Computational fluid dynamics (CFD) is increasingly used to analyze \ wind turbines, and the next logical step is to develop CFD-based optimization to enable further gains in performance and reduce model uncertainties. We present an aerodynamic shape optimization framework consisting of a Reynolds-averaged Navier-Stokes solver coupled to a numerical optimization algorithm, a geometry modeler, and a mesh perturbation algorithm. To efficiently handle the large number of design variables, we use a gradient-based optimization technique together with an adjoint method for computing the gradients of the torque coefficient with respect to the design variables. To demonstrate the effectiveness of the proposed approach, we maximize the torque of the NREL VI wind turbine blade with respect to pitch, twist, and airfoil shape design variables while constraining the blade thickness. We present a series of optimization cases with increasing number of variables, both for a single \ wind speed and for multiple wind speeds. For the optimization at a single wind speed performed with respect to all the design variables (1 pitch, 11 twist, and 240 airfoil shape variables), the torque coefficient increased by 22.4\% relative to the NREL VI design. For the multiple-speed optimization, the torque increased by an average of 22.1\%. Depending on the CFD mesh size and number of design variables, the optimization time ranges from 2 to 24 h when using 256 cores, which means that wind turbine designers can use this process routinely.

}, doi = {10.1002/we.2070}, author = {Dhert, Tristan and Turaj Ashuri and Joaquim R. R. A. Martins} } @article {Ashuri2016, title = {Aeroservoelastic Design Definition of a 20 {MW} Common Research Wind Turbine Model}, journal = {Wind Energy}, volume = {19}, year = {2016}, abstract = {Wind turbine upscaling is motivated by the fact that larger machines can achieve lower levelized cost of energy. However, there are several fundamental issues with the design of such turbines, and there is little public data available for large wind turbine studies. To address this need, we develop a 20 MW common research wind turbine design that is available to the public*. Multidisciplinary design optimization is used to define the aeroservoelastic design of the rotor and tower subject to the following constraints: blade-tower clearance, structural stresses, modal frequencies, tip-speed, and fatigue damage at several sections of the tower and blade. For the blade, the design variables include blade length, twist and chord distribution, structural thicknesses distribution, and rotor speed at the rated. The tower design variables are the height, and the diameter distribution in the vertical direction. For the other components, mass models are employed to capture their dynamic interactions. The associated cost of these components is obtained by using cost models. The design objective is to minimize the levelized cost of energy. The results of this research show the feasibility of a 20 MW wind turbine and provide a model with the corresponding data for wind energy researchers to use in the investigation of different aspects of wind turbine design and upscaling.

}, doi = {10.1002/we.1970}, author = {Turaj Ashuri and Joaquim R. R. A. Martins and Michiel B. Zaaijer and Gijs A.M. van Kuik and Gerard J.W. van Bussel} }