A DNN-based data-driven modeling employing coarse sample data for real-time flexible multibody dynamics simulations

DOI10.1016/j.cma.2020.113480zbMath1506.65097OpenAlexW3094248249MaRDI QIDQ2020773

Hee-Sun Choi, Jin Hwan Choi, Seongji Han, Juhwan Choi, Jin-Gyun Kim

Publication date: 26 April 2021

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.2020.113480

zbMATH Keywords

error correctionreal-time simulationsdeep neural networksdata-driven modelingcoarse sample dataflexible multibody dynamics (FMBD)

Mathematics Subject Classification ID

Numerical methods for initial value problems involving ordinary differential equations (65L05) Dynamics of multibody systems (70E55)

Related Items

Multibody dynamics and control using machine learning, CNN-DP: composite neural network with differential propagation for impulsive nonlinear dynamics, Multi-fidelity meta modeling using composite neural network with online adaptive basis technique

Uses Software

• Adam

Cites Work

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