Faster Thermal Profiling of a Lunar Rover with Machine Learning Adapted Finite Difference Model

In three linesA physics-informed machine learning (PIML) framework for thermal modeling of a lunar rover. An adaptive neural network determines 3D finite-difference meshing based on thermal loads, improving accuracy by 50% vs coarse-mesh physics models and 39% vs pure ANN, while being 3x faster than high-fidelity simulations.

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