基于遗传算法和空间推进方法的高超声速进气道优化设计研究

将遗传算法（单目标遗传算法GA和多目标遗传算法NSGA-Ⅱ、NCGA）与高效、高精度的卒间推进方法——SSPNS（Single-sweep Parabolized Navier-Stokes Algorithm）流场计算方法相结合，对二维高超声速进气道进行了气动优化设计研究。在单目标优化设计中以巡航点（Ma=7．0）的总压恢复最大为设计目标，多目标设计中则在巡航点分别考察了总压恢复最大-压升最大两目标模型、总压恢复最大-压升最大-阻力系数最小三目标模型。优化设计结果表明，单目标设计使得总压恢复有明显提高；多目标优化设计所得的Pareto最优前沿为设计者提供了可靠的设计依据。为了兼顾巡航点和加速爬升段的综合忭能，采用多目标优化方法对进气道进行了多点优化设计，并开展了基于等动压弹道的设计点选择问题初步研究。计算结果表明，若将设计点选在Ma=6．5左右，则进气道的综合性能较好。

Optimization Design of Hypersonic Inlets Using Genetic Algorithm Based on a Parabolized Navier-Stokes Flow Solver

The single and multi-objective optimization designs of a 2D inlet are carried out on cruise operation point(Ma=7.0) by Genetic Algorithm(GA),and multi-objective GAs,including NCGA and NSGA-II.In these optimization design processes,the inlet flowfields are calculated with the space-marching CFD algorithm,i.e.SSPNS(Single-Sweep Parabolized Navier-Stokes Algorithm) which had been validated soundly previously.The single objective optimization reached the maximum pressure recovery design.Multi-objective optimization results reveal the tradeoffs of pressure recovery,static pressure rise,and drag coefficients of the inlet.Based on the multi-objective design process,a two-point design and a design point choosing process are also investigated.Results show if design point is set at cruise point,the off-design mass capture coefficients is relatively low;whereas if the design Mach number is set to 6.5,the 2D inlet will get good overall operation performances along the constant dynamic pressure trajectory.