CFD Data on a Vertical Axis Wave Turbine

Dataset · Mon Jul 31 04:00:00 EDT 2023

DOI:https://doi.org/10.15473/2006434· OSTI ID:2006434

Yang, Yingchen ^[1]; Yan, Deguang; Ge, Zhongfu

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1. University of Texas Rio Grande Valley

In this study January to July, 2023, different variations of the original geometry of a vertical-axis wave turbine (VAWT) were generated and evaluated for hydrodynamic power efficiency using computational fluid dynamics (CFD). The key geometrical parameters considered in this parametric study included the chord length of the rotor blades and the horizontal semi-axis length. The immersion depth of the rotor was also examined as a key deployment parameter for the wave turbine. The CFD simulation results revealed that a medium chord length of the blade (i.e., the same as that of the baseline design) and a shorter horizontal semi-axis for the guide curve of the blade than that of the baseline design resulted in higher hydrodynamic power to extract. With the most efficient turbine rotor geometry identified in this study, a deployment depth that could assure full submergence of the rotor in waves but as close to the free surface as possible led to a higher hydrodynamic power. These findings revealed a pathway for the improvement of the wave turbine energy efficiency.

• Research Organization: Marine and Hydrokinetic Data Repository (MHKDR); University of Texas Rio Grande Valley
• Sponsoring Organization: USDOE Office of Energy Efficiency and Renewable Energy (EERE), Renewable Power Office. Water Power Technologies Office (EE-4WP)
• Contributing Organization: University of Texas Rio Grande Valley
• DOE Contract Number: EE0008895
• OSTI ID: 2006434
• Report Number(s): 503
• Availability: [e-mail]
• Country of Publication: United States
• Language: English

Related Subjects

16 TIDAL AND WAVE POWER
Excel
Paraview
TEAMER
WEC
chord length
horizontal semi-axis length
immersion depth
processed data
technology
testing
unidirectional rotation
wave energy
wave energy converter
wave turbine