Deep learning‐based reduced order models for the real‐time simulation of the nonlinear dynamics of microstructures

DOI10.1002/nme.7054arXiv2111.12511OpenAlexW3216863713MaRDI QIDQ6071430

Andrea Manzoni, Giorgio Gobat, Attilio Frangi, Patrick Fedeli, Stefania Fresca

Publication date: 23 November 2023

Published in: International Journal for Numerical Methods in Engineering (Search for Journal in Brave)

Full work available at URL: https://arxiv.org/abs/2111.12511

zbMATH Keywords

nonlinear dynamicsMEMSreduced order modelsdeep learning

Mathematics Subject Classification ID

Artificial neural networks and deep learning (68T07) Micromechanics of solids (74M25) Finite difference methods for initial value and initial-boundary value problems involving PDEs (65M06)

Related Items (2)

Deep learning methods for partial differential equations and related parameter identification problems ⋮ Data-driven reduced-order modelling for blood flow simulations with geometry-informed snapshots

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