Inverse homogenization using the topological derivative
ISSN: 0264-4401
Article publication date: 28 September 2021
Issue publication date: 1 February 2022
Abstract
Purpose
The purpose of this study is to solve the inverse homogenization problem, or so-called material design problem, using the topological derivative concept.
Design/methodology/approach
The optimal topology is obtained through a relaxed formulation of the problem by replacing the characteristic function with a continuous design variable, so-called density variable. The constitutive tensor is then parametrized with the density variable through an analytical interpolation scheme that is based on the topological derivative concept. The intermediate values that may appear in the optimal topologies are removed by penalizing the perimeter functional.
Findings
The optimization process benefits from the intermediate values that provide the proposed method reaching to solutions that the topological derivative had not been able to find before. In addition, the presented theory opens the path to propose a new framework of research where the topological derivative uses classical optimization algorithms.
Originality/value
The proposed methodology allows us to use the topological derivative concept for solving the inverse homogenization problem and to fulfil the optimality conditions of the problem with the use of classical optimization algorithms. The authors solved several material design examples through a projected gradient algorithm to show the advantages of the proposed method.
Keywords
Acknowledgements
This research was partially supported by Serra Húnter Research Program (Spain), PID-UTN (Research and Development Program of the National Technological University, Argentina) and CONICET (National Council for Scientific and Technical Research, Argentina). The supports of these agencies are gratefully acknowledged.
Citation
Ferrer, À. and Giusti, S.M. (2022), "Inverse homogenization using the topological derivative", Engineering Computations, Vol. 39 No. 1, pp. 337-353. https://doi.org/10.1108/EC-08-2021-0435
Publisher
:Emerald Publishing Limited
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