Variable stiffness optimization algorithm for vibration optimization of variable-stiffness composite plates

被引:12
作者
Jing, Zhao [1 ]
Duan, Lei [1 ]
Li, Biao [1 ]
机构
[1] Northwestern Polytech Univ, Sch Aeronaut, Xian 710072, Shaanxi, Peoples R China
基金
中国国家自然科学基金;
关键词
Variable stiffness optimization algorithm; Variable -stiffness composite plates; Vibration; Fundamental frequency; MAXIMUM FUNDAMENTAL-FREQUENCY; BUCKLING OPTIMIZATION; LAMINATION PARAMETERS; DESIGN OPTIMIZATION; CURVILINEAR FIBERS; RECTANGULAR-PLATES; PANELS; FRAMEWORK; INPLANE; MODES;
D O I
10.1016/j.apm.2022.12.003
中图分类号
T [工业技术];
学科分类号
08 ;
摘要
A novel variable stiffness optimization (VSO) algorithm is proposed for vibration optimiza-tion of variable-stiffness composite (VSC) plates uisng linear variation fiber path function. Firstly, an independent 2D-sampling optimization method (2DSOind) is employed to gener-ate a good initial point. Then, optimization is conducted in multiple phases, within each phase, the problem is simplified to an approximately one-dimensional linear search prob-lem. By dividing the fiber angles into two groups, VSO algorithm designs the laminate between two fiber angle groups sequentially and iteratively, making the stiffness of VSC plate stiffened part by part. Lastly, the VSC plate is redesigned accounting for the cur-vature constraint. The sequential permutation search (SPS) algorithm is coupled into VSO to optimize one group of fiber angles whilst the angles of another group are fixed dur-ing the iteration. Under a variety of boundary conditions, the free vibration frequencies of VSC plates are optimized using VSO. In comparison to conventional layerwise optimization (LO) and genetic algorithm (GA), the present results demonstrate much higher efficiency and similar robustness. Moreover, the maximum fundamental frequency of VSC plates can be improved by about 10% in comparison to straight fiber laminates.(c) 2022 Elsevier Inc. All rights reserved.
引用
收藏
页码:569 / 592
页数:24
相关论文
共 58 条
  • [21] Nonlinear free vibration of laminated composite rectangular plates with curvilinear fibers
    Houmat, A.
    [J]. COMPOSITE STRUCTURES, 2013, 106 : 211 - 224
  • [22] An efficient reanalysis assisted optimization for variable-stiffness composite design by using path functions
    Huang, Guanxin
    Wang, Hu
    Li, Guangyao
    [J]. COMPOSITE STRUCTURES, 2016, 153 : 409 - 420
  • [23] Jing Z., 2022, MECH ADV MATER STRUC, V29, P4614
  • [24] Lamination Parameter-Based Two-Dimension Sampling Optimization Method for Stacking Sequence Design of Composite Laminates
    Jing, Zhao
    [J]. AIAA JOURNAL, 2022, 60 (05) : 3225 - 3250
  • [25] Optimal design of laminated composite cylindrical shells for maximum fundamental frequency using sequential permutation search with mode identification
    Jing, Zhao
    [J]. COMPOSITE STRUCTURES, 2022, 279
  • [26] Design of curved composite panels for maximum buckling load using sequential permutation search algorithm
    Jing, Zhao
    Sun, Qin
    Liang, Ke
    Zhang, Yongjie
    [J]. STRUCTURES, 2021, 34 : 4169 - 4192
  • [27] Buckling optimization of composite rectangular plates by sequential permutation search with bending-twisting correction
    Jing, Zhao
    Sun, Qin
    Zhang, Yongjie
    Liang, Ke
    [J]. APPLIED MATHEMATICAL MODELLING, 2021, 100 : 751 - 779
  • [28] Stacking sequence optimization of composite cylindrical panels by sequential permutation search and Rayleigh-Ritz method
    Jing, Zhao
    Sun, Qin
    Zhang, Yongjie
    Liang, Ke
    Li, Xu
    [J]. EUROPEAN JOURNAL OF MECHANICS A-SOLIDS, 2021, 88
  • [29] Stacking sequence optimization of doubly-curved laminated composite shallow shells for maximum fundamental frequency by sequential permutation search algorithm
    Jing, Zhao
    Sun, Qin
    Zhang, Yongjie
    Liang, Ke
    Li, Xu
    [J]. COMPUTERS & STRUCTURES, 2021, 252
  • [30] An investigation on design of signs in composite laminates to control bending-twisting coupling effects using sign optimization algorithm
    Jing, Zhao
    Chen, Jianqiao
    [J]. STRUCTURAL AND MULTIDISCIPLINARY OPTIMIZATION, 2019, 60 (05) : 2131 - 2156