A physics-informed variational DeepONet for predicting crack path in quasi-brittle materials

Failure trajectories, probable failure zones, and damage indices are some of the key quantities of relevance in brittle fracture mechanics. High-fidelity numerical solvers that reliably estimate these relevant quantities exist but they are computationally demanding requiring a high resolution of the...

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Vydané v:	Computer methods in applied mechanics and engineering Ročník 391; číslo C; s. 114587
Hlavní autori:	Goswami, Somdatta, Yin, Minglang, Yu, Yue, Karniadakis, George Em
Médium:	Journal Article
Jazyk:	English
Vydavateľské údaje:	Amsterdam Elsevier B.V 01.03.2022 Elsevier BV Elsevier
Predmet:	Accuracy Brittle fracture Brittle materials Configurations Damage DeepONet Domains Fracture mechanics Interpolation Material properties Materials failure Phase-field Physics-informed learning Solvers Surrogate modeling Training Variational energy Variational energy Physics-informed learning Phase-field DeepONet Surrogate modeling Brittle fracture
ISSN:	0045-7825, 1879-2138
On-line prístup:	Získať plný text
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