Model order reduction for large-scale structures with local nonlinearities

DOI10.1016/j.cma.2019.04.042zbMath1441.74285OpenAlexW2903057625WikidataQ127757192 ScholiaQ127757192MaRDI QIDQ1988121

Mengwu Guo, Zhenying Zhang, Jan S. Hesthaven

Publication date: 16 April 2020

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

Full work available at URL: https://infoscience.epfl.ch/record/260413/files/MOR_local_nonlinear.pdf

zbMATH Keywords

reduced basis methodmachine learningGaussian process regressionmodel order reductionnonlinear structural analysis

Mathematics Subject Classification ID

Classical linear elasticity (74B05) Nonlinear elasticity (74B20) Structured surfaces and interfaces, coexistent phases (74A50) Finite element methods applied to problems in solid mechanics (74S05) Finite element, Rayleigh-Ritz and Galerkin methods for boundary value problems involving PDEs (65N30)

Related Items

Rare event simulation for large-scale structures with local nonlinearities, Discrete orthogonal polynomials reduced models based on shift-transformation and discrete Walsh functions, Uncertainty quantification for nonlinear solid mechanics using reduced order models with Gaussian process regression, An improved model order reduction method for dynamic analysis of large-scale structures with local nonlinearities, Sampling Low-Dimensional Markovian Dynamics for Preasymptotically Recovering Reduced Models from Data with Operator Inference, Physics-informed multi-LSTM networks for metamodeling of nonlinear structures, Efficient uncertainty quantification of CFD problems by combination of proper orthogonal decomposition and compressed sensing

Uses Software

• rbMIT
• FEAPpv
• redbKIT

Cites Work

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