DeepPhysics: A physics aware deep learning framework for real‐time simulation

DOI10.1002/NME.6943arXiv2109.09491MaRDI QIDQ6129672

Unnamed Author, Ryadh Haferssas, Stéphane Cotin

Publication date: 17 April 2024

Published in: International Journal for Numerical Methods in Engineering (Search for Journal in Brave)

Full work available at URL: https://arxiv.org/abs/2109.09491

zbMATH Keywords

finite element methodneural networkNewton-Raphsonreal-timedeep learningphysics informed neural network

Mathematics Subject Classification ID

Multigrid methods; domain decomposition for boundary value problems involving PDEs (65N55) Artificial neural networks and deep learning (68T07) Nonlinear elasticity (74B20) Finite element, Rayleigh-Ritz and Galerkin methods for boundary value problems involving PDEs (65N30)

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