A coupled LSTM-GNN model reconstructs local elasto-plastic stress fields from macroscopic loading paths on a plate-with-hole microstructure, achieving 1000x speedup and mesh transferability with 1.9% error.
Computer Methods in Applied Mechanics and Engineering 192(28-30), 3233–3244 (2003)
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MuMFiM is a new open-source two-scale modeling framework achieving 1000x GPU microscale speedup and near-optimal strong/weak scaling to 128 nodes on heterogeneous hardware, demonstrated on a human spine ligament.
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Non-linear mechanical field reconstruction coupling recurrent neural networks with physics-informed graph neural networks
A coupled LSTM-GNN model reconstructs local elasto-plastic stress fields from macroscopic loading paths on a plate-with-hole microstructure, achieving 1000x speedup and mesh transferability with 1.9% error.