基于CG法及Taguchi理论的气动力鲁棒性优化方法

Robust aerodynamic optimization based on conjugate gradient algorithm and Taguchi's theory

针对传统的基于固定设计点气动力优化设计方法中存在的非设计点性能较差的问题,利用Taguchi鲁棒性设计理论和共轭梯度(Conjugate Gradient,CG)法,在斯坦福大学的开源CFD软件平台SU2的基础上,提出了一种高鲁棒性气动力优化设计方法。以NACA0012翼型为算例,以降低波阻为目标,对翼型的气动外形进行了鲁棒性优化设计,并与单点设计结果进行了对比。研究结果表明,采用提出的高鲁棒性气动力优化设计方法,在一定的亚声速范围内可以有效降低翼型波阻,实现翼型在波动飞行环境下的高鲁棒性气动力设计。研究结果对高鲁棒性气动力优化设计具有一定的工程指导价值。

Traditional aerodynamic optimization is commonly carried out under a fixed operating condition,and the result usually suffers from localized property. In order to solve this problem,a robust optimization method was established by using the conjugate gradient algorithm and the well-renowned Taguchi＇s robust design theory,based on SU2 program which is an open-source CFD code developed in Stanford University. Through the optimizations of the wave drag of the NACA0012 airfoil,both the results of single-point and robust optimization were obtained and compared with each other. The example shows that the robust optimization method succeeded in reducing the airfoil＇s wave drag under a certain range of subsonic speed. The result of the test example approves the effectiveness of the method in solving robust optimization problems under changing operating conditions.