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A Genetic Algorithm Based Multi-Objective Thermal Design Optimization of Liquid Cooled Offset Strip Fin Heat Sinks

[+] Author Affiliations
Sidy Ndao, Yoav Peles, Michael K. Jensen

Rensselaer Polytechnic Institute, Troy, NY

Paper No. HT2009-88039, pp. 755-763; 9 pages
  • ASME 2009 Heat Transfer Summer Conference collocated with the InterPACK09 and 3rd Energy Sustainability Conferences
  • Volume 1: Heat Transfer in Energy Systems; Thermophysical Properties; Heat Transfer Equipment; Heat Transfer in Electronic Equipment
  • San Francisco, California, USA, July 19–23, 2009
  • Conference Sponsors: Heat Transfer Division
  • ISBN: 978-0-7918-4356-7 | eISBN: 978-0-7918-3851-8
  • Copyright © 2009 by ASME


A genetic algorithm based multi-objective thermal design optimization of liquid cooled offset strip fin heat sinks is presented. Using water and HFE-7000 as coolants, Matlab’s genetic algorithm and direct search toolbox functions were utilized to determine the optimal thermal design of the offset strip fin heat sink based on the total thermal resistance and power consumption under constant pressure drop. For a relatively small fin length, the total thermal resistance decreases with increasing fin length and aspect ratio α. For larger fin lengths, the total thermal resistance increases with increasing fin length whereas the power consumption continuously increases with increasing fin length and aspect ratio α for a given pressure drop. A plot of the Pareto front indicates a trade-off between the total thermal resistance and pumping power consumption.

Copyright © 2009 by ASME



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