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Thermal prediction of convective-radiative porous fin heatsink of functionally graded material using adomian decomposition method

Oguntala, George A.
; 
Sobamowo, G.
; 
Ahmed, Y.
; 
Publication Date
2019-03
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Keywords
Functionally graded materials, Heatsink, Porous media, Thermal management
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© 2019 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (http://creativecommons.org/licenses/by/4.0/).
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2019-03-20
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Engineering and Digital Technology Publications
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Abstract
In recent times, the subject of effective cooling have become an interesting research topic for electronic and mechanical engineers due to the increased miniaturization trend in modern electronic systems. However, fins are useful for cooling various low and high power electronic systems. For improved thermal management of electronic systems, porous fins of functionally graded materials (FGM) have been identified as a viable candidate to enhance cooling. The present study presents an analysis of a convective–radiative porous fin of FGM. For theoretical investigations, the thermal property of the functionally graded material is assumed to follow linear and power-law functions. In this study, we investigated the effects of inhomogeneity index of FGM, convective and radiative variables on the thermal performance of the porous heatsink. The results of the present study show that an increase in the inhomogeneity index of FGM, convective and radiative parameter improves fin efficiency. Moreover, the rate of heat transfer in longitudinal FGM fin increases as b increases. The temperature prediction using the Adomian decomposition method is in excellent agreement with other analytical and method.
URI
http://hdl.handle.net/10454/16936
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Published version
Citation
Oguntala G, Sobamowo G, Ahmed Y et al (2019) Thermal prediction of convective-radiative porous fin heatsink of functionally graded material using adomian decomposition method. Computation. 7(1): 19.
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https://doi.org/10.3390/computation7010019
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Article
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