fix wsl links (#5251)

* fix wsl links

* forgot to save file

* ai 3d fix

---------

Co-authored-by: Alec Bills <[email protected]>

Author: valentinsulzer

docs/source/user_guide/installation/install-from-source.rst

@@ -16,7 +16,7 @@ Prerequisites
 ---------------
 
 The following instructions are valid for both GNU/Linux distributions and MacOS.
-If you are running Windows, consider using the `Windows Subsystem for Linux (WSL) <https://docs.microsoft.com/en-us/windows/wsl/install-win10>`_.
+If you are running Windows, consider using the `Windows Subsystem for Linux (WSL) <https://learn.microsoft.com/en-us/windows/wsl/install-win10>`_.
 
 To obtain the PyBaMM source code, clone the GitHub repository
 

docs/source/user_guide/installation/windows-wsl.rst

@@ -6,7 +6,7 @@ To make it easier to install PyBaMM, we recommend using the Windows Subsystem fo
 Install WSL
 -----------
 
-Install Ubuntu 22.04 or 20.04 LTS as a distribution for WSL following `Microsoft's guide to install WSL <https://docs.microsoft.com/en-us/windows/wsl/install-win10>`__. For a seamless development environment, refer to `this guide <https://docs.microsoft.com/en-us/windows/wsl/setup/environment>`__.
+Install Ubuntu 22.04 or 20.04 LTS as a distribution for WSL following `Microsoft's guide to install WSL <https://learn.microsoft.com/en-us/windows/wsl/install-win10>`__.
 
 Install PyBaMM
 --------------

src/pybamm/models/full_battery_models/lithium_ion/basic_spm_with_3d_thermal.py

@@ -287,8 +287,14 @@ def set_thermal_bcs(self, T):
             )  # pragma: no cover
 
         self.boundary_conditions[T] = {}
-        lambda_eff = self.param.lambda_eff(T)
 
         for face, h_coeff in face_params.items():
-            q_face = -h_coeff * (T - T_amb)
-            self.boundary_conditions[T][face] = (q_face / lambda_eff, "Neumann")
+            # Evaluate T and lambda_eff at the boundary
+            T_boundary = pybamm.boundary_value(T, face)
+            lambda_eff_boundary = pybamm.boundary_value(self.param.lambda_eff(T), face)
+            # T_amb is already evaluated at the boundary coordinates
+            q_face = -h_coeff * (T_boundary - T_amb)
+            self.boundary_conditions[T][face] = (
+                q_face / lambda_eff_boundary,
+                "Neumann",
+            )