北京航空航天大学学报 ›› 2015, Vol. 41 ›› Issue (3): 443-448.doi: 10.13700/j.bh.1001-5965.2014.0198

• 论文 • 上一篇    下一篇

基于改进多目标遗传算法的舰尾紊流模拟方法

陶杨1,2, 韩维1   

  1. 1. 海军航空工程学院 飞行器工程系, 烟台 264001;
    2. 海军装备研究院, 上海 200436
  • 收稿日期:2014-04-10 出版日期:2015-03-20 发布日期:2015-04-02
  • 通讯作者: 韩维(1970—),男,湖南湘潭人,教授,Luckydevilhan@163.com,主要研究方向为飞行器动力学. E-mail:Luckydevilhan@163.com
  • 作者简介:陶杨(1985—),男,江苏吴江人,博士生,timothy1205@163.com
  • 基金资助:
    国家自然科学基金资助项目(61032001)

Carrier airwake simulation methods based on improved multi-objective genetic algorithm

TAO Yang1,2, HAN Wei1   

  1. 1. Department of Airborne Vehicle Engineering, Naval Aeronautical and Astronautical University, Yantai 264001, China;
    2. Naval Academy of Armament, Shanghai 200436, China
  • Received:2014-04-10 Online:2015-03-20 Published:2015-04-02

摘要: 为提高舰尾紊流自由大气紊流分量仿真的可信度,提出了一种紊流数值模拟的新方法.首先,使用带有修正系数的Euler前向差分格式表示各个方向的紊流序列,同时结合智能算法的思想,把紊流相关性检验中的均方差误差和相关函数误差作为待优化目标函数,将修正系数的选择看成一个多目标优化问题,并采用改进的多目标遗传算法进行求解.最后,通过仿真算例验证了本文方法的正确性与合理性,计算结果表明该方法可以根据不同的采样步长灵活地生成所需紊流.尤其在小步长情况下,亦可得到很好符合理论值的紊流序列,可以满足虚拟飞行实验的要求.

关键词: 舰尾流, 自由大气紊流, 多目标优化, 遗传算法, 误差函数

Abstract: A new numerical turbulence simulation method to enhance the credibility of simulation of carrier airwake free-air turbulence components has been presented. At first, the turbulence sequence of each direction was presented as the Euler forward different format with correction factors. Meanwhile, associated with the thought of intelligence algorithm, the mean squared error and correlation function error in turbulence correlation test were regarded as the optimized objective functions. And the selection of correction factors was treated as a multi-objective optimization problem. The correction factors were determined by improving multi-objective genetic algorithm. At last, the validity and rationality of this method were verified by simulation cases. The calculation results show that the required turbulence sequences can be generated flexibly with different sampling steps. Especially in case of some small sampling step, the simulated turbulence sequences fit the theoretical values very well, and the method can meet the requirement of virtual flight test.

Key words: carrier airwake, free-air random turbulence, multi-objective optimization, genetic algorithm, error functions

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