应用后缘装置的跨声速层流翼型多岛优化设计

高雷诺数状态下,自然层流技术(Natural laminar flow,NLF)是减小机翼表面湍流摩擦阻力的有效方法。然而由于层流翼面上大范围顺压梯度的存在使得后缘处的恢复压差更大,产生更强的激波。因此在减小摩擦阻力的同时又增加了激波阻力。本文采用后缘装置(Trailing edge device,TED)来控制翼型后缘处的激波强度,基于线性稳定性理论(Linear stability theory,LST)的eN方法对流动进行转捩判断,进而应用多岛并行多目标进化算法(multi-objective evolutionary algorithm,MOEA)以获得大范围层流区域和弱化激波强度为目标对翼型进行优化设计。优化结果表明合作均衡策略耦合进化算法可以快速地捕捉到该多目标问题的Pareto阵面解,阵面上翼型的波阻力和摩擦阻力性能较初始翼型大大改善。同时,采用后缘装置控制激波强度时,无论在设计点还是偏离设计点时,优化后翼型均具有良好的升阻力特性和鲁棒性。

Trailing Edge Device Application for Wave Drag Reduction in NLF Airfoil Multi-island Design Optimization

The natural laminar flow (NLF) technology is an efficient method used to reduce wing surface turbulence friction drag significantly by delaying transition location at high Reynolds numbers. However, the existence of wide range of favorable pressure gradient on laminar flow airfoil/wing surface leads to strong shock waves occurring at the neighborhood of the trailing edge at transonic regimes. Consequently, the reduction of the friction drag is compensated with the increase of the shock wave induced drag. In this paper, a trailing edge device (TED) is applied to control shock wave on surface of designed airfoil, and the eN method based on linear stability theory (LST) is introduced to predict the flow transition location. A multi-island parallel multi-objective evolutionary algorithm (MOEA) is implemented to optimize the airfoil shape and TED configuration for obtaining a larger laminar flow region and a weaker wave drag simultaneously. Optimization results indicate that cooperative game coupled with the evolutionary algorithm optimizer can easily capture a Pareto front of this two-objective optimization problem. Numerical simulations demonstrate that both wave drag and friction drag performances of Pareto members are significantly improved compared with that of baseline. Meanwhile, the optimized airfoils equipped with TED are all have great aerodynamics performance and robustness both at design or off-design conditions.