Structural and Multidisciplinary Optimization

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

Topology optimization for heat conduction using generative design algorithms

  • Danny J. LohanEmail author
  • Ercan M. Dede
  • James T. Allison


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.


Topology optimization Generative algorithms Conductive heat transfer 



The authors would like to acknowledge the Toyota Research Institute of North America for funding this work.


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Copyright information

© Springer-Verlag Berlin Heidelberg 2016

Authors and Affiliations

  • Danny J. Lohan
    • 1
    Email author
  • 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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