Global Shape Optimization of Airfoil Using Multi-objective Genetic Algorithm
Juhee Lee, Sang-Hwan Lee, Kyoungwoo Park · Transactions of the Korean Society of Mechanical Engineers B · 2005
The shape optimization of an airfoil has been performed for an incompressible viscous flow. In this study, Pareto frontier sets, which are global, non-dominated solutions, can be obtained without various weighting factors by using the multi-objective genetic algorithm. An NACA0012 airfoil is considered as a baseline model,, the profile of the airfoil is parameterized, rebuilt with four Bezier curves. Two curves, from leading to maximum thickness, are composed of five control points, the rest, from maximum thickness to tailing edge, are composed of four control points. There are eighteen design variables, two objective functions such as the lift, drag coefficients. A generation is made up of forty-five individuals. After fifteenth evolutions, the Pareto individuals of twenty can be achieved. One Pareto, which is the best of the reduction of the drag force, improves its drag to 13%, lift-drag ratio to 2%. Another Pareto, however, which is focused on increasing the lift force, can improve its lift force to 61%, while sustaining its drag force, compared to those of the baseline model.