Performance optimization and investigation of flow phenomena on tidal turbine blade airfoil considering cavitation and roughness

Since the underwater impurity and cavitation could have a significant impact on the aerodynamic performance of tidal turbine blade airfoil, it is necessary to consider both roughness and cavitation in the process of optimization design. In the present study, a novel multi-objective evolution algorithm based on NSGA-II is proposed for the design of tidal turbine blade airfoil, to overcome the adverse effects of cavitation and roughness. Nonuniform rational B-spline (NURBS) representation is adopted in the process of optimization; a new performance evaluation index of airfoil under rough condition is formed; multi-objective optimization was conducted for NACA2415 airfoil. The minimum pressure coefficient is the criterion used for the identification of cavitation on tidal turbine blade airfoil. The CFD and XFOIL are employed to calculate the lift drag coefficient and pressure coefficient of airfoil. The transition position of airfoil is predicted by the improved transition model. A comprehensive experimental study was conducted to evaluate the aerodynamic performance of optimized airfoil, revealing flow patterns such as flow separation over the initial airfoil and optimized airfoil through smoke flow experiment. In order to simulate the rough condition, sandpaper was pasted on the leading edge surface of airfoil and experiments indicated that location and formation of laminar separation bubble were affected . Numerical simulation and experimental results show that the optimized airfoil enjoys a better aerodynamic performance than the original ones under the roughness condition, in terms of cavitation inhibition. Within the range of design conditions, the lift drag ratio of optimized airfoils increased by an average of 20% and the minimum pressure coefficient peak decreased by about 17.2% on average. Thus,the proposed method can effectively guide the design and technical reserve of the tidal turbine.

Automated summary

A novel multi-objective evolution algorithm based on NSGA-II was proposed to optimize the tidal turbine blade airfoil, considering the impact of cavitation and roughness on aerodynamic performance. Numerical simulations and experiments showed that the optimized airfoil had better aerodynamic performance under rough conditions in terms of cavitation inhibition, with an average increase in lift drag ratio by 20% and average decrease in minimum pressure coefficient by 17.2%.