Using deep generative adversarial network to explore novel airfoil designs for vertical-axis wind turbines

Santos, Gabriel Bertacco dos; PANTALEAO, ALUISIO; Salviano, Leandro

doi:10.1016/j.enconman.2023.116849

Energy Conversion and Management

2023

DOI: 10.1016/j.enconman.2023.116849

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Using deep generative adversarial network to explore novel airfoil designs for vertical-axis wind turbines

Gabriel Bertacco dos Santos

ALUISIO PANTALEAO

Leandro Salviano

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Cited by 8 publications

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Using deep generative adversarial network to explore novel airfoil designs for vertical-axis wind turbines

Cited by 8 publications

References 61 publications

Deep generative models in energy system applications: Review, challenges, and future directions

Deep generative models in energy system applications: Review, challenges, and future directions

General framework for unsteady aerodynamic prediction of airfoils based on deep transfer learning

Adversarial image-to-image model to obtain highly detailed wind fields from mesoscale simulations in urban environments

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