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Direct Numerical Simulation of flow instabilities over Savonius style wind turbine blades

Author

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  • Ducoin, A.
  • Shadloo, M.S.
  • Roy, S.

Abstract

In this paper, Direct Numerical Simulations (DNS) are carried out in order to capture the flow instabilities and transition to turbulence occurring on a Savonius style wind turbine (SSWT) blade. Simulations are conducted with the open source code Nek5000, solving the incompressible Navier-Stokes equations with a high order, spectral element method. Because of the relatively high Reynolds number considered (Reξ=9×104), the computational domain of the Savonius blade is reduced to the pressure side, and the blade is studied in static condition, which avoids the large scale vortex shedding that occurs on its suction side, particularly allows to investigate the static performance of the wind turbine. The results suggest that Görtler vortices can occur and cause the flow to transit to turbulence, which modify the pressure and wall friction distributions, and consequently alter the drag and lift forces.

Suggested Citation

  • Ducoin, A. & Shadloo, M.S. & Roy, S., 2017. "Direct Numerical Simulation of flow instabilities over Savonius style wind turbine blades," Renewable Energy, Elsevier, vol. 105(C), pages 374-385.
    • Handle: RePEc:eee:renene:v:105:y:2017:i:c:p:374-385
    DOI: 10.1016/j.renene.2016.12.072
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    References listed on IDEAS

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    1. Mohamed, M.H. & Janiga, G. & Pap, E. & Thévenin, D., 2010. "Optimization of Savonius turbines using an obstacle shielding the returning blade," Renewable Energy, Elsevier, vol. 35(11), pages 2618-2626.
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    5. Roy, Sukanta & Saha, Ujjwal K., 2013. "Review on the numerical investigations into the design and development of Savonius wind rotors," Renewable and Sustainable Energy Reviews, Elsevier, vol. 24(C), pages 73-83.
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    Cited by:

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    3. Patel, Vimal & Eldho, T.I. & Prabhu, S.V., 2019. "Velocity and performance correction methodology for hydrokinetic turbines experimented with different geometry of the channel," Renewable Energy, Elsevier, vol. 131(C), pages 1300-1317.
    4. Mohammadi, M. & Lakestani, M. & Mohamed, M.H., 2018. "Intelligent parameter optimization of Savonius rotor using Artificial Neural Network and Genetic Algorithm," Energy, Elsevier, vol. 143(C), pages 56-68.
    5. Fusheng Meng & Qun Zheng & Jie Gao & Weiliang Fu, 2019. "Effect of Tip Clearance on Flow Field and Heat Transfer Characteristics in a Large Meridional Expansion Turbine," Energies, MDPI, vol. 12(1), pages 1-19, January.

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