Learning finite element convergence with the multi-fidelity graph neural network

DOI10.1016/j.cma.2022.115120OpenAlexW4281784690WikidataQ114952520 ScholiaQ114952520MaRDI QIDQ2145122

Nolan Black, Ahmad R. Najafi

Publication date: 17 June 2022

Published in: Computer Methods in Applied Mechanics and Engineering (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1016/j.cma.2022.115120

zbMATH Keywords

machine learningsurrogate modelinggraph neural networksmulti-fidelity analysis

Mathematics Subject Classification ID

Artificial neural networks and deep learning (68T07) Finite element, Rayleigh-Ritz and Galerkin methods for boundary value problems involving PDEs (65N30)

Uses Software

• SciPy
• FEAPpv
• Python
• Adam
• DiscretizationNet
• ParaFEM

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