Three-field floating projection topology optimization of continuum structures

被引:30
|
作者
Huang, Xiaodong [1 ]
Li, Weibai [1 ]
机构
[1] Swinburne Univ Technol, Sch Engn, Dept Mech Engn & Prod Design Engn, Hawthorn, Vic 3122, Australia
基金
澳大利亚研究理事会;
关键词
Topology optimization; Implicit floating projection constraint; Robust formulation; Shell-infill structures; LEVEL SET METHOD; SHELL-INFILL STRUCTURES; LENGTH SCALE; DESIGN; HOMOGENIZATION; CODE;
D O I
10.1016/j.cma.2022.115444
中图分类号
T [工业技术];
学科分类号
08 ;
摘要
Topology optimization using the variable substitution among three fields can achieve a design with desired solid and/or void features. This paper proposes a three-field floating projection topology optimization (FPTO) method using the linear material interpolation. The implicit floating projection constraint is used as an engine for generating a 0/1 solution at the design field. The substitution filtering and projection schemes enhance the length scale and solid/void features to accelerate the formation of structural topology in the physical field. Meanwhile, the three-field FPTO method can be extended to robust formulation, which obtains the eroded, intermediate, and dilated designs with the same topology. The most distinct feature of the FPTO method lies in the adoption of the linear material interpolation scheme, which makes many topology optimization problems straightforward. As an example, the proposed three-field FPTO algorithm is further applied to the design of shell-infill structures using the linear multi-material interpolation scheme. The distribution of the shell material is generated through a simple filtering scheme, and the shell thickness is accurately controlled by the filter radius. Numerical examples are presented to demonstrate the effectiveness and advantage of the proposed three-field FPTO method. (c) 2022 Elsevier B.V. All rights reserved.
引用
收藏
页数:18
相关论文
共 50 条
  • [31] Topology optimization of continuum structures under multiple constraints
    Bian, Bing-Chuan
    Sui, Yun-Kang
    Jisuan Lixue Xuebao/Chinese Journal of Computational Mechanics, 2010, 27 (05): : 781 - 788
  • [32] Continuum topology optimization of buckling-sensitive structures
    Rahmatalla, S
    Swan, CC
    AIAA JOURNAL, 2003, 41 (06) : 1180 - 1189
  • [33] Robust topology optimization for continuum structures with random loads
    Liu, Jie
    Wen, Guilin
    Qing, Qixiang
    Li, Fangyi
    Xie, Yi Min
    ENGINEERING COMPUTATIONS, 2018, 35 (02) : 710 - 732
  • [34] A new bionics method for topology optimization of continuum structures
    Cai, K.
    Zhang, H. W.
    CMESM 2006: Proceedings of the 1st International Conference on Enhancement and Promotion of Computational Methods in Engineering Science and Mechanics, 2006, : 639 - 643
  • [35] Evolutionary topology optimization of continuum structures with stress constraints
    Zhao Fan
    Liang Xia
    Wuxing Lai
    Qi Xia
    Tielin Shi
    Structural and Multidisciplinary Optimization, 2019, 59 : 647 - 658
  • [36] Topology optimization of continuum structures under hybrid uncertainties
    Seyyed Ali Latifi Rostami
    Ali Ghoddosian
    Structural and Multidisciplinary Optimization, 2018, 57 : 2399 - 2409
  • [37] Wind load modeling for topology optimization of continuum structures
    Ramzi Zakhama
    Mostafa M. Abdalla
    Zafer Gürdal
    Hichem Smaoui
    Structural and Multidisciplinary Optimization, 2010, 42 : 157 - 164
  • [38] Topology optimization of continuum structures under hybrid uncertainties
    Rostami, Seyyed Ali Latifi
    Ghoddosian, Ali
    STRUCTURAL AND MULTIDISCIPLINARY OPTIMIZATION, 2018, 57 (06) : 2399 - 2409
  • [39] Three-field topology optimization of single-phase phononic crystals with desired bandgaps for elastic wave manipulation
    Yan, Gengwang
    Huang, Xiaodong
    Li, Yingli
    Li, Weibai
    Yao, Song
    ENGINEERING STRUCTURES, 2025, 326
  • [40] A geometry projection method for the topology optimization of plate structures
    Zhang, Shanglong
    Norato, Julian A.
    Gain, Arun L.
    Lyu, Naesung
    STRUCTURAL AND MULTIDISCIPLINARY OPTIMIZATION, 2016, 54 (05) : 1173 - 1190