Development of a high performance air cooled heat sink for multi-chip modules

Kitajo, Sakae; Takeda, Yoichi; Kurokawa, Y.; Ohta, Taro; Mizunashi, H.

doi:10.1109/stherm.1992.172849

Cited by 12 publications

(2 citation statements)

References 4 publications

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“…With the advent of high heat-dissipating and densely packed electronics, there is increasing need to optimize the existing cooling solutions and to design newer and more efficient ones. To date, air cooling remains the most widely used approach, owing to its inherent simplicity, low cost, and low maintenance [4]. Extended surfaces, such as pin-fins and parallel-plate fins, aid the heat transfer from a hot surface to the surroundings and are often employed in conjunction with air cooling [5].…”

Section: Introductionmentioning

confidence: 99%

Optimization Under Uncertainty Applied to Heat Sink Design

Bodla¹,

Murthy²,

Garimella

2012

Journal of Heat Transfer

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Optimization under uncertainty (OUU) is a powerful methodology used in design and optimization to produce robust, reliable designs. Such an optimization methodology, employed when the input quantities of interest are uncertain, yields output uncertainties that help the designer choose appropriate values for input parameters to produce safe designs. Apart from providing basic statistical information, such as mean and standard deviation in the output quantities, uncertainty-based optimization produces auxiliary information, such as local and global sensitivities. The designer may thus decide the input parameter(s) to which the output quantity of interest is most sensitive, and thereby design better experiments based on just the most sensitive input parameter(s). Another critical output of such a methodology is the solution to the inverse problem, i.e., finding the allowable uncertainty (range) in the input parameter(s), given an acceptable uncertainty (range) in the output quantities of interest. We apply optimization under uncertainty to the problem of heat transfer in fin heat sinks with uncertainties in geometry and operating conditions. The analysis methodology is implemented using DAKOTA, an open-source design and analysis kit. A response surface is first generated which captures the dependence of the quantity of interest on inputs. This response surface is then used to perform both deterministic and probabilistic optimization of the heat sink, and the results of the two approaches are compared.

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Section: Introductionmentioning

confidence: 99%

Optimization Under Uncertainty Applied to Heat Sink Design

Bodla¹,

Murthy²,

Garimella

2012

Journal of Heat Transfer

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“…In addition, local power densities are more difficult to be managed, thus making thermal management more challenging. Many technologies [1][2][3][4][5][6][7][8][9][10][11][12][13][14][15][16][17][18][19][20] ranging from air cooling to refrigeration have been proposed for CPU cooling in the last years but their cooling significance was not well quantified in relationship to peak power density cooling, therefore there is a need to focus electronics cooling research and development on the most promising and cost effective technologies. As well known, the primary objective of thermal management in microelectronics applications is to keep the die junction temperature (T j ) below acceptable limits in order to ensure device performance and reliability.…”

Section: Introductionmentioning

confidence: 99%

Thermal Performance and Key Challenges for Future CPU Cooling Technologies

Sauciuc

Prasher

Chang

et al. 2005

Advances in Electronic Packaging, Parts A, B, and C

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Over the past few years, thermal design for cooling microprocessors has become increasingly challenging mainly because of an increase in both average power density and local power density, commonly referred to as “hot spots”. The current air cooling technologies present diminishing returns, thus it is strategically important for the microelectronics industry to establish the research and development focus for future non air-cooling technologies. This paper presents the thermal performance capability for enabling and package based cooling technologies using a range of “reasonable” boundary conditions. In the enabling area a few key main building blocks are considered: air cooling, high conductivity materials, liquid cooling (single and two-phase), thermoelectric modules integrated with heat pipes/vapor chambers, refrigeration based devices and the thermal interface materials performance. For package based technologies we present only the microchannel building block (cold plate in contact with the back-side of the die). It will be shown that as the hot spot density factor increases, package based cooling technologies should be considered for more significant cooling improvements. In addition to thermal performance, a summary of the key technical challenges are presented in the paper. This paper was also originally published as part of the Proceedings of the ASME 2005 Heat Transfer Summer Conference.

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