微注塑散热器流动诱导热导率变化的多尺度数值预测

杨灿; 曹泽卫; 尹晓红; 阚君武; 程光明; 李熹平

doi:10.3788/OPE.20162403.0566

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微注塑散热器流动诱导热导率变化的多尺度数值预测

微纳技术与精密机械 | 更新时间：2020-08-13

- 微注塑散热器流动诱导热导率变化的多尺度数值预测
- Multi-scale numerical prediction of flow-induced thermal conductivity variation in micro-injection molded heat sink
- 光学精密工程 2016年24卷第3期页码：566-573
- 作者机构：
  
  浙江师范大学精密机械研究所, 浙江金华 321004
- 作者简介：
- 基金信息：
  
  国家自然科学青年基金项目(No.51405451, 51305406)();浙江省自然科学青年基金项目(No.LQ13E050008)();浙江省"钱江人才计划"资助项
- DOI：10.3788/OPE.20162403.0566
  中图分类号： TH145.4;TQ320.6
- 收稿日期：2015-07-20，
  
  修回日期：2015-08-25，
  
  纸质出版日期：2016-03-25
- 稿件说明：
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杨灿, 曹泽卫, 尹晓红等. 微注塑散热器流动诱导热导率变化的多尺度数值预测[J]. 光学精密工程, 2016,24(3): 566-573

YANG Can, CAO Ze-wei, YIN Xiao-hong etc. Multi-scale numerical prediction of flow-induced thermal conductivity variation in micro-injection molded heat sink[J]. Editorial Office of Optics and Precision Engineering, 2016,24(3): 566-573
杨灿, 曹泽卫, 尹晓红等. 微注塑散热器流动诱导热导率变化的多尺度数值预测[J]. 光学精密工程, 2016,24(3): 566-573 DOI： 10.3788/OPE.20162403.0566.

YANG Can, CAO Ze-wei, YIN Xiao-hong etc. Multi-scale numerical prediction of flow-induced thermal conductivity variation in micro-injection molded heat sink[J]. Editorial Office of Optics and Precision Engineering, 2016,24(3): 566-573 DOI： 10.3788/OPE.20162403.0566.

摘要

为进一步提高聚合物复合材料热导率

采用多尺度数值预测法研究了微注塑聚酰胺/碳纤维(PA66/CFs)散热器内部CF的流动诱导取向及其对制品热导率的影响规律。首先

利用Moldflow获取CF取向张量

并以Comsol Multiphysics构建与之对应的复合材料微元胞。利用正交实验法研究熔体温度、模具温度、最大注射压力及注射流率对微散热器热导率的影响。然后

对预测数据进行分析获得最优注塑参数组合。最后

对优化结果进行模拟实验

验证了多尺度数值预测法的有效性。结果显示:上述各参数重要程度由大到小依次排列为熔体温度、注射流率、最大注射压力和模具温度;最佳组合为熔体温度360℃、模具温度70℃、最大注射压力220 MPa及注射流率3×10

-4

/s。另外

流动诱导热导率变化最大值达0.36 W/(m·K)

为基体热导率的1.5倍。得到的研究结果为从工艺调控的新角度来改善聚合物复合材料的导热性能提供了理论依据与数据支撑。

Abstract

To further increase the thermal conductivity of polymer composites

a multi-scale numerical prediction method was applied to investigation of the CF flow induced orientation in micro-injection molded polyamide/carbon fibers(PA66/CFs) micro heat sink as well as its influence on the thermal conductivity of composites. Firstly

the Moldflow was used to determine the orientation tensor of the CF

the Comsol Multiphysics was used to develop the corresponding micro cell of the composite

and an orthogonal experiment method was utilized to study the effects of processing parameters including melt temperature

mold temperature

maximal injection pressure and injection flow rate

on the thermal conductivity. Then

on the basis of prediction data analysis

the optimal combination of the injection molding processing parameters was obtained. Finally

the optimal combination results were confirmed using simulated experiment

which verified the feasibility of the proposed multi-scale numerical prediction method. The results show that the influential parameters in descending order of importance are melt temperature

injection flow rate

maximal injection pressure

and mold temperature. Moreover

the obtained optimal combination of the investigated factors is identified as the melt temperature of 360℃

mold temperature of 70℃

maximal injection pressure of 220 MPa and the injection flow rate of 3×10

-4

/s. In addition

the maximal variation of the flow-induced thermal conductivity is determined as 0.36 W/(m·K)

which is 1.5 times that of polymer matrix. The findings in the present work provide theoretical basis and data supports for further increasing the thermal conductivity of polymer composites from a new viewpoint of processing control.

关键词

Keywords

references

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