Topology Optimization for Large‐Scale Unsteady Flow With the Building‐Cube Method
ABSTRACT This study proposes a novel framework for solving large‐scale unsteady flow topology optimization problems. While most previous studies on fluid topology optimization assume steady‐state flows, an increasing number of recent studies deal with unsteady flows, which are more general in engine...
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| Vydáno v: | International journal for numerical methods in engineering Ročník 126; číslo 5 |
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| Hlavní autoři: | , , , |
| Médium: | Journal Article |
| Jazyk: | angličtina |
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Hoboken, USA
John Wiley & Sons, Inc
15.03.2025
Wiley Subscription Services, Inc |
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| ISSN: | 0029-5981, 1097-0207 |
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| Abstract | ABSTRACT
This study proposes a novel framework for solving large‐scale unsteady flow topology optimization problems. While most previous studies on fluid topology optimization assume steady‐state flows, an increasing number of recent studies deal with unsteady flows, which are more general in engineering. However, unsteady flow topology optimization involves solving the governing and adjoint equations of a time‐evolving system, which requires a significant 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 one of the hierarchical Cartesian mesh methods. Although the BCM has been confirmed to have excellent scalability and is suitable for massively parallel computing, there are no studies that have applied it to unsteady flow topology optimization. In the proposed method, the governing and adjoint equations are discretized by a cell‐centered finite volume method based on the BCM, which can achieve high parallel efficiency even with a fine mesh. The effectiveness of the proposed method for large‐scale computing is discussed through several examples of optimization and verification of computational efficiency by weak scaling. |
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| AbstractList | This study proposes a novel framework for solving large‐scale unsteady flow topology optimization problems. While most previous studies on fluid topology optimization assume steady‐state flows, an increasing number of recent studies deal with unsteady flows, which are more general in engineering. However, unsteady flow topology optimization involves solving the governing and adjoint equations of a time‐evolving system, which requires a significant 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 one of the hierarchical Cartesian mesh methods. Although the BCM has been confirmed to have excellent scalability and is suitable for massively parallel computing, there are no studies that have applied it to unsteady flow topology optimization. In the proposed method, the governing and adjoint equations are discretized by a cell‐centered finite volume method based on the BCM, which can achieve high parallel efficiency even with a fine mesh. The effectiveness of the proposed method for large‐scale computing is discussed through several examples of optimization and verification of computational efficiency by weak scaling. ABSTRACT This study proposes a novel framework for solving large‐scale unsteady flow topology optimization problems. While most previous studies on fluid topology optimization assume steady‐state flows, an increasing number of recent studies deal with unsteady flows, which are more general in engineering. However, unsteady flow topology optimization involves solving the governing and adjoint equations of a time‐evolving system, which requires a significant 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 one of the hierarchical Cartesian mesh methods. Although the BCM has been confirmed to have excellent scalability and is suitable for massively parallel computing, there are no studies that have applied it to unsteady flow topology optimization. In the proposed method, the governing and adjoint equations are discretized by a cell‐centered finite volume method based on the BCM, which can achieve high parallel efficiency even with a fine mesh. The effectiveness of the proposed method for large‐scale computing is discussed through several examples of optimization and verification of computational efficiency by weak scaling. |
| Author | Kato, Junji Hoshiba, Hiroya Nishiguchi, Koji Katsumata, Ryohei |
| Author_xml | – sequence: 1 givenname: Ryohei surname: Katsumata fullname: Katsumata, Ryohei organization: Nagoya University – sequence: 2 givenname: Koji orcidid: 0000-0003-2264-2840 surname: Nishiguchi fullname: Nishiguchi, Koji email: nishiguchi.koji.r9@f.mail.nagoya-u.ac.jp organization: Nagoya University – sequence: 3 givenname: Hiroya surname: Hoshiba fullname: Hoshiba, Hiroya organization: Nagoya University – sequence: 4 givenname: Junji surname: Kato fullname: Kato, Junji organization: Nagoya University |
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This study proposes a novel framework for solving large‐scale unsteady flow topology optimization problems. While most previous studies on fluid... This study proposes a novel framework for solving large‐scale unsteady flow topology optimization problems. While most previous studies on fluid topology... |
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| SubjectTerms | building‐cube method Computational efficiency Computing costs Finite volume method large‐scale computing Optimization Topology optimization Unsteady flow |
| Title | Topology Optimization for Large‐Scale Unsteady Flow With the Building‐Cube Method |
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