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A complement to neural networks for anisotropic inelasticity at finite strains
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In
Computer methods in applied mechanics and engineering 450, Seiten/Artikel-Nr.:118612
2026 & 2025
Available online 8 December 2025, Version of Record 8 December 2025
Online
DOI: 10.1016/j.cma.2025.118612
DOI: 10.18154/RWTH-2026-04563
URL: https://publications.rwth-aachen.de/record/1034221/files/1034221.pdf
Projekte
- GSO090 - Automated model discovery of inelastic materials in a multiphysical context using Machine Learning (EXS-TvK-GSO090) (EXS-TvK-GSO090)
- ERS TvK (EXS) - Theodore von Kármán Fellowships (EXS) (EXS-TvK) (EXS-TvK)
- EXS - Excellence Strategy (EXS) (EXS)
Thematische Einordnung (Klassifikation)
DDC: 004
OpenAccess: 
PDF
Dokumenttyp
Journal Article
Format
online, print
Herkunft
Externe Einrichtung
Sprache
English
Anmerkung
Peer reviewed article
Externe Identnummern
SCOPUS: SCOPUS:2-s2.0-105023952349
WOS Core Collection: WOS:001638043300001
Interne Identnummern
RWTH-2026-04563
Datensatz-ID: 1034221
Beteiligte Länder
Germany, USA
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