The influence of thermal contact resistance on the relative performance of heat pipe-fin array systems

Sharifi, Nourouddin; Stark, John R.; Bergman, T. L.; Faghri, Amir

doi:10.1016/j.applthermaleng.2016.05.121

Cited by 13 publications

(5 citation statements)

References 43 publications

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“…The thermal resistance network approach is a robust engineering tool that is easy to implement and program, computationally efficient and serves as a baseline methodology to produce results of reasonable accuracy. Therefore, in the present study, the thermal resistance network model suggested by Shabgard et al and Sharifi et al [19,28] was employed to analyze the component thermal resistance of the HP including the external fin thermal resistances.…”

Section: Thermal Resistance Networkmentioning

confidence: 99%

“…3 shows the configuration of fins attached on the condenser section: (a) cross-section of condenser part with fins, and (b) geometries of various types of fins. In the present study, the resistance-related fins on the condenser section were considered, including a fin array similar to that described elsewhere [19,31]. As shown in Fig.…”

Section: ( ) E Wk E Inter V C Inter C Wk a Wk E W C W A W E Wk E Inte...mentioning

confidence: 99%

“…The heat transfer capability of the HP system is often limited by the convective resistances associated with the external fluid flow about the condenser section. Therefore, numerous external fins or fin arrays are often employed to reduce the overall thermal resistance of the HP system [14][15][16][17][18][19].…”

Section: Introductionmentioning

confidence: 99%

“…This problem was solved by installing fins on the condenser section, which reduced the thermal resistance. Sharifi et al [19] reported that the heat dissipation performance of the HP-fin array systems was limited by heat transfer from the condenser to outside based on the thermal resistance model. They highlighted the importance of the thermal contact resistance between the HP and the fin.…”

Section: Introductionmentioning

confidence: 99%

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Artificial Neural Network Modeling on Heat Transfer Performance of Finned Heat Pipe

Seo,

Choi,

et al. 2024

Preprint

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A numerical analysis has been conducted to examine the heat transfer characteristics of a finned heat pipe based on thermal resistance networks. The present numerical analysis also reports the enhancement of heat transport of heat pipe using the fins. The key simulation parameters considered were three types of fins with circular, square, and hexagonal shapes, the fin length in the range from 19.05mm to 38.1mm, the number of fins in the range from 5 to 20, and the fin thickness in the range from 0.25mm to 1mm. The heat transfer rate shoots up by 62.58% in the case of finned heat pipe when compared with the baseline model with respect to the variation in the simulation parameters. An artificial neural network, which is one of the machine learning methods, was used to predict the heat transfer performance obtained from thermal resistance analysis of the finned heat pipe. The optimized ANN model could predict the heat transfer performance of the finned heat pipe with reasonable accuracy. In addition, the heat transfer rate of the finned heat pipe could be predicted accurately from extrapolated and interpolated data using the optimized ANN model.

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Section: Thermal Resistance Networkmentioning

confidence: 99%

Section: ( ) E Wk E Inter V C Inter C Wk a Wk E W C W A W E Wk E Inte...mentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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Artificial Neural Network Modeling on Heat Transfer Performance of Finned Heat Pipe

Seo,

Choi,

et al. 2024

Preprint

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“…Zhao et al [19] investigated effects of pressure and temperature on thermal contact resistance between different materials. A detailed heat pipe model was used by Sharifi et al [20] to quantify the influence of the contact resistances on the heat transfer and fluid flow within the heat pipe, as well as on the overall heat transfer rate. However, as far as we know, it is the first time using the novel equivalenttemperature method to solve three-dimensional thermal contact resistance problem and convective problem towards outside thermal environment for the CFML structure, which has not been found in previous papers.…”

Section: Introductionmentioning

confidence: 99%

An equivalent temperature model of 3-D steady heat conduction analysis for a fiber metal laminated plate coated with a thermal barrier

Gao

Lian

et al. 2021

THERM SCI

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In this paper, an equivalent temperature model of three-dimensional steady heat conduction analysis for a fiber metal laminated plate coated with a thermal barrier (CFML) is presented. The separate variable method (SVM) and equivalent temperature (ET) method are applied comprehensively to solve the temperature field at the interface between the thermal barrier and top aluminum 2024-T3 layer for the fiber metal laminated (FML) structure firstly, and values of other layers' temperature and thermal contact resistance are obtained based on balance principle of heat flux between respective adjacent top and bottom layers subsequently. The aim of this research is to understand the influences of kinds of fiber species, numbers of FML layers, thickness ratio between total CFML structure and thermal barrier as well as temperature distributed function on the values of thermal contact resistance between respective adjacent layers and temperature distribution from top to bottom surfaces for the CFML structure. Especially, the ratio of thermal contact resistance between maximum and minimum values are about 5 times no matter considering one or two kinds of fiber species. Besides the present results (mainly geometrical and physical parameters' effect) could guide engineers designing the CFML structures to adapt to high-temperature environment especially aerospace temperature environment.

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Heat Pipes and Thermosyphons

Faghri¹

2018

Handbook of Thermal Science and Engineering

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The influence of thermal contact resistance on the relative performance of heat pipe-fin array systems

Cited by 13 publications

References 43 publications

Artificial Neural Network Modeling on Heat Transfer Performance of Finned Heat Pipe

Artificial Neural Network Modeling on Heat Transfer Performance of Finned Heat Pipe

An equivalent temperature model of 3-D steady heat conduction analysis for a fiber metal laminated plate coated with a thermal barrier

Heat Pipes and Thermosyphons

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