Flow reconstruction over a SUBOFF model based on LBM-generated data and physics-informed neural networks-Reference-Cited by-同舟云学术

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Flow reconstruction over a SUBOFF model based on LBM-generated data and physics-informed neural networks

Published:2024-09 Issue: Volume:308 Page:118250
ISSN:0029-8018
Container-title:Ocean Engineering
language:en
Short-container-title:Ocean Engineering

Author:

Chu Xuesen,Guo Wei,Wu Tianqi,Zhou Yuanye^ORCID,Zhang Yanbo,Cai Shengze^ORCID,Yang Guangwen

Publisher

Elsevier BV

Reference40 articles.

1. The structure of the wake generated by a submarine model in yaw;Ashok;Exp. Fluid,2015

2. Artificial intelligence velocimetry reveals in vivo flow rates, pressure gradients, and shear stresses in murine perivascular flows;Boster;Proc. Natl. Acad. Sci. USA,2023

3. Machine learning for fluid mechanics;Brunton;Annu. Rev. Fluid Mech.,2020

4. Particle image velocimetry based on a deep learning motion estimator;Cai;IEEE Trans. Instrum. Meas.,2019

5. Physics-informed neural networks (PINNs) for fluid mechanics: a review;Cai;Acta Mech. Sin.,2021

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