The present article reports optimization of the performance of a Wells turbine, which is an axial turbine utilized for wave energy conversion, through a computational fluid dynamics (CFD) based automated optimization technique. The in-house optimization library OPAL++ was coupled to a commercial CFD solver to get the Pareto front defining the relationships between two objectives. Four different geometric parameters of the turbine with ring-type endplate were used, and the objectives were to maximize the torque coefficient and simultaneously minimize the pressure drop coefficient. From the Pareto front, two designs (G1 and G2) were chosen for further analysis. G1 improved the peak torque-coefficient by more than 120 % and delayed the stall point from φ = 0.225 to φ = 0.3, while the peak efficiency dropped. Whereas, G2 improved the peak efficiency by 9.1 %, but the peak torque coefficient was reduced by about 50 %. The main contribution of the study is to develop an optimum Wells turbine geometry through the coupling of CFD and automated optimization algorithm - first of its kind applied to a Wells turbine with endplate. A detailed flow analysis, the influence of the endplate, and a comparison of the optimized geometries are presented.
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