Optimization of SiO2 nanoparticle mass concentration and heat input on a loop heat pipe

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Abstract

This study presents the effect of nanoparticle mass concentration and heat input based on the total thermal resistance (Rth) of loop heat pipe (LHP), employed for PC-CPU cooling. In this study, silica nanoparticles (SiO2) in water with particle mass concentration ranged from 0% (pure water) to 3% is considered as the working fluid within the LHP. The experimental design and optimization is accomplished by the design of experimental tool, Response Surface Methodology (RSM). The results show that the nanoparticle mass concentration and the heat input have significant effect on the Rth of LHP. For a given heat input, the Rth is found to decrease with the increase of the nanoparticle mass concentration up to 0.5% and increased thereafter. It is also found that the Rth is decreased when the heat input is increased from 20 W to 60 W. The results are optimized with the objective of minimizing the Rth, using Design-Expert software, and the optimized nanoparticle mass concentration and heat input are 0.48% and 59.97 W, respectively, the minimum Rth being 2.66 (C/W). The existence of an optimum nanoparticle mass concentration and heat input are the predominant factors for the improvement in the thermal performance of nanofluid-charged LHP.

Original languageEnglish
Pages (from-to)238-250
Number of pages13
JournalCase Studies in Thermal Engineering
Volume6
DOIs
Publication statusPublished - 01 Jan 2015

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Heat pipes
Nanoparticles
Water
Hot Temperature
Heat resistance
Silicon Dioxide
Design of experiments
Program processors
Silica
Cooling
Fluids

All Science Journal Classification (ASJC) codes

  • Engineering (miscellaneous)
  • Fluid Flow and Transfer Processes

Cite this

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title = "Optimization of SiO2 nanoparticle mass concentration and heat input on a loop heat pipe",
abstract = "This study presents the effect of nanoparticle mass concentration and heat input based on the total thermal resistance (Rth) of loop heat pipe (LHP), employed for PC-CPU cooling. In this study, silica nanoparticles (SiO2) in water with particle mass concentration ranged from 0{\%} (pure water) to 3{\%} is considered as the working fluid within the LHP. The experimental design and optimization is accomplished by the design of experimental tool, Response Surface Methodology (RSM). The results show that the nanoparticle mass concentration and the heat input have significant effect on the Rth of LHP. For a given heat input, the Rth is found to decrease with the increase of the nanoparticle mass concentration up to 0.5{\%} and increased thereafter. It is also found that the Rth is decreased when the heat input is increased from 20 W to 60 W. The results are optimized with the objective of minimizing the Rth, using Design-Expert software, and the optimized nanoparticle mass concentration and heat input are 0.48{\%} and 59.97 W, respectively, the minimum Rth being 2.66 (C/W). The existence of an optimum nanoparticle mass concentration and heat input are the predominant factors for the improvement in the thermal performance of nanofluid-charged LHP.",
author = "Prem Gunnasegaran and Abdullah, {Mohd Zulkifly} and Yusoff, {Mohd Zamri} and Abdullah, {Siti Fazlili}",
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AB - This study presents the effect of nanoparticle mass concentration and heat input based on the total thermal resistance (Rth) of loop heat pipe (LHP), employed for PC-CPU cooling. In this study, silica nanoparticles (SiO2) in water with particle mass concentration ranged from 0% (pure water) to 3% is considered as the working fluid within the LHP. The experimental design and optimization is accomplished by the design of experimental tool, Response Surface Methodology (RSM). The results show that the nanoparticle mass concentration and the heat input have significant effect on the Rth of LHP. For a given heat input, the Rth is found to decrease with the increase of the nanoparticle mass concentration up to 0.5% and increased thereafter. It is also found that the Rth is decreased when the heat input is increased from 20 W to 60 W. The results are optimized with the objective of minimizing the Rth, using Design-Expert software, and the optimized nanoparticle mass concentration and heat input are 0.48% and 59.97 W, respectively, the minimum Rth being 2.66 (C/W). The existence of an optimum nanoparticle mass concentration and heat input are the predominant factors for the improvement in the thermal performance of nanofluid-charged LHP.

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