基于遗传算法的超声速二维进气道优化设计  

On Optimization Design Genetic Algorithms of Two-dimensional Supersonic Inlet Based

作　　者：韩文俊[1] 吴虎[1] 郭莹[1] 

机构地区：[1]西北工业大学动力与能源学院,西安710072

出　　处：《科学技术与工程》2009年第4期943-949,共7页Science Technology and Engineering

摘　　要：首先介绍了基本遗传算法,并由基本遗传算法演化出小生境遗传算法。应用简单的测试函数对两种遗传算法进行测试,对两种遗传算法进行比较。然后应用小生境遗传算法对二维超声速进气道进行优化设计。在单目标优化设计中,以最大总压恢复系数为优化目标,在多目标优化设计中分别顾及到总压回复系数要求最大和增压比也要很高。在对进气道的优化设计之后,对单目标优化和多目标优化的结果进行比较。Simple genetic algorithms is introduced at first, and niche genetic algorithms evolve from simple genetic algorithms. A simple test function is used to test the two GAs, and compare them. And then optimization design of the two-dimensional supersonic inlet is carried out with niche gas. In singular-objective optimization design, the maximal total pressure recovery coefficient is the objective function; and in the multi-objective, not only is the maximal total pressure recovery coefficient is the objective function but also the boost pressure ratio. The results of the two are compared, after the optimization design

关 键 词：遗传算法 小生境 进气道 优化设计 

分 类 号：V211.42[航空宇航科学与技术—航空宇航推进理论与工程]