A novel Bayesian deep learning method for fast wake field prediction of the DARPA SUBOFF-Reference-Cited by-同舟云学术

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A novel Bayesian deep learning method for fast wake field prediction of the DARPA SUBOFF

Published:2024-09 Issue: Volume:150 Page:104074
ISSN:0141-1187
Container-title:Applied Ocean Research
language:en
Short-container-title:Applied Ocean Research

Author:

Xie Xinyu^ORCID,Zhao Pu,Bian Chao,Xia Linsheng,Ding Jiaqi,Wang Xiaofang,Liu Haitao^ORCID

Publisher

Elsevier BV

Reference53 articles.

1. A review of uncertainty quantification in deep learning: Techniques, applications and challenges;Abdar;Inf. Fusion,2021

2. Coherent flow noise beneath a flat plate in a water tunnel experiment;Abshagen;J. Sound Vib.,2015

3. Survey on traditional and AI based estimation techniques for hydrodynamic coefficients of autonomous underwater vehicle;Ahmed;Ocean Eng.,2023

4. Combining differentiable PDE solvers and graph neural networks for fluid flow prediction;Belbute-Peres,2020

5. Estimation of the induced hydrodynamic periodic forces of marine propeller under non-uniform inflow via CFD;Bennaya;Appl. Mech. Mater.,2014

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1. Hydro-acoustic optimization of propellers: A review of design methods;Applied Ocean Research;2024-10

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