Genetic algorithm design of a 3D printed heat sink

Tong Wu, Burak Ozpineci, Curtis Ayers

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

21 Scopus citations

Abstract

In this paper, a genetic algorithm- (GA-) based approach is discussed for designing heat sinks based on total heat generation and dissipation for a pre-specified size and shape. This approach combines random iteration processes and genetic algorithms with finite element analysis (FEA) to design the optimized heat sink. With an approach that prefers survival of the fittest, a more powerful heat sink can be designed which can cool power electronics more efficiently. Some of the resulting designs can only be 3D printed due to their complexity. In addition to describing the methodology, this paper also includes comparisons of different cases to evaluate the performance of the newly designed heat sink compared to commercially available heat sinks.

Original languageEnglish
Title of host publication2016 IEEE Applied Power Electronics Conference and Exposition, APEC 2016
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages3529-3536
Number of pages8
ISBN (Electronic)9781467383936
DOIs
StatePublished - May 10 2016
Event31st Annual IEEE Applied Power Electronics Conference and Exposition, APEC 2016 - Long Beach, United States
Duration: Mar 20 2016Mar 24 2016

Publication series

NameConference Proceedings - IEEE Applied Power Electronics Conference and Exposition - APEC
Volume2016-May

Conference

Conference31st Annual IEEE Applied Power Electronics Conference and Exposition, APEC 2016
Country/TerritoryUnited States
CityLong Beach
Period03/20/1603/24/16

Keywords

  • 3D Printing
  • Cold Plate
  • Genetic Algorithm
  • Liquid Cooled Heat sink
  • Thermal management

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