Journal Article10.1007/S00158-013-0956-Z
A survey of structural and multidisciplinary continuum topology optimization: post 2000
TL;DR: Topology optimization is the process of determining the optimal layout of material and connectivity inside a design domain this paper, which is the same as the problem of finding the optimal configuration of a set of components.
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Abstract: Topology optimization is the process of determining the optimal layout of material and connectivity inside a design domain. This paper surveys topology optimization of continuum structures from the year 2000 to 2012. It focuses on new developments, improvements, and applications of finite element-based topology optimization, which include a maturation of classical methods, a broadening in the scope of the field, and the introduction of new methods for multiphysics problems. Four different types of topology optimization are reviewed: (1) density-based methods, which include the popular Solid Isotropic Material with Penalization (SIMP) technique, (2) hard-kill methods, including Evolutionary Structural Optimization (ESO), (3) boundary variation methods (level set and phase field), and (4) a new biologically inspired method based on cellular division rules. We hope that this survey will provide an update of the recent advances and novel applications of popular methods, provide exposure to lesser known, yet promising, techniques, and serve as a resource for those new to the field. The presentation of each method's focuses on new developments and novel applications.
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Citations
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TL;DR: Two different evolutionary approaches, based on the von Mises stress and the Strain Energy criteria, have been implemented and analyzed and the related results have been compared.
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FEA Structural Optimization Based on Metagraphs
Diego Montoya-Zapata,Diego A. Acosta,Oscar Ruiz-Salguero,David Sanchez-Londono +3 more
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Topology optimization using a kriging-assisted genetic algorithm with a novel level set representation approach
Mitsuo Yoshimura,Koji Shimoyama,Takashi Misaka,Shigeru Obayashi +3 more
- 01 Jan 2016
TL;DR: This paper presents a novel representation method to obtain the distribution of level set function with a reasonable number of design variables and confirms that the proposed representation method enables to represent flow channels that balance both objective functions and GA captures the trade-off between two objective functions.
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