Estimation of in-plane thermal conductivity of copper clad board by inverse analysis using artificial neural networks

This study presents a methodology to estimate the in-plane thermal conductivity of copper clad board used in electronic applications. Experiments are performed in vacuum environment and an inverse heat conduction problem (IHCP) is solved employing artificial neural networks to estimate the in-plane...

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Bibliographic Details
Published in:IOP conference series. Materials Science and Engineering 2018-08, Vol.396 (1), p.12054
Main Authors: Niju Mohammed, K, Chanda, Samarjeet
Format: Article
Language:English
Subjects:
Algorithms
Artificial neural networks
Back propagation networks
Conduction heating
Conductive heat transfer
Copper
Heat conductivity
Inverse problems
Neural networks
Thermal conductivity
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Summary:This study presents a methodology to estimate the in-plane thermal conductivity of copper clad board used in electronic applications. Experiments are performed in vacuum environment and an inverse heat conduction problem (IHCP) is solved employing artificial neural networks to estimate the in-plane thermal conductivity. A comparison of estimates of thermal conductivity as obtained by solving the inverse problem using back propagation artificial neural networks trained using two algorithms namely Levenberg-Marquardt and Scaled Conjugate Gradient are presented.
ISSN:1757-8981
1757-899X
1757-899X
DOI:10.1088/1757-899X/396/1/012054