Structural and Multidisciplinary Optimization

, Volume 55, Issue 3, pp 1063–1077 | Cite as

Topology optimization for heat conduction using generative design algorithms

  • Danny J. Lohan
  • Ercan M. Dede
  • James T. Allison
RESEARCH PAPER
  • 567 Downloads

Abstract

In this article we present a new approach to topological design for steady-state heat conduction. The method capitalizes on the use of a generative algorithm to represent topology, resulting in a decrease in the number of variables in the design description. Using a generative algorithm as a design abstraction, the optimization technique is targeted to dendritic topologies that are known to perform well for heat conduction. Specifically, a traditional topology optimization technique (SIMP) is confirmed to produce branching characteristics in optimal designs. The Space Colonization Algorithm, which can generate similar topological patterns, is selected for in-depth investigation. A genetic algorithm drives generation of design candidates, providing a highly diversified search of the target design space. Finally, several synthesized optimal designs for steady-state heat conduction, derived using the described algorithms, are compared using commercial finite element software.

Keywords

Topology optimization Generative algorithms Conductive heat transfer 

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Copyright information

© Springer-Verlag Berlin Heidelberg 2016

Authors and Affiliations

  • Danny J. Lohan
    • 1
  • Ercan M. Dede
    • 2
  • James T. Allison
    • 1
  1. 1.Department of Industrial and Enterprise Systems EngineeringUniversity of Illinois at Urbana-ChampaignUrbanaUSA
  2. 2.Electronics Research DepartmentToyota Research Institute of North AmericaAnn ArborUSA

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