Topology optimization of multiphase material structures under design dependent pressure loads

Gao, Tong; Zhang, Weihong

doi:10.1051/ijsmdo/2009002

Cited by 4 publications

(2 citation statements)

References 24 publications

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“…Recently, Lee and Martins (2012) improved upon the method of Du and Olhoff (2004b), by removing the need for the predefinition of isoline endpoints. Likewise, Gao and Zhang (2009) developed a pressure updating scheme for contact problems with solid weight pressure loading. Finally, Zhang et al (2008) presented a boundary search scheme where the sensitivity of the loading to the element density can be ignored since the loads are determined from real element boundaries, rather than isolines.…”

Section: Introductionmentioning

confidence: 99%

On the effect of fluid-structure interactions and choice of algorithm in multi-physics topology optimisation

Munk

Kipouros

Vio

et al. 2018

Finite Elements in Analysis and Design

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This article presents an optimisation framework for the compliance minimisation of structures subjected to design-dependent pressure loads. A finite element solver coupled to a Lattice Boltzmann method is employed, such that the effect of the fluid-structure interactions on the optimised design can be considered. It is noted that the main computational expense of the algorithm is the Lattice Boltzmann method. Therefore, to improve the computational efficiency and to assess the effect of the fluid-structure interactions on the final optimised design, the degree of coupling is changed. Several successful topology optimisation algorithms exist with thousands of associated publications in the literature. However, only a small portion of these are applied to real-world problems, with even fewer offering a comparison of methodologies. This is especially important for problems involving fluid-structure interactions, where discrete and continuous methods can provide different advantages. The goal of this research is to couple two key disciplines, fluids and structures, into a topology optimisation framework, which shows fast convergence for multi-physics optimisation problems. This is achieved by offering a comparison of three popular, but competing, optimisation methodologies. The needs for the exploration of larger design spaces and to produce innovative designs make meta-heuristic algorithms less efficient for this task. A coupled analysis, where the fluid and structural mechanics are updated, provides superior results compared with an uncoupled analysis approach, however

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Section: Introductionmentioning

confidence: 99%

On the effect of fluid-structure interactions and choice of algorithm in multi-physics topology optimisation

Munk

Kipouros

Vio

et al. 2018

Finite Elements in Analysis and Design

View full text Add to dashboard Cite

show abstract

“…) (Yang andChuang, 1994, Bendsøe andSigmund, 1999) (Allaire et al, 2004) (Yamada et al, 2010) (Yamada et al, 2011) (Isakari et al, 2014, Noguchi et al, 2015) (Otomori et al, 2012) (Sigmund, 2001, Yin and Ananthasuresh, 2001, Gao and Zhang, 2009, Luo et al, 2010) Wang, 2004, Wang et al, 2015) ( Cui et al, 2016) 2 3 4 5 6 2.…”

mentioning

confidence: 99%

Topology optimization for multi-material structures based on the level set method

Kishimoto

Noguchi

Sato

et al. 2017

Transactions of the JSME (In Japanese)

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Topology optimization is the most flexible type of structural optimization method. This method has been applied in a variety of physics problems dealing with a multitude of design problems. In a given design problem, however, the optimization problem often has conflicting evaluative functions, such as the need for high rigidity in combination with minimal weight. The difficulty of simultaneously achieving high performance for two or more functions may be further compounded because current topology optimization methods typically only deal with a single material. On the other hand, when multiple kinds of materials having various properties can be selected for use, the range of a designer's choices is increased and an appropriate solution that greatly improves product functions may be achieved. Thus, this paper presents a new topology optimization method for multi-materials that obtains high-performance configurations. We apply the Multi-Material Level Set (MM-LS) topology description model in the topology optimization method, which uses a total of n level set functions to represent n materials, plus the void phase. The advantage of the MM-LS model is that clear optimal configurations are obtained and the design sensitivity for multi-material structures can be easily calculated. The level set functions that are design variables are updated using the topological derivatives, which also function as design sensitivities, and we derive the topological derivatives for multiple materials. Through several numerical examples, we demonstrate the validity of the proposed method.

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Introduction

Deng¹,

Wu²,

Liu³

2017

Topology Optimization Theory for Laminar Flow

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Topology optimization of multiphase material structures under design dependent pressure loads

Cited by 4 publications

References 24 publications

On the effect of fluid-structure interactions and choice of algorithm in multi-physics topology optimisation

On the effect of fluid-structure interactions and choice of algorithm in multi-physics topology optimisation

Topology optimization for multi-material structures based on the level set method

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