A comparative study on different neural network architectures to model inelasticity

DOI10.1002/nme.7319arXiv2303.03402MaRDI QIDQ6082629

Markus Kästner, Unnamed Author, Jörg Brummund, Karl A. Kalina

Publication date: 30 November 2023

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

Full work available at URL: https://arxiv.org/abs/2303.03402

zbMATH Keywords

neural networksviscoelasticityplasticityrecurrent neural networksthermodynamic consistencyconstitutive modelingenforcing physics

Mathematics Subject Classification ID

Plastic materials, materials of stress-rate and internal-variable type (74Cxx) Material properties given special treatment (74Exx) Homogenization, determination of effective properties in solid mechanics (74Qxx)

Related Items (1)

A monolithic hyper ROM \(\mathrm{FE}^2\) method with clustered training at finite deformations

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