Parameterized Airfoil Design and Optimization for Vertical-Axis Tidal Turbines

This study presents a systematic airfoil optimization framework to enhance the hydrodynamic performance of vertical-axis tidal turbines (VATTs) under low-flow conditions. The integrated methodology combines parameterized design, response surface methodology (RSM) optimization, and high-fidelity computational fluid dynamics (CFD) validation to investigate the effects of maximum thickness (Factor A), maximum thickness position (Factor B), and maximum camber (Factor C). The shear stress transport (SST) k-ω turbulence model was employed for flow simulation, with experimental validation conducted across Reynolds numbers from 5.2 × 105 to 8.6 × 105. The tip speed ratio (TSR) predictions demonstrated excellent agreement with experimental measurements, showing a maximum relative error of only 4.5%. From hundreds of Pareto-optimal solutions, five candidate designs were selected for high-fidelity verification. The final optimized airfoil (Optimized Foil 5) achieved a power coefficient (CP) of 0.1887, representing a 27.5% improvement over the baseline National Advisory Committee for Aeronautics (NACA) 2414 airfoil. This optimal configuration features 23.51% maximum thickness, 30.14% maximum thickness position, and 3.99% maximum camber, with only 0.2% deviation between RSM prediction and CFD validation. The research establishes a reliable design framework for VATTs operating in low-velocity tidal streams, providing significant potential for harnessing previously uneconomical marine energy resources.

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Publication Details

Journal
Journal of Marine Science and Engineering
Published
2025-12-30
DOI
https://doi.org/10.3390/jmse14010068
Primary Topic
Wind Energy Research and Development
Type
article
Field-Weighted Citation Impact
0.00

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article

Parameterized Airfoil Design and Optimization for Vertical-Axis Tidal Turbines

Lin Li, Xiaozhou Hu, Shunjun Hong, Xingpeng Wang
Journal of Marine Science and Engineering
Wind Energy Research and Development
article

Parameterized Airfoil Design and Optimization for Vertical-Axis Tidal Turbines

Lin Li, Xiaozhou Hu, Shunjun Hong, Xingpeng Wang
article en

Abstract

This study presents a systematic airfoil optimization framework to enhance the hydrodynamic performance of vertical-axis tidal turbines (VATTs) under low-flow conditions. The integrated methodology combines parameterized design, response surface methodology (RSM) optimization, and high-fidelity computational fluid dynamics (CFD) validation to investigate the effects of maximum thickness (Factor A), maximum thickness position (Factor B), and maximum camber (Factor C). The shear stress transport (SST) k-ω turbulence model was employed for flow simulation, with experimental validation conducted across Reynolds numbers from 5.2 × 105 to 8.6 × 105. The tip speed ratio (TSR) predictions demonstrated excellent agreement with experimental measurements, showing a maximum relative error of only 4.5%. From hundreds of Pareto-optimal solutions, five candidate designs were selected for high-fidelity verification. The final optimized airfoil (Optimized Foil 5) achieved a power coefficient (CP) of 0.1887, representing a 27.5% improvement over the baseline National Advisory Committee for Aeronautics (NACA) 2414 airfoil. This optimal configuration features 23.51% maximum thickness, 30.14% maximum thickness position, and 3.99% maximum camber, with only 0.2% deviation between RSM prediction and CFD validation. The research establishes a reliable design framework for VATTs operating in low-velocity tidal streams, providing significant potential for harnessing previously uneconomical marine energy resources.

Journal of Marine Science and EngineeringVol. 14(1)
Central South University (CN), Tarim University (CN)
Tarim University, Xinjiang Production and Construction Corps
Life below water
Openalex Percentile: Top 20%
Wind Energy Research and Development
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Parameterized Airfoil Design and Optimization for Vertical-Axis Tidal Turbines — Lin Li, Xiaozhou Hu, et al. · Journal of Marine Science and Engineering (2025) | TGRS Research Map | TGRS