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
Hlavní autoři: Katsumata, Ryohei, Nishiguchi, Koji, Hoshiba, Hiroya, Kato, Junji
Médium: Journal Article
Jazyk:angličtina
Vydáno: Hoboken, USA John Wiley & Sons, Inc 15.03.2025
Wiley Subscription Services, Inc
Témata:
building‐cube method
Computational efficiency
Computing costs
Finite volume method
large‐scale computing
Optimization
Topology optimization
Unsteady flow
ISSN:0029-5981, 1097-0207
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Shrnutí: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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ISSN:0029-5981
1097-0207
DOI:10.1002/nme.70016