Research Papers: Conduction

An Integrated Mechanical–Thermal Predictive Model of Thermal Contact Conductance

[+] Author and Article Information
Jun Hong

School of Mechanical Engineering,
Xi’an Jiaotong University,
Xi’an, 710049, China
e-mail: jhong@mail.xjtu.edu.cn

Junfeng Peng

School of Mechanical Engineering,
Xi’an Jiaotong University,
Xi’an, 710049, China;
Université de Lyon,
F-69622, Lyon, France;
Bron, France;
Université Lyon 1,
Villeurbanne, France
e-mail: junfeng.peng@stu.xjtu.edu.cn

Baotong Li

School of Mechanical Engineering,
Xi'an Jiaotong University,
Xi'an, 710049, China

1Corresponding author.

Contributed by the Heat Transfer Division of ASME for publication in the Journal of Heat Transfer. Manuscript received November 3, 2011; final manuscript received November 22, 2012; published online March 20, 2013. Assoc. Editor: Sujoy Kumar Saha.

J. Heat Transfer 135(4), 041301 (Mar 20, 2013) (8 pages) Paper No: HT-11-1498; doi: 10.1115/1.4023223 History: Received November 03, 2011; Revised November 22, 2012

In this paper, an integrated mechanical–thermal predictive model of thermal contact conductance (TCC) between two nominally flat metallic rough surfaces is developed. Asperities on rough surface were approximated as parabolas. The asperity height deviation and average asperity top radius were measured as surface parameters and then used for mechanical and thermal modeling. A 3D shoulder–shoulder contact deformation model was then extended, taking into account different degrees of misalignment of contact between asperities and three modes of deformation: elastic, elastoplastic, and plastic. The yielded normal contact pressure, which should be equal to the exterior load, was formulated as a function of the given mean separation between the contacting surfaces for given surfaces and material properties. Based on the contact deformation model, a regression correlation of thermal contact conductance of a single pair shoulder–shoulder contacting asperities was integrated to get total TCC as a function of material properties and mean separation. As contact pressure and thermal contact conductance are all monotonically correlated with the mean separation, the mapping between the pressure and thermal contact conductance can be established by integrating the two parts. Finally, the integrated mechanical–thermal predictive model was compared to an existing predictive model and a series of experimental data. The results were in good agreement, demonstrating the validity of the model.

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Fig. 1

Representation of a peak by a parabola

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Fig. 2

3D representation of a peak

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Fig. 3

Shoulder–shoulder contact of two asperities

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Fig. 4

Scheme of thermal simulation model of contacting asperities

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Fig. 5

Computational algorithm

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Fig. 6

Experimental setup

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Fig. 7

Comparison of predictions by algorithm in Fig. 5 with correlation of Yovanovich [12] and experimental data for test pair No. 1

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Fig. 8

Comparison of predictions by algorithm in Fig. 5 with correlation of Yovanovich [12] and experimental data for test pair No. 2

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Fig. 9

Comparison of predictions by algorithm in Fig. 5 with correlation of Yovanovich [12] and experimental data for test pair No. 3

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Fig. 10

Influence of surface rms roughness on thermal contact conductance

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Fig. 11

Influence of average asperity top radius on thermal contact conductance

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Fig. 12

Influence of asperity density on TCC



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