NACA four-digit airfoil series optimization: a comparison between genetic algorithm and sequential quadratic programming

Abstract

In this study, the results of genetic algorithm and sequential quadratic programming are discussed for NACA four-digit airfoil series optimization. The lift-to-drag ratio is defined as the objective function. The aerodynamic constraints related to the lift, drag, moment values of the airfoil at high and low angle of attack, and the geometric constraints related to the wetted length and internal volume are set. Results show that the sequential use of the former and latter methods and the stand-alone use of the latter method yield an increment of approximately 20 % in the objective function. The change in the geometric design variables reveals that the optimum airfoils are obtained by the variation in the maximum camber and thickness. Sequential quadratic programming is proven to converge to the global optimum in a significantly shorter solution time than genetic algorithm when the practical constraints are defined into the optimization problems.