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Transfer-learned Kolosov–Muskhelishvili informed neural networks for fracture mechanics

; ; ; ; ; ; ;

In
Theoretical and applied fracture mechanics 144, Seiten/Artikel-Nr.:105582

ImpressumAmsterdam : North-Holland

Umfang[1]-19

ISSN0167-8442

Online
DOI: 10.1016/j.tafmec.2026.105582

DOI: 10.18154/RWTH-2026-04141
URL: https://publications.rwth-aachen.de/record/1033427/files/1033427.pdf

Einrichtungen

  1. Lehrstuhl für Werkstoffmodellierung in der Umformtechnik (522520 ; 522510)
  2. Fachgruppe Materialwissenschaft und Werkstofftechnik (520000)


Thematische Einordnung (Klassifikation)
DDC: 670

OpenAccess:
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Dokumenttyp
Journal Article

Format
online, print

Sprache
English

Anmerkung
Peer reviewed article

Externe Identnummern
SCOPUS: SCOPUS:2-s2.0-105033917114
WOS Core Collection: WOS:001729497500001

Interne Identnummern
RWTH-2026-04141
Datensatz-ID: 1033427

Beteiligte Länder
Germany, Peoples R China

Lizenzstatus der Zeitschrift

 GO

Creative Commons Attribution-NonCommercial-NoDerivs CC BY-NC-ND 4.0 ; OpenAccess ; Clarivate Analytics Master Journal List ; Current Contents - Engineering, Computing and Technology ; Ebsco Academic Search ; Essential Science Indicators ; IF >= 5 ; JCR ; SCOPUS ; Science Citation Index Expanded ; Web of Science Core Collection
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Faculty of Georesources and Materials Engineering (Fac.5) > Division of Materials Science and Engineering
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520000
522520
 Record created 2026-04-13, last modified 2026-04-17
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