关键词: 单壁扩张喷管, 优化设计, 遗传算法, 空间推进算法, Pareto最优前沿

Abstract:

The single- and multi-objective optimization designs of several 2D single-expansion-ramp nozzles (SERNs) are carried out by single-objective genetic algorithm (GA) and multi-objective GAs (including NCGA and NSGA-II). In these optimization design processes, the SERN flowfields are calculated with SSPNS (single-sweep Parabolized Navier-Stokes algorithm) codes which are proved highly accurate and highly efficient for supersonic/hypersonic flowfield simulations. The single-objective optimization design results show that the objective (i.e. thrust coefficient) is improved, but the lift coefficient is too low.

Key words: single-expansion-ramp , nozzle , (SERN),  , optimization , design,  , genetic , algorithms , (GAs),  , spacemarching , algorithms,  , Pareto , optimum , front