Helicopter blade design and optimization with b-spline, genetic algorithm and blade elements momentum theory

Helicopter wing optimization is needed to increase efficiency, reduce energy consumption, achieve better flight performance and increase the overall effectiveness of helicopter operations. The rotor blade is a critical component that generates lift and provides maneuverability to ensure efficiency and control, improve performance and enhance cost efficiency of a helicopter. It is a vital component of helicopter design that greatly influences the achievement of optimal flight characteristics and operational capabilities. In this study helicopter blade design and optimization tool has been developed via Python software by using B-spline, Blade Element-Momentum Theory and Genetic Algorithm methods. Rotor blade cross section curves are created from the points on the two-dimensional axis with the B-spline method. Helicopter blade sections with different geometries are generated from these points with genetic algorithm. The aerodynamic parameters are obtained by putting the previously created airfoil sections in the flow solver via XFOIL and the objective function determined by the blade elements momentum theory is minimized by using genetic algorithm. Helicopter blades are optimized according to airfoil shapes obtained from B-spline, rotational speed, number of blades, chord length, span, twist angle and taper ratio and blade section curves that will provide maximum thrust and related geometric parameters of the blade are determined. The created code was verified by comparing it with the experimental study results, and it was understood that the thrust (C_T) coefficient increased by 30%, the total thrust force by 48%, and the total torque and power by 44%, depending on the parameters and boundary conditions fed into the developed algorithm.