摘要
采用Pareto排名策略和共享小生境技术,实现遗传算法的多目标优化设计.叶栅的气动性能通过求解二维Navier-Stokes方程获得.本文中压气机叶栅的多目标优化确定为在给定条件下同时追求高增压比和低总压损失系数.优化设计获得的Pareto解集显示出本文发展的优化设计平台能够较好的实现多目标的气动优化设计.
A multiobjective genetic algorithm（GA） has been developed by introducing Pareto ranking and fitness-sharing techniques. Performance of the cascade airfoils was evaluated based on the two dimensional Navier-Stokes equations. To demonstrate the feasibility of the algorithm, a multiobjective design optimization of cascade airfoils was performed for minimizing the total pressure loss coefficient and maximizing the high pressure ratio at the same time. The optimization results show that the present method is effective and efficient in multiobjective aerodynamic design optimization.
出处
《航空动力学报》
EI
CAS
CSCD
北大核心
2007年第2期285-290,共6页
Journal of Aerospace Power
基金
国家自然科学基金资助(50076001
50136010)
关键词
航空
航天推进系统
压气机
遗传算法
优化设计
aerospace propulsion system
compressor
genetic algorithm（GA）
optimization
