Machine learning methods to assist structure design and optimization of Dual Darrieus Wind Turbines
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DOI: 10.1016/j.energy.2021.122643
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- Li, Jinlong & Wang, ZhuoTeng & Zhang, Shuai & Shi, Xilin & Xu, Wenjie & Zhuang, Duanyang & Liu, Jia & Li, Qingdong & Chen, Yunmin, 2022. "Machine-learning-based capacity prediction and construction parameter optimization for energy storage salt caverns," Energy, Elsevier, vol. 254(PA).
- Cheng, Biyi & Yao, Yingxue, 2023. "Machine learning based surrogate model to analyze wind tunnel experiment data of Darrieus wind turbines," Energy, Elsevier, vol. 278(PA).
- Salari, Ali & Shakibi, Hamid & Soleimanzade, Mohammad Amin & Sadrzadeh, Mohtada & Hakkaki-Fard, Ali, 2024. "Application of machine learning in evaluating and optimizing the hydrogen production performance of a solar-based electrolyzer system," Renewable Energy, Elsevier, vol. 220(C).
- Marzec, Łukasz & Buliński, Zbigniew & Krysiński, Tomasz & Tumidajski, Jakub, 2023. "Structural optimisation of H-Rotor wind turbine blade based on one-way Fluid Structure Interaction approach," Renewable Energy, Elsevier, vol. 216(C).
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Keywords
Dual Darrieus Wind Turbines; Power prediction; Structure optimization; Machine learning;All these keywords.
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