纳米流体矩形微通道热沉结构参数多目标优化

史晓军; 李珊; 魏亚东; 高建民

doi:10.7652/xjtuxb201805008

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纳米流体矩形微通道热沉结构参数多目标优化

更新时间：2025-07-09

- 纳米流体矩形微通道热沉结构参数多目标优化
- Multi-Objective Optimization on the Geometrical Parameters of a Nanofluid-Cooled Rectangular Microchannel Heat Sink
- 西安交通大学学报 2018年52卷第5期页码：56-61+132
- 作者机构：
  
  西安交通大学机械制造系统工程国家重点实验室,西安,710054
- 作者简介：
- 基金信息：
  
  : 2017-09-20。作者简介: 史晓军(1974—),男,副教授。基金项目: 陕西省国际合作重点资助项目(2014KW07-03)
- DOI：10.7652/xjtuxb201805008
  中图分类号： TH113
- 网络首发：2018-05-10，
  
  纸质出版：2018
- 稿件说明：
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史晓军, 李珊, 魏亚东, 等. 纳米流体矩形微通道热沉结构参数多目标优化[J]. 西安交通大学学报, 2018,52(5):56-61+132.

Multi-Objective Optimization on the Geometrical Parameters of a Nanofluid-Cooled Rectangular Microchannel Heat Sink[J]. 2018, 52(5): 56-61+132.
史晓军, 李珊, 魏亚东, 等. 纳米流体矩形微通道热沉结构参数多目标优化[J]. 西安交通大学学报, 2018,52(5):56-61+132. DOI： 10.7652/xjtuxb201805008.

Multi-Objective Optimization on the Geometrical Parameters of a Nanofluid-Cooled Rectangular Microchannel Heat Sink[J]. 2018, 52(5): 56-61+132. DOI： 10.7652/xjtuxb201805008.

摘要

为了开发高效低阻的纳米流体微通道热沉

对单层矩形纳米流体微通道热沉几何结构参数进行了多目标优化。设计变量为高宽比α和微通道宽度与间距比β

优化目标是使全局热阻和泵功最小。对Pareto最优解进行K均值聚类分析发现

在5个聚类点的最高点和最低点之间存在有效权衡点

让泵功和热阻均处于较优范围内。实际设计中可以根据泵功或所需的热阻来选择最优结构参数。相对于高宽比

热阻和泵功对微通道宽度与间距比更敏感。尤其当β大于1.15时

其对热阻和泵功的影响非常强烈。相对于热阻

泵功对设计变量更敏感

在α和β的设计空间内

泵功的变化幅度约为360%

而热阻的变化幅度只有135%。纳米流体的热阻比去离子水显著减小

且随泵功的增大

去离子水和纳米流体热阻之差有缓慢增大的趋势。

Abstract

To develop the microchannel heat sinks with high heat transfer coefficient and low pressure drop

a multi-objective optimization on the geometrical parameters of a single-layer nanofluid-cooled microchannel heat sink with rectangular cross section was performed. The channel aspect ratio α and channel width ratio β were selected as design variables. The optimization objective is to minimize the thermal resistance and pumping power of the heat sink. The K-means clustering analysis was applied for the Pareto optimal solutions

and it was found that there is a tradeoff between the highest and lowest points of the five clusters which can make both pumping power and thermal resistance within the optimal range. The optimal geometrical parameters can be selected based on the requirements of pumping power or thermal resistance in the actual design process. The thermal resistance and pumping power are more sensitive to the width ratio β than to the aspect ratio α. The width ratio β has more significant effect on thermal resistance and pumping power especially when β is greater than 1.15. Compared with the thermal resistance

the pumping power is more sensitive to the design variables. In the design space of variables α and β

the pumping power varies by about 360%

while the thermal resistance only varies by about 135%. The thermal resistance of nanofluid is significantly lower than that of deionized water. The difference of thermal resistance between deionized water and nanofluid increases slowly with the increase of pumping power.

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Keywords

references

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