Physics-guided neural networks in the stationary heat equation: calculating solutions, disentangling equations of state and revealing the microstructure of materials

Abstract

This study combines machine learning algorithms with physical principles to solve the stationary heat equation, improving the predictive ability of the models with respect to classical neural networks, and providing explanatory power, discovering non-linear state models and revealing the heterogeneous microstructure of a material.