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Wind Energy Science The interactive open-access journal of the European Academy of Wind Energy
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In RANS-CFD, eN-based method showed its superiority over local correlation-based transition models (LCTM) coupled with the SST turbulence model for predicting transition behavior at high-Reynolds number flows (3–15 million). In this study, we evaluated performance of two LCTMs coupled with SA turbulence model. As a result, the SA-based two-equation transition model showed a comparable performance with the eN-based method and better glide ratio (L / D) predictions than the SST-based model.
Preprints
https://doi.org/10.5194/wes-2021-23
https://doi.org/10.5194/wes-2021-23

  23 Mar 2021

23 Mar 2021

Review status: this preprint is currently under review for the journal WES.

Local Correlation-based Transition Models for High-Reynolds-Number Wind Turbine Airfoils

Yong Su Jung1, Ganesh Vijayakumar2, Shreyas Ananthan2, and James Baeder1 Yong Su Jung et al.
  • 1University of Maryland, College Park, MD
  • 2National Renewable Energy Laboratory, Golden, CO

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 Reynold-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 (γ) and two-equation model 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. The two-equation model also predicts the correct trends with the variation of Reynolds number comparable to the 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 transition model coupled with the Spalart-Allmaras (SA) RANS turbulence model is a robust method for performance prediction of modern wind-turbine airfoils using CFD.

Yong Su Jung et al.

Status: open (until 04 May 2021)

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Yong Su Jung et al.

Yong Su Jung et al.

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Short summary
In RANS-CFD, eN-based method showed its superiority over local correlation-based transition models (LCTM) coupled with the SST turbulence model for predicting transition behavior at high-Reynolds number flows (3–15 million). In this study, we evaluated performance of two LCTMs coupled with SA turbulence model. As a result, the SA-based two-equation transition model showed a comparable performance with the eN-based method and better glide ratio (L / D) predictions than the SST-based model.
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