Unsupervised learning of history-dependent constitutive material laws with thermodynamically-consistent neural networks in the modified Constitutive Relation Error framework-Reference-Cited by-同舟云学术

Unsupervised learning of history-dependent constitutive material laws with thermodynamically-consistent neural networks in the modified Constitutive Relation Error framework

Published:2024-05 Issue: Volume:425 Page:116967
ISSN:0045-7825
Container-title:Computer Methods in Applied Mechanics and Engineering
language:en
Short-container-title:Computer Methods in Applied Mechanics and Engineering

Author:

Benady Antoine^ORCID,Baranger Emmanuel^ORCID,Chamoin Ludovic

Funder

European Research Council

Horizon 2020

Horizon 2020 Framework Programme

Publisher

Elsevier BV

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