APPLICATION OF HYBRID GENETIC ALGORITHM IN AEROELASTIC MULTIDISCIPLINARY DESIGN OPTIMIZATION OF LARGE AIRCRAFT

被引:0
|
作者
唐长红 [1 ]
万志强 [2 ]
机构
[1] School of Mechanical and Engineering,Northwestern Polytechnical University
[2] School of Aeronautic Science and Engineering,Beijing University of Aeronautics and Astronautics
基金
中国国家自然科学基金;
关键词
aeroelasticity; multidisciplinary design optimization; genetic/gradient-based hybrid algorithm; large aircraft;
D O I
10.16356/j.1005-1120.2013.02.004
中图分类号
V211.4 [飞机空气动力学]; TP18 [人工智能理论];
学科分类号
0801 ; 080103 ; 080104 ; 081104 ; 0812 ; 0835 ; 1405 ;
摘要
The genetic/gradient-based hybrid algorithm is introduced and used in the design studies of aeroelastic optimization of large aircraft wings to attain skin distribution,stiffness distribution and design sensitivity.The program of genetic algorithm is developed by the authors while the gradient-based algorithm borrows from the modified method for feasible direction in MSC/NASTRAN software.In the hybrid algorithm,the genetic algorithm is used to perform global search to avoid to fall into local optima,and then the excellent individuals of every generation optimized by the genetic algorithm are further fine-tuned by the modified method for feasible direction to attain the local optima and hence to get global optima.Moreover,the application effects of hybrid genetic algorithm in aeroelastic multidisciplinary design optimization of large aircraft wing are discussed,which satisfy multiple constraints of strength,displacement,aileron efficiency,and flutter speed.The application results show that the genetic/gradient-based hybrid algorithm is available for aeroelastic optimization of large aircraft wings in initial design phase as well as detailed design phase,and the optimization results are very consistent.Therefore,the design modifications can be decreased using the genetic/gradient-based hybrid algorithm.
引用
收藏
页码:109 / 117
页数:9
相关论文
共 50 条
  • [31] Optimization design of a hybrid mechanism based on genetic algorithm
    Zhang, Ke
    IEEE ICMA 2006: PROCEEDING OF THE 2006 IEEE INTERNATIONAL CONFERENCE ON MECHATRONICS AND AUTOMATION, VOLS 1-3, PROCEEDINGS, 2006, : 2346 - 2351
  • [32] Multiobjective optimization design of a hybrid actuator with genetic algorithm
    Zhang, Ke
    NEURAL INFORMATION PROCESSING, PT 3, PROCEEDINGS, 2006, 4234 : 845 - 855
  • [33] Multidisciplinary electronic package design and optimization methodology based on genetic algorithm
    Suwa, Tohru
    Hadim, Hamid
    IEEE TRANSACTIONS ON ADVANCED PACKAGING, 2007, 30 (03): : 402 - 410
  • [34] On maximizing solution diversity in a multiobjective multidisciplinary genetic algorithm for design optimization
    Gunawan, S
    Farhang-Mehr, A
    Azarm, S
    MECHANICS BASED DESIGN OF STRUCTURES AND MACHINES, 2004, 32 (04) : 491 - 514
  • [35] Aeroelastic Optimization Design of the Global Stiffness for a Joined Wing Aircraft
    Li, Xuyang
    Wan, Zhiqiang
    Wang, Xiaozhe
    Yang, Chao
    APPLIED SCIENCES-BASEL, 2021, 11 (24):
  • [36] Structural Sizing, Aeroelastic Analysis, and Optimization in Aircraft Conceptual Design
    Cavagna, L.
    Ricci, S.
    Riccobene, L.
    JOURNAL OF AIRCRAFT, 2011, 48 (06): : 1840 - 1855
  • [37] Improvement of the Aircraft Traffic Management Advisor Optimization Using a Hybrid Genetic Algorithm
    Adel Soheili
    Habib Rajabi Mashhadi
    International Journal of Computational Intelligence Systems, 2016, 9 : 559 - 571
  • [38] Improvement of the Aircraft Traffic Management Advisor Optimization Using a Hybrid Genetic Algorithm
    Soheili, Adel
    Mashhadi, Habib Rajabi
    INTERNATIONAL JOURNAL OF COMPUTATIONAL INTELLIGENCE SYSTEMS, 2016, 9 (03) : 559 - 571
  • [39] Studies on the influence of spar position on aeroelastic optimization of a large aircraft wing
    WAN ZhiQiangLIU DongYueTANG ChangHong YANG Chao School of Aeronautic Science and EngineeringBeihang UniversityBeijing China
    Science China(Technological Sciences), 2012, 55 (01) : 117 - 124
  • [40] Application of improved hybrid genetic algorithm on optimum design
    Bai, Lili
    Jiang, Fengguo
    PROCEEDINGS OF FIRST INTERNATIONAL CONFERENCE OF MODELLING AND SIMULATION, VOL II: MATHEMATICAL MODELLING, 2008, : 247 - 251