Large-Scale Topology Optimization for Unsteady Flow Using the Building-Cube Method

被引:0
|
作者
Katsumata R. [1 ]
Nishiguchi K. [1 ]
Shimada T. [2 ]
Hoshiba H. [1 ]
Kato J. [1 ]
机构
[1] Nagoya University, Japan
[2] Kobe University, Japan
关键词
Building-cube method; Finite volume method; Topology optimization; Unsteady flow;
D O I
10.11421/jsces.2023.20230007
中图分类号
学科分类号
摘要
In recent years, topology optimization methods have been applied not only to structural problems but also to fluid flow problems. Most of the previous studies assume steady-state flow. In contrast, this paper focuses on topology optimization for unsteady flow, which is more general from an engineering point of view. However, unsteady flow topology optimization involves solving the governing and adjoint equations of a time-evolving system, which requires a huge computational cost for topology optimization with a fine mesh. Therefore, we propose a large-scale unsteady flow topology optimization based on the building-cube method (BCM), which is suitable for massively parallel computing. BCM is one of the hierarchical Cartesian mesh methods and is confirmed to have very good scalability. The governing equations are discretized by a cell-centered finite volume method based on the BCM. The objective sensitivity is obtained by the continuous adjoint method. Several numerical examples are demonstrated to discuss its applicability to large-scale computations. © 2023 by the Japan Society for Computational Engineering and Science.
引用
收藏
相关论文
共 50 条
  • [31] Large-scale level set topology optimization for elasticity and heat conduction
    Sandilya Kambampati
    Carolina Jauregui
    Ken Museth
    H. Alicia Kim
    Structural and Multidisciplinary Optimization, 2020, 61 : 19 - 38
  • [32] Large-scale level set topology optimization for elasticity and heat conduction
    Kambampati, Sandilya
    Jauregui, Carolina
    Museth, Ken
    Kim, H. Alicia
    STRUCTURAL AND MULTIDISCIPLINARY OPTIMIZATION, 2020, 61 (01) : 19 - 38
  • [33] A multi-regional MFSE topology optimization method for large-scale structures with arbitrary design domains
    Sun, Zhaoyou
    Yuan, Tingxi
    Liu, Wenbo
    He, Jiaqi
    Sui, Tiejun
    Luo, Yangjun
    ADVANCES IN ENGINEERING SOFTWARE, 2024, 198
  • [34] An efficient topology optimization algorithm for large-scale three-dimensional structures
    Vitorino, Alfredo
    Gomes, Francisco A. M.
    OPTIMIZATION AND ENGINEERING, 2024, : 1281 - 1316
  • [35] CUBE: A scalable framework for large-scale industrial simulations
    Jansson, Niclas
    Bale, Rahul
    Onishi, Keiji
    Tsubokura, Makoto
    INTERNATIONAL JOURNAL OF HIGH PERFORMANCE COMPUTING APPLICATIONS, 2019, 33 (04) : 678 - 698
  • [36] Topology Optimization of Large-Scale 3D Morphing Wing Structures
    Jensen, Peter Dorffler Ladegaard
    Wang, Fengwen
    Dimino, Ignazio
    Sigmund, Ole
    ACTUATORS, 2021, 10 (09)
  • [37] Topology optimization using the lattice Boltzmann method for unsteady natural convection problems
    Yuta Tanabe
    Kentaro Yaji
    Kuniharu Ushijima
    Structural and Multidisciplinary Optimization, 2023, 66
  • [38] Topology optimization using the lattice Boltzmann method for unsteady natural convection problems
    Tanabe, Yuta
    Yaji, Kentaro
    Ushijima, Kuniharu
    STRUCTURAL AND MULTIDISCIPLINARY OPTIMIZATION, 2023, 66 (05)
  • [39] Topology optimization of large-scale structures subjected to stationary random excitation: An efficient optimization procedure integrating pseudo excitation method and mode acceleration method
    Zhang, Weihong
    Liu, Hu
    Gao, Tong
    COMPUTERS & STRUCTURES, 2015, 158 : 61 - 70
  • [40] Large-Scale Truss Topology and Sizing Optimization by an Improved Genetic Algorithm with Multipoint Approximation
    Dong, Tianshan
    Chen, Shenyan
    Huang, Hai
    Han, Chao
    Dai, Ziqi
    Yang, Zihan
    APPLIED SCIENCES-BASEL, 2022, 12 (01):