A multi-objective optimization algorithm is proposed to address the problem of the complex operating conditions of large horizontal axis hydraulic turbine blades.

An airfoil optimization model is established based on the multi-island genetic algorithm, the airfoil is parametrically fitted using the class shape function transformation (CST) function method, and the whole optimization process is integrated on the Isight platform to achieve automatic optimization.

Using the above method, NACA 63813/63815/63816 airfoils are selected as the initial airfoils for multi-objective optimization, CFD numerical validation is carried out on the obtained airfoils using the Fluent turning model, and the lift-to-drag ratios and lifting forces at the airfoil attack angle of 5° are selected as the optimization objectives, resulting in the optimized airfoils gaining increased lift coefficients of 14%, 15% and 20%, and increased lift-to-drag ratios of 14%, 16% and 28%, respectively.

Numerical validation shows that the lift-to-drag ratios of the optimized airfoil is higher than those of the original airfoils with the same thickness under several operating conditions, and the structural strength of the blade is improved while ensuring good aerodynamic performance, making it more suitable than conventional airfoils for large-scale tidal current energy horizontal axis hydraulic turbines.