Physics-inspired architecture for neural network modeling of forces and torques in particle-laden flows
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Publication:2129550
DOI10.1016/j.compfluid.2022.105379OpenAlexW3192242357MaRDI QIDQ2129550
Arman Seyed-Ahmadi, Anthony Wachs
Publication date: 22 April 2022
Published in: Computers and Fluids (Search for Journal in Brave)
Full work available at URL: https://arxiv.org/abs/2108.04958
neural networkinterpretabilityparticle-laden flowphysics-informedhydrodynamic force and torque modelpairwise interaction superposition
Uses Software
Cites Work
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