The EE-UQ
desktop application is a user-facing portal for cutting-edge engineering workflows targeting earthquake demands on structures. It is a free, open-source, graphical software for simulating a structures's response with uncertainty quantification (UQ) during seismic hazard loading. The application's interchangeable workflow allows you to swap between popular uncertainty quantification methods (e.g. Forward, Sensitivity, Reliability), upgrading your previously deterministic models to probabilistic analysis. Modular design lets you drop-in your own building models (SIM), event types (EVT), nonlinear structural analysis (FEM), engineering demand parameters (EDP), and more.
Get ground motions that fit your workflow:
- Stochastic generation of acceleration time histories from earthquake rupture characteristics.
- Select records from the PEER NGA West 2 or a user-sepecified ground-motion database to match a target spectrum or to fill an intensity-measure space.
- Simulate free-field shaking based on specified bedrock motions and soil column information using OpenSees-based site-response analysis.
- Incorporate physics-based M9 simulations.
- Provide your own ground motion time histories.
Multiple ways to create structural models that characterize your design:
- Automatic generation of an idealized Opensees shear column model from basic building information.
- Automatic generation of a steel or reinforced concrete OpenSees frame model from detailed design.
- User-specified OpenSees model in Tcl or Python format.
- User-specified Python script that prepares a structural model and performs the response simulation.
- Import a user-specified structural-response surrogate model.
- A multi-model approach, which allows you to specify multiple combinations of the above options.
- Multi-fidelity Monte Carlo (MFMC) routines for accurate and expedient results by using both high and low fidelity models.
Robust catalogue of drop-in uncertainty quantification:
- Forward propagation: Define a set of random input parameters and perform Monte Carlo simulations to obtain a corresponding sample of output parameters.
- Sensitivity analysis: Measure the influence of variability in each input on the uncertainty of outputs.
- Reliability analysis: Algorithms to estimate the probability of exceeding a failure threshold.
- Surrogate models: Generate training data and develop surrogate models using Gaussian Process (GP) and Probabilistic Learning on Manifolds techniques (PLoM).
- Download Application
- Step-by-Step Examples
- Documentation & Guides
- Overview Web-Page
- Forum & Feature Requests
If you use EE-UQ
in your own work, please cite our software as:
@software{McKennaZhongGardnerZsarnoczayYiSatishWangElhaddad2024EEUQ,
author = {Frank McKenna and
Kuanshi Zhong and
Michael Gardner and
Adam Zsarnoczay and
Sang-ri Yi and
Aakash Bangalore Satish and
Charles Wang and
Wael Elhaddad},
title = {NHERI-SimCenter/EE-UQ: Version 3.5.0},
month = apr,
year = 2024,
publisher = {Zenodo},
version = {v3.5.0},
doi = {10.5281/zenodo.10902075},
url = {https://doi.org/10.5281/zenodo.10902075}
}
and include the NHERI SimCenter's workflow architecture using:
@Article{Deierlein2020,
author={Deierlein, Gregory G. and McKenna, Frank and ZsarnĂłczay, Adam and Kijewski-Correa, Tracy and Kareem, Ahsan and Elhaddad, Wael and Lowes, Laura and Schoettler, Matthew J. and Govindjee, Sanjay},
title={A Cloud-Enabled Application Framework for Simulating Regional-Scale Impacts of Natural Hazards on the Built Environment},
journal={Frontiers in Built Environment},
volume={6},
year={2020},
url={https://www.frontiersin.org/articles/10.3389/fbuil.2020.558706},
doi={10.3389/fbuil.2020.558706},
issn={2297-3362},
}
The challenges of natural hazards engineering are addressed by the NHERI SimCenter through a suite of applications that provide cutting-edge tools for researchers, practitioners, and stakeholders. The applications are designed to work together to provide a comprehensive solution for natural hazards engineering. A puzzle-piece diagram of the SimCenter ecosystem is shown below:
In reality, this is a software workflow representation of the PEER Performance-Based Earthquake Engineering (PBEE) framework that has been extended to include other natural hazards:
EE-UQ
is just one part of the NHERI SimCenter ecosystem that provides cutting-edge open-source tools for natural hazards engineering. Tools like quoFEM
, EE-UQ
, WE-UQ
, HydroUQ
, PBE
, and R2D
work together to provide a comprehensive solution for natural hazards engineering. The SimCenter ecosytem forms a modular hierarchy that allows users to pick and choose the tools they need for their specific research or engineering problem.
While R2D
is the top-level application that provides a regional resilience assessment, EE-UQ
, WE-UQ
, and HydroUQ
provide uncertainty quantified simulations for earthquake, wind, and water-borne natural hazards, respectively. quoFEM
is the backend UQ functionality they use.
Additional tools, such as BRAILS
and TInF
, have special use-cases including AI-augmentation of building stock and creation of turbulent wind inflow for OpenFOAM CFD simulations.
All applications are free, open-source, and available for download on the DesignSafe-CI website. See the table below for more information on each application:
The EE-UQ
application can be downloaded, installed, built, and launched on Windows, Mac, and Linux operating systems. With a free DesignSafe account, you can run EE-UQ
simulations remotely on powerful supercomputers including Frontera
and Stampede3
.
The EE-UQ
desktop application is available for download on Windows and Mac operating systems from the DesignSafe-CI website at the EE-UQ Download Link.
The EE-UQ
installation instructions are available in the EE-UQ Installation Guide.
The EE-UQ
application can be built from source code on Windows, Mac, and Linux operating systems. The source code is available in this repository.
Clone the repository using the following command if the Github CLI is installed on your system:
git clone https://github.com/NHERI-SimCenter/EE-UQ.git
Otherwise, you can clone the repository on this page by clicking on the green Code
button and then clicking on Download ZIP
. Extract the downloaded ZIP file to a location on your system.
Instructions on building the EE-UQ
application from downloaded source code are available in the EE-UQ How-To-Build Guide
The EE-UQ
application can be run by executing the EE_UQ
executable file. The instructions to run the EE-UQ
application are available in the EE-UQ Documentation
With a free DesignSafe account you can use the EE-UQ
desktop app to launch a remote job to run simulations on powerful supercomputers with ease.
Available systems are the Frontera
and Stampede3
supercomputers. Systems are located at the Texas Advanced Computing Center (TACC) and made available to you through NSF's NHERI DesignSafe-CI, the cyberinfrastructure provider for NHERI.
EE-UQ
is an open-source project developed for practitioners, researchers, students, and stakeholders by our team of experts at the NHERI SimCenter. We welcome contributions from the community to help improve the application and add new features.
Interested in contributing to the open-source EE-UQ
project? Find out how in the EE-UQ Documentation.
We encourage practitioners, researchers, and students to comment on what additional features or step-by-step examples they would like to see in EE-UQ
. If you want it, chances are many of your colleagues will also benefit from it. We appreciate all input from the earthquake engineering community during the active development of EE-UQ
.
Submit your requests on the SimCenter forum.
Message us on the SimCenter Message Board for any questions, feature requests, or issues.
Developer | Role | |
---|---|---|
Frank McKenna | [email protected] | |
Sang-ri Yi | [email protected] | |
Kuanshi Zhong | [email protected] | |
NHERI SimCenter | [email protected] |
Stay up-to-date with the latest news, updates, and releases with the NHERI Newsletter and the SimCenter Newsletter newsletters.
EE-UQ
is released as an open-source research application under a BSD 2-Clause License
This material is based upon work supported by the National Science Foundation under Grant No. 1612843 and No. 2131111. Any opinions, findings, conclusions or recommendations expressed in this material are those of the author(s) and do not necessarily reflect the views of the U.S. National Science Foundation.