Physics‐Informed Graph Neural Networks to Reconstruct Local Fields Considering Finite Strain Hyperelasticity

We propose a physics-informed machine learning framework called P-DivGNN to reconstruct local stress fields at the micro-scale, in the context of multi-scale simulation, given a periodic micro-structure mesh and mean, macro-scale, stress values. This method is based on representing a periodic micro-