The RANS inaccuracy in predicting flow separation becomes relevant in thick-modern blades, especially once they get dirt or eroded. The literature has tackled the problem by modifying the coefficient a 1 in the k - ω - SST turbulence model without considering its dependency on the adverse pressure gradient condition. This study aims to assess the mentioned dependency by estimating a 1 per blade side and angle of attack. Pressure-coefficient measurements for 18 %, 25 %, and 30 % thick airfoils in clean-inflow conditions at a Reynolds number based on chord of 3 × 106 are considered in the estimation. Hence, a unique variation of a 1 is obtained per each airfoil, justifying the need to adapt a 1 locally within the OpenFOAM code. This modification considerably improves the flow separation prediction with respect to the standard a 1 value and the fb method. As a result, the CL error is reduced by 8 %, whereas a certain CD error remains for all the RANS solutions. Finally, an aeroelastic model of a 4.5 MW wind turbine reveals that the non-corrected RANS solution causes an overshoot of power and loads near rated power, whereas the corrected RANS replicates the shape of the power and loads curves. Consequently, the suggested methodology can be used to search for the required a 1 relation to local flow conditions.

Modern wind turbines employ thick airfoils in the outer region of the blade with strong adverse pressure gradients and high sensitivity to flow separation, which can be anticipated by leading-edge roughness. However, Reynolds average Navier-Stokes simulations currently overpredict the Reynolds shear stresses near the surface, and the flow separation is not correctly predicted. Hence, these methods are not representative enough to optimize the blade design to avoid flow separation, which becomes relevant for rough blades. While several eddy-viscosity corrections in the (Figure presented.) turbulence model have been previously studied to predict flow separation over smooth airfoils, the present study aims to extend their applicability to airfoils with leading-edge roughness. Two corrections, whose effect on flow physics has not been empirically quantified, are addressed. Particle image velocimetry measurements have been performed on a 30% thick airfoil to quantify the impact of these corrections. The reduction of the eddy viscosity introduced by the corrections leads to a shift of the peak location of the Reynolds shear stresses away from the surface, which, in turn, promotes flow separation and improves the prediction of the mean velocity and the pressure-coefficient distribution. Besides, the ratio between the main turbulent shear stress and turbulent kinetic energy is demonstrated to be lower than the standard value used in the (Figure presented.) turbulence model at the boundary-layer outer edge. Adjusting this ratio for an angle of attack of 0° decreases the error on the predicted lift and drag coefficients from 75% to 3% and from 58% to 39%, respectively.

The mid-span region of wind turbine blades can be thickened to fulfil the structural requirements of the blade. Hence, thick airfoils, that were designed to operate at the root region of the blade, are moved to the mid-span region. This could not imply remarkable variations of the blade performance once its surface is smooth. However, the sensitivity of thick airfoils to roughness could cause significant aerodynamic impacts such as flow separation. This research aims to quantify the impact of the blade thickness, under smooth and rough conditions, in the annual energy production and the fatigue loads of the blade. Ten blade designs, linearly interpolated in thickness, are studied employing aero-elastic computations. The results reveal that the thickest blade increases the annual energy production by 5% with respect to the thinnest blade under rough conditions. Whereas this increase is less than 1% under smooth conditions. The loss of annual energy production varies with the blade thickness linearly for thin blades while it varies exponentially for thick blades up to 22%. Fatigue loads assessment confirmed a reduction of the damage equivalent load under smooth conditions, whereas the thickest blade increased it 28% under rough conditions.

A computational fluid dynamics study is carried out to model the effects of distributed roughness at the airfoil leading-edge using the equivalent sand grain approach and Reynolds-averaged Navier–Stokes equations. The turbulence model k - ω-shear stress transport (SST) is selected to emulate a fully turbulent flow. Three k and ω boundary conditions are studied to model roughness effects. One refers to Wilcox’s boundary condition and the other two refer to Aupoix’s boundary conditions. Besides, Hellsten’s correction is used to ensure Wilcox’s boundary condition compatibility with the shear stress transport limiter. After validating the implementation of these boundary conditions, they are applied to three different airfoils. One of them is a thick airfoil with industrial relevance. For this airfoil, Wilcox’s boundary condition significantly underestimates the roughness impact on aerodynamic coefficients. The pressure gradient simplification in Wilcox’s boundary condition formulation is the driving factor behind this effect. The pressure gradient effect on Aupoix’s boundary condition is minimal.