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

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 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.

GPU-accelerated aerodynamic shape optimisation framework for large turbine blades

“…al. reported the chord reynolds number for the majority of the blade sits above the 1 × 10 7 value used in the EllipSys3D simulations [18]. This paper uses a Reynolds number of 1 × 10 7 however, the high sensitivity in predicted performance against Reynolds number between BEM and CFD solutions is something which warrants further investigation.…”