Finite element approximation of wave problems with correcting terms based on training artificial neural networks with fine solutions

DOI10.1016/j.cma.2022.115280OpenAlexW4285585614WikidataQ114196759 ScholiaQ114196759MaRDI QIDQ2674053

Arnau Fabra, Ramon Codina, Joan Baiges

Publication date: 22 September 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.2022.115280

zbMATH Keywords

wave equationartificial neural networksstabilized finite element methodsleast squares training

Mathematics Subject Classification ID

Finite element methods applied to problems in fluid mechanics (76M10) Finite element, Rayleigh-Ritz and Galerkin methods for initial value and initial-boundary value problems involving PDEs (65M60)

Related Items (3)

Artificial neural network based correction for reduced order models in computational fluid mechanics ⋮ Accelerating high order discontinuous Galerkin solvers using neural networks: 3D compressible Navier-Stokes equations ⋮ DNN-MG: a hybrid neural network/finite element method with applications to 3D simulations of the Navier-Stokes equations

Uses Software

• FANN
• redbKIT
• GitHub

Cites Work

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