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Research Papers

User Preference-Oriented Design of Heat Dissipating Elements for Densely Packaged Transistors With Consideration of Design Robustness

[+] Author and Article Information
Mark Christian E. Manuel

School of Mechanical and Manufacturing
Engineering,
Mapua Institute of Technology,
Muralla Street,
Intramuros 1002, Manila, Philippines
e-mail: marchm.090407@gmail.com

Kuan Sung Hsu

R&D Division,
San Shing Fastech Corp.,
No. 355-6, Sec. 3, Zhongshan Road,
Guiren District,
Tainan City 711, Taiwan
e-mail: larry79131@gmail.com

Shu-Ping Lin

Department of Mechanical Engineering,
Chung Yuan Christian University,
200 Chungpei Road,
Chungli 32023, Taoyuan, Taiwan
e-mail: lin9923203@gmail.com

Po Ting Lin

Mem. ASME
Department of Mechanical Engineering,
Chung Yuan Christian University,
200 Chungpei Road,
Chungli 32023, Taoyuan, Taiwan;
Department of Mechanical Engineering,
National Taiwan University of Science
and Technology,
43 Keelung Road, Sec. 4,
Taipei 10607, Taiwan
e-mail: potinglin223@gmail.com

1Corresponding author.

Contributed by the Heat Transfer Division of ASME for publication in the JOURNAL OF THERMAL SCIENCE AND ENGINEERING APPLICATIONS. Manuscript received March 8, 2016; final manuscript received December 13, 2016; published online March 7, 2017. Assoc. Editor: Gamal Refaie-Ahmed.

J. Thermal Sci. Eng. Appl 9(2), 021012 (Mar 07, 2017) (9 pages) Paper No: TSEA-16-1057; doi: 10.1115/1.4035837 History: Received March 08, 2016; Revised December 13, 2016

Tremendous efforts had been given to ensure proper heat dissipation in electronics cooling but very seldom consider design robustness and user preferences in design principles of the heat-dissipating devices. Multi-objective optimization problems are one of the preferences elicitation tools that could be used and is highly visual on the costs and benefits associated in choosing different preferences. It would be better if a wider temperature range is offered for thermal management schemes and is made available if the user desires. It would also be sought upon if automatic determination of the user preference for a wider range of varying performance were available. In this paper, a liquid impinging heat exchanger with a thermoelectric module was chosen as the example of how this paradigmatic scheme was implemented using black box models. An orthogonal sampling method was applied with three parameters considered. The temperature at the interface between the chip surface and the liquid impinging thermoelectric cooler (LITEC) is taken as the desired response. A response surface was generated using Kriging method, after which, a multi-objective optimization problem was then formulated to include robust definition and user preference for energy efficiency. The optimal operation parameters of the inlet flow velocity and the thermoelectric (TE) chip control voltage were found for various levels of heat loading conditions and different considerations of design robustness and energy awareness.

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Figures

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Fig. 1

Design of the impinging geometry: (a) basis for the geometry of the liquid impinging heat exchanger and (b) engineering drawing of the heat sink design (unit: mm) [31]

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Fig. 2

The heat sink assembly has (a) an O-ring being placed between (b) the heat sink design, which was shown in Fig. 1(c), and (c) the circular metal plate. Another (d) metal plate, which is assembled at the bottom of (c), has a square cut at the middle for the installation of (e) the TE chip

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Fig. 3

Experimental setup: (a) cross section of the entire measurement tests and (b) image of the heat sink assembly

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Fig. 4

Positions of sampling points on investigated space

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Fig. 5

Semivariograms for the (a) mean and (b) standard deviation of Tb (h stands for the distance between design points; γ is the value of semivariogram) [11]

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Fig. 6

Response isosurface of the baseplate temperature under various operation parameters (each factor was normalized between the smallest and highest values)

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Fig. 7

Isosurface plots of the multi-objective functions under different preferences on energy saving: (a) w=0, (b) w=0.1, (c) w=0.2, (d) w=0.3, (e) w=0.4, (f) w=0.5, (g) w=0.6, (h) w=0.7, (i) w=0.8, (j) w=0.9, (k) w=1, and (l) legend of each subfigure

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Fig. 8

Optimal settings for robust designs under different hotplate temperature and energy-aware user preference weights: (a) isometric view reflecting verified optimal points [11], (b) T¯hp−V¯ perspective, and (c) T¯hp−Q¯ perspective

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