Karl A. Kalina | DeepAI

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∙ 08/30/2023

Neural network-based multiscale modeling of finite strain magneto-elasticity with relaxed convexity criteria

We present a framework for the multiscale modeling of finite strain magn...

0 Karl A. Kalina, et al. ∙

∙ 03/06/2023

A comparative study on different neural network architectures to model inelasticity

The mathematical formulation of constitutive models to describe the path...

0 Max Rosenkranz, et al. ∙

∙ 02/05/2023

Neural networks meet hyperelasticity: A guide to enforcing physics

In the present work, a hyperelastic constitutive model based on neural n...

0 Lennart Linden, et al. ∙

∙ 07/03/2022

FE^ANN - An efficient data-driven multiscale approach based on physics-constrained neural networks and automated data mining

Herein, we present a new data-driven multiscale framework called FE^ANN ...

0 Karl A. Kalina, et al. ∙

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