2 papers
cs.CE2026
Non-linear mechanical field reconstruction coupling recurrent neural networks with physics-informed graph neural networks
Manuel Ricardo Guevara Garban, Yves Chemisky, Étienne Prulière +3
Reconstructing local stress fields in heterogeneous microstructures under non-linear, history-dependent loading remains a major computational bottleneck in multi-scale simulations.…
cs.LG2025
Physics-Informed Graph Neural Networks to Reconstruct Local Fields Considering Finite Strain Hyperelasticity
Manuel Ricardo Guevara Garban, Yves Chemisky, Étienne Prulière +1
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 per…