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Non-intrusive measurement of thermal contact conductance at polymer-metal two dimensional annular interface

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Abstract

This work reports the development of a measurement technique for the estimation of thermal contact conductance at a polymer (Nylon)-metal(Copper) two dimensional interface having an annular contact under low external loading. The experimental setup consists of a vacuum chamber capable of achieving a pressure of 10−6 mbar. The chamber is fitted with electrical, thermocouple and fluid feed-throughs. Two dimensional temperature measurements are performed on the top surface of the polymer sample away from the boundary interface and are used to estimate the thermal contact conductance at the interface. The estimation process is accomplished by solving an inverse heat conduction problem using artificial neural networks coupled with Genetic algorithm. The actual pressure distribution at the annular Nylon-Copper interface is measured using a pressure sensitive film and the variation and the distribution of contact area between the mating surfaces is shown. The estimated values of thermal contact conductance obtained using the developed non-intrusive technique are found to be in good agreement with those reported in literature.

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Abbreviations

ᅟ:

hc :

mean thermal contact conductance over the annular interface, W/m2K

k:

thermal conductivity of sample, W/m K

m:

number of samples used for testing the network

l:

length of the nylon sample and copper frame (along x), mm

n:

number of temperature measurement points

t:

thickness of the nylon sample (along z), mm

T:

computed temperature, C or K

w:

width of the nylon sample and copper frame (along y), mm

x,y,z:

Cartesian coordinates

𝜖 :

emissivity

σ :

uncertainty in measurement

a:

actual value obtained from numerical solution of direct problem

b:

physical dimension of heater (mm)

Cu:

value at the copper frame surface

e:

experimental value

max:

maximum value

min:

minimum value

p:

predicted value obtained from the trained artificial neural network

s:

simulated value

ANN:

artificial neural network

GA:

genetic algorithm

MSE:

mean squared error

MRE:

mean relative error

MAE:

mean absolute error

PDF:

probability density function

SS 304:

stainless steel of grade 304 designated by American Iron and Steel Institute

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Acknowledgements

The authors thank IITM-ISRO Space Technology Cell for funding this research work.

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Correspondence to Samarjeet Chanda.

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Chanda, S., Balaji, C. & Venkateshan, S.P. Non-intrusive measurement of thermal contact conductance at polymer-metal two dimensional annular interface. Heat Mass Transfer 55, 327–340 (2019). https://doi.org/10.1007/s00231-018-2410-7

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  • DOI: https://doi.org/10.1007/s00231-018-2410-7

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