研究论文
A novel cost-efficient deep learning framework for static fluid–structure interaction analysis of hydrofoil in tidal turbine morphing blade
Longyan Wang, Jian Hong Xu, Zilu Wang, Bowen Zhang, Zhaohui Luo, Jianping Yuan, Andy C. C. Tan
Jiangsu University Jiangsu Industry Technology Research Institute Universiti Tunku Abdul Rahman Sungai Long Campus Universiti Tunku Abdul Rahman
来源Renewable Energy
年份2023
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38
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4.62
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学术脉络
学科主题
物理Model Reduction and Neural Networks
Fluid Dynamics and Vibration Analysis · Lattice Boltzmann Simulation Studies
参考文献 53
FSI modeling of a propulsion system based on compliant hydrofoils in a tandem configuration
被引 87Jinhui Yan, Benoît Augier, Artem Korobenko · Computers & Fluids · 2015
Fluid-structure interaction : modelling, simulation, optimisation
被引 119Hans‐Joachim Bungartz, Michael Schäfer, Miriam Mehl · CERN Document Server (European Organization for Nuclear Research) · 2006
Hydro-elastic analysis of marine propellers based on a BEM-FEM coupled FSI algorithm
被引 66Hyoungsuk Lee, Min-Churl Song, Jung‐Chun Suh · International Journal of Naval Architecture and Ocean Engineering · 2014
此处列出前 3 条
引用本文 38
Recent advancements in morphing applications: Architecture, artificial intelligence integration, challenges, and future trends-a comprehensive survey
被引 49Md. Najmul Mowla, Davood Asadi, Tahir Durhasan · Aerospace Science and Technology · 2025
A reduced order modeling-based machine learning approach for wind turbine wake flow estimation from sparse sensor measurements
被引 38Zhaohui Luo, Longyan Wang, Jian Hong Xu · Energy · 2024
Offshore wind turbine tower design and optimization: A review and AI-driven future directions
被引 36João Alves Ribeiro, Bruno Alves Ribeiro, Francisco Pimenta · Applied Energy · 2025
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