Airfoil Shape Optimization: Comparative Study of Meta-heuristic Algorithms, Airfoil Parameterization Methods and Reynolds Number Impact

Abstract

Abstract The aerodynamic efficiency in airfoil theory is defined as the ratio between the lift and drag force, which is the main objective function to be maximized in a wide kind of vehicle design due to its strong relationship between fuel consumption and range. This work employs the 4-digits NACA parameterization, a recently developed 6-parameters method, and the PARSEC technique with a correction of the matrices available in the literature, to compare the computational cost and the ability to achieved higher efficiency of these parameterizations. A genetic algorithm and particle swarm optimization routines are developed and implemented in Matlab, also a sine-cosine algorithm is tested, where Xfoil and the open-source computational fluid dynamic software OpenFOAM are coupled with the optimization algorithms. Finally, a Reynolds number impact study is performed related to the airfoil shape and the angle of attack which maximizes the aerodynamic efficiency. The results showed a faster convergence for the particle swarm optimization and the highest aerodynamic efficiency achieved by the 6-parameter method. Furthermore, with a higher Reynolds number, a higher angle of attack for the optimum lift-to-drag ratio as well a less camber is obtained.