关键词: 粒子群优化算法, Kriging代理模型, 多目标加权, 翼型, 数值模拟, 翼型参数化

Abstract: An efficient synthesis optimization method is developed to obtain optimal airfoil designs that satisfy all design objectives and constraints. In the particle swarm optimization, reproduction of the particle strategy is used to dig the global information based on Kriging surrogate model. Efficiency is enhanced greatly by mapping the solution space for some benchmark function tests and airfoil geometry reshape and laminar flow airfoil design problems. A modified Hicks-Henne function is used to parameterize airfoils, Reynolds-averaged Navier-Stokes (N-S) flow solver is combined with the optimization arithmetic, and a new nonlinear weighted sum of multi-objective method which can determine the weight of different objects easily is developed. Supercritical airfoil and low speed airfoil design problems with multi-point, multi-objective and multi-restriction are tested. Results show that the optimization method can greatly improve the practicability of aerodynamic shape optimization.

Key words: particle swarm optimization, Kriging surrogate model, weighted sum of multi-objective, airfoils, numerical simulation, airfoil parameterization