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Concurrent material and structure optimization of multiphase hierarchical systems within a continuum micromechanics

Tarun Gangwar1,2, Dominik Schillinger2

  • 1Department of Civil, Environmental, and Geo-Engineering, University of Minnesota, Twin Cities, USA.

Structural and Multidisciplinary Optimization : Journal of the International Society for Structural and Multidisciplinary Optimization
|November 1, 2021
PubMed
Summary

This study introduces a novel optimization framework for hierarchical materials, enabling efficient material and structure design across multiple length scales. The approach uses continuum micromechanics for cost-effective, scalable material optimization.

Keywords:
Concurrent designContinuum micromechanicsHierarchical systemsHomogenizationMultiphase topology optimizationSensitivity analysis

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Area of Science:

  • Multiphase hierarchical systems
  • Continuum micromechanics
  • Computational material science

Background:

  • Hierarchical materials exhibit complex behavior across multiple length scales.
  • Optimizing these systems requires computationally intensive methods.
  • Understanding multiscale material properties is crucial for advanced engineering.

Purpose of the Study:

  • To develop a concurrent material and structure optimization framework for multiphase hierarchical systems.
  • To leverage homogenization estimates for efficient multiscale analysis.
  • To demonstrate the framework's computational feasibility and engineering applicability.

Main Methods:

  • Utilizing homogenization estimates from continuum micromechanics.
  • Implementing a "discretization-free" constraint optimization approach.
  • Developing a framework with computational cost independent of hierarchical scales.

Main Results:

  • The analytical nature of homogenization estimates enables efficient material optimization.
  • New benchmark tests with multiple material scales become computationally feasible.
  • The framework successfully reproduces self-optimizing mechanisms observed in natural hierarchical systems like bamboo.

Conclusions:

  • The proposed framework offers a computationally efficient solution for optimizing multiphase hierarchical materials.
  • This approach significantly reduces the computational burden associated with multiscale material design.
  • The framework has broad potential for engineering applications, inspired by natural designs.