A non-intrusive multifidelity method for the reduced order modeling of nonlinear problems

DOI10.1016/j.cma.2020.112947zbMath1442.65094OpenAlexW3009859350MaRDI QIDQ2180467

Mariella Kast, Mengwu Guo, Jan S. Hesthaven

Publication date: 14 May 2020

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.2020.112947

zbMATH Keywords

Gaussian process regressionnonlinear structural analysismultifidelity methodsnon-intrusive reduced order modelingvector-valued machine learning

Mathematics Subject Classification ID

Learning and adaptive systems in artificial intelligence (68T05) Numerical computation of solutions to systems of equations (65H10)

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Uses Software

• redbKIT
• GPy
• GitHub

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