Correlation between hole insertion criteria in a boundary element and level set based topology optimisation method

被引:10
|
作者
Ullah, B. [1 ]
Trevelyan, J. [1 ]
机构
[1] Univ Durham, Sch Engn & Comp Sci, Durham DH1 3LE, England
关键词
Structural optimisation; Boundary element method; Level set method; NURBS; EVOLUTIONARY STRUCTURAL OPTIMIZATION; SENSITIVITY-ANALYSIS; SHAPE OPTIMIZATION; ALGORITHMS; REPRESENTATION; DESIGN; NURBS; MESH;
D O I
10.1016/j.enganabound.2013.08.003
中图分类号
T [工业技术];
学科分类号
08 ;
摘要
The research work presented in this paper is based on the correlation between two hole insertion criteria in a boundary element method (BEM) and level set method (LSM) based structural topology optimisation scheme for 2D elastic problems. The hole insertion criteria used in this work are based on the von Mises stress and the topological derivative approaches. During the optimisation process holes are automatically inserted in the design domain using each of the two criteria. The LSM is used to provide an implicit description of the structural geometry, and is also capable of automatically handling topological changes, i.e. holes merging with each other or with the boundary. The evolving structural geometry (i.e. the zero level set contours) is represented by NURBS, providing a smooth geometry throughout the optimisation process and completely eliminate jagged edges. In addition the optimal NURBS geometry can be used directly in other design processes. Four different benchmark examples are considered in this study and each is tested against the two hole insertion criteria. The results obtained validate the proposed optimisation method and we demonstrate a clear correlation between the two hole insertion criteria. (C) 2013 Elsevier Ltd. All rights reserved.
引用
收藏
页码:1457 / 1470
页数:14
相关论文
共 50 条
  • [1] A boundary element and level set based topology optimisation using sensitivity analysis
    Ullah, B.
    Trevelyan, J.
    ENGINEERING ANALYSIS WITH BOUNDARY ELEMENTS, 2016, 70 : 80 - 98
  • [2] A new hole insertion method for level set based structural topology optimization
    Dunning, Peter D.
    Kim, H. Alicia
    INTERNATIONAL JOURNAL FOR NUMERICAL METHODS IN ENGINEERING, 2013, 93 (01) : 118 - 134
  • [3] A topology optimisation for three-dimensional acoustics with the level set method and the fast multipole boundary element method
    Isakari, Hiroshi
    Kuriyama, Kohei
    Harada, Shinya
    Yamada, Takayuki
    Takahashi, Toru
    Matsumoto, Toshiro
    MECHANICAL ENGINEERING JOURNAL, 2014, 1 (04):
  • [4] An immersed boundary element method for level-set based topology optimization
    Yamasaki, Shintaro
    Yamada, Takayuki
    Matsumoto, Toshiro
    INTERNATIONAL JOURNAL FOR NUMERICAL METHODS IN ENGINEERING, 2013, 93 (09) : 960 - 988
  • [5] Structural optimisation based on the boundary element and level set methods
    Ullah, B.
    Trevelyan, J.
    Matthews, P. C.
    COMPUTERS & STRUCTURES, 2014, 137 : 14 - 30
  • [6] A level set-based topology optimization method using the Boundary Element Method in three dimension
    Shichi, S., 1600, Japan Society of Mechanical Engineers (78):
  • [7] An isogeometric boundary element approach for topology optimization using the level set method
    Oliveira, Hugo Luiz
    de Castro e Andrade, Heider
    Leonel, Edson Denner
    APPLIED MATHEMATICAL MODELLING, 2020, 84 : 536 - 553
  • [8] A boundary element approach for topology optimization problem using the level set method
    Abe, Kazuhisa
    Kazama, Shunsuke
    Koro, Kazuhiro
    COMMUNICATIONS IN NUMERICAL METHODS IN ENGINEERING, 2007, 23 (05): : 405 - 416
  • [9] Topology optimization of multimaterial distribution based on isogeometric boundary element and piecewise constant level set method
    Jiang, Fuhang
    Chen, Leilei
    Wang, Jie
    Miao, Xiaofei
    Chen, Haibo
    COMPUTER METHODS IN APPLIED MECHANICS AND ENGINEERING, 2022, 390
  • [10] A Hilbertian projection method for constrained level set-based topology optimisation
    Wegert, Zachary J.
    Roberts, Anthony P.
    Challis, Vivien J.
    STRUCTURAL AND MULTIDISCIPLINARY OPTIMIZATION, 2023, 66 (09)