Efficient geometric parametrization of blades cross-sections by means of B-splines

Optimization and enhancement of rotor blade design are critical to improving the productivity of the wind energy industry. Airfoil geometry is a key factor that makes airfoil design and optimization a common task for aerodynamicists. Ensuring proper airfoil parametrization is essential. It serves as the first step in aerodynamic optimization, where the efficiency is directly related to the geometric complexity. This research presents a cost-effective and robust method for fitting airfoils using B-splines. We take into account factors such as computational cost, resource requirements, and accuracy. In this work, we present a method for minimizing the geometric distances between target points and a B-spline curve. We streamline the fitting process, create a computational Python package, and explore different approaches, objective functions, algorithms, and error tolerance settings. The work concludes that it is highly recommended to use an iterative fitting process, to adequately represent common airfoils with B-splines. Moreover, the accuracy and the computational cost can be managed subject to the minimization algorithm used, and the technique utilized for the objective cost calculation. The fitting procedure we develop in this study gives the smallest number of variables capable of accurately representing a desired airfoil.