Neural-network-based fluid-structure interaction applied to vortex-induced vibration

DOI10.1016/J.CAM.2023.115170zbMath1530.70002OpenAlexW4323352947MaRDI QIDQ6114712

Aleš Pecka, Ondřej Bublík, Václav Heidler, Jan Vimmr

Publication date: 12 July 2023

Published in: Journal of Computational and Applied Mathematics (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1016/j.cam.2023.115170

zbMATH Keywords

Navier-Stokes equationsdiscontinuous Galerkin methodunsteady fluid flowconvolution neural networkelastically-mounted cylinderlinear spring-mass-damper model

Mathematics Subject Classification ID

Artificial neural networks and deep learning (68T07) Navier-Stokes equations for incompressible viscous fluids (76D05) Computational methods for problems pertaining to mechanics of particles and systems (70-08) Fluid-solid interactions (including aero- and hydro-elasticity, porosity, etc.) (74F10) Forced motions in linear vibration theory (70J35)

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