General Information
    • ISSN: 1793-821X
    • Frequency: Quarterly (2013-2014); Bimonthly (Since 2015)
    • DOI: 10.18178/JOCET
    • Editor-in-Chief: Prof. Haider F. Abdul Amir
    • Executive Editor: Ms. Julia S. Ma
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Editor-in-chief
School of Science and Technology Universiti Malaysia Sabah, Malaysia.
I would like to express my appreciation to all authors, reviewers and edtors.
JOCET 2017 Vol.5(6): 496-500 ISSN: 1793-821X
DOI: 10.18178/JOCET.2017.5.6.423

Turbulence Model Prediction Capability in 2D Airfoil of NREL Wind Turbine Blade at Stall and Post Stall Region

Shrabanti Roy, Ziaul Huque, Kyoungsoo Lee, and Raghava Kommalapati
Abstract—Aerodynamic force that generated on 2D section of a blade is important for measuring the blade performance. Therefore in this current work Computational Fluid Dynamics (CFD) analysis was performed on 2D S809 airfoil. S809 airfoil was designed by National Renewable Energy Laboratory (NREL). Experimental analysis of this airfoil was done and available for the validation purpose. Aerodynamic forces like lift and drag coefficients were measured by using CFD in this work. Pressure coefficients around the airfoil were also generated to compare with experimental results. A wide range of angle of attack cases with a fixed Reynolds number of 2×106 were considered which helped to analyze all stall and post stall flow conditions. It is clear that capturing all practical phenomena of 2D airfoil through CFD simulations are difficult. Over predictions of lift-coefficient and under-prediction of drag coefficient from the simulations as compared to experimental data were observed. Five different model equations were used to find the accuracy of various turbulence models in CFD calculation. The main emphasis of the result was on the variation at stall and post stall region. It has found that SST gamma-theta model is more accurate in predicting the effect of flow transition and separation than the other equations used in this work.

Index Terms—Wind energy, wind blade, S809, airfoil, k-, k-, SST

Shrabanti Roy, Ziaul Huque, Kyoungsoo Lee, and Raghava Kommalapati are with the Prairie View A & M University, Prairie View, TX 77446 USA (e-mail: shroy@pvamu.edu; zihuque@pvamu.edu; lks1838@naver.com; rrkommalapati@pvamu.edu).

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Cite:Shrabanti Roy, Ziaul Huque, Kyoungsoo Lee, and Raghava Kommalapati, "Turbulence Model Prediction Capability in 2D Airfoil of NREL Wind Turbine Blade at Stall and Post Stall Region," Journal of Clean Energy Technologies vol. 5, no. 6, pp. 496-500, 2017.

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