Implementation of topological derivative in the moving morphable components approach

We propose a new topology optimization approach based on the moving morphable components (MMC) framework with an explicitly described a layout through a finite number of components. The position and shape values of each component were defined as design variables. In this study, a method was develope...

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Published inFinite elements in analysis and design Vol. 134; pp. 16 - 26
Main Authors Takalloozadeh, Meisam, Yoon, Gil Ho
Format Journal Article
LanguageEnglish
Published Amsterdam Elsevier B.V 15.10.2017
Elsevier BV
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ISSN0168-874X
1872-6925
1872-6925
DOI10.1016/j.finel.2017.05.008

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Summary:We propose a new topology optimization approach based on the moving morphable components (MMC) framework with an explicitly described a layout through a finite number of components. The position and shape values of each component were defined as design variables. In this study, a method was developed by utilizing topological derivative. Instead of performing a discrete sensitivity analysis based on finite element methods, a topological derivative was used to calculate the first derivative of an objective function with respect to the shape and position of the components. The obtained derivative was validated via discrete sensitivity analysis. The topological derivative formulation has been well developed in recent years for different structural and non-structural problems. Utilizing this powerful tool enabled the MMC approach to easily solve various types of topology optimization problems. Herein, the presented method is illustrated through several topology optimization problems such as stress-based and thermo-mechanical topology optimization. •Topological derivative is utilized in moving morphable components framework.•Sensitivity of strain energy with respect to change in shape and position of the components is calculated.•Optimum layout for thermo-elastic structures considering both temperature changes and mechanical loading is obtained.•Stress constrained topology optimization problems are solved.
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ISSN:0168-874X
1872-6925
1872-6925
DOI:10.1016/j.finel.2017.05.008