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cs.CE2026
Modeling isotropic polyconvex hyperelasticity by neural networks -- sufficient and necessary criteria for compressible and incompressible materials
Gian-Luca Geuken, Patrick Kurzeja, David Wiedemann +3
This work investigates different sufficient and necessary criteria for hyperelastic, isotropic polyconvex material models, focusing on neural network implementations for compressib…
cs.CE2024★ 15 cited
Data-driven methods for computational mechanics: A fair comparison between neural networks based and model-free approaches
Martin Zlatić, Felipe Rocha, Laurent Stainier +1
We present a comparison between two approaches to modelling hyperelastic material behaviour using data. The first approach is a novel approach based on Data-driven Computational Me…