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基于改进多目标遗传算法的舰尾紊流模拟方法

陶杨 韩维

陶杨, 韩维. 基于改进多目标遗传算法的舰尾紊流模拟方法[J]. 北京航空航天大学学报, 2015, 41(3): 443-448. doi: 10.13700/j.bh.1001-5965.2014.0198
引用本文: 陶杨, 韩维. 基于改进多目标遗传算法的舰尾紊流模拟方法[J]. 北京航空航天大学学报, 2015, 41(3): 443-448. doi: 10.13700/j.bh.1001-5965.2014.0198
TAO Yang, HAN Wei. Carrier airwake simulation methods based on improved multi-objective genetic algorithm[J]. Journal of Beijing University of Aeronautics and Astronautics, 2015, 41(3): 443-448. doi: 10.13700/j.bh.1001-5965.2014.0198(in Chinese)
Citation: TAO Yang, HAN Wei. Carrier airwake simulation methods based on improved multi-objective genetic algorithm[J]. Journal of Beijing University of Aeronautics and Astronautics, 2015, 41(3): 443-448. doi: 10.13700/j.bh.1001-5965.2014.0198(in Chinese)

基于改进多目标遗传算法的舰尾紊流模拟方法

doi: 10.13700/j.bh.1001-5965.2014.0198
基金项目: 国家自然科学基金资助项目(61032001)
详细信息
    作者简介:

    陶杨(1985—),男,江苏吴江人,博士生,timothy1205@163.com

    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.

  • 中图分类号: TP202.7

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

  • 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.

     

  • [1] Moorhouse D J, Woodcock R J.Background information and user guide for MIL-F-8785C,military specification-flying qualities of piloted airplanes,AD-A11942[R].1982.
    [2] 胡国才, 王奇,刘湘一,等.舰尾流对舰载机着舰轨迹和动态响应的影响研究[J].飞行力学,2009,27(6):18-21. Hu G C,Wang Q,Liu X Y,et al.Influence of carrier airwake on carrier-based aircraft landing trajectory and dynamic response[J].Flight Dynamics,2009,27(6):18-21(in Chinese).
    [3] 蒋康博, 刘超,袁东.近舰区风场建模与着舰仿真分析[J].飞行力学,2010,28(6):11-15. Jiang K B,Liu C Yuan D.Close-carrier-area wind field modeling and carrier-landing simulation analysis[J].Flight Dynamics,2010,28(6):11-15(in Chinese).
    [4] 吕开东,李新飞, 姜迈,等.舰载机着舰过程的舰尾气流场数值仿真分析[J].飞行力学,2013,31(1):18-23. Lü K D,Li X F,Jiang M,et al.Simulation analysis on carrier landing disturbance model[J].Flight Dynamics,2013,31(1):18-23(in Chinese).
    [5] 赵震炎,肖业伦, 施毅坚.Dryden大气紊流模型的数字仿真技术[J].航空学报,1986,7(5):433-443. Zhao Z Y,Xiao Y L,Shi Y J.A digital simulation technique for Dryden atmospheric turbulence model[J].Acta Aeronautica et Astronautica Sinica,1986,7(5):433-443(in Chinese).
    [6] 屈香菊,李勇. 一种改进的紊流风模型及其仿真算法[J].系统仿真学报,2004,16(1):10-13. Qu X J,Li Y.An improved model of atmospheric turbulence and its simulation algorithm[J].Journal of System Simulation,2004,16(1):10-13(in Chinese).
    [7] 马东立. 大气紊流数字仿真的改进方法[J].北京航空航天大学学报,1990,16(3):57-63. Ma D L.An improvement of the digital simulation method for atmospheric turbulence[J].Journal of Beijing University of Aeronautics and Astronautics,1990,16(3):57-63(in Chinese).
    [8] 吴扬,姜守达. 非质点飞行器模型的大气紊流仿真[J].沈阳工业大学学报,2010,32(1):22-26. Wu Y,Jiang S D.Simulation of atmospheric turbulence for non-particle aircraft model[J].Journal of Shenyang University of Technology,2010,32(1):22-26(in Chinese).
    [9] Reid L D. Correlation model for turbulence along the glide path[J].Journal of Aircraft,1978,15(1):13-20.
    [10] 申晓宁,郭毓, 陈庆伟,等.一种保持群体多样性的多目标遗传算法[J].控制与决策,2008,23(12):1435-1440. Shen X N,Guo Y,Chen Q W,et al.Multi objective optimization genetic algorithm keeping diversity of population[J].Control and Decision,2008,23(12):1435-1440(in Chinese).
    [11] Schaffer J D. Multiple objective optimizations with vector evaluated genetic algorithms[C]//Proceedings of the 1st International Conference on Genetic Algorithms.New Jersey:Lawrence Erlbaum Associates,1985:93-100.
    [12] Fonseca C M. Multi-objective genetic algorithms with application to control engineering problems[D].UK:The University of Shefield,1995.
    [13] Horn J, Nafpliotis N,Goldberg D E.A niched pareto genetic algorithm for multi-objective optimization[C]//Proceedings of the 1st IEEE Conference on Evolutionary Computation.New York:IEEE,1994:82-87.
    [14] Srinivas N, Deb K.Multi-objective function optimization using non-dominated sorting genetic algorithms[J].Evolutionary Computation,1995,2(2):221-248.
    [15] Zitzler E, Thiele L.Multi-objective evolutionary algorithms: a comparative case study and the strength Pareto approach[J].IEEE Trans on Evolutionary Computation,1999,3(4):257-271.
    [16] Deb K, Pratap A,Agarwal R B.A fast and elitist multi-objective genetic algorithms:NSGA2[J].IEEE Transactions on Evolutionary Computation,2002,6(2):182-197.
    [17] Deb K, Agrawal R B.Simulated binary crossover for continuous search space[J].Complex Systems,1995,9(3):1-15.
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出版历程
  • 收稿日期:  2014-04-10
  • 网络出版日期:  2015-03-20

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