A convex neural network is trained inside an elastoplastic stress integration loop using force equilibrium losses to identify yield functions from full-field displacement data.
International Journal of Solids and Structures 206, 314–321 (2020)
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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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A new open source framework for multiscale modeling of fibrous materials on heterogeneous supercomputers
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.