Numerical investigation for optimizing segmented micro-channel heat sink by Taguchi-Grey method
Document Type
Article
Publication Date
1-1-2018
Abstract
The scale-down trend increases the chips’ density and the high power handling capability generates unnecessary heat which can disrupt the reliability of the electronic devices. Therefore, various types of cooling solution have been proposed to enhance heat dissipation from the electronic devices. One of the solution is using inexpensive straight-channel heat sink. However, the presence of large temperature gradient between the upstream and downstream in the straight-channel can shorten the life span of the device and subsequently reduce the reliability. In this study, a novel segmented micro-channel is introduced to improve the thermal performance of the straight-channel heat sink. Computational fluid dynamic analysis are performed to investigate the performance of the micro-channel heat sink. The bottom of the heat sink is subjected to a constant heat flux condition and water is used as a coolant. Following that, Taguchi-grey method is applied to optimize the design of the segmented micro-channel. The effect of fin width, fin length, fin transverse distance, number of segments, channel width and mass flow rate on the specific performance, variation of temperature and pressure drop are investigated. The results indicate that a three segments of segmented micro-channel, fin width-1 mm, fin length-2 mm, fin transverse distance-5 mm and channel width-1 mm have successfully enhance the heat transfer performance with minimum pressure drop. It is also found that the optimized micro-channel heat sink is able to cool the chip with heat flux of 800 W to 56.6 °C and pumping power of 0.13 W using 15 gs −1 of water.
Keywords
Micro-channel, Heat sink, Thermal management, Segmented micro-channel, Computational fluid dynamics
Divisions
fac_eng
Funders
Science fund Grant No. 03-02-11-SF2016 from Ministry of Science, Technology and Innovation, Malaysia
Publication Title
Applied Energy
Volume
222
Publisher
Elsevier