An inverse method for 3d aerodynamic design of wing shape

Aerodynamic optimization design of wing shape is a complicated problem, so the computational efficiency of the method is very important. Genetic Algorithms (GAs) are strong tools for solving the large-scale optimization problems. They have very strong global search capability, but poor local search capability. This makes GAs converge very slowly especially when they are used for such complex question as the inverse design of 3d wing shape. The genetic operators are specially designed and Simultaneous Perturbation Stochastic Approximation (SPSA) is introduced into Stochastic Gradient Genetic Algorithm (SGGA). In fact, SPSA is a simple, easily implemented and efficient stochastic approximation algorithm. Also SGGA is used for the inverse design of wing shape. And flow field is calculated by means of wing supercritical analysis program-the software of simplification version of FLO22VSE. The paper explores a high efficient method for the inverse design of wing shape. The experiments show satisfactory results.