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Research Papers: Electronic Cooling

Nonlocal Modeling and Swarm-Based Design of Heat Sinks

[+] Author and Article Information
Ivan Catton

Morrin-Gier-Martinelli
Heat Transfer Memorial Laboratory,
Department of Mechanical
and Aerospace Engineering,
School of Engineering and Applied Science,
University of California, Los Angeles,
48-121 Engineering IV,
420 Westwood Plaza,
Los Angeles, CA 90095-1597

1Corresponding author.

Contributed by the Heat Transfer Division of ASME for publication in the JOURNAL OF HEAT TRANSFER. Manuscript received March 22, 2013; final manuscript received August 21, 2013; published online October 25, 2013. Assoc. Editor: Giulio Lorenzini.

J. Heat Transfer 136(1), 011401 (Oct 25, 2013) (11 pages) Paper No: HT-13-1158; doi: 10.1115/1.4025300 History: Received June 29, 2012; Revised February 26, 2013

Cooling electronic chips to satisfy the ever-increasing heat transfer demands of the electronics industry is a perpetual challenge. One approach to addressing this is through improving the heat rejection ability of air-cooled heat sinks, and nonlocal thermal-fluid-solid modeling based on volume averaging theory (VAT) has allowed for significant strides in this effort. A number of optimization methods for heat sink designers who model heat sinks with VAT can be envisioned due to VAT's singular ability to rapidly provide solutions, when compared to computational fluid dynamics (CFD) approaches. The particle swarm optimization (PSO) method appears to be an attractive multiparameter heat transfer device optimization tool; however, it has received very little attention in this field compared to its older population-based optimizer cousin, the genetic algorithm (GA). The PSO method is employed here to optimize smooth and scale-roughened straight-fin heat sinks modeled with VAT by minimizing heat sink thermal resistance for a specified pumping power. A new numerical design tool incorporates the PSO method with a VAT-based heat sink solver. Optimal designs are obtained with this new tool for both types of heat sinks, the performances of the heat sink types are compared, the performance of the PSO method is discussed with reference to the GA method, and it is observed that this new method yields optimal designs much quicker than traditional approaches. This study demonstrates, for the first time, the effectiveness of combining a VAT-based nonlocal thermal-fluid-solid model with population-based optimization methods, such as PSO, to design heat sinks for electronics cooling applications. The VAT-based nonlocal modeling method provides heat sink design capabilities, in terms of solution speed and model rigor, that existing modeling methods do not match.

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References

Figures

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Fig. 1

Illustration of a straight-fin heat sink with tapered, (a) smooth and (b) scale-roughed surface fins

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Fig. 2

Flow chart of the VAT-based heat sink simulation routine

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Fig. 3

Flow chart of PSO algorithm [62]

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Fig. 4

Evolution of thermal resistance during the (a) PSO and (b) GA optimizations of a smooth surface straight-fin heat sink. Thin, light colored lines indicate the individual trials while thick, dark colored lines indicate the average of the ten trials.

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Fig. 5

Evolution of the scaled design parameters during the (a) PSO and (b) GA optimizations of a smooth surface straight-fin heat sink. Thin, light colored lines indicate the individual trials while thick, dark colored lines indicate the average of the ten trials.

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Fig. 6

Evolution of thermal resistance during the (a) PSO and (b) GA optimizations of a scale-roughened straight-fin heat sink

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Fig. 7

Evolution of the scaled design parameters during the (a) PSO and (b) GA optimizations of a scale-roughened straight-fin heat sink

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Fig. 8

Nonlocal fluid (left) and solid (right) temperature fields for the optimal scale-roughened straight-fin heat sink found by the PSO after its (a) first, (b) fourth, and (c) final iteration, along with those for the (d) optimal smooth straight-fin heat sink. The fully developed velocity field profiles and the 90 °C contour lines are indicated superimposed on the fluid and solid temperature fields, respectively.

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