Local correlation-based transition models for high-Reynolds-number wind-turbine airfoils

Author:

Jung Yong Su,Vijayakumar Ganesh,Ananthan ShreyasORCID,Baeder James

Abstract

Abstract. Modern wind-turbine airfoil design requires robust performance predictions for varying thicknesses, shapes, and appropriate Reynolds numbers. The airfoils of current large offshore wind turbines operate with chord-based Reynolds numbers in the range of 3–15 million. Turbulence transition in the airfoil boundary layer is known to play an important role in the aerodynamics of these airfoils near the design operating point. While the lack of prediction of lift stall through Reynolds-averaged Navier–Stokes (RANS) computational fluid dynamics (CFD) is well known, airfoil design using CFD requires the accurate prediction of the glide ratio (L/D) in the linear portion of the lift polar. The prediction of the drag bucket and the glide ratio is greatly affected by the choice of the transition model in RANS CFD of airfoils. We present the performance of two existing local correlation-based transition models – one-equation model (γ− SA) and two-equation model (γ-Reθt‾- SA) coupled with the Spalart–Allmaras (SA) RANS turbulence model – for offshore wind-turbine airfoils operating at a high Reynolds number. We compare the predictions of the two transition models with available experimental and CFD data in the literature in the Reynolds number range of 3–15 million including the AVATAR project measurements of the DU00-W-212 airfoil. Both transition models predict a larger L/D compared to fully turbulent results at all Reynolds numbers. The two models exhibit similar behavior at Reynolds numbers around 3 million. However, at higher Reynolds numbers, the one-equation model fails to predict the natural transition behavior due to early transition onset. The two-equation transition model predicts the aerodynamic coefficients for airfoils of various thickness at higher Reynolds numbers up to 15 million more accurately compared to the one-equation model. As a result, the two-equation model predictions are more comparable to the predictions from eN transition model. However, a limitation of this model is observed at very high Reynolds numbers of around 12–15 million where the predictions are very sensitive to the inflow turbulent intensity. The combination of the two-equation transition model coupled with the Spalart–Allmaras (SA) RANS turbulence model is a good method for performance prediction of modern wind-turbine airfoils using CFD.

Funder

Advanced Research Projects Agency - Energy

Publisher

Copernicus GmbH

Subject

Energy Engineering and Power Technology,Renewable Energy, Sustainability and the Environment

Reference32 articles.

1. Abbott, I. H. and von Doenhoff, A. E.: Theory of Wing Sections: Including a Summary of Airfoil Data, Dover Publicatios, Inc., 586–587, ISBN 978-0486605869, 1959. a

2. Bak, C., Zahle, C., Bitsche, R., Kim, T., Yde, A., Henrikson, L. C., Hansen, M. H., Blasques, J. P. A. A., Guanaa, M., and Natarajan, A.: The DTU 10-MW Reference Wind Turbine, Tech. rep., DTU, https://findit.dtu.dk/en/catalog/2389486991 (last access: July 2020), 2013. a, b, c, d, e, f, g, h, i, j

3. Ceyhan, O., Pires, O., and Munduate, X.: AVATAR HIGH REYNOLDS NUMBER TESTS ON AIRFOIL DU00-W-212, Tech. rep., Zenodo [data set], https://doi.org/10.5281/zenodo.439827, 2017a. a, b, c, d, e, f, g, h, i, j

4. Ceyhan, O., Pires, O., Munduate, X., Sorensen, N., Reichstein, T., Schaffarczyk, A., Diakakis, K., Papadakis, G., Daniele, E., Schwarz, M., Lutz, T., and Prieto, R.: Summary of the Blind Test Compaign to predict the High Reynolds number performance of DU00-W-210 airfoil, in: AIAA Scitech, https://doi.org/10.2514/6.2017-0915, 2017b. a, b, c, d, e, f, g, h, i, j, k, l

5. Coder, J.: Further Development of the Amplification Factor Transport Transition Model for Aerodynamic Flows, in: AIAA Scitech, https://doi.org/10.2514/6.2019-0039, 2019. a, b, c, d, e

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