Split the models into separate classes

.virtual_documents/docs/source/examples/notebooks/models/tortuosity_models.ipynb

@@ -0,0 +1,81 @@
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+import pybamm
+import numpy as np
+
+
+sols = []
+te_opts = pybamm.BatteryModelOptions({}).possible_options["transport efficiency"]
+parameter_values = pybamm.ParameterValues("Marquis2019")
+print(te_opts)
+
+
+parameter_values.search("porosity")
+
+
+parameter_values.search("Bruggeman")
+
+
+
+
+
+parameter_values.update({'Negative electrode tortuosity factor (electrolyte)': 0.3**(-0.5),
+                         'Positive electrode tortuosity factor (electrolyte)': 0.3**(-0.5),
+                         'Negative electrode tortuosity factor (electrode)': 0.7**(-0.5),
+                         'Positive electrode tortuosity factor (electrode)': 0.7**(-0.5),
+                         'Separator tortuosity factor (electrolyte)': 1.0}, check_already_exists=False)
+
+
+
+
+
+for t_label in te_opts:
+    model = pybamm.lithium_ion.DFN(options={'transport efficiency': t_label})  # Doyle-Fuller-Newman model
+    sim = pybamm.Simulation(model, parameter_values=parameter_values)
+    sols.append(sim.solve([0, 3600]))  # solve for 1 hour
+
+
+pybamm.dynamic_plot(sols,labels=te_opts)
+
+
+
+
+
+np.allclose(sols[0]["Terminal voltage [V]"].data, sols[4]["Terminal voltage [V]"].data)
+
+
+
+
+
+parameter_values.update({'Negative electrode tortuosity factor (electrolyte)': 4.0,
+                         'Positive electrode tortuosity factor (electrolyte)': 4.0,
+                         'Negative electrode tortuosity factor (electrode)': 3.0,
+                         'Positive electrode tortuosity factor (electrode)': 3.0,
+                         'Separator tortuosity factor (electrolyte)': 1.5}, check_already_exists=False)
+
+
+model = pybamm.lithium_ion.DFN(options={'transport efficiency': "tortuosity factor"})  # Doyle-Fuller-Newman model
+sim = pybamm.Simulation(model, parameter_values=parameter_values)
+sols.append(sim.solve([0, 3600]))
+
+
+pybamm.dynamic_plot(sols,labels=te_opts+["higher tortuosity factor"])
+
+
+
+
+
+pybamm.print_citations()

docs/source/api/models/submodels/transport_efficiency/bruggeman.rst

@@ -0,0 +1,5 @@
+Bruggeman Transport Efficiency Model
+====================================
+
+.. autoclass:: pybamm.transport_efficiency.Bruggeman
+    :members:

docs/source/api/models/submodels/transport_efficiency/cation_exchange_membrane.rst

@@ -0,0 +1,5 @@
+Cation-Exchange Membrane Transport Efficiency Model
+===================================================
+
+.. autoclass:: pybamm.transport_efficiency.CationExchangeMembrane
+    :members:

docs/source/api/models/submodels/transport_efficiency/heterogeneous_catalyst.rst

@@ -0,0 +1,5 @@
+Heterogeneous Catalyst Transport Efficiency Model
+=================================================
+
+.. autoclass:: pybamm.transport_efficiency.HeterogeneousCatalyst
+    :members:

docs/source/api/models/submodels/transport_efficiency/hyperbola_of_revolution.rst

@@ -0,0 +1,5 @@
+Hyperbola of Revolution Transport Efficiency Model
+==================================================
+
+.. autoclass:: pybamm.transport_efficiency.HyperbolaOfRevolution
+    :members:

docs/source/api/models/submodels/transport_efficiency/index.rst

@@ -5,4 +5,11 @@ transport_efficiency
   :maxdepth: 1
 
   base_transport_efficiency
-  general_transport_efficiency
+  bruggeman
+  cation_exchange_membrane
+  heterogeneous_catalyst
+  hyperbola_of_revolution
+  ordered_packing
+  overlapping_spheres
+  random_overlapping_cylinders
+  tortuosity_factor

docs/source/api/models/submodels/transport_efficiency/ordered_packing.rst

@@ -0,0 +1,5 @@
+Ordered Packing Transport Efficiency Model
+==========================================
+
+.. autoclass:: pybamm.transport_efficiency.OrderedPacking
+    :members:

docs/source/api/models/submodels/transport_efficiency/overlapping_spheres.rst

@@ -0,0 +1,5 @@
+Overlapping Spheres Transport Efficiency Model
+==============================================
+
+.. autoclass:: pybamm.transport_efficiency.OverlappingSpheres
+    :members:

docs/source/api/models/submodels/transport_efficiency/random_overlapping_cylinders.rst

@@ -0,0 +1,5 @@
+Random Overlapping Cylinders Transport Efficiency Model
+=======================================================
+
+.. autoclass:: pybamm.transport_efficiency.RandomOverlappingCylinders
+    :members:

docs/source/api/models/submodels/transport_efficiency/tortuosity_factor.rst

@@ -0,0 +1,5 @@
+Tortuosity Factor Transport Efficiency Model
+============================================
+
+.. autoclass:: pybamm.transport_efficiency.TortuosityFactor
+    :members:

docs/source/examples/notebooks/models/tortuosity_models.ipynb

@@ -166,7 +166,7 @@
     {
      "data": {
       "application/vnd.jupyter.widget-view+json": {
-       "model_id": "240db810f1e0430696821ee44192b2b1",
+       "model_id": "93cb2f124bd348a0bf99249423a14717",
        "version_major": 2,
        "version_minor": 0
       },
@@ -180,7 +180,7 @@
     {
      "data": {
       "text/plain": [
-       "<pybamm.plotting.quick_plot.QuickPlot at 0x1cdea7f35b0>"
+       "<pybamm.plotting.quick_plot.QuickPlot at 0x1b7f3ebec50>"
       ]
      },
      "execution_count": 7,
@@ -258,7 +258,7 @@
     {
      "data": {
       "application/vnd.jupyter.widget-view+json": {
-       "model_id": "cbdb93c1b74f434880b57dc8f8a0f3f6",
+       "model_id": "abd08396d3434395833472560a7114d1",
        "version_major": 2,
        "version_minor": 0
       },
@@ -272,7 +272,7 @@
     {
      "data": {
       "text/plain": [
-       "<pybamm.plotting.quick_plot.QuickPlot at 0x1cdf8c86950>"
+       "<pybamm.plotting.quick_plot.QuickPlot at 0x1b7f8659b10>"
       ]
      },
      "execution_count": 11,
@@ -338,7 +338,7 @@
    "name": "python",
    "nbconvert_exporter": "python",
    "pygments_lexer": "ipython3",
-   "version": "3.10.13"
+   "version": "3.11.5"
   }
  },
  "nbformat": 4,

pybamm/models/full_battery_models/base_battery_model.py

@@ -1153,16 +1153,94 @@ def set_external_circuit_submodel(self):
         self.submodels["external circuit"] = model
 
     def set_transport_efficiency_submodels(self):
-        self.submodels[
-            "electrolyte transport efficiency"
-        ] = pybamm.transport_efficiency.GeneralTransportEfficiency(
-            self.param, "Electrolyte", self.options
-        )
-        self.submodels[
-            "electrode transport efficiency"
-        ] = pybamm.transport_efficiency.GeneralTransportEfficiency(
-            self.param, "Electrode", self.options
-        )
+        if self.options["transport efficiency"] == "Bruggeman":
+            self.submodels[
+                "electrolyte transport efficiency"
+            ] = pybamm.transport_efficiency.Bruggeman(
+                self.param, "Electrolyte", self.options
+            )
+            self.submodels[
+                "electrode transport efficiency"
+            ] = pybamm.transport_efficiency.Bruggeman(
+                self.param, "Electrode", self.options
+            )
+        elif self.options["transport efficiency"] == "tortuosity factor":
+            self.submodels[
+                "electrolyte transport efficiency"
+            ] = pybamm.transport_efficiency.TortuosityFactor(
+                self.param, "Electrolyte", self.options
+            )
+            self.submodels[
+                "electrode transport efficiency"
+            ] = pybamm.transport_efficiency.TortuosityFactor(
+                self.param, "Electrode", self.options
+            )
+        elif self.options["transport efficiency"] == "ordered packing":
+            self.submodels[
+                "electrolyte transport efficiency"
+            ] = pybamm.transport_efficiency.OrderedPacking(
+                self.param, "Electrolyte", self.options
+            )
+            self.submodels[
+                "electrode transport efficiency"
+            ] = pybamm.transport_efficiency.OrderedPacking(
+                self.param, "Electrode", self.options
+            )
+        elif self.options["transport efficiency"] == "hyperbola of revolution":
+            self.submodels[
+                "electrolyte transport efficiency"
+            ] = pybamm.transport_efficiency.HyperbolaOfRevolution(
+                self.param, "Electrolyte", self.options
+            )
+            self.submodels[
+                "electrode transport efficiency"
+            ] = pybamm.transport_efficiency.HyperbolaOfRevolution(
+                self.param, "Electrode", self.options
+            )
+        elif self.options["transport efficiency"] == "overlapping spheres":
+            self.submodels[
+                "electrolyte transport efficiency"
+            ] = pybamm.transport_efficiency.OverlappingSpheres(
+                self.param, "Electrolyte", self.options
+            )
+            self.submodels[
+                "electrode transport efficiency"
+            ] = pybamm.transport_efficiency.OverlappingSpheres(
+                self.param, "Electrode", self.options
+            )
+        elif self.options["transport efficiency"] == "random overlapping cylinders":
+            self.submodels[
+                "electrolyte transport efficiency"
+            ] = pybamm.transport_efficiency.RandomOverlappingCylinders(
+                self.param, "Electrolyte", self.options
+            )
+            self.submodels[
+                "electrode transport efficiency"
+            ] = pybamm.transport_efficiency.RandomOverlappingCylinders(
+                self.param, "Electrode", self.options
+            )
+        elif self.options["transport efficiency"] == "heterogeneous catalyst":
+            self.submodels[
+                "electrolyte transport efficiency"
+            ] = pybamm.transport_efficiency.HeterogeneousCatalyst(
+                self.param, "Electrolyte", self.options
+            )
+            self.submodels[
+                "electrode transport efficiency"
+            ] = pybamm.transport_efficiency.HeterogeneousCatalyst(
+                self.param, "Electrode", self.options
+            )
+        elif self.options["transport efficiency"] == "cation-exchange membrane":
+            self.submodels[
+                "electrolyte transport efficiency"
+            ] = pybamm.transport_efficiency.CationExchangeMembrane(
+                self.param, "Electrolyte", self.options
+            )
+            self.submodels[
+                "electrode transport efficiency"
+            ] = pybamm.transport_efficiency.CationExchangeMembrane(
+                self.param, "Electrode", self.options
+            )
 
     def set_thermal_submodel(self):
         if self.options["thermal"] == "isothermal":

pybamm/models/submodels/transport_efficiency/__init__.py

@@ -1,2 +1,9 @@
 from .base_transport_efficiency import BaseModel
-from .general_transport_efficiency import GeneralTransportEfficiency
+from .bruggeman import Bruggeman
+from .cation_exchange_membrane import CationExchangeMembrane
+from .heterogeneous_catalyst import HeterogeneousCatalyst
+from .hyperbola_of_revolution import HyperbolaOfRevolution
+from .ordered_packing import OrderedPacking
+from .overlapping_spheres import OverlappingSpheres
+from .random_overlapping_cylinders import RandomOverlappingCylinders
+from .tortuosity_factor import TortuosityFactor

pybamm/models/submodels/transport_efficiency/bruggeman.py

@@ -0,0 +1,50 @@
+#
+# Class for Bruggeman transport_efficiency
+#
+import pybamm
+from .base_transport_efficiency import BaseModel
+
+
+class Bruggeman(BaseModel):
+    """Submodel for transport_efficiency
+
+    Parameters
+    ----------
+    param : parameter class
+        The parameters to use for this submodel
+    component : str
+        The material for the model ('electrolyte' or 'electrode').
+    options : dict, optional
+        A dictionary of options to be passed to the model.
+    """
+
+    def __init__(self, param, component, options=None):
+        super().__init__(param, component, options=options)
+
+    def get_coupled_variables(self, variables):
+        if self.component == "Electrolyte":
+            tor_dict = {}
+            for domain in self.options.whole_cell_domains:
+                Domain = domain.capitalize()
+                eps_k = variables[f"{Domain} porosity"]
+                pybamm.citations.register("bruggeman1935berechnung")
+                b_k = self.param.domain_params[domain.split()[0]].b_e
+                tor_k = eps_k**b_k
+                tor_dict[domain] = tor_k
+        elif self.component == "Electrode":
+            tor_dict = {}
+            for domain in self.options.whole_cell_domains:
+                if domain == "separator":
+                    tor_k = pybamm.FullBroadcast(0, "separator", "current collector")
+                else:
+                    Domain = domain.capitalize()
+                    phi_k = (1 - variables[f"{Domain} porosity"])
+                    pybamm.citations.register("bruggeman1935berechnung")
+                    b_k = self.param.domain_params[domain.split()[0]].b_s
+                    tor_k = phi_k**b_k
+                tor_dict[domain] = tor_k
+        variables.update(self._get_standard_transport_efficiency_variables(tor_dict))
+
+        return variables
+
+