An optimization strategy for customizable global elastic deformation of unit cell-based metamaterials with variable material section discretization

Andreas Thalhamer, Mathias Fleisch, Clara Schuecker, Peter Filipp Fuchs, Sandra Schlögl, Michael Berer

Research output: Contribution to journalArticleResearchpeer-review

Abstract

Metamaterials with their distinctive unit cell-based periodic architecture feature a wide range of possible properties with unusual characteristics and a high potential for optimization. Due to their complex interaction between unit cell geometry and material properties, as well as their inherent multi-scale nature, suitable optimization strategies need to be developed for metamaterials. One potential approach is to optimize the distribution of unit cells within a part to achieve a predefined deformation response. However, a significant challenge lies in determining the appropriate number and distribution of areas with varying properties (material sections) to facilitate an efficient optimization. In this study, a variable material section discretization scheme is presented, which is aimed at automatically updating the discretization to enhance the efficiency of metamaterial optimizations. This scheme is implemented as an extension to a previously proposed Finite Element simulation-based optimization framework for unit cell-based metamaterials. The framework includes a numerical homogenization method and interpolation scheme for efficiently correlating unit cell parameters with homogenized material properties, coupled with a black-box optimization method. In the present study, the previously proposed framework was extended to incorporate a scheme for monitoring and adjusting the material section discretization during the optimization process. To assess the effectiveness of the implemented routine, it was tested in conjunction with a genetic algorithm for optimizing the parameter distribution of a 2D tri-anti-chiral metamaterial to match a predefined lateral deformation under load.
Original languageEnglish
Article number103817
Number of pages17
JournalAdvances in Engineering Software
Volume199.2025
Issue numberJanuary
DOIs
Publication statusPublished - 12 Nov 2024

Bibliographical note

Publisher Copyright: © 2024 The Author(s)

Keywords

  • Finite Element Method
  • Genetic Algorithm
  • Homogenization
  • Optimization
  • Simulation

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