional Monte Carlo method generates each sample independently, which may produce undesired clusters and gaps between the samples arising from the sampling variability. On the other hand, Latin hypercube sampling (LHS) aims to prevent those gaps and clusters by ‘evenly’ spreading out the samples throughout the whole input domain. This can significantly reduce the sampling variability and facilitate faster convergence of the probabilistic statistics. In particular, LHS divides the input domain of each variable into N intervals with equal probability and locates the samples such that only one sample lies on each interval. This strategy enforces the samples to be more uniformly spread across the domain. In general, LHS encouraged over MCS as it provides unbiased estimation with smaller standard error. For example, this article suggests that the convergence rate of a sample mean is about quadratically faster with LHS than with Monte Carlo simulation. However, it is noted that one drawback of LHS is that there is no closed-form expression to quantify the error level of the estimators. This means that the user may need to perform the multiple batch samplings to quantify the error from the sample variability

                    +

                    Latin Hypercube Sampling (LHS)

                    +

                    Conventional Monte Carlo method generates each sample independently, which may produce undesired clusters and gaps between the samples arising from the sampling variability. On the other hand, Latin hypercube sampling (LHS) aims to prevent those gaps and clusters by ‘evenly’ spreading out the samples throughout the whole input domain. This can significantly reduce the sampling variability and facilitate faster convergence of the probabilistic statistics. In particular, LHS divides the input domain of each variable into N intervals with equal probability and locates the samples such that only one sample lies on each interval. This strategy forces the samples to be more uniformly spread across the domain. In general, LHS is encouraged over MCS as it provides unbiased estimation with a smaller standard error. For example, this article suggests that the convergence rate of a sample mean is about quadratically faster with LHS than with Monte Carlo simulation. However, it is noted that one drawback of LHS is that there is no closed-form expression to quantify the error level of the estimators. This means that the user may need to perform multiple batch samplings to quantify the error from the sample variability

                    ../../../../_images/Sampling_LHS1.png

                    Fig. 2.1.2.1.2 Monte Carlo sampling vs. Latin hypercube sampling

                    @@ -271,18 +267,18 @@

                    Latin Hypercube Sampling (LHS) -

                    Gaussian Process Regression (GPR)

                    -

                    For the problems in which computationally expensive models are involved, conventional sampling schemes such as LHS and MCS can be extremely time-consuming. In such case, a surrogate model can be constructed based on a smaller number of simulation runs, and then the surrogate model can be used to efficiently generate a larger number of samples replacing the expensive simulations.

                    +

                    Gaussian Process Regression (GPR)

                    +

                    For the problems in which computationally expensive models are involved, conventional sampling schemes such as LHS and MCS can be extremely time-consuming. In this case, a surrogate model can be constructed based on a smaller number of simulation runs, and then the surrogate model can be used to efficiently generate a larger number of samples replacing the expensive simulations.

                    Gaussian Process Regression (GPR), also known as Kriging is one of the well-established surrogate techniques, which constructs an approximated response surface based on Gaussian process modeling and covariance matrix optimizations. Fig. 2.1.2.1.4 shows the input panel for the GPR model that consists of training and sampling panels.

                    ../../../../_images/fwGP.png

                    Fig. 2.1.2.1.4 GPR forward propagation input panel.

                    -

                    In the Surrogate Training Data panel, the users specify the number of samples of the output of the computationally expensive model to be select either Monte Carlo Sampling or Latin Hypercube Sampling to generate sample output values from the computationally expensive model, which, along with the corresponding input values are used to train the surrogate models.

                    -

                    Other surrogate models, different from Gaussian process regression are also available in the drop-down menu titled Surface Fitting Method. All thse surrogate models utilize either Monte Carlo Sampling or Latin Hypercube Sampling to generate sample output values, which, along with the corresponding input values are used to train the surrogate models.

                    +

                    In the Surrogate Training Data panel, the users specify the number of samples of the output of the computationally expensive model to be either Monte Carlo Sampling or Latin Hypercube Sampling to generate sample output values from the computationally expensive model, which, along with the corresponding input values are used to train the surrogate models.

                    +

                    Other surrogate models, different from Gaussian process regression are also available in the drop-down menu titled Surface Fitting Method. All these surrogate models utilize either Monte Carlo Sampling or Latin Hypercube Sampling to generate sample output values, which, along with the corresponding input values are used to train the surrogate models.

                    -

                    Polynomial Chaos Expansion (PCE)

                    +

                    Polynomial Chaos Expansion (PCE)

                    Polynomial Chaos Expansion (PCE) is another surrogate model that can replace the expensive simulation model. Similar to the input GPR panel, the input panel for PCE model shown in Fig. 2.1.2.1.5 consists of training and sampling parts. The input parameters in the surrogate training data set specify the dataset used for training the surrogate model, while the parameters in the surrogate sampling data are related to the samples generated using the surrogate. Extreme care must be taken in specifying the parameters of the training dataset to result in an accurate approximation.

                    diff --git a/docs/common/user_manual/usage/desktop/DakotaSensitivity.html b/docs/common/user_manual/usage/desktop/DakotaSensitivity.html index 209d2f52..b3625976 100644 --- a/docs/common/user_manual/usage/desktop/DakotaSensitivity.html +++ b/docs/common/user_manual/usage/desktop/DakotaSensitivity.html @@ -40,6 +40,7 @@ + @@ -147,11 +148,6 @@
                  • 5. Requirements
                  • 6. Bugs & Feature Requests
                  -

                  Damage and Loss DB

                  -

                  Technical Manual

                  • 1. Technical Manual
                  • @@ -235,10 +231,10 @@
                    -

                    2.1.2.2. Global Sensitivity Analysis

                    -

                    Global sensitivity analysis is used to quantify contribution of each input variable to the uncertainty in the output quantity of interest (QoI). In particular, by calculating the global sensitivity indices, users can set preferences between random variables considering both inherent randomness and its propagation through the model. Global sensitivity analysis helps users to understand the overall impact of different sources of uncertainties and their interactions, as well as to accelerate UQ computations by focusing on dominant dimensions or screening out trivial input variables. Sensitivity index can also be used to identify the input variables for which extra experimentation/research may be useful in reducing the uncertainty in the initial specification.

                    -

                    Sobol indices are widely used variance-based global sensitivity measures which have two types: main effect and total effect sensitivity indices. The main effect index quantifies the fraction of variance in QoI that can be attributed to specific input random variable(s) but without considering interactive effect with other input variables. The total effect index, on the other hand, additionally takes the interactions into account. Please read HERE for more details on the equations.

                    -

                    Dakota Sensitivity Analysis is based on efficient Monte Carlo method (See Eqs. (8) and (9) in [Weirs12] which is referred in Dakota Technical manual [Adams20]), and the user has two options to generate the samples on which the statistics are created: Monte Carlo, and Latin Hypercube Sampling (LHS). For both, they are required, as shown in figure below, to specify the number of samples and a seed.

                    +

                    2.1.2.2. Global Sensitivity Analysis

                    +

                    Global sensitivity analysis is used to quantify the contribution of each input variable to the uncertainty in the output quantity of interest (QoI). In particular, by calculating the global sensitivity indices, users can set preferences between random variables considering both inherent randomness and its propagation through the model. Global sensitivity analysis helps users to understand the overall impact of different sources of uncertainties and their interactions, as well as to accelerate UQ computations by focusing on dominant dimensions or screening out trivial input variables. The sensitivity index can also be used to identify the input variables for which extra experimentation/research may be useful in reducing the uncertainty in the initial specification.

                    +

                    Sobol indices are widely used variance-based global sensitivity measures which have two types: main effect and total effect sensitivity indices. The main effect index quantifies the fraction of variance in QoI that can be attributed to specific input random variable(s) but without considering the interactive effect with other input variables. The total effect index, on the other hand, additionally takes the interactions into account. Please read HERE for more details on the equations.

                    +

                    Dakota Sensitivity Analysis is based on the efficient Monte Carlo method (See Eqs. (8) and (9) in [Weirs12] which is referenced in the Dakota Technical manual [Adams20]), and the user has two options to generate the samples on which the statistics are created: Monte Carlo, and Latin Hypercube Sampling (LHS). For both, they are required, as shown in the figure below, to specify the number of samples and a seed.

                    The results of the Sensitivity analysis will show both the main effect and total effect Sobol indices for each random variable (RV) for each of the quantity of interest (QoI).

                    ../../../../_images/DakotaSensitivityAnalysis.png @@ -249,7 +245,7 @@

                    When the associated FEM model is computationally expensive, the user should consider that the actual number of the simulation runs is larger than the number of samples specified in the input panel. The actual number of simulation runs are NS*(2+NRV)

                      -
                    • NS = number of samples specified by user

                    • +
                    • NS = number of samples specified by the user

                    • NRV = number of random variables

                    @@ -284,7 +280,7 @@

                    - © Copyright 2023, The Regents of the University of California. + © Copyright 2024, The Regents of the University of California.

                    diff --git a/docs/common/user_manual/usage/desktop/FEM.html b/docs/common/user_manual/usage/desktop/FEM.html index e2198e92..010195f4 100644 --- a/docs/common/user_manual/usage/desktop/FEM.html +++ b/docs/common/user_manual/usage/desktop/FEM.html @@ -40,6 +40,7 @@ + @@ -144,11 +145,6 @@
                  • 5. Requirements
                  • 6. Bugs & Feature Requests
                  -

                  Damage and Loss DB

                  -

                  Technical Manual

                  -

                  Damage and Loss DB

                  -

                  Technical Manual

                  • 1. Technical Manual
                  • @@ -210,7 +206,7 @@
                    -

                    Surrogate (GP)

                    +

                    Surrogate (GP)

                    In place of the physical simulation models, the Surrogate (Gaussian Process) model trained in EE-UQ can be imported.

                    ../../../../_images/Surrogate_EEUQ_FEM.png @@ -239,7 +235,7 @@

                    - © Copyright 2023, The Regents of the University of California. + © Copyright 2024, The Regents of the University of California.

                    diff --git a/docs/common/user_manual/usage/desktop/GI.html b/docs/common/user_manual/usage/desktop/GI.html index 298c05a6..d45cf4b7 100644 --- a/docs/common/user_manual/usage/desktop/GI.html +++ b/docs/common/user_manual/usage/desktop/GI.html @@ -40,6 +40,7 @@ + @@ -138,11 +139,6 @@
                  • 5. Requirements
                  • 6. Bugs & Feature Requests
                  -

                  Damage and Loss DB

                  -

                  Technical Manual

                  • 1. Technical Manual
                  • @@ -224,7 +220,7 @@
                    -

                    2.2. GI: General Information

                    +

                    2.2. GI: General Information

                    The GI tab allows the user to provide information about the building and the units the user will work with. The widget contains the following four frames, as shown in Fig. 2.2.1.

                    1. Building Information: Collects general information about the building. This includes the name of the building.

                    2. @@ -248,7 +244,7 @@

                      - © Copyright 2023, The Regents of the University of California. + © Copyright 2024, The Regents of the University of California.

                      diff --git a/docs/common/user_manual/usage/desktop/RV.html b/docs/common/user_manual/usage/desktop/RV.html index af6a3252..9c059625 100644 --- a/docs/common/user_manual/usage/desktop/RV.html +++ b/docs/common/user_manual/usage/desktop/RV.html @@ -40,6 +40,7 @@ + @@ -145,11 +146,6 @@
                    3. 5. Requirements
                    4. 6. Bugs & Feature Requests
                  -

                  Damage and Loss DB

                  -

                  Technical Manual

                  -

                  Damage and Loss DB

                  -

                  Technical Manual

                  • 1. Technical Manual
                  • @@ -234,7 +230,7 @@
                    -

                    2.3. SIM: Structural Model

                    +

                    2.3. SIM: Structural Model

                    The user here defines the structural system of the building. The structural system is the part of the building provided to resist the gravity loads and those loads arising from the natural hazard. There are a number of backend applications provided for this part of the workflow, each responsible for defining the structural analysis model. The user can select the application to use from the drop-down menu at the top of this panel. As the user switches between applications, the input panel changes to reflect the inputs each particular application requires. At present, there are two backend applications available.

                      @@ -247,7 +243,7 @@
                    -

                    2.3.1. Multiple Degrees of Freedom (MDOF)

                    +

                    2.3.1. Multiple Degrees of Freedom (MDOF)

                    This panel is provided for users to quickly create simple shear models of a building. The panel, as shown in Fig. 2.3.1.1 is divided into 3 frames:

                    1. The top left frame allows the user to specify the number of stories and properties that are constant for every floor and story in the building. The following properties are available: floor weight, story height, torsional stiffness, initial stiffness, yield strength, and hardening ratio for each direction in each story. The user has the option of specifying values for eccentricity of mass in \(x\) and \(y\) directions, and eccentricities for the location of the response quantities. Here, the one and two directions are orthogonal \(x\) and \(y\) axes in plan view.

                    2. @@ -265,7 +261,7 @@
                  -

                  2.3.2. OpenSees

                  +

                  2.3.2. OpenSees

                  This panel is for users who have an existing OpenSees model of a building that performs a gravity analysis and now they wish to subject that building model to one of the EVT options provided. The input panel for this option is shown in Fig. 2.3.2.1. Users need to provide three pieces of information:

                  1. Main OpenSees Script: The main script that contains the building model. This script should build a model and perform any gravity analysis of the building that is required before the event is applied.

                  2. @@ -280,7 +276,7 @@

                    In OpenSees there is an option to set variables to have certain values using the pset command, e.g pset a 5.0 will set the variable a to have a value 5 in the OpenSees script. In EE-UQ, any variable found in the main script to be set using the pset command will be assumed to be a random variable. As such, when a new main script is loaded all variables set with pset will appear as random variables in the UQ panel.

                  -

                  2.3.3. Steel Building Model (AutoSDA)

                  +

                  2.3.3. Steel Building Model (AutoSDA)

                  This module provides a way for a user to create a nonlinear structural model of a moment-resisting steel-framed building. The AutoSDA computer program [GBS20] is used for the seismic design and to generate the resulting two-dimensional structural model in OpenSees. AutoSDA automates the seismic design process and nonlinear structural model construction, generating code-conforming section sizes and detailing for beams, columns, and beam-column connections based on the user-specified input design parameters. The resulting nonlinear model is then subjected to the hazard option that is selected by the user in the EVT panel. The TCL files of the OpenSees model generated by AutoSDA are located in the individual work directories in the tmp.SimCenter folder that EE-UQ creates on the user’s computer.

                  The input panel for this module is shown in Fig. 2.3.3.1. Users need to provide the following information:

                    @@ -304,7 +300,7 @@

                    2.3.3.

                  -

                  2.3.4. Concrete Building Model (RC-FIAP)

                  +

                  2.3.4. Concrete Building Model (RC-FIAP)

                  This module provides a way for a user to create a nonlinear structural model of a reinforced concrete building. The RC-FIAP (Reinforced Concrete Frame Inelastic Analysis Platform) computer program generates a two-dimensional structural model that is employed in OpenSees. RC-FIAP automates the seismic design process and inelastic structural model construction based on user-provided input design parameters. The resulting nonlinear model is then subjected to the hazard option that is selected by the user in the EVT panel. The TCL files of the OpenSees model generated by RC-FIAP are located in the individual work directories in the tmp.SimCenter folder that EE-UQ creates on the user’s computer.

                  The input panel for this module is shown in Fig. 2.3.4.1. Users need to provide the following information:

                    @@ -324,7 +320,7 @@

                    2.3.4.

                  -

                  2.3.5. Surrogate (GP)

                  +

                  2.3.5. Surrogate (GP)

                  In place of the physical simulation models, the Surrogate (Gaussian Process) model trained in EE-UQ can be imported.

                  ../../../../_images/Surrogate_EEUQ_FEM.png @@ -343,7 +339,7 @@

                  2.3.4.

                  -

                  2.3.6. MDOF-LU Building Model

                  +

                  2.3.6. MDOF-LU Building Model

                  The MDOF-LU building modeling application creates a hysteretic, multi-degree of freedom (MDOF) model based on the Lu method. As seen in Fig. 2.3.6.1, the following inputs are required:

                    @@ -357,7 +353,7 @@

                    2.3.6.

                  -

                  2.3.7. Multiple Models

                  +

                  2.3.7. Multiple Models

                  The Multiple Models structural modeling application allows users to define multiple structural models for use in their analysis. The Add and Remove buttons allow users to control the number of models they want to use in the analysis.

                  By adding a model, a new tab is created in the SIM panel where users can choose one of the structural modeling applications described in the sections above and provide the inputs necessary to create the model. Users also need to specify their belief about the credibility of the model in the tab corresponding to that model. The beliefs are expressed as non-negative numerical values. The belief value for each model is defined relative to the other models, and the beliefs do not need to sum to 1.

                  diff --git a/docs/common/user_manual/usage/desktop/SimCenterUQ.html b/docs/common/user_manual/usage/desktop/SimCenterUQ.html index 35293423..448dba8b 100644 --- a/docs/common/user_manual/usage/desktop/SimCenterUQ.html +++ b/docs/common/user_manual/usage/desktop/SimCenterUQ.html @@ -40,6 +40,7 @@ + @@ -126,11 +127,6 @@
                • 5. Requirements
                • 6. Bugs & Feature Requests
                -

                Damage and Loss DB

                -

                Technical Manual

                -

                Damage and Loss DB

                -

                Technical Manual

                • 1. Technical Manual
                • @@ -211,7 +207,7 @@
                  -

                  Multi-fidelity Monte Carlo

                  +

                  Multi-fidelity Monte Carlo

                  SimCenter UQ supports a multi-fidelity Monte Carlo option, where the user can import both high-fidelity and low-fidelity simulation models to estimate the statistics of high-fidelity responses. See more information in the technical manual.

                  ../../../../_images/Sampling_MF1.png @@ -248,7 +244,7 @@

                  - © Copyright 2023, The Regents of the University of California. + © Copyright 2024, The Regents of the University of California.

                  diff --git a/docs/common/user_manual/usage/desktop/SimCenterUQPLoM.html b/docs/common/user_manual/usage/desktop/SimCenterUQPLoM.html index c863c26c..77607554 100644 --- a/docs/common/user_manual/usage/desktop/SimCenterUQPLoM.html +++ b/docs/common/user_manual/usage/desktop/SimCenterUQPLoM.html @@ -40,6 +40,7 @@ + @@ -49,7 +50,7 @@ - + @@ -148,11 +149,6 @@
                • 5. Requirements
                • 6. Bugs & Feature Requests
                -

                Damage and Loss DB

                -

                Technical Manual

                -

                Damage and Loss DB

                -

                Technical Manual

                -

                Damage and Loss DB

                -

                Technical Manual

                • 1. Technical Manual
                • @@ -237,11 +233,11 @@
                  -

                  2.1.3.2. Global Sensitivity Analysis

                  +

                  2.1.3.2. Global Sensitivity Analysis

                  Global sensitivity analysis is used to quantify the contribution of each input variable to the uncertainty in the quantities of interest (QoI). Using the global sensitivity indices, users can set preferences between random variables considering both inherent randomness and its propagation through the model. Global sensitivity analysis helps users to understand the overall impact of different sources of uncertainties and their intersections, as well as to accelerate UQ computations by focusing on dominant dimensions or screening out trivial input variables. This can also be useful in identifying the input variables for which extra experimentation/research may be useful in reducing the uncertainty in the initial specification.

                  Sobol indices are widely used variance-based global sensitivity measures which have two types: main effect and total effect sensitivity indices. The main effect index quantifies the fraction of variance in QoI that can be attributed to specific input random variable(s) but without considering the interaction effect with other input variables. The total effect index, on the other hand, additionally takes the interactions into account. Please read HERE for more details on the equations and implemented algorithms.

                  -

                  Algorithm

                  +

                  Algorithm

                  In the SimCenterUQ engine, sensitivity indices are estimated by Gaussian mixture model-based probability distribution approximation method presented in Hu and Mahadevan (2019) [Hu19]. To run this sensitivity analysis, the user has to specify the number of samples and a random seed. The method can handle correlated random variables as well.

                  Note

                  @@ -252,7 +248,7 @@

                  Algorithm -

                  Sample Generation

                  +

                  Sample Generation

                  Performing sensitivity analysis requires Monte Carlo Samples. This can be either generated by quoFEM or imported from separate data files.

                  -

                  Damage and Loss DB

                  -

                  Technical Manual

                  • 1. Technical Manual
                  • @@ -237,11 +233,34 @@
                    -

                    2.1.3.3. Gaussian Process (GP) Surrogate Modeling

                    +

                    2.1.3.3. Gaussian Process (GP) Surrogate Modeling

                    Note

                    Surrogate modeling functionality of EE-UQ is built upon GPy library (available under BSD 3-clause license), an opensource python framework for Gaussian process modeling developed in the Sheffield machine learning group.

                    +
                    +

                    Warning

                    +

                    Update: 01.04.2024

                    +

                    Only on Mac, the GPy module (v.1.12 or lower) has a dependency version compatibility issue with other python packages SimCenter uses. +To run GPy on SimCenter tools, one needs to install the latest developer release of GPy. Below is the error message you get.

                    +
                    Surrogate modeling module uses GPy python package which is facing a version compatibility issue at this moment (01.05.2024).
                    +To use the surrogate module, one needs to update manually the GPy version to 1.13. The instructions can be found in the documentation:
                    +https://nheri-simcenter.github.io/quoFEM-Documentation/common/user_manual/usage/desktop/SimCenterUQSurrogate.html#lblsimsurrogate
                    +
                    +
                    +

                    Until the GPy version v1.13 is available on pip, one can install the developer release of GPy v1.13 by typing the following commands one by one in the terminal

                    +
                    git clone https://github.com/SheffieldML/GPy.git
                    +cd GPy
                    +{$PathToPythonExe} -m pip uninstall GPy
                    +{$PathToPythonExe} setup.py install
                    +
                    +
                    +

                    where {$PathToPythonExe} should be replaced with the python path found in the File-Preference window. After the third line, they will ask for the confirmation (type Y and enter). Check the installation status by typing

                    +
                    {$PathToPythonExe} -m pip show GPy
                    +
                    +
                    +

                    and confirming that the version appears as 1.13.x. For any questions and bug reports, please contact us through user forum.

                    +

                    The Train GP Surrogate Model module is used to construct a Gaussian process (GP) based surrogate model that substitutes expensive computational simulation models. The challenge of surrogate modeling in earthquake engineering arrives from the stochasticity in the ground motion time history and corresponding stochastic output.

                    ../../../../_images/Surrogate_EEUQ1.png @@ -262,9 +281,9 @@
              -

              Input description

              +

              Input description

              -

              Case 1: Sampling and Simulation

              +

              Case 1: Sampling and Simulation

              Note

              Another SimCenter tool named quoFEM also supports surrogate modeling capability that shares the same algorithm with EE-UQ. However, quoFEM is targeted at more general applications not restricted to earthquake problems. quoFEM additionally supports different user-provided information types, allowing users to directly (i) Import RV Dataset and run the Simulation (Case 2), or (ii) Import both RV and EDP Dataset (Case 3). Currently, in EE-UQ, we only support the Sampling and simulation option (Case 1).

              @@ -321,7 +340,7 @@

              Case 1: Sampling and Simulation -

              RV (Random Variables) Tab

              +

              RV (Random Variables) Tab

              The bounds of RVs need to cover the domain of interest in future applications, while it should not be unnecessarily stretched. Input type and Distribution should be set to Parameters and Uniform. When a dataset is provided, make sure to match the order of RVs in the RV tab to the order of data columns. Any correlation values will be ignored.

              ../../../../_images/Surrogate7_SimUQ.jpg @@ -330,9 +349,9 @@

              RV (Random Variables) Tab -

              Output description

              +

              Output description

              -

              Goodness-of-Fit

              +

              Goodness-of-Fit

              Once the training is completed, the following three verification measures are presented based on leave-one-out cross-validation (LOOCV) error estimation.

              diff --git a/docs/common/user_manual/usage/desktop/UCSD_UQ_Hierarchical.html b/docs/common/user_manual/usage/desktop/UCSD_UQ_Hierarchical.html new file mode 100644 index 00000000..ea934298 --- /dev/null +++ b/docs/common/user_manual/usage/desktop/UCSD_UQ_Hierarchical.html @@ -0,0 +1,345 @@ + + + + + + + + + + 2.1.4.2. Calibration of Hierarchical Model — Earthquake Engineering with Uncertainty Quantification documentation + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + +
              + + + +
              + + + + + +
              + +
              + + + + + + + + + + + + + + + + + + + +
              + + + + +
              +
              +
              +
              + +
              +

              2.1.4.2. Calibration of Hierarchical Model

              +
              +

              Introduction

              +

              Bayesian calibration of a hierarchical model is performed using the Adaptive Metropolis-within-Gibbs sampling algorithm in quoFEM. Adaptive Metropolis-within-Gibbs is an advanced Markov chain Monte Carlo (MCMC) method that is designed to efficiently sample from complex, high-dimensional distributions, especially when direct sampling of these distributions is impractical.

              +

              The sampler is initialized with a set of reasonable values for the variables (i.e., parameters of the hierarchical model). The hierarchical model that is used in the UCSD_UQ engine (refer the Technical Manual for more details) results in a structure where the variables can be grouped into blocks. For example, the parameters of the computational model for each dataset have strong interactions/dependencies among themselves, while they are independent of the parameters of the model for other datasets or the hyperparameters or the prediction error variances that are also part of the variables calibrated in the hierarchical model. After the variables have been grouped into blocks, Gibbs sampling involves updating the variables within each block sequentially, conditioned on the current values of variables in other blocks, and generating a sample from the updated distribution. For all the blocks where it is not possible to directly generate a sample from the updated distribution, adaptive Metropolis steps are used. In this step, a new state is proposed for all the variables within the block based on the current values using an adaptive proposal distribution. The acceptance probability for the proposed state is computed using the Metropolis-Hastings criterion and the proposed state is accepted or rejected based on this probability. The proposal distributions are adapted based on the accept/reject decisions made during the previous adaptive Metropolis steps. The adaptation is performed to improve the efficiency of the sampling process by adjusting the proposal distributions to better match the target distribution. This process is repeated for a large number of iterations, after which the sampler generates values from the updated distributions of the parameters of the hierarchical model.

              +
              +
              +

              Usage

              +

              To use the Adaptive Metropolis-within-Gibbs algorithm, select the UCSD-UQ engine in the UQ panel and select the Hierarchical Model.

              +

              The required inputs to perform Bayesian calibration of a hierarchical model in quoFEM are Sample Size, Random State, Calibration Data File Name, and Calibration Datasets Directory.

              +

              The optional inputs are Restart File Name, Adaptation Duration, and Adaptation Frequency. Figure Fig. 2.1.4.2.1 shows the input panel that is presented when the Hierarchical model is selected. Each of the options on this panel will be explained next.

              +
              +../../../../_images/UCSD_Hierarchical.png +

              Fig. 2.1.4.2.1 Input panel for Bayesian calibration of a hierarchical model.

              +
              +
                +
              1. Sample Size defines the number of values to be sampled from the posterior probability distribution of the parameters of the computational model.

              2. +
              3. Random State is an integer that is used to specify the seed value of the pseudorandom number generator used in the Bayesian updating algorithm. Setting the same seed as in a previous analysis ensures that the same result is reproduced if the analysis is run again with the same inputs used in the previous analysis.

              4. +
              5. Restart File Name is the name of a JSON file containing the results from a previous Bayesian calibration of the same hierarchical model using quoFEM. The restart option allows users to resume the MCMC sampling from a previously obtained sample value.

              6. +
              7. Adaptation Duration is an integer that specifies the initial number of steps of the sampler during which the characteristics of the proposal distribution are adjusted to increase the efficiency of the sampling.

              8. +
              9. Adaptation Frequency is an integer that defines the number of steps within the adaptation duration after which the proposal distribution is adapted.

              10. +
              11. Calibration Data File Name is the name of a text file that contains the data of the measured values of the output quantity of interest.

              12. +
              13. Calibration Datasets Directory is the path to the directory that contains the datasets from multiple measurements.

              14. +
              +
              +
              + + +
              + +
              +
              + +
              + +
              +

              + © Copyright 2024, The Regents of the University of California. + +

              +
              + + + + Built with Sphinx using a + + theme + + provided by Read the Docs. + +
              +
              +
              + +
              + +
              + + + + + + + + + + + + + + + + + + + + \ No newline at end of file diff --git a/docs/common/user_manual/usage/desktop/UCSD_UQ_TMCMC.html b/docs/common/user_manual/usage/desktop/UCSD_UQ_TMCMC.html index 4c8bb46e..50b14057 100644 --- a/docs/common/user_manual/usage/desktop/UCSD_UQ_TMCMC.html +++ b/docs/common/user_manual/usage/desktop/UCSD_UQ_TMCMC.html @@ -7,7 +7,7 @@ - 2.1.4.1. Transitional Markov chain Monte Carlo (TMCMC) algorithm — Earthquake Engineering with Uncertainty Quantification documentation + 2.1.4.1. Calibration of Non-hierarchical Model — Earthquake Engineering with Uncertainty Quantification documentation @@ -40,6 +40,7 @@ + @@ -50,7 +51,7 @@ - + @@ -129,11 +130,6 @@
            • 5. Requirements
            • 6. Bugs & Feature Requests
            -

            Damage and Loss DB

            -

            Technical Manual

            • 1. Technical Manual
            • @@ -197,7 +193,7 @@
            • 2.1. UQ: Uncertainty Quantification »
            • -
            • 2.1.4.1. Transitional Markov chain Monte Carlo (TMCMC) algorithm
            • +
            • 2.1.4.1. Calibration of Non-hierarchical Model
            • @@ -216,23 +212,24 @@
              -
              -

              2.1.4.1. Transitional Markov chain Monte Carlo (TMCMC) algorithm

              +
              +

              2.1.4.1. Calibration of Non-hierarchical Model

              -

              Introduction

              -

              TMCMC is an algorithm which is used to draw samples from the posterior probability distribution of random variables when performing Bayesian estimation. Bayesian estimation is a probabilistic inverse problem where the objective is to estimate the probability distribution of the parameters of a computational model, given data. The data consist of numbers which are typically obtained from measurements of a physical phenomenon being studied. In quoFEM, the data are provided in a text file, whose path is defined in the UQ panel. The computational model (defined in the FEM panel) is an approximation of the real process that generated the data and the outputs of this model (defined in the QoI panel) are the same quantities of interest for which we have measured data. The model has several parameters that influence the output predicted by the model when it is evaluated at a set of inputs. In the inverse problem, the values of these parameters are unknown, and in the Bayesian setting, they are treated as random variables, with specified prior probability distribution functions (defined in the RV panel). To complete the definition of the Bayesian inverse problem, the probability model for the data needs to be specified, which is done by the log-likelihood function in the UQ panel.

              +

              Introduction

              +

              Bayesian calibration of a non-hierarchical model is a probabilistic inverse problem where the objective is to estimate the probability distribution of the parameters of a computational model, using all the available data. The data consist of numbers which are typically obtained from measurements of a physical phenomenon being studied. In quoFEM, the data are provided in a text file, whose path is defined in the UQ panel. The computational model (defined in the FEM panel) is an approximation of the real process that generated the data and the outputs of this model (defined in the QoI panel) are the same quantities of interest for which we have measured data. The model has several parameters that influence the output predicted by the model when it is evaluated at a set of inputs. In the inverse problem, the values of these parameters are unknown, and in the Bayesian setting, they are treated as random variables, with specified prior probability distribution functions (defined in the RV panel). To complete the definition of the Bayesian inverse problem, the probability model for the data needs to be specified, which is done by the log-likelihood function in the UQ panel.

              -

              Usage

              +

              Usage

              +

              Transitional Markov chain Monte Carlo (TMCMC) is an algorithm that is used to draw samples from the posterior probability distribution of the parameters of a computational model when performing Bayesian calibration using a non-hierarchical model.

              To use the TMCMC algorithm, select the UCSD-UQ engine in the UQ panel. Currently, only the TMCMC method is available with the UCSD-UQ engine.

              The required inputs to perform Bayesian calibration in quoFEM using the TMCMC algorithm are # Samples, Seed, and Calibration Data File. Specifying Log Likelihood Script is optional. Figure Fig. 2.1.4.1.1 shows the input panel that is presented when the TMCMC method is selected. Each of the options on this panel will be explained next.

              -../../../../_images/UCSD_UQ_Engine.png +../../../../_images/UCSD_Non-hierarchical.png

              Fig. 2.1.4.1.1 TMCMC algorithm input panel.

                -
              1. # Samples defines the number of values to be sampled from the posterior probability distribution of the parameters of the computational model. This number is not the same as the number of times the computational model is evaluated. In order to sample from the posterior probability distribution of the inputs, the TMCMC algorithm relies on gradually changing the target distribution from the prior to posterior in a number of stages. The number of stages is not known apriori. In every stage, the Markov chain is propagated for a number of steps (which varies betwen 2-5) for each sample, which requires the computational model to be evaluated. So, if # Samples is set to a number denoted as \(N_{samples}\), the total number of times that the computational model is evaluated is given by \(N_{eval} = \sum_{i=1}^{N_{stages}} N_{samples}*N_{steps}^{(i)}\).

              2. -
              3. Seed is an integer that specifies the seed value of the psuedo-random number generator. If the same Bayesian estimation problem is run multiple times without having the same seed, a different set of samples produced in each run. Setting the same seed as a previous TMCMC sampling run ensures that the the same result is reproduced if the TMCMC sampling is run again.

              4. +
              5. # Samples defines the number of values to be sampled from the posterior probability distribution of the parameters of the computational model. This number is not the same as the number of times the computational model is evaluated. To sample from the posterior probability distribution of the inputs, the TMCMC algorithm relies on gradually changing the target distribution from the prior to the posterior in several stages. The number of stages is not known in advance. In every stage, the Markov chain is propagated for several steps (which vary between 2-5) for each sample, which requires the computational model to be evaluated. So, if # Samples is set to a number denoted as \(N_{samples}\), the total number of times that the computational model is evaluated is given by \(N_{eval} = \sum_{i=1}^{N_{stages}} N_{samples}*N_{steps}^{(i)}\).

              6. +
              7. Seed is an integer that specifies the seed value of the pseudorandom number generator. If the same Bayesian estimation problem is run multiple times without having the same seed, a different set of samples is produced in each run. Setting the same seed as a previous TMCMC sampling run ensures that the same result is reproduced if the TMCMC sampling is run again.

              8. Calibration Data File is the path to a text file that contains the data of the measured values of the quantities of interest.

              @@ -250,14 +247,14 @@

              Usage

              -

              Defining the log-likelihood function

              +

              Defining the log-likelihood function

              Warning

              -

              This feature is meant for advanced users, and users must exercise care if defining their own log-likelihood function.

              +

              This feature is meant for advanced users, and users must exercise care if defining their log-likelihood function.

              -

              In the Log Likelihood Script field, users can provide the path to a Python script which contains a function called log_likelihood that returns the log-likelihood value.

              +

              In the Log Likelihood Script field, users can provide the path to a Python script that contains a function called log_likelihood that returns the log-likelihood value.

              By allowing users to define a log_likelihood function in the Log Likelihood Script, the workflow provides users full control in defining the log-likelihood model they desire to use. -The log_likelihood function is called internally during the execution of the TMCMC algorithm, and this function must compute and return the log-likelihood value at a point in the parameter space. The function must take the arguments as shown below in signature of the default log-likelihood script. Within this function, users can define their own log-likelihood function.

              +The log_likelihood function is called internally during the execution of the TMCMC algorithm, and this function must compute and return the log-likelihood value at a point in the parameter space. The function must take the arguments as shown below in the signature of the default log-likelihood script. Within this function, users can define their log-likelihood function.

               1def log_likelihood(calibrationData, prediction, parameters, numExperiments, covarianceMatrixList, edpNamesList,
                2                   edpLengthsList, covarianceMultiplierList, scaleFactors, shiftFactors):
                3    """ Compute the log-likelihood
              @@ -307,16 +304,16 @@ 

              Defining the log-likelihood function -

              Default error covariance structure

              +

              Default error covariance structure

              The likelihood is a function of the difference between the predicted and the measured values of the response quantities of interest. These differences are also called residuals or errors. The likelihood function assumes a structure of the covariance matrix for these error terms.

              -

              By default, quoFEM assumes a block-diagonal error covariance structure. An example of the block-diagonal covariance structure is shown in Fig. 2.1.4.1.2. In this figure, the number of experiments is denoted as \(N_{exp}\). The number of response quantities of interest is denoted as \(N_{q}\), and \(q_1, q_2, ..., q5\) are the names of the quantities of interest in this example (these will be defined in the QoI panel when using quoFEM). Of these, \(q_1\) and \(q_2\) are scalar response quantities (i.e., they have a length of 1), while \(q_3\), \(q_4\), and \(q_5\) are response quantities whose length > 1 (referred to as vector/field quantities). The length of each of the \(N_q\) quantities of interest is denoted by \(l_i\). So, \(N\), the total number of calibration data terms, which is the same as the total number of terms in the results.out file output from the model, and is also equal to the total number of error/residual terms, is given by:

              +

              By default, quoFEM assumes a block-diagonal error covariance structure. An example of the block-diagonal covariance structure is shown in Fig. 2.1.4.1.2. In this figure, the number of experiments is denoted as \(N_{exp}\). The number of response quantities of interest is denoted as \(N_{q}\), and \(q_1, q_2, ..., q5\) are the names of the quantities of interest in this example (these will be defined in the QoI panel when using quoFEM). Of these, \(q_1\) and \(q_2\) are scalar response quantities (i.e., they have a length of 1), while \(q_3\) ,:math:q_4, and \(q_5\) are response quantities whose length > 1 (referred to as vector/field quantities). The length of each of the \(N_q\) quantities of interest is denoted by \(l_i\). So, \(N\), the total number of calibration data terms, which is the same as the total number of terms in the results.out file output from the model, and is also equal to the total number of error/residual terms, is given by:

              (2.1.4.1.1)\[N = N_{exp} \times \sum_{i=1}^{N_q} l_i\]

              Note that quoFEM requires that the calibration data be provided in a text file separate from the script where the model is defined. In this text file, the number of rows corresponds to the number of experiment \(N_{exp}\), and the number of terms in each row (i.e., the number of columns) is equal to \(\sum_{i=1}^{N_q} l_i\). Hence, the total number of calibration terms \(N\) is equal to the product of the number of rows and number of columns in the calibration data file.

              The error-covariance matrix is a block-diagonal square matrix of size \(N \times N\). There are \(N_{exp} \times N_q\) blocks on the diagonal. For each of these blocks, if it corresponds to a scalar response quantity, then a scalar variance value is used by default else, a scalar matrix (i.e., an identity matrix of size \(l_i \times l_i\) multiplied by a scalar value) is used by default.

              Note

              -

              For numerical convenience, during execution, a transformation is applied to the calibration data and model prediction corresponding to each response quantity. The calibration data and model prediction for each response quantity are first shifted (a scalar value is added to the data and prediction) and then scaled (the data and prediction is divided by a positive scalar value).

              +

              For numerical convenience, during execution, a transformation is applied to the calibration data and model prediction corresponding to each response quantity. The calibration data and model prediction for each response quantity are first shifted (a scalar value is added to the data and prediction) and then scaled (the data and prediction are divided by a positive scalar value).

              Currently, the shift factors are set to 0.0 for all response quantities by default. The scale factors used are the absolute maximum of the data for each response variable. If the absolute maximum of the data for any response variable is 0.0, then the scale factor is set to 1.0, and the shift factor is set to 1.0.

              If there is data from more than one experiment, the default variance value used per response quantity, which is constant across experiments, is computed as the variance of the transformed calibration data. If there is data from only one experiment, then a default variance value is computed by assuming that the standard deviation of the error is 5% of the absolute maximum value of the corresponding transformed calibration data.

              @@ -328,11 +325,11 @@

              Default error covariance structure -

              User-defined covariance structure

              -

              quoFEM provides users the option to supply error covariance matrices per response quantity per experiment, i.e., users can define each block of the diagonal error-covariance structure which will be utilized in the calculation of the log-likelihood. To do so, users must provide a separate text file for each block containing the values for that block. The names of these text files are expected to follow the convention of “{QoIName}.{ExpNum}.sigma”. Examples of the names of the files that contain values which will be used instead of the default values are shown for each block in Fig. 2.1.4.1.3.

              +

              User-defined covariance structure

              +

              quoFEM provides users the option to supply error covariance matrices per response quantity per experiment, i.e., users can define each block of the diagonal error-covariance structure which will be utilized in the calculation of the log-likelihood. To do so, users must provide a separate text file for each block containing the values for that block. The names of these text files are expected to follow the convention of “{QoIName}.{ExpNum}.sigma”. Examples of the names of the files that contain values that will be used instead of the default values are shown for each block in Fig. 2.1.4.1.3.

              Within these files, the entries can be separated by either commas, spaces, or tabs. Users can provide a scalar variance value for scalar response quantities, which will be used instead of the default value. For vector/field response quantities, users can supply in the files either

                -
              1. a scalar value, in which case the block corresponding to this response variable and this experiment will be an identity matrix of size \(l_i \times l_i\) multipled by this scalar value, or

              2. +
              3. a scalar value, in which case the block corresponding to this response variable and this experiment will be an identity matrix of size \(l_i \times l_i\) multiplied by this scalar value, or

              4. a row/column of \(l_i\) values, in which case, these will be treated as the elements of the diagonal of the block, or

              5. a matrix of values of size \(l_i \times l_i\), which implies that the error/residual terms corresponding to this block are correlated.

              @@ -342,8 +339,8 @@

              User-defined covariance structure -

              Additional calibration parameters

              -

              In Bayesian calibration problems, the value of the variance/covariances of the error/residual terms is also typically unknown. The residuals include not only measurement errors, but also errors caused due to the inability of the model to prefectly represent the behavior being modeled. Hence, by default, quoFEM also calibrates the values of multipliers on the block-diagonal terms in the error covariance matrix. Therefore, the total number of parameters being calibrated is given by the sum of the number of parameters of the computational model and the number of response quantities of interest.

              +

              Additional calibration parameters

              +

              In Bayesian calibration problems, the value of the variance/covariances of the error/residual terms is also typically unknown. The residuals include not only measurement errors but also errors caused due to the inability of the model to perfectly represent the behavior being modeled. Hence, by default, quoFEM also calibrates the values of multipliers on the block-diagonal terms in the error covariance matrix. Therefore, the total number of parameters being calibrated is given by the sum of the number of parameters of the computational model and the number of response quantities of interest.

              In quoFEM, the parameters of the model are defined in the RV panel, and the response quantities are specified in the QoI panel. Hence the total number of parameters being calibrated is equal to the sum of the number of RVs and the number of QoIs. There is one multiplier per response quantity, irrespective of it being either a scalar or a vector/field quantity. Also, the same multiplier per response quantity is used on the blocks of the error covariance matrix across experiments.

              @@ -358,7 +355,7 @@

              Additional calibration parameters

              - © Copyright 2023, The Regents of the University of California. + © Copyright 2024, The Regents of the University of California.

              diff --git a/docs/common/user_manual/usage/desktop/UQ.html b/docs/common/user_manual/usage/desktop/UQ.html index 2616681a..d70a7a41 100644 --- a/docs/common/user_manual/usage/desktop/UQ.html +++ b/docs/common/user_manual/usage/desktop/UQ.html @@ -40,6 +40,7 @@ + @@ -153,11 +154,6 @@
            • 5. Requirements
            • 6. Bugs & Feature Requests
            -

            Damage and Loss DB

            -

            Technical Manual

            • 1. Technical Manual
            • @@ -239,11 +235,11 @@
              -

              2.1. UQ: Uncertainty Quantification

              +

              2.1. UQ: Uncertainty Quantification

              The first selection panel the user must select from and enter data into is the UQ tab. It is in this panel that the user selects the UQ Engine to use for performing the uncertainty quantification calculations. The UQ Engine provides algorithms for solving various types of uncertainty analysis and optimization problems.

              The UQ Engine options currently available are Dakota and SimCenterUQ

              -

              2.1.2. Dakota UQ Engine

              +

              2.1.2. Dakota UQ Engine

              This UQ engine utilizes the Dakota Software, a state-of-the-art research application that is robust and provides many methods for optimization and UQ, a selection of which we utilize in this application. Dakota provides the user with a large number of methods for different kinds of analyses. For this reason, we have divided the methods into categories through a pull-down menu, as shown below. Once the category has been selected, a number of different methods are made available to the user.

              -

              Damage and Loss DB

              -

              Technical Manual

              • 1. Technical Manual
              • @@ -232,7 +228,7 @@
                -

                2.4. EVT: Earthquake Events

                +

                2.4. EVT: Earthquake Events

                The event panel presents the user with a drop-down menu with a list of available event applications. Event applications are applications that, given the building and user supplied data inputs, will generate @@ -259,7 +255,7 @@

                - © Copyright 2023, The Regents of the University of California. + © Copyright 2024, The Regents of the University of California.

                diff --git a/docs/common/user_manual/usage/desktop/earthquake/multipleExisting.html b/docs/common/user_manual/usage/desktop/earthquake/multipleExisting.html index 31ab0997..861ff31c 100644 --- a/docs/common/user_manual/usage/desktop/earthquake/multipleExisting.html +++ b/docs/common/user_manual/usage/desktop/earthquake/multipleExisting.html @@ -40,6 +40,7 @@ + @@ -146,11 +147,6 @@
              • 5. Requirements
              • 6. Bugs & Feature Requests
              -

              Damage and Loss DB

              -

              Technical Manual

              -

              Damage and Loss DB

              -

              Technical Manual

              -

              Damage and Loss DB

              -

              Technical Manual

              -

              Damage and Loss DB

              -

              Technical Manual

              -

              Damage and Loss DB

              -

              Technical Manual

              -

              Damage and Loss DB

              -

              Technical Manual

              -

              Damage and Loss DB

              -

              Technical Manual

              -

              Damage and Loss DB

              -

              Technical Manual

              -

              Damage and Loss DB

              -

              Technical Manual

              • 1. Technical Manual
              • @@ -224,7 +220,7 @@
                -

                2.8. RES: Results

                +

                2.8. RES: Results

                A successful run or download of a job that ran successfully at DesignSafe will result in 2 tabbed widgets being displayed in the results panel. The first tab, as shown in Fig. 2.8.1 shows the summary statistics: mean, stdDev, and kurtosis.

                ../../../../../_images/resultsSummary.png @@ -256,7 +252,7 @@

                - © Copyright 2023, The Regents of the University of California. + © Copyright 2024, The Regents of the University of California.

                diff --git a/docs/common/user_manual/usage/desktop/usage.html b/docs/common/user_manual/usage/desktop/usage.html index 579c95d4..65357fe1 100644 --- a/docs/common/user_manual/usage/desktop/usage.html +++ b/docs/common/user_manual/usage/desktop/usage.html @@ -40,6 +40,7 @@ + @@ -138,11 +139,6 @@
              • 5. Requirements
              • 6. Bugs & Feature Requests
              -

              Damage and Loss DB

              -

              Technical Manual

              • 1. Technical Manual
              • @@ -222,7 +218,7 @@
                -

                2. User Interface

                +

                2. User Interface

                The EE-UQ app is a scientific workflow application that creates workflows and runs them in the background. These workflows can involve multiple different workflow applications (see more information the backend and workflows under Software Architecture). Once the EE-UQ app is started, the user is presented with the user interface (UI) shown in Fig. 2.3. This interface allows the user to select the applications to run in a workflow, input the controlling parameters for each of these applications, start the workflow either locally or remotely, and finally view the results of the simulation.

                @@ -302,7 +298,7 @@

                - © Copyright 2023, The Regents of the University of California. + © Copyright 2024, The Regents of the University of California.

                diff --git a/docs/common/user_manual/user_inputs_documentation/User_Input_Documentation_Tables.html b/docs/common/user_manual/user_inputs_documentation/User_Input_Documentation_Tables.html new file mode 100644 index 00000000..b26198f8 --- /dev/null +++ b/docs/common/user_manual/user_inputs_documentation/User_Input_Documentation_Tables.html @@ -0,0 +1,376 @@ + + + + + + + + + + User Inputs — Earthquake Engineering with Uncertainty Quantification documentation + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + +
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                + + + + Built with Sphinx using a + + theme + + provided by Read the Docs. + +
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                + + + + + + + + + + + + + + + + + + + + \ No newline at end of file diff --git a/docs/common/user_manual/user_inputs_documentation/User_Inputs_Documentation_RST_Files/ConcreteBuildingModel.html b/docs/common/user_manual/user_inputs_documentation/User_Inputs_Documentation_RST_Files/ConcreteBuildingModel.html new file mode 100644 index 00000000..eaef2ca0 --- /dev/null +++ b/docs/common/user_manual/user_inputs_documentation/User_Inputs_Documentation_RST_Files/ConcreteBuildingModel.html @@ -0,0 +1,315 @@ + + + + + + + + + + ConcreteBuildingModel — Earthquake Engineering with Uncertainty Quantification documentation + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + +
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                + © Copyright 2024, The Regents of the University of California. + +

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                + © Copyright 2024, The Regents of the University of California. + +

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                + © Copyright 2024, The Regents of the University of California. + +

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                +
                +
                +
                + +
                +

                DakotaInputSensitivity

                +
                + + +
                + +
                +
                + +
                + +
                +

                + © Copyright 2024, The Regents of the University of California. + +

                +
                + + + + Built with Sphinx using a + + theme + + provided by Read the Docs. + +
                +
                +
                + +
                + +
                + + + + + + + + + + + + + + + + + + + + \ No newline at end of file diff --git a/docs/common/user_manual/user_inputs_documentation/User_Inputs_Documentation_RST_Files/EDP.html b/docs/common/user_manual/user_inputs_documentation/User_Inputs_Documentation_RST_Files/EDP.html new file mode 100644 index 00000000..432659e0 --- /dev/null +++ b/docs/common/user_manual/user_inputs_documentation/User_Inputs_Documentation_RST_Files/EDP.html @@ -0,0 +1,315 @@ + + + + + + + + + + EDP — Earthquake Engineering with Uncertainty Quantification documentation + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + +
                + + + +
                + + + + + +
                + +
                + + + + + + + + + + + + + + + + + + + +
                + + + + +
                +
                +
                +
                + +
                +

                EDP

                +
                + + +
                + +
                +
                + +
                + +
                +

                + © Copyright 2024, The Regents of the University of California. + +

                +
                + + + + Built with Sphinx using a + + theme + + provided by Read the Docs. + +
                +
                +
                + +
                + +
                + + + + + + + + + + + + + + + + + + + + \ No newline at end of file diff --git a/docs/common/user_manual/user_inputs_documentation/User_Inputs_Documentation_RST_Files/EDP_EarthquakeSelection.html b/docs/common/user_manual/user_inputs_documentation/User_Inputs_Documentation_RST_Files/EDP_EarthquakeSelection.html new file mode 100644 index 00000000..1d6e9de5 --- /dev/null +++ b/docs/common/user_manual/user_inputs_documentation/User_Inputs_Documentation_RST_Files/EDP_EarthquakeSelection.html @@ -0,0 +1,315 @@ + + + + + + + + + + EDP_EarthquakeSelection — Earthquake Engineering with Uncertainty Quantification documentation + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + +
                + + + +
                + + + + + +
                + +
                + + + + + + + + + + + + + + + + + + + +
                + + + + +
                +
                +
                +
                + +
                +

                EDP_EarthquakeSelection

                +
                + + +
                + +
                +
                + +
                + +
                +

                + © Copyright 2024, The Regents of the University of California. + +

                +
                + + + + Built with Sphinx using a + + theme + + provided by Read the Docs. + +
                +
                +
                + +
                + +
                + + + + + + + + + + + + + + + + + + + + \ No newline at end of file diff --git a/docs/common/user_manual/user_inputs_documentation/User_Inputs_Documentation_RST_Files/ExampleWidget.html b/docs/common/user_manual/user_inputs_documentation/User_Inputs_Documentation_RST_Files/ExampleWidget.html new file mode 100644 index 00000000..711989d6 --- /dev/null +++ b/docs/common/user_manual/user_inputs_documentation/User_Inputs_Documentation_RST_Files/ExampleWidget.html @@ -0,0 +1,378 @@ + + + + + + + + + + ExampleWidget — Earthquake Engineering with Uncertainty Quantification documentation + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + +
                + + + +
                + + + + + +
                + +
                + + + + + + + + + + + + + + + + + + + +
                + + + + +
                +
                +
                +
                + +
                +

                ExampleWidget

                +
                +
                Compound Widget

                Follow the link for a description of the inputs to Compound Widget

                +

                Key in JSON file: compound_widget

                +
                +

                See also

                +
                +
                Compound Widget

                User inputs for Compound Widget

                +
                +
                +
                +
                +
                +
                +
                Sample Size

                Number of samples from the posterior probability distribution

                +

                Default: 2000

                +

                Key in JSON file: sample_size

                +
                +
                +
                +
                Seed

                State of pseudo-random number generator for reproducibility

                +

                Key in JSON file: seed

                +
                +

                See also

                +
                +
                seed

                Compare with this parameter too

                +
                +
                +
                +
                +
                +
                +
                Calibration Data File

                Full path to the file containing the calibration data

                +

                Key in JSON file: calibration_data_file

                +
                +
                +
                +
                Log Likelihood Script

                Full path to the file containing the log-likelihood function

                +

                Default: probability density of multivariate normal with independent components

                +

                Key in JSON file: log_likelihood_script

                +
                +

                See also

                +
                +
                log_likelihood_script

                This is also relevant to this parameter and adds some context

                +
                +
                +
                +
                +
                +
                +
                Dummy Variable

                This is a dummy variable

                +

                Default: check_default

                +

                Key in JSON file: dummy

                +
                +
                +
                +

                See also

                +
                +
                Defining the log-likelihood function

                Can link to external webpages too

                +
                +
                Calibration data file

                Look at the requirements of how to define the calibration data file

                +
                +
                +
                +
                + + +
                + +
                +
                + +
                + +
                +

                + © Copyright 2024, The Regents of the University of California. + +

                +
                + + + + Built with Sphinx using a + + theme + + provided by Read the Docs. + +
                +
                +
                + +
                + +
                + + + + + + + + + + + + + + + + + + + + \ No newline at end of file diff --git a/docs/common/user_manual/user_inputs_documentation/User_Inputs_Documentation_RST_Files/ExistingSimCenterEvents.html b/docs/common/user_manual/user_inputs_documentation/User_Inputs_Documentation_RST_Files/ExistingSimCenterEvents.html new file mode 100644 index 00000000..dc508cc2 --- /dev/null +++ b/docs/common/user_manual/user_inputs_documentation/User_Inputs_Documentation_RST_Files/ExistingSimCenterEvents.html @@ -0,0 +1,315 @@ + + + + + + + + + + ExistingSimCenterEvents — Earthquake Engineering with Uncertainty Quantification documentation + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + +
                + + + +
                + + + + + +
                + +
                + + + + + + + + + + + + + + + + + + + +
                + + + + +
                +
                +
                +
                + +
                +

                ExistingSimCenterEvents

                +
                + + +
                + +
                +
                + +
                + +
                +

                + © Copyright 2024, The Regents of the University of California. + +

                +
                + + + + Built with Sphinx using a + + theme + + provided by Read the Docs. + +
                +
                +
                + +
                + +
                + + + + + + + + + + + + + + + + + + + + \ No newline at end of file diff --git a/docs/common/user_manual/user_inputs_documentation/User_Inputs_Documentation_RST_Files/GaussianProcessInputWidget.html b/docs/common/user_manual/user_inputs_documentation/User_Inputs_Documentation_RST_Files/GaussianProcessInputWidget.html new file mode 100644 index 00000000..e21e2715 --- /dev/null +++ b/docs/common/user_manual/user_inputs_documentation/User_Inputs_Documentation_RST_Files/GaussianProcessInputWidget.html @@ -0,0 +1,315 @@ + + + + + + + + + + GaussianProcessInputWidget — Earthquake Engineering with Uncertainty Quantification documentation + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + +
                + + + +
                + + + + + +
                + +
                + + + + + + + + + + + + + + + + + + + +
                + + + + +
                +
                +
                +
                + +
                +

                GaussianProcessInputWidget

                +
                + + +
                + +
                +
                + +
                + +
                +

                + © Copyright 2024, The Regents of the University of California. + +

                +
                + + + + Built with Sphinx using a + + theme + + provided by Read the Docs. + +
                +
                +
                + +
                + +
                + + + + + + + + + + + + + + + + + + + + \ No newline at end of file diff --git a/docs/common/user_manual/user_inputs_documentation/User_Inputs_Documentation_RST_Files/GlobalReliabilityWidget.html b/docs/common/user_manual/user_inputs_documentation/User_Inputs_Documentation_RST_Files/GlobalReliabilityWidget.html new file mode 100644 index 00000000..30898568 --- /dev/null +++ b/docs/common/user_manual/user_inputs_documentation/User_Inputs_Documentation_RST_Files/GlobalReliabilityWidget.html @@ -0,0 +1,315 @@ + + + + + + + + + + GlobalReliabilityWidget — Earthquake Engineering with Uncertainty Quantification documentation + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + +
                + + + +
                + + + + + +
                + +
                + + + + + + + + + + + + + + + + + + + +
                + + + + +
                +
                +
                +
                + +
                +

                GlobalReliabilityWidget

                +
                + + +
                + +
                +
                + +
                + +
                +

                + © Copyright 2024, The Regents of the University of California. + +

                +
                + + + + Built with Sphinx using a + + theme + + provided by Read the Docs. + +
                +
                +
                + +
                + +
                + + + + + + + + + + + + + + + + + + + + \ No newline at end of file diff --git a/docs/common/user_manual/user_inputs_documentation/User_Inputs_Documentation_RST_Files/ImportSamplesWidget.html b/docs/common/user_manual/user_inputs_documentation/User_Inputs_Documentation_RST_Files/ImportSamplesWidget.html new file mode 100644 index 00000000..31d18895 --- /dev/null +++ b/docs/common/user_manual/user_inputs_documentation/User_Inputs_Documentation_RST_Files/ImportSamplesWidget.html @@ -0,0 +1,315 @@ + + + + + + + + + + ImportSamplesWidget — Earthquake Engineering with Uncertainty Quantification documentation + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + +
                + + + +
                + + + + + +
                + +
                + + + + + + + + + + + + + + + + + + + +
                + + + + +
                +
                +
                +
                + +
                +

                ImportSamplesWidget

                +
                + + +
                + +
                +
                + +
                + +
                +

                + © Copyright 2024, The Regents of the University of California. + +

                +
                + + + + Built with Sphinx using a + + theme + + provided by Read the Docs. + +
                +
                +
                + +
                + +
                + + + + + + + + + + + + + + + + + + + + \ No newline at end of file diff --git a/docs/common/user_manual/user_inputs_documentation/User_Inputs_Documentation_RST_Files/ImportanceSamplingInputWidget.html b/docs/common/user_manual/user_inputs_documentation/User_Inputs_Documentation_RST_Files/ImportanceSamplingInputWidget.html new file mode 100644 index 00000000..173d9a8f --- /dev/null +++ b/docs/common/user_manual/user_inputs_documentation/User_Inputs_Documentation_RST_Files/ImportanceSamplingInputWidget.html @@ -0,0 +1,315 @@ + + + + + + + + + + ImportanceSamplingInputWidget — Earthquake Engineering with Uncertainty Quantification documentation + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + +
                + + + +
                + + + + + +
                + +
                + + + + + + + + + + + + + + + + + + + +
                + + + + +
                +
                +
                +
                + +
                +

                ImportanceSamplingInputWidget

                +
                + + +
                + +
                +
                + +
                + +
                +

                + © Copyright 2024, The Regents of the University of California. + +

                +
                + + + + Built with Sphinx using a + + theme + + provided by Read the Docs. + +
                +
                +
                + +
                + +
                + + + + + + + + + + + + + + + + + + + + \ No newline at end of file diff --git a/docs/common/user_manual/user_inputs_documentation/User_Inputs_Documentation_RST_Files/InputWidgetBIM.html b/docs/common/user_manual/user_inputs_documentation/User_Inputs_Documentation_RST_Files/InputWidgetBIM.html new file mode 100644 index 00000000..4d179e81 --- /dev/null +++ b/docs/common/user_manual/user_inputs_documentation/User_Inputs_Documentation_RST_Files/InputWidgetBIM.html @@ -0,0 +1,315 @@ + + + + + + + + + + InputWidgetBIM — Earthquake Engineering with Uncertainty Quantification documentation + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + +
                + + + +
                + + + + + +
                + +
                + + + + + + + + + + + + + + + + + + + +
                + + + + +
                +
                +
                +
                + +
                +

                InputWidgetBIM

                +
                + + +
                + +
                +
                + +
                + +
                +

                + © Copyright 2024, The Regents of the University of California. + +

                +
                + + + + Built with Sphinx using a + + theme + + provided by Read the Docs. + +
                +
                +
                + +
                + +
                + + + + + + + + + + + + + + + + + + + + \ No newline at end of file diff --git a/docs/common/user_manual/user_inputs_documentation/User_Inputs_Documentation_RST_Files/InputWidgetExistingEvent.html b/docs/common/user_manual/user_inputs_documentation/User_Inputs_Documentation_RST_Files/InputWidgetExistingEvent.html new file mode 100644 index 00000000..bc06a70a --- /dev/null +++ b/docs/common/user_manual/user_inputs_documentation/User_Inputs_Documentation_RST_Files/InputWidgetExistingEvent.html @@ -0,0 +1,315 @@ + + + + + + + + + + InputWidgetExistingEvent — Earthquake Engineering with Uncertainty Quantification documentation + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + +
                + + + +
                + + + + + +
                + +
                + + + + + + + + + + + + + + + + + + + +
                + + + + +
                +
                +
                +
                + +
                +

                InputWidgetExistingEvent

                +
                + + +
                + +
                +
                + +
                + +
                +

                + © Copyright 2024, The Regents of the University of California. + +

                +
                + + + + Built with Sphinx using a + + theme + + provided by Read the Docs. + +
                +
                +
                + +
                + +
                + + + + + + + + + + + + + + + + + + + + \ No newline at end of file diff --git a/docs/common/user_manual/user_inputs_documentation/User_Inputs_Documentation_RST_Files/InputWidgetOpenSeesAnalysis.html b/docs/common/user_manual/user_inputs_documentation/User_Inputs_Documentation_RST_Files/InputWidgetOpenSeesAnalysis.html new file mode 100644 index 00000000..8491680b --- /dev/null +++ b/docs/common/user_manual/user_inputs_documentation/User_Inputs_Documentation_RST_Files/InputWidgetOpenSeesAnalysis.html @@ -0,0 +1,315 @@ + + + + + + + + + + InputWidgetOpenSeesAnalysis — Earthquake Engineering with Uncertainty Quantification documentation + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + +
                + + + +
                + + + + + +
                + +
                + + + + + + + + + + + + + + + + + + + +
                + + + + +
                +
                +
                +
                + +
                +

                InputWidgetOpenSeesAnalysis

                +
                + + +
                + +
                +
                + +
                + +
                +

                + © Copyright 2024, The Regents of the University of California. + +

                +
                + + + + Built with Sphinx using a + + theme + + provided by Read the Docs. + +
                +
                +
                + +
                + +
                + + + + + + + + + + + + + + + + + + + + \ No newline at end of file diff --git a/docs/common/user_manual/user_inputs_documentation/User_Inputs_Documentation_RST_Files/LatinHypercubeInputWidget.html b/docs/common/user_manual/user_inputs_documentation/User_Inputs_Documentation_RST_Files/LatinHypercubeInputWidget.html new file mode 100644 index 00000000..c8dcc406 --- /dev/null +++ b/docs/common/user_manual/user_inputs_documentation/User_Inputs_Documentation_RST_Files/LatinHypercubeInputWidget.html @@ -0,0 +1,315 @@ + + + + + + + + + + LatinHypercubeInputWidget — Earthquake Engineering with Uncertainty Quantification documentation + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + +
                + + + +
                + + + + + +
                + +
                + + + + + + + + + + + + + + + + + + + +
                + + + + +
                +
                +
                +
                + +
                +

                LatinHypercubeInputWidget

                +
                + + +
                + +
                +
                + +
                + +
                +

                + © Copyright 2024, The Regents of the University of California. + +

                +
                + + + + Built with Sphinx using a + + theme + + provided by Read the Docs. + +
                +
                +
                + +
                + +
                + + + + + + + + + + + + + + + + + + + + \ No newline at end of file diff --git a/docs/common/user_manual/user_inputs_documentation/User_Inputs_Documentation_RST_Files/LocalReliabilityWidget.html b/docs/common/user_manual/user_inputs_documentation/User_Inputs_Documentation_RST_Files/LocalReliabilityWidget.html new file mode 100644 index 00000000..a9280c58 --- /dev/null +++ b/docs/common/user_manual/user_inputs_documentation/User_Inputs_Documentation_RST_Files/LocalReliabilityWidget.html @@ -0,0 +1,315 @@ + + + + + + + + + + LocalReliabilityWidget — Earthquake Engineering with Uncertainty Quantification documentation + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + +
                + + + +
                + + + + + +
                + +
                + + + + + + + + + + + + + + + + + + + +
                + + + + +
                +
                +
                +
                + +
                +

                LocalReliabilityWidget

                +
                + + +
                + +
                +
                + +
                + +
                +

                + © Copyright 2024, The Regents of the University of California. + +

                +
                + + + + Built with Sphinx using a + + theme + + provided by Read the Docs. + +
                +
                +
                + +
                + +
                + + + + + + + + + + + + + + + + + + + + \ No newline at end of file diff --git a/docs/common/user_manual/user_inputs_documentation/User_Inputs_Documentation_RST_Files/MDOF_BuildingModel.html b/docs/common/user_manual/user_inputs_documentation/User_Inputs_Documentation_RST_Files/MDOF_BuildingModel.html new file mode 100644 index 00000000..f6ef9f56 --- /dev/null +++ b/docs/common/user_manual/user_inputs_documentation/User_Inputs_Documentation_RST_Files/MDOF_BuildingModel.html @@ -0,0 +1,315 @@ + + + + + + + + + + MDOF_BuildingModel — Earthquake Engineering with Uncertainty Quantification documentation + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + +
                + + + +
                + + + + + +
                + +
                + + + + + + + + + + + + + + + + + + + +
                + + + + +
                +
                +
                +
                + +
                +

                MDOF_BuildingModel

                +
                + + +
                + +
                +
                + +
                + +
                +

                + © Copyright 2024, The Regents of the University of California. + +

                +
                + + + + Built with Sphinx using a + + theme + + provided by Read the Docs. + +
                +
                +
                + +
                + +
                + + + + + + + + + + + + + + + + + + + + \ No newline at end of file diff --git a/docs/common/user_manual/user_inputs_documentation/User_Inputs_Documentation_RST_Files/MDOF_LU.html b/docs/common/user_manual/user_inputs_documentation/User_Inputs_Documentation_RST_Files/MDOF_LU.html new file mode 100644 index 00000000..4b230884 --- /dev/null +++ b/docs/common/user_manual/user_inputs_documentation/User_Inputs_Documentation_RST_Files/MDOF_LU.html @@ -0,0 +1,315 @@ + + + + + + + + + + MDOF_LU — Earthquake Engineering with Uncertainty Quantification documentation + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + +
                + + + +
                + + + + + +
                + +
                + + + + + + + + + + + + + + + + + + + +
                + + + + +
                +
                +
                +
                + +
                +

                MDOF_LU

                +
                + + +
                + +
                +
                + +
                + +
                +

                + © Copyright 2024, The Regents of the University of California. + +

                +
                + + + + Built with Sphinx using a + + theme + + provided by Read the Docs. + +
                +
                +
                + +
                + +
                + + + + + + + + + + + + + + + + + + + + \ No newline at end of file diff --git a/docs/common/user_manual/user_inputs_documentation/User_Inputs_Documentation_RST_Files/MonteCarloInputSimWidget.html b/docs/common/user_manual/user_inputs_documentation/User_Inputs_Documentation_RST_Files/MonteCarloInputSimWidget.html new file mode 100644 index 00000000..7f487be0 --- /dev/null +++ b/docs/common/user_manual/user_inputs_documentation/User_Inputs_Documentation_RST_Files/MonteCarloInputSimWidget.html @@ -0,0 +1,315 @@ + + + + + + + + + + MonteCarloInputSimWidget — Earthquake Engineering with Uncertainty Quantification documentation + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + +
                + + + +
                + + + + + +
                + +
                + + + + + + + + + + + + + + + + + + + +
                + + + + +
                +
                +
                +
                + +
                +

                MonteCarloInputSimWidget

                +
                + + +
                + +
                +
                + +
                + +
                +

                + © Copyright 2024, The Regents of the University of California. + +

                +
                + + + + Built with Sphinx using a + + theme + + provided by Read the Docs. + +
                +
                +
                + +
                + +
                + + + + + + + + + + + + + + + + + + + + \ No newline at end of file diff --git a/docs/common/user_manual/user_inputs_documentation/User_Inputs_Documentation_RST_Files/MonteCarloInputWidget.html b/docs/common/user_manual/user_inputs_documentation/User_Inputs_Documentation_RST_Files/MonteCarloInputWidget.html new file mode 100644 index 00000000..fea1c6c4 --- /dev/null +++ b/docs/common/user_manual/user_inputs_documentation/User_Inputs_Documentation_RST_Files/MonteCarloInputWidget.html @@ -0,0 +1,315 @@ + + + + + + + + + + MonteCarloInputWidget — Earthquake Engineering with Uncertainty Quantification documentation + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + +
                + + + +
                + + + + + +
                + +
                + + + + + + + + + + + + + + + + + + + +
                + + + + +
                +
                +
                +
                + +
                +

                MonteCarloInputWidget

                +
                + + +
                + +
                +
                + +
                + +
                +

                + © Copyright 2024, The Regents of the University of California. + +

                +
                + + + + Built with Sphinx using a + + theme + + provided by Read the Docs. + +
                +
                +
                + +
                + +
                + + + + + + + + + + + + + + + + + + + + \ No newline at end of file diff --git a/docs/common/user_manual/user_inputs_documentation/User_Inputs_Documentation_RST_Files/MultiFidelityMonteCarlo.html b/docs/common/user_manual/user_inputs_documentation/User_Inputs_Documentation_RST_Files/MultiFidelityMonteCarlo.html new file mode 100644 index 00000000..8536f2a4 --- /dev/null +++ b/docs/common/user_manual/user_inputs_documentation/User_Inputs_Documentation_RST_Files/MultiFidelityMonteCarlo.html @@ -0,0 +1,315 @@ + + + + + + + + + + MultiFidelityMonteCarlo — Earthquake Engineering with Uncertainty Quantification documentation + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + +
                + + + +
                + + + + + +
                + +
                + + + + + + + + + + + + + + + + + + + +
                + + + + +
                +
                +
                +
                + +
                +

                MultiFidelityMonteCarlo

                +
                + + +
                + +
                +
                + +
                + +
                +

                + © Copyright 2024, The Regents of the University of California. + +

                +
                + + + + Built with Sphinx using a + + theme + + provided by Read the Docs. + +
                +
                +
                + +
                + +
                + + + + + + + + + + + + + + + + + + + + \ No newline at end of file diff --git a/docs/common/user_manual/user_inputs_documentation/User_Inputs_Documentation_RST_Files/MultiFidelitySimWidget.html b/docs/common/user_manual/user_inputs_documentation/User_Inputs_Documentation_RST_Files/MultiFidelitySimWidget.html new file mode 100644 index 00000000..26617f6c --- /dev/null +++ b/docs/common/user_manual/user_inputs_documentation/User_Inputs_Documentation_RST_Files/MultiFidelitySimWidget.html @@ -0,0 +1,315 @@ + + + + + + + + + + MultiFidelitySimWidget — Earthquake Engineering with Uncertainty Quantification documentation + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + +
                + + + +
                + + + + + +
                + +
                + + + + + + + + + + + + + + + + + + + +
                + + + + +
                +
                +
                +
                + +
                +

                MultiFidelitySimWidget

                +
                + + +
                + +
                +
                + +
                + +
                +

                + © Copyright 2024, The Regents of the University of California. + +

                +
                + + + + Built with Sphinx using a + + theme + + provided by Read the Docs. + +
                +
                +
                + +
                + +
                + + + + + + + + + + + + + + + + + + + + \ No newline at end of file diff --git a/docs/common/user_manual/user_inputs_documentation/User_Inputs_Documentation_RST_Files/NoneEngine.html b/docs/common/user_manual/user_inputs_documentation/User_Inputs_Documentation_RST_Files/NoneEngine.html new file mode 100644 index 00000000..65c5492c --- /dev/null +++ b/docs/common/user_manual/user_inputs_documentation/User_Inputs_Documentation_RST_Files/NoneEngine.html @@ -0,0 +1,315 @@ + + + + + + + + + + NoneEngine — Earthquake Engineering with Uncertainty Quantification documentation + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + +
                + + + +
                + + + + + +
                + +
                + + + + + + + + + + + + + + + + + + + +
                + + + + +
                +
                +
                +
                + +
                +

                NoneEngine

                +
                + + +
                + +
                +
                + +
                + +
                +

                + © Copyright 2024, The Regents of the University of California. + +

                +
                + + + + Built with Sphinx using a + + theme + + provided by Read the Docs. + +
                +
                +
                + +
                + +
                + + + + + + + + + + + + + + + + + + + + \ No newline at end of file diff --git a/docs/common/user_manual/user_inputs_documentation/User_Inputs_Documentation_RST_Files/OpenSeesBuildingModel.html b/docs/common/user_manual/user_inputs_documentation/User_Inputs_Documentation_RST_Files/OpenSeesBuildingModel.html new file mode 100644 index 00000000..828f50ee --- /dev/null +++ b/docs/common/user_manual/user_inputs_documentation/User_Inputs_Documentation_RST_Files/OpenSeesBuildingModel.html @@ -0,0 +1,315 @@ + + + + + + + + + + OpenSeesBuildingModel — Earthquake Engineering with Uncertainty Quantification documentation + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + +
                + + + +
                + + + + + +
                + +
                + + + + + + + + + + + + + + + + + + + +
                + + + + +
                +
                +
                +
                + +
                +

                OpenSeesBuildingModel

                +
                + + +
                + +
                +
                + +
                + +
                +

                + © Copyright 2024, The Regents of the University of California. + +

                +
                + + + + Built with Sphinx using a + + theme + + provided by Read the Docs. + +
                +
                +
                + +
                + +
                + + + + + + + + + + + + + + + + + + + + \ No newline at end of file diff --git a/docs/common/user_manual/user_inputs_documentation/User_Inputs_Documentation_RST_Files/PCEInputWidget.html b/docs/common/user_manual/user_inputs_documentation/User_Inputs_Documentation_RST_Files/PCEInputWidget.html new file mode 100644 index 00000000..33549939 --- /dev/null +++ b/docs/common/user_manual/user_inputs_documentation/User_Inputs_Documentation_RST_Files/PCEInputWidget.html @@ -0,0 +1,315 @@ + + + + + + + + + + PCEInputWidget — Earthquake Engineering with Uncertainty Quantification documentation + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + +
                + + + +
                + + + + + +
                + +
                + + + + + + + + + + + + + + + + + + + +
                + + + + +
                +
                +
                +
                + +
                +

                PCEInputWidget

                +
                + + +
                + +
                +
                + +
                + +
                +

                + © Copyright 2024, The Regents of the University of California. + +

                +
                + + + + Built with Sphinx using a + + theme + + provided by Read the Docs. + +
                +
                +
                + +
                + +
                + + + + + + + + + + + + + + + + + + + + \ No newline at end of file diff --git a/docs/common/user_manual/user_inputs_documentation/User_Inputs_Documentation_RST_Files/PLoMInputWidget.html b/docs/common/user_manual/user_inputs_documentation/User_Inputs_Documentation_RST_Files/PLoMInputWidget.html new file mode 100644 index 00000000..a769dc87 --- /dev/null +++ b/docs/common/user_manual/user_inputs_documentation/User_Inputs_Documentation_RST_Files/PLoMInputWidget.html @@ -0,0 +1,315 @@ + + + + + + + + + + PLoMInputWidget — Earthquake Engineering with Uncertainty Quantification documentation + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + +
                + + + +
                + + + + + +
                + +
                + + + + + + + + + + + + + + + + + + + +
                + + + + +
                +
                +
                +
                + +
                +

                PLoMInputWidget

                +
                + + +
                + +
                +
                + +
                + +
                +

                + © Copyright 2024, The Regents of the University of California. + +

                +
                + + + + Built with Sphinx using a + + theme + + provided by Read the Docs. + +
                +
                +
                + +
                + +
                + + + + + + + + + + + + + + + + + + + + \ No newline at end of file diff --git a/docs/common/user_manual/user_inputs_documentation/User_Inputs_Documentation_RST_Files/PLoMSimuWidget.html b/docs/common/user_manual/user_inputs_documentation/User_Inputs_Documentation_RST_Files/PLoMSimuWidget.html new file mode 100644 index 00000000..2289882a --- /dev/null +++ b/docs/common/user_manual/user_inputs_documentation/User_Inputs_Documentation_RST_Files/PLoMSimuWidget.html @@ -0,0 +1,315 @@ + + + + + + + + + + PLoMSimuWidget — Earthquake Engineering with Uncertainty Quantification documentation + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + +
                + + + +
                + + + + + +
                + +
                + + + + + + + + + + + + + + + + + + + +
                + + + + +
                +
                +
                +
                + +
                +

                PLoMSimuWidget

                +
                + + +
                + +
                +
                + +
                + +
                +

                + © Copyright 2024, The Regents of the University of California. + +

                +
                + + + + Built with Sphinx using a + + theme + + provided by Read the Docs. + +
                +
                +
                + +
                + +
                + + + + + + + + + + + + + + + + + + + + \ No newline at end of file diff --git a/docs/common/user_manual/user_inputs_documentation/User_Inputs_Documentation_RST_Files/SimCenterIntensityMeasureCombo.html b/docs/common/user_manual/user_inputs_documentation/User_Inputs_Documentation_RST_Files/SimCenterIntensityMeasureCombo.html new file mode 100644 index 00000000..2a1e8401 --- /dev/null +++ b/docs/common/user_manual/user_inputs_documentation/User_Inputs_Documentation_RST_Files/SimCenterIntensityMeasureCombo.html @@ -0,0 +1,315 @@ + + + + + + + + + + SimCenterIntensityMeasureCombo — Earthquake Engineering with Uncertainty Quantification documentation + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + +
                + + + +
                + + + + + +
                + +
                + + + + + + + + + + + + + + + + + + + +
                + + + + +
                +
                +
                +
                + +
                +

                SimCenterIntensityMeasureCombo

                +
                + + +
                + +
                +
                + +
                + +
                +

                + © Copyright 2024, The Regents of the University of California. + +

                +
                + + + + Built with Sphinx using a + + theme + + provided by Read the Docs. + +
                +
                +
                + +
                + +
                + + + + + + + + + + + + + + + + + + + + \ No newline at end of file diff --git a/docs/common/user_manual/user_inputs_documentation/User_Inputs_Documentation_RST_Files/SimCenterIntensityMeasureWidget.html b/docs/common/user_manual/user_inputs_documentation/User_Inputs_Documentation_RST_Files/SimCenterIntensityMeasureWidget.html new file mode 100644 index 00000000..8717150b --- /dev/null +++ b/docs/common/user_manual/user_inputs_documentation/User_Inputs_Documentation_RST_Files/SimCenterIntensityMeasureWidget.html @@ -0,0 +1,315 @@ + + + + + + + + + + SimCenterIntensityMeasureWidget — Earthquake Engineering with Uncertainty Quantification documentation + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + +
                + + + +
                + + + + + +
                + +
                + + + + + + + + + + + + + + + + + + + +
                + + + + +
                +
                +
                +
                + +
                +

                SimCenterIntensityMeasureWidget

                +
                + + +
                + +
                +
                + +
                + +
                +

                + © Copyright 2024, The Regents of the University of California. + +

                +
                + + + + Built with Sphinx using a + + theme + + provided by Read the Docs. + +
                +
                +
                + +
                + +
                + + + + + + + + + + + + + + + + + + + + \ No newline at end of file diff --git a/docs/common/user_manual/user_inputs_documentation/User_Inputs_Documentation_RST_Files/SimCenterUQInputPLoM.html b/docs/common/user_manual/user_inputs_documentation/User_Inputs_Documentation_RST_Files/SimCenterUQInputPLoM.html new file mode 100644 index 00000000..64f1aa8c --- /dev/null +++ b/docs/common/user_manual/user_inputs_documentation/User_Inputs_Documentation_RST_Files/SimCenterUQInputPLoM.html @@ -0,0 +1,315 @@ + + + + + + + + + + SimCenterUQInputPLoM — Earthquake Engineering with Uncertainty Quantification documentation + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + +
                + + + +
                + + + + + +
                + +
                + + + + + + + + + + + + + + + + + + + +
                + + + + +
                +
                +
                +
                + +
                +

                SimCenterUQInputPLoM

                +
                + + +
                + +
                +
                + +
                + +
                +

                + © Copyright 2024, The Regents of the University of California. + +

                +
                + + + + Built with Sphinx using a + + theme + + provided by Read the Docs. + +
                +
                +
                + +
                + +
                + + + + + + + + + + + + + + + + + + + + \ No newline at end of file diff --git a/docs/common/user_manual/user_inputs_documentation/User_Inputs_Documentation_RST_Files/SimCenterUQInputSampling.html b/docs/common/user_manual/user_inputs_documentation/User_Inputs_Documentation_RST_Files/SimCenterUQInputSampling.html new file mode 100644 index 00000000..7e001c88 --- /dev/null +++ b/docs/common/user_manual/user_inputs_documentation/User_Inputs_Documentation_RST_Files/SimCenterUQInputSampling.html @@ -0,0 +1,315 @@ + + + + + + + + + + SimCenterUQInputSampling — Earthquake Engineering with Uncertainty Quantification documentation + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + +
                + + + +
                + + + + + +
                + +
                + + + + + + + + + + + + + + + + + + + +
                + + + + +
                +
                +
                +
                + +
                +

                SimCenterUQInputSampling

                +
                + + +
                + +
                +
                + +
                + +
                +

                + © Copyright 2024, The Regents of the University of California. + +

                +
                + + + + Built with Sphinx using a + + theme + + provided by Read the Docs. + +
                +
                +
                + +
                + +
                + + + + + + + + + + + + + + + + + + + + \ No newline at end of file diff --git a/docs/common/user_manual/user_inputs_documentation/User_Inputs_Documentation_RST_Files/SimCenterUQInputSensitivity.html b/docs/common/user_manual/user_inputs_documentation/User_Inputs_Documentation_RST_Files/SimCenterUQInputSensitivity.html new file mode 100644 index 00000000..a9fed585 --- /dev/null +++ b/docs/common/user_manual/user_inputs_documentation/User_Inputs_Documentation_RST_Files/SimCenterUQInputSensitivity.html @@ -0,0 +1,315 @@ + + + + + + + + + + SimCenterUQInputSensitivity — Earthquake Engineering with Uncertainty Quantification documentation + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + +
                + + + +
                + + + + + +
                + +
                + + + + + + + + + + + + + + + + + + + +
                + + + + +
                +
                +
                +
                + +
                +

                SimCenterUQInputSensitivity

                +
                + + +
                + +
                +
                + +
                + +
                +

                + © Copyright 2024, The Regents of the University of California. + +

                +
                + + + + Built with Sphinx using a + + theme + + provided by Read the Docs. + +
                +
                +
                + +
                + +
                + + + + + + + + + + + + + + + + + + + + \ No newline at end of file diff --git a/docs/common/user_manual/user_inputs_documentation/User_Inputs_Documentation_RST_Files/SimCenterUQInputSurrogate.html b/docs/common/user_manual/user_inputs_documentation/User_Inputs_Documentation_RST_Files/SimCenterUQInputSurrogate.html new file mode 100644 index 00000000..80bdf735 --- /dev/null +++ b/docs/common/user_manual/user_inputs_documentation/User_Inputs_Documentation_RST_Files/SimCenterUQInputSurrogate.html @@ -0,0 +1,320 @@ + + + + + + + + + + SimCenterUQInputSurrogate — Earthquake Engineering with Uncertainty Quantification documentation + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + +
                + + + +
                + + + + + +
                + +
                + + + + + + + + + + + + + + + + + + + +
                + + + + +
                +
                +
                +
                + +
                +

                SimCenterUQInputSurrogate

                +

                Training Datase

                +
                +

                Default: Sampling and Simulation

                +

                Key in JSON file: method

                +
                +
                + + +
                + +
                +
                + +
                + +
                +

                + © Copyright 2024, The Regents of the University of California. + +

                +
                + + + + Built with Sphinx using a + + theme + + provided by Read the Docs. + +
                +
                +
                + +
                + +
                + + + + + + + + + + + + + + + + + + + + \ No newline at end of file diff --git a/docs/common/user_manual/user_inputs_documentation/User_Inputs_Documentation_RST_Files/SimCenterUnitsCombo.html b/docs/common/user_manual/user_inputs_documentation/User_Inputs_Documentation_RST_Files/SimCenterUnitsCombo.html new file mode 100644 index 00000000..0b32d10a --- /dev/null +++ b/docs/common/user_manual/user_inputs_documentation/User_Inputs_Documentation_RST_Files/SimCenterUnitsCombo.html @@ -0,0 +1,315 @@ + + + + + + + + + + SimCenterUnitsCombo — Earthquake Engineering with Uncertainty Quantification documentation + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + +
                + + + +
                + + + + + +
                + +
                + + + + + + + + + + + + + + + + + + + +
                + + + + +
                +
                +
                +
                + +
                +

                SimCenterUnitsCombo

                +
                + + +
                + +
                +
                + +
                + +
                +

                + © Copyright 2024, The Regents of the University of California. + +

                +
                + + + + Built with Sphinx using a + + theme + + provided by Read the Docs. + +
                +
                +
                + +
                + +
                + + + + + + + + + + + + + + + + + + + + \ No newline at end of file diff --git a/docs/common/user_manual/user_inputs_documentation/User_Inputs_Documentation_RST_Files/StandardEDP.html b/docs/common/user_manual/user_inputs_documentation/User_Inputs_Documentation_RST_Files/StandardEDP.html new file mode 100644 index 00000000..3cbec039 --- /dev/null +++ b/docs/common/user_manual/user_inputs_documentation/User_Inputs_Documentation_RST_Files/StandardEDP.html @@ -0,0 +1,315 @@ + + + + + + + + + + StandardEDP — Earthquake Engineering with Uncertainty Quantification documentation + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + +
                + + + +
                + + + + + +
                + +
                + + + + + + + + + + + + + + + + + + + +
                + + + + +
                +
                +
                +
                + +
                +

                StandardEDP

                +
                + + +
                + +
                +
                + +
                + +
                +

                + © Copyright 2024, The Regents of the University of California. + +

                +
                + + + + Built with Sphinx using a + + theme + + provided by Read the Docs. + +
                +
                +
                + +
                + +
                + + + + + + + + + + + + + + + + + + + + \ No newline at end of file diff --git a/docs/common/user_manual/user_inputs_documentation/User_Inputs_Documentation_RST_Files/StandardEarthquakeEDP.html b/docs/common/user_manual/user_inputs_documentation/User_Inputs_Documentation_RST_Files/StandardEarthquakeEDP.html new file mode 100644 index 00000000..72b55ba7 --- /dev/null +++ b/docs/common/user_manual/user_inputs_documentation/User_Inputs_Documentation_RST_Files/StandardEarthquakeEDP.html @@ -0,0 +1,315 @@ + + + + + + + + + + StandardEarthquakeEDP — Earthquake Engineering with Uncertainty Quantification documentation + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + +
                + + + +
                + + + + + +
                + +
                + + + + + + + + + + + + + + + + + + + +
                + + + + +
                +
                +
                +
                + +
                +

                StandardEarthquakeEDP

                +
                + + +
                + +
                +
                + +
                + +
                +

                + © Copyright 2024, The Regents of the University of California. + +

                +
                + + + + Built with Sphinx using a + + theme + + provided by Read the Docs. + +
                +
                +
                + +
                + +
                + + + + + + + + + + + + + + + + + + + + \ No newline at end of file diff --git a/docs/common/user_manual/user_inputs_documentation/User_Inputs_Documentation_RST_Files/SteelBuildingModel.html b/docs/common/user_manual/user_inputs_documentation/User_Inputs_Documentation_RST_Files/SteelBuildingModel.html new file mode 100644 index 00000000..bd31d44b --- /dev/null +++ b/docs/common/user_manual/user_inputs_documentation/User_Inputs_Documentation_RST_Files/SteelBuildingModel.html @@ -0,0 +1,315 @@ + + + + + + + + + + SteelBuildingModel — Earthquake Engineering with Uncertainty Quantification documentation + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + +
                + + + +
                + + + + + +
                + +
                + + + + + + + + + + + + + + + + + + + +
                + + + + +
                +
                +
                +
                + +
                +

                SteelBuildingModel

                +
                + + +
                + +
                +
                + +
                + +
                +

                + © Copyright 2024, The Regents of the University of California. + +

                +
                + + + + Built with Sphinx using a + + theme + + provided by Read the Docs. + +
                +
                +
                + +
                + +
                + + + + + + + + + + + + + + + + + + + + \ No newline at end of file diff --git a/docs/common/user_manual/user_inputs_documentation/User_Inputs_Documentation_RST_Files/SurrogateDoEInputWidget.html b/docs/common/user_manual/user_inputs_documentation/User_Inputs_Documentation_RST_Files/SurrogateDoEInputWidget.html new file mode 100644 index 00000000..a044a337 --- /dev/null +++ b/docs/common/user_manual/user_inputs_documentation/User_Inputs_Documentation_RST_Files/SurrogateDoEInputWidget.html @@ -0,0 +1,458 @@ + + + + + + + + + + SurrogateDoEInputWidget — Earthquake Engineering with Uncertainty Quantification documentation + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + +
                + + + +
                + + + + + +
                + +
                + + + + + + + + + + + + + + + + + + + +
                + + + + +
                +
                +
                +
                + +
                +

                SurrogateDoEInputWidget

                +
                +
                Number of Samples

                When the number of simulation runs reaches the limit, the analysis will be terminated.

                +

                Default: 150

                +

                Key in JSON file: samples

                +
                +
                +
                +
                Max Computation Time (minutes)

                When the tolerance limit of the computation time is reached, the analysis will be terminated. There will be a few minutes of error.

                +

                Default: 60

                +

                Key in JSON file: timeLimit

                +
                +
                +
                +
                Target Accuracy (normalized err)

                The target accuracy is defined in terms of normalized root-mean-squared error (NRMSE) estimated by leave-out-one cross-validation (LOOCV).

                +

                Default: 0.02

                +

                Key in JSON file: accuracyLimit

                +
                +
                +
                +
                Random Seed

                Seed of the random number generator

                +

                Default: a random integer

                +

                Key in JSON file: seed

                +
                +
                +
                +
                Parallel Execution

                This engine implemented multiprocessing (local) or mpi4py (remote) python packages to run parallel execution.

                +

                Default: checked

                +

                Key in JSON file: parallelExecution

                +
                +
                +
                +
                Advanced Options for Gaussian Process Model

                If unchecked, default values will be used

                +

                Default: unchecked

                +

                Key in JSON file: advancedOpt

                +
                +
                +
                +
                Kernel Function

                Correlation function for Gaussian process regression. Matern5/2 function is the default, and Matern3/2, Radial Basis, and Exponential functions (exponent) are additionally supported.

                +

                Default: Matern5/2

                +

                Key in JSON file: kernel

                +
                +
                +
                +
                Add Linear Trend Function

                When increasing or decreasing trend is expected over the variables domain, a linear trend function may be introduced.

                +

                Default: unchecked

                +

                Key in JSON file: linear

                +
                +
                +
                +
                Log-space Transform of QoI

                When the user can guarantee that the response quantities are always greater than 0, user may want to introduce a surrogate model in log-transformed space of QoI.

                +

                Default: unchecked

                +

                Key in JSON file: logTransform

                +
                +
                +
                +
                DoE Options

                Design of Experiment method

                +

                Default: none

                +

                Key in JSON file: DoEmethod

                +
                +
                +
                +
                Initial DoE #

                The number of the initial DoE

                +

                Default: 4 x #RV

                +

                Key in JSON file: initialDoE

                +
                +
                +
                +
                Nugget Variances

                User may define nugget variances or bounds of the nugget variances if needed.

                +

                Default: Optimize

                +

                Key in JSON file: nuggetOpt

                +
                +
                +
                +
                Nugget Values/Bounds

                User-defined nugget variances or bounds

                +

                Key in JSON file: nuggetString

                +
                +
                +
                +
                # samples to be replicated (A)

                From the number of unique samples specified in the ‘Number of Samples’ field, decide how many of them will have replications.

                +

                Default: 8 x #RV

                +

                Key in JSON file: numSampToBeRepl

                +
                +
                +
                +
                # replications per sample (B)

                Specify how many replications will be generated for the number of samples specified in A.

                +

                Default: 10

                +

                Key in JSON file: numRepl

                +
                +
                +
                +
                Start with Existing Dataset

                If unchecked, no existing dataset is utilized

                +

                Default: checked

                +

                Key in JSON file: existingDoE

                +
                +
                +
                +
                Training Points (Input RV)

                Full path to the file containing training points (samples of RV)

                +

                Key in JSON file: inpFile

                + +
                +
                +
                +
                System Responses (Output QoI)

                Full path to the file containing system responses (samples of QoI) corresponding to the specified training points

                +

                Key in JSON file: outFile

                + +
                +
                +
                +
                Advanced Options (Earthquake specific)

                If unchecked, default values will be used

                +

                Default: unchecked

                +

                Key in JSON file: none

                +
                +
                +
                +
                Input postprocess

                Ground motion pre-processing for surrogate model training

                +

                Default: Ground Motion Intensity

                +

                Key in JSON file: none

                +
                +
                +
                +
                IM

                The user can select intensity measures (IMs) that will be used as auxiliary inputs of the surrogate model, in addition to those specified in the RV tab.

                +

                Default: Pseudo Spectral Velocity (in/sec)

                +

                Key in JSON file: IntensityMeasure

                +
                +
                +
                +
                Periods

                Specify period(s) corresponding to IM

                +

                Default: 0.5 or 0.1,1.0,1.5

                +

                Key in JSON file: Periods

                +
                +
                +
                +
                Geometric mean

                If ground motions have more than one directional component, either each component’s IM can be added as a separate surrogate input parameter, or they can be aggregated by using their geometric mean.

                +

                Default: checked

                +

                Key in JSON file: useGeoMean

                +
                +
                +
                + + +
                + +
                +
                + +
                + +
                +

                + © Copyright 2024, The Regents of the University of California. + +

                +
                + + + + Built with Sphinx using a + + theme + + provided by Read the Docs. + +
                +
                +
                + +
                + +
                + + + + + + + + + + + + + + + + + + + + \ No newline at end of file diff --git a/docs/common/user_manual/user_inputs_documentation/User_Inputs_Documentation_RST_Files/SurrogateEDP.html b/docs/common/user_manual/user_inputs_documentation/User_Inputs_Documentation_RST_Files/SurrogateEDP.html new file mode 100644 index 00000000..f99701ef --- /dev/null +++ b/docs/common/user_manual/user_inputs_documentation/User_Inputs_Documentation_RST_Files/SurrogateEDP.html @@ -0,0 +1,315 @@ + + + + + + + + + + SurrogateEDP — Earthquake Engineering with Uncertainty Quantification documentation + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + +
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                + +
                + + + + + + + + + + + + + + + + + + + +
                + + + + +
                +
                +
                +
                + +
                +

                SurrogateEDP

                +
                + + +
                + +
                +
                + +
                + +
                +

                + © Copyright 2024, The Regents of the University of California. + +

                +
                + + + + Built with Sphinx using a + + theme + + provided by Read the Docs. + +
                +
                +
                + +
                + +
                + + + + + + + + + + + + + + + + + + + + \ No newline at end of file diff --git a/docs/common/user_manual/user_inputs_documentation/User_Inputs_Documentation_RST_Files/SurrogateGP.html b/docs/common/user_manual/user_inputs_documentation/User_Inputs_Documentation_RST_Files/SurrogateGP.html new file mode 100644 index 00000000..98a190c2 --- /dev/null +++ b/docs/common/user_manual/user_inputs_documentation/User_Inputs_Documentation_RST_Files/SurrogateGP.html @@ -0,0 +1,315 @@ + + + + + + + + + + SurrogateGP — Earthquake Engineering with Uncertainty Quantification documentation + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + +
                + + + +
                + + + + + +
                + +
                + + + + + + + + + + + + + + + + + + + +
                + + + + +
                +
                +
                +
                + +
                +

                SurrogateGP

                +
                + + +
                + +
                +
                + +
                + +
                +

                + © Copyright 2024, The Regents of the University of California. + +

                +
                + + + + Built with Sphinx using a + + theme + + provided by Read the Docs. + +
                +
                +
                + +
                + +
                + + + + + + + + + + + + + + + + + + + + \ No newline at end of file diff --git a/docs/common/user_manual/user_inputs_documentation/User_Inputs_Documentation_RST_Files/SurrogateMFInputWidget.html b/docs/common/user_manual/user_inputs_documentation/User_Inputs_Documentation_RST_Files/SurrogateMFInputWidget.html new file mode 100644 index 00000000..0ac3d0af --- /dev/null +++ b/docs/common/user_manual/user_inputs_documentation/User_Inputs_Documentation_RST_Files/SurrogateMFInputWidget.html @@ -0,0 +1,315 @@ + + + + + + + + + + SurrogateMFInputWidget — Earthquake Engineering with Uncertainty Quantification documentation + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + +
                + + + +
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                + +
                + + + + + + + + + + + + + + + + + + + +
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                +
                +
                +
                + +
                +

                SurrogateMFInputWidget

                +
                + + +
                + +
                +
                + +
                + +
                +

                + © Copyright 2024, The Regents of the University of California. + +

                +
                + + + + Built with Sphinx using a + + theme + + provided by Read the Docs. + +
                +
                +
                + +
                + +
                + + + + + + + + + + + + + + + + + + + + \ No newline at end of file diff --git a/docs/common/user_manual/user_inputs_documentation/User_Inputs_Documentation_RST_Files/SurrogateNoDoEInputWidget.html b/docs/common/user_manual/user_inputs_documentation/User_Inputs_Documentation_RST_Files/SurrogateNoDoEInputWidget.html new file mode 100644 index 00000000..9b402f55 --- /dev/null +++ b/docs/common/user_manual/user_inputs_documentation/User_Inputs_Documentation_RST_Files/SurrogateNoDoEInputWidget.html @@ -0,0 +1,315 @@ + + + + + + + + + + SurrogateNoDoEInputWidget — Earthquake Engineering with Uncertainty Quantification documentation + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + +
                + + + +
                + + + + + +
                + +
                + + + + + + + + + + + + + + + + + + + +
                + + + + +
                +
                +
                +
                + +
                +

                SurrogateNoDoEInputWidget

                +
                + + +
                + +
                +
                + +
                + +
                +

                + © Copyright 2024, The Regents of the University of California. + +

                +
                + + + + Built with Sphinx using a + + theme + + provided by Read the Docs. + +
                +
                +
                + +
                + +
                + + + + + + + + + + + + + + + + + + + + \ No newline at end of file diff --git a/docs/common/user_manual/user_inputs_documentation/User_Inputs_Documentation_RST_Files/SurrogateSimulation.html b/docs/common/user_manual/user_inputs_documentation/User_Inputs_Documentation_RST_Files/SurrogateSimulation.html new file mode 100644 index 00000000..51761ccf --- /dev/null +++ b/docs/common/user_manual/user_inputs_documentation/User_Inputs_Documentation_RST_Files/SurrogateSimulation.html @@ -0,0 +1,315 @@ + + + + + + + + + + SurrogateSimulation — Earthquake Engineering with Uncertainty Quantification documentation + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + +
                + + + +
                + + + + + +
                + +
                + + + + + + + + + + + + + + + + + + + +
                + + + + +
                +
                +
                +
                + +
                +

                SurrogateSimulation

                +
                + + +
                + +
                +
                + +
                + +
                +

                + © Copyright 2024, The Regents of the University of California. + +

                +
                + + + + Built with Sphinx using a + + theme + + provided by Read the Docs. + +
                +
                +
                + +
                + +
                + + + + + + + + + + + + + + + + + + + + \ No newline at end of file diff --git a/docs/common/user_manual/user_inputs_documentation/User_Inputs_Documentation_RST_Files/UCSD_InputBayesianCalibration.html b/docs/common/user_manual/user_inputs_documentation/User_Inputs_Documentation_RST_Files/UCSD_InputBayesianCalibration.html new file mode 100644 index 00000000..c5fd0c75 --- /dev/null +++ b/docs/common/user_manual/user_inputs_documentation/User_Inputs_Documentation_RST_Files/UCSD_InputBayesianCalibration.html @@ -0,0 +1,315 @@ + + + + + + + + + + UCSD_InputBayesianCalibration — Earthquake Engineering with Uncertainty Quantification documentation + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + +
                + + + +
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                + +
                + + + + + + + + + + + + + + + + + + + +
                + + + + +
                +
                +
                +
                + +
                +

                UCSD_InputBayesianCalibration

                +
                + + +
                + +
                +
                + +
                + +
                +

                + © Copyright 2024, The Regents of the University of California. + +

                +
                + + + + Built with Sphinx using a + + theme + + provided by Read the Docs. + +
                +
                +
                + +
                + +
                + + + + + + + + + + + + + + + + + + + + \ No newline at end of file diff --git a/docs/common/user_manual/user_inputs_documentation/User_Inputs_Documentation_RST_Files/UCSD_InputHierarchicalBayesian.html b/docs/common/user_manual/user_inputs_documentation/User_Inputs_Documentation_RST_Files/UCSD_InputHierarchicalBayesian.html new file mode 100644 index 00000000..4db89d5d --- /dev/null +++ b/docs/common/user_manual/user_inputs_documentation/User_Inputs_Documentation_RST_Files/UCSD_InputHierarchicalBayesian.html @@ -0,0 +1,315 @@ + + + + + + + + + + UCSD_InputHierarchicalBayesian — Earthquake Engineering with Uncertainty Quantification documentation + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + +
                + + + +
                + + + + + +
                + +
                + + + + + + + + + + + + + + + + + + + +
                + + + + +
                +
                +
                +
                + +
                +

                UCSD_InputHierarchicalBayesian

                +
                + + +
                + +
                +
                + +
                + +
                +

                + © Copyright 2024, The Regents of the University of California. + +

                +
                + + + + Built with Sphinx using a + + theme + + provided by Read the Docs. + +
                +
                +
                + +
                + +
                + + + + + + + + + + + + + + + + + + + + \ No newline at end of file diff --git a/docs/common/user_manual/user_inputs_documentation/User_Inputs_Documentation_RST_Files/UCSD_InputTMCMC.html b/docs/common/user_manual/user_inputs_documentation/User_Inputs_Documentation_RST_Files/UCSD_InputTMCMC.html new file mode 100644 index 00000000..ed16e801 --- /dev/null +++ b/docs/common/user_manual/user_inputs_documentation/User_Inputs_Documentation_RST_Files/UCSD_InputTMCMC.html @@ -0,0 +1,343 @@ + + + + + + + + + + UCSD_InputTMCMC — Earthquake Engineering with Uncertainty Quantification documentation + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + +
                + + + +
                + + + + + +
                + +
                + + + + + + + + + + + + + + + + + + + +
                + + + + +
                +
                +
                +
                + +
                +

                UCSD_InputTMCMC

                +
                +
                Sample Size

                Number of samples from the posterior probability distribution

                +

                Key in JSON file: sample_size

                +
                +
                +
                +
                Seed

                State of pseudo-random number generator for reproducibility

                +

                Key in JSON file: seed

                +
                +
                +
                +
                Calibration Data File

                Full path to the file containing the calibration data

                +

                Key in JSON file: calibration_data_file

                +
                +

                See also

                +

                Calibration data file

                +
                +
                +
                +
                +
                Log Likelihood Script

                Full path to the file containing the log-likelihood function

                +

                Key in JSON file: log_likelihood_script

                + +
                +
                +
                + + +
                + +
                +
                + +
                + +
                +

                + © Copyright 2024, The Regents of the University of California. + +

                +
                + + + + Built with Sphinx using a + + theme + + provided by Read the Docs. + +
                +
                +
                + +
                + +
                + + + + + + + + + + + + + + + + + + + + \ No newline at end of file diff --git a/docs/common/user_manual/user_inputs_documentation/User_Inputs_Documentation_RST_Files/UQpyStretch.html b/docs/common/user_manual/user_inputs_documentation/User_Inputs_Documentation_RST_Files/UQpyStretch.html new file mode 100644 index 00000000..157713b7 --- /dev/null +++ b/docs/common/user_manual/user_inputs_documentation/User_Inputs_Documentation_RST_Files/UQpyStretch.html @@ -0,0 +1,351 @@ + + + + + + + + + + UQpyStretch — Earthquake Engineering with Uncertainty Quantification documentation + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + +
                + + + +
                + + + + + +
                + +
                + + + + + + + + + + + + + + + + + + + +
                + + + + +
                +
                +
                +
                + +
                +

                UQpyStretch

                +
                +
                burn length

                Burn length of the Markov Chain Monte Carlo algorithm

                +

                Default: 0

                +

                Key in JSON file: burn_in

                +
                +
                +
                +
                jump

                Jump parameter of the Markov Chain Monte Carlo sampling

                +

                Default: 1

                +

                Key in JSON file: jump

                +
                +
                +
                +
                method

                String that defines the MCMC algorithm to be used

                +

                Default: ModifiedMetropolisHastings

                +

                Key in JSON file: method

                +
                +
                +
                +
                # Chains

                Number of chains to be used in the MCMC sampling algorithm

                +

                Default: 1

                +

                Key in JSON file: n_chains

                +
                +
                +
                +
                # Dimension

                Number of parameters to be sampled

                +

                Default: 1

                +

                Key in JSON file: n_dimension

                +
                +
                +
                +
                Scale

                Parameter specific to the Stretch sampling aglorithm

                +

                Default: 2

                +

                Key in JSON file: scale

                +
                +
                +
                + + +
                + +
                +
                + +
                + +
                +

                + © Copyright 2024, The Regents of the University of California. + +

                +
                + + + + Built with Sphinx using a + + theme + + provided by Read the Docs. + +
                +
                +
                + +
                + +
                + + + + + + + + + + + + + + + + + + + + \ No newline at end of file diff --git a/docs/common/user_manual/user_inputs_documentation/User_Inputs_Documentation_RST_Files/UQpySubsetSimulation.html b/docs/common/user_manual/user_inputs_documentation/User_Inputs_Documentation_RST_Files/UQpySubsetSimulation.html new file mode 100644 index 00000000..3e6851a0 --- /dev/null +++ b/docs/common/user_manual/user_inputs_documentation/User_Inputs_Documentation_RST_Files/UQpySubsetSimulation.html @@ -0,0 +1,355 @@ + + + + + + + + + + UQpySubsetSimulation — Earthquake Engineering with Uncertainty Quantification documentation + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + +
                + + + +
                + + + + + +
                + +
                + + + + + + + + + + + + + + + + + + + +
                + + + + +
                +
                +
                +
                + +
                +

                UQpySubsetSimulation

                +
                +
                method

                Reliability analysis method to be used

                +

                Default: SubsetSimulation

                +

                Key in JSON file: method

                +
                +
                +
                +
                Conditional Probabaility

                Conditional probability for each conditional level

                +

                Default: 0.1

                +

                Key in JSON file: conditionalProbability

                +
                +
                +
                +
                Failure Threshold

                Threshold over which it is assume that the simulated system fails

                +

                Default: 0.001

                +

                Key in JSON file: failureThreshold

                +
                +
                +
                +
                Max. Levels

                Maximum number of allowable conditional levels

                +

                Default: 10

                +

                Key in JSON file: maxLevels

                +
                +
                +
                +
                Initial samples

                Initial samples to bootstrap the Subset simulation algorithm

                +

                Default: 1000

                +

                Key in JSON file: initialSamples

                +
                +
                +
                +
                Sampling Method

                Specifies the MCMC sampling agorithm to be used

                +

                Default: MetropolisHastings

                +

                Key in JSON file: samplingMethod

                +
                +

                See also

                +

                MCMC Algorithm

                +
                +
                +
                +
                + + +
                + +
                +
                + +
                + +
                +

                + © Copyright 2024, The Regents of the University of California. + +

                +
                + + + + Built with Sphinx using a + + theme + + provided by Read the Docs. + +
                +
                +
                + +
                + +
                + + + + + + + + + + + + + + + + + + + + \ No newline at end of file diff --git a/docs/common/user_manual/user_inputs_documentation/User_Inputs_Documentation_RST_Files/UserDefinedEDP.html b/docs/common/user_manual/user_inputs_documentation/User_Inputs_Documentation_RST_Files/UserDefinedEDP.html new file mode 100644 index 00000000..58ec7638 --- /dev/null +++ b/docs/common/user_manual/user_inputs_documentation/User_Inputs_Documentation_RST_Files/UserDefinedEDP.html @@ -0,0 +1,315 @@ + + + + + + + + + + UserDefinedEDP — Earthquake Engineering with Uncertainty Quantification documentation + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + +
                + + + +
                + + + + + +
                + +
                + + + + + + + + + + + + + + + + + + + +
                + + + + +
                +
                +
                +
                + +
                +

                UserDefinedEDP

                +
                + + +
                + +
                +
                + +
                + +
                +

                + © Copyright 2024, The Regents of the University of California. + +

                +
                + + + + Built with Sphinx using a + + theme + + provided by Read the Docs. + +
                +
                +
                + +
                + +
                + + + + + + + + + + + + + + + + + + + + \ No newline at end of file diff --git a/docs/genindex.html b/docs/genindex.html index fe96e3ab..ab770cf6 100644 --- a/docs/genindex.html +++ b/docs/genindex.html @@ -40,6 +40,7 @@ + @@ -127,11 +128,6 @@
              • 5. Requirements
              • 6. Bugs & Feature Requests
              -

              Damage and Loss DB

              -

              Technical Manual

              • 1. Technical Manual
              • @@ -258,7 +254,7 @@

                W

                - © Copyright 2023, The Regents of the University of California. + © Copyright 2024, The Regents of the University of California.

                diff --git a/docs/index.html b/docs/index.html index d3e66541..3ffef135 100644 --- a/docs/index.html +++ b/docs/index.html @@ -40,6 +40,7 @@ + @@ -127,11 +128,6 @@
              • 5. Requirements
              • 6. Bugs & Feature Requests
              -

              Damage and Loss DB

              -

              Technical Manual

              • 1. Technical Manual
              • @@ -211,7 +207,7 @@
                -

                Earthquake Engineering with Uncertainty Quantification Application (EE-UQ)

                +

                Earthquake Engineering with Uncertainty Quantification Application (EE-UQ)

                Frank McKenna , Wael Elhaddad , Michael Gardner , Chaofeng Wang , Adam Zsarnóczay

                The Earthquake Engineering with Uncertainty Quantification Application (EE-UQ) (EE-UQ app) is an open-source research application that can be used to predict the response of a building subjected to earthquake events. The application is focused on quantifying the uncertainties in the predicted response, given the uncertainties in models, earthquake loads, and analysis. The computations are performed in a workflow application that will run on either the user’s local machine or on a high-performance computer made available by DesignSafe.

                The Earthquake Engineering with Uncertainty Quantification Application (EE-UQ) is a short course on programming Python, C, and C++ for personal computers (PC) through high-performance computers (HPC). It is designed for engineering students who want to integrate SimCenter Workflow Tools with their research, use and extend their capabilities, and hopefully share their contributions with the broader research community.

                @@ -241,14 +237,9 @@

                Earthquake Engineering with Uncertainty Quantification Application (EE-UQ)6. Bugs & Feature Requests

              -
              +

              Technical Manual

              @@ -268,11 +259,11 @@

              Earthquake Engineering with Uncertainty Quantification Application (EE-UQ)

              -

              Contact

              +

              Contact

              Frank McKenna, NHERI SimCenter, UC Berkeley, fmckenna@berkeley.edu

              -

              References

              +

              References

              AS00

              Ronald. D. Andrus and Kenneth H Stokoe. Liquefaction resistance of soils from shear wave velocity. Journal of Geotechnical and Geoenvironmental Engineering, 126(11):1015–1025, 2000.

              @@ -339,7 +330,7 @@

              References

              - © Copyright 2023, The Regents of the University of California. + © Copyright 2024, The Regents of the University of California.

              diff --git a/docs/objects.inv b/docs/objects.inv index 39e1346d..7be51f15 100644 Binary files a/docs/objects.inv and b/docs/objects.inv differ diff --git a/docs/search.html b/docs/search.html index 5234e672..ed9efeef 100644 --- a/docs/search.html +++ b/docs/search.html @@ -41,6 +41,7 @@ + @@ -130,11 +131,6 @@
            • 5. Requirements
            • 6. Bugs & Feature Requests
            -

            Damage and Loss DB

            -

            Technical Manual

            • 1. Technical Manual
            • @@ -231,7 +227,7 @@

              - © Copyright 2023, The Regents of the University of California. + © Copyright 2024, The Regents of the University of California.

              diff --git a/docs/searchindex.js b/docs/searchindex.js index c1ef0231..676e40b1 100644 --- a/docs/searchindex.js +++ b/docs/searchindex.js @@ -1 +1 @@ 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308,360],"static":[30,280,352,355],"super":[61,166,321],"switch":[14,33,296,297,318,331,340],"throw":[],"transient":[30,336,357],"true":[19,26,29,30,32,33,38,230,233,253,299,333],"try":[26,29,237,290,308,348],"universit\u00e4t":230,"var":[230,345],"void":[29,355],"while":[14,30,32,39,108,112,115,127,131,134,230,239,242,245,246,248,251,252,254,257,261,262,264,265,266,280,291,293,294,296,298,301,326,329,333,334,336,345,346,347,355,357],"zsarn\u00f3czai":[0,1,2,3,4,5,6,7,8,9,10,11,12,13,14,15,16,17,18,19,20,21,22,23,24,25,26,27,28,29,30,31,32,33,34,35,36,37,38,39,40,41,42,43,44,45,46,47,48,49,50,51,52,53,54,55,56,57,58,59,60,61,62,63,64,65,66,67,68,69,70,71,72,73,74,75,76,77,78,79,80,81,82,83,84,85,86,87,88,89,90,91,92,93,94,95,96,97,98,99,100,101,102,103,104,105,106,107,108,109,110,111,112,113,114,115,116,117,118,119,120,121,122,123,124,125,126,127,128,129,130,131,132,133,134,135,136,137,138,139,140,141,142,143,144,145,146,147,148,149,150,151,152,153,154,155,156,157,158,159,160,161,162,163,164,165,166,167,168,169,170,171,172,173,174,175,176,177,178,179,180,181,182,183,184,185,186,187,188,189,190,191,192,193,194,195,196,197,198,199,200,201,202,203,204,205,206,207,208,209,210,211,212,213,214,215,216,217,218,219,220,221,222,223,224,225,226,227,228,229,230,231,232,233,234,235,236,237,238,239,240,241,242,243,244,245,246,247,248,249,250,251,252,253,254,255,256,257,258,259,260,261,262,263,264,265,266,267,268,269,270,271,272,273,274,275,276,277,278,279,280,281,282,283,284,285,286,287,288,289,290,291,292,293,294,295,296,297,298,299,300,301,302,303,304,305,306,307,308,309,310,311,312,313,314,315,316,317,318,319,320,321,322,323,324,325,326,327,328,329,330,331,332,333,334,335,336,337,338,339,340,341,342,343,344,345,346,347,348,349,350,351,352,353,354,355,356,357,358,359,360],"zsarn\u00f3czay20":279,A:[0,13,16,22,23,24,27,29,33,38,41,46,69,75,76,77,78,79,83,87,100,143,146,151,174,180,181,182,183,184,188,192,205,217,220,221,230,232,233,234,236,237,238,239,240,241,244,245,246,247,252,253,254,255,259,261,264,265,278,279,280,282,283,284,285,286,291,292,295,298,299,301,315,318,327,329,330,331,332,333,336,340,346,347,350,351,352,353,355,356,357,358,360],AND:[29,221,232],AS:[29,221],And:[234,242,257,280,294,295,296],As:[13,14,16,32,33,35,39,104,105,106,107,108,109,110,111,112,113,114,115,116,117,118,119,206,234,237,238,239,240,245,247,252,253,254,255,257,262,264,265,266,280,287,288,292,293,294,295,301,305,306,308,329,331,333,336,340,345,352,355,356,357],At:[28,29,30,33,94,231,241,305,306,340],BE:[29,221],BUT:[29,221],BY:[29,221],But:[13,16,301],By:[0,24,33,238,245,253,291,295,297,298,299,305,308,336,340,342,344,345,347,348,350,358],FOR:[29,221],For:[11,13,14,16,18,19,22,23,24,25,26,27,29,30,32,33,34,35,36,58,109,128,163,220,222,230,231,233,234,237,238,239,240,241,242,245,247,252,253,255,256,257,260,262,264,265,266,278,280,282,285,287,291,292,293,294,295,296,297,298,299,300,301,305,306,316,320,327,330,331,333,334,335,336,337,339,340,343,344,346,347,348,350,351,352,354,355,357,359],IF:[29,221,239,252,254,265],IN:[29,221,238,239],INTO:329,IS:[29,221],IT:329,If:[5,18,19,20,22,23,24,33,34,35,36,38,230,232,233,234,239,240,243,246,255,257,258,261,281,288,289,290,291,292,295,299,300,305,306,307,308,311,314,317,320,324,327,330,334,336,340,345,346,347,350,351,352,354,355,357,358,359],In:[13,14,16,18,24,25,26,29,30,32,33,34,35,36,38,83,94,101,102,105,106,112,115,117,124,125,131,134,136,188,230,231,232,233,234,237,238,239,240,241,245,246,247,248,253,254,255,262,264,266,280,285,288,291,292,293,294,295,296,297,298,299,300,301,305,306,307,308,312,317,329,332,333,334,335,336,337,340,342,343,344,345,347,352,354,355,356],It:[3,4,5,6,7,8,12,13,14,16,19,23,29,30,32,33,35,121,122,207,208,220,222,230,232,233,234,238,239,242,245,253,254,257,260,264,266,286,291,299,300,305,306,307,332,333,336,343,346,348,352,355,356,357,360],Its:[247,262],NO:[19,29,32,221,238],NOT:[29,221,299,329,350],Near:360,No:[10,23,26,50,53,70,83,87,101,102,155,158,175,188,192,218,219,238,239,254,266,292,299,327,331,332,345,352,355,360],Not:[29,54,55,81,82,83,84,85,89,90,91,159,160,186,187,188,189,190,194,195,196,305],OF:[29,221],ON:[29,221],OR:[29,221,239,247,254],Of:347,On:[23,35,230,237,253,300,301,305,308,328,332,334,344,355],One:[13,33,83,87,188,192,222,230,238,242,257,285,296,297,299,346],Or:23,SUCH:[29,221],Such:[234,246,248,254,261],THE:[14,29,221,329],THe:[252,280,287],TO:[29,221],That:[13,16,35,232,288,340],The:[0,3,4,5,6,7,8,11,12,13,15,16,17,19,20,22,23,24,26,27,28,29,30,31,32,33,35,38,39,41,42,43,44,45,46,47,48,49,50,51,52,53,54,55,56,57,58,59,60,61,62,63,64,65,66,67,68,69,70,71,72,73,74,75,76,77,78,79,80,81,82,83,84,85,86,87,88,89,90,91,92,93,94,95,96,97,98,99,100,101,102,103,104,105,106,107,108,109,110,111,112,113,114,115,116,117,118,119,120,121,122,123,124,125,126,127,128,129,130,131,132,133,134,135,136,137,138,139,140,141,142,143,144,145,146,147,148,149,150,151,152,153,154,155,156,157,158,159,160,161,162,163,164,165,166,167,168,169,170,171,172,173,174,175,176,177,178,179,180,181,182,183,184,185,186,187,188,189,190,191,192,193,194,195,196,197,198,199,200,201,202,203,204,205,206,207,208,209,210,211,212,213,214,215,216,219,220,221,222,223,224,226,228,229,230,231,232,233,234,236,237,238,239,240,241,242,244,245,246,247,250,251,252,253,254,255,256,257,259,260,261,262,263,264,265,266,278,279,280,282,283,284,285,286,287,288,289,291,292,293,294,295,296,297,298,299,300,301,302,304,305,306,307,308,310,311,313,314,315,316,317,318,319,320,321,323,324,327,329,330,331,332,333,334,335,336,337,338,339,340,342,343,344,345,346,347,348,349,350,351,352,354,355,356,357,358,359,360],Their:[239,244,245,254,259],Then:[35,38,230,233,260,292,293,294,299,355],There:[23,33,101,102,104,123,232,244,259,266,280,282,294,296,305,308,340,346,347,357,358],These:[12,14,15,16,24,33,104,105,106,107,108,109,110,111,112,113,114,115,116,117,118,119,123,125,126,127,128,129,130,131,132,133,136,137,138,206,223,224,226,229,231,232,233,238,239,240,241,245,246,248,252,253,254,255,256,257,261,262,265,278,280,283,286,287,288,289,292,294,296,317,324,327,329,333,340,347,355,357,359],To:[13,14,16,17,19,21,23,24,28,34,35,36,38,230,231,232,233,238,239,245,251,253,266,280,285,290,291,292,295,298,299,300,301,305,306,307,308,319,327,339,344,345,346,347,350,351,355,360],Wills:[33,233,319,321],With:[244,246,259,261,308,320,329,336,352],_0199:360,_1:[230,346],_2:[230,346],_:[13,22,35,222,223,224,225,226,229,230,231,234,242,257,260,305,306,308,315,345,346,354,355,357,359],___:20,__future__:357,__main__:357,__name__:357,_figcustomuq:[],_i:234,_j:231,_k:[230,346],_n:[230,346],_searchresult:351,_w:[],a23:[47,152],a3163:230,a94:230,a_0:[232,336],a_1:[232,336],a_2:[],a_3:[],a_4:[],a_:234,a_n:339,aa:301,aakash:217,aall:224,ab:[30,357,360],abaqu:[],abbrevi:[20,238,357,360],abid:23,abil:[23,33,222,223,224,225,226,229,244,245,259,282,322,324],abl:[33,35,39,237,288,306,329,343,350,351],about:[29,30,32,105,124,231,233,237,247,252,257,261,262,265,266,272,278,280,284,285,287,290,292,297,298,307,308,315,327,330,332,333,334,337,338,340,354,355,356],abov:[19,29,32,35,51,58,62,66,70,156,163,167,171,175,221,230,233,237,238,239,241,242,244,245,253,254,256,257,262,264,266,282,283,287,291,293,294,295,296,297,299,301,305,306,336,339,340,346],abrahamson:[283,285,319,321,360],abscissa:[299,300,301],absecon:238,absenc:[240,255],absolut:[30,33,301,347,357],ac:[238,247],acc:[33,38,286],accel:30,accel_roof_x:[],acceleart:[],acceler:[19,20,30,33,38,39,53,58,67,73,140,158,163,172,178,210,230,232,233,234,242,257,279,283,286,287,292,293,294,295,296,297,298,299,300,301,310,317,323,330,335,336,340,343,345,346,351,352,353,357],accelera:[319,321],accelerogram:289,accelert:[319,321],accelhistoryrecord:30,accept:[23,29,264,291,329,333,345],access:[13,14,16,23,71,97,121,176,202,207,222,237,244,247,253,254,257,261,262,264,266,284,285,307,311,314,315,320,329,330,348],accfil:33,accfile2:33,accomend:285,accommod:[33,64,169,222,230,341,348],accompani:[29,245,246,248,327],accord:[13,18,53,118,137,158,220,238,239,240,245,253,254,255,317,355],accordingli:[245,252,265,280],account:[23,39,222,224,225,226,230,242,245,252,257,279,287,289,292,293,294,298,299,300,335,337,340,345,352,355,356,359],accumul:247,accur:[33,222,230,238,240,241,253,255,299,333,334,346],accuraci:[33,230,233,238,240,253,255,296,297,299,333,345,346,355],achiev:[34,36,119,138,230,231,238,253,329,333,336,352,355],aci318:[44,149],aci:[44,47,149,152],acknowledg:[246,254,261,272,284,360],acm:331,acoust:[69,174],acquir:230,acquisit:13,across:[20,28,29,222,230,238,245,247,253,262,279,280,315,334,347,358],act:[106,112,116,125,131,135,244,259,291,313,351],action:[13,220,238,239,245,247,254,280],activ:[0,245,296,311,314,317,320,324,345,346,355],actual:[13,14,16,54,55,94,159,160,230,238,245,247,253,266,288,299,300,301,305,308,335,336,344,346],ad:[14,35,42,147,222,223,226,228,229,246,257,261,285,300,301,312,314,315,318,322,325,336,340,346,347,350,353,355],adam:[0,1,2,3,4,5,6,7,8,9,10,11,12,13,14,15,16,17,18,19,20,21,22,23,24,25,26,27,28,29,30,31,32,33,34,35,36,37,38,39,40,41,42,43,44,45,46,47,48,49,50,51,52,53,54,55,56,57,58,59,60,61,62,63,64,65,66,67,68,69,70,71,72,73,74,75,76,77,78,79,80,81,82,83,84,85,86,87,88,89,90,91,92,93,94,95,96,97,98,99,100,101,102,103,104,105,106,107,108,109,110,111,112,113,114,115,116,117,118,119,120,121,122,123,124,125,126,127,128,129,130,131,132,133,134,135,136,137,138,139,140,141,142,143,144,145,146,147,148,149,150,151,152,153,154,155,156,157,158,159,160,161,162,163,164,165,166,167,168,169,170,171,172,173,174,175,176,177,178,179,180,181,182,183,184,185,186,187,188,189,190,191,192,193,194,195,196,197,198,199,200,201,202,203,204,205,206,207,208,209,210,211,212,213,214,215,216,217,218,219,220,221,222,223,224,225,226,227,228,229,230,231,232,233,234,235,236,237,238,239,240,241,242,243,244,245,246,247,248,249,250,251,252,253,254,255,256,257,258,259,260,261,262,263,264,265,266,267,268,269,270,271,272,273,274,275,276,277,278,279,280,281,282,283,284,285,286,287,288,289,290,291,292,293,294,295,296,297,298,299,300,301,302,303,304,305,306,307,308,309,310,311,312,313,314,315,316,317,318,319,320,321,322,323,324,325,326,327,328,329,330,331,332,333,334,335,336,337,338,339,340,341,342,343,344,345,346,347,348,349,350,351,352,353,354,355,356,357,358,359,360],adams20:335,adamz:357,adapt:[222,233,239,252,254,265,287,316,318,330,331,333,346],adcirc:[13,245,246],adcirc_exampl:245,adcirc_pwd:245,adcirc_sitepwd:245,adcirc_waterelev:245,add:[14,30,35,38,291,296,298,299,301,305,307,308,320,322,329,336,337,339,340,343,346,350,351,355,356],addfactori:329,addinfo_ruleset:[239,254],addinfo_ruleset_concret:239,addinfo_ruleset_ef:239,addinfo_ruleset_flood:239,addinfo_ruleset_masonri:239,addinfo_ruleset_metavar:[239,254],addinfo_ruleset_mh:239,addinfo_ruleset_njdep:238,addinfo_ruleset_steel:239,addinfo_ruleset_wood:[239,254],addit:[13,16,19,27,29,33,34,35,36,42,147,223,226,229,230,232,237,240,245,246,248,253,255,257,261,278,279,280,285,287,288,289,291,299,300,301,305,306,308,313,314,315,317,319,322,324,329,333,334,336,343,346,355,357,358,360],additin:[],addition:[20,29,222,230,237,257,299,301,321,335,342,344,345,346,352,354,356],address:[23,32,237,238,239,253,264,305,306],ade20k:[238,253],adequ:[33,41,146,333],adher:29,adhes:[68,94,173],adit:[],adjac:[58,163,238,240,255,355],adjust:[100,205,239,240,245,255,355],admin:306,administr:[237,280],adopt:[13,16,234,238,239,245,246,247,248,250,254,259,261,262,266,285,292,293],adress:237,adriat:238,adv:286,advanc:[222,230,244,245,259,262,282,288,296,299,301,315,317,322,324,325,333,336,337,340,342,344,345,346,347,355,356],advantag:[238,261,262,315,336],advengsoft:286,advis:[29,221,230,248,261],advisori:260,ae:[240,255],aerial:[238,239,253,254],aerodynam:[245,323,324],aesthet:20,aff:266,affair:246,affect:[233,238,244,245,260,261,262,266],affili:296,affirm:[238,253],aforement:245,after:[12,20,24,28,30,35,38,106,117,125,136,233,234,238,239,242,253,257,262,264,266,288,291,292,299,300,301,305,307,308,316,318,327,342,344,348,350,351,352,355,356,357,359],ag:[117,136,238,239,254],again:[17,35,232,239,254,262,295,301,308,347],against:[38,222,238,240,253,255,262,264,266,305],agarag:239,agav:[14,23],agaveapi:23,agenc:[241,247,253,254,256,262,265,279,285],aggreg:[20,22,23,26,28,30,32,233,244,259,280,316,345,346],agr1:[206,207,208,209,238,239,241],agr:[238,239],agre:23,agreement:[38,251,264,266,280,296,300],agri:[238,239],agricultur:[206,207,208,209,238,239],ah:[240,255],ah_:355,ahm:360,ahsan:217,ai:[13,222],aid:[13,220,325,344],aim:[13,16,230,333,334],air:[82,84,86,187,189,191],aisc:[42,147,340],aisi:[50,53,155,158],ajai:246,al132020_laura:262,al:[14,39,231,233,262,280,283,295,301,319,321,335,354],alameda:285,alaska:237,albani:238,albeit:[232,253,334],aleator:230,aleatori:[252,265,287],alert:23,alexandro:246,algorithm:[11,13,30,32,222,231,233,238,253,283,299,301,316,324,325,330,331,332,333,336,343,344,346,348,352,355,356],algortihm:332,align:[230,238,253,308,346],all:[0,13,14,15,16,19,20,22,23,24,26,27,28,29,30,32,33,34,35,36,38,53,58,59,64,67,68,70,83,85,90,91,104,105,106,107,108,109,110,111,112,113,114,115,116,117,118,119,121,123,124,125,126,127,128,129,130,131,132,133,134,135,136,137,138,143,158,163,164,169,172,173,175,188,190,195,196,221,222,224,225,226,230,232,233,237,239,241,244,246,247,251,252,253,254,256,261,265,266,279,284,287,291,292,293,294,295,297,299,300,301,305,306,308,309,315,316,320,327,330,331,333,334,339,340,346,347,348,350,351,352,354,355],all_bldg:[],allen:33,allevi:233,alloc:[241,352],alloct:[],allow:[13,14,16,17,29,33,75,76,77,78,79,87,180,181,182,183,184,192,220,222,228,239,241,254,256,280,292,296,298,299,305,306,308,312,315,318,322,329,332,333,334,336,338,339,340,343,346,347,350,351,352,354,355,356,357,359],almost:[112,115,131,134,232,239,254,301],alon:331,along:[33,51,53,67,156,158,172,230,233,238,239,245,246,252,253,257,261,265,278,287,292,296,299,331,332,334,340,346,347,352,355,357],alp:344,alpha:[249,336,339,355],alpha_:249,alpha_c:249,alphabet:307,alphanumer:[238,253],alreadi:[238,239,245,254,261,344],also:[13,14,16,19,23,26,33,34,35,36,51,53,54,122,156,158,159,208,230,232,233,234,238,239,240,242,245,246,247,253,254,255,257,259,261,262,264,266,278,279,280,285,287,288,289,291,292,294,295,296,299,300,301,302,305,306,308,317,321,327,329,331,332,333,334,335,336,340,343,345,346,347,350,351,352,355,356],alt_rom_simulation_boucwen_drift:301,alter:340,altern:[19,35,222,224,225,226,230,245,291,299,300,301,305,306,333,340,343,346,351,355],although:[17,121,122,207,208,239,266,297],alum:234,alwai:[29,230,237,292,300,305,308,333,336,340,342,344,346,352,356],always_xi:33,am:278,amazon:14,ambient:[],ambros:[259,266],amd64:26,amend:239,america:234,american:[245,249,262,319],among:[13,26,230,252,262,265,292,301,334,347,355],amount:[13,101,102,220,230,238,253,346],amp:[90,195],ampl:262,amplitud:[33,355,360],amv2:333,amv:333,an:[4,7,13,14,15,16,18,19,20,22,23,24,26,27,29,30,32,33,34,35,36,38,39,51,53,54,55,104,105,106,107,108,109,110,111,112,113,114,115,116,117,118,119,123,156,158,159,160,206,220,222,224,225,226,228,230,233,234,237,238,239,240,241,242,243,245,247,250,252,253,254,257,258,262,264,265,266,280,281,284,285,286,287,289,290,291,293,294,296,298,299,300,301,303,305,306,307,308,315,318,320,322,323,324,327,329,330,331,332,333,334,336,337,339,340,341,343,344,345,346,347,350,351,352,355,357,359,360],ana:[224,225,226,242,257],anaconda:[],analog:[13,14,16],analys:[33,38,232,244,257,259,279,285,286,287,289,292,296,299,301,313,314,315,340,348,352,355,356],analysi:[8,12,14,15,19,30,32,35,38,39,216,228,232,233,234,238,239,242,244,247,250,253,257,259,262,280,282,285,286,287,295,302,307,310,312,315,318,319,320,321,322,323,325,327,329,330,334,336,340,341,342,343,344,346,348,349,353,356,357,360],analysisadopt:238,analysisdefault:[238,253],analyt:[14,222,230,245,252],analyz:[19,30,33,233,242,257,286,292,296,336],ananlysi:233,anaywai:[305,308],anchor:[68,81,82,83,84,85,89,90,91,94,117,136,173,186,187,188,189,190,194,195,196,279,299,352],anchorag:[53,81,82,83,84,85,89,90,91,107,108,121,122,126,127,158,186,187,188,189,190,194,195,196,207,208,262,279],anchoragebuild:237,andr:[51,53,156,158],andrea:[284,285],andrei:230,andrew:[46,151,246,261],andru:360,angel:[261,295],angl:[42,69,147,174,252],angular_freq:30,ani:[5,13,16,24,26,29,35,57,73,94,107,112,115,126,131,134,142,162,178,218,219,221,233,238,239,240,243,244,245,246,253,254,255,258,259,261,278,281,282,284,288,289,291,292,293,301,311,313,314,315,316,317,320,323,324,327,332,333,334,340,344,346,347,350,352,355,356],anlaysi:343,ann:219,anneal:[54,55,159,160],annual:[238,247],anonym:289,anoth:[13,14,16,220,230,238,253,308,312,333,334,344,346,350],anotherrandomvari:329,ansi:[],answer:[246,261],anticip:[238,240,255,322],anymor:305,anyth:[238,239,254],anywher:[112,131,305,306],anza:234,ao:[240,255],ap:301,apach:[],apart:[67,172,206,207,208,209,230,237,238,239,245],apartmen:237,apawood:239,apex:[238,253],api:[13,14,16,23,35,233,238,253],apivatanagul:233,app:[0,1,2,3,4,5,6,7,8,9,10,11,12,13,14,15,16,17,18,19,20,21,22,23,24,25,26,27,28,29,30,31,32,33,34,35,36,37,38,39,40,41,42,43,44,45,46,47,48,49,50,51,52,53,54,55,56,57,58,59,60,61,62,63,64,65,66,67,68,69,70,71,72,73,74,75,76,77,78,79,80,81,82,83,84,85,86,87,88,89,90,91,92,93,94,95,96,97,98,99,100,101,102,103,104,105,106,107,108,109,110,111,112,113,114,115,116,117,118,119,120,121,122,123,124,125,126,127,128,129,130,131,132,133,134,135,136,137,138,139,140,141,142,143,144,145,146,147,148,149,150,151,152,153,154,155,156,157,158,159,160,161,162,163,164,165,166,167,168,169,170,171,172,173,174,175,176,177,178,179,180,181,182,183,184,185,186,187,188,189,190,191,192,193,194,195,196,197,198,199,200,201,202,203,204,205,206,207,208,209,210,211,212,213,214,215,216,217,218,219,220,221,222,223,224,225,226,227,228,229,230,231,232,233,234,235,236,237,238,239,240,241,242,243,244,245,246,247,248,249,250,251,252,253,254,255,256,257,258,259,260,261,262,263,264,265,266,267,268,269,270,271,272,273,274,275,276,277,278,279,280,281,282,283,284,285,286,287,288,289,290,291,292,293,294,295,296,297,298,299,300,301,302,303,304,305,306,307,308,309,310,311,312,313,314,315,316,317,318,319,320,322,323,324,325,326,327,328,329,330,331,332,333,334,335,336,337,338,339,340,341,342,343,344,345,346,347,348,349,350,351,352,353,354,355,356,357,358,359,360],appar:355,appear:[23,24,42,147,305,308,340,350,351],append:[30,38,237,306,357],appendix:[],appl:305,appli:[16,27,30,33,51,53,73,156,158,178,220,231,232,233,234,238,239,241,243,245,246,252,253,254,255,258,260,261,262,265,266,284,296,300,306,335,336,340,343,347,352],applic:[0,1,2,9,10,13,16,17,18,19,20,21,22,23,24,25,26,28,29,30,31,32,33,34,36,37,38,39,40,41,42,43,44,45,46,47,48,49,50,51,52,53,54,55,56,57,58,59,60,61,62,63,64,65,66,67,68,69,70,71,72,73,74,75,76,77,78,79,80,81,82,83,84,85,86,87,88,89,90,91,92,93,94,95,96,97,98,99,100,101,102,103,104,105,106,107,108,109,110,111,112,113,114,115,116,117,118,119,120,121,122,123,124,125,126,127,128,129,130,131,132,133,134,135,136,137,138,139,140,141,142,143,144,145,146,147,148,149,150,151,152,153,154,155,156,157,158,159,160,161,162,163,164,165,166,167,168,169,170,171,172,173,174,175,176,177,178,179,180,181,182,183,184,185,186,187,188,189,190,191,192,193,194,195,196,197,198,199,200,201,202,203,204,205,206,207,208,209,210,211,212,213,214,215,216,217,218,219,220,221,227,228,230,231,232,233,234,235,236,237,238,239,240,241,242,243,244,245,247,248,249,250,251,252,253,254,255,256,257,258,259,260,262,263,264,265,266,267,268,269,270,271,272,273,274,275,276,277,278,279,280,281,282,283,284,285,286,287,288,289,290,291,292,293,294,295,296,297,298,299,300,301,302,303,305,306,309,311,312,313,314,315,316,317,318,319,320,321,322,324,325,326,327,328,329,330,331,332,333,334,335,336,337,338,339,340,341,342,343,344,345,346,347,348,349,350,351,352,353,354,355,356,357,358,359],applicationagain:[],applicationdata:[24,30,32,33],applict:[],apprais:238,appreci:[246,261,288,289],approach:[13,16,29,222,230,232,238,239,241,242,244,245,247,250,253,254,257,259,261,262,285,286,299,301,333,334,344,346,355],appropri:[27,30,32,104,105,106,107,108,109,110,111,112,113,114,115,116,117,118,119,121,123,124,125,126,127,128,129,130,131,132,133,134,135,136,137,138,206,239,295,298,305,306,308,334],approv:[237,239,305],approx:[],approxim:[59,64,104,105,106,107,108,109,110,111,112,113,114,115,116,117,118,119,121,123,124,125,126,127,128,129,130,131,132,133,134,135,136,137,138,164,169,206,230,231,232,237,238,244,245,247,259,262,279,282,285,286,287,296,299,300,315,317,320,331,332,333,334,345,347,355],apprxim:[],appveyor:35,april:315,apriori:347,apt:[238,239,307],ar:[4,5,6,11,13,14,15,16,18,19,20,22,23,24,26,27,28,29,30,32,33,34,35,36,38,39,41,42,43,44,45,46,47,48,49,50,51,52,53,54,55,56,57,58,59,60,61,62,63,64,65,66,67,68,69,70,71,72,73,74,75,76,77,78,79,80,81,82,83,84,85,86,87,88,89,90,91,92,93,94,95,96,97,98,99,100,101,102,103,104,105,106,107,108,109,110,111,112,113,114,115,116,117,118,119,120,121,122,123,124,125,126,127,128,129,130,131,132,133,134,135,136,137,138,139,140,141,142,143,144,145,146,147,148,149,150,151,152,153,154,155,156,157,158,159,160,161,162,163,164,165,166,167,168,169,170,171,172,173,174,175,176,177,178,179,180,181,182,183,184,185,186,187,188,189,190,191,192,193,194,195,196,197,198,199,200,201,202,203,204,205,206,207,208,209,210,211,212,213,214,215,216,218,219,220,221,222,224,226,228,230,231,232,233,234,236,237,238,239,240,241,242,244,245,246,247,248,249,250,251,252,253,254,255,256,257,259,261,262,263,264,265,266,278,279,280,283,284,285,286,287,288,289,291,292,293,294,295,296,297,298,299,300,301,302,305,306,307,308,310,311,313,314,315,316,317,318,319,320,321,323,324,327,329,330,331,332,333,334,335,336,337,338,339,340,342,343,344,345,346,347,348,349,350,351,352,353,354,355,356,357,360],ara20:262,ara:[245,260,261,262],ara_exampl:245,ara_pw:245,araport:23,arash:360,arbitrari:[222,228,230,238,245,253,313,325],arbitrarili:299,arc:322,arcgi:[238,322],archaic:228,archetyp:[238,244,253,259,282],architectur:[121,122,207,208,238,253,304,315,359,360],archiv:[20,23,26,230,245,246,261,307,327],arduino:[33,292,360],area:[33,41,67,68,69,83,94,104,105,106,107,108,109,110,111,112,113,114,115,116,117,118,119,121,123,124,125,126,127,128,129,130,131,132,133,134,135,136,137,138,146,172,173,174,188,222,233,237,238,239,240,243,245,246,247,253,254,255,258,259,260,261,262,264,266,272,278,279,280,281,283,284,285,286,290,291,297,299,305,306,312,318,320,338,352,353,357,359],areafootprint:33,areasqft:238,arg:[29,357],argc:14,argument:[13,14,16,33,35,339,347],argv:[14,357],aris:[29,221,334,340],arithmet:352,arm64:308,arm:[],armen:360,armi:245,around:[69,116,135,174,254,266,286,296,300,315,333,346,355],arrai:[30,38,347,357],arrang:17,arriv:[296,346],arrow:[28,355],art:[230,238,253,348],articl:[239,334,360],artifactori:35,artifici:[230,262,289],arup:[313,315],arxiv:360,as00:[355,360],asarrai:30,asc:[44,149,233,238,245,249,253,262,293,294,300,340,352,353,356,360],asce16:[245,249,262],asce41:[44,149],asce6:[44,149],asce7:312,asce7_windspe:26,asd:[242,257],asimaki:33,ask:[23,246,253,261,306,327,352,354],asm:233,aspect:[29,45,46,54,55,94,150,151,159,160,246,248,261,262,264,266,320],asphalt:[239,240,254,255],aspir:[244,259,282],ass:222,assem:228,assembl:[33,64,114,133,169,228,232,259,280],asses:320,assess:[3,13,20,25,26,28,31,222,228,230,233,237,238,240,241,245,247,251,253,255,256,259,262,264,272,279,280,284,285,296,301,311,313,315,320,322,324,327,346,352,356,360],assessor:[237,238,240,247,253,255,262,278,285],asset:[6,15,16,19,20,22,23,24,26,28,30,32,33,222,224,225,226,228,241,242,244,245,246,247,257,259,261,262,264,266,272,280,284,285,287,315,319,320,321,322,327],assetrepresentationruleset:[246,261,264],assign:[0,11,19,20,26,28,29,30,32,33,222,233,240,246,247,248,252,253,255,257,260,261,262,264,265,266,283,285,350,351,355],assist:[246,261],assoc:278,associ:[7,14,19,28,67,172,223,226,229,230,237,238,239,241,245,246,247,253,254,256,260,261,262,266,285,329,331,332,335,339,340,345,357],assum:[4,20,33,35,38,46,50,51,53,67,94,97,101,102,104,105,106,107,108,109,110,111,112,113,114,115,116,117,118,119,121,122,151,155,156,158,172,202,206,207,208,230,233,234,237,238,239,241,245,252,253,254,256,265,266,292,294,295,298,300,301,303,305,306,340,347,355,357],assumpt:[33,101,102,230,234,238,239,244,246,248,253,259,261,266,282,288,301,346],assur:[238,240,253,255],asymmetr:[54,159],asymptot:[],at2:[291,351],atc20:[238,245,253],atc:[238,245,253,314,340],atcouncil:[238,245,253],atkinson:[319,321],atl:32,atlant:[32,239,240,242,244,245,247,248,253,254,256,259,261,262,285],atleast_2d:347,atm:355,atmospher:[245,249],attach:[50,53,155,158,222,238,239,241,252,253,254,256,265,266,279],attain:[238,253],attempt:[101,102,232],attenu:[104,105,106,107,108,109,110,111,112,113,114,115,116,117,118,119,206,360],attibut:[239,252],attribut:[14,230,240,241,244,246,247,248,252,255,256,257,259,261,262,264,265,266,278,282,285,300,301,335,345,356],au:[],audienc:[246,248,261],aug:26,augment:[13,16,247,262,285,299],augmentedgarag:[238,253,254],august:262,aup:23,a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rl:[217,246,260,262],chart:[296,298,316],chase:[58,163],check:[23,24,30,35,230,240,242,246,255,257,261,301,305,306,307,308,318,327,339,342,343,344,346,348],checkbox:[35,343],chem:[238,239],chemic:[206,207,208,209,239],chen:[231,360],chevron:[42,147],chi:[33,234,316],childress:[259,266],chill:[80,86,185,191],chiller:[81,186],chimnei:[60,118,137,165,222,279,280],ching2007:231,ching:231,chino:234,chiou:[319,321],chip:[],chl:245,choic:[13,16,27,230,238,239,253,254,306,329,336],choos:[13,14,25,38,222,228,238,291,292,293,295,297,298,306,308,318,336,340,342,344,350,351,352,355,356],chop:[51,53,156,158],chopra:[291,295],chosen:[11,13,14,16,19,25,26,230,232,291,292,295,301,331,332,336,355],christchurch:233,christenson:301,christo:360,chrome:237,church:[206,207,208,209,239,262],ci:[14,23,35,237,259,261,262,266,355,359],circl:[252,265,287,339,350,351],circul:245,circumst:[239,355],citat:238,cite:[14,360],citi:[32,222,233,234,238,239,242,245,246,247,248,253,262,266,278,284,285],citybuild:[238,253],civil:[233,245,249,262,360],cl_c2:242,cl_c5:242,clad:325,clai:[57,162],clang_64:35,clara:280,classic:[232,319,322,353],classif:[19,100,205,222,238,240,247,253,255,262,285],classifi:[143,222,238,239,246,253,254,261,262,264],claudio:246,claus:[221,288,289,346],clean:[38,238,253],clear:[13,230,239,241,254,264,346],clearanc:[54,55,159,160],cli:[10,23],click:[23,35,38,233,237,242,257,291,292,293,294,295,296,297,298,299,300,301,305,306,307,308,316,318,327,340,343,344,350,351,352,355,359],client:35,climat:[238,239,241,254],cline:[38,357],clinic:[206,207,208,209,239],clink:[237,299,300,301],clock:301,clone:[23,34,35,36],close:[14,232,234,238,240,254,255,266,280,284,299,334,345,352,355,357,359],closest:[39,44,149,245,295,324,352],closur:[109,128],cloud:[13,14,16,23,217,307],clue:[],cluster:[234,283,329,334],cm:[33,352,356],cmake:[34,35,36],cmd:306,cmmi:284,cnn:[238,253],co:23,coalit:[13,220],coars:286,coarser:230,coast:[244,245,247,259],coastal:[238,239,241,244,245,246,248,253,254,259,261],coastlin:247,coat:[239,254],coc:23,coco:[238,253],code:[14,23,34,35,36,58,68,104,105,106,107,108,109,110,111,112,113,114,115,116,117,118,119,121,123,124,125,126,127,128,129,130,131,132,133,134,135,136,137,138,163,173,220,221,222,237,238,239,245,246,248,253,254,261,262,264,266,280,283,286,305,308,329,340,357,360],codemaincod:14,codifi:239,codnod:30,coeffici:[94,230,232,286,287,292,318,336,346,355],coher:33,cohes:33,coil:[83,188],coincid:230,col:[44,149],cold:[52,53,80,157,158,185],coliny_pattern_search:332,collabor:[246,261,278,284],collaps:[20,30,32,104,106,116,123,125,135,222,228,279,280,355],colleagu:[288,289,331],collect:[13,14,20,23,26,33,40,145,215,222,233,237,238,239,253,262,266,278,285,315,320,338,359],colleg:[206,207,208,209,239],collet:[],color:[280,299,321,347,352,353,355],column:[19,33,43,46,47,52,106,109,110,111,112,114,115,119,125,128,129,130,131,133,134,138,143,148,151,152,157,230,237,238,253,286,291,292,293,294,295,301,315,316,340,343,345,346,347,352,356,357,358],com10:[206,207,208,209,238,239,241],com1:[206,207,208,209,238,239,241,253,254],com2:[206,207,208,209,238,239,241],com3:[206,207,208,209,238,239,241],com4:[206,207,208,209,238,239,241],com5:[206,207,208,209,238,239,241],com6:[206,207,208,209,238,239,241],com7:[206,207,208,209,238,239,241],com8:[206,207,208,209,238,239,241],com9:[206,207,208,209,238,239,241],com:[23,35,100,205,230,238,239,253,278,343,354,360],combin:[55,81,82,83,84,85,89,90,91,114,133,160,186,187,188,189,190,194,195,196,230,232,241,247,251,252,256,262,265,280,292,315,330,333,352,355],combo:329,combobox:329,come:[13,14,16,223,226,229,230,232,305,308,327],comerci:278,comm:[238,239],comma:[237,330,331,340,345,347,350,351],command:[5,13,16,22,23,24,26,28,30,32,33,34,35,36,38,223,229,291,299,300,301,305,306,308,327,336,340,346,357],commend:[],comment:[238,243,258,288,289,360],commer:239,commerc:245,commerci:[120,139,237,238,247,253,262,278,285],common:[13,14,16,117,136,230,232,238,239,240,253,254,255,262,305,327,355],commonli:[33,238,239,240,292,298,302,333],commun:[0,13,14,16,17,23,29,33,35,222,223,226,229,244,245,246,247,252,254,259,261,262,265,279,280,282,284,285,287,311,314,317,319,320,360],comp_typ:[20,30,32],compact:[42,147],compani:[],companion:[35,238,253,302],compar:[38,39,230,234,251,255,261,264,266,280,292,295,296,299,300,301,306,307,345,346],comparison:[233,234,238,251,253,259,266,280,283,285,299,300],compat:[27,245,299,308,315],compil:[14,33,34,35,36,237],complement:314,complet:[12,13,16,18,20,23,26,28,30,58,101,102,115,134,163,230,233,242,244,257,279,280,282,284,285,291,295,297,299,300,301,307,308,315,327,342,343,344,346,347,354,359],complex:[238,245,253,280,324],compli:355,complianc:[239,254,266],compliant:[35,44,57,58,149,162,163],compliment:[44,149],compon:[13,15,17,20,25,28,30,32,33,35,54,55,58,59,64,81,82,83,84,85,89,90,91,94,100,101,102,104,105,106,107,108,109,110,111,112,113,114,115,116,117,118,119,121,122,123,124,125,126,127,128,129,130,131,132,133,134,135,136,137,138,159,160,163,164,169,186,187,188,189,190,194,195,196,205,206,207,208,209,220,222,228,230,232,239,241,244,252,254,256,259,265,280,282,283,285,287,292,293,294,295,299,300,301,313,314,315,316,320,343,346,355,360],compos:[109,111,128,130],composit:[52,67,106,115,116,125,134,135,157,172],comprehens:[236,245,355],compress:[13,16,69,106,116,125,135,174,340],compressor:[82,187,307],compris:[13,14,29,35,238,253],compromis:230,compuat:332,comput:[1,13,14,16,22,23,28,30,38,94,220,222,228,230,231,233,234,239,240,241,242,245,247,248,249,251,255,256,257,279,280,283,284,285,286,288,289,292,293,294,296,298,299,301,302,304,305,308,315,318,320,321,327,329,330,331,332,333,334,335,340,342,343,344,345,346,347,352,353,355,359,360],computation:[230,231,333,334,335],computedperiod:[],conan:[34,36],conc:[44,149],concaten:285,conceal:[112,131],concentr:[42,147,296,333,343],concept:[1,230,233,261],conceptu:[246,261],concern:[105,124,330,332,346],conclus:[29,218,219,284,305,308],concret:[38,44,45,46,47,53,57,64,67,110,112,117,120,129,131,136,139,143,149,150,151,152,158,162,169,172,220,232,238,247,251,278,285,310,312,315,353],concurr:[26,30,33],cond:[55,160],condit:[1,29,30,33,39,50,53,57,58,59,64,68,69,70,75,76,77,78,79,81,82,83,84,85,87,89,90,91,94,97,104,105,106,107,108,109,110,111,112,113,114,115,116,117,118,119,155,158,162,163,164,169,173,174,175,180,181,182,183,184,186,187,188,189,190,192,194,195,196,202,206,221,222,230,234,257,260,287,291,292,295,312,325,345,346,352,353,355,356],condo:[237,238],condominium:[206,207,208,209,237],conduct:[23,230,233,238,241,242,244,245,251,253,257,259,261,264,266,298,336,352,355,356],cone:245,confer:[233,279],conferenc:0,confid:[238,253,266,300,316],config:[34,35,36,54,55,159,160],configur:[6,8,11,22,23,24,26,28,30,32,33,34,35,36,233,239,241,242,254,256,257,279,286,292,293,294,295,299,316,343,353],configureandrunuq:329,confin:[44,149,244,247,259,355],confirm:[42,54,64,147,159,169,308],conflict:29,conform:[44,149,340],confront:333,confus:[238,253],conjunct:[16,238,253],connect:[41,52,62,66,108,109,112,115,127,128,131,134,146,157,167,171,222,224,225,226,232,233,238,239,241,253,254,256,279,280,293,294,299,301,315,340],conquer:336,consent:23,consequ:[13,14,35,54,55,68,75,76,77,78,79,94,146,147,148,149,150,151,152,153,154,155,156,158,159,160,162,163,164,167,169,171,172,173,174,175,178,180,181,182,183,184,186,187,188,189,190,192,194,195,196,202,206,207,208,209,211,212,213,222,228,284,305,308,313,315,322,331,333,339,345,360],consequenti:[29,221],conserv:[230,238,239,240,253,254,255,335],consid:[33,38,39,46,101,102,104,105,106,107,108,109,110,111,112,113,114,115,116,117,118,119,122,151,206,208,230,233,234,238,239,245,247,252,254,255,259,260,264,265,266,278,279,286,287,291,292,295,297,298,299,300,301,302,319,321,335,342,343,344,345,346,355,358,359],consider:[233,244,250,259,263,280,282],consist:[14,19,29,51,53,64,114,117,133,136,156,158,169,230,233,234,239,241,247,253,254,256,257,262,266,280,285,299,301,334,343,347,355],consol:33,consolid:8,constant:[29,230,291,292,295,340,345,347],constitut:33,constrain:[230,247,291,343],constraint:[30,33,230,233,241,355],constrast:[233,245],constrmateri:[247,285],construct:[14,19,30,33,47,50,51,53,57,58,59,62,65,66,67,68,69,70,72,73,75,76,77,78,79,81,82,83,84,85,87,89,90,91,94,97,100,104,105,106,107,108,109,110,111,112,113,114,115,116,117,118,119,121,123,124,125,126,127,128,129,130,131,132,133,134,135,136,137,138,152,155,156,158,162,163,164,167,170,171,172,173,174,175,177,178,180,181,182,183,184,186,187,188,189,190,192,194,195,196,202,205,206,207,208,209,222,232,238,239,240,244,245,246,247,248,253,254,259,261,262,264,266,279,285,286,294,331,333,334,340,346,360],consult:[240,255],consum:[13,220,230,334],cont:[],contact:[33,238,311,314,315,317,320,324,353],contai:29,contain:[7,10,13,15,18,19,22,23,29,34,35,36,109,128,220,226,234,237,238,240,245,246,253,255,261,278,291,294,295,298,299,305,306,307,308,327,329,330,331,337,338,340,345,346,347,350,351,355,357],contdmgfnid:238,contemporari:[240,254],content:[18,28,33,94,97,121,122,202,207,208,241,278,291,295,327,329,346],contentcost:238,contermin:352,context:[13,246,248,261,284],contin:222,continent:33,continu:[26,33,35,47,143,152,230,237,239,241,246,252,253,254,256,259,261,265,287,316,346],continuingeduc:239,continuousdesign:[],contour:[319,321,333],contract:[29,221,292,332,355],contrast:[13,234,253,266,280,284,285],contribut:[219,230,232,244,246,247,259,261,262,282,284,285,311,314,317,320,324,335,345,360],contributor:[29,221],control:[13,14,16,86,90,191,195,222,228,230,231,247,261,291,295,301,325,336,340,347,352,356,359],conu:233,convei:[93,198],conveni:[22,266,315,347,350,351],convent:[118,137,143,233,239,254,317,333,334,347],convention:[45,150,230,346],converg:[12,30,222,224,225,226,231,232,238,253,331,332,333,334,336,340],convergencetest:301,convers:[238,245,246,253],convert:[20,33,230,238,242,245,249,253,257,279,283,315],convolut:[238,253],cool:[86,191],cooper:286,coord:[],coordiant:245,coordin:[13,19,33,220,228,238,240,253,255,262],copi:[13,16,35,38,44,51,53,149,156,158,242,257,291,295,305,308,346],copular:339,copyfil:[13,16],copyright:[29,288,289,299,300,360],corbel:[109,128],core:[29,222,223,224,225,226,229,238,242,246,253,257,261,285],corei:219,corel:355,cori:283,corner:[55,160,238,253,279,280,296,305,307,308,343,355],corp:245,correa:[217,239,241,246,247,254,259,261,262,266],correct:[24,39,40,232,237,238,266,301,305,308,320,327,329],correctli:[305,308,309],correl:[222,223,224,225,226,229,230,233,238,253,266,289,292,297,310,316,318,319,321,323,337,339,340,342,344,345,346,347,352,355],correlogram:234,correspoind:285,correspond:[3,4,5,7,8,11,13,14,15,26,30,32,42,147,222,228,230,233,238,239,241,252,253,254,256,261,264,265,266,279,286,287,291,292,293,294,296,298,299,301,313,320,327,329,330,331,333,334,336,340,342,343,344,345,346,347,351,352,355,359],correspondingli:355,corrug:[114,133],corrupt:327,cost:[3,20,30,32,41,42,43,44,46,47,48,49,50,51,53,54,55,57,59,66,67,68,69,70,73,75,76,77,78,79,81,82,83,84,85,87,89,90,91,94,97,146,147,148,149,150,151,152,153,154,155,156,158,159,160,162,163,164,167,169,171,172,173,174,175,178,180,181,182,183,184,186,187,188,189,190,192,194,195,196,202,206,207,208,209,211,212,213,222,228,230,233,237,238,241,257,280,284,315,334],could:[29,223,226,229,233,238,242,243,253,257,258,259,266,281,285,290,291,293,294,295,296,297,299,301,307,327,342,344,356],council:[238,245,253,262],count:[30,238,241,253,355],counter:241,counterweight:279,counti:[222,239,240,244,245,247,248,253,254,255,256,259,261,262,266,278,280,285],countri:239,coupl:[13,77,182,220,222,228,241,244,245,251,256,259,280,282,344,355],coupled_edp:[26,30,32],coupon:[],cours:[232,239,285,291,305,306,360],courtesi:[33,245,292],cov:[291,292,355],covari:[222,230,234,316,318,334],covariancematrixlist:347,covariancemultiplierlist:347,cove:32,cover:[60,67,107,118,126,137,142,165,172,222,230,238,239,240,241,245,253,254,255,262,288,293,294,299,346,352,355,360],coverag:[244,280,299,352],covid:[0,266],cox:[245,280],cpp:29,cpt:355,cpu:[238,242,257,286],cr:33,cr_1:[],cr_2:[],crack:[55,106,116,125,135,160,279,280],crai:283,cramer:[230,299,346],cramervonmis:[230,346],crash:290,creat:[6,7,13,14,15,16,22,23,26,27,33,34,35,36,38,44,149,222,223,224,225,226,228,229,232,237,238,239,243,244,245,246,253,258,259,261,262,281,290,291,293,296,298,299,305,306,307,308,310,312,313,320,323,325,327,329,333,335,336,337,340,345,351,353,355,357,359],createbim:26,createedp:26,createev:26,createlaunchertask:23,createrunn:329,createsam:26,creation:[244,259,282,298],creator:35,credenti:[14,352],credibl:340,crippl:279,criteria:[30,42,147,332,336,352,355,356],criterion:332,critial:[238,253],critic:[101,102,247,253,262,266,285,355],crop:33,cross:[13,14,16,83,188,230,234,238,239,240,243,254,255,258,259,294,297,299,346],crr:355,crr_:355,crude:33,crustal:33,cs:356,cshl:[238,239],csr:355,csv:[3,22,24,26,28,33,233,237,242,257,278,279,293,294,296,315,319,321,340,343,345,351,352],csv_to_bim:[26,30,32,33],cth:[355,360],ctrl:[23,299,300,301],cube:38,cumbersom:[230,355],cumul:[222,241,256,266,298,300,301,316,333],curat:[239,254,261],curr_drift:30,currenc:20,currenli:[],current:[13,14,16,27,30,35,42,147,230,232,233,234,239,241,243,244,248,253,254,256,258,259,282,292,299,300,301,305,306,310,315,316,318,319,323,329,330,331,334,336,339,340,341,343,344,346,347,348,354,355,356],curtain:[46,56,112,131,151,161],curv:[101,102,104,105,106,107,108,109,110,111,112,113,114,115,116,117,118,119,206,230,232,233,241,264,286,300,340,343,355],custom:[13,19,25,27,30,32,35,222,228,230,239,245,301,315,316,322,324],custompi:[310,319,323],customuq:316,cut:142,cvm:33,cwd:38,cwe:325,cwh:[],cyberinfrastructur:288,cycl:355,cyclic:355,cyclon:[245,262],cyvers:23,d1:[293,352],d4:253,d5:299,d7:[238,253],d:[44,69,100,101,102,104,105,106,107,108,109,110,111,112,113,114,115,116,117,118,119,149,174,205,206,222,223,224,225,226,227,228,229,230,231,233,238,239,241,245,247,253,254,256,257,259,262,265,266,279,280,283,285,294,301,305,319,330,331,333,345,346,360],d_1:230,d_2:230,d_:[230,352],d_r:355,d_rg_o:355,dabaghi:[222,224,225,226,302,354,360],dabahi:14,dai:[0,305,308],daili:253,dakota:[0,1,2,3,4,5,6,7,8,9,10,11,12,13,14,15,16,17,18,19,20,21,22,23,24,25,26,27,28,29,30,31,32,33,34,35,36,37,38,39,40,41,42,43,44,45,46,47,48,49,50,51,52,53,54,55,56,57,58,59,60,61,62,63,64,65,66,67,68,69,70,71,72,73,74,75,76,77,78,79,80,81,82,83,84,85,86,87,88,89,90,91,92,93,94,95,96,97,98,99,100,101,102,103,104,105,106,107,108,109,110,111,112,113,114,115,116,117,118,119,120,121,122,123,124,125,126,127,128,129,130,131,132,133,134,135,136,137,138,139,140,141,142,143,144,145,146,147,148,149,150,151,152,153,154,155,156,157,158,159,160,161,162,163,164,165,166,167,168,169,170,171,172,173,174,175,176,177,178,179,180,181,182,183,184,185,186,187,188,189,190,191,192,193,194,195,196,197,198,199,200,201,202,203,204,205,206,207,208,209,210,211,212,213,214,215,216,217,218,219,220,221,222,223,224,225,226,227,228,229,230,231,232,233,234,235,237,238,239,240,241,242,243,244,245,246,247,248,249,250,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94,296,304,305,355],disintegr:[106,116,125,135],disk:[291,295,346],dismiss:355,disp:[33,357],disp_x:[],dispers:[54,64,67,81,82,83,84,85,89,90,91,94,159,169,172,186,187,188,189,190,194,195,196,279,287],dispfil:33,dispfile2:33,displ:357,displac:[20,104,105,106,107,108,109,110,111,112,113,114,115,116,117,118,119,128,136,206,232,279,291,292,296,298,299,301,310,336,340,353,357],displai:[13,14,16,26,230,238,245,253,291,292,293,294,295,296,298,299,300,305,308,316,318,338,346,352,355,357,358,359],dispos:[],disregard:300,disrupt:222,dissip:232,distanc:[33,39,104,105,106,107,108,109,110,111,112,113,114,115,116,117,118,119,206,230,234,238,253,283,293,294,295,312,346,352,353,354,356],distant:233,distassetmunicip:247,distbuiltyear:[247,285],distinct:[238,253,280,295],distinctli:29,distinguish:[101,102,238],distort:[238,253],distribt:[],distribut:[5,14,20,29,30,32,33,38,80,86,92,108,114,127,133,185,191,197,221,222,223,224,225,226,228,229,230,231,233,234,238,241,247,251,252,253,256,257,262,264,265,266,279,280,285,286,287,288,291,292,294,295,298,301,316,320,325,329,330,331,332,333,337,340,344,345,346,347,350,351,355],distributor:308,district:247,div:30,diverg:266,divers:[13,16,261,262,352],divid:[230,232,334,336,340,346,347,348],divis:[264,357],dj:234,dk14:[354,360],dl:[13,15,16,19,20,23,26,27,28,30,32,216,242,257,294,307,315,322],dl_and_cdf_lc:257,dl_c2:242,dl_c5:242,dl_calcul:26,dl_method:[26,30,32],dl_summari:22,dld:228,dll:[],dm:[3,19,22,23,26,28,30,32,33,242,257],dm_:22,dmg:308,dmg_level:266,doc:283,doc_version_ac:246,dockabl:359,docker:23,doctor:284,document:[0,1,2,3,4,5,6,7,8,9,10,11,12,13,14,15,16,17,18,19,20,21,22,23,24,25,26,27,28,29,30,31,32,33,34,35,36,37,38,39,40,41,42,43,44,45,46,47,48,49,50,51,52,53,54,55,56,57,58,59,60,61,62,63,64,65,66,67,68,69,70,71,72,73,74,75,76,77,78,79,80,81,82,83,84,85,86,87,88,89,90,91,92,93,94,95,96,97,98,99,100,101,102,103,104,105,106,107,108,109,110,111,112,113,114,115,116,117,118,119,120,121,122,123,124,125,126,127,128,129,130,131,132,133,134,135,136,137,138,139,140,141,142,143,144,145,146,147,148,149,150,151,152,153,154,155,156,157,158,159,160,161,162,163,164,165,166,167,168,169,170,171,172,173,174,175,176,177,178,179,180,181,182,183,184,185,186,187,188,189,190,191,192,193,194,195,196,197,198,199,200,201,202,203,204,205,206,207,208,209,210,211,212,213,214,215,216,217,218,219,220,221,222,223,224,225,226,227,228,229,230,231,232,233,234,235,236,237,238,239,240,241,242,243,244,245,246,247,248,249,250,251,252,253,254,255,256,257,258,259,260,261,262,263,264,265,266,267,268,269,270,271,272,273,274,275,276,277,278,279,280,281,282,283,285,286,287,288,289,290,291,292,293,294,295,296,297,298,299,300,301,302,303,304,305,306,307,308,309,310,311,312,313,314,315,316,317,318,319,320,321,322,323,324,325,326,327,328,329,330,331,332,333,334,335,336,337,338,339,340,341,342,343,344,345,346,347,348,349,350,351,352,353,354,355,356,357,358,359,360],doe:[24,29,32,41,42,43,46,146,147,148,151,234,238,244,245,250,251,259,266,291,292,300,305,327,336,337,340,344,346,350,351,352,355,356],dof1:357,dof2:357,dof:[4,30,291,351,357],dofmap:[26,30],doi:[217,238,241,246,253,259,261,262,266,278,280,283,284,286,299,346,352,360],domain:[13,220,230,238,283,291,324,331,332,333,334,346,352],domest:[80,185],domin:[48,49,153,154,230,238,247,253,262,266,284,285,335,345],don:[291,299,355],done:[13,14,16,34,35,36,38,222,242,257,291,292,293,294,296,301,329,340,347,350,351,352,355,356],door:[51,53,108,127,156,158,238,239,241,253,262,279,280],dorayleigh:30,dormitori:[206,207,208,209],dot:[30,232,252,265,287,299,300,336,347,352],doubl:[29,42,46,51,53,147,151,156,158,241,305,308,329,355],doublespinbox:329,doubt:[305,308],dover:232,down:[13,14,16,26,29,51,53,156,158,224,226,237,245,261,279,280,291,292,295,305,306,331,333,334,336,339,340,348,349,352,354,357,359],download:[0,1,2,3,4,5,6,7,8,9,10,11,12,13,14,15,16,17,18,19,20,21,22,23,24,25,26,27,28,29,30,31,32,33,34,35,36,37,38,39,40,41,42,43,44,45,46,47,48,49,50,51,52,53,54,55,56,57,58,59,60,61,62,63,64,65,66,67,68,69,70,71,72,73,74,75,76,77,78,79,80,81,82,83,84,85,86,87,88,89,90,91,92,93,94,95,96,97,98,99,100,101,102,103,104,105,106,107,108,109,110,111,112,113,114,115,116,117,118,119,120,121,122,123,124,125,126,127,128,129,130,131,132,133,134,135,136,137,138,139,140,141,142,143,144,145,146,147,148,149,150,151,152,153,154,155,156,157,158,159,160,161,162,163,164,165,166,167,168,169,170,171,172,173,174,175,176,177,178,179,180,181,182,183,184,185,186,187,188,189,190,191,192,193,194,195,196,197,198,199,200,201,202,203,204,205,206,207,208,209,210,211,212,213,214,215,216,217,218,219,220,221,222,223,224,225,226,227,228,229,230,231,232,233,234,235,236,237,238,239,240,241,242,243,244,245,246,247,248,249,250,251,252,253,254,255,256,257,258,259,260,261,262,263,264,265,266,267,268,269,270,271,272,273,274,275,276,277,278,279,280,281,282,283,284,285,286,287,288,289,290,291,292,293,294,295,296,297,298,299,300,301,302,303,304,305,306,309,310,311,312,313,314,315,316,317,318,319,320,321,322,323,324,3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50,352,355],editor:[23,29],edp:[3,5,12,13,14,15,16,22,23,26,27,28,30,32,38,216,222,228,242,244,250,252,257,259,265,287,291,292,295,296,297,298,299,300,301,302,310,312,313,315,319,321,323,332,336,337,340,343,345,346,353,359],edp_1:33,edp_:22,edp_spec:[26,30,33],edp_typ:30,edplengthslist:347,edpnameslist:347,edpspec:[26,30,33],edu1:[206,207,208,209,238,239,241],edu2:[206,207,208,209,238,239,241],edu:[0,1,2,3,4,5,6,7,8,9,10,11,12,13,14,15,16,17,18,19,20,21,22,23,24,25,26,27,28,29,30,31,32,33,34,35,36,37,38,39,40,41,42,43,44,45,46,47,48,49,50,51,52,53,54,55,56,57,58,59,60,61,62,63,64,65,66,67,68,69,70,71,72,73,74,75,76,77,78,79,80,81,82,83,84,85,86,87,88,89,90,91,92,93,94,95,96,97,98,99,100,101,102,103,104,105,106,107,108,109,110,111,112,113,114,115,116,117,118,119,120,121,122,123,124,125,126,127,128,129,130,131,132,133,134,135,136,137,138,139,140,141,142,143,144,145,146,147,148,149,150,151,152,153,154,155,156,157,158,159,160,161,162,163,164,165,166,167,168,169,170,171,172,173,174,175,176,177,178,179,180,181,182,183,184,185,186,187,188,189,190,191,192,193,194,195,196,197,198,199,200,201,202,203,204,205,206,207,208,209,210,211,212,213,214,215,216,217,218,219,220,221,222,223,224,225,226,227,228,229,230,231,232,233,234,235,236,237,238,239,240,241,242,243,244,245,246,247,248,249,250,251,252,253,254,255,256,257,258,259,260,261,262,263,264,265,266,267,268,269,270,271,272,273,274,275,276,277,278,279,280,281,282,283,284,285,286,287,288,289,290,291,292,293,294,295,296,297,298,299,300,301,302,303,304,305,306,307,308,309,310,311,312,313,314,315,316,317,318,319,320,321,322,323,324,325,326,327,328,329,330,331,332,333,334,335,336,337,338,339,340,341,342,343,344,345,346,347,348,349,350,351,352,353,354,355,356,357,358,359,360],educ:[222,238],ee:[0,1,2,3,4,5,6,7,8,9,10,11,12,13,15,16,17,18,19,20,21,22,23,24,25,26,27,28,29,30,31,32,33,34,35,36,37,38,39,40,41,42,43,44,45,46,47,48,49,50,51,52,53,54,55,56,57,58,59,60,61,62,63,64,65,66,67,68,69,70,71,72,73,74,75,76,77,78,79,80,81,82,83,84,85,86,87,88,89,90,91,92,93,94,95,96,97,98,99,100,101,102,103,104,105,106,107,108,109,110,111,112,113,114,115,116,117,118,119,120,121,122,123,124,125,126,127,128,129,130,131,132,133,134,135,136,137,138,139,140,141,142,143,144,145,146,147,148,149,150,151,152,153,154,155,156,157,158,159,160,161,162,163,164,165,166,167,168,169,170,171,172,173,174,175,176,177,178,179,180,181,182,183,184,185,186,187,188,189,190,191,192,193,194,195,196,197,198,199,200,201,202,203,204,205,206,207,208,209,210,211,212,213,214,215,216,217,218,219,220,221,223,224,225,226,227,228,229,230,231,232,233,234,235,236,237,238,239,240,241,242,243,244,245,246,247,248,249,250,251,252,253,254,255,256,257,258,259,260,261,262,263,264,265,266,267,268,269,270,271,272,273,274,275,276,277,278,279,280,281,282,283,284,285,286,287,288,289,290,291,292,293,294,295,296,297,299,300,301,302,303,304,305,306,307,308,309,310,311,312,313,314,315,316,317,318,319,320,322,323,324,325,326,327,328,329,330,331,332,333,334,335,336,337,338,339,340,341,342,343,344,345,346,347,348,349,350,351,352,353,354,355,356,357,358,359],ee_uq:311,eeuq:[222,224,225,226,298,299,346],eeuq_app:230,ef_attri:239,effect:[104,105,106,107,108,109,110,111,112,113,114,115,116,117,118,119,125,142,143,206,222,224,225,226,230,231,232,233,237,244,245,247,250,251,259,266,283,285,291,295,301,306,316,333,335,345,355,360],effici:[104,105,106,107,108,109,110,111,112,113,114,115,116,117,118,119,133,206,222,228,230,233,237,238,239,241,242,245,256,257,282,292,296,301,315,318,320,324,333,334,335,343,344,355],efficiendet:253,efficientdet:[238,253],effort:[0,14,230,246,248,259,261],eg:318,egg:238,eig11:[],eig12:[],eig1:[],eig21:[],eig22:[],eig2:[],eigdata:[],eigen:[30,343],eigenmod:30,eigenvalu:[291,296,301,316,343],eigenvector:232,eignevalu:343,einv:[],either:[13,14,16,23,29,58,70,81,82,83,84,85,89,90,91,101,102,110,129,163,175,186,187,188,189,190,194,195,196,233,245,253,266,333,334,337,339,340,344,345,346,347,352,354,355,358,359,360],eject:308,el2:[],el:[38,224,225,226,298,357],elabor:333,elaps:301,elast:[30,38,232,292,301,340],elastic_random:[292,355],elasticbeamcolumn:291,elasticisotrop:[33,302,355],elastictruss:[],elasto:283,elcentro:351,eldr:335,electr:[93,121,122,198,207,208,241,279],electron:94,element:[8,12,13,14,16,17,30,35,109,110,111,114,117,121,128,129,130,133,136,207,216,230,232,233,282,286,291,292,298,301,347,353,355,357,359],element_tag:30,elementari:238,elementtag:291,eletag1:357,eletagn:357,elev:[58,74,121,122,163,179,207,208,222,238,239,240,241,245,253,255,279,280],elevationlowestfloor:238,elevationr0:238,elevationr1:238,elevunit:238,elf:[294,340],elfparamet:[294,296,340],elgam:360,elhad:237,elhaddad:[0,1,2,3,4,5,6,7,8,9,10,11,12,13,14,15,16,17,18,19,20,21,22,23,24,25,26,27,28,29,30,31,32,33,34,35,36,37,38,39,40,41,42,43,44,45,46,47,48,49,50,51,52,53,54,55,56,57,58,59,60,61,62,63,64,65,66,67,68,69,70,71,72,73,74,75,76,77,78,79,80,81,82,83,84,85,86,87,88,89,90,91,92,93,94,95,96,97,98,99,100,101,102,103,104,105,106,107,108,109,110,111,1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8,241,253,256,257,293,294,296,299,301,305,306,307,315,316,318,327,328,334,337,340,342,343,344,346,352,356,357,359],ertugrul:261,es:352,esampl:38,esdu02:[245,249],esdu:[245,249],especi:[34,36,118,137,230,244,259,266,282,317,344,355],essenc:[101,102],essenti:[118,137,238,296,300],essentialclass:238,establish:[64,169,222,238,239,240,245,253,255,262,334,355],estat:278,estim:[3,12,14,15,19,20,30,32,121,122,207,208,222,228,233,234,237,239,242,244,245,246,247,248,250,251,252,253,254,257,259,260,261,262,263,264,265,266,272,280,284,285,287,291,292,300,301,313,315,316,318,322,330,331,333,334,335,342,344,345,346,347,355],estuari:245,et:[14,39,231,233,262,280,283,295,301,319,321,335,354],eta_j:234,etab:[],etc:[12,13,14,16,94,230,237,238,241,243,253,258,301,340,350],eu:14,euclidean:343,ev:[239,254],eval:[329,332,347],evalu:[33,104,105,106,107,108,109,110,111,112,113,114,115,116,117,118,119,206,222,224,225,226,230,231,233,244,245,247,259,264,265,279,296,297,298,301,317,320,325,331,332,333,334,345,346,347,352,353,357,360],evalut:252,even:[29,118,137,221,232,262,266,301,305,327,342,344],evenli:334,event:[3,4,5,8,11,12,13,14,15,16,20,22,23,26,28,29,30,32,33,38,39,104,105,106,107,108,109,110,111,112,113,114,115,116,117,118,119,206,216,221,222,224,225,226,228,232,233,234,237,242,244,245,252,257,259,261,262,265,266,282,284,285,287,288,291,297,302,312,313,315,319,321,325,327,333,336,338,340,350,351,352,353,354,355,356,357,359,360],event_tim:[26,30],eventclassif:[30,32,33],eventgrid:[19,26,33,242,257],eventid:26,eventu:[259,315,355],ever:[13,29,220],everi:[15,20,23,28,30,231,238,239,254,283,299,300,327,328,330,331,336,340,347,350,351],every_r:[30,32,33],everyth:233,everytim:[305,308],evolut:[330,355],evolv:[239,245,246,254,261,262],evrei:35,evt:[33,38,216,291,292,293,294,295,296,297,298,299,300,301,340,353,359],ew:[50,53,155,158],ex1b:38,ex:[230,306,307,308,328],exact:[230,300,301,308,342,344,346],exactli:[288,299,346,352],exam:245,examin:[230,242,257,264,295],exampl:[13,14,19,20,21,22,23,24,26,29,30,32,33,38,39,121,122,207,208,220,222,230,233,238,239,240,241,252,253,254,255,256,257,265,279,284,286,290,291,292,293,294,295,296,297,298,299,300,301,307,308,315,317,318,320,324,325,327,329,330,331,334,340,343,344,345,346,347,350,351,352,353,355,356,357,360],example1:[],example2:[],example_eq:30,example_hu:32,example_result:242,exce:[230,233,291,300,345,346,352],exceed:[233,257,262,266,291,299,300,301,333,342,344],except:[29,104,106,113,123,125,132,230,237,239,266,291,292,295,333,340,343],excercis:237,excess:[33,233,292,333,355],excit:[222,299,300,301,345,346],exclud:[26,28,58,163,206,207,208,209,238,253,298,345],exclus:[44,100,149,205],excut:[],exec:14,execut:[5,12,13,15,16,19,23,24,26,28,30,32,33,35,238,242,244,245,246,248,253,254,257,259,261,293,294,299,305,306,307,308,313,333,336,346,347,348,355],exemplari:[29,221],exercis:[0,40,259,266,280,285,291,295,347],exhaust:[14,345],exhibit:[44,149,279,331],exist:[13,14,16,33,35,38,58,163,222,224,225,226,228,230,238,245,247,261,262,284,285,299,310,316,318,319,322,323,325,327,340,346,350,351,355],existingpeer_ev:26,existingsimcenterev:26,exit:[23,305,306,308,359],exp:[230,234,339,347],expand:[228,238,244,246,253,257,259,261,264,282,333],expans:[86,191,230,244,259,282,310,316,323,333],expect:[4,15,39,41,83,87,114,133,146,188,192,230,234,238,240,241,242,251,253,255,256,257,264,266,279,299,301,343,345,346,347],expens:[230,231,288,296,317,320,333,334,335,346],experi:[15,222,245,262,280,316,318,323,330,331,346,347],experiment:[13,14,228,317,324,330,335,345],expert:[219,222,224,225,226,325],expertis:222,explain:[26,257,264,266,301,329,345,347,355],explan:[239,246,248],explicit:[29,245],explicitli:[232,233,244,247,259,262,291,324,339,344],exploit:230,explor:[242,244,246,248,253,259,261,262,266,280,282,330,352,355,359],expnum:347,expon:346,exponenti:[230,234,301,316,346],expos:[240,242,244,247],exposur:[233,237,238,239,241,245,247,249,256,280],expr:[291,357],express:[6,29,104,105,106,107,108,109,110,111,112,113,114,115,116,117,118,119,206,218,219,221,237,244,245,249,282,284,322,334,336,340,355],extecc_x:[],extecc_z:[],extend:[13,30,51,53,156,158,220,222,228,233,238,239,244,245,246,248,254,259,261,262,280,291,305,306,308,313,315,320,324,336,355,360],extens:[1,13,16,29,35,101,102,105,115,124,134,230,243,244,245,246,258,259,261,262,279,280,282,305,306,350,351,352,354],extent:[105,117,124,136,245,266],exterior:[50,51,58,61,112,116,119,122,131,135,138,155,156,163,166,208,239,241,254,279,280,294,340],exteriorfinish:238,extern:[14,222,230,305,307,308,313,315,322,352,359],extra:[30,320,335,343,345],extract:[230,237,238,242,253,257,298,305,306,307,322,323,327],extractiung:237,extractpga:26,extrapol:[230,299,355],extrem:[245,247,261,262,266,334],f5:35,f:[23,44,46,69,75,76,77,78,79,83,87,100,149,151,174,180,181,182,183,184,188,192,205,230,238,253,278,284,314,330,331,333,339,346,355,360],f_:[230,333,355],f_y:344,f_yield:[30,33],facad:[238,253],facadepars:[246,261],face:[44,149,230,238,247,253],facil:[104,105,106,107,108,109,110,111,112,113,114,115,116,117,118,119,140,210,247,262,285,288,298,317],facilit:[13,16,33,230,262,280,284,298,308,314,315,334],facilitei:239,fact:[14,101,102,230,232,239,254,266,280],factor:[19,30,42,101,102,104,105,106,107,108,109,110,111,112,113,114,115,116,117,118,119,147,206,230,248,249,251,266,278,291,292,294,295,299,301,332,343,347,350,351,352,355,356],factorec:291,factori:[206,207,208,209,239,329],faculti:[223,226,229,284],fail:[24,35,222,224,225,226,237,262,279,299,300,305,307,308,327,332,333,339],failur:[44,67,83,87,101,102,104,106,115,116,123,125,134,135,140,142,143,149,172,188,192,242,257,279,307,327,333,360],fairli:[230,266],faith:[238,240,255,259],fall:[39,54,159,238,240,255,262,279,280,300],fallen:279,fals:[19,26,29,30,32,33,299],famili:[118,119,137,138,206,207,208,209,237,238,240,241,247,253,255,256,262,264,285],familiar:[261,334],fan:[83,188],far:331,farther:[311,314,317,320],fast:[259,266,318],fasten:[51,53,156,158],faster:[230,238,253,301,334],fatal:[222,228],fau:230,fault:[222,228,231,244,259,280,282,283,284,285,289,295,297,312,319,321,352,353,360],faulti:346,fbuil:217,fclose:345,fe:[222,224,225,226,231,298,301],feap:16,feappv:[0,1,2,3,4,5,6,7,8,9,10,11,12,13,14,15,16,17,18,19,20,21,22,23,24,25,26,27,28,29,30,31,32,33,34,35,36,37,38,39,40,41,42,43,44,45,46,47,48,49,50,51,52,53,54,55,56,57,58,59,60,61,62,63,64,65,66,67,68,69,70,71,72,73,74,75,76,77,78,79,80,81,82,83,84,85,86,87,88,89,90,91,92,93,94,95,96,97,98,99,100,101,102,103,104,105,106,107,108,109,110,111,112,113,114,115,116,117,118,119,120,121,122,123,124,125,126,127,128,129,130,131,132,133,134,135,136,137,138,139,140,141,142,143,144,145,146,147,148,149,150,151,152,153,154,155,156,157,158,159,160,161,162,163,164,165,166,167,168,169,170,171,172,173,174,175,176,177,178,179,180,181,182,183,184,185,186,187,188,189,190,191,192,193,194,195,196,197,198,199,200,201,202,203,204,205,206,207,208,209,210,211,212,213,214,215,216,217,218,219,220,221,222,223,224,225,226,227,228,229,230,231,232,233,234,235,236,237,238,239,240,241,242,243,244,245,246,247,248,249,250,251,252,253,254,255,256,257,258,259,260,261,262,263,264,265,266,267,268,269,270,271,272,273,274,275,276,277,278,279,280,281,282,283,284,285,286,287,288,289,290,291,292,293,294,295,296,297,298,299,300,301,302,303,304,305,306,307,308,309,310,311,312,313,314,315,316,317,318,319,320,321,322,323,324,325,326,327,328,329,330,331,332,333,334,335,336,337,338,339,340,341,342,343,344,345,346,347,348,349,350,351,352,353,354,355,356,357,358,359,360],feasibl:[284,317],featur:[13,29,35,118,137,223,226,229,238,239,240,241,243,246,252,254,255,256,257,258,261,262,265,266,280,288,289,295,301,305,310,311,312,314,315,316,317,319,320,321,322,323,324,325,344,346,347,353,355,360],feb:[],februari:332,feder:[222,241,247,253,254,256,262,265,279,285],feedback:[222,223,224,225,226,227,228,229,246,261,284,288,289,311,314,317,320,324],feel:[233,312],feet:[51,53,87,118,119,137,138,156,158,192,238,239,241,253,340],felt:[239,254],fem:[14,16,26,222,224,225,226,230,232,291,292,293,295,296,297,298,299,300,301,305,306,312,318,325,331,332,335,337,340,342,343,344,345,347,353,355,359],fema18:[262,279,285],fema18a:[241,247,256],fema18b:[241,247,256],fema21:[253,254,265],fema:[145,215,222,228,237,240,241,245,247,253,254,255,256,259,260,261,262,265,279,280,285,313,315],fema_damage_bim:266,fema_damage_subset:266,fema_dc:266,fema_ds_comp:266,fema_hazu:[254,265],fema_p58:[100,205],femap:[100,205],femuq:[13,14,16],fenestr:[241,262],fepr:[],fetch:[233,264],few:[100,205,230,237,279,280,301,302,305,308,320,342,344,346],fewer:257,ffh_attri:239,fiber:[51,53,156,158,301],fiberboard:[118,137],fidel:[25,222,238,244,245,247,253,259,262,280,282,285,302,310,312,315,316,318,320,324,336,340,346],field:[14,20,50,51,53,114,133,155,156,158,222,223,224,225,226,229,230,232,238,239,242,244,245,246,252,253,254,257,259,260,261,262,266,291,292,295,301,312,316,319,321,338,339,340,342,344,345,347,350,351,354,360],fig:[0,1,2,3,4,5,6,7,8,9,10,11,12,13,14,15,16,17,18,19,20,21,22,23,24,25,26,27,28,29,30,31,32,33,34,35,36,37,38,39,40,41,42,43,44,45,46,47,48,49,50,51,52,53,54,55,56,57,58,59,60,61,62,63,64,65,66,67,68,69,70,71,72,73,74,75,76,77,78,79,80,81,82,83,84,85,86,87,88,89,90,91,92,93,94,95,96,97,98,99,100,101,102,103,104,105,106,107,108,109,110,111,112,113,114,115,116,117,118,119,120,121,122,123,124,125,126,127,128,129,130,131,132,133,134,135,136,137,138,139,140,141,142,143,144,145,146,147,148,149,150,151,152,153,154,155,156,157,158,159,160,161,162,163,164,165,166,167,168,169,170,171,172,173,174,175,176,177,178,179,180,181,182,183,184,185,186,187,188,189,190,191,192,193,194,195,196,197,198,199,200,201,202,203,204,205,206,207,208,209,210,211,212,213,214,215,216,217,218,219,220,221,222,223,224,225,226,227,228,229,230,231,232,233,234,235,236,237,238,239,240,241,242,243,244,245,246,247,248,249,250,251,252,253,254,255,256,257,258,259,260,261,262,263,264,265,266,267,268,269,270,271,272,273,274,275,276,277,278,279,280,281,282,283,284,285,286,287,288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34,35,36,246,254,261,266,307,315,329,354],repres:[8,13,20,29,54,55,64,81,82,83,84,85,89,90,91,94,104,105,106,107,108,109,110,111,112,113,114,115,116,117,118,119,123,124,125,126,127,128,129,130,131,132,133,134,135,136,137,138,159,160,169,186,187,188,189,190,194,195,196,206,209,222,224,225,226,230,231,232,233,238,240,241,253,255,256,266,280,285,289,295,298,299,300,301,302,311,347,349,350,351,352,355,356,359],represent:[233,242,245,246,247,253,257,261,262,264,266,272,285,287,316,325,343],reproduc:[26,29,39,221,230,237,299,300,301,334,342,344,347,355],req:233,request:[13,14,16,26,243,258,284,288,289,315,321,327,329,337,339,340,348,353,360],requi:245,requir:[0,1,2,3,4,5,6,7,8,9,10,11,12,13,14,15,16,17,18,19,20,21,22,23,24,25,26,27,28,29,30,31,32,33,34,35,36,37,38,39,40,41,42,43,44,45,46,47,48,49,50,51,52,53,54,55,56,57,58,59,60,61,62,63,64,65,66,67,68,69,70,71,72,73,74,75,76,77,78,79,80,81,82,83,84,85,86,87,88,89,90,91,92,93,94,95,96,97,98,99,100,101,102,103,104,105,106,107,108,109,110,111,112,113,114,115,116,117,118,119,120,121,122,123,124,125,126,127,128,129,130,131,132,133,134,135,136,137,138,139,140,141,142,143,144,145,146,147,148,149,150,151,152,153,154,155,156,157,158,159,160,161,162,163,164,165,166,167,168,169,170,171,172,173,174,175,176,177,178,179,180,181,182,183,184,185,186,187,188,189,190,191,192,193,194,195,196,197,198,199,200,201,202,203,204,205,206,207,208,209,210,211,212,213,214,215,216,217,218,219,220,221,227,230,231,232,233,234,235,236,237,238,239,240,241,242,243,244,245,246,247,248,249,250,251,252,253,254,255,256,257,258,259,260,261,262,263,264,265,266,267,268,269,270,271,272,273,274,275,276,277,278,279,280,281,282,283,284,285,286,287,288,289,290,291,292,293,294,295,296,297,298,299,300,301,302,303,304,305,306,307,308,309,310,311,312,313,314,315,316,317,318,319,320,321,322,323,324,325,326,327,328,329,330,331,332,333,334,335,336,337,338,339,340,341,342,343,344,345,346,347,348,349,350,351,352,353,354,355,356,357,358,359,360],requisit:257,reroduc:[],rerun:[24,305],res1:[19,30,32,33,206,207,208,209,238,239,241,253,254,264,266],res2:[206,207,208,209,238,239,241],res3:[206,207,208,209,238,239,241,253,254,266],res3a:[238,241],res3b:[238,241],res3c:[238,241],res3d:[238,241],res3f:[238,241],res4:[206,207,208,209,238,239,241],res5:[206,207,208,209,238,239,241],res6:[206,207,208,209,238,239,241],resampl:[231,310,316,323,344,345],research:[0,1,2,3,4,5,6,7,8,9,10,11,12,13,14,15,16,17,18,19,20,21,22,23,24,25,26,27,28,29,30,31,32,33,34,35,36,37,38,39,40,41,42,43,44,45,46,47,48,49,50,51,52,53,54,55,56,57,58,59,60,61,62,63,64,65,66,67,68,69,70,71,72,73,74,75,76,77,78,79,80,81,82,83,84,85,86,87,88,89,90,91,92,93,94,95,96,97,98,99,100,101,102,103,104,105,106,107,108,109,110,111,112,113,114,115,116,117,118,119,120,121,122,123,124,125,126,127,128,129,130,131,132,133,134,135,136,137,138,139,140,141,142,143,144,145,146,147,148,149,150,151,152,153,154,155,156,157,158,159,160,161,162,163,164,165,166,167,168,169,170,171,172,173,174,175,176,177,178,179,180,181,182,183,184,185,186,187,188,189,190,191,192,193,194,195,196,197,198,199,200,201,202,203,204,205,206,207,208,209,210,211,212,213,214,215,216,217,218,219,220,221,227,228,230,231,232,233,234,235,236,237,238,239,240,241,242,243,244,245,246,247,248,249,250,251,252,253,254,255,256,257,258,260,261,262,263,264,265,266,267,268,269,270,271,272,273,274,275,276,277,278,279,280,281,282,283,284,285,286,287,288,289,290,291,292,293,294,295,296,297,298,299,300,301,302,303,304,305,306,307,308,309,310,311,312,313,314,315,316,317,318,319,320,321,322,323,324,325,326,327,328,329,330,331,332,333,334,335,336,337,338,339,340,341,342,343,344,345,346,347,348,349,350,351,352,353,354,355,356,357,358,359,360],resembl:[307,308],reserv:[29,221],reset:[242,257],resid:[13,118,137,220,237,238,240,247,253,255,285],residencetyp:238,residenti:[119,138,237,238,247,253,254,259,261,262,278,280,285,286],residu:[222,224,225,226,228,230,234,253,266,292,331,346,347,355],resili:[222,244,247,252,259,262,265,279,280,282,285,287,320],resio:245,resist:[68,94,104,105,106,109,110,112,113,114,115,116,118,119,123,124,125,128,129,131,132,133,134,135,137,138,173,232,238,241,252,253,256,257,262,264,265,266,279,294,301,302,340,355,360],resiz:359,resnet:[238,253],resolut:[33,222,228,230,234,245,266,280,284,292,314,320,324,333,355],resolv:[238,245,333],resort:262,resourc:[13,14,16,22,28,222,231,242,245,247,248,257,266,278,284,298,346],respect:[22,33,230,232,233,234,238,239,244,245,253,257,259,266,280,282,292,298,299,301,330,331,332,346,347,355],respon:[],respond:[14,24],respons:[3,4,8,10,12,13,14,15,16,19,20,22,23,24,26,27,30,31,32,40,44,54,64,81,82,83,84,85,89,90,91,94,104,105,106,107,108,109,110,111,112,113,114,115,116,117,118,119,149,159,169,186,187,188,189,190,194,195,196,206,207,208,209,222,223,225,226,228,229,233,239,244,245,246,248,259,260,261,262,272,280,284,288,291,295,297,298,299,301,302,308,310,312,315,322,323,324,327,330,331,333,334,336,340,342,343,344,345,346,347,349,352,353,356,357,358,360],respspect:[],rest:[13,14,16,32,232,253,291,331],restart:[],restaur:[206,207,208,209,237],restock:[97,202],restor:[58,163,359],restrain:[42,50,53,81,82,83,91,147,155,158,186,187,188,196],restraint:[50,53,81,82,83,84,85,89,90,91,94,155,158,186,187,188,189,190,194,195,196],restrict:[266,300,346],restructur:318,result:[6,11,12,13,14,16,18,20,22,23,24,26,28,30,32,39,106,112,116,125,131,135,222,223,228,229,230,232,233,234,238,244,245,246,247,248,249,252,253,259,261,262,265,272,279,280,282,283,285,286,291,292,295,301,305,306,308,311,312,313,314,315,318,320,322,327,329,330,331,332,333,334,335,340,342,344,346,347,352,353,356,357,359],resultfil:357,resultsloc:[],resum:299,retail:[67,97,172,202,206,207,208,209,237,238,239,278],retain:[29,221,238,253],retriev:[14,242,257,299,352],retrofit:280,reus:[13,16,299,300],rever:32,revers:[33,352],review:[0,13,14,16,67,172,230,248,279,288,289,355,360],revis:[237,239,246,261,262,264,266,322],reynold:325,rho:[33,230,234,346],rho_:[230,234,346],rhode:238,ri:217,ribbon:359,richer:262,richter:301,rider:335,right:[16,23,29,30,221,230,232,233,238,253,280,291,295,296,298,299,300,301,305,306,307,308,331,333,339,340,343,346,355,356,358,359],rightarrow:230,rigid:[64,114,119,133,138,169],rigidli:[64,169],rinaldi228:351,rinaldi318:351,rio:33,rioxarrai:33,rise:[46,104,105,106,109,110,111,112,113,115,116,117,123,124,125,128,129,130,131,132,134,135,136,151,222,237,247,253,262,285,323,324,325],risk:[21,30,31,32,33,222,230,233,234,238,240,245,247,253,255,262,285,296,301,302,307,311,346,352],rita:262,river:[237,245],riverin:[238,239,245,247],riverinecoast:238,riverlin:247,rm1:[120,139,278],rm2:[120,139,278],rm:[230,245,292,346],rmsa:[],rmtree:38,road:[144,214],roadb:141,roadwai:211,robert:[262,360],robinson:330,robust:[230,334,348],robustli:[244,259,282],rock:[33,104,105,106,107,108,109,110,111,112,113,114,115,116,117,118,119,206,234,310,322,353,355],rockoutcrop:14,rockv:33,rod:[70,114,119,133,138,175],rodger:[283,285],rodgers19:[283,285],rodriguez:[259,266],role:247,roller:[],rom:301,ronald:360,roof:[20,58,61,107,108,109,110,111,114,117,118,126,127,128,129,130,133,136,137,163,166,222,238,239,240,241,252,253,254,255,256,262,264,265,266,279,291,292,299,301,340],roof_shap:[238,253],roof_shape_vali:[238,253],roofcov:[19,32,238,253,254],roofcvr:239,roofdeckag:238,roofdeckattachmentm:238,roofdeckattachmentw:[238,253,254],roofqual:[238,239,253,254],roofshap:[19,32,239,252,254,264,265,266],roofslop:[19,32,239,254,264,266],roofsystem:[19,32,238,239,253],rooftowallconnect:[238,253,254],rooftypeclassif:[246,261],room:[237,262,279],root:[41,146,230,291,292,295,346,355],rose:239,rosenbrock:[],rosetta:[],rotat:[222,224,225,226,291],rotd100:[293,294,352],rotd50:[293,294,352],rouech:[259,262,266],roueche20:262,roueche21:[259,266],rough:[230,238,239,241,245,251,254,256,264,266,325],rougher:230,roughli:[238,239,252,265],round:[41,42,43,44,45,47,64,73,81,82,84,85,89,90,91,101,102,104,105,106,107,108,109,110,111,112,113,114,115,116,117,118,119,121,122,123,124,125,126,127,128,129,130,131,132,133,134,135,136,137,138,141,142,143,206,207,208,209,211,212,213,230,252,265,299,355],roustant2012:230,roustant:230,rout:291,routin:[121,122,207,208,316,331],row:[20,33,38,237,238,253,291,294,306,330,331,340,343,345,347],rsn1737x00000:26,rsn244:30,rsn251:30,rsn30:[30,33],rsn564:30,rsn626:30,rsn63:[30,33],rsn692:30,rsn707x00001:26,rstrip:237,rt:357,ru:292,rule:[13,220,231,239,241,252,254,265,355],ruleset:[242,244,246,248,253,257,259,261,262,266,278],rulest:239,rulset:[242,257],run:[5,13,14,16,18,19,20,24,26,27,28,29,33,34,35,36,38,220,222,223,224,225,226,229,230,233,237,238,242,245,248,251,253,261,264,283,284,285,288,289,291,292,295,302,303,305,307,308,315,316,317,322,325,326,328,329,330,334,335,336,340,342,343,344,345,346,347,348,352,354,355,356,357,358,359,360],run_analysi:30,run_rwhal:23,rundir:[19,22,23,30,32,33],rundynamicanalysi:30,runfem:[],runner:329,runnerfactori:329,runnig:[],runningloc:33,runtim:328,runtyp:[26,33,329],runuq:329,rup:[352,356],rupsampl:233,rupt:39,ruptur:[39,233,280,283,284,287,295,319,321,322,352,354,356,360],rv:[5,10,26,38,216,230,239,254,291,292,294,295,298,299,300,301,318,330,331,332,333,335,337,340,343,344,345,347,359],rv_column1:[297,352],rv_column2:[297,352],rvobject:29,rw:360,rwhale:[22,23,26,30,32,237,278,284,327],rwhale_:[30,32,33],rwhale_config:[22,26],rwhale_config_eq:[22,30],rwhale_config_hu:32,rwhale_config_remot:23,rwhale_config_srt:33,rxr:33,ryng:[278,284],s0267726117308722:360,s10584:241,s1:[120,139,238,239,278,294,355],s2212420916303855:239,s2:[120,139,238,239,278],s30:[39,234,293,294,352],s3:[120,139,238,239],s4:[120,139],s5:[120,139,352],s:[0,1,2,3,4,5,6,7,8,9,10,11,12,13,14,15,16,17,18,19,20,21,22,23,24,25,26,27,28,29,30,31,32,33,34,35,36,37,38,39,40,41,42,43,44,45,46,47,48,49,50,51,52,53,54,55,56,57,58,59,60,61,62,63,64,65,66,67,68,69,70,71,72,73,74,75,76,77,78,79,80,81,82,83,84,85,86,87,88,89,90,91,92,93,94,95,96,97,98,99,100,101,102,103,104,105,106,107,108,109,110,111,112,113,114,115,116,117,118,119,12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0,31,32,33,34,35,36,37,38,39,40,41,42,43,44,45,46,47,48,49,50,51,52,53,54,55,56,57,58,59,60,61,62,63,64,65,66,67,68,69,70,71,72,73,74,75,76,77,78,79,80,81,82,83,84,85,86,87,88,89,90,91,92,93,94,95,96,97,98,99,100,101,102,103,104,105,106,107,108,109,110,111,112,113,114,115,116,117,118,119,120,121,122,123,124,125,126,127,128,129,130,131,132,133,134,135,136,137,138,139,140,141,142,143,144,145,146,147,148,149,150,151,152,153,154,155,156,157,158,159,160,161,162,163,164,165,166,167,168,169,170,171,172,173,174,175,176,177,178,179,180,181,182,183,184,185,186,187,188,189,190,191,192,193,194,195,196,197,198,199,200,201,202,203,204,205,206,207,208,209,210,211,212,213,214,215,216,217,218,219,220,221,222,223,224,225,226,227,228,229,230,231,232,233,234,235,236,237,238,239,240,241,242,243,244,245,246,247,248,249,250,251,252,253,254,255,256,257,258,259,260,261,262,263,264,265,266,267,268,269,270,271,272,273,274,275,276,277,278,279,280,281,282,283,284,285,286,287,288,289,290,291,292,294,295,296,297,298,299,300,301,302,303,304,305,306,307,308,309,310,311,312,313,314,315,316,317,318,319,320,321,322,323,324,325,326,327,328,329,330,331,332,333,334,335,336,337,338,339,340,341,342,343,344,345,346,347,348,349,350,351,352,353,354,355,356,357,358,359,360],tcr:262,td:237,td_attri:239,team:[0,24,237,243,246,258,259,261,266,280],tech:335,technic:[121,122,140,144,206,207,208,209,210,214,230,239,241,245,247,252,253,254,256,262,265,279,285,286,288,335,342,344],techniqu:[222,230,233,244,245,246,248,259,262,282,301,313,334,335],technisch:230,technolog:[13,206,207,208,209,238,239,245,253,260,261,284],tee:[111,130],tehe:[],tell:[13,16,291],temper:[54,55,159,160,231],temperatur:[238,239,253,254],templat:[22,23,33,246,248,317,320,329,346],templatedir:[13,16,22,33,327],templatedir_sim:[],tempor:[222,228],temporari:[13,16,206,207,208,209,230,237,299,300,329,346],temporarili:305,temprarili:308,ten:301,tenant:[14,23],tenant_nam:23,tend:[39,266,280],teng:246,tension:[47,92,114,133,152,197],tenth:238,ter:330,term:[13,23,104,105,106,107,108,109,110,111,112,113,114,115,116,117,118,119,206,220,230,232,238,239,252,253,254,261,265,287,300,333,336,345,346,347,355],termin:[26,30,32,34,35,36,86,191,305,306,308,327,332,346],termini:332,terminolog:[13,14,16,238,253,333],terrain:[222,238,239,241,245,249,253,254,256,257,260,264,266],terrain_swr:257,terrainrough:[238,253],terzic:219,test:[30,33,40,47,54,55,152,159,160,222,224,225,226,230,232,234,238,239,245,253,257,262,285,299,309,318,331,336,340,346,355,360],testb:[33,237,238,239,242,243,244,245,247,248,250,251,252,253,254,256,258,259,260,262,263,264,265,278,279,280,281,282,284,285,287],testbed_ac_asset_represent:241,testresult:[],texa:[288,355],text:[230,237,253,272,293,308,329,340,345,347,352],textbox:[233,297],th:[230,231,232,234,241],than:[33,35,43,46,48,49,76,78,79,83,101,102,104,105,106,108,109,111,112,113,115,116,117,118,119,123,124,125,127,128,130,131,132,134,135,136,137,138,143,148,151,153,154,181,183,184,188,222,224,225,226,230,233,234,237,238,239,241,242,244,245,251,253,254,257,259,264,266,278,280,283,285,291,299,300,301,331,333,334,335,344,345,346,347,355,358],thank:[],theat:[238,239],theater:[206,207,208,209],theatr:[206,207,208,209,239],thee:[],thehaywir:280,thei:[13,14,16,23,33,35,104,105,106,107,108,109,110,111,112,113,114,115,116,117,118,119,121,123,124,125,126,127,128,129,130,131,132,133,134,135,136,137,138,220,222,228,230,232,238,239,240,245,254,255,280,288,289,291,295,299,305,306,308,315,317,327,333,335,336,337,340,344,346,347,350,351,354,360],theinputapp:14,thelist:357,them:[13,16,29,38,106,114,116,125,133,135,222,228,234,240,242,255,257,266,288,289,298,305,306,308,315,327,340,346,355,356,359],themselv:[247,262,331],theorem:234,theoret:[230,299,346],theori:[0,1,2,3,4,5,6,7,8,9,10,11,12,13,14,15,16,17,18,19,20,21,22,23,24,25,26,27,28,29,30,31,32,33,34,35,36,37,38,39,40,41,42,43,44,45,46,47,48,49,50,51,52,53,54,55,56,57,58,59,60,61,62,63,64,65,66,67,68,69,70,71,72,73,74,75,76,77,78,79,80,81,82,83,84,85,86,87,88,89,90,91,92,93,94,95,96,97,98,99,100,101,102,103,104,105,106,107,108,109,110,111,112,113,114,115,116,117,118,119,120,121,122,123,124,125,126,127,128,129,130,131,132,133,134,135,136,137,138,139,140,141,142,143,144,145,146,147,148,149,150,151,152,153,154,155,156,157,158,159,160,161,162,163,164,165,166,167,168,169,170,171,172,173,174,175,176,177,178,179,180,181,182,183,184,185,186,187,188,189,190,191,192,193,194,195,196,197,198,199,200,201,202,203,204,205,206,207,208,209,210,211,212,213,214,215,216,217,218,219,220,221,222,223,224,225,226,227,228,229,230,231,232,233,234,235,236,237,238,239,240,241,242,243,244,245,246,247,248,249,250,251,252,253,254,255,256,257,258,259,260,261,262,263,264,265,266,267,268,269,270,271,272,273,274,275,276,277,278,279,280,281,282,283,284,285,286,287,288,289,290,291,292,293,294,295,296,297,298,299,300,301,302,303,304,305,306,307,308,309,310,311,312,313,314,315,316,317,318,319,320,321,322,323,324,325,326,327,328,329,330,331,332,333,334,335,336,337,338,339,340,341,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DL Applications","2.2.5. EDP Applications","2.2.7. UQ Applications","2.2.8. Building Applications","2.2.3. Event Applications","2.2.4. Modeling Applications","2.2.1. FEM Pre-processors","2.2.2. UQ Pre-processors","2.2.10. Regional Mapping Applications","2.2.6. Simulation Applications","2. Software Architecture","Software Architecture","2.2. Backend Applications","2.3. C4 Model of Software Architecture","Level 4 Dynamic Diagrams","2.1. File Types and Schemas","2.1.1. Inputs","2.1.2. Outputs","Running Manually","Run Locally on Your Desktop","Run Remotely on DesignSafe","Troubleshooting Errors","Creating Workflows","Reading the Log File","Choosing Component Applications","Workflow Structure","5. Coding Style","Earthquake Assessment","Examples","Hurricane Assessment","Regional Site Response Assessment","Build the Backend","1. How to Build","Build the Backend","3. How to Extend","4.1. Earthquake Response of Portal Frame","4.2. Response to Stochastic Ground Motion","4. Verification","B.10.31 - Steel Columns","B.10.33 - Steel Braces","B.10.35 - Steel Connections","B.10.41 - RC or Composite Columns","B.10.42 - RC or Composite Beams","B.10.44 - RC or Composite Shearwalls","B.10.49 - RC Flat Slabs","B.10.51 - Ordinary Reinforced Masonry Walls","B.10.52 - Special Reinforced Masonry Walls","B.10.61 - Cold-formed Steel Walls","B.10.71 - Wood Light Frame","B.10 - Super Structure","B.20.11 - Exterior Walls","B.20.22 - Curtain Walls","B.20.23 - Storefronts","B.20 - Exterior Enclosure","B.30.11 - Roof Coverings","B.30.31 - Masonry Chimney","B.30.41 - Masonry Parapet","B.30 - Roofing","1.1.1. B - Shell","C.10.11 - Partitions","C.10 - Interior Construction","C.20.11 - Stair Construction","C.20 - Stairs","C.30.11 - Wall Finishes","C.30.21 - Floor Finishes","C.30.27 - Access Pedastal Flooring","C.30.32 - Ceiling Finishes","C.30.34 - Independent Pendant Lighting","C.30 - Interior Finishes","1.1.2. C - Interiors","D.10.14 - Elevators & Lifts","D.10 - Conveying","D.20.21 - Domestic Water Distribution - Cold Water","D.20.22 - Domestic Water Distribution - Hot Water","D.20.31 - Sanitary Waste","D.20.51 - Chilled Water Distribution","D.20.61 - Steam Distribution","D.20 - Plumbing","D.30.31 - Cooling Generating Systems - Chilled Water","D.30.32 - Cooling Generating Systems - Direct Expansion","D.30.41 - Air Distribution Systems","D.30.52 - Terminal & Package Units","D.30.67 - Controls and Instrumentation","D.30 - HVAC","D.40.11 - Sprinklers","D.40 - Fire Protection","D.50.11 - Electrical Service & Distribution - High Tension","D.50.12 - Electrical Service & Distribution - Low Tension","D.50.92 - Other Electrical Systems","D.50 - Electrical","1.1.3. D - Services","E.20.22 - Movable Furnishings","E.20 - Furnishings","1.1.4. E - Equipments and furnishings","F.10.12 - Special Structures","F.10 - Special Construction","1.1.5. F - Special Construction & Demolition","1.1. FEMA P-58 2nd Edition","GF.H - Horizontal Spreading","GF.V - Vertical Settlement","1.2.1. GF - Geotechnical Failure","LF.C1 - Concrete Moment Frame","LF.C2 - Concrete Shear Walls","LF.C3 - Concrete Frame with Unreinforced Masonry Infill Walls","LF.MH - Mobile Homes","LF.PC1 - Precast Concrete Tilt-Up Walls","LF.PC2 - Precast Concrete Frames with Concrete Shear Walls","LF.RM1 - Reinforced Masonry Bearing Walls with Wood or Metal Deck Diaphragms","LF.RM2 - Reinforced Masonry Bearing Walls with Precast Concrete Diaphragms","LF.S1 - Steel Moment Frame","LF.S2 - Steel Braced Frame","LF.S3 - Steel Light Frame","LF.S4 - Steel Frame with Cast-in-Place Concrete Shear Walls","LF.S5 - Steel Frame with Unreinforced Masonry Infill Walls","LF.URM - Unreinforced Masonry Bearing Walls","LF.W1 - Wood, Light Frame","LF.W2 - Wood, Commercial & Industrial","1.2.2. LF - Lifeline Facilities","1.2.3. NSA - Non-Structural Acceleration-Sensitive","1.2.4. NSD - Non-Structural Drift-Sensitive","STR.C1 - Concrete Moment Frame","STR.C2 - Concrete Shear Walls","STR.C3 - Concrete Frame with Unreinforced Masonry Infill Walls","STR.MH - Mobile Homes","STR.PC1 - Precast Concrete Tilt-Up Walls","STR.PC2 - Precast Concrete Frames with Concrete Shear Walls","STR.RM1 - Reinforced Masonry Bearing Walls with Wood or Metal Deck Diaphragms","STR.RM2 - Reinforced Masonry Bearing Walls with Precast Concrete Diaphragms","STR.S1 - Steel Moment Frame","STR.S2 - Steel Braced Frame","STR.S3 - Steel Light Frame","STR.S4 - Steel Frame with Cast-in-Place Concrete Shear Walls","STR.S5 - Steel Frame with Unreinforced Masonry Infill Walls","STR.URM - Unreinforced Masonry Bearing Walls","STR.W1 - Wood, Light Frame","STR.W2 - Wood, Commercial & Industrial","1.2.5. STR - Structural","1.2. Hazus Earthquake Methodology - Buildings","1.3.1. HRD - Road segments","1.3.3. HTU - Tunnels","1.3.2. HWB - Bridges","1.3. Hazus Earthquake Methodology - Transportation","1. Damage Models","B.10.31 - Steel Columns","B.10.33 - Steel Braces","B.10.35 - Steel Connections","B.10.41 - RC or Composite Columns","B.10.42 - RC or Composite Beams","B.10.44 - RC or Composite Shearwalls","B.10.49 - RC Flat Slabs","B.10.51 - Ordinary Reinforced Masonry Walls","B.10.52 - Special Reinforced Masonry Walls","B.10.61 - Cold-formed Steel Walls","B.10.71 - Wood Light Frame","B.10 - Super Structure","B.20.11 - Exterior Walls","B.20.22 - Curtain Walls","B.20.23 - Storefronts","B.20 - Exterior Enclosure","B.30.11 - Roof Coverings","B.30.31 - Masonry Chimney","B.30.41 - Masonry Parapet","B.30 - Roofing","2.1.1. B - Shell","C.10.11 - Partitions","C.10 - Interior Construction","C.20.11 - Stair Construction","C.20 - Stairs","C.30.11 - Wall Finishes","C.30.21 - Floor Finishes","C.30.27 - Access Pedastal Flooring","C.30.32 - Ceiling Finishes","C.30.34 - Independent Pendant Lighting","C.30 - Interior Finishes","2.1.2. C - Interiors","D.10.14 - Elevators & Lifts","D.10 - Conveying","D.20.21 - Domestic Water Distribution - Cold Water","D.20.22 - Domestic Water Distribution - Hot Water","D.20.31 - Sanitary Waste","D.20.51 - Chilled Water Distribution","D.20.61 - Steam Distribution","D.20 - Plumbing","D.30.31 - Cooling Generating Systems - Chilled Water","D.30.32 - Cooling Generating Systems - Direct Expansion","D.30.41 - Air Distribution Systems","D.30.52 - Terminal & Package Units","D.30.67 - Controls and Instrumentation","D.30 - HVAC","D.40.11 - Sprinklers","D.40 - Fire Protection","D.50.11 - Electrical Service & Distribution - High Tension","D.50.12 - Electrical Service & Distribution - Low Tension","D.50.92 - Other Electrical Systems","D.50 - Electrical","2.1.3. D - Services","E.20.22 - Movable Furnishings","E.20 - Furnishings","2.1.4. E - Equipments and furnishings","F.10.12 - Special Structures","F.10 - Special Construction","2.1.5. F - Special Construction & Demolition","2.1. FEMA P-58 2nd Edition","2.2.1. LF - Lifeline Facilities","2.2.2. NSA - Non-Structural Acceleration-Sensitive","2.2.3. NSD - Non-Structural Drift-Sensitive","2.2.4. STR - Structural","2.2. Hazus Earthquake Methodology - Buildings","2.3.1. HRD - Road segments","2.3.3. HTU - Tunnels","2.3.2. HWB - Bridges","2.3. Hazus Earthquake Methodology - Transportation","2. Repair Consequence Models","9. Abbreviations","4. How To Cite","2. Acknowledgments","Acknowledgments","8. Glossary","3. Copyright and License","R2D","Requirements","Response of Building to Earthquake","General Requirements","5. Requirements","<no title>","Requirements","Requirements","1.2. Methods in SimCenterUQ Engine","Methods in UCSD UQ Engine","1.3. Damping Options","Hazard Occurrence","Ground Motion Intensity Spatial Correlation Model Options","1. Technical Manual","1.1. Dakota Methods","Anchorage, AK","Asset Description","Asset Representation","Best Practices","Damage and Loss Estimation","Getting Started","Feedback","Opportunity Areas for Future Refinements","Hazard Characterization","Atlantic County, NJ","Overview","Preface","Standard Wind Speed Conversions","Response Simulation","Verification Results","Uncertainty Quantification","Asset Description","Asset Representation","Best Practices","Damage and Loss Estimation","Getting Started","Feedback","Research Opportunities","Hazard Characterization","Lake Charles, LA","Overview","Response Simulation","Verification Results","Uncertainty Quantification","Validation Results","Asset Description","Asset Representation","Damage and Loss Estimation","Opportunity Areas for Future Refinements","Hazard Characterization","Memphis, TN","Network Performance Assessment","Overview","Response Simulation","Sample Results","Uncertainty Quantification","Asset Description","Damage and Loss Estimation","Example Outputs","Feedback and Data Request","Opportunity Areas for Future Refinements","Hazard Characterization","San Francisco, CA","Overview","Response Simulation","Uncertainty Quantification","1. About","About","6. Bugs & Feature Requests","3.1. Shear Building: Sampling, Reliability and Sensitivity","3.2. Including Spatial Variability in Site Response Event","3.3. Ground Motion Selection and Nonlinear Response Analysis","3.4. AutoSDA and Nonlinear Response Analysis","3.5. Shear Building: Synthetic Ground Motion","3.6. Surrogate Model for Structural Response Prediction (Probabilistic Learning on Manifolds)","3.7. Target Spectrum by Surrogate Hazard GP Model","3.8. Using Multiple Models and Analysis Options in EE-UQ","3.9. Training a Surrogate Model (Gaussian Process)","3.10. Structural Response Prediction Using a Surrogate Model (Gaussian Process)","3.11. Multi-fidelity Monte Carlo Simulation","3. Examples","Coupled Digital Twin Example","Install Additional Applications","MacOS Users","Windows Users","1.1. Install on Windows 10","1.2. Install on macOS 10","1. Installation","5. Capabilities","7. Release Plans","6. Release Notes","Capabilities","Release Plans","Release Notes","Capabilities","Release Plans","Release Notes","Capabilities","Release Plans","Release Notes","Release Notes","Capabilities","Release Plans","Release Notes","4. Troubleshooting","4.2. Issues While Running","4.1. Startup Issues","2.1.5.1. Configuring CustomUQ Engine","Bayesian Calibration","Deterministic Calibration","Gradient-free Parameter Estimation","2.1.2.3. Reliability Analysis","2.1.2.1. Forward Propagation","2.1.2.2. Global Sensitivity Analysis","2.5. FEM: Finite Element Method","Surrogate (GP)","2.2. GI: General Information","2.6. RV: Random Variables","2.3. SIM: Structural Model","SimCenter UQ Engine","Multi-fidelity Monte Carlo","2.1.3.4. Probabilistic Learning on Manifolds (PLoM)","2.1.3.1. Forward Propagation","2.1.3.2. Global Sensitivity Analysis","2.1.3.3. Gaussian Process (GP) Surrogate Modeling","2.1.4.1. Transitional Markov chain Monte Carlo (TMCMC) algorithm","2.1. UQ: Uncertainty Quantification","2.4. EVT: Earthquake Events","2.4.4. Multiple SimCenter","2.4.3. Multiple PEER","2.4.2. PEER NGA Records","Release Notes","2.4.1. Stochastic Ground Motions","2.4.5. Site Response Analysis","2.4.6. User Specified Database","2.7. EDP: Demand Parameters","2.8. RES: Results","2. User Interface","Earthquake Engineering with Uncertainty Quantification Application 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Conveying", "D.20.21 - Domestic Water Distribution - Cold Water", "D.20.22 - Domestic Water Distribution - Hot Water", "D.20.31 - Sanitary Waste", "D.20.51 - Chilled Water Distribution", "D.20.61 - Steam Distribution", "D.20 - Plumbing", "D.30.31 - Cooling Generating Systems - Chilled Water", "D.30.32 - Cooling Generating Systems - Direct Expansion", "D.30.41 - Air Distribution Systems", "D.30.52 - Terminal & Package Units", "D.30.67 - Controls and Instrumentation", "D.30 - HVAC", "D.40.11 - Sprinklers", "D.40 - Fire Protection", "D.50.11 - Electrical Service & Distribution - High Tension", "D.50.12 - Electrical Service & Distribution - Low Tension", "D.50.92 - Other Electrical Systems", "D.50 - Electrical", "D - Services", "E.20.22 - Movable Furnishings", "E.20 - Furnishings", "E - Equipments and furnishings", "F.10.12 - Special Structures", "F.10 - Special Construction", "F - Special Construction & Demolition", "FEMA P-58 2nd Edition", "GF.H - Horizontal Spreading", "GF.V - Vertical Settlement", "GF - Geotechnical Failure", "LF.C1 - Concrete Moment Frame", "LF.C2 - Concrete Shear Walls", "LF.C3 - Concrete Frame with Unreinforced Masonry Infill Walls", "LF.MH - Mobile Homes", "LF.PC1 - Precast Concrete Tilt-Up Walls", "LF.PC2 - Precast Concrete Frames with Concrete Shear Walls", "LF.RM1 - Reinforced Masonry Bearing Walls with Wood or Metal Deck Diaphragms", "LF.RM2 - Reinforced Masonry Bearing Walls with Precast Concrete Diaphragms", "LF.S1 - Steel Moment Frame", "LF.S2 - Steel Braced Frame", "LF.S3 - Steel Light Frame", "LF.S4 - Steel Frame with Cast-in-Place Concrete Shear Walls", "LF.S5 - Steel Frame with Unreinforced Masonry Infill Walls", "LF.URM - Unreinforced Masonry Bearing Walls", "LF.W1 - Wood, Light Frame", "LF.W2 - Wood, Commercial & Industrial", "LF - Lifeline Facilities", "NSA - Non-Structural Acceleration-Sensitive", "NSD - Non-Structural Drift-Sensitive", "STR.C1 - Concrete Moment Frame", "STR.C2 - Concrete Shear Walls", "STR.C3 - Concrete Frame with Unreinforced Masonry Infill Walls", "STR.MH - Mobile Homes", "STR.PC1 - Precast Concrete Tilt-Up Walls", "STR.PC2 - Precast Concrete Frames with Concrete Shear Walls", "STR.RM1 - Reinforced Masonry Bearing Walls with Wood or Metal Deck Diaphragms", "STR.RM2 - Reinforced Masonry Bearing Walls with Precast Concrete Diaphragms", "STR.S1 - Steel Moment Frame", "STR.S2 - Steel Braced Frame", "STR.S3 - Steel Light Frame", "STR.S4 - Steel Frame with Cast-in-Place Concrete Shear Walls", "STR.S5 - Steel Frame with Unreinforced Masonry Infill Walls", "STR.URM - Unreinforced Masonry Bearing Walls", "STR.W1 - Wood, Light Frame", "STR.W2 - Wood, Commercial & Industrial", "STR - Structural", "Hazus Earthquake Methodology - Buildings", "HRD - Road segments", "HTU - Tunnels", "HWB - Bridges", "Hazus Earthquake Methodology - Transportation", "Damage Models", "B.10.31 - Steel Columns", "B.10.33 - Steel Braces", "B.10.35 - Steel Connections", "B.10.41 - RC or Composite Columns", "B.10.42 - RC or Composite Beams", "B.10.44 - RC or Composite Shearwalls", "B.10.49 - RC Flat Slabs", "B.10.51 - Ordinary Reinforced Masonry Walls", "B.10.52 - Special Reinforced Masonry Walls", "B.10.61 - Cold-formed Steel Walls", "B.10.71 - Wood Light Frame", "B.10 - Super Structure", "B.20.11 - Exterior Walls", "B.20.22 - Curtain Walls", "B.20.23 - Storefronts", "B.20 - Exterior Enclosure", "B.30.11 - Roof Coverings", "B.30.31 - Masonry Chimney", "B.30.41 - Masonry Parapet", "B.30 - Roofing", "B - Shell", "C.10.11 - Partitions", "C.10 - Interior Construction", "C.20.11 - Stair Construction", "C.20 - Stairs", "C.30.11 - Wall Finishes", "C.30.21 - Floor Finishes", "C.30.27 - Access Pedastal Flooring", "C.30.32 - Ceiling Finishes", "C.30.34 - Independent Pendant Lighting", "C.30 - Interior Finishes", "C - Interiors", "D.10.14 - Elevators & Lifts", "D.10 - Conveying", "D.20.21 - Domestic Water Distribution - Cold Water", "D.20.22 - Domestic Water Distribution - Hot Water", "D.20.31 - Sanitary Waste", "D.20.51 - Chilled Water Distribution", "D.20.61 - Steam Distribution", "D.20 - Plumbing", "D.30.31 - Cooling Generating Systems - Chilled Water", "D.30.32 - Cooling Generating Systems - Direct Expansion", "D.30.41 - Air Distribution Systems", "D.30.52 - Terminal & Package Units", "D.30.67 - Controls and Instrumentation", "D.30 - HVAC", "D.40.11 - Sprinklers", "D.40 - Fire Protection", "D.50.11 - Electrical Service & Distribution - High Tension", "D.50.12 - Electrical Service & Distribution - Low Tension", "D.50.92 - Other Electrical Systems", "D.50 - Electrical", "D - Services", "E.20.22 - Movable Furnishings", "E.20 - Furnishings", "E - Equipments and furnishings", "F.10.12 - Special Structures", "F.10 - Special Construction", "F - Special Construction & Demolition", "FEMA P-58 2nd Edition", "LF - Lifeline Facilities", "NSA - Non-Structural Acceleration-Sensitive", "NSD - Non-Structural Drift-Sensitive", "STR - Structural", "Hazus Earthquake Methodology - Buildings", "HRD - Road segments", "HTU - Tunnels", "HWB - Bridges", "Hazus Earthquake Methodology - Transportation", "Repair Consequence Models", "9. Abbreviations", "4. How To Cite", "2. Acknowledgments", "Acknowledgments", "8. Glossary", "3. Copyright and License", "R2D", "Requirements", "Response of Building to Earthquake", "General Requirements", "5. Requirements", "<no title>", "Requirements", "Requirements", "Regional Earthquake Hazard Use Cases", "1.2. Methods in SimCenterUQ Engine", "Methods in UCSD UQ Engine", "1.3. Damping Options", "Hazard Occurrence", "1.4. Ground Motion Intensity Spatial Correlation Model Options", "1. Technical Manual", "1.1. Dakota Methods", "Anchorage, AK", "Asset Description", "Asset Representation", "Best Practices", "Damage and Loss Estimation", "Getting Started", "Feedback", "Opportunity Areas for Future Refinements", "Hazard Characterization", "Atlantic County, NJ", "Overview", "Preface", "Standard Wind Speed Conversions", "Response Simulation", "Verification Results", "Uncertainty Quantification", "Asset Description", "Asset Representation", "Best Practices", "Damage and Loss Estimation", "Getting Started", "Feedback", "Research Opportunities", "Hazard Characterization", "Lake Charles, LA", "Overview", "Response Simulation", "Verification Results", "Uncertainty Quantification", "Validation Results", "Asset Description", "Asset Representation", "Damage and Loss Estimation", "Opportunity Areas for Future Refinements", "Hazard Characterization", "Memphis, TN", "Network Performance Assessment", "Overview", "Response Simulation", "Sample Results", "Uncertainty Quantification", "Asset Description", "Damage and Loss Estimation", "Example Outputs", "Feedback and Data Request", "Opportunity Areas for Future Refinements", "Hazard Characterization", "San Francisco, CA", "Overview", "Response Simulation", "Uncertainty Quantification", "1. About", "About", "6. Bugs & Feature Requests", "3.1. Shear Building: Sampling, Reliability and Sensitivity", "3.2. Including Spatial Variability in Site Response Event", "3.3. Ground Motion Selection and Nonlinear Response Analysis", "3.4. AutoSDA and Nonlinear Response Analysis", "3.5. Shear Building: Synthetic Ground Motion", "3.6. Surrogate Model for Structural Response Prediction (Probabilistic Learning on Manifolds)", "3.7. Target Spectrum by Surrogate Hazard GP Model", "3.8. Using Multiple Models and Analysis Options in EE-UQ", "3.9. Training a Surrogate Model (Gaussian Process)", "3.10. Structural Response Prediction Using a Surrogate Model (Gaussian Process)", "3.11. Multi-fidelity Monte Carlo Simulation", "3. Examples", "Coupled Digital Twin Example", "Install Additional Applications", "MacOS Users", "Windows Users", "1.1. Install on Windows 10", "1.2. Install on macOS 10", "1. Installation", "5. Capabilities", "7. Release Plans", "6. Release Notes", "Capabilities", "Release Plans", "Release Notes", "Capabilities", "Release Plans", "Release Notes", "Capabilities", "Release Plans", "Release Notes", "Release Notes", "Capabilities", "Release Plans", "Release Notes", "4. Troubleshooting", "4.2. Issues While Running", "4.1. Startup Issues", "2.1.5.1. Configuring CustomUQ Engine", "Bayesian Calibration", "Deterministic Calibration", "Gradient-free Parameter Estimation", "2.1.2.3. Reliability Analysis", "2.1.2.1. Forward Propagation", "2.1.2.2. Global Sensitivity Analysis", "2.5. FEM: Finite Element Method", "Surrogate (GP)", "2.2. GI: General Information", "2.6. RV: Random Variables", "2.3. SIM: Structural Model", "SimCenter UQ Engine", "Multi-fidelity Monte Carlo", "2.1.3.4. Probabilistic Learning on Manifolds (PLoM)", "2.1.3.1. Forward Propagation", "2.1.3.2. Global Sensitivity Analysis", "2.1.3.3. Gaussian Process (GP) Surrogate Modeling", "2.1.4.2. Calibration of Hierarchical Model", "2.1.4.1. Calibration of Non-hierarchical Model", "2.1. UQ: Uncertainty Quantification", "2.4. EVT: Earthquake Events", "2.4.4. Multiple SimCenter", "2.4.3. Multiple PEER", "2.4.2. PEER NGA Records", "Release Notes", "2.4.1. Stochastic Ground Motions", "2.4.5. Site Response Analysis", "2.4.6. User Specified Database", "2.7. EDP: Demand Parameters", "2.8. RES: Results", "2. User Interface", "User Inputs", "ConcreteBuildingModel", "CustomPy", "CustomPySimulation", "DakotaInputBayesianCalibration", "DakotaInputCalibration", "DakotaInputOptimization", "DakotaInputReliability", "DakotaInputSampling", "DakotaInputSensitivity", "EDP", "EDP_EarthquakeSelection", "ExampleWidget", "ExistingSimCenterEvents", "GaussianProcessInputWidget", "GlobalReliabilityWidget", "ImportSamplesWidget", "ImportanceSamplingInputWidget", "InputWidgetBIM", "InputWidgetExistingEvent", "InputWidgetOpenSeesAnalysis", "LatinHypercubeInputWidget", "LocalReliabilityWidget", "MDOF_BuildingModel", "MDOF_LU", "MonteCarloInputSimWidget", "MonteCarloInputWidget", "MultiFidelityMonteCarlo", "MultiFidelitySimWidget", "NoneEngine", "OpenSeesBuildingModel", "PCEInputWidget", "PLoMInputWidget", "PLoMSimuWidget", "SimCenterIntensityMeasureCombo", "SimCenterIntensityMeasureWidget", "SimCenterUQInputPLoM", "SimCenterUQInputSampling", "SimCenterUQInputSensitivity", "SimCenterUQInputSurrogate", 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240, 241, 242, 245, 246, 247, 248, 253, 254, 255, 256, 260, 262, 265, 266, 279, 280, 281, 283, 284, 285, 286, 287, 292, 293, 296, 299, 300, 302, 316, 319, 328, 330, 331, 332, 333, 334, 337, 341, 347, 349, 352, 353, 354, 355, 357, 358, 359, 360, 406, 418], "topic": [0, 244, 259, 282, 291], "later": [0, 34, 35, 36, 38, 62, 66, 70, 73, 94, 101, 102, 105, 106, 108, 109, 110, 112, 113, 114, 115, 116, 118, 119, 124, 125, 127, 128, 129, 131, 132, 133, 134, 135, 137, 138, 167, 171, 175, 178, 234, 238, 240, 243, 246, 255, 258, 280, 294, 295, 296, 297, 300, 302, 306, 309, 311, 317, 328, 341, 347, 355], "week": [0, 238, 246, 300, 301], "introduct": [1, 2, 347], "setup": [1, 2, 234, 243, 258, 297, 326, 328, 347], "quick": [1, 263, 308], "intro": 1, "linux": [1, 2, 35, 306, 309, 344], "virtual": [1, 29, 263, 267], "machin": [1, 13, 14, 16, 222, 223, 224, 225, 226, 229, 231, 239, 243, 254, 258, 263, 309, 326, 347, 350, 418], "git": [1, 2, 23, 35, 347], "what": [1, 13, 14, 16, 29, 35, 231, 239, 240, 255, 289, 290, 291, 292, 293, 302, 328, 357, 418], "comput": [1, 13, 14, 16, 22, 23, 28, 30, 38, 94, 220, 223, 224, 225, 226, 228, 229, 231, 232, 234, 235, 240, 241, 242, 243, 246, 248, 249, 250, 252, 256, 257, 258, 280, 281, 284, 285, 286, 287, 289, 290, 293, 294, 295, 297, 299, 300, 302, 303, 305, 306, 309, 316, 319, 321, 322, 328, 330, 331, 332, 333, 334, 335, 336, 341, 343, 344, 345, 346, 347, 348, 349, 354, 355, 357, 361, 406, 418], "philosphi": 1, "data": [1, 13, 14, 16, 23, 24, 25, 26, 27, 28, 29, 42, 47, 54, 55, 64, 94, 147, 152, 159, 160, 169, 220, 221, 222, 223, 224, 225, 226, 228, 229, 231, 232, 234, 235, 240, 241, 242, 243, 244, 245, 246, 247, 248, 249, 250, 252, 253, 255, 256, 257, 258, 259, 260, 261, 262, 263, 265, 266, 267, 279, 280, 281, 283, 284, 285, 286, 292, 293, 294, 295, 296, 297, 298, 299, 300, 301, 302, 306, 309, 311, 313, 314, 316, 317, 318, 319, 320, 321, 324, 328, 331, 332, 333, 335, 340, 341, 345, 346, 347, 348, 349, 350, 351, 352, 354, 355, 357, 358, 359, 361, 374, 414], "type": [1, 3, 4, 6, 7, 8, 12, 13, 14, 19, 20, 23, 24, 25, 26, 27, 30, 32, 33, 35, 38, 51, 54, 55, 62, 66, 67, 101, 102, 114, 116, 117, 133, 135, 136, 156, 159, 160, 167, 171, 172, 206, 207, 208, 209, 222, 228, 230, 231, 234, 238, 239, 240, 241, 242, 246, 247, 248, 253, 254, 255, 256, 258, 262, 266, 267, 280, 281, 286, 287, 292, 296, 297, 306, 307, 309, 313, 316, 320, 322, 323, 330, 336, 341, 346, 347, 349, 350, 354, 355, 357, 358], "loop": [1, 14, 38, 231, 238], "condit": [1, 29, 30, 33, 39, 50, 53, 57, 58, 59, 64, 68, 69, 70, 75, 76, 77, 78, 79, 81, 82, 83, 84, 85, 87, 89, 90, 91, 94, 97, 104, 105, 106, 107, 108, 109, 110, 111, 112, 113, 114, 115, 116, 117, 118, 119, 155, 158, 162, 163, 164, 169, 173, 174, 175, 180, 181, 182, 183, 184, 186, 187, 188, 189, 190, 192, 194, 195, 196, 202, 206, 221, 222, 231, 232, 235, 258, 261, 288, 292, 293, 296, 313, 326, 346, 347, 348, 354, 355, 357, 358, 416], "function": [1, 13, 14, 15, 19, 27, 29, 30, 32, 33, 94, 104, 105, 106, 107, 108, 109, 110, 111, 112, 113, 114, 115, 116, 117, 118, 119, 121, 122, 123, 124, 125, 126, 127, 128, 129, 130, 131, 132, 133, 134, 135, 136, 137, 138, 206, 207, 208, 220, 222, 223, 224, 225, 226, 228, 229, 230, 232, 234, 235, 238, 239, 240, 242, 243, 253, 257, 258, 265, 266, 267, 280, 281, 286, 288, 299, 301, 302, 308, 311, 314, 315, 316, 317, 319, 320, 321, 322, 323, 324, 328, 330, 331, 332, 333, 334, 340, 344, 347, 357, 374, 406, 414], "matrix": [1, 30, 222, 223, 224, 225, 226, 229, 232, 233, 239, 252, 254, 265, 335, 337, 346, 349, 355], "6": [1, 13, 19, 20, 27, 30, 32, 33, 35, 38, 39, 44, 47, 48, 50, 51, 53, 54, 55, 83, 87, 94, 104, 105, 107, 108, 109, 110, 111, 112, 113, 114, 115, 118, 119, 121, 123, 124, 126, 127, 128, 129, 130, 131, 132, 133, 134, 137, 138, 143, 149, 152, 153, 155, 156, 158, 159, 160, 188, 192, 217, 222, 223, 224, 225, 226, 228, 229, 231, 235, 239, 240, 242, 245, 246, 248, 254, 255, 260, 265, 267, 279, 281, 285, 286, 291, 292, 295, 296, 302, 306, 307, 321, 325, 336, 340, 341, 354, 357, 358, 418], "plot": [1, 33, 234, 239, 254, 265, 267, 281, 292, 293, 296, 297, 299, 300, 301, 302, 317, 344, 347, 354, 357, 358], "object": [1, 14, 19, 29, 94, 232, 234, 239, 254, 330, 332, 333, 336, 349], "orient": [1, 14, 30, 112, 131, 235, 239, 254, 331, 332, 336], "concept": [1, 231, 234, 262], "7": [1, 20, 26, 27, 30, 32, 33, 35, 50, 51, 53, 104, 105, 106, 107, 108, 109, 110, 111, 112, 113, 114, 115, 116, 117, 118, 119, 121, 123, 124, 125, 126, 127, 128, 129, 130, 131, 132, 133, 134, 135, 136, 137, 138, 143, 155, 156, 158, 222, 223, 224, 225, 226, 228, 229, 232, 234, 235, 238, 239, 240, 242, 246, 250, 254, 263, 265, 267, 279, 281, 284, 285, 286, 292, 294, 295, 296, 298, 300, 301, 302, 306, 307, 308, 330, 332, 333, 340, 341, 354, 357, 358, 361, 418], "class": [1, 13, 14, 19, 29, 104, 105, 106, 107, 108, 109, 110, 111, 112, 113, 114, 115, 116, 117, 118, 119, 206, 220, 231, 232, 238, 239, 241, 242, 245, 248, 254, 256, 257, 260, 262, 263, 265, 279, 286, 295, 330, 334, 340, 354], "8": [1, 13, 16, 19, 20, 27, 29, 30, 32, 33, 44, 46, 48, 49, 50, 51, 53, 55, 94, 104, 105, 106, 109, 111, 112, 113, 115, 116, 123, 124, 125, 128, 130, 131, 132, 134, 135, 143, 149, 151, 153, 154, 155, 156, 158, 160, 222, 223, 224, 225, 226, 228, 229, 234, 235, 238, 239, 240, 242, 252, 254, 263, 265, 267, 279, 281, 284, 285, 286, 292, 295, 302, 306, 307, 336, 357, 360, 406], "modul": [1, 15, 222, 231, 239, 253, 254, 265, 266, 306, 307, 313, 314, 341, 344, 347], "9": [1, 19, 23, 26, 30, 32, 33, 38, 66, 143, 171, 222, 223, 224, 225, 226, 228, 229, 231, 234, 238, 239, 242, 250, 254, 265, 267, 279, 287, 292, 293, 296, 302, 303, 310, 336, 352, 357], "file": [1, 3, 4, 5, 6, 7, 8, 10, 11, 12, 13, 14, 15, 16, 22, 24, 25, 27, 28, 30, 32, 33, 34, 35, 36, 38, 94, 100, 205, 220, 222, 223, 224, 225, 226, 229, 230, 234, 238, 239, 243, 254, 255, 258, 266, 279, 280, 284, 292, 294, 295, 296, 297, 298, 299, 300, 302, 303, 307, 308, 309, 311, 313, 316, 317, 319, 323, 324, 326, 328, 330, 331, 332, 333, 337, 338, 341, 346, 347, 348, 349, 350, 352, 353, 354, 357, 358, 359, 361, 374, 401, 406, 414, 415, 416], "handl": [1, 29, 30, 35, 84, 189, 222, 223, 224, 225, 226, 229, 319, 328, 334, 346], "10": [1, 20, 26, 30, 32, 33, 35, 38, 39, 54, 55, 58, 59, 61, 72, 83, 93, 99, 101, 102, 143, 159, 160, 163, 164, 166, 177, 188, 198, 204, 217, 222, 223, 224, 225, 226, 228, 229, 230, 231, 234, 235, 238, 239, 240, 242, 246, 247, 250, 254, 258, 260, 261, 263, 265, 267, 279, 281, 284, 285, 286, 287, 292, 294, 295, 296, 298, 300, 302, 306, 307, 310, 331, 337, 341, 345, 347, 354, 358, 406, 416, 418], "us": [1, 3, 5, 8, 11, 12, 13, 14, 15, 16, 19, 20, 21, 22, 23, 27, 28, 29, 30, 31, 32, 34, 36, 38, 39, 40, 41, 47, 51, 53, 101, 102, 109, 128, 146, 152, 156, 158, 216, 220, 221, 222, 223, 224, 225, 226, 228, 229, 232, 233, 234, 235, 238, 241, 242, 243, 245, 246, 248, 249, 250, 252, 253, 255, 256, 257, 258, 260, 263, 265, 267, 279, 280, 281, 283, 284, 285, 287, 288, 289, 290, 291, 292, 294, 295, 296, 297, 298, 300, 302, 303, 305, 306, 307, 308, 309, 311, 312, 313, 314, 315, 316, 317, 318, 319, 320, 321, 322, 323, 324, 325, 326, 328, 330, 331, 332, 333, 334, 335, 336, 337, 338, 339, 340, 341, 343, 344, 345, 346, 347, 348, 349, 350, 352, 353, 354, 355, 356, 357, 358, 359, 360, 361, 406, 415, 416, 418], "extens": [1, 13, 16, 29, 35, 101, 102, 105, 115, 124, 134, 231, 244, 245, 246, 247, 259, 260, 262, 263, 280, 281, 283, 306, 307, 352, 353, 354, 356], "11": [1, 13, 16, 26, 29, 30, 32, 33, 38, 54, 55, 56, 60, 63, 65, 71, 88, 92, 143, 159, 160, 161, 165, 168, 170, 176, 193, 197, 222, 228, 231, 235, 238, 239, 242, 246, 254, 262, 265, 267, 279, 294, 418], "web": [1, 2, 13, 14, 16, 43, 46, 148, 151, 222, 223, 224, 225, 226, 229, 238, 354], "scrab": [1, 2], "selenium": [1, 238], "gener": [2, 13, 14, 16, 23, 27, 28, 30, 34, 36, 39, 54, 55, 67, 86, 91, 105, 121, 122, 124, 159, 160, 172, 191, 196, 206, 207, 208, 209, 216, 222, 223, 229, 231, 232, 234, 235, 238, 240, 241, 243, 244, 245, 246, 247, 249, 253, 256, 259, 260, 261, 262, 263, 266, 267, 280, 281, 282, 283, 287, 290, 292, 294, 295, 296, 297, 298, 299, 300, 301, 302, 313, 314, 316, 318, 320, 322, 323, 326, 328, 330, 331, 332, 334, 335, 336, 337, 338, 341, 343, 345, 347, 348, 349, 351, 354, 355, 356, 358, 359, 361, 374, 406, 414, 418], "c": [2, 13, 14, 16, 22, 26, 30, 32, 34, 35, 36, 44, 46, 75, 76, 77, 78, 79, 83, 87, 100, 149, 151, 180, 181, 182, 183, 184, 188, 192, 205, 220, 221, 231, 232, 233, 235, 239, 240, 242, 246, 248, 250, 254, 255, 257, 258, 260, 263, 266, 267, 279, 280, 281, 285, 286, 287, 296, 297, 307, 308, 329, 331, 337, 344, 356, 357, 418], "perform": [3, 5, 13, 14, 16, 22, 25, 26, 28, 30, 32, 35, 42, 64, 75, 76, 77, 78, 79, 101, 102, 109, 121, 122, 128, 147, 169, 180, 181, 182, 183, 184, 207, 208, 220, 222, 223, 224, 225, 226, 228, 229, 231, 232, 234, 235, 238, 239, 243, 246, 252, 253, 254, 265, 266, 267, 273, 280, 281, 285, 288, 289, 292, 293, 296, 297, 298, 299, 300, 301, 302, 303, 304, 305, 306, 307, 309, 311, 316, 317, 320, 321, 322, 323, 324, 326, 330, 333, 334, 335, 337, 341, 343, 345, 346, 347, 348, 349, 350, 354, 357, 358, 359, 418], "damag": [3, 13, 15, 16, 19, 20, 22, 26, 28, 29, 30, 32, 42, 44, 54, 55, 58, 62, 94, 100, 101, 102, 104, 105, 106, 107, 108, 109, 110, 111, 112, 113, 114, 115, 116, 117, 118, 119, 121, 122, 123, 124, 125, 126, 127, 128, 129, 130, 131, 132, 133, 134, 135, 136, 137, 138, 147, 149, 159, 160, 163, 167, 205, 206, 207, 208, 215, 216, 221, 228, 234, 238, 240, 241, 243, 245, 246, 247, 248, 249, 251, 255, 256, 258, 260, 262, 263, 264, 265, 273, 283, 285, 286, 287, 315, 316, 320, 321, 322, 325], "loss": [3, 13, 14, 15, 16, 19, 22, 25, 26, 28, 29, 30, 32, 145, 215, 216, 221, 228, 234, 238, 239, 241, 243, 245, 246, 247, 248, 249, 251, 254, 256, 258, 260, 262, 263, 264, 265, 267, 273, 283, 285, 286, 287, 315, 316, 320, 321, 322, 323, 325], "assess": [3, 13, 20, 25, 26, 28, 31, 222, 228, 231, 234, 238, 239, 241, 242, 246, 248, 252, 254, 256, 257, 260, 263, 265, 273, 280, 281, 285, 286, 297, 302, 314, 316, 321, 323, 325, 328, 347, 354, 358, 418], "subject": [3, 14, 32, 38, 142, 143, 233, 240, 244, 246, 253, 255, 259, 266, 267, 282, 289, 291, 292, 299, 300, 303, 322, 341, 418], "region": [3, 13, 15, 21, 25, 26, 30, 31, 32, 117, 136, 217, 222, 224, 225, 226, 231, 234, 235, 238, 239, 240, 243, 244, 245, 246, 247, 248, 249, 252, 254, 255, 256, 259, 260, 261, 262, 263, 267, 280, 281, 284, 285, 286, 290, 298, 320, 321, 323, 325, 328, 332, 334, 347], "event": [3, 4, 5, 8, 11, 12, 13, 14, 15, 16, 20, 22, 23, 26, 28, 29, 30, 32, 33, 38, 39, 104, 105, 106, 107, 108, 109, 110, 111, 112, 113, 114, 115, 116, 117, 118, 119, 206, 216, 221, 222, 223, 224, 225, 226, 228, 229, 230, 233, 234, 238, 243, 245, 246, 253, 258, 260, 262, 263, 266, 267, 283, 285, 286, 288, 289, 292, 298, 303, 313, 314, 316, 320, 322, 326, 328, 334, 337, 339, 341, 352, 353, 354, 355, 356, 357, 358, 359, 361, 418], "It": [3, 4, 5, 6, 7, 8, 12, 13, 14, 16, 19, 23, 29, 30, 32, 33, 35, 121, 122, 207, 208, 220, 222, 231, 232, 233, 234, 235, 239, 240, 243, 246, 254, 255, 258, 261, 265, 267, 287, 292, 300, 301, 306, 307, 308, 333, 334, 337, 344, 347, 350, 354, 357, 358, 359, 418], "take": [3, 6, 7, 8, 12, 13, 14, 16, 23, 30, 32, 220, 231, 234, 238, 239, 240, 250, 253, 254, 255, 258, 262, 263, 266, 289, 298, 300, 301, 302, 303, 306, 309, 314, 316, 323, 328, 331, 336, 337, 346, 349, 359], "input": [3, 6, 7, 8, 10, 12, 13, 14, 16, 18, 20, 22, 24, 26, 27, 28, 35, 38, 39, 67, 172, 220, 222, 223, 224, 225, 226, 229, 230, 233, 234, 239, 243, 246, 247, 252, 254, 258, 261, 262, 265, 267, 281, 289, 290, 292, 293, 294, 295, 296, 297, 298, 299, 300, 301, 302, 303, 311, 314, 316, 317, 319, 320, 322, 323, 324, 328, 330, 331, 332, 333, 334, 335, 336, 337, 338, 339, 340, 341, 344, 346, 348, 349, 351, 353, 354, 356, 357, 359, 361, 374, 406], "properti": [3, 4, 7, 15, 19, 20, 33, 104, 105, 106, 107, 108, 109, 110, 111, 112, 113, 114, 115, 116, 117, 118, 119, 206, 231, 246, 252, 253, 254, 266, 279, 288, 289, 290, 292, 293, 304, 313, 339, 341, 347], "determin": [3, 4, 13, 14, 16, 27, 30, 33, 53, 115, 134, 158, 222, 228, 231, 233, 239, 253, 254, 266, 281, 289, 304, 311, 324, 337, 341, 347, 357, 359], "e": [3, 13, 14, 16, 23, 24, 29, 30, 32, 33, 34, 35, 38, 69, 75, 76, 77, 78, 79, 83, 87, 100, 101, 102, 104, 105, 106, 107, 108, 109, 110, 111, 112, 113, 114, 115, 116, 117, 118, 119, 121, 122, 135, 174, 180, 181, 182, 183, 184, 188, 192, 205, 206, 207, 208, 216, 222, 223, 224, 225, 226, 227, 228, 229, 231, 232, 233, 234, 235, 238, 239, 240, 241, 242, 243, 244, 245, 246, 250, 251, 253, 254, 255, 256, 257, 258, 259, 260, 263, 265, 266, 267, 279, 280, 281, 282, 288, 290, 291, 292, 293, 294, 296, 297, 299, 300, 301, 302, 306, 308, 309, 316, 319, 320, 322, 328, 331, 332, 334, 340, 341, 343, 344, 345, 346, 347, 348, 349, 351, 352, 353, 354, 355, 357, 361, 418], "g": [3, 13, 14, 29, 30, 32, 33, 34, 35, 36, 38, 69, 75, 76, 77, 78, 79, 83, 87, 94, 101, 102, 104, 105, 106, 107, 108, 109, 110, 111, 112, 113, 114, 115, 116, 117, 118, 119, 121, 122, 174, 180, 181, 182, 183, 184, 188, 192, 206, 207, 208, 217, 219, 222, 223, 224, 225, 226, 229, 231, 233, 234, 235, 238, 239, 240, 241, 242, 243, 244, 245, 246, 250, 253, 254, 255, 256, 257, 258, 259, 260, 263, 266, 267, 280, 282, 287, 288, 290, 292, 293, 294, 296, 297, 300, 306, 308, 309, 316, 319, 328, 331, 334, 341, 344, 345, 346, 347, 352, 354, 355, 357, 361, 418], "occup": [3, 33, 206, 207, 208, 209, 222, 238, 239, 240, 242, 248, 254, 255, 257, 263, 265, 280, 286, 287], "structur": [3, 8, 13, 14, 15, 18, 19, 20, 25, 27, 30, 32, 35, 39, 50, 51, 53, 58, 61, 68, 98, 104, 105, 106, 107, 108, 109, 110, 111, 112, 113, 114, 115, 116, 117, 118, 119, 123, 124, 125, 126, 127, 128, 129, 130, 131, 132, 133, 134, 135, 136, 137, 138, 140, 155, 156, 158, 163, 166, 173, 203, 206, 210, 212, 213, 216, 222, 223, 224, 225, 226, 228, 229, 230, 231, 232, 233, 234, 235, 239, 240, 241, 242, 245, 246, 248, 250, 251, 253, 254, 255, 256, 260, 262, 263, 266, 267, 280, 281, 283, 286, 287, 289, 292, 294, 295, 296, 298, 303, 313, 316, 317, 319, 320, 323, 328, 337, 344, 346, 347, 348, 354, 355, 358, 361, 418], "replac": [3, 20, 33, 35, 38, 58, 64, 100, 163, 169, 205, 222, 224, 225, 226, 231, 238, 239, 242, 280, 281, 300, 301, 303, 316, 318, 335, 345, 346, 347], "cost": [3, 20, 30, 32, 41, 42, 43, 44, 46, 47, 48, 49, 50, 51, 53, 54, 55, 57, 59, 66, 67, 68, 69, 70, 73, 75, 76, 77, 78, 79, 81, 82, 83, 84, 85, 87, 89, 90, 91, 94, 97, 146, 147, 148, 149, 150, 151, 152, 153, 154, 155, 156, 158, 159, 160, 162, 163, 164, 167, 169, 171, 172, 173, 174, 175, 178, 180, 181, 182, 183, 184, 186, 187, 188, 189, 190, 192, 194, 195, 196, 202, 206, 207, 208, 209, 211, 212, 213, 222, 228, 231, 234, 238, 239, 242, 258, 281, 285, 316, 335], "number": [3, 11, 14, 16, 17, 19, 20, 30, 33, 34, 36, 38, 222, 224, 225, 226, 228, 231, 232, 233, 234, 238, 239, 240, 241, 242, 243, 245, 246, 247, 248, 250, 254, 255, 257, 258, 260, 261, 262, 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335, 336, 337, 340, 341, 343, 345, 346, 347, 348, 349, 351, 352, 353, 354, 355, 356, 357, 359, 360, 406, 416, 418], "bim": [3, 4, 6, 7, 8, 11, 12, 14, 15, 19, 22, 26, 28, 33, 216, 243, 254, 258, 337], "well": [3, 22, 39, 109, 128, 206, 207, 208, 209, 231, 232, 234, 240, 242, 245, 246, 247, 248, 249, 257, 262, 263, 265, 267, 286, 299, 300, 301, 302, 314, 335, 336, 346, 347, 357], "respons": [3, 4, 8, 10, 12, 13, 14, 15, 16, 19, 20, 22, 23, 24, 26, 27, 30, 31, 32, 40, 44, 54, 64, 81, 82, 83, 84, 85, 89, 90, 91, 94, 104, 105, 106, 107, 108, 109, 110, 111, 112, 113, 114, 115, 116, 117, 118, 119, 149, 159, 169, 186, 187, 188, 189, 190, 194, 195, 196, 206, 207, 208, 209, 222, 223, 225, 226, 228, 229, 232, 234, 240, 245, 246, 247, 249, 260, 261, 262, 263, 273, 281, 285, 289, 292, 296, 298, 299, 300, 302, 303, 309, 311, 313, 316, 323, 324, 325, 328, 331, 332, 334, 335, 337, 341, 343, 344, 345, 346, 347, 349, 351, 354, 355, 358, 359, 360, 406, 418], "simul": [3, 4, 5, 6, 7, 8, 10, 13, 14, 15, 16, 18, 19, 20, 21, 22, 23, 24, 26, 27, 28, 30, 32, 33, 38, 216, 217, 222, 223, 224, 225, 226, 228, 229, 230, 231, 234, 235, 238, 240, 243, 245, 246, 247, 248, 252, 253, 255, 258, 260, 262, 265, 266, 273, 281, 283, 284, 285, 286, 289, 290, 292, 293, 296, 297, 299, 300, 301, 303, 304, 307, 311, 312, 313, 314, 315, 316, 319, 320, 321, 322, 323, 324, 325, 326, 328, 330, 331, 332, 334, 335, 336, 337, 338, 341, 343, 345, 346, 350, 354, 355, 357, 358, 359, 361, 401, 406, 416, 418], "output": [3, 4, 10, 13, 14, 15, 16, 18, 19, 22, 23, 24, 26, 28, 33, 34, 36, 38, 220, 222, 223, 224, 225, 226, 229, 232, 234, 239, 243, 246, 247, 254, 258, 262, 280, 285, 289, 293, 298, 299, 300, 301, 302, 309, 311, 313, 314, 316, 319, 320, 321, 322, 324, 328, 331, 332, 333, 334, 335, 336, 338, 339, 341, 344, 345, 346, 348, 349, 355, 357, 358, 359, 361, 406], "record": [3, 11, 14, 19, 20, 26, 27, 30, 33, 38, 222, 224, 225, 226, 230, 234, 235, 238, 239, 265, 267, 287, 292, 296, 297, 298, 299, 300, 301, 302, 303, 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253, 266, 267, 287, 288, 292, 295, 296, 297, 298, 299, 302, 303, 306, 309, 311, 314, 324, 328, 330, 331, 332, 333, 334, 335, 336, 337, 341, 345, 346, 348, 349, 352, 353, 354, 356, 359, 360, 361, 374, 406, 418], "estim": [3, 12, 14, 15, 19, 20, 30, 32, 121, 122, 207, 208, 222, 223, 224, 225, 226, 228, 229, 232, 234, 235, 238, 240, 243, 245, 246, 247, 248, 249, 251, 252, 253, 254, 255, 258, 260, 261, 262, 263, 264, 265, 266, 267, 273, 281, 285, 286, 288, 292, 293, 301, 302, 314, 316, 317, 319, 323, 331, 332, 334, 335, 336, 343, 345, 346, 347, 349, 357, 406], "dv": [3, 19, 22, 23, 26, 28, 30, 32, 33, 222, 228, 243, 258], "each": [3, 4, 5, 6, 7, 8, 10, 11, 13, 14, 15, 16, 19, 20, 22, 23, 24, 26, 28, 30, 32, 33, 39, 46, 48, 49, 50, 51, 53, 69, 121, 122, 151, 153, 154, 155, 156, 158, 174, 207, 208, 220, 222, 228, 231, 232, 234, 235, 238, 239, 240, 241, 242, 243, 246, 253, 254, 255, 256, 257, 261, 265, 266, 267, 279, 280, 281, 284, 287, 288, 292, 293, 295, 296, 298, 299, 300, 302, 314, 316, 318, 319, 323, 328, 331, 332, 333, 334, 335, 336, 337, 338, 340, 341, 345, 346, 347, 348, 349, 350, 352, 353, 354, 356, 357, 358, 360, 361, 406, 416], "save": [3, 7, 12, 23, 30, 222, 223, 224, 225, 226, 229, 231, 234, 246, 253, 294, 295, 297, 298, 300, 301, 309, 313, 316, 317, 319, 325, 341, 344, 350, 354, 355, 358], "its": [3, 4, 7, 8, 11, 13, 14, 16, 24, 28, 33, 58, 116, 117, 121, 122, 135, 136, 163, 207, 208, 231, 232, 233, 234, 239, 240, 241, 245, 246, 247, 248, 254, 255, 256, 260, 261, 262, 263, 265, 267, 283, 284, 286, 292, 293, 306, 309, 314, 328, 330, 336, 341, 346, 352, 353, 356, 357, 361, 418], "correspond": [3, 4, 5, 7, 8, 11, 13, 14, 15, 26, 30, 32, 42, 147, 222, 228, 231, 232, 234, 239, 240, 242, 253, 254, 255, 257, 262, 265, 266, 267, 280, 287, 288, 292, 293, 294, 295, 297, 299, 300, 302, 314, 328, 330, 331, 332, 334, 335, 337, 341, 343, 344, 345, 346, 347, 349, 353, 354, 357, 361, 406], "work": [3, 4, 7, 8, 12, 13, 14, 16, 22, 26, 29, 33, 38, 75, 76, 77, 78, 79, 94, 115, 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223, 224, 225, 226, 229, 231, 238, 281, 284, 289, 305, 306, 307, 328, 332, 350, 361, 418], "packag": [3, 5, 14, 35, 86, 191, 231, 258, 306, 307, 309, 316, 319, 329, 330, 344, 347, 353, 406], "main": [3, 4, 5, 6, 7, 8, 11, 12, 14, 29, 30, 35, 87, 100, 192, 205, 231, 240, 242, 246, 255, 281, 292, 300, 302, 320, 328, 336, 341, 346, 347, 361], "html": [3, 4, 5, 6, 7, 8, 11, 12, 238, 347], "demand": [4, 14, 15, 38, 53, 54, 55, 58, 64, 73, 81, 82, 83, 84, 85, 89, 90, 91, 94, 104, 105, 106, 107, 108, 109, 110, 111, 112, 113, 114, 115, 116, 117, 118, 119, 122, 158, 159, 160, 163, 169, 178, 186, 187, 188, 189, 190, 194, 195, 196, 206, 208, 216, 222, 234, 248, 253, 280, 286, 287, 288, 296, 297, 299, 302, 314, 316, 320, 321, 330, 346, 355, 361], "paramet": [4, 6, 12, 13, 14, 15, 16, 19, 20, 30, 32, 58, 73, 100, 163, 178, 205, 216, 222, 223, 224, 225, 226, 228, 229, 231, 239, 253, 254, 266, 267, 287, 288, 292, 293, 295, 296, 299, 300, 301, 302, 314, 316, 317, 319, 320, 322, 330, 331, 332, 334, 335, 336, 338, 340, 341, 344, 345, 346, 347, 348, 354, 355, 356, 357, 361, 374, 406, 415], "expect": [4, 15, 39, 41, 83, 87, 114, 133, 146, 188, 192, 231, 235, 239, 241, 242, 243, 252, 254, 256, 257, 258, 265, 267, 280, 300, 302, 344, 346, 347, 349, 406], "from": [4, 5, 7, 13, 14, 15, 16, 18, 20, 23, 26, 28, 29, 30, 32, 33, 34, 36, 38, 39, 41, 47, 51, 53, 64, 70, 97, 100, 101, 102, 104, 105, 106, 107, 108, 109, 110, 111, 112, 113, 114, 115, 116, 117, 118, 119, 135, 146, 152, 156, 158, 169, 175, 202, 205, 206, 220, 222, 223, 224, 225, 226, 228, 229, 230, 231, 232, 233, 234, 235, 238, 239, 240, 241, 242, 243, 245, 246, 247, 248, 249, 250, 251, 252, 253, 254, 255, 256, 257, 258, 260, 261, 262, 263, 265, 266, 267, 279, 280, 281, 283, 284, 286, 288, 289, 290, 292, 293, 295, 296, 297, 298, 299, 300, 301, 302, 306, 307, 308, 309, 310, 311, 312, 313, 314, 315, 316, 318, 319, 320, 321, 322, 323, 324, 326, 328, 330, 331, 332, 333, 334, 335, 337, 338, 340, 341, 344, 346, 347, 348, 349, 350, 352, 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231, 234, 235, 239, 240, 241, 242, 243, 246, 253, 254, 255, 261, 266, 267, 279, 280, 281, 285, 286, 288, 289, 290, 295, 297, 298, 301, 302, 308, 309, 313, 314, 320, 322, 328, 330, 333, 334, 335, 339, 340, 341, 347, 354, 357, 361], "direct": [4, 19, 20, 22, 23, 29, 30, 33, 86, 101, 102, 112, 114, 131, 133, 191, 221, 222, 228, 231, 235, 239, 240, 243, 254, 258, 262, 284, 287, 292, 293, 295, 299, 300, 301, 302, 330, 341, 347, 348, 353, 354, 356, 357, 406, 418], "dof": [4, 30, 292, 353, 359], "an": [4, 7, 13, 14, 15, 16, 18, 19, 20, 22, 23, 24, 26, 27, 29, 30, 32, 33, 34, 35, 36, 38, 39, 51, 53, 54, 55, 104, 105, 106, 107, 108, 109, 110, 111, 112, 113, 114, 115, 116, 117, 118, 119, 123, 156, 158, 159, 160, 206, 220, 222, 223, 224, 225, 226, 228, 229, 230, 231, 232, 234, 235, 238, 239, 240, 241, 242, 243, 244, 246, 248, 251, 253, 254, 255, 258, 259, 263, 265, 266, 267, 281, 282, 285, 286, 287, 288, 290, 291, 292, 294, 295, 297, 299, 300, 301, 302, 304, 306, 307, 308, 309, 316, 319, 321, 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28, 30, 32, 33, 34, 35, 36, 38, 223, 229, 292, 300, 301, 302, 306, 307, 309, 328, 337, 341, 347, 359], "written": [5, 13, 14, 16, 26, 29, 34, 36, 232, 234, 242, 247, 249, 262, 330, 345, 346, 347], "driver": [5, 26, 308, 328, 330, 350], "which": [5, 13, 14, 15, 16, 17, 19, 20, 22, 23, 24, 26, 27, 29, 30, 32, 33, 35, 51, 53, 101, 102, 104, 105, 106, 107, 108, 109, 110, 111, 112, 113, 114, 115, 116, 117, 118, 119, 127, 131, 156, 158, 206, 220, 222, 223, 224, 225, 226, 228, 229, 230, 231, 232, 233, 234, 235, 238, 239, 240, 241, 242, 243, 245, 246, 248, 252, 253, 254, 255, 256, 258, 260, 263, 265, 266, 267, 279, 281, 283, 285, 286, 288, 289, 292, 293, 294, 295, 296, 297, 298, 299, 300, 301, 302, 305, 306, 307, 308, 309, 320, 329, 330, 331, 332, 333, 334, 335, 336, 337, 340, 341, 344, 346, 347, 348, 349, 350, 352, 353, 354, 356, 357, 359, 361, 416], "call": [5, 15, 22, 23, 26, 33, 34, 35, 36, 38, 39, 231, 232, 239, 240, 242, 246, 255, 267, 297, 299, 313, 328, 332, 333, 334, 346, 349, 357], "backend": [5, 13, 16, 22, 23, 24, 26, 28, 29, 30, 31, 32, 39, 234, 248, 263, 286, 289, 292, 293, 294, 295, 296, 297, 298, 299, 305, 306, 309, 316, 319, 323, 328, 341, 347, 356, 357, 361], "execut": [5, 12, 13, 15, 16, 19, 23, 24, 26, 28, 30, 32, 33, 35, 239, 243, 245, 246, 247, 249, 254, 255, 258, 260, 262, 294, 295, 300, 306, 307, 308, 309, 314, 334, 337, 347, 349, 350, 357, 406], "r2d": [5, 13, 14, 16, 27, 230, 234, 235, 247, 262, 322, 323, 325], "first": [5, 13, 14, 16, 23, 24, 26, 27, 28, 30, 35, 38, 58, 73, 163, 178, 222, 223, 224, 225, 226, 228, 229, 230, 231, 233, 234, 235, 238, 239, 242, 246, 253, 254, 258, 261, 265, 266, 267, 287, 292, 294, 296, 297, 299, 300, 301, 302, 306, 308, 309, 316, 317, 330, 331, 332, 334, 340, 341, 344, 346, 347, 349, 350, 352, 353, 354, 357, 360], "popul": [5, 12, 15, 26, 33, 222, 228, 233, 240, 243, 248, 253, 258, 263, 266, 279, 281, 285, 286, 298, 299, 301, 302, 323, 338, 341, 354], "valu": [5, 10, 13, 16, 19, 20, 29, 30, 32, 33, 35, 38, 39, 54, 55, 64, 67, 81, 82, 83, 84, 85, 89, 90, 91, 94, 104, 105, 106, 107, 108, 109, 110, 111, 112, 113, 114, 115, 116, 117, 118, 119, 159, 160, 169, 172, 186, 187, 188, 189, 190, 194, 195, 196, 206, 222, 228, 230, 231, 232, 233, 235, 238, 239, 240, 241, 242, 246, 252, 253, 254, 255, 256, 265, 266, 267, 281, 288, 292, 293, 294, 295, 296, 297, 298, 299, 300, 301, 302, 307, 317, 319, 330, 331, 332, 333, 334, 335, 337, 341, 343, 344, 345, 346, 347, 348, 349, 352, 353, 354, 355, 356, 357, 359, 406], "distribut": [5, 14, 20, 29, 30, 32, 33, 38, 80, 86, 92, 108, 114, 127, 133, 185, 191, 197, 221, 222, 223, 224, 225, 226, 228, 229, 230, 231, 234, 235, 239, 242, 248, 252, 253, 254, 257, 258, 263, 265, 266, 267, 280, 281, 286, 287, 288, 289, 292, 293, 295, 296, 299, 302, 317, 321, 326, 330, 331, 332, 333, 334, 338, 341, 345, 346, 347, 348, 349, 352, 353, 357, 374, 414], "sim": [5, 12, 15, 26, 38, 75, 76, 77, 78, 79, 83, 87, 180, 181, 182, 183, 184, 188, 192, 216, 231, 232, 292, 293, 294, 295, 296, 297, 298, 299, 300, 301, 302, 313, 337, 338, 343, 345, 346, 359, 361], "befor": [5, 13, 16, 97, 117, 136, 202, 231, 232, 240, 243, 248, 249, 253, 263, 265, 266, 267, 286, 291, 292, 293, 294, 295, 306, 309, 328, 340, 341, 354, 358, 359], "If": [5, 18, 19, 20, 22, 23, 24, 33, 34, 35, 36, 38, 231, 233, 234, 235, 240, 241, 244, 247, 256, 258, 259, 262, 282, 289, 290, 291, 292, 293, 296, 300, 301, 306, 307, 308, 309, 312, 315, 318, 321, 325, 328, 331, 335, 337, 341, 346, 347, 349, 352, 353, 354, 356, 357, 359, 360, 361, 406], "directli": [5, 14, 23, 32, 33, 68, 173, 232, 234, 235, 246, 251, 263, 267, 280, 295, 297, 317, 344, 345, 346, 347, 348, 353, 354, 357], "without": [5, 29, 47, 51, 53, 64, 83, 104, 107, 109, 110, 123, 126, 128, 129, 152, 156, 158, 169, 188, 221, 231, 255, 292, 306, 316, 319, 333, 334, 336, 344, 345, 346, 349, 354], "creat": [6, 7, 13, 14, 15, 16, 22, 23, 26, 27, 33, 34, 35, 36, 38, 44, 149, 222, 223, 224, 225, 226, 228, 229, 233, 238, 239, 240, 244, 245, 246, 247, 254, 259, 260, 262, 263, 282, 291, 292, 294, 297, 299, 300, 306, 307, 308, 309, 311, 313, 314, 324, 326, 328, 330, 334, 336, 337, 338, 341, 346, 353, 355, 357, 359, 361], "rang": [6, 13, 16, 30, 38, 222, 228, 231, 232, 238, 246, 260, 261, 300, 301, 331, 346, 347, 354, 357, 358], "asset": [6, 15, 16, 19, 20, 22, 23, 24, 26, 28, 30, 32, 33, 222, 224, 225, 226, 228, 242, 243, 245, 246, 247, 248, 258, 260, 262, 263, 265, 267, 273, 281, 285, 286, 288, 316, 320, 321, 322, 323, 328], "id": [6, 19, 22, 23, 26, 30, 33, 34, 35, 36, 238, 239, 243, 254, 258, 265, 267, 279, 330], "select": [6, 7, 11, 13, 14, 16, 19, 23, 27, 30, 32, 33, 34, 35, 36, 38, 222, 224, 225, 226, 230, 231, 232, 234, 241, 243, 247, 248, 249, 252, 253, 254, 256, 258, 262, 265, 266, 288, 289, 290, 292, 293, 296, 297, 299, 302, 303, 306, 307, 309, 311, 313, 316, 318, 320, 322, 323, 324, 326, 328, 330, 334, 335, 337, 338, 340, 341, 343, 345, 346, 347, 348, 349, 350, 352, 353, 355, 356, 357, 358, 359, 360, 361, 406], "express": [6, 29, 104, 105, 106, 107, 108, 109, 110, 111, 112, 113, 114, 115, 116, 117, 118, 119, 206, 218, 219, 221, 238, 245, 246, 250, 283, 285, 323, 335, 337, 341, 357], "min": [6, 22, 26, 30, 32, 33, 234, 242, 267, 300, 302, 357], "max": [6, 22, 26, 30, 32, 33, 238, 242, 300, 302, 333, 343, 345, 357, 359, 406, 416], "configur": [6, 8, 11, 22, 23, 24, 26, 28, 30, 32, 33, 34, 35, 36, 234, 240, 242, 243, 255, 257, 258, 280, 287, 293, 294, 295, 296, 300, 317, 344, 355], "specif": [6, 13, 16, 20, 23, 24, 27, 29, 30, 33, 34, 35, 36, 38, 100, 205, 222, 224, 225, 226, 231, 234, 235, 239, 240, 241, 242, 243, 244, 246, 247, 248, 249, 253, 255, 256, 258, 259, 262, 263, 265, 266, 267, 286, 288, 293, 294, 296, 298, 300, 306, 309, 313, 316, 319, 323, 326, 332, 333, 336, 339, 340, 341, 343, 345, 346, 347, 357, 406, 415, 418], "sourc": [6, 13, 16, 29, 30, 32, 33, 34, 35, 36, 104, 105, 106, 107, 108, 109, 110, 111, 112, 113, 114, 115, 116, 117, 118, 119, 206, 221, 222, 223, 224, 225, 226, 227, 228, 229, 230, 231, 232, 234, 239, 240, 241, 245, 247, 248, 249, 253, 254, 255, 256, 260, 262, 266, 267, 281, 284, 286, 288, 289, 290, 294, 295, 296, 308, 316, 320, 322, 323, 330, 336, 344, 346, 347, 418], "pars": [6, 8, 13, 14, 16, 26, 28, 100, 205, 238, 239, 246, 250, 254, 258, 279, 290, 353], "result": [6, 11, 12, 13, 14, 16, 18, 20, 22, 23, 24, 26, 28, 30, 32, 39, 106, 112, 116, 125, 131, 135, 222, 223, 224, 225, 226, 228, 229, 231, 232, 233, 234, 235, 239, 245, 246, 247, 248, 249, 250, 253, 254, 260, 262, 263, 266, 273, 280, 281, 283, 284, 286, 287, 292, 293, 296, 302, 306, 307, 309, 312, 313, 314, 315, 316, 319, 321, 323, 328, 330, 331, 332, 333, 334, 335, 336, 341, 343, 345, 347, 348, 349, 354, 355, 358, 359, 361], "folder": [6, 11, 13, 16, 19, 20, 22, 23, 24, 26, 30, 32, 34, 35, 36, 38, 230, 243, 258, 292, 296, 299, 300, 306, 307, 308, 309, 328, 329, 341, 347, 352, 353, 361], "process": [6, 7, 13, 14, 16, 20, 26, 28, 35, 38, 121, 206, 207, 208, 209, 220, 222, 223, 224, 225, 226, 229, 232, 234, 235, 238, 239, 240, 241, 243, 246, 247, 248, 249, 252, 254, 256, 258, 263, 265, 280, 284, 286, 288, 293, 294, 302, 303, 306, 309, 310, 311, 313, 314, 316, 317, 319, 323, 324, 328, 332, 333, 334, 338, 341, 342, 343, 345, 346, 348, 349, 350, 354, 355, 357, 359, 361, 406], "site": [7, 8, 11, 14, 15, 19, 26, 28, 30, 31, 32, 39, 104, 105, 106, 107, 108, 109, 110, 111, 112, 113, 114, 115, 116, 117, 118, 119, 126, 206, 222, 224, 225, 226, 230, 234, 235, 239, 240, 241, 242, 246, 253, 255, 261, 265, 266, 267, 284, 286, 288, 290, 294, 295, 296, 298, 301, 303, 311, 313, 316, 320, 322, 323, 328, 341, 347, 351, 354, 355, 356, 418], "associ": [7, 14, 19, 28, 67, 172, 223, 226, 229, 231, 238, 239, 240, 242, 246, 247, 248, 254, 255, 257, 261, 262, 263, 267, 286, 330, 332, 333, 336, 340, 341, 346, 359], "one": [7, 13, 14, 15, 16, 19, 20, 23, 24, 28, 30, 32, 33, 39, 42, 43, 44, 50, 51, 53, 67, 97, 108, 112, 114, 116, 127, 131, 133, 135, 147, 148, 149, 155, 156, 158, 172, 202, 220, 230, 231, 233, 234, 235, 239, 240, 243, 254, 255, 258, 263, 280, 287, 288, 292, 293, 294, 295, 297, 298, 299, 300, 301, 302, 306, 308, 309, 328, 331, 332, 333, 334, 335, 337, 341, 346, 347, 349, 352, 353, 354, 357, 358, 360, 361, 406], "contain": [7, 10, 13, 15, 18, 19, 22, 23, 29, 34, 35, 36, 109, 128, 220, 226, 230, 235, 238, 239, 241, 246, 247, 254, 256, 262, 279, 292, 295, 296, 299, 300, 306, 307, 308, 309, 328, 330, 331, 332, 338, 339, 341, 346, 347, 348, 349, 352, 353, 357, 359, 374, 406, 414], "intens": [7, 15, 19, 27, 30, 32, 33, 216, 222, 224, 225, 226, 230, 234, 236, 242, 246, 248, 252, 253, 257, 263, 265, 266, 281, 284, 286, 287, 290, 297, 298, 300, 301, 313, 320, 322, 323, 344, 347, 354, 355, 406], "measur": [7, 15, 19, 27, 30, 32, 104, 105, 106, 107, 108, 109, 110, 111, 112, 113, 114, 115, 116, 117, 118, 119, 206, 216, 222, 223, 224, 225, 226, 229, 230, 232, 234, 235, 239, 240, 242, 246, 248, 252, 253, 254, 255, 257, 261, 263, 265, 266, 267, 289, 290, 292, 297, 298, 300, 301, 313, 317, 320, 322, 323, 324, 325, 331, 332, 336, 344, 346, 347, 348, 349, 354, 355, 357, 406], "obtain": [7, 13, 14, 16, 30, 35, 38, 222, 223, 224, 225, 226, 229, 230, 231, 232, 233, 235, 238, 239, 254, 267, 292, 293, 299, 301, 302, 303, 309, 314, 319, 323, 334, 337, 341, 345, 346, 348, 349, 354, 357, 358, 359, 361], "name": [7, 10, 11, 13, 14, 16, 19, 20, 23, 25, 26, 30, 32, 33, 35, 235, 238, 239, 240, 254, 255, 292, 293, 299, 300, 301, 302, 303, 306, 307, 308, 309, 313, 330, 332, 333, 334, 339, 340, 341, 344, 347, 348, 349, 352, 353, 354, 355, 357, 359], "format": [7, 14, 18, 20, 22, 23, 24, 29, 30, 33, 222, 228, 230, 234, 238, 239, 240, 246, 254, 255, 280, 284, 293, 297, 301, 306, 311, 314, 316, 319, 320, 322, 323, 330, 344, 347, 352, 354, 355, 357, 358, 406], "consolid": 8, "analysi": [8, 12, 14, 15, 19, 30, 32, 35, 38, 39, 216, 223, 228, 229, 233, 234, 235, 239, 240, 243, 245, 248, 251, 254, 258, 260, 263, 281, 283, 286, 287, 288, 296, 303, 308, 311, 313, 316, 319, 320, 322, 323, 324, 326, 328, 330, 331, 335, 337, 341, 342, 343, 344, 345, 347, 348, 350, 351, 355, 358, 359, 406, 416, 418], "repres": [8, 13, 20, 29, 54, 55, 64, 81, 82, 83, 84, 85, 89, 90, 91, 94, 104, 105, 106, 107, 108, 109, 110, 111, 112, 113, 114, 115, 116, 117, 118, 119, 123, 124, 125, 126, 127, 128, 129, 130, 131, 132, 133, 134, 135, 136, 137, 138, 159, 160, 169, 186, 187, 188, 189, 190, 194, 195, 196, 206, 209, 222, 224, 225, 226, 230, 231, 232, 233, 234, 239, 241, 242, 254, 256, 257, 267, 281, 286, 290, 296, 299, 300, 301, 302, 303, 349, 351, 352, 353, 354, 357, 358, 361], "finit": [8, 12, 14, 16, 35, 216, 232, 252, 283, 284, 286, 287, 299, 302, 344, 355, 357, 359, 361], "element": [8, 12, 13, 14, 16, 17, 30, 35, 109, 110, 111, 114, 117, 121, 128, 129, 130, 133, 136, 207, 216, 231, 233, 234, 283, 287, 292, 293, 299, 302, 349, 355, 357, 359, 361], "bknd": 10, "0039": 10, "No": [10, 23, 26, 50, 53, 70, 83, 87, 101, 102, 155, 158, 175, 188, 192, 218, 219, 230, 239, 240, 255, 267, 293, 300, 328, 332, 333, 346, 354, 357, 418], "descript": [10, 23, 29, 46, 101, 102, 151, 222, 223, 224, 225, 226, 228, 229, 230, 240, 243, 245, 246, 247, 248, 249, 255, 258, 260, 262, 263, 267, 273, 280, 281, 285, 286, 287, 316, 328, 354, 361, 374], "cli": [10, 23], "inputfil": 10, "lt": 10, "filenam": [10, 359], "r": [10, 38, 42, 147, 231, 234, 239, 240, 246, 248, 255, 263, 295, 296, 297, 302, 332, 336, 344, 347, 357, 418], "gt": 10, "outfil": [10, 406], "w": [10, 13, 14, 16, 22, 27, 30, 32, 33, 38, 41, 42, 43, 44, 62, 66, 77, 146, 147, 148, 149, 167, 171, 182, 219, 231, 232, 234, 235, 238, 239, 240, 246, 255, 279, 281, 285, 292, 336, 345, 346, 357, 418], "tabfil": 10, "tab": [10, 35, 38, 41, 146, 230, 239, 254, 258, 292, 293, 294, 295, 296, 297, 298, 299, 300, 301, 302, 303, 309, 313, 316, 319, 328, 331, 332, 337, 338, 339, 340, 341, 343, 344, 345, 346, 349, 350, 352, 353, 354, 356, 358, 359, 360, 406], "0041": 10, "simcenteruq": [10, 236, 297, 302, 311, 317, 319, 324, 340, 344, 345, 346, 350, 355], "under": [11, 14, 21, 32, 33, 35, 41, 101, 102, 146, 218, 219, 221, 222, 223, 224, 225, 226, 228, 229, 230, 232, 234, 235, 240, 243, 245, 246, 248, 253, 258, 260, 261, 262, 263, 266, 267, 285, 286, 287, 288, 289, 290, 293, 297, 299, 300, 301, 302, 303, 306, 307, 308, 309, 314, 316, 321, 332, 344, 347, 354, 357, 358, 361, 418], "For": [11, 13, 14, 16, 18, 19, 22, 23, 24, 25, 26, 27, 29, 30, 32, 33, 34, 35, 36, 58, 109, 128, 163, 220, 222, 230, 231, 232, 234, 235, 238, 239, 240, 241, 242, 243, 246, 248, 253, 254, 256, 257, 258, 261, 263, 265, 266, 267, 279, 281, 283, 286, 288, 292, 293, 294, 295, 296, 297, 298, 299, 300, 301, 302, 306, 307, 317, 321, 328, 331, 332, 334, 335, 336, 337, 338, 340, 341, 344, 345, 347, 348, 349, 350, 352, 353, 354, 356, 357, 359, 361], "set": [11, 13, 14, 15, 16, 20, 22, 23, 26, 28, 30, 32, 33, 35, 38, 39, 101, 102, 104, 105, 106, 107, 108, 109, 110, 111, 112, 113, 114, 115, 116, 117, 118, 119, 206, 220, 222, 223, 226, 228, 229, 230, 232, 233, 234, 238, 239, 242, 243, 247, 254, 258, 262, 263, 265, 267, 280, 284, 292, 293, 294, 295, 297, 298, 302, 306, 307, 309, 314, 316, 319, 328, 330, 332, 333, 334, 335, 336, 337, 338, 341, 344, 346, 347, 348, 349, 352, 353, 354, 357, 358, 359], "candid": [11, 232, 234, 316], "must": [11, 18, 19, 25, 27, 29, 109, 128, 221, 228, 230, 233, 239, 240, 242, 255, 292, 299, 306, 307, 309, 328, 330, 331, 332, 333, 335, 337, 338, 340, 341, 349, 350, 352, 353, 354, 357, 358, 359], "input_data": [11, 19, 22, 23, 26, 30, 32, 33], "onc": [11, 13, 14, 16, 23, 30, 33, 35, 58, 73, 163, 178, 231, 234, 239, 241, 243, 254, 256, 258, 294, 295, 298, 302, 306, 307, 308, 309, 330, 333, 338, 341, 344, 347, 350, 354, 357, 358, 361], "chosen": [11, 13, 14, 16, 19, 25, 26, 231, 232, 233, 292, 293, 296, 302, 332, 333, 337, 357], "algorithm": [11, 13, 30, 32, 222, 223, 224, 225, 226, 229, 232, 234, 239, 254, 284, 300, 302, 317, 325, 326, 331, 332, 333, 334, 337, 344, 345, 347, 348, 349, 350, 354, 357, 358, 415, 416], "method": [11, 13, 14, 16, 23, 24, 26, 29, 30, 32, 33, 35, 38, 228, 234, 235, 236, 239, 240, 243, 245, 246, 253, 254, 258, 260, 263, 266, 283, 285, 286, 287, 288, 289, 292, 293, 294, 295, 297, 299, 300, 301, 302, 303, 313, 314, 315, 316, 317, 318, 319, 321, 324, 330, 331, 332, 333, 335, 336, 341, 342, 344, 345, 346, 347, 348, 349, 350, 352, 353, 354, 355, 357, 358, 361, 401, 406, 415, 416], "make": [11, 13, 14, 15, 23, 29, 33, 34, 35, 36, 222, 228, 231, 232, 233, 239, 240, 241, 246, 253, 255, 256, 266, 267, 281, 289, 300, 301, 302, 306, 307, 309, 328, 330, 347, 357], "script": [12, 13, 14, 16, 19, 23, 24, 26, 27, 33, 222, 224, 225, 226, 228, 233, 234, 239, 240, 243, 247, 249, 254, 255, 258, 262, 292, 296, 300, 302, 306, 309, 311, 319, 320, 322, 328, 332, 333, 337, 341, 344, 346, 347, 349, 357, 359, 374, 414], "These": [12, 14, 15, 16, 24, 33, 104, 105, 106, 107, 108, 109, 110, 111, 112, 113, 114, 115, 116, 117, 118, 119, 123, 125, 126, 127, 128, 129, 130, 131, 132, 133, 136, 137, 138, 206, 223, 224, 226, 229, 230, 232, 233, 234, 235, 239, 240, 241, 242, 246, 247, 249, 253, 254, 255, 256, 257, 258, 262, 263, 266, 279, 281, 284, 287, 288, 289, 290, 293, 295, 297, 318, 325, 328, 330, 334, 341, 349, 357, 359, 361], "mai": [12, 13, 14, 16, 19, 20, 22, 23, 25, 33, 34, 35, 36, 42, 44, 51, 53, 58, 94, 104, 106, 112, 115, 116, 117, 118, 119, 123, 125, 131, 134, 135, 136, 137, 138, 147, 149, 156, 158, 163, 220, 231, 234, 235, 238, 239, 240, 241, 245, 247, 249, 254, 255, 256, 258, 260, 262, 266, 267, 280, 281, 292, 294, 295, 298, 300, 301, 302, 306, 307, 308, 309, 312, 315, 316, 318, 319, 321, 323, 325, 334, 335, 336, 338, 340, 341, 343, 345, 346, 347, 354, 358, 360, 406], "includ": [12, 13, 14, 19, 27, 29, 30, 32, 35, 38, 41, 42, 43, 51, 53, 58, 69, 75, 76, 77, 78, 79, 87, 94, 101, 102, 117, 119, 121, 122, 136, 138, 141, 146, 147, 148, 156, 158, 163, 174, 180, 181, 182, 183, 184, 192, 206, 207, 208, 209, 221, 222, 223, 224, 225, 226, 229, 230, 232, 233, 234, 235, 239, 240, 241, 242, 243, 245, 246, 247, 248, 253, 254, 255, 256, 258, 260, 262, 263, 265, 266, 267, 279, 280, 281, 286, 288, 299, 303, 306, 307, 313, 315, 316, 319, 322, 323, 325, 326, 328, 329, 335, 337, 339, 341, 344, 345, 349, 353, 354, 355, 357, 418], "integr": [12, 30, 35, 222, 231, 245, 260, 302, 314, 315, 316, 323, 325, 326, 334, 337, 418], "scheme": [12, 334, 335, 337], "converg": [12, 30, 222, 224, 225, 226, 232, 233, 239, 254, 332, 333, 334, 335, 337, 341], "toler": [12, 30, 332, 333, 337, 344, 347, 406], "size": [12, 30, 41, 42, 43, 44, 45, 46, 47, 48, 49, 50, 51, 53, 54, 55, 57, 58, 59, 62, 64, 66, 67, 68, 69, 70, 73, 75, 76, 77, 78, 79, 81, 82, 83, 84, 85, 87, 89, 90, 91, 94, 97, 101, 102, 104, 105, 106, 107, 108, 109, 110, 111, 112, 113, 114, 115, 116, 117, 118, 119, 121, 122, 123, 124, 125, 126, 127, 128, 129, 130, 131, 132, 133, 134, 135, 136, 137, 138, 141, 142, 143, 146, 147, 148, 149, 150, 151, 152, 153, 154, 155, 156, 158, 159, 160, 162, 163, 164, 167, 169, 171, 172, 173, 174, 175, 178, 180, 181, 182, 183, 184, 186, 187, 188, 189, 190, 192, 194, 195, 196, 202, 206, 207, 208, 209, 211, 212, 213, 239, 240, 252, 254, 267, 293, 301, 302, 333, 341, 344, 345, 346, 347, 348, 349, 357, 374, 414], "etc": [12, 13, 14, 16, 94, 230, 231, 238, 239, 242, 244, 254, 259, 302, 341, 352], "numer": [12, 14, 30, 108, 127, 228, 231, 232, 233, 239, 246, 253, 266, 289, 326, 331, 337, 341, 344, 346, 349, 357, 418], "after": [12, 20, 24, 28, 30, 35, 38, 106, 117, 125, 136, 232, 234, 235, 239, 240, 243, 254, 258, 263, 265, 267, 289, 292, 293, 300, 301, 302, 306, 308, 309, 317, 319, 328, 343, 345, 347, 348, 350, 352, 353, 354, 357, 358, 359, 361], "complet": [12, 13, 16, 18, 20, 23, 26, 28, 30, 58, 101, 102, 115, 134, 163, 231, 234, 243, 245, 258, 280, 281, 283, 285, 286, 292, 296, 298, 300, 301, 302, 308, 309, 316, 328, 343, 344, 345, 347, 349, 356, 361], "procedur": [12, 13, 33, 220, 231, 239, 254, 293, 298, 300, 301, 308, 309, 334, 341, 347, 357], "scientif": [13, 14, 220, 223, 224, 225, 226, 229, 231, 284, 331, 361], "system": [13, 14, 15, 16, 23, 26, 30, 33, 34, 35, 36, 39, 68, 86, 92, 104, 105, 106, 107, 108, 109, 110, 111, 112, 113, 114, 115, 116, 117, 118, 119, 121, 122, 123, 124, 125, 126, 127, 128, 129, 130, 131, 132, 133, 134, 135, 136, 137, 138, 173, 191, 197, 206, 207, 208, 209, 220, 222, 223, 224, 225, 226, 229, 231, 233, 234, 239, 246, 254, 280, 284, 287, 294, 305, 306, 307, 308, 309, 310, 311, 322, 324, 329, 334, 336, 337, 341, 346, 355, 406, 416, 418], "sequenc": [13, 14, 16, 17, 26, 220, 245, 260, 283, 292, 335, 343, 345], "task": [13, 26, 220, 231, 239, 241, 243, 254, 258, 307, 320, 330, 347], "special": [13, 29, 42, 52, 69, 75, 76, 77, 78, 79, 81, 82, 83, 84, 85, 87, 89, 90, 91, 100, 147, 157, 174, 180, 181, 182, 183, 184, 186, 187, 188, 189, 190, 192, 194, 195, 196, 205, 221, 222, 248, 262, 280, 293, 303, 339, 352, 357], "natur": [13, 14, 16, 21, 39, 114, 133, 217, 222, 231, 233, 234, 238, 246, 253, 266, 288, 289, 300, 302, 314, 316, 341, 343, 345, 346, 351], "hazard": [13, 15, 16, 19, 21, 25, 27, 32, 33, 216, 217, 222, 224, 228, 231, 238, 239, 240, 241, 242, 244, 245, 247, 249, 254, 255, 257, 258, 259, 260, 262, 267, 273, 280, 283, 285, 289, 295, 301, 303, 313, 314, 316, 320, 321, 322, 323, 325, 341, 354, 355, 358], "nhe": [13, 14, 16], "problem": [13, 24, 29, 38, 220, 231, 235, 292, 294, 296, 297, 302, 303, 306, 308, 309, 319, 328, 332, 333, 335, 337, 340, 347, 349, 350, 357], "In": [13, 14, 16, 18, 24, 25, 26, 29, 30, 32, 33, 34, 35, 36, 38, 83, 94, 101, 102, 105, 106, 112, 115, 117, 124, 125, 131, 134, 136, 188, 231, 232, 233, 234, 235, 238, 239, 240, 241, 242, 246, 247, 248, 249, 254, 255, 256, 263, 265, 267, 281, 286, 289, 292, 293, 294, 295, 296, 297, 298, 299, 300, 301, 302, 306, 307, 308, 309, 313, 318, 330, 333, 334, 335, 336, 337, 338, 341, 343, 344, 345, 346, 348, 349, 354, 356, 357, 358], "contrast": [13, 235, 254, 267, 281, 285, 286], "more": [13, 16, 19, 22, 23, 24, 30, 32, 33, 35, 70, 104, 105, 106, 108, 109, 111, 112, 113, 115, 116, 117, 118, 123, 124, 125, 127, 128, 130, 131, 132, 134, 135, 136, 137, 141, 175, 222, 224, 225, 226, 230, 231, 233, 234, 235, 238, 239, 240, 241, 242, 243, 245, 246, 247, 248, 249, 251, 253, 254, 255, 256, 257, 258, 260, 262, 263, 264, 266, 267, 279, 280, 281, 283, 284, 286, 293, 297, 300, 302, 306, 313, 316, 319, 328, 330, 332, 333, 334, 335, 336, 343, 344, 345, 346, 347, 348, 349, 354, 356, 357, 358, 360, 361, 406], "purpos": [13, 29, 33, 39, 221, 223, 226, 229, 233, 239, 240, 255, 262, 281, 294, 296, 301, 302, 312, 315, 318, 321, 325, 347, 357, 359], "taverna": 13, "kepler": 13, "pegasu": 13, "featur": [13, 29, 35, 118, 137, 223, 226, 229, 239, 240, 241, 242, 244, 247, 253, 255, 256, 257, 258, 259, 262, 263, 266, 267, 281, 289, 290, 296, 302, 306, 311, 312, 313, 315, 316, 317, 318, 320, 321, 322, 323, 324, 325, 326, 345, 347, 349, 355, 357, 418], "access": [13, 14, 16, 23, 71, 97, 121, 176, 202, 207, 222, 238, 245, 248, 254, 255, 258, 262, 263, 265, 267, 285, 286, 308, 312, 315, 316, 321, 330, 331, 350], "high": [13, 14, 16, 22, 44, 46, 50, 53, 66, 75, 76, 77, 78, 79, 83, 87, 92, 94, 104, 105, 106, 107, 108, 109, 110, 111, 112, 113, 114, 115, 116, 118, 119, 121, 123, 124, 125, 126, 127, 128, 129, 130, 131, 132, 133, 134, 135, 137, 138, 149, 151, 155, 158, 171, 180, 181, 182, 183, 184, 188, 192, 197, 206, 207, 208, 209, 222, 223, 228, 229, 232, 238, 239, 245, 246, 248, 260, 263, 267, 281, 283, 285, 286, 299, 317, 319, 321, 322, 324, 325, 326, 334, 337, 341, 343, 345, 347, 348, 418], "resourc": [13, 14, 16, 22, 28, 222, 223, 224, 225, 226, 229, 232, 243, 246, 248, 249, 258, 267, 279, 285, 299, 347], "avail": [13, 14, 16, 22, 25, 26, 27, 33, 35, 38, 41, 42, 43, 44, 45, 46, 47, 48, 49, 50, 51, 52, 53, 54, 55, 56, 57, 58, 59, 60, 61, 62, 63, 64, 65, 66, 67, 68, 69, 70, 71, 72, 73, 74, 75, 76, 77, 78, 79, 80, 81, 82, 83, 84, 85, 86, 87, 88, 89, 90, 91, 92, 93, 94, 95, 96, 97, 98, 99, 101, 102, 103, 104, 105, 106, 107, 108, 109, 110, 111, 112, 113, 114, 115, 116, 117, 118, 119, 120, 121, 122, 123, 124, 125, 126, 127, 128, 129, 130, 131, 132, 133, 134, 135, 136, 137, 138, 139, 141, 142, 143, 145, 146, 147, 148, 149, 150, 151, 152, 153, 154, 155, 156, 157, 158, 159, 160, 161, 162, 163, 164, 165, 166, 167, 168, 169, 170, 171, 172, 173, 174, 175, 176, 177, 178, 179, 180, 181, 182, 183, 184, 185, 186, 187, 188, 189, 190, 191, 192, 193, 194, 195, 196, 197, 198, 199, 200, 201, 202, 203, 204, 206, 207, 208, 209, 211, 212, 213, 215, 222, 223, 224, 225, 226, 228, 229, 230, 231, 235, 237, 238, 240, 241, 243, 245, 246, 247, 253, 254, 255, 256, 261, 262, 266, 279, 281, 289, 294, 295, 298, 303, 306, 307, 309, 311, 314, 316, 317, 320, 321, 324, 328, 332, 333, 334, 335, 337, 341, 344, 345, 347, 349, 350, 351, 354, 355, 356, 357, 358, 359, 361, 418], "cloud": [13, 14, 16, 23, 217, 308], "enabl": [13, 217, 222, 228, 239, 240, 245, 247, 248, 255, 260, 262, 263, 296, 306, 313, 315, 316, 321, 324, 344, 345, 347, 354, 355, 358], "parallel": [13, 28, 35, 117, 136, 239, 243, 254, 258, 287, 296, 300, 319, 333, 336, 347, 350, 406], "non": [13, 44, 58, 64, 68, 70, 82, 108, 127, 140, 143, 149, 163, 169, 173, 175, 187, 210, 222, 223, 224, 225, 226, 228, 229, 231, 233, 239, 240, 241, 242, 256, 280, 281, 287, 288, 296, 299, 308, 316, 328, 332, 337, 340, 341, 344, 346, 347, 357, 418], "trivial": [13, 231, 336, 346], "larg": [13, 76, 78, 79, 82, 104, 105, 106, 107, 108, 109, 110, 111, 112, 113, 114, 115, 116, 117, 118, 119, 121, 123, 127, 131, 136, 138, 181, 183, 184, 187, 206, 207, 231, 235, 238, 239, 240, 243, 254, 258, 263, 280, 281, 285, 286, 292, 293, 297, 299, 300, 302, 316, 326, 332, 334, 348, 350, 357, 361], "scale": [13, 14, 19, 22, 30, 32, 33, 38, 217, 222, 223, 224, 225, 226, 229, 231, 232, 234, 238, 239, 243, 245, 254, 260, 280, 285, 292, 293, 298, 300, 301, 302, 303, 311, 313, 321, 325, 326, 331, 340, 347, 349, 352, 353, 355, 357, 358, 415], "capabl": [13, 223, 226, 229, 244, 245, 247, 259, 260, 262, 283, 285, 289, 290, 313, 316, 322, 326, 332, 340, 345, 347, 418], "allow": [13, 14, 16, 17, 19, 29, 33, 75, 76, 77, 78, 79, 87, 180, 181, 182, 183, 184, 192, 220, 222, 223, 224, 225, 226, 228, 229, 240, 242, 255, 257, 281, 293, 297, 299, 300, 306, 307, 309, 313, 316, 319, 323, 330, 333, 334, 335, 337, 339, 340, 341, 344, 347, 348, 349, 352, 353, 354, 356, 357, 358, 359, 361, 416], "introduc": [13, 38, 220, 231, 234, 239, 240, 242, 246, 247, 249, 251, 253, 254, 255, 257, 262, 263, 264, 265, 266, 281, 285, 288, 297, 298, 306, 334, 345, 346, 347, 357, 360, 406], "propag": [13, 15, 28, 33, 35, 38, 220, 231, 232, 234, 253, 266, 281, 287, 288, 292, 293, 294, 295, 296, 299, 302, 311, 313, 314, 316, 317, 319, 321, 324, 328, 334, 336, 342, 346, 349, 350, 354, 355, 358], "streamlin": 13, "interfac": [13, 14, 16, 23, 29, 34, 36, 220, 222, 224, 225, 226, 230, 231, 295, 306, 307, 308, 309, 313, 316, 319, 323, 326, 328, 330, 357, 362, 418], "between": [13, 14, 16, 17, 20, 27, 33, 45, 46, 51, 53, 101, 102, 109, 117, 128, 136, 150, 151, 156, 158, 222, 224, 225, 226, 228, 231, 232, 233, 234, 235, 239, 240, 241, 246, 247, 248, 254, 255, 256, 263, 267, 281, 292, 293, 294, 295, 297, 299, 300, 301, 302, 306, 309, 316, 321, 332, 333, 335, 336, 341, 343, 344, 345, 346, 347, 349, 354, 357, 358], "exist": [13, 14, 16, 33, 35, 38, 58, 163, 222, 223, 224, 225, 226, 228, 229, 231, 239, 246, 248, 262, 263, 285, 286, 300, 311, 317, 319, 323, 324, 326, 328, 341, 347, 352, 353, 357, 406], "dataset": [13, 14, 16, 33, 100, 140, 144, 205, 210, 214, 222, 223, 224, 225, 226, 229, 231, 232, 240, 245, 246, 254, 255, 260, 263, 267, 283, 297, 298, 311, 317, 319, 321, 324, 326, 335, 344, 346, 347, 348, 406], "wide": [13, 29, 45, 69, 150, 174, 231, 235, 281, 300, 336, 346], "openfoam": [13, 16, 222, 304, 326], "adcirc": [13, 246, 247], "peer": [13, 14, 222, 224, 225, 226, 290, 292, 294, 295, 297, 298, 299, 300, 301, 311, 313, 316, 320, 322, 323, 351, 352, 355, 358, 418], "strong": [13, 33, 44, 112, 131, 149, 246, 250, 263, 348, 418], "ground": [13, 19, 20, 27, 30, 33, 38, 40, 94, 101, 102, 104, 105, 106, 107, 108, 109, 110, 111, 112, 113, 114, 115, 116, 117, 118, 119, 142, 143, 206, 216, 222, 224, 225, 226, 230, 231, 234, 236, 239, 245, 246, 247, 249, 254, 255, 262, 263, 267, 281, 284, 286, 287, 288, 290, 292, 293, 297, 299, 302, 303, 311, 312, 313, 315, 316, 320, 321, 322, 323, 324, 326, 341, 344, 347, 351, 353, 355, 357, 358, 406, 418], "motion": [13, 19, 27, 30, 33, 38, 40, 94, 216, 222, 224, 225, 226, 230, 231, 234, 236, 281, 284, 286, 287, 288, 290, 292, 293, 297, 299, 302, 303, 312, 313, 315, 316, 320, 321, 322, 323, 324, 344, 347, 351, 353, 355, 357, 358, 406, 418], "databas": [13, 14, 16, 33, 145, 215, 223, 224, 225, 226, 229, 230, 239, 242, 246, 253, 257, 266, 279, 281, 290, 294, 295, 297, 300, 301, 311, 316, 320, 322, 323, 324, 325, 326, 341, 351, 354, 355], "To": [13, 14, 16, 17, 19, 21, 23, 24, 28, 34, 35, 36, 38, 231, 232, 233, 234, 239, 240, 246, 252, 254, 267, 281, 286, 291, 292, 293, 296, 299, 300, 301, 302, 306, 307, 308, 309, 320, 328, 340, 345, 346, 347, 348, 349, 352, 353, 357, 418], "do": [13, 14, 23, 33, 34, 35, 36, 54, 55, 58, 64, 81, 82, 83, 84, 85, 89, 90, 91, 94, 101, 102, 159, 160, 163, 169, 186, 187, 188, 189, 190, 194, 195, 196, 218, 219, 231, 232, 234, 235, 240, 254, 262, 285, 292, 296, 300, 306, 309, 321, 328, 330, 334, 337, 341, 346, 347, 349, 352, 354, 356, 359], "develop": [13, 14, 16, 21, 24, 29, 33, 38, 44, 101, 102, 104, 105, 106, 107, 108, 109, 110, 111, 112, 113, 114, 115, 116, 117, 118, 119, 131, 149, 206, 219, 220, 222, 223, 224, 225, 226, 228, 229, 230, 231, 234, 235, 237, 238, 239, 240, 242, 244, 245, 246, 247, 248, 249, 253, 254, 255, 259, 260, 261, 262, 263, 266, 267, 279, 280, 283, 286, 287, 297, 302, 303, 306, 307, 309, 312, 314, 315, 316, 318, 321, 325, 328, 342, 347, 350, 357], "pre": [13, 14, 16, 26, 28, 33, 43, 58, 104, 105, 106, 107, 108, 109, 110, 111, 112, 113, 114, 115, 116, 117, 118, 119, 121, 123, 124, 125, 126, 127, 128, 129, 130, 131, 132, 133, 134, 135, 136, 137, 138, 148, 163, 239, 253, 254, 256, 260, 265, 266, 267, 300, 301, 302, 303, 306, 323, 337, 344, 354, 357, 359, 406], "post": [13, 14, 16, 20, 24, 43, 47, 69, 104, 105, 106, 107, 108, 109, 110, 111, 112, 113, 114, 115, 116, 117, 118, 119, 121, 123, 124, 125, 126, 127, 128, 129, 130, 131, 132, 133, 134, 135, 136, 137, 138, 148, 152, 174, 231, 239, 240, 243, 244, 254, 258, 259, 263, 265, 267, 281, 282, 285, 291, 316, 323, 328, 333, 337, 346, 359, 418], "processor": [13, 14, 16, 239, 243, 254, 258, 284, 302, 337, 350], "util": [13, 14, 16, 22, 104, 105, 106, 107, 108, 109, 110, 111, 112, 113, 114, 115, 116, 117, 118, 119, 206, 222, 223, 224, 225, 226, 229, 232, 238, 239, 254, 267, 289, 299, 302, 314, 323, 325, 335, 349, 350, 353, 406], "technolog": [13, 206, 207, 208, 209, 239, 240, 246, 254, 261, 262, 285], "servic": [13, 14, 16, 29, 35, 92, 100, 197, 205, 206, 207, 208, 209, 221, 222, 224, 225, 226, 238, 239, 240, 254, 255, 266, 267, 324, 354, 361], "addit": [13, 16, 19, 27, 29, 33, 34, 35, 36, 42, 147, 223, 226, 229, 230, 231, 233, 238, 241, 246, 247, 249, 254, 256, 258, 262, 279, 280, 281, 286, 288, 289, 290, 292, 300, 301, 302, 306, 307, 309, 314, 315, 316, 318, 320, 323, 325, 330, 334, 335, 337, 344, 347, 357, 359, 360, 406, 418], "custom": [13, 19, 25, 27, 30, 32, 35, 222, 228, 231, 240, 246, 302, 316, 317, 323, 325], "produc": [13, 18, 20, 22, 23, 26, 28, 30, 32, 38, 39, 220, 231, 240, 261, 331, 334, 335, 344, 345, 346, 349, 354, 357], "among": [13, 26, 231, 235, 253, 263, 266, 293, 302, 335, 348, 349, 357], "autom": [13, 14, 220, 238, 239, 245, 247, 249, 254, 260, 283, 295, 303, 311, 326, 341, 355, 418], "acquisit": 13, "inventori": [13, 19, 222, 234, 240, 241, 243, 245, 246, 247, 249, 255, 256, 258, 260, 261, 262, 279, 281, 283, 321, 323], "brail": [13, 239, 254, 260, 263, 323], "pass": [13, 14, 16, 26, 28, 29, 220, 231, 306, 309, 314, 319, 330, 359], "regionalev": [13, 26], "modular": [13, 94, 356], "framework": [13, 14, 16, 217, 220, 222, 228, 231, 234, 248, 255, 263, 280, 314, 316, 323, 324, 331, 336, 347], "incorpor": [13, 33, 222, 223, 229, 242, 245, 246, 254, 260, 261, 262, 283, 291, 293, 303, 323, 324, 357], "own": [13, 14, 24, 222, 223, 224, 225, 226, 229, 234, 247, 249, 262, 314, 319, 330, 337, 341, 352, 353, 357, 359], "compon": [13, 15, 17, 20, 25, 28, 30, 32, 33, 35, 54, 55, 58, 59, 64, 81, 82, 83, 84, 85, 89, 90, 91, 94, 100, 101, 102, 104, 105, 106, 107, 108, 109, 110, 111, 112, 113, 114, 115, 116, 117, 118, 119, 121, 122, 123, 124, 125, 126, 127, 128, 129, 130, 131, 132, 133, 134, 135, 136, 137, 138, 159, 160, 163, 164, 169, 186, 187, 188, 189, 190, 194, 195, 196, 205, 206, 207, 208, 209, 220, 222, 228, 231, 233, 240, 242, 245, 253, 255, 257, 260, 266, 281, 283, 284, 286, 288, 293, 294, 295, 296, 300, 301, 302, 314, 315, 316, 317, 321, 344, 347, 357, 374, 406, 418], "so": [13, 14, 32, 35, 112, 131, 223, 224, 225, 226, 229, 231, 232, 233, 234, 235, 240, 242, 243, 246, 253, 255, 258, 262, 266, 267, 288, 292, 293, 296, 306, 307, 309, 334, 341, 344, 346, 349, 353, 356, 358], "long": [13, 19, 23, 46, 51, 53, 70, 87, 104, 105, 106, 107, 108, 109, 110, 111, 112, 113, 114, 115, 116, 117, 118, 119, 151, 156, 158, 175, 192, 206, 219, 238, 239, 240, 258, 262, 331, 418], "meet": [13, 14, 16, 44, 68, 149, 173, 220, 240, 249], "detail": [13, 19, 22, 23, 24, 26, 33, 42, 44, 54, 55, 104, 109, 123, 128, 147, 149, 159, 160, 222, 224, 225, 226, 230, 232, 234, 238, 243, 247, 249, 251, 253, 258, 262, 263, 264, 266, 279, 280, 281, 283, 288, 300, 301, 302, 316, 330, 333, 336, 341, 343, 345, 346, 347, 348, 357, 361], "schema": [13, 19, 20, 240, 255], "c4": [13, 14, 17], "dl": [13, 15, 16, 19, 20, 23, 26, 27, 28, 30, 32, 216, 243, 258, 295, 316, 323], "infrastructur": [13, 14, 222, 234, 262, 263, 279, 284, 289, 320, 321, 323], "given": [13, 14, 16, 19, 33, 222, 230, 231, 232, 233, 234, 235, 239, 240, 245, 246, 247, 249, 253, 254, 255, 260, 262, 263, 265, 266, 267, 288, 289, 290, 292, 294, 297, 298, 301, 311, 313, 324, 331, 333, 334, 337, 338, 341, 343, 344, 345, 347, 349, 351, 352, 353, 354, 355, 357, 418], "lifelin": [13, 104, 105, 106, 107, 108, 109, 110, 111, 112, 113, 114, 115, 116, 117, 118, 119, 140, 210, 222, 228, 234, 321], "level": [13, 20, 25, 30, 38, 97, 104, 105, 106, 107, 108, 109, 110, 111, 112, 113, 114, 115, 116, 117, 118, 119, 121, 123, 124, 125, 126, 127, 128, 129, 130, 131, 132, 133, 134, 135, 136, 137, 138, 202, 222, 230, 231, 233, 234, 239, 240, 241, 242, 245, 248, 253, 254, 256, 257, 260, 261, 263, 266, 267, 279, 280, 281, 283, 285, 286, 292, 302, 306, 315, 334, 335, 357, 416], "learn": [13, 222, 223, 224, 225, 226, 229, 231, 239, 254, 263, 300, 303, 311, 314, 317, 319, 324, 328, 342, 347, 350, 354, 356], "consequ": [13, 14, 35, 54, 55, 68, 75, 76, 77, 78, 79, 94, 146, 147, 148, 149, 150, 151, 152, 153, 154, 155, 156, 158, 159, 160, 162, 163, 164, 167, 169, 171, 172, 173, 174, 175, 178, 180, 181, 182, 183, 184, 186, 187, 188, 189, 190, 192, 194, 195, 196, 202, 206, 207, 208, 209, 211, 212, 213, 222, 228, 232, 285, 306, 309, 314, 316, 323, 332, 334, 340, 346], "experiment": [13, 14, 228, 232, 318, 325, 331, 336, 346], "futur": [13, 222, 223, 224, 225, 226, 227, 228, 229, 247, 248, 263, 266, 267, 273, 285, 286, 301, 316, 318, 344, 347, 357, 358, 418], "base": [13, 14, 16, 27, 30, 32, 33, 34, 36, 38, 39, 41, 47, 51, 53, 59, 62, 64, 66, 68, 75, 76, 77, 78, 79, 81, 83, 84, 87, 89, 90, 91, 94, 97, 100, 101, 102, 104, 105, 106, 107, 108, 109, 110, 111, 112, 113, 114, 115, 116, 117, 118, 119, 121, 122, 140, 144, 146, 152, 156, 158, 164, 167, 169, 171, 173, 180, 181, 182, 183, 184, 186, 188, 189, 192, 194, 195, 196, 202, 205, 206, 207, 208, 210, 214, 218, 219, 222, 223, 224, 225, 226, 228, 229, 230, 232, 234, 235, 239, 240, 241, 242, 246, 248, 251, 253, 254, 255, 256, 263, 265, 266, 267, 279, 280, 281, 284, 286, 287, 292, 293, 295, 296, 301, 302, 303, 309, 311, 312, 313, 315, 316, 317, 319, 321, 323, 324, 326, 330, 331, 332, 333, 334, 335, 336, 337, 341, 344, 345, 346, 347, 348, 354, 355, 357, 358, 418], "ai": [13, 222], "within": [13, 28, 30, 33, 39, 54, 55, 58, 94, 159, 160, 163, 231, 232, 239, 240, 241, 242, 245, 248, 255, 256, 257, 260, 281, 283, 293, 299, 300, 301, 319, 328, 332, 333, 337, 341, 343, 345, 348, 349, 353, 357], "sever": [13, 14, 16, 20, 32, 33, 101, 102, 230, 235, 239, 240, 255, 267, 280, 281, 289, 293, 300, 301, 302, 309, 323, 326, 333, 349, 357], "open": [13, 14, 16, 23, 34, 35, 36, 38, 51, 53, 69, 108, 119, 127, 138, 156, 158, 174, 222, 223, 224, 225, 226, 229, 233, 238, 239, 240, 242, 246, 248, 250, 254, 255, 261, 263, 267, 280, 281, 287, 289, 290, 292, 296, 306, 307, 308, 309, 311, 316, 324, 328, 344, 352, 353, 355, 361, 418], "nga": [13, 14, 39, 235, 290, 294, 295, 297, 298, 300, 301, 311, 313, 316, 320, 322, 323, 351, 355, 358], "current": [13, 14, 16, 27, 30, 35, 42, 147, 231, 233, 234, 235, 240, 242, 244, 245, 249, 254, 255, 257, 259, 260, 283, 293, 300, 301, 302, 306, 307, 311, 316, 317, 319, 320, 324, 330, 331, 332, 335, 337, 340, 341, 342, 344, 345, 347, 348, 349, 350, 356, 357, 358], "avoid": [13, 29, 232, 242, 254, 291, 326, 354], "duplic": [13, 291, 292], "mani": [13, 16, 33, 35, 222, 233, 234, 235, 239, 240, 254, 255, 263, 267, 280, 285, 289, 290, 292, 306, 309, 323, 341, 350, 354, 358, 359, 406], "aim": [13, 16, 19, 231, 334, 335], "facilit": [13, 16, 33, 231, 232, 263, 281, 285, 299, 309, 315, 316, 335], "reus": [13, 16, 300, 301], "common": [13, 14, 16, 117, 136, 231, 233, 239, 240, 241, 254, 255, 256, 263, 306, 320, 328, 347, 357], "encount": [13, 16, 239, 241], "broad": [13, 16], "skill": [13, 16, 247], "chapter": [13, 14, 16, 23, 40, 53, 158, 310, 347], "present": [13, 14, 16, 17, 29, 33, 35, 116, 135, 223, 226, 229, 231, 233, 235, 238, 239, 246, 248, 254, 263, 267, 286, 292, 293, 296, 302, 311, 317, 324, 328, 332, 333, 337, 341, 346, 347, 348, 349, 351, 360, 361], "encourag": [13, 16, 24, 255, 262, 289, 290, 312, 315, 318, 321, 322, 335, 341, 354, 357, 361, 418], "adopt": [13, 16, 232, 235, 239, 240, 246, 247, 248, 249, 251, 255, 260, 262, 263, 267, 286, 293, 294], "graphic": [13, 14, 16, 222, 223, 224, 225, 226, 229, 292, 296, 341, 360, 362], "approach": [13, 16, 29, 222, 231, 232, 233, 239, 240, 242, 243, 245, 246, 248, 251, 254, 255, 258, 260, 262, 263, 286, 287, 300, 302, 334, 335, 345, 347, 357], "diagram": [13, 28, 357], "describ": [13, 16, 19, 20, 33, 51, 53, 156, 158, 230, 232, 235, 237, 238, 239, 240, 242, 245, 246, 248, 253, 254, 255, 257, 260, 263, 266, 283, 286, 288, 293, 301, 314, 330, 337, 340, 341, 344, 356, 357, 361], "variou": [13, 222, 223, 224, 225, 226, 228, 229, 231, 235, 239, 240, 247, 248, 249, 254, 255, 262, 263, 267, 281, 286, 292, 293, 303, 340, 344, 350, 354, 357], "abstract": [13, 16, 29, 220, 222, 330], "top": [13, 16, 30, 33, 39, 51, 53, 109, 111, 128, 130, 156, 158, 222, 239, 240, 241, 242, 243, 254, 256, 292, 294, 295, 296, 297, 302, 306, 341, 344, 345, 352, 353, 354, 357, 358, 361], "down": [13, 14, 16, 26, 29, 51, 53, 156, 158, 224, 226, 238, 246, 262, 280, 281, 292, 293, 296, 306, 307, 332, 334, 335, 337, 340, 341, 350, 351, 354, 356, 359, 361], "start": [13, 14, 16, 19, 20, 26, 28, 29, 35, 38, 222, 223, 224, 225, 226, 227, 228, 229, 232, 238, 240, 247, 260, 262, 291, 293, 295, 297, 302, 306, 307, 308, 309, 326, 328, 329, 331, 332, 333, 344, 347, 352, 358, 359, 361, 406], "show": [13, 14, 16, 33, 35, 38, 39, 222, 223, 229, 230, 231, 232, 234, 235, 238, 239, 246, 252, 254, 258, 261, 263, 265, 267, 281, 284, 287, 292, 293, 294, 295, 296, 298, 299, 300, 301, 302, 303, 309, 319, 328, 331, 334, 335, 336, 340, 341, 347, 348, 349, 352, 354, 357, 358, 360, 361], "how": [13, 14, 16, 21, 22, 23, 26, 27, 31, 231, 239, 240, 245, 247, 248, 249, 254, 255, 260, 262, 291, 292, 293, 294, 300, 301, 302, 303, 304, 328, 337, 347, 354, 358, 374, 406, 418], "would": [13, 16, 23, 35, 115, 134, 223, 226, 229, 230, 231, 234, 235, 238, 239, 242, 243, 244, 245, 246, 253, 255, 257, 258, 259, 260, 265, 266, 267, 282, 283, 285, 289, 290, 291, 292, 293, 296, 297, 301, 344, 359, 418], "interact": [13, 14, 16, 17, 231, 246, 262, 300, 301, 302, 317, 336, 346, 348, 354], "drill": [13, 16, 142], "three": [13, 16, 19, 24, 30, 33, 51, 53, 97, 156, 158, 202, 231, 234, 235, 240, 246, 252, 253, 254, 255, 266, 267, 284, 285, 286, 292, 295, 296, 300, 302, 303, 306, 307, 332, 334, 341, 347, 354, 357], "typic": [13, 16, 20, 109, 112, 114, 118, 119, 121, 122, 128, 131, 133, 137, 138, 207, 208, 220, 231, 233, 234, 235, 239, 240, 254, 255, 280, 292, 293, 297, 300, 306, 307, 309, 328, 331, 332, 333, 347, 349, 351, 352, 357], "uml": [13, 16, 17], "wa": [13, 14, 16, 23, 33, 35, 36, 38, 39, 47, 64, 152, 169, 234, 235, 238, 239, 240, 245, 246, 247, 249, 254, 255, 261, 262, 263, 267, 279, 280, 281, 284, 285, 299, 301, 302, 306, 307, 309, 311, 314, 317, 319, 320, 324, 328, 337, 341, 357, 360, 418], "divers": [13, 16, 262, 263, 354], "knowledg": [13, 16, 222], "understand": [13, 14, 16, 17, 26, 231, 234, 240, 247, 249, 252, 262, 263, 267, 292, 293, 296, 328, 335, 336, 345, 346], "behind": [13, 16, 232, 233, 337], "fit": [13, 14, 16, 29, 46, 64, 151, 169, 221, 222, 228, 231, 234, 235, 239, 242, 253, 254, 257, 266, 300, 317, 332, 333, 335, 345], "four": [13, 16, 19, 20, 32, 39, 141, 231, 234, 239, 240, 243, 252, 255, 258, 267, 280, 284, 292, 294, 295, 297, 299, 333, 335, 339, 340, 341, 361], "real": [13, 230, 232, 239, 246, 254, 267, 279, 293, 308, 318, 330, 349, 357], "world": [13, 14, 16, 232, 239, 254, 280, 293, 318], "term": [13, 23, 104, 105, 106, 107, 108, 109, 110, 111, 112, 113, 114, 115, 116, 117, 118, 119, 206, 220, 231, 232, 233, 239, 240, 253, 254, 255, 262, 266, 288, 301, 334, 337, 346, 347, 349, 357, 406], "peopl": [13, 285, 286], "who": [13, 29, 245, 247, 249, 262, 283, 285, 337, 338, 341, 347, 354, 418], "other": [13, 14, 16, 19, 23, 29, 32, 33, 43, 54, 55, 73, 92, 94, 104, 105, 106, 107, 108, 109, 110, 111, 112, 113, 114, 115, 116, 117, 118, 119, 121, 123, 124, 125, 126, 127, 128, 129, 130, 131, 132, 133, 134, 135, 136, 137, 138, 141, 148, 159, 160, 178, 197, 206, 221, 222, 223, 224, 225, 226, 228, 229, 230, 231, 233, 234, 239, 240, 242, 243, 245, 246, 247, 248, 250, 252, 254, 255, 260, 262, 263, 267, 279, 280, 281, 283, 289, 293, 294, 295, 296, 298, 300, 301, 302, 306, 307, 308, 309, 323, 330, 334, 335, 336, 337, 338, 341, 345, 346, 347, 348, 352, 353, 355, 357], "up": [13, 14, 15, 16, 23, 26, 28, 35, 38, 41, 42, 43, 44, 45, 46, 47, 48, 49, 64, 73, 81, 82, 84, 85, 89, 90, 91, 101, 102, 104, 105, 106, 107, 109, 110, 111, 112, 113, 114, 115, 116, 117, 118, 119, 120, 121, 122, 123, 124, 125, 126, 128, 129, 130, 131, 132, 133, 134, 135, 136, 137, 138, 139, 141, 142, 143, 151, 153, 154, 206, 207, 208, 209, 211, 212, 213, 220, 234, 238, 240, 242, 243, 246, 255, 257, 258, 263, 267, 285, 286, 292, 294, 295, 298, 302, 306, 307, 308, 309, 314, 316, 319, 326, 328, 352, 354, 357, 358, 361], "individu": [13, 14, 16, 22, 24, 26, 28, 35, 220, 222, 223, 229, 234, 235, 238, 239, 241, 243, 245, 247, 248, 249, 253, 254, 256, 258, 260, 262, 263, 265, 266, 281, 286, 292, 293, 296, 309, 328, 331, 332, 341, 349, 350, 354, 357], "implement": [13, 27, 33, 39, 40, 220, 222, 223, 224, 225, 226, 227, 228, 229, 231, 233, 234, 235, 237, 239, 240, 242, 246, 247, 249, 251, 253, 254, 255, 256, 257, 260, 262, 264, 265, 266, 267, 281, 285, 288, 302, 321, 322, 326, 330, 331, 337, 344, 346, 347, 356, 357, 406, 418], "thei": [13, 14, 16, 23, 33, 35, 104, 105, 106, 107, 108, 109, 110, 111, 112, 113, 114, 115, 116, 117, 118, 119, 121, 123, 124, 125, 126, 127, 128, 129, 130, 131, 132, 133, 134, 135, 136, 137, 138, 220, 222, 228, 230, 231, 233, 235, 239, 240, 241, 246, 255, 256, 281, 289, 290, 292, 296, 300, 306, 307, 309, 316, 318, 328, 334, 336, 337, 338, 341, 345, 347, 348, 349, 352, 353, 356, 406, 418], "section": [13, 21, 26, 29, 35, 38, 83, 114, 133, 188, 223, 224, 226, 229, 231, 234, 235, 238, 239, 240, 243, 246, 253, 254, 255, 258, 260, 265, 266, 267, 281, 288, 292, 294, 295, 297, 306, 307, 309, 323, 334, 337, 341, 347, 361], "definit": [13, 19, 33, 220, 222, 230, 231, 235, 240, 255, 316, 320, 322, 349, 357], "busi": [13, 29, 220, 221, 222, 228, 238, 240, 248, 321], "whole": [13, 220, 239, 240, 334, 335, 347], "part": [13, 35, 70, 100, 175, 205, 220, 222, 228, 231, 234, 239, 241, 246, 250, 255, 256, 296, 334, 335, 341, 348, 352, 353, 357], "dure": [13, 16, 19, 24, 33, 104, 123, 220, 231, 232, 234, 239, 240, 246, 254, 263, 286, 299, 314, 326, 328, 331, 333, 348, 349, 418], "particip": [13, 220], "anoth": [13, 14, 16, 220, 231, 239, 254, 309, 313, 334, 335, 345, 347, 352], "action": [13, 220, 239, 240, 246, 248, 255, 281], "accord": [13, 18, 53, 118, 137, 158, 220, 239, 240, 241, 246, 254, 255, 256, 357], "rule": [13, 220, 232, 240, 242, 253, 255, 266, 357], "manag": [13, 14, 35, 220, 231, 242, 246, 248, 254, 255, 257, 263, 266, 280, 286, 316, 328, 350], "coalit": [13, 220], "oper": [13, 23, 35, 220, 223, 224, 225, 226, 229, 231, 232, 239, 263, 280, 305, 306, 308, 309, 310, 321, 329, 353], "resid": [13, 118, 137, 220, 238, 239, 241, 248, 254, 256, 286], "can": [13, 14, 16, 19, 23, 26, 27, 29, 30, 32, 33, 34, 35, 36, 38, 39, 101, 102, 104, 108, 112, 117, 123, 127, 131, 136, 220, 223, 224, 225, 226, 229, 230, 231, 232, 233, 234, 235, 238, 239, 240, 241, 242, 243, 245, 246, 247, 248, 249, 253, 254, 255, 256, 258, 260, 261, 262, 263, 265, 266, 267, 280, 281, 283, 286, 288, 289, 290, 292, 293, 294, 295, 296, 297, 298, 299, 300, 301, 302, 303, 306, 307, 308, 309, 310, 314, 317, 318, 324, 325, 328, 329, 330, 331, 332, 333, 334, 335, 336, 337, 338, 341, 343, 344, 345, 346, 347, 348, 349, 350, 352, 353, 354, 356, 357, 358, 359, 361, 374, 406, 418], "self": [13, 220, 330, 331], "group": [13, 16, 19, 20, 30, 32, 33, 121, 122, 206, 207, 208, 209, 220, 222, 224, 226, 228, 231, 238, 240, 242, 243, 246, 247, 252, 255, 262, 281, 296, 316, 317, 345, 347, 348], "loos": [13, 220], "coupl": [13, 77, 182, 220, 222, 223, 224, 225, 226, 228, 229, 242, 245, 246, 252, 257, 260, 281, 283, 345, 357], "coordin": [13, 19, 33, 220, 228, 239, 241, 254, 256, 263], "consum": [13, 220, 231, 335], "subsequ": [13, 14, 16, 58, 163, 220, 238, 258, 287, 293, 330, 357], "becaus": [13, 32, 33, 220, 230, 233, 235, 240, 242, 246, 255, 257, 267, 292, 301, 302, 306, 309, 334, 337, 346, 347, 359, 360], "scientist": [13, 220], "visual": [13, 34, 35, 36, 220, 223, 224, 225, 226, 229, 231, 239, 243, 246, 248, 254, 258, 263, 267, 280, 286, 297, 298, 299, 313, 319, 321, 322, 323, 326, 329, 344, 355, 357], "ever": [13, 29, 220], "increas": [13, 30, 220, 222, 228, 232, 233, 234, 235, 239, 242, 245, 248, 254, 260, 263, 265, 267, 281, 283, 286, 300, 302, 306, 319, 346, 347, 348, 406], "amount": [13, 101, 102, 220, 231, 239, 254, 347], "One": [13, 33, 83, 87, 188, 192, 222, 231, 239, 243, 258, 286, 297, 298, 300, 347], "aid": [13, 220, 326, 345], "schedul": [13, 14, 220], "monitor": [13, 14, 16, 94, 220, 243, 258, 326], "defin": [13, 14, 19, 24, 26, 27, 29, 30, 33, 35, 58, 73, 101, 102, 163, 178, 220, 222, 223, 224, 225, 226, 228, 229, 230, 231, 232, 235, 240, 241, 242, 246, 248, 254, 255, 256, 257, 261, 263, 279, 280, 286, 287, 290, 292, 293, 294, 295, 296, 297, 299, 303, 306, 309, 311, 313, 314, 316, 317, 320, 322, 323, 324, 330, 331, 332, 333, 334, 337, 340, 341, 343, 345, 346, 347, 348, 350, 352, 353, 354, 355, 357, 362, 374, 406, 414, 415], "collect": [13, 14, 20, 23, 26, 33, 40, 145, 215, 222, 232, 234, 238, 239, 240, 254, 263, 267, 279, 286, 316, 321, 339, 361], "domain": [13, 220, 231, 239, 284, 292, 325, 332, 333, 334, 335, 347, 354, 406], "exampl": [13, 14, 19, 20, 21, 22, 23, 24, 26, 29, 30, 32, 33, 35, 38, 39, 121, 122, 207, 208, 220, 222, 223, 224, 225, 226, 229, 230, 231, 234, 239, 240, 241, 242, 253, 254, 255, 256, 257, 258, 266, 280, 285, 287, 291, 292, 293, 294, 295, 296, 297, 298, 299, 300, 301, 302, 308, 309, 316, 318, 319, 321, 325, 326, 328, 330, 331, 332, 335, 341, 344, 345, 346, 347, 348, 349, 352, 353, 354, 355, 357, 358, 359, 418], "clear": [13, 231, 240, 242, 255, 265, 347], "extend": [13, 30, 51, 53, 156, 158, 220, 222, 228, 234, 239, 240, 245, 246, 247, 249, 255, 260, 262, 263, 281, 292, 306, 307, 309, 314, 316, 325, 337, 357, 418], "context": [13, 232, 247, 249, 262, 285, 374], "i": [13, 14, 16, 19, 23, 24, 32, 35, 38, 104, 105, 106, 107, 108, 109, 110, 111, 112, 113, 114, 115, 116, 117, 118, 119, 135, 206, 216, 222, 223, 224, 225, 226, 227, 228, 229, 231, 232, 233, 234, 235, 238, 240, 241, 242, 243, 246, 250, 251, 255, 256, 258, 260, 265, 267, 279, 281, 288, 291, 292, 293, 296, 297, 299, 300, 301, 302, 306, 309, 316, 320, 322, 331, 332, 334, 341, 345, 346, 347, 348, 349, 351, 352, 353, 354, 357, 418], "shown": [13, 14, 16, 26, 27, 28, 33, 35, 38, 39, 42, 147, 222, 231, 232, 238, 239, 243, 246, 252, 254, 258, 261, 265, 281, 291, 292, 293, 294, 296, 299, 300, 301, 302, 306, 308, 309, 329, 330, 332, 333, 334, 335, 336, 337, 339, 341, 345, 347, 349, 350, 352, 353, 354, 356, 357, 358, 359, 360, 361], "we": [13, 16, 17, 23, 33, 35, 40, 230, 231, 234, 238, 240, 254, 267, 281, 285, 289, 290, 292, 293, 294, 295, 296, 297, 298, 299, 300, 301, 302, 306, 307, 308, 309, 312, 315, 318, 321, 322, 325, 328, 334, 346, 347, 349, 350, 352, 353, 354, 359, 361], "hydrouq": 13, "pbe": [13, 16, 219, 300, 314, 316], "box": [13, 14, 38, 51, 53, 83, 97, 143, 156, 158, 188, 202, 238, 239, 254, 294, 295, 302, 307, 308, 309, 313, 320, 322, 330, 341, 345, 350, 354, 357], "center": [13, 14, 16, 33, 51, 53, 54, 90, 156, 158, 159, 195, 231, 232, 238, 239, 246, 254, 261, 263, 284, 289, 293, 300, 334, 354, 357, 418], "surround": [13, 14, 16, 116, 135, 240, 248, 285, 286, 325], "datadepot": [13, 14], "either": [13, 14, 16, 23, 29, 58, 70, 81, 82, 83, 84, 85, 89, 90, 91, 101, 102, 110, 129, 163, 175, 186, 187, 188, 189, 190, 194, 195, 196, 234, 246, 254, 267, 334, 335, 338, 340, 341, 345, 346, 347, 349, 354, 356, 357, 360, 361, 406, 418], "local": [13, 14, 16, 20, 21, 24, 26, 30, 32, 34, 35, 36, 38, 222, 224, 225, 226, 231, 232, 238, 240, 241, 246, 247, 249, 255, 256, 258, 263, 279, 280, 288, 289, 306, 308, 317, 319, 322, 326, 328, 330, 333, 347, 350, 354, 357, 361, 406, 418], "desktop": [13, 14, 16, 21, 30, 32, 35, 94, 223, 224, 225, 226, 229, 292, 296, 306, 308, 309, 328, 329, 347], "hpc": [13, 14, 16, 223, 224, 225, 226, 229, 232, 249, 330, 418], "environ": [13, 14, 34, 36, 217, 223, 224, 225, 226, 229, 248, 260, 262, 267, 319, 328], "demonstr": [13, 14, 16, 31, 33, 222, 223, 224, 225, 226, 229, 234, 239, 240, 245, 246, 247, 248, 249, 252, 254, 255, 260, 262, 263, 286, 292, 295, 296, 297, 298, 300, 302, 303, 304, 309, 316, 318, 326, 344], "broken": [13, 14, 16, 26, 223, 224, 226, 229, 238, 280], "split": [13, 238, 239, 240, 280, 334, 357], "two": [13, 14, 16, 19, 23, 28, 30, 32, 33, 35, 38, 42, 70, 108, 127, 141, 147, 175, 222, 224, 225, 226, 230, 231, 233, 235, 238, 239, 240, 242, 246, 247, 248, 249, 252, 253, 254, 255, 257, 258, 262, 265, 266, 267, 279, 281, 288, 292, 293, 294, 296, 297, 298, 299, 300, 301, 302, 303, 306, 309, 316, 330, 331, 332, 335, 336, 337, 341, 344, 345, 346, 347, 349, 352, 353, 354, 356, 357], "front": [13, 16, 239, 254, 262, 328], "end": [13, 16, 19, 28, 30, 50, 53, 66, 155, 158, 171, 222, 224, 225, 226, 231, 232, 233, 239, 247, 249, 254, 262, 292, 306, 308, 309, 328, 343, 345, 347, 357], "ui": [13, 14, 16, 35, 238, 319, 328, 357, 361], "back": [13, 16, 97, 202, 231, 235, 238, 245, 247, 248, 260, 262, 283, 296, 306, 309, 328, 344, 361], "cross": [13, 14, 16, 83, 188, 231, 235, 239, 240, 241, 244, 255, 256, 259, 260, 295, 298, 300, 347, 406], "platform": [13, 14, 16, 23, 24, 223, 224, 225, 226, 229, 267, 295, 303, 306, 307, 309, 341, 344, 357, 418], "qt": [13, 14, 16, 29], "come": [13, 14, 16, 223, 226, 229, 231, 233, 306, 309, 328], "form": [13, 14, 16, 17, 23, 29, 51, 52, 53, 156, 157, 158, 221, 231, 232, 235, 239, 240, 242, 253, 254, 255, 266, 288, 299, 307, 319, 331, 334, 335, 347, 354, 358, 359, 360], "where": [13, 14, 16, 19, 20, 22, 23, 27, 30, 32, 33, 41, 42, 58, 104, 105, 106, 107, 108, 109, 110, 111, 112, 113, 114, 115, 116, 117, 118, 119, 121, 123, 124, 125, 126, 127, 128, 129, 130, 131, 132, 133, 134, 135, 136, 137, 138, 146, 147, 163, 223, 224, 225, 226, 229, 230, 231, 232, 233, 234, 235, 239, 240, 241, 242, 243, 244, 245, 250, 251, 255, 256, 258, 259, 260, 263, 265, 267, 280, 281, 283, 284, 287, 296, 298, 300, 301, 302, 303, 306, 308, 309, 330, 332, 334, 337, 340, 341, 343, 345, 347, 348, 349, 357, 359, 361], "possibl": [13, 14, 16, 27, 29, 117, 136, 221, 222, 223, 224, 225, 226, 227, 228, 229, 233, 234, 239, 240, 241, 242, 244, 247, 253, 255, 256, 257, 259, 263, 266, 267, 281, 288, 292, 297, 298, 299, 300, 328, 347, 348, 352, 353, 354], "made": [13, 14, 16, 101, 102, 222, 232, 238, 240, 241, 245, 246, 247, 248, 249, 252, 256, 260, 262, 263, 283, 289, 292, 296, 306, 307, 309, 319, 348, 350, 357, 361, 418], "now": [13, 14, 16, 35, 38, 231, 234, 238, 292, 294, 295, 296, 306, 307, 313, 330, 341, 355, 357], "break": [13, 14, 16, 242, 246, 248, 280, 316], "major": [13, 14, 16, 33, 117, 119, 136, 138, 141, 143, 230, 234, 239, 243, 252, 254, 258, 262, 265, 267, 280, 293, 295, 297, 316, 320, 346], "block": [13, 14, 16, 29, 35, 41, 42, 43, 44, 45, 46, 47, 48, 49, 50, 51, 53, 54, 55, 57, 58, 59, 62, 64, 66, 67, 68, 69, 70, 73, 75, 76, 77, 78, 79, 81, 82, 83, 84, 85, 87, 89, 90, 91, 94, 97, 101, 102, 104, 105, 106, 107, 108, 109, 110, 111, 112, 113, 114, 115, 116, 117, 118, 119, 121, 122, 123, 124, 125, 126, 127, 128, 129, 130, 131, 132, 133, 134, 135, 136, 137, 138, 141, 142, 143, 146, 147, 148, 149, 150, 151, 152, 153, 154, 155, 156, 158, 159, 160, 162, 163, 164, 167, 169, 171, 172, 173, 174, 175, 178, 180, 181, 182, 183, 184, 186, 187, 188, 189, 190, 192, 194, 195, 196, 202, 206, 207, 208, 209, 211, 212, 213, 232, 248, 263, 286, 348, 349, 359], "terminolog": [13, 14, 16, 239, 254, 334], "outlin": [13, 14, 16, 26, 29, 35, 241, 256, 357], "widget": [13, 14, 16, 29, 234, 298, 302, 323, 328, 339, 341, 352, 353, 357, 360, 374], "jigsaw": [13, 14, 16], "puzzl": [13, 14, 16], "analog": [13, 14, 16], "piec": [13, 14, 16, 280, 341], "displai": [13, 14, 16, 26, 231, 239, 246, 254, 292, 293, 294, 295, 296, 297, 299, 300, 301, 306, 309, 317, 319, 339, 347, 354, 357, 359, 360, 361], "when": [13, 14, 16, 20, 23, 24, 28, 29, 33, 34, 35, 36, 38, 39, 101, 102, 106, 116, 125, 135, 222, 223, 224, 225, 226, 229, 231, 232, 233, 235, 239, 240, 241, 242, 243, 244, 246, 247, 254, 256, 257, 258, 259, 262, 267, 282, 291, 292, 293, 294, 295, 296, 297, 299, 300, 301, 302, 306, 307, 308, 309, 318, 319, 328, 329, 331, 332, 333, 334, 336, 337, 338, 340, 341, 345, 346, 347, 348, 349, 350, 352, 353, 354, 357, 358, 359, 406], "choos": [13, 14, 25, 38, 222, 228, 239, 292, 293, 294, 296, 298, 299, 307, 309, 319, 337, 341, 343, 345, 352, 353, 354, 357, 358], "remot": [13, 14, 16, 20, 21, 24, 26, 28, 35, 223, 229, 243, 258, 289, 319, 322, 328, 330, 347, 361, 406], "job": [13, 14, 16, 20, 22, 24, 26, 243, 258, 328, 350, 360, 361], "previous": [13, 14, 16, 24, 235, 263, 292, 344, 348], "As": [13, 14, 16, 32, 33, 35, 39, 104, 105, 106, 107, 108, 109, 110, 111, 112, 113, 114, 115, 116, 117, 118, 119, 206, 235, 238, 239, 240, 241, 246, 248, 253, 254, 255, 256, 258, 263, 265, 266, 267, 281, 288, 289, 293, 294, 295, 296, 302, 306, 307, 309, 330, 332, 334, 337, 341, 346, 354, 357, 358, 359], "seen": [13, 14, 16, 38, 39, 252, 267, 296, 341], "http": [13, 14, 16, 23, 35, 100, 205, 217, 231, 238, 239, 240, 242, 246, 248, 254, 255, 260, 263, 266, 267, 279, 284, 285, 300, 344, 347, 354, 356, 357, 418], "request": [13, 14, 16, 26, 244, 259, 285, 289, 290, 316, 322, 328, 330, 338, 340, 341, 350, 355, 418], "tapi": [13, 14, 16, 26], "rest": [13, 14, 16, 32, 233, 254, 292, 332], "api": [13, 14, 16, 23, 35, 234, 239, 254], "remoteservic": [13, 14, 16], "compris": [13, 14, 29, 35, 239, 254], "femuq": [13, 14, 16], "py": [13, 14, 16, 22, 26, 30, 32, 33, 38, 243, 249, 258, 292, 293, 328, 330, 344, 347, 357], 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267, 280, 283, 292, 299, 305, 306, 307, 309, 316, 319, 328, 330, 332, 333, 335, 337, 341, 344, 346, 347, 349, 354, 356, 357, 359, 361, 406], "recompil": [13, 14, 16], "control": [13, 14, 16, 86, 90, 191, 195, 222, 228, 230, 231, 232, 248, 262, 292, 296, 302, 326, 337, 341, 349, 354, 358, 361], "repeatedli": [13, 14, 16], "invok": [13, 14, 16, 29, 306, 309, 330, 344, 355, 359], "figur": [13, 14, 16, 38, 39, 222, 231, 232, 234, 235, 238, 248, 258, 281, 286, 292, 293, 294, 296, 297, 299, 300, 301, 306, 309, 332, 334, 336, 347, 348, 349, 354, 357, 358, 360], "hydro": [13, 16], "r2d_workflow": [13, 16, 22, 30, 32], "best": [13, 16, 24, 64, 169, 231, 237, 239, 247, 254, 262, 263, 267, 333, 334, 337, 341], "understood": [13, 16, 231, 240, 255], "look": [13, 16, 35, 108, 127, 296, 303, 306, 309, 313, 316, 321, 328, 354, 357, 359, 374], "press": [13, 16, 231, 292, 299, 300, 307, 309, 340, 352, 353, 357, 360, 361], "button": [13, 16, 35, 38, 234, 238, 243, 258, 292, 293, 294, 295, 296, 297, 298, 299, 300, 301, 302, 306, 307, 308, 309, 313, 319, 328, 337, 340, 341, 347, 352, 353, 354, 355, 358, 360, 361], "temporari": [13, 16, 206, 207, 208, 209, 231, 238, 300, 301, 330, 347], "tmp": [13, 16, 23, 328, 341], "insid": [13, 14, 16, 33, 34, 35, 36, 112, 131, 231, 239, 240, 254, 255, 306, 307, 309, 316, 345, 357], "templatedir": [13, 16, 22, 33, 328], "copyfil": [13, 16], "tell": [13, 16, 292], "copi": [13, 16, 35, 38, 44, 51, 53, 149, 156, 158, 243, 258, 292, 296, 306, 309, 347], "outputtojson": [13, 16, 29], "outputappdatatojson": [13, 16], "augment": [13, 16, 248, 263, 286, 300], "ha": [13, 14, 16, 23, 29, 30, 33, 38, 41, 42, 44, 94, 101, 102, 146, 147, 149, 220, 222, 230, 231, 233, 238, 239, 246, 247, 248, 253, 254, 255, 256, 261, 262, 266, 267, 280, 281, 289, 292, 294, 296, 306, 308, 309, 310, 330, 331, 334, 336, 337, 341, 345, 346, 347, 349, 350, 352, 354, 357, 358, 359], "also": [13, 14, 16, 19, 23, 26, 33, 34, 35, 36, 51, 53, 54, 122, 156, 158, 159, 208, 230, 231, 232, 233, 234, 235, 239, 240, 241, 243, 246, 247, 248, 254, 255, 256, 258, 260, 262, 263, 265, 267, 279, 280, 281, 286, 288, 289, 290, 292, 293, 295, 296, 297, 300, 301, 302, 303, 306, 307, 309, 318, 322, 328, 330, 332, 333, 334, 335, 336, 337, 341, 344, 346, 347, 348, 349, 352, 353, 354, 357, 358, 374], "spin": [13, 14, 16, 263, 292, 330], "until": [13, 14, 16, 24, 232, 240, 255, 267, 334, 343, 345, 347, 357], "signal": [13, 16, 29], "been": [13, 14, 16, 23, 30, 33, 44, 100, 101, 102, 149, 205, 220, 223, 226, 229, 233, 239, 240, 241, 247, 248, 254, 256, 262, 286, 306, 308, 309, 310, 328, 330, 334, 348, 350, 352, 354, 357, 358], "over": [13, 14, 16, 51, 53, 119, 138, 156, 158, 231, 234, 240, 242, 245, 246, 247, 248, 250, 254, 255, 260, 262, 263, 267, 280, 281, 284, 286, 306, 335, 347, 357, 361, 406, 416], "argument": [13, 14, 16, 33, 35, 340, 349], "full": [13, 16, 22, 26, 30, 32, 35, 39, 46, 51, 54, 55, 62, 66, 104, 112, 122, 123, 131, 151, 156, 159, 160, 167, 171, 208, 222, 224, 225, 226, 234, 239, 248, 254, 265, 267, 280, 286, 349, 357, 374, 406, 414], "path": [13, 16, 19, 22, 24, 26, 30, 32, 35, 38, 240, 242, 243, 255, 257, 258, 284, 286, 292, 293, 306, 307, 308, 309, 319, 330, 331, 332, 344, 347, 348, 349, 352, 353, 357, 361, 374, 406, 414], "out": [13, 16, 22, 23, 24, 26, 29, 35, 38, 53, 54, 108, 127, 158, 159, 221, 230, 231, 232, 238, 239, 247, 262, 267, 292, 296, 300, 325, 328, 331, 332, 333, 335, 336, 346, 347, 349, 357, 359, 406], "singl": [13, 14, 16, 20, 28, 30, 33, 38, 39, 42, 46, 51, 53, 97, 104, 105, 106, 107, 108, 109, 110, 111, 112, 113, 114, 115, 116, 117, 118, 119, 133, 137, 143, 147, 151, 156, 158, 202, 206, 207, 208, 209, 224, 230, 231, 232, 233, 234, 238, 239, 241, 242, 248, 254, 256, 257, 263, 265, 279, 286, 292, 299, 300, 301, 302, 306, 307, 333, 334, 345, 354, 357, 359], "line": [13, 14, 16, 26, 35, 83, 119, 138, 188, 223, 229, 238, 239, 240, 254, 255, 265, 292, 294, 296, 306, 307, 309, 328, 330, 334, 341, 347, 349, 352, 353, 357, 359], "space": [13, 16, 30, 33, 44, 50, 53, 70, 117, 136, 149, 155, 158, 175, 231, 232, 235, 239, 240, 246, 254, 265, 267, 284, 292, 296, 300, 308, 319, 330, 331, 332, 334, 341, 343, 344, 345, 346, 347, 349, 350, 352, 406], "separ": [13, 14, 16, 22, 35, 101, 102, 235, 238, 239, 240, 292, 293, 299, 317, 330, 331, 332, 341, 346, 347, 349, 352, 353, 357, 406], "suppli": [13, 14, 16, 82, 187, 222, 224, 225, 226, 313, 319, 324, 349, 351, 355], "getrv": [13, 16, 26], "uqengin": [13, 16], "actual": [13, 14, 16, 54, 55, 94, 159, 160, 231, 239, 246, 248, 254, 267, 300, 301, 302, 306, 309, 336, 337, 345, 347], "param": [13, 16, 29, 330, 349], "done": [13, 14, 16, 34, 35, 36, 38, 222, 230, 243, 258, 292, 293, 294, 295, 297, 302, 330, 341, 349, 352, 353, 354, 357, 358], "notifi": [13, 16], "uqpreprocessor": [13, 16], "read": [13, 16, 18, 24, 25, 28, 29, 30, 38, 222, 223, 224, 225, 226, 229, 262, 292, 300, 306, 307, 309, 326, 334, 336, 346], "them": [13, 16, 29, 38, 106, 114, 116, 125, 133, 135, 222, 228, 235, 241, 243, 256, 258, 267, 289, 290, 299, 306, 307, 309, 316, 328, 341, 347, 357, 358, 361, 406], "happen": [13, 16], "That": [13, 16, 35, 233, 289, 341], "case": [13, 14, 16, 27, 29, 30, 33, 109, 112, 128, 131, 231, 234, 239, 240, 241, 242, 245, 246, 247, 249, 252, 255, 260, 262, 267, 279, 292, 298, 302, 326, 335, 345, 346, 349], "differ": [13, 14, 15, 16, 29, 33, 38, 121, 207, 222, 224, 225, 226, 228, 230, 233, 234, 235, 238, 239, 240, 243, 245, 247, 248, 249, 252, 253, 254, 255, 258, 260, 263, 265, 266, 267, 281, 283, 284, 286, 287, 288, 289, 290, 292, 294, 296, 299, 300, 301, 302, 307, 308, 309, 313, 326, 331, 332, 333, 334, 335, 336, 339, 340, 342, 345, 346, 347, 349, 350, 353, 354, 356, 357, 360, 361], "same": [13, 14, 16, 20, 22, 26, 29, 30, 38, 44, 51, 53, 101, 102, 116, 135, 149, 156, 158, 231, 232, 233, 238, 239, 240, 241, 256, 292, 294, 295, 296, 298, 300, 301, 302, 307, 331, 334, 335, 345, 346, 347, 348, 349, 352, 353, 356, 360], "But": [13, 16, 302], "uqwrapp": [13, 16], "instead": [13, 14, 16, 19, 35, 231, 235, 242, 267, 292, 300, 301, 302, 333, 335, 337, 340, 341, 344, 345, 346, 349, 354, 357], "compress": [13, 16, 69, 106, 116, 125, 135, 174, 341], "12": [13, 16, 26, 30, 32, 33, 35, 38, 46, 47, 48, 49, 50, 51, 53, 70, 92, 94, 98, 143, 151, 152, 153, 154, 155, 156, 158, 175, 197, 203, 222, 231, 235, 238, 239, 240, 242, 254, 255, 265, 267, 279, 292, 294, 336, 340, 345, 347, 418], "send": [13, 16, 361], "13": [13, 16, 26, 30, 32, 33, 51, 54, 55, 62, 143, 156, 159, 160, 167, 222, 231, 235, 238, 242, 254, 265, 267, 279, 284, 294, 295, 302, 309, 347, 354], "transfer": [13, 16, 112, 115, 118, 131, 134, 137], "invoc": [13, 16], "tacc": [13, 16, 23, 223, 224, 225, 226, 229, 289, 317, 357], "portal": [13, 16, 23, 40, 279], "field": [14, 20, 50, 51, 53, 114, 133, 155, 156, 158, 222, 223, 224, 225, 226, 229, 230, 231, 233, 239, 240, 243, 245, 246, 247, 253, 254, 255, 258, 260, 261, 262, 263, 267, 292, 293, 296, 302, 313, 317, 320, 322, 339, 340, 341, 343, 345, 346, 349, 352, 353, 356, 406, 418], "both": [14, 22, 33, 38, 43, 44, 148, 149, 222, 223, 224, 225, 226, 229, 230, 231, 232, 233, 239, 241, 246, 253, 254, 255, 256, 262, 267, 281, 283, 288, 289, 292, 295, 296, 301, 302, 306, 309, 328, 332, 334, 336, 341, 343, 345, 346, 347, 354, 357, 360], "regionsl": 14, "releas": [14, 16, 34, 35, 36, 38, 220, 239, 240, 241, 247, 254, 261, 262, 263, 267, 285, 289, 290, 306, 307, 311, 314, 317, 320, 324, 347, 358, 418], "built": [14, 16, 19, 22, 23, 26, 35, 54, 114, 117, 133, 136, 159, 217, 222, 238, 239, 240, 243, 248, 252, 253, 254, 255, 263, 265, 266, 279, 286, 313, 314, 316, 337, 344, 347], "those": [14, 29, 33, 35, 39, 111, 117, 119, 130, 136, 138, 218, 219, 230, 231, 233, 239, 240, 241, 245, 246, 247, 249, 254, 255, 260, 262, 267, 281, 283, 285, 335, 339, 341, 344, 346, 347, 352, 353, 359, 406], "have": [14, 23, 24, 29, 32, 33, 34, 35, 36, 94, 100, 108, 109, 110, 111, 112, 117, 118, 119, 121, 122, 127, 128, 129, 130, 131, 136, 137, 138, 205, 207, 208, 223, 226, 229, 231, 233, 234, 235, 239, 240, 241, 242, 243, 244, 245, 246, 247, 248, 253, 254, 255, 256, 257, 258, 259, 262, 263, 265, 266, 267, 280, 281, 282, 285, 286, 289, 290, 291, 292, 295, 299, 300, 302, 306, 307, 309, 312, 315, 316, 318, 321, 325, 328, 334, 336, 337, 340, 341, 345, 346, 347, 348, 349, 350, 354, 357, 358, 406], "limit": [14, 29, 30, 33, 42, 94, 101, 102, 105, 106, 121, 122, 124, 125, 147, 207, 208, 221, 222, 228, 230, 231, 233, 238, 239, 245, 246, 251, 252, 254, 260, 262, 263, 264, 280, 281, 286, 289, 292, 293, 300, 301, 302, 306, 309, 334, 337, 340, 342, 343, 345, 347, 354, 357, 406], "involv": [14, 19, 35, 232, 234, 238, 239, 254, 265, 280, 286, 293, 308, 331, 334, 335, 348, 361], "move": [14, 22, 30, 223, 224, 225, 226, 229, 246, 267, 280, 306, 307, 308, 309, 313, 316, 320, 323, 361], "begin": [14, 28, 29, 231, 232, 233, 238, 262, 331, 332, 347, 357], "state": [14, 19, 20, 30, 32, 42, 54, 62, 73, 100, 101, 102, 104, 105, 106, 107, 108, 109, 110, 111, 112, 113, 114, 115, 116, 117, 118, 119, 121, 123, 124, 125, 126, 127, 128, 129, 130, 131, 132, 133, 134, 135, 136, 137, 138, 141, 147, 159, 167, 178, 205, 206, 219, 222, 231, 239, 241, 242, 245, 246, 248, 253, 254, 256, 257, 258, 265, 266, 267, 279, 280, 288, 316, 334, 348, 350, 352, 357, 374, 414], "being": [14, 20, 224, 232, 240, 243, 258, 281, 292, 293, 296, 299, 319, 330, 332, 333, 337, 341, 349, 352, 353, 360], "figcontext": 14, "figcontain": 14, "deisignsaf": 14, "figcomponentfront": 14, "figcomponentback": 14, "mostli": [14, 114, 133, 233], "figumle": 14, "figumlw": 14, "figumlpb": 14, "share": [14, 23, 222, 223, 224, 225, 226, 229, 279, 302, 306, 307, 345, 347, 418], "code": [14, 19, 23, 34, 35, 36, 58, 68, 104, 105, 106, 107, 108, 109, 110, 111, 112, 113, 114, 115, 116, 117, 118, 119, 121, 123, 124, 125, 126, 127, 128, 129, 130, 131, 132, 133, 134, 135, 136, 137, 138, 163, 173, 220, 221, 222, 223, 224, 225, 226, 229, 238, 239, 240, 246, 247, 249, 254, 255, 262, 263, 265, 267, 281, 284, 287, 306, 309, 330, 341, 359, 418], "bundl": [14, 316], "figumlearthquakeev": 14, "figumlwindev": 14, "figumlcommon": 14, "were": [14, 23, 26, 34, 35, 38, 47, 104, 105, 106, 107, 108, 109, 110, 111, 112, 113, 114, 115, 116, 117, 118, 119, 121, 123, 124, 125, 126, 127, 128, 129, 130, 131, 132, 133, 134, 135, 136, 137, 138, 152, 206, 235, 238, 239, 240, 242, 245, 246, 247, 248, 253, 254, 255, 257, 260, 262, 263, 266, 267, 279, 281, 283, 284, 285, 286, 288, 292, 293, 301, 319, 320, 321, 357], "place": [14, 64, 107, 109, 111, 117, 120, 126, 128, 130, 136, 139, 169, 233, 240, 243, 244, 254, 255, 258, 259, 282, 291, 292, 293, 296, 306, 307, 308, 309, 328, 330, 338, 341, 347, 352, 353, 357], "simplifi": [14, 33, 235, 239, 254, 281, 289, 293, 295, 357], "outsid": [14, 54, 107, 112, 117, 126, 131, 136, 159, 233, 239, 241, 254, 256, 301, 314, 349], "programm": [14, 29], "whom": 14, "envis": [14, 247, 262], "ad": [14, 35, 42, 147, 222, 223, 226, 228, 229, 247, 258, 262, 286, 301, 302, 313, 315, 316, 319, 320, 323, 326, 337, 341, 347, 349, 352, 355, 357, 406], "new": [14, 23, 35, 222, 223, 224, 225, 226, 228, 229, 233, 234, 235, 239, 240, 244, 245, 246, 247, 248, 249, 254, 255, 256, 259, 260, 263, 267, 282, 283, 291, 296, 297, 298, 299, 300, 307, 311, 313, 314, 316, 317, 319, 320, 322, 323, 324, 326, 337, 340, 341, 344, 348, 355, 357], "reduc": [14, 101, 102, 106, 117, 125, 136, 222, 223, 224, 225, 226, 229, 231, 232, 234, 262, 265, 267, 281, 294, 302, 308, 319, 325, 335, 336, 346], "overhead": 14, "compil": [14, 33, 34, 35, 36, 238], "THE": [14, 29, 221, 330], "exhaust": [14, 346], "decid": [14, 222, 228, 231, 302, 343, 345, 406], "myriad": 14, "edit": [14, 23, 29, 35, 38, 145, 215, 222, 228, 240, 255, 292, 307, 309, 316, 330, 334, 352, 354, 357], "label": [14, 20, 24, 30, 239, 254, 265], "suffici": [14, 109, 128, 230, 234, 243, 246, 258, 267, 347], "while": [14, 30, 32, 39, 108, 112, 115, 127, 131, 134, 231, 232, 235, 240, 243, 246, 247, 249, 252, 253, 255, 258, 262, 263, 265, 266, 267, 281, 292, 294, 295, 297, 299, 302, 327, 330, 334, 335, 337, 346, 347, 348, 349, 357], "consist": [14, 19, 29, 51, 53, 64, 114, 117, 133, 136, 156, 158, 169, 230, 231, 232, 234, 235, 240, 242, 248, 254, 255, 257, 258, 263, 267, 281, 286, 300, 302, 335, 344, 349, 357], "certain": [14, 122, 208, 230, 231, 247, 249, 253, 262, 266, 267, 292, 334, 341, 357, 360], "attribut": [14, 231, 241, 242, 245, 247, 248, 249, 253, 256, 257, 258, 260, 262, 263, 265, 266, 267, 279, 283, 286, 301, 302, 336, 346, 358], "relationship": [14, 101, 102, 240, 248, 262, 263], "order": [14, 16, 17, 18, 23, 24, 39, 222, 223, 224, 225, 226, 229, 231, 233, 234, 239, 246, 247, 249, 254, 262, 265, 286, 292, 293, 299, 301, 302, 317, 319, 325, 330, 331, 332, 334, 341, 343, 345, 346, 347, 349, 354, 356, 357], "codemaincod": 14, "strip": [14, 109, 128, 239], "version": [14, 23, 29, 34, 35, 36, 140, 144, 210, 214, 217, 222, 228, 232, 238, 239, 246, 248, 254, 258, 279, 281, 284, 289, 290, 306, 307, 309, 311, 314, 317, 320, 324, 336, 337, 347, 357, 358, 418], "deal": 14, "style": [14, 87, 192, 418], "sheet": [14, 19, 46, 67, 83, 107, 126, 151, 172, 188, 240, 255, 281, 346], "analyt": [14, 223, 224, 225, 226, 229, 231, 246, 253], "pertin": 14, "int": [14, 20, 30, 232, 238, 349], "argc": 14, "char": 14, "argv": 14, "qapplic": 14, "qstring": [14, 29], "tenant": [14, 23], "storag": [14, 94, 97, 121, 202, 207, 228, 242, 257, 263], "agav": [14, 23], "default": [14, 19, 24, 26, 29, 33, 35, 54, 55, 64, 81, 82, 83, 84, 85, 89, 90, 91, 94, 159, 160, 169, 186, 187, 188, 189, 190, 194, 195, 196, 222, 223, 224, 225, 226, 229, 231, 233, 234, 239, 240, 241, 246, 254, 255, 256, 265, 266, 279, 289, 290, 292, 293, 294, 295, 296, 297, 298, 299, 300, 301, 302, 306, 307, 308, 309, 317, 319, 334, 337, 341, 343, 345, 346, 347, 351, 352, 353, 354, 357, 361, 374, 401, 406, 415, 416], "dirnam": 14, "window": [14, 22, 23, 24, 29, 33, 34, 35, 36, 51, 53, 108, 127, 156, 158, 222, 239, 242, 246, 250, 253, 254, 255, 260, 266, 280, 281, 294, 297, 299, 300, 301, 302, 305, 306, 309, 310, 316, 326, 329, 344, 347, 357, 361], "workflowappwidget": 14, "theinputapp": 14, "workflowappee_uq": 14, "theremoteservic": 14, "mainwindowworkflowapp": 14, "setvers": 14, "0": [14, 19, 20, 23, 29, 30, 32, 33, 35, 38, 44, 45, 46, 47, 54, 55, 69, 104, 105, 106, 107, 108, 109, 110, 111, 112, 113, 114, 115, 116, 117, 118, 119, 121, 123, 124, 125, 126, 127, 128, 129, 130, 131, 132, 133, 134, 135, 136, 137, 138, 149, 150, 151, 152, 159, 160, 174, 206, 217, 231, 232, 233, 234, 235, 238, 239, 240, 242, 246, 247, 250, 254, 255, 258, 261, 262, 265, 267, 279, 280, 281, 284, 285, 286, 287, 288, 292, 293, 294, 295, 296, 297, 298, 300, 301, 302, 306, 307, 316, 319, 320, 324, 334, 337, 340, 341, 344, 346, 347, 349, 352, 353, 354, 357, 359, 406, 415, 416], "thread": [14, 75, 76, 78, 79, 87, 180, 181, 183, 184, 192], "qthread": 14, "movetothread": 14, "re": [14, 24, 222, 228, 230, 238, 239, 240, 243, 254, 258, 280, 284, 286, 292, 293, 294, 295, 296, 297, 298, 299, 300, 301, 302, 319, 328, 344, 346, 357, 361], "exec": 14, "logout": 14, "stop": [14, 309, 320, 322], "quit": [14, 105, 124, 306, 307], "mention": [14, 279, 337], "qmainwindow": 14, "menu": [14, 35, 292, 293, 294, 295, 296, 297, 299, 308, 320, 328, 332, 334, 335, 337, 340, 341, 350, 351, 354, 356, 361], "item": [14, 19, 222, 239, 240, 242, 245, 260, 283, 349, 361], "close": [14, 233, 235, 239, 241, 255, 256, 267, 281, 285, 300, 335, 346, 354, 357, 361], "help": [14, 222, 231, 234, 239, 244, 248, 259, 267, 282, 286, 291, 306, 316, 318, 328, 336, 346, 347, 354, 361], "cite": [14, 418], "qmainwindowworkflowapp": 14, "qwidget": [14, 29], "respond": [14, 24], "underwai": 14, "earthquakeeventselect": 14, "intern": [14, 232, 246, 250, 255, 263, 312, 315, 318, 321, 325, 331, 344, 349], "fem": [14, 16, 26, 222, 223, 224, 225, 226, 229, 231, 233, 292, 293, 294, 296, 297, 298, 299, 300, 301, 302, 306, 307, 313, 319, 326, 332, 333, 336, 338, 341, 343, 344, 345, 346, 349, 355, 357, 361], "randomvariablecontain": 14, "statu": [14, 23, 29, 222, 223, 224, 225, 226, 227, 228, 229, 243, 258, 334, 347, 357, 361], "retriev": [14, 243, 258, 300, 354], "old": [14, 87, 192, 239, 240, 306, 309, 319], "login": [14, 243, 258, 294, 361], "credenti": [14, 354], "ci": [14, 23, 35, 238, 260, 262, 263, 267, 357, 361], "switch": [14, 33, 297, 298, 319, 332, 341], "amazon": 14, "ec": 14, "ibm": 14, "azur": 14, "elsewher": 14, "eu": 14, "similar": [14, 17, 23, 30, 33, 35, 104, 106, 111, 113, 123, 125, 130, 132, 222, 228, 231, 235, 239, 240, 245, 246, 254, 260, 263, 265, 267, 283, 296, 302, 334, 335, 357, 358], "construct": [14, 19, 30, 33, 47, 50, 51, 53, 57, 58, 59, 62, 65, 66, 67, 68, 69, 70, 72, 73, 75, 76, 77, 78, 79, 81, 82, 83, 84, 85, 87, 89, 90, 91, 94, 97, 100, 104, 105, 106, 107, 108, 109, 110, 111, 112, 113, 114, 115, 116, 117, 118, 119, 121, 123, 124, 125, 126, 127, 128, 129, 130, 131, 132, 133, 134, 135, 136, 137, 138, 152, 155, 156, 158, 162, 163, 164, 167, 170, 171, 172, 173, 174, 175, 177, 178, 180, 181, 182, 183, 184, 186, 187, 188, 189, 190, 192, 194, 195, 196, 202, 205, 206, 207, 208, 209, 222, 223, 224, 225, 226, 229, 233, 239, 240, 241, 245, 246, 247, 248, 249, 254, 255, 260, 262, 263, 265, 267, 280, 286, 287, 295, 332, 334, 335, 341, 347, 418], "fact": [14, 101, 102, 231, 233, 240, 255, 267, 281], "onli": [14, 19, 20, 23, 27, 33, 42, 43, 47, 69, 73, 75, 76, 77, 78, 79, 81, 82, 83, 84, 85, 89, 90, 91, 94, 101, 102, 104, 105, 106, 107, 108, 109, 110, 111, 112, 113, 114, 115, 116, 117, 118, 119, 121, 122, 134, 147, 148, 152, 174, 178, 180, 181, 182, 183, 184, 186, 187, 188, 189, 190, 194, 195, 196, 206, 207, 208, 222, 228, 230, 231, 234, 235, 240, 243, 246, 248, 254, 255, 257, 258, 260, 263, 265, 285, 292, 293, 294, 295, 296, 300, 301, 306, 307, 308, 309, 311, 316, 317, 328, 330, 334, 335, 337, 345, 346, 347, 349, 352, 353, 357, 359, 361], "wind": [14, 19, 25, 27, 32, 228, 239, 243, 245, 247, 248, 251, 253, 254, 257, 258, 260, 262, 263, 264, 265, 266, 267, 288, 315, 320, 321, 322, 325, 326], "figwindev": 14, "stochast": [14, 40, 222, 223, 224, 225, 226, 228, 229, 231, 293, 296, 300, 301, 302, 311, 316, 317, 319, 324, 326, 347, 351, 355, 357, 418], "load": [14, 15, 16, 26, 27, 30, 33, 38, 42, 44, 68, 81, 82, 83, 84, 85, 89, 90, 91, 104, 105, 106, 107, 108, 109, 110, 111, 112, 113, 114, 115, 116, 117, 118, 119, 121, 123, 124, 125, 126, 127, 128, 129, 130, 131, 132, 133, 134, 135, 136, 137, 138, 147, 149, 173, 186, 187, 188, 189, 190, 194, 195, 196, 223, 229, 230, 233, 234, 240, 242, 243, 245, 246, 250, 255, 257, 258, 260, 263, 280, 283, 292, 293, 295, 296, 297, 298, 302, 303, 304, 313, 316, 317, 319, 320, 323, 326, 338, 341, 344, 351, 352, 353, 354, 357, 358, 418], "vortex": [14, 222], "tunnel": [14, 19, 144, 214, 222, 324, 325, 326], "tokyo": 14, "polytechn": 14, "calcul": [14, 26, 39, 94, 222, 224, 225, 226, 228, 231, 232, 233, 239, 242, 245, 251, 254, 260, 280, 281, 283, 293, 295, 297, 300, 313, 314, 315, 316, 321, 323, 336, 341, 347, 349, 350, 354, 357], "downtim": [14, 68, 173, 222, 314, 316], "add": [14, 30, 35, 38, 292, 297, 299, 300, 302, 306, 309, 321, 323, 330, 337, 338, 340, 341, 344, 347, 352, 353, 357, 358, 374, 406], "lossmodelselect": 14, "p58": [14, 222, 228, 316], "hazu": [14, 19, 26, 30, 32, 121, 122, 145, 207, 208, 215, 222, 228, 242, 243, 245, 246, 248, 253, 254, 257, 258, 260, 263, 265, 266, 267, 280, 281, 286, 287, 313, 314, 315, 316, 320, 322, 323], "depend": [14, 27, 28, 30, 33, 34, 36, 115, 117, 121, 122, 134, 136, 207, 208, 222, 228, 231, 232, 235, 239, 241, 246, 254, 256, 258, 302, 305, 306, 309, 312, 315, 316, 318, 321, 325, 335, 347, 348, 351, 354, 356, 357], "calculatedl": 14, "selector": 14, "west": [14, 267, 284, 285, 286, 294, 295, 300, 320, 322, 354, 358], "server": [14, 23, 281, 354], "vlacho": [14, 39, 222, 224, 225, 226, 302, 303, 356, 418], "et": [14, 39, 232, 234, 263, 281, 284, 296, 302, 320, 322, 336, 356], "al": [14, 39, 232, 234, 263, 281, 284, 296, 302, 320, 322, 336, 356], "dabahi": 14, "derkiuerghian": 14, "our": [14, 23, 35, 145, 215, 254, 261, 265, 267, 284, 292, 293, 296, 306, 307, 308, 328], "simcenterev": [14, 26, 30, 32, 33, 243, 258], "rockoutcrop": 14, "siterespons": 14, "wnd": 14, "forc": [14, 19, 26, 30, 32, 33, 105, 106, 108, 110, 112, 113, 115, 118, 124, 125, 127, 129, 131, 132, 134, 137, 233, 292, 295, 331, 335, 337, 341, 359], "univers": [14, 29, 206, 207, 208, 209, 219, 221, 231, 240, 246, 247, 262, 335, 418], "subclass": [14, 242, 248, 257, 286], "simcenterappwidget": 14, "randomvariablescontain": 14, "randomvari": [14, 330], "ransomvari": 14, "randomvariabledistribut": 14, "normal": [14, 38, 51, 58, 59, 62, 64, 66, 67, 68, 69, 70, 75, 76, 77, 78, 79, 81, 82, 83, 84, 85, 87, 89, 90, 91, 94, 97, 156, 163, 164, 167, 169, 171, 172, 173, 174, 175, 180, 181, 182, 183, 184, 186, 187, 188, 189, 190, 192, 194, 195, 196, 202, 222, 223, 224, 225, 226, 229, 231, 235, 242, 253, 257, 266, 267, 281, 284, 286, 292, 296, 299, 300, 302, 317, 338, 340, 341, 347, 349, 354, 357, 374, 406], "lognorm": [14, 20, 30, 32, 33, 222, 223, 224, 225, 226, 229, 242, 253, 257, 266, 280, 288, 317, 338, 340, 341], "uniform": [14, 29, 114, 133, 222, 223, 224, 225, 226, 229, 232, 242, 246, 292, 295, 300, 301, 317, 319, 340, 347, 354, 357, 358], "beta": [14, 20, 30, 32, 33, 67, 172, 222, 223, 224, 225, 226, 229, 231, 317, 337, 340, 357], "gumbel": [14, 222, 223, 224, 225, 226, 229, 317, 340], "backendappl": 14, "reli": [14, 33, 231, 306, 349, 356], "extern": [14, 222, 223, 224, 225, 226, 229, 230, 231, 306, 308, 309, 314, 316, 323, 354, 361, 374], "websit": [14, 38, 222, 223, 224, 225, 226, 229, 238, 328, 354, 361], "librari": [14, 16, 33, 35, 39, 222, 235, 240, 245, 255, 260, 283, 306, 314, 329, 344, 347, 354, 356], "figappdiagrambackend": 14, "categor": [15, 346], "intermedi": [15, 28, 232], "next": [15, 30, 33, 232, 235, 238, 243, 253, 254, 258, 288, 292, 293, 294, 295, 296, 297, 299, 309, 312, 315, 318, 321, 330, 333, 334, 348, 349], "everi": [15, 20, 23, 28, 30, 232, 239, 240, 255, 284, 300, 301, 306, 309, 328, 329, 331, 332, 337, 341, 349, 352, 353], "im": [15, 19, 20, 27, 30, 32, 216, 230, 243, 258, 300, 301, 313, 320, 322, 347, 354, 355, 406], "quantifi": [15, 231, 233, 235, 239, 246, 253, 254, 261, 266, 288, 289, 317, 334, 335, 336, 346, 347, 418], "experi": [15, 222, 223, 224, 225, 226, 229, 232, 246, 263, 281, 317, 319, 324, 331, 332, 347, 349, 406], "backbon": [15, 239, 254], "subset": [15, 231, 234, 239, 248, 267, 316, 352, 353, 416], "depot": [16, 23, 247, 258, 262, 328], "right": [16, 23, 29, 30, 221, 231, 233, 234, 239, 254, 281, 292, 296, 297, 299, 300, 301, 302, 306, 307, 308, 309, 332, 334, 340, 341, 344, 347, 357, 358, 360, 361], "left": [16, 30, 35, 38, 231, 233, 234, 254, 281, 292, 294, 295, 296, 297, 299, 300, 301, 302, 332, 334, 337, 340, 341, 347, 352, 353, 357, 358, 360, 361], "conjunct": [16, 239, 254], "feap": 16, "upload": [16, 23, 30, 32, 258, 341, 344, 354], "filesystem": [16, 299, 308, 309], "optim": [16, 30, 231, 234, 239, 254, 286, 297, 302, 319, 332, 333, 334, 335, 336, 343, 345, 347, 350, 406], "appli": [16, 27, 30, 33, 51, 53, 73, 156, 158, 178, 220, 232, 233, 234, 235, 239, 240, 242, 244, 246, 247, 253, 254, 255, 256, 259, 261, 262, 263, 266, 267, 285, 297, 301, 307, 336, 337, 341, 344, 349, 354], "occur": [16, 54, 101, 102, 104, 123, 159, 233, 234, 235, 238, 280, 281, 285, 286, 323, 328, 333, 357], "preprocessor": 16, "better": [17, 101, 102, 234, 243, 252, 267, 281, 334, 348, 357], "again": [17, 35, 233, 240, 255, 263, 296, 302, 309, 348, 349], "although": [17, 121, 122, 207, 208, 240, 267, 298], "free": [17, 30, 35, 223, 224, 225, 226, 229, 234, 238, 299, 317, 319, 357], "arrang": 17, "indic": [17, 19, 20, 23, 30, 38, 116, 135, 222, 223, 224, 225, 226, 229, 235, 239, 240, 244, 253, 254, 255, 259, 265, 266, 267, 280, 282, 291, 292, 309, 317, 334, 336, 349, 357], "instanc": [18, 32, 34, 35, 36, 234, 235, 240, 246, 253, 255, 283, 330, 335, 344, 354], "prepar": [18, 22, 25, 222, 228, 230, 231, 293, 328, 352, 353, 357, 358], "standard": [18, 20, 28, 29, 30, 32, 33, 38, 39, 42, 50, 53, 87, 94, 97, 147, 155, 158, 192, 202, 222, 228, 231, 232, 233, 234, 235, 239, 240, 246, 247, 249, 254, 255, 261, 262, 263, 267, 292, 293, 294, 295, 296, 297, 299, 300, 301, 302, 311, 314, 316, 317, 324, 334, 335, 337, 340, 345, 347, 349, 354, 355, 418], "content": [18, 28, 33, 94, 97, 121, 122, 202, 207, 208, 242, 279, 292, 296, 328, 330, 347], "deviat": [18, 20, 30, 32, 33, 38, 39, 231, 234, 235, 256, 267, 292, 293, 294, 295, 296, 299, 301, 317, 334, 335, 340, 345, 347, 349, 354], "error": [18, 21, 23, 26, 29, 100, 205, 222, 223, 224, 225, 226, 229, 231, 232, 234, 238, 239, 242, 254, 257, 258, 294, 295, 297, 300, 302, 306, 307, 308, 316, 317, 319, 328, 329, 335, 338, 341, 343, 344, 345, 347, 348, 354, 358, 361, 406], "upon": [18, 51, 53, 59, 62, 66, 68, 75, 76, 77, 78, 79, 81, 83, 84, 87, 89, 90, 91, 94, 97, 106, 116, 125, 135, 156, 158, 164, 167, 171, 173, 180, 181, 182, 183, 184, 186, 188, 189, 192, 194, 195, 196, 202, 218, 219, 222, 240, 241, 245, 248, 254, 255, 256, 260, 263, 283, 286, 292, 296, 340, 344, 347, 357], "summari": [18, 22, 23, 28, 33, 38, 293, 297, 299, 300, 301, 302, 340, 344, 345, 355, 357, 360, 418], "guid": [18, 23, 25, 26, 27, 29, 35, 240, 243, 247, 255, 258, 262, 300, 328, 347, 361], "refer": [18, 21, 23, 24, 25, 26, 28, 30, 32, 104, 105, 106, 107, 108, 109, 110, 111, 112, 113, 114, 115, 116, 117, 118, 119, 206, 231, 232, 234, 239, 240, 246, 254, 255, 258, 260, 281, 302, 333, 334, 338, 341, 347, 348, 349, 356], "rundir": [19, 22, 23, 30, 32, 33], "localappdir": [19, 22, 23, 30, 32, 33, 330], "unit": [19, 20, 26, 30, 32, 33, 38, 54, 55, 69, 81, 82, 83, 85, 86, 87, 89, 90, 91, 104, 105, 106, 107, 108, 109, 110, 111, 112, 113, 114, 115, 116, 117, 118, 119, 121, 123, 124, 125, 126, 127, 128, 129, 130, 131, 132, 133, 134, 135, 136, 137, 138, 159, 160, 174, 186, 187, 188, 190, 191, 192, 194, 195, 196, 206, 239, 243, 246, 250, 254, 258, 265, 279, 287, 292, 293, 299, 313, 339, 341, 355, 357], "dictionari": [19, 30], "string": [19, 20, 23, 319, 341, 349, 352, 353, 356, 359, 415], "specifii": 19, "length": [19, 26, 30, 32, 33, 44, 143, 149, 222, 230, 231, 232, 235, 239, 246, 293, 302, 326, 331, 332, 333, 341, 345, 346, 349, 357, 415], "n": [19, 23, 231, 232, 233, 234, 235, 238, 239, 240, 246, 254, 255, 260, 263, 267, 284, 286, 332, 335, 347, 349], "m": [19, 30, 33, 38, 39, 41, 104, 105, 106, 109, 110, 111, 112, 113, 115, 116, 117, 123, 124, 125, 128, 129, 130, 131, 132, 134, 135, 136, 143, 146, 222, 223, 224, 225, 226, 227, 228, 229, 231, 232, 233, 234, 235, 239, 240, 246, 250, 260, 261, 263, 267, 279, 281, 284, 285, 286, 287, 293, 296, 301, 302, 331, 332, 336, 337, 341, 347, 357, 418], "sec": [19, 26, 30, 33, 298, 300, 302, 354, 406], "true": [19, 26, 29, 30, 32, 33, 38, 231, 234, 254, 300, 334], "fals": [19, 26, 29, 30, 32, 33, 300], "bool": [19, 29], "dict": 19, "necessari": 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293, 294, 295, 296, 297, 301, 330, 334, 335, 336, 337, 341, 346, 349, 357], "keyword": [19, 319], "longitud": [19, 30, 32, 33, 234, 238, 239, 246, 254, 265, 267, 279, 298, 354], "latitud": [19, 30, 32, 33, 234, 238, 239, 246, 254, 265, 267, 279, 298, 354], "occupancyclass": [19, 30, 32, 239, 240, 255, 263, 265, 267], "buildingtyp": [19, 32, 239, 265, 267], "structuretyp": [19, 30, 32, 239], "yearbuilt": [19, 30, 32, 33, 238, 239, 240, 253, 255, 260, 263, 265, 266, 267], "numberofstori": [19, 30, 32, 240, 265, 267], "planarea": [19, 30, 32, 254], "replacementcost": [19, 20, 30, 32, 33], "roofshap": [19, 32, 240, 253, 255, 265, 266, 267], "roofslop": [19, 32, 240, 255, 265, 267], "roofcov": [19, 32, 239, 254, 255], "roofsystem": [19, 32, 239, 240, 254], "meanroofht": [19, 32, 265, 267], "windowarea": [19, 32, 240, 254], "garag": [19, 32, 119, 138, 222, 238, 239, 240, 242, 255, 257, 263, 265, 267, 280], "nounit": [19, 32, 239], "designlevel": [19, 32, 239], "dswii": [19, 32, 239, 240, 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260, 267, 281, 283, 295, 297, 306, 309, 341, 347, 349, 359, 360, 406], "wai": [23, 29, 33, 35, 221, 231, 242, 246, 255, 257, 333, 341, 357], "notebook": [23, 222, 258, 280], "ubuntu": 23, "rwhale_config_remot": 23, "my": [23, 35, 306], "createlaunchertask": 23, "run_rwhal": 23, "ipynb": [23, 258], "On": [23, 35, 231, 238, 254, 301, 302, 306, 309, 329, 333, 335, 345, 357], "appear": [23, 24, 42, 147, 306, 309, 341, 347, 352, 353], "click": [23, 35, 38, 231, 234, 238, 243, 258, 292, 293, 294, 295, 296, 297, 298, 299, 300, 301, 302, 306, 307, 308, 309, 317, 319, 328, 341, 344, 345, 352, 353, 354, 357, 361], "taken": [23, 234, 240, 248, 253, 288, 302, 335, 354, 358], "frontera": [23, 243, 247, 258, 262, 289, 317, 357], "cell": [23, 48, 49, 153, 154, 258, 280, 292, 341, 357], "navig": [23, 24, 35, 294, 295, 296, 297, 298, 299, 308, 309], "workspac": [23, 238], "bar": [23, 38, 206, 207, 208, 209, 232, 235, 280, 357], "newest": 23, "oldest": 23, "info": [23, 300, 338, 341, 347], "realiz": 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334, 346, 348], "polici": [23, 29, 281], "found": [23, 26, 33, 39, 220, 230, 231, 235, 239, 243, 254, 258, 267, 280, 299, 300, 302, 308, 309, 330, 335, 341, 347, 354, 357], "utexa": [23, 357], "usag": [23, 222, 223, 224, 225, 226, 229, 248, 286, 303, 309, 347], "abid": 23, "aup": 23, "conduct": [23, 231, 234, 239, 242, 243, 245, 246, 252, 254, 258, 260, 262, 265, 267, 299, 337, 354, 357, 358], "coc": 23, "improv": [23, 101, 102, 121, 122, 207, 208, 222, 231, 234, 238, 241, 243, 245, 247, 254, 256, 260, 262, 265, 267, 283, 302, 313, 316, 318, 319, 321, 322, 326, 346, 348, 355, 357], "abil": [23, 33, 222, 223, 224, 225, 226, 229, 245, 246, 260, 283, 323, 325], "support": [23, 27, 28, 29, 69, 83, 101, 102, 109, 110, 111, 117, 128, 129, 130, 136, 143, 174, 188, 218, 219, 231, 238, 239, 242, 245, 246, 254, 257, 260, 261, 280, 283, 285, 293, 302, 314, 315, 316, 317, 319, 320, 322, 323, 325, 326, 340, 343, 345, 347, 349, 354, 357, 406], "like": [23, 34, 36, 104, 108, 115, 123, 127, 134, 222, 223, 226, 229, 235, 239, 240, 241, 243, 246, 253, 255, 256, 258, 266, 267, 279, 281, 285, 289, 290, 292, 296, 297, 300, 301, 302, 306, 309, 313, 347, 354, 355, 357, 359, 418], "ip": [23, 69, 174], "address": [23, 32, 238, 239, 240, 254, 265, 306, 307], "funder": 23, "stakehold": 23, "consent": 23, "url": [23, 238, 418], "3dem": 23, "prod": 23, "public": [23, 29, 238, 263, 267, 279, 281, 306, 307, 316, 321], "agaveapi": 23, "co": 23, "araport": 23, "iplantc": 23, "cyvers": 23, "scienc": [23, 218, 223, 224, 225, 226, 229, 240, 245, 246, 250, 260, 283, 285, 418], "irec": 23, "ireceptor": 23, "sd2e": 23, "sgci": 23, "gatewai": 23, "institut": [23, 206, 207, 208, 209, 261, 262, 263, 418], "vdjserver": 23, "vdj": 23, "taccus": 23, "r2d_test_run": 23, "chang": [23, 30, 35, 38, 44, 149, 234, 235, 239, 240, 242, 247, 249, 254, 255, 262, 266, 292, 293, 296, 301, 306, 307, 312, 313, 315, 318, 319, 321, 323, 325, 328, 330, 333, 337, 341, 349, 352, 357, 360], "vim": 23, "editor": [23, 29], "ctrl": 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353, 354, 357, 358, 406], "successfulli": [24, 26, 27, 243, 258, 302, 328, 354, 358, 360], "recommend": [24, 35, 94, 218, 219, 230, 239, 240, 241, 255, 256, 285, 293, 300, 301, 306, 307, 308, 309, 335, 346, 347, 352, 353, 354, 357], "fail": [24, 35, 222, 224, 225, 226, 238, 263, 280, 300, 301, 306, 308, 309, 328, 333, 334, 340, 416], "verifi": [24, 38, 39, 248, 252, 263, 265, 306], "correct": [24, 39, 40, 233, 238, 239, 267, 302, 306, 309, 321, 328, 330], "applicationdata": [24, 30, 32, 33], "incorrect": [24, 328], "serial": [24, 347], "mistak": 24, "unclos": 24, "bracket": [24, 94, 325], "indent": [24, 29], "caus": [24, 29, 33, 55, 58, 67, 122, 160, 163, 172, 208, 221, 241, 256, 265, 267, 280, 292, 293, 294, 295, 296, 306, 328, 329, 340, 349], "print": [24, 26, 30, 33, 38, 238, 319], "rerun": [24, 306], "suppress": [24, 347], "issu": [24, 30, 35, 239, 241, 254, 256, 300, 301, 306, 307, 309, 327, 337, 347], "find": [24, 34, 35, 36, 218, 219, 231, 235, 238, 256, 258, 285, 291, 292, 296, 306, 309, 316, 328, 332, 333, 347, 357], "still": [24, 240, 241, 256, 267, 309], "persist": [24, 328], "question": [24, 244, 247, 249, 259, 262, 281, 282, 291, 347], "forum": [24, 226, 247, 262, 282, 312, 315, 318, 321, 325, 347, 355], "member": [24, 104, 105, 114, 116, 119, 123, 124, 133, 135, 138, 222, 224, 225, 226, 233, 241, 242, 245, 247, 256, 262, 267, 283, 295, 341], "storm": [25, 32, 216, 222, 228, 239, 240, 242, 245, 247, 248, 251, 253, 260, 261, 262, 263, 266, 267, 288, 325, 334], "surg": [25, 216, 228, 240, 242, 245, 247, 248, 251, 253, 260, 262, 263, 266, 267, 288, 334], "fidel": [25, 222, 223, 224, 225, 226, 229, 239, 245, 246, 248, 254, 260, 263, 281, 283, 286, 303, 311, 313, 316, 317, 319, 321, 325, 337, 341, 347], "match": [25, 30, 44, 149, 222, 224, 225, 226, 230, 231, 234, 238, 239, 246, 254, 260, 297, 300, 301, 302, 331, 332, 341, 346, 347, 348, 349, 354, 357], "carri": [26, 35, 235, 238, 242, 357], "termin": [26, 30, 32, 34, 36, 86, 191, 306, 307, 309, 328, 333, 347, 406], "reproduc": [26, 29, 39, 221, 231, 238, 300, 301, 302, 335, 343, 345, 348, 349, 357, 374, 414], "explain": [26, 258, 265, 267, 302, 330, 346, 348, 349, 357], "statement": 26, "success": [26, 29, 34, 35, 36, 38, 254, 309, 360], "16": [26, 30, 32, 33, 35, 45, 46, 48, 49, 50, 51, 53, 70, 94, 143, 150, 151, 153, 154, 155, 156, 158, 175, 222, 234, 235, 239, 240, 242, 246, 250, 254, 263, 265, 267, 294, 295, 301, 306, 341, 354], "62": [26, 30, 32, 33, 235, 242], "64": [26, 239, 242, 281, 306, 307, 309], "85": [26, 231, 238, 239, 242, 246, 252, 254, 263, 357], "skip": [26, 28, 292, 293, 296], "exclud": [26, 28, 58, 163, 206, 207, 208, 209, 239, 254, 299, 346], "93": [26, 30, 33, 55, 160, 231, 242, 254, 265, 267, 286, 347], "createbim": 26, "csv_to_bim": [26, 30, 32, 33], "buildingfil": [26, 32, 33], "earthquake_exampl": 26, "buildings1": 26, "buildingsourcefil": [26, 30, 32, 33], "input_param": [26, 33], "103": [26, 30, 32, 33, 46, 151, 287], "performregionalmap": 26, 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281, 284, 285, 286, 292, 296, 326, 328, 347, 349, 357], "prefer": [27, 231, 235, 239, 241, 243, 256, 258, 306, 308, 309, 316, 328, 336, 337, 346, 347, 350], "summar": [27, 33, 231, 234, 235, 238, 239, 240, 241, 243, 248, 252, 253, 254, 255, 256, 258, 263, 265, 266, 267, 279, 281, 286, 293, 297, 357], "figworkflowdiagram": 27, "flowchart": [27, 234], "suitabl": [27, 33, 240, 255], "hu": [27, 32, 231, 243, 258, 320, 322, 346], "appropri": [27, 30, 32, 104, 105, 106, 107, 108, 109, 110, 111, 112, 113, 114, 115, 116, 117, 118, 119, 121, 123, 124, 125, 126, 127, 128, 129, 130, 131, 132, 133, 134, 135, 136, 137, 138, 206, 232, 240, 296, 299, 306, 307, 309, 335], "hurrican": [27, 31, 222, 228, 240, 242, 243, 245, 247, 248, 249, 251, 252, 253, 255, 257, 258, 260, 262, 263, 264, 266, 267, 288, 315, 320, 322], "known": [27, 33, 35, 101, 102, 231, 232, 233, 241, 248, 256, 289, 293, 306, 332, 334, 335, 340, 349, 357], "fragil": [27, 32, 44, 47, 53, 58, 67, 73, 75, 76, 77, 78, 79, 81, 82, 83, 84, 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73, 94, 148, 151, 153, 159, 178], "031": [43, 46, 47, 51, 53, 54, 55, 148, 151, 152, 156, 158, 159, 160], "032": [43, 46, 47, 54, 55, 148, 151, 152, 159, 160], "041": [43, 46, 51, 54, 55, 148, 151, 156, 159, 160], "wuf": [43, 148], "joint": [43, 44, 47, 64, 109, 114, 128, 133, 148, 149, 152, 169, 222, 228, 231, 232, 235, 253, 280, 334, 346], "042": [43, 46, 148, 151], "051": [43, 46, 54, 55, 148, 151, 159, 160], "052": [43, 46, 54, 55, 148, 151, 159, 160], "ebf": [43, 148], "200": [43, 148, 239, 242, 246, 248, 257, 300, 301], "aci": [44, 47, 149, 152], "318": [44, 47, 149, 152], "smf": [44, 149], "conc": [44, 149], "col": [44, 149], "bm": [44, 149, 222, 224, 225, 226], "aci318": [44, 149], "mutual": [44, 100, 149, 205, 232], "exclus": [44, 100, 149, 205], "compliment": [44, 149], "laura": [44, 149, 217, 258, 260, 262, 263, 267], "low": [44, 46, 70, 76, 78, 79, 87, 92, 94, 104, 105, 106, 107, 108, 109, 110, 111, 112, 113, 114, 115, 116, 117, 118, 119, 121, 123, 124, 125, 126, 127, 128, 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"7iii": [44, 149], "face": [44, 149, 231, 239, 248, 254, 347], "longitudin": [44, 114, 133, 149], "steel": [44, 52, 53, 64, 75, 76, 78, 79, 83, 87, 104, 106, 109, 110, 111, 117, 119, 120, 123, 125, 128, 129, 130, 136, 138, 139, 143, 149, 157, 158, 169, 180, 181, 183, 184, 188, 192, 222, 224, 225, 226, 233, 239, 248, 252, 279, 286, 294, 295, 302, 303, 311, 313, 316, 355, 418], "discontinu": [44, 149, 231, 347], "131b": [44, 149], "132a": [44, 149], "132b": [44, 149], "133a": [44, 149], "133b": [44, 149], "convention": [45, 150, 231, 347], "rectangular": [46, 151, 261, 326], "wall": [46, 51, 52, 56, 62, 69, 71, 87, 94, 112, 114, 118, 119, 120, 122, 131, 133, 137, 138, 139, 151, 156, 157, 161, 167, 174, 176, 192, 208, 233, 239, 241, 242, 254, 255, 256, 257, 280, 281, 302], "less": [46, 75, 76, 78, 79, 83, 117, 136, 143, 151, 180, 181, 183, 184, 188, 233, 235, 240, 246, 254, 255, 256, 258, 265, 267, 281, 292, 357], "curtain": [46, 56, 112, 131, 151, 161], "orthogon": [46, 151, 235, 239, 254, 296, 341, 418], "psi": [46, 151], "shorten": [46, 151], "pact": [46, 54, 55, 64, 81, 82, 83, 84, 85, 89, 90, 91, 94, 151, 159, 160, 169, 186, 187, 188, 189, 190, 194, 195, 196, 222], "andrew": [46, 151, 247, 262], "whittak": [46, 151], "sf": [46, 48, 49, 50, 51, 53, 54, 55, 57, 67, 68, 69, 94, 151, 153, 154, 155, 156, 158, 159, 160, 162, 172, 173, 174, 279], "900": [46, 151, 239], "013": [46, 48, 49, 57, 94, 151, 153, 154, 162], "023": [46, 48, 54, 94, 151, 153, 159], "rise": [46, 104, 105, 106, 109, 110, 111, 112, 113, 115, 116, 117, 123, 124, 125, 128, 129, 130, 131, 132, 134, 135, 136, 151, 222, 238, 248, 254, 263, 286, 324, 325, 326], "flang": [46, 151], "033": [46, 54, 55, 151, 159, 160], "053": [46, 54, 55, 151, 159, 160], "062": [46, 151], "063": [46, 151, 357], "071": [46, 54, 151, 159], "072": [46, 54, 151, 159, 263], "073": [46, 151], "081": [46, 54, 151, 159], "082": [46, 54, 151, 159], "083": [46, 54, 151, 159], "091": [46, 54, 151, 159], "greater": [46, 48, 49, 76, 78, 79, 83, 104, 105, 106, 107, 108, 109, 110, 111, 112, 113, 114, 115, 116, 117, 118, 119, 131, 138, 143, 151, 153, 154, 181, 183, 184, 188, 206, 231, 235, 240, 243, 248, 255, 258, 265, 346, 347, 406], "092": [46, 151], "112": [46, 151, 231, 238, 267], "vg": [47, 152], "vo": [47, 152], "reinf": [47, 152], "qualiti": [47, 50, 51, 53, 57, 58, 59, 62, 64, 66, 67, 68, 69, 70, 73, 75, 76, 77, 78, 79, 81, 82, 83, 84, 85, 87, 89, 90, 91, 94, 97, 152, 155, 156, 158, 162, 163, 164, 167, 169, 171, 172, 173, 174, 175, 178, 180, 181, 182, 183, 184, 186, 187, 188, 189, 190, 192, 194, 195, 196, 202, 231, 239, 240, 241, 254, 255, 256, 302], "56": [47, 94, 152, 239, 242, 254], "63": [47, 152, 235, 242], "89": [47, 55, 152, 160, 238, 239, 242, 254], "can3": [47, 152], "a23": [47, 152], "m84": [47, 152], "mc": [47, 104, 105, 107, 108, 109, 110, 111, 112, 113, 114, 115, 118, 119, 121, 123, 124, 126, 127, 128, 129, 130, 131, 132, 133, 134, 137, 138, 152, 231, 311, 317, 320, 322, 324, 334, 345, 346], "tension": [47, 92, 114, 133, 152, 197], "ibc": [47, 152, 240, 263, 267, 354], "judgment": [47, 101, 102, 152, 239, 240, 241, 255, 256], "lack": [47, 152, 235, 267], "drop": [47, 83, 87, 152, 188, 192, 262, 292, 293, 332, 334, 335, 341, 351, 354, 356, 361], "capit": [47, 152], "specimen": [47, 55, 152, 160, 232], "partial": [48, 62, 66, 104, 112, 118, 123, 131, 137, 153, 167, 171, 231, 280], "grout": [48, 49, 153, 154], "domin": [48, 49, 153, 154, 231, 235, 239, 248, 254, 263, 267, 285, 286, 336, 346], "foot": [48, 67, 101, 102, 153, 172, 239, 242, 248], "tall": [48, 49, 51, 53, 59, 94, 97, 153, 154, 156, 158, 164, 202, 245, 248, 260, 280, 281, 283, 286], "benson": [48, 49, 153, 154], "shing": [48, 49, 153, 154], "225": [48, 49, 90, 153, 154, 195], "004": [48, 49, 153, 154], "014": [48, 49, 57, 153, 154, 162], "024": [48, 153], "t": [49, 94, 154, 231, 232, 233, 234, 235, 240, 242, 246, 248, 255, 260, 263, 267, 280, 292, 300, 337, 354, 357, 418], "o12": [49, 154], "sheath": [50, 51, 53, 110, 117, 118, 119, 129, 136, 137, 138, 155, 156, 158, 242, 254, 265], "interior": [50, 53, 100, 110, 111, 117, 118, 129, 130, 136, 137, 155, 158, 205, 240, 242, 255, 267, 295, 341], "gypsum": [50, 51, 53, 62, 66, 118, 137, 155, 156, 158, 167, 171, 280, 281], "mil": [50, 53, 155, 158], "osb": [50, 51, 53, 155, 156, 158], "plywood": [50, 53, 107, 110, 117, 118, 119, 126, 129, 136, 137, 138, 155, 158, 280], "overturn": [50, 53, 105, 124, 155, 158, 280], "restraint": [50, 53, 81, 82, 83, 84, 85, 89, 90, 91, 94, 155, 158, 186, 187, 188, 189, 190, 194, 195, 196], "aisi": [50, 53, 155, 158], "screw": [50, 53, 155, 158], "oc": [50, 53, 155, 158], "perimet": [50, 53, 110, 117, 129, 136, 155, 158, 240, 255], "ew": [50, 53, 155, 158], "exterior": [50, 51, 58, 61, 112, 116, 119, 122, 131, 135, 138, 155, 156, 163, 166, 208, 240, 242, 255, 280, 281, 295, 341], "stucco": [50, 51, 53, 118, 119, 137, 138, 155, 156, 158, 280], "strap": [50, 53, 155, 158, 239, 240, 254, 255], "brace": [50, 51, 52, 53, 62, 66, 68, 70, 75, 76, 77, 78, 79, 87, 106, 110, 114, 116, 119, 120, 121, 122, 125, 129, 133, 135, 138, 139, 155, 156, 157, 158, 167, 171, 173, 175, 180, 181, 182, 183, 184, 192, 207, 208], "inch": [50, 51, 53, 69, 70, 75, 76, 78, 79, 155, 156, 158, 174, 175, 180, 181, 183, 184, 240, 254, 255, 297], "attach": [50, 53, 155, 158, 222, 239, 240, 242, 253, 254, 255, 257, 266, 267, 280], "driven": [50, 53, 155, 158, 222, 231, 240, 255, 297, 344, 346], "flush": [50, 53, 155, 158], "surfac": [50, 53, 94, 107, 126, 155, 158, 231, 239, 252, 254, 261, 263, 265, 267, 284, 293, 297, 311, 323, 334, 335, 347, 355, 357], "wallboard": [51, 53, 156, 158], "hold": [51, 53, 156, 158, 231, 239], "ply": [51, 53, 156, 158, 240, 255], "8d": [51, 53, 156, 158, 240, 255, 265], "nail": [51, 53, 156, 158, 239, 240, 254, 255, 265, 267], "df": [51, 53, 156, 158], "2x4": [51, 53, 156, 158], "stud": [51, 53, 62, 118, 137, 156, 158, 167, 241, 256, 280], "feet": [51, 53, 87, 118, 119, 137, 138, 156, 158, 192, 239, 240, 242, 254, 341], "door": [51, 53, 108, 127, 156, 158, 239, 240, 242, 254, 263, 280, 281], "andr": [51, 53, 156, 158], "filiatrault": [51, 53, 156, 158], "chop": [51, 53, 156, 158], "strand": [51, 53, 156, 158], "fiber": [51, 53, 156, 158, 302], "wire": [51, 53, 69, 83, 156, 158, 174, 188], "mesh": [51, 53, 156, 158, 222, 224, 225, 226, 231, 246, 293, 326], "fasten": [51, 53, 156, 158], "stapl": [51, 53, 156, 158], "let": [51, 53, 156, 158, 231, 232, 238, 294, 295, 300, 301, 302, 308, 314], "sill": [51, 53, 156, 158, 235, 280], "opposit": [51, 53, 156, 158], "1x": [51, 53, 156, 158], "2x": [51, 53, 156, 158], "inclin": [51, 53, 156, 158], "recess": [51, 53, 156, 158], "lumber": [51, 53, 118, 137, 156, 158], "x100": [51, 62, 66, 156, 167, 171, 239, 254], "c1011": [51, 156], "lf": [51, 53, 59, 62, 66, 75, 76, 77, 78, 79, 83, 87, 97, 101, 102, 140, 156, 158, 164, 167, 171, 180, 181, 182, 183, 184, 188, 192, 202, 210, 231, 302], "rc": [52, 157], "composit": [52, 67, 106, 115, 116, 125, 134, 135, 157, 172], "shearwal": [52, 157], "slab": [52, 109, 128, 157, 241, 242, 256], "masonri": [52, 60, 107, 112, 118, 120, 126, 131, 137, 139, 157, 165, 222, 239, 248, 252, 254, 279, 280, 281, 286], "cold": [52, 53, 80, 157, 158, 185], "light": [52, 53, 69, 71, 105, 108, 120, 121, 124, 127, 139, 141, 157, 158, 174, 176, 206, 207, 208, 209, 240, 267, 280, 357], "b1061": [53, 158], "b1071": [53, 158], "201a": [53, 158], "precast": [53, 64, 112, 120, 131, 139, 158, 169], "plane": [53, 55, 108, 116, 127, 135, 158, 160, 239, 254, 296, 357], "deform": [53, 104, 123, 158, 233], "x13": [53, 158], "volum": [53, 83, 100, 158, 188, 205, 332], "201b": [53, 158], "anchorag": [53, 81, 82, 83, 84, 85, 89, 90, 91, 107, 108, 121, 122, 126, 127, 158, 186, 187, 188, 189, 190, 194, 195, 196, 207, 208, 263, 280], "capac": [53, 81, 82, 83, 84, 85, 89, 90, 91, 109, 112, 115, 128, 131, 134, 158, 186, 187, 188, 189, 190, 194, 195, 196, 248, 262, 263, 286, 287], "midris": [54, 159], "stick": [54, 159], "monolith": [54, 55, 64, 159, 160, 169], "lamin": [54, 55, 119, 138, 159, 160], "glass": [54, 55, 94, 159, 160, 239, 240, 255, 280, 306], "insul": [54, 55, 159, 160, 242], "dual": [54, 55, 115, 134, 159, 160], "pane": [54, 55, 159, 160, 280], "asymmetr": [54, 159], "unequ": [54, 159], "igu": [54, 55, 159, 160], "anneal": [54, 55, 159, 160], "mm": [54, 55, 159, 160], "inner": [54, 55, 159, 160], "outer": [54, 55, 159, 160, 240], "lam": [54, 55, 119, 138, 159, 160], "030": [54, 55, 159, 160], "pvb": [54, 55, 159, 160], "clearanc": [54, 55, 159, 160], "sealant": [54, 55, 159, 160], "dry": [54, 55, 67, 159, 160, 172, 246], "ssg": [54, 159], "wet": [54, 55, 75, 76, 77, 78, 79, 159, 160, 180, 181, 182, 183, 184, 246], "dispers": [54, 64, 67, 81, 82, 83, 84, 85, 89, 90, 91, 94, 159, 169, 172, 186, 187, 188, 189, 190, 194, 195, 196, 280, 288], "lead": [54, 104, 112, 123, 131, 159, 231, 234, 235, 267, 302, 308, 354, 357], "casualti": [54, 159], "034": [54, 55, 159, 160], "035": [54, 159], "036": [54, 159], "037": [54, 159], "038": [54, 159, 418], "039": [54, 159], "040": [54, 159], "temper": [54, 55, 159, 160, 232], "seam": [54, 159], "054": [54, 55, 159, 160], "polish": [54, 159], "heat": [54, 76, 159, 181, 239], "strengthen": [54, 159], "hs": [54, 159, 230, 239], "symmetr": [54, 55, 159, 160], "060": [54, 159], "201": [54, 159], "vhbtm": [54, 159], "sgttm": [54, 159], "did": [54, 55, 159, 160, 246, 263, 328], "intent": [54, 55, 159, 160, 239, 248, 254, 263, 286], "none": [55, 160, 238, 239, 240, 243, 254, 255, 258, 280, 281, 300, 301, 311, 317, 319, 320, 322, 338, 341, 344, 347, 406], "planar": [55, 160, 292], "corner": [55, 160, 239, 254, 280, 281, 297, 306, 308, 309, 344, 357], "cond": [55, 160], "combin": [55, 81, 82, 83, 84, 85, 89, 90, 91, 114, 133, 160, 186, 187, 188, 189, 190, 194, 195, 196, 231, 233, 242, 248, 252, 253, 257, 263, 266, 281, 293, 316, 331, 334, 354, 357], "short": [55, 104, 105, 106, 107, 108, 109, 110, 111, 112, 113, 114, 115, 116, 117, 118, 119, 160, 206, 238, 239, 240, 306, 309, 418], "crack": [55, 106, 116, 125, 135, 160, 280, 281], "055": [55, 160], "056": [55, 160], "82": [55, 160, 239, 242], "storefront": [56, 161], "tile": [57, 66, 67, 69, 87, 162, 171, 172, 174, 192, 280, 281], "secur": [57, 94, 162, 306, 309], "ubc94": [57, 162], "squar": [57, 67, 118, 119, 137, 138, 162, 172, 223, 229, 231, 235, 239, 253, 266, 281, 284, 288, 293, 301, 317, 332, 333, 347, 349, 354, 358, 406], "ubc": [57, 104, 105, 106, 107, 108, 109, 110, 111, 112, 113, 114, 115, 116, 117, 118, 119, 121, 123, 124, 125, 126, 127, 128, 129, 130, 131, 132, 133, 134, 135, 136, 137, 138, 162], "clai": [57, 162], "unsecur": [57, 94, 162], "unreinforc": [58, 59, 120, 139, 163, 164], "industri": [58, 70, 120, 139, 163, 175, 206, 207, 208, 209, 238, 239, 246, 248, 255, 263, 279, 286], "firebox": [58, 163], "veneer": [58, 118, 122, 137, 163, 208, 280], "ornament": [58, 163], "elev": [58, 74, 121, 122, 163, 179, 207, 208, 222, 239, 240, 241, 242, 246, 254, 256, 280, 281], "rebuild": [58, 163], "restor": [58, 163, 361], "jurisdict": [58, 163], "prohibit": [58, 163, 289, 334], "portion": [58, 163, 239, 254, 280, 301, 349], "metal": [58, 62, 83, 94, 107, 108, 111, 114, 117, 120, 126, 127, 130, 133, 136, 139, 163, 167, 188, 206, 207, 208, 209, 239], "flue": [58, 163], "chase": [58, 163], "fireplac": [58, 163], "toppl": [58, 163, 280, 281], "adjac": [58, 163, 239, 241, 256, 357], "unbrac": [59, 87, 164, 192], "approxim": [59, 64, 104, 105, 106, 107, 108, 109, 110, 111, 112, 113, 114, 115, 116, 117, 118, 119, 121, 123, 124, 125, 126, 127, 128, 129, 130, 131, 132, 133, 134, 135, 136, 137, 138, 164, 169, 206, 231, 232, 233, 238, 239, 245, 246, 248, 260, 263, 280, 283, 286, 287, 288, 297, 300, 301, 316, 318, 321, 332, 333, 334, 335, 346, 349, 357], "3ft": [59, 164], "10ft": [59, 164], "segment": [59, 75, 76, 77, 78, 79, 83, 87, 114, 133, 144, 164, 180, 181, 182, 183, 184, 188, 192, 214, 230, 239, 254], "cover": [60, 67, 107, 118, 126, 137, 142, 165, 172, 222, 231, 239, 240, 241, 242, 246, 254, 255, 256, 263, 289, 294, 295, 300, 347, 354, 357, 418], "chimnei": [60, 118, 137, 165, 222, 280, 281], "parapet": [60, 121, 165, 207], "super": [61, 166, 322], "enclosur": [61, 166], "slip": [62, 64, 66, 94, 167, 169, 171, 280, 296, 354], "001d": [62, 66, 67, 69, 83, 167, 171, 172, 174, 188], "friction": [62, 66, 94, 167, 171, 233], "partit": [63, 66, 117, 118, 122, 136, 137, 168, 171, 208, 233, 248, 280, 281], "prefabr": [64, 107, 114, 126, 133, 169], "tread": [64, 169, 315], "land": [64, 169, 238, 239, 240, 241, 246, 254, 255, 256, 263, 279, 281], "flexibl": [64, 77, 112, 131, 169, 182, 231, 232, 248, 300, 316], "prefab": [64, 169], "stringer": [64, 169], "fill": [64, 110, 117, 129, 136, 169, 231, 238, 292, 294, 298, 321, 349, 354], "pan": [64, 169], "rigid": [64, 114, 119, 133, 138, 169], "insuffici": [64, 169], "establish": [64, 169, 222, 239, 240, 241, 246, 254, 256, 263, 335, 357], "mka": [64, 169], "cast": [64, 77, 109, 111, 117, 120, 128, 130, 136, 139, 169, 182], "kind": [64, 169, 232, 340, 345, 350], "021d": [64, 81, 83, 90, 169, 186, 188, 195], "hybrid": [64, 169, 240, 263], "rigidli": [64, 169], "wallpap": [66, 171], "ceram": [66, 171], "002d": [66, 83, 171, 188], "marbl": [66, 171], "003d": [66, 69, 171, 174], "pipe": [67, 75, 76, 77, 78, 79, 87, 121, 122, 172, 180, 181, 182, 183, 184, 192, 207, 208, 280, 281], "offic": [67, 94, 172, 206, 207, 208, 209, 238, 239, 240, 246, 279], "ceil": [67, 70, 71, 83, 87, 112, 131, 172, 175, 176, 188, 192, 280, 300, 302], "lowest": [67, 172, 239, 240, 241, 242, 254, 256], "carpet": [67, 94, 172], "vinyl": [67, 172, 241, 256], "humid": [67, 172], "laboratori": [67, 172, 336, 357], "001e": [67, 172], "hospit": [67, 172, 206, 207, 208, 209, 239, 263], "001f": [67, 172], "001g": [67, 172], "school": [67, 172, 206, 207, 208, 209, 238, 239, 279], "001h": [67, 172], "001i": [67, 172], "apart": [67, 172, 206, 207, 208, 209, 231, 238, 239, 240, 246], "001j": [67, 172], "001k": 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124, 125, 128, 129, 131, 132, 133, 134, 135, 137, 138, 173, 233, 239, 242, 253, 254, 257, 258, 263, 265, 266, 267, 280, 295, 302, 303, 341, 357, 418], "heavier": [68, 173, 246], "suspend": [69, 70, 83, 174, 175, 188, 280], "sdc": [69, 75, 76, 77, 78, 79, 83, 87, 174, 180, 181, 182, 183, 184, 188, 192], "250": [69, 81, 89, 91, 174, 186, 194, 196, 254, 357], "vert": [69, 174], "lai": [69, 87, 174, 192], "acoust": [69, 174], "hang": [69, 70, 174, 175, 280], "fixtur": [69, 70, 121, 174, 175, 207, 280], "600": [69, 174, 239, 246, 250], "ledger": [69, 174], "overs": [69, 174], "hole": [69, 174], "around": [69, 116, 135, 174, 255, 267, 287, 297, 301, 316, 334, 347, 357], "004a": [69, 174], "inspect": [69, 174, 239, 267, 280, 281, 308, 317, 354, 358], "oshpd": [69, 75, 76, 77, 78, 79, 83, 87, 174, 180, 181, 182, 183, 184, 188, 192, 341], "004b": [69, 174], "004c": [69, 174], "004d": [69, 174], "hung": [70, 175], "rod": [70, 114, 119, 133, 138, 175], "cabl": [70, 175], "gymnasium": [70, 175], 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84, 85, 89, 90, 91, 186, 187, 188, 189, 190, 194, 195, 196, 239, 241, 256], "013d": [81, 82, 84, 89, 90, 186, 187, 189, 194, 195], "013e": [81, 82, 84, 89, 186, 187, 189, 194], "013f": [81, 82, 84, 89, 186, 187, 189, 194], "013g": [81, 82, 84, 89, 186, 187, 189, 194], "013h": [81, 82, 84, 89, 186, 187, 189, 194], "013i": [81, 82, 84, 89, 186, 187, 189, 194], "013j": [81, 82, 84, 89, 186, 187, 189, 194], "013k": [81, 82, 84, 89, 186, 187, 189, 194], "013l": [81, 82, 84, 89, 186, 187, 189, 194], "tower": [81, 121, 186, 207], "022d": [81, 83, 186, 188], "022e": [81, 186], "022f": [81, 186], "022g": [81, 186], "022h": [81, 186], "022i": [81, 186], "022j": [81, 186], "022k": [81, 186], "022l": [81, 186], "023d": [81, 90, 186, 195], "023e": [81, 90, 186, 195], "023f": [81, 90, 186, 195], "023g": [81, 90, 186, 195], "023h": [81, 90, 186, 195], "023i": [81, 90, 186, 195], "023j": [81, 90, 186, 195], "023k": [81, 90, 186, 195], "023l": [81, 90, 186, 195], "compressor": [82, 187, 308], "medic": 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242], "latch": 94, "velcro": 94, "sticki": 94, "stuff": 94, "coeffici": [94, 231, 233, 287, 288, 293, 319, 337, 347, 357], "020": 94, "home": [94, 120, 139, 206, 207, 208, 209, 238, 239, 242, 246, 247, 248, 252, 254, 257, 262, 263, 286, 306, 309], "entertain": [94, 206, 207, 208, 209, 240], "electron": 94, "mount": [94, 280], "stereo": 94, "bookcas": 94, "deep": [94, 101, 102, 284], "104a": 94, "104b": 94, "105a": 94, "105b": 94, "106a": 94, "81": [94, 235, 242], "106b": 94, "drawer": 94, "114a": 94, "114b": 94, "124a": 94, "124b": 94, "125a": 94, "125b": 94, "movabl": [95, 200], "pallet": [97, 202], "restock": [97, 202], "furnish": [97, 100, 202, 205], "femap": [100, 205], "58_fragilitydatabase_v3": [100, 205], "xl": [100, 205], "publish": [100, 205, 222, 262, 263], "methodolog": [100, 145, 205, 215, 222, 228, 234, 242, 245, 246, 248, 257, 260, 263, 267, 280, 283, 286, 315], "few": [100, 205, 231, 232, 238, 280, 281, 302, 303, 306, 309, 321, 343, 345, 347, 406], "obviou": [100, 205], "typo": [100, 205], "adjust": [100, 205, 230, 240, 241, 246, 256, 348, 357], "captur": [100, 205, 222, 230, 231, 232, 233, 239, 240, 245, 246, 248, 254, 255, 260, 262, 263, 283, 284, 334, 347, 357], "changelog": [100, 205], "db_damageandloss": [100, 205, 316], "blob": [100, 205], "data_sourc": [100, 205], "fema_p58": [100, 205], "simultan": [100, 205, 231, 253, 266, 288, 331], "uniformat": [100, 205], "ii": [100, 205, 240, 255, 263, 284, 347], "nistir": [100, 205], "6389": [100, 205], "demolit": [100, 205], "foundat": [101, 102, 107, 126, 218, 239, 240, 241, 242, 254, 256, 280, 285], "curv": [101, 102, 104, 105, 106, 107, 108, 109, 110, 111, 112, 113, 114, 115, 116, 117, 118, 119, 206, 231, 233, 234, 242, 265, 287, 301, 341, 344, 357], "distinguish": [101, 102, 239], "settlement": [101, 103], "essenc": [101, 102], "undamag": [101, 102, 267], "slight": [101, 102, 115, 134, 235, 280, 281], "tacitli": [101, 102], "pgd": [101, 102, 230], "attempt": [101, 102, 233], "critic": [101, 102, 248, 254, 263, 267, 286, 357], "pile": [101, 102, 242], "much": [101, 102, 231, 234, 243, 245, 246, 252, 260, 263, 267, 357], "settl": [101, 102], "shallow": [101, 102], "spread": [102, 103, 242, 335], "hc": [104, 105, 107, 108, 109, 110, 111, 112, 113, 114, 115, 118, 119, 121, 123, 124, 126, 127, 128, 129, 130, 131, 132, 133, 134, 137, 138], "facil": [104, 105, 106, 107, 108, 109, 110, 111, 112, 113, 114, 115, 116, 117, 118, 119, 140, 210, 248, 263, 286, 289, 299, 318], "effici": [104, 105, 106, 107, 108, 109, 110, 111, 112, 113, 114, 115, 116, 117, 118, 119, 133, 206, 222, 223, 224, 225, 226, 228, 229, 231, 234, 238, 239, 240, 242, 243, 246, 257, 258, 283, 293, 297, 302, 316, 319, 321, 325, 334, 335, 336, 344, 345, 348, 357], "transport": [104, 105, 106, 107, 108, 109, 110, 111, 112, 113, 114, 115, 116, 117, 118, 119, 145, 206, 215, 222, 228, 245, 260, 279, 293, 316, 320, 321, 323, 357], "shape": [104, 105, 106, 107, 108, 109, 110, 111, 112, 113, 114, 115, 116, 117, 118, 119, 206, 222, 231, 234, 239, 240, 242, 254, 255, 257, 265, 325, 326, 340, 341], "relat": [104, 105, 106, 107, 108, 109, 110, 111, 112, 113, 114, 115, 116, 117, 118, 119, 206, 224, 233, 235, 240, 242, 247, 248, 252, 255, 262, 263, 267, 281, 293, 321, 328, 335, 418], "veri": [104, 105, 106, 107, 108, 109, 110, 111, 112, 113, 114, 115, 116, 117, 118, 119, 127, 131, 206, 231, 233, 235, 239, 254, 258, 281, 319, 357], "influenc": [104, 105, 106, 107, 108, 109, 110, 111, 112, 113, 114, 115, 116, 117, 118, 119, 206, 231, 240, 249, 252, 253, 258, 265, 266, 281, 288, 292, 293, 296, 349], "wu": [104, 105, 106, 107, 108, 109, 110, 111, 112, 113, 114, 115, 116, 117, 118, 119, 206, 246, 247, 320, 322], "ceu": [104, 105, 106, 107, 108, 109, 110, 111, 112, 113, 114, 115, 116, 117, 118, 119, 206], "attenu": [104, 105, 106, 107, 108, 109, 110, 111, 112, 113, 114, 115, 116, 117, 118, 119, 206, 235, 418], "effect": [104, 105, 106, 107, 108, 109, 110, 111, 112, 113, 114, 115, 116, 117, 118, 119, 125, 142, 143, 206, 222, 224, 225, 226, 231, 232, 233, 234, 238, 245, 246, 248, 251, 252, 260, 267, 284, 286, 292, 296, 302, 317, 334, 336, 346, 357, 418], "formula": [104, 105, 106, 107, 108, 109, 110, 111, 112, 113, 114, 115, 116, 117, 118, 119, 206, 239], "m7": [104, 105, 106, 107, 108, 109, 110, 111, 112, 113, 114, 115, 116, 117, 118, 119, 206, 230, 238], "varieti": [104, 121, 123, 207, 235, 248, 286, 300], "proport": [104, 123, 231, 233, 239, 281, 284, 296, 337], "brittl": [104, 108, 123, 127], "modern": [104, 115, 123, 134, 143, 228, 240, 263], "zone": [104, 105, 106, 107, 108, 109, 110, 111, 112, 113, 114, 115, 116, 117, 118, 119, 121, 123, 124, 125, 126, 127, 128, 129, 130, 131, 132, 133, 134, 135, 136, 137, 138, 239, 240, 241, 242, 255, 256, 263, 281], "nehrp": [104, 105, 106, 107, 108, 109, 110, 111, 112, 113, 114, 115, 116, 117, 118, 119, 121, 123, 124, 125, 126, 127, 128, 129, 130, 131, 132, 133, 134, 135, 136, 137, 138, 231, 354], "lc": [104, 105, 106, 107, 108, 109, 110, 111, 112, 113, 114, 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      Software and Supporting Files