基于能量观点的混合层流优化设计

为了合理地在混合层流设计中减小阻力，降低能量消耗，利用吸气控制功率消耗与阻力、吸气速度的关系式，建立了考虑以吸气功率最小为优化目标的优化设计方法。该优化设计方法采用了自由变形（FFD）参数化方法，紧支型的径向基函数（RBF）动网格技术，改进的微分进化（DE）算法，以及耦合基于eN转捩预测的RANS流场高精度求解器。针对25°后掠角的跨声速无限展长后掠翼，进行了以阻力最小为优化目标的均匀吸气和以功率消耗最小为优化目标的分布式吸气的混合层流优化设计。优化结果表明，基于能量观点的优化结果在雷诺数10×106下可以达到均匀吸气的阻力收益，相比初始构型，阻力降低了29.1%，上下翼面转捩位置分别推迟了18%和15%弦长，功耗降低了1.7%；而在雷诺数20×106状态下，相比初始构型，阻力减小了41.3%，比均匀吸气阻力优化结果提高了4.5%，上下翼面转捩位置分别推迟了52%和14%弦长，功耗降低了8.14%。优化结果表明，建立的基于能量观点的混合层流优化方法是可行的。 

Hybrid laminar flow optimization design from energy view

For decreasing the drag and lowering the energy consumption for the hybrid laminar flow design correctly, the optimization system, whose object can be set as minimum energy cost, is built by correlating the relationship of suction control power consumption and drag. The optimization system includes the free freedom deformation (FFD) parameterization, the compact radial basis function (RBF) dynamic mesh method, the improved differential evolution (DE), and the high-fidelity Reynolds averaged Navier-Stokes (RANS) solver, which couples with the eN transition prediction method. For the infinite spanwise wing with 25° sweep angle, there are two optimizations:one is the uniform suction with minimum drag object; one is the distributed suction with minimum energy consumption object. At Reynolds number 10×106, the optimization results with minimum power consumption can obtain the same drag coefficient benefit with 29.1% decrease. The transition location is extended by 18% chord on the upper surface, while 15% chord on the lower surface. The power consumption is reduced by 1.7%. At Reynolds number 20×106, the distributed suction result can get more benefit than the uniform suction. The drag is reduced by 41.3% compared with the original configuration, which is improved by 4.5% compared with uniform suction dirstibution. The transition locations are extended by 52% chord on the upper surface and 14% chord on the lower surface. The suction power consumption is reduced by 8.14%. Thus, the optimization results show that the proposed hybrid laminar flow optimization method from energy view is reliable.