A hybrid partitioned deep learning methodology for moving interface and fluid-structure interaction

DOI10.1016/j.compfluid.2021.105239OpenAlexW3213650470MaRDI QIDQ2072360

Rachit Gupta, Rajeev K. Jaiman

Publication date: 26 January 2022

Published in: Computers and Fluids (Search for Journal in Brave)

Full work available at URL: https://arxiv.org/abs/2102.09095

zbMATH Keywords

proper orthogonal decompositionfluid-structure interactiondigital twinlong short-term memory networkconvolutional autoencoderdeep learning-based reduced-order model

Mathematics Subject Classification ID

Fluid mechanics (76-XX)

Related Items (2)

A novel artificial neural network-based interface coupling approach for partitioned fluid-structure interaction problems ⋮ Differentiable hybrid neural modeling for fluid-structure interaction

Uses Software

• Adam
• AntisymmetricRNN
• DeepONet
• DeepAdverserialRegulariser

Cites Work

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