FNO battery module cooling example #7
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| ## Requirements | ||
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| Requires | ||
| - [MATLAB](https://www.mathworks.com/products/matlab.html) (R2025a or newer) |
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Could this run in earlier releases? What 25a features are requied?
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OK the example states we're using 25a functionality to handle the geometry.
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Yeah the helper function in this example should work in some older releases than 25a. I'm not sure what the most recent Deep Learning Toolbox code I've used is, maybe the networkLayer from 24a, though it isn't strictly necessary. The PDE Toolbox introduced the femodel in 23a, but there was ThermalModel before that which might suffice for this example. So potentially we could write a version of the example that's supported quite a few releases back.
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the old APIs like ThermalModel will eventually be removed, so I would strongly suggest staying with femodel (23a as Ben mentioned)
battery-module-cooling-analysis-with-fourier-neural-operator/spectralConvolution3dLayer.m
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battery-module-cooling-analysis-with-fourier-neural-operator/spectralConvolution3dLayer.m
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battery-module-cooling-analysis-with-fourier-neural-operator/createBatteryModuleGeometry.m
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…d files, add images in the resources sub-directory
I've added a bunch more detail and a few images now. |
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Example looks fantastic, README is clear, and I love the thoughtful discussion at the end of the example about other methods/approaches.
One tiny suggestion for consideration: Maybe rename the sections "Specify material and physical properties and solve" to "Generate simulation data for training" and "Interpolate inputs and targets onto a grid" to "Prepare data for training", to capture the big ideas of those sections as well as to make it resonate more with a deep learning workflow.
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