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TECHNICAL PAPERS

Multiobjective Optimal Placement of Convectively and Conductively Cooled Electronic Components on Printed Wiring Boards

[+] Author and Article Information
Nestor V. Queipo

Applied Computing Institute, Faculty of Engineering, University of Zulia, Maracaibo, Zulia 4011-A-526, Venezuelae-mail: nqueipo@luz.ve

Guy F. Gil

School of Mechanical Engineering, Faculty of Engineering, University of Zulia, Maracaibo, Zulia 4011-A-526, Venezuela,e-mail: ggil@luz.ve

J. Electron. Packag 122(2), 152-159 (Oct 20, 1999) (8 pages) doi:10.1115/1.483148 History: Received July 10, 1999; Revised October 20, 1999
Copyright © 2000 by ASME
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References

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Figures

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Schematic of the heat transfer configuration of interest
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Illustration of the solution methodology
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Model of the heat transfer configuration of interest
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Evolution of the lowest failure rate value along the search process considering γ=1.0 and (wλ=1.0,wg=0.0) (Pareto optimization)
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Evolution of the lowest failure rate value along the search process considering γ=1.25 and (wλ=1.0,wg=0.0) (Pareto optimization)
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Legend used for graphically identifying the heat generation rates and thermal sensitivities of the heat sources when reporting temperature distributions among them
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Temperature distribution among the heat sources considering γ=1.0 and (wλ=1.0,wg=0.0) (Pareto optimization)
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Best arrangements obtained by the CSGA using Pareto optimization for the cases of (wλ,wg): (1.0, 0.0), (0.5, 0.5), and (0.0, 1.0) (linear case)
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Best arrangements obtained by the CSGA using Pareto optimization for the cases of (wλ,wg): (1.0, 0.0), (0.5, 0.5), and (0.0, 1.0) (nonlinear case)
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Temperature distribution among the heat sources for a selected Pareto optimal solution; γ=1.0 and (wλ=0.5,wg=0.5)
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Single attribute utility function for failure rate
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Single attribute utility function for wiring length
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Maximum temperatures of the heat sources associated with the best arrangement uncovered by the CSGA; f1=9.179-03fr Mh−1 and f2=8.56 m (multiattribute utility analysis)

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