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.
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The authors would like to acknowledge the Toyota Research Institute of North America for funding this work.
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Lohan, D.J., Dede, E.M. & Allison, J.T. Topology optimization for heat conduction using generative design algorithms. Struct Multidisc Optim 55, 1063–1077 (2017). https://doi.org/10.1007/s00158-016-1563-6
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DOI: https://doi.org/10.1007/s00158-016-1563-6