遗传算法结合反设计的翼型优化设计研究

Improving Design of Airfoil with Genetic Algorithm (GA) Combined with Inverse Design Method

针对传统的气动外形优化设计存在计算量大、精度低的不足,以及采用余量修正方法的气动外形反设计存在难以提供合理目标压力的难题,为了提高已有气动外形设计方法的工程实用性,创新性地将优化方法中的遗传算法与反设计的余量修正方法相结合,并采用高精度的CFD分析方法,进行了翼型的气动外形设计。设计实践表明,文中的气动外形设计方法是可行的,且由于在优化方法和反设计方法中采用了不同的CFD分析方法,提高了气动外形设计的效率和精度。

Aim. Past researchers either use GA or inverse design method; both have, in our opinion, advantages and disadvantages. We now propose using GA combined with inverse design method with a view to retaining the advantages as much as possible while minimizing the disadvantages. In the full paper, we explain in detail our new method; in this abstract, we just add some pertinent remarks to listing the four topics of our explanation： （A） GA; （B） distributed computing; （C） inverse design method; （D） CFD analysis; we use GA, which is based on distributed computing, to enhance the efficiency of low-precision CFD optimization to provide suitable target pressure distribution of inverse design; then we use inverse design method combined with high-precision CFD analysis to enhance quality of design results. Numerical results of a design example, given in Figs. 1 through 4 and Table 1, show preliminarily that our hybrid design method and software are robust and provide practical tools for the design of aerodynamic configurations.