A generalized DCT compression based density method for topology optimization of 2D and 3D continua

被引:15
|
作者
Zhou, Pingzhang [1 ]
Du, Jianbin [2 ]
Lu, Zhenhua [1 ]
机构
[1] Tsinghua Univ, Dept Automot Engn, Beijing, Peoples R China
[2] Tsinghua Univ, Sch Aerosp Engn, Beijing, Peoples R China
关键词
Topology optimization; Discrete cosine transform (DCT); Digital image compression; Density method; MORPHABLE COMPONENTS MMC; HOMOGENIZATION; FILTERS;
D O I
10.1016/j.cma.2018.01.051
中图分类号
T [工业技术];
学科分类号
08 ;
摘要
In this paper, a novel topology optimization method based on discrete cosine transform (DCT) and density interpolation is proposed for layout designs of 2D and 3D continua. As one of the most frequently used transforms in digital image compression, the DCT may significantly reduce the number of design variables in density-based topology optimization, and can hereby improve the efficiency of solving the topology optimization problems to a great extent. This way the DCT compression based density method (DCDM) could be quite attractive in the topology optimization of large-scale engineering structures where a huge number of design variables may present. Effectiveness and efficiency of the proposed method is demonstrated with several 2D and 3D examples including both mechanical and heat conduction problems. Through these examples, some interesting features of DCDM are revealed and discussed. Since high frequency components are inherently filtered in DCDM, there is no need to introduce additional density filter or sensitivity filter in the present model. It is shown by numerical examples that there is no sharp corners present in the final optimized layout obtained by DCDM, which is beneficial when considering the stress of structures. (C) 2018 Elsevier B.V. All rights reserved.
引用
收藏
页码:1 / 21
页数:21
相关论文
共 50 条
  • [1] Explicit control of 2D and 3D structural complexity by discrete variable topology optimization method
    Liang, Yuan
    Yan, XinYu
    Cheng, GengDong
    COMPUTER METHODS IN APPLIED MECHANICS AND ENGINEERING, 2022, 389
  • [2] FEniTop: a simple FEniCSx implementation for 2D and 3D topology optimization supporting parallel computing
    Jia, Yingqi
    Wang, Chao
    Zhang, Xiaojia Shelly
    STRUCTURAL AND MULTIDISCIPLINARY OPTIMIZATION, 2024, 67 (08)
  • [3] Topology optimization of 2D continua for minimum compliance using parallel computing
    Department of Mechanical and Nuclear Engineering, Pennsylvania State University, University Park, PA 16802, United States
    不详
    Struct. Mutltidiscip. Opt., 2006, 2 (121-132): : 121 - 132
  • [4] Topology optimization of 2D continua for minimum compliance using parallel computing
    Mahdavi, A.
    Balaji, R.
    Frecker, M.
    Mockensturm, E. M.
    STRUCTURAL AND MULTIDISCIPLINARY OPTIMIZATION, 2006, 32 (02) : 121 - 132
  • [5] Topology optimization of periodic 3D heat transfer problems with 2D design
    Lundgren, Jonas
    Klarbring, Anders
    Lundgren, Jan-Erik
    Thore, Carl-Johan
    STRUCTURAL AND MULTIDISCIPLINARY OPTIMIZATION, 2019, 60 (06) : 2295 - 2303
  • [6] Topology optimization of periodic 3D heat transfer problems with 2D design
    Jonas Lundgren
    Anders Klarbring
    Jan-Erik Lundgren
    Carl-Johan Thore
    Structural and Multidisciplinary Optimization, 2019, 60 : 2295 - 2303
  • [7] Topology optimization of 2D continua for minimum compliance using parallel computing
    A. Mahdavi
    R. Balaji
    M. Frecker
    E. M. Mockensturm
    Structural and Multidisciplinary Optimization, 2006, 32 : 121 - 132
  • [8] Design Applicable 3D Microfluidic Functional Units Using 2D Topology Optimization with Length Scale Constraints
    Guo, Yuchen
    Pan, Hui
    Wadbro, Eddie
    Liu, Zhenyu
    MICROMACHINES, 2020, 11 (06) : 1 - 20
  • [9] Pixel-based shape optimization in 2D using constrained density-based topology optimization
    Zegard, Tomas
    Salinas, Diego
    Silva, Emilio C. N.
    ENGINEERING WITH COMPUTERS, 2025,
  • [10] Highly efficient density-based topology optimization using DCT-based digital image compression
    Zhou, Pingzhang
    Du, Jianbin
    Lu, Zhenhua
    STRUCTURAL AND MULTIDISCIPLINARY OPTIMIZATION, 2018, 57 (01) : 463 - 467