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A mixed formulation for physics-informed neural networks as a potential solver for engineering problems in heterogeneous domains: Comparison with finite element method2022 Computer Methods in Applied Mechanics and Engineering article Physics and Astronomy Model Reduction and Neural Networks Open access
Shahed Rezaei, Ahmad Moeineddin, Bai‐Xiang Xu, Stefanie Reese
12citations -
An approach to encode divergence-free stress fields in neural approximations based on stress potentials2026 Computer Methods in Applied Mechanics and Engineering article Physics and Astronomy Model Reduction and Neural Networks Open access
Mohammad Sarkari Khorrami, Pawan Goyal, Soroush Motahari, David Oexle, Jaber Rezaei Mianroodi, Bob Svendsen, +2 more
0citations -
Mixed formulation of physics‐informed neural networks for thermo‐mechanically coupled systems and heterogeneous domains2023 International Journal for Numerical Methods in Engineering article Physics and Astronomy Model Reduction and Neural Networks Open access
Ahmad Moeineddin, Michael Kaliske, Stefanie Reese, Shahed Rezaei
98citations -
Introducing a microstructure-embedded autoencoder approach for reconstructing high-resolution solution field data from a reduced parametric space2024 Computational Mechanics article Physics and Astronomy Model Reduction and Neural Networks Open access
Rasoul Najafi Koopas, Shahed Rezaei, Natalie Rauter, Richard Ostwald, Rolf Lammering
5citations
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