Skip to content
Licensed Unlicensed Requires Authentication Published by De Gruyter August 31, 2016

Identification of the effective thermal conductivity of a powdered composite using a genetic algorithm

  • Muhammad Zain-ul-abdein , Waqas Saleem , Hassan Ijaz and Aqeel A. Taimoor


This work presents a computational method for the identification of the thermal conductivity of a powdered composite. The thermo-physical properties of powdered composites depend not only upon the intrinsic material properties of the filler and the matrix, but also upon several other parameters including the packing density, the particle shape factor and the particle size. In this paper, a genetic algorithm-based model is proposed for the identification of the effective thermal conductivity of a Bakelite–graphite powdered composite. A comparative analysis is also developed between the genetic algorithm and the experimental, theoretical and finite element results. In comparison with the experimental observations, the genetic algorithm model was found to have error values of approximately 5 %, whereas the errors resulting from the theoretical models were up to 12 %.

*Correspondence address, Muhammad Zain-ul-abdein, Assistant Professor, Mechanical Engineering Departmen, University of Jeddah, Asfan Road, Jeddah, 21589, Saudi Arabia, Tel.: +966 12 695 2000 ext. 74252, Fax: +966 12 695 2000 ext. 52257, E-mail:


[1] R.Clausius: Die Mechanische Behandlung der Elektricitat, Vieweg, Braunschweig (1879). 10.1007/978-3-663-20232-5Search in Google Scholar

[2] J.C.Maxwell: A Treatise on Electricity and Magnetism, 3rd Ed., Dover Publications Inc., USA (1884) 440.Search in Google Scholar

[3] D.A.G.Bruggeman: Ann. Phys.24 (1935) 636. 10.1002/andp.19354160705Search in Google Scholar

[4] T.Mori, K.Tanaka: Acta Metall.21 (1973) 571. 10.1016/0001-6160(73)90064-3Search in Google Scholar

[5] S.K.Kanaun, V.M.Levin, in: K.Z.Markov (Ed.), Recent Advances in Mathematical Modelling of Composite Materials, World Sci. (1994) 1. 10.1142/9789814354219_0001Search in Google Scholar

[6] S.K.Kanaun: Int. J. Eng. Sci.41 (2003) 1287. 10.1016/S0020-7225(03)00042-9Search in Google Scholar

[7] K.Z.Markov, in: K.Z.Markov, L.Preziozi (Eds.), Heterogeneous Media: Micromechanics Modeling Methods and Simulations, Birkhauser, Boston, USA (2000) 1. 10.1007/978-1-4612-1332-1Search in Google Scholar

[8] I.Sevostianov, M.J.Kachanov: J. Mech. Phys. Solids50 (2002) 253. 10.1016/S0022-5096(01)00051-5Search in Google Scholar

[9] I.Sevostianov, J.Kovacik, F.Simancik: Mat. Sci. Eng. A - Struct.420 (2006) 87. 10.1016/j.msea.2006.01.064Search in Google Scholar

[10] I.Sevostianov, M.Kachanov: Int. J. Solids Struct.44 (2007) 1304. 10.1016/j.ijsolstr.2006.06.020Search in Google Scholar

[11] O.Wiener: Abh. Math.-Phys. Kl. Königlich-Sächsischen Gesellschaft der Wissenschaften32 (1912) 509.Search in Google Scholar

[12] Z.Hashin, S.Shtrikman: J. Appl. Phys.33 (1962) 3125. 10.1063/1.1728579Search in Google Scholar

[13] R.L.Hamilton, O.K.Crosser: Ind. Eng. Chem. Fund.1 (1962) 187. 10.1021/i160003a005Search in Google Scholar

[14] T.B.Lewis, L.E.Nielsen: J. Appl. Polym. Sci.14 (1970) 1449. 10.1002/app.1970.070140604Search in Google Scholar

[15] T.Telejko, Z.Malinowski: J. Mater. Process. Technol.146 (2004) 145. 10.1016/j.jmatprotec.2003.10.006Search in Google Scholar

[16] Y.S.Song, J.R.Youn: Carbon44 (2006) 710. 10.1016/j.carbon.2005.09.034Search in Google Scholar

[17] A.Decarlis, M.Jaeger: Scr. Mater.44 (2001) 1955. 10.1016/S1359-6462(01)00830-2Search in Google Scholar

[18] K.Bakker: Int. J. Heat Mass Transfer40 (1997) 3503. 10.1016/S0017-9310(97)00017-3Search in Google Scholar

[19] R.Yamada, N.Igawa, T.Taguchi, S.Jitsukawa: J. Nucl. Mater.307 (2002) 1215. 10.1016/S0022-3115(02)00957-1Search in Google Scholar

[20] J.H.Holland: Adaptation in Natural and Artificial Systems: An Introductory Analysis with Applications to Biology, Control, and Artificial Intelligence, University of Michigan Press, Ann Arbor (MI), USA (1975).Search in Google Scholar

[21] J.J.Grefenstette: IEEE Trans. Syst. Man Cybern.16 (1986) 122. 10.1109/TSMC.1986.289288Search in Google Scholar

[22] J.E.Baker: Reducing Bias and Inefficiency in the Selection Algorithm, Genetic Algorithms and their Applications, Hillsdale, NJ, USA (1987) 14.Search in Google Scholar

[23] D.E.Goldberg: Genetic Algorithms in Search, Optimization and Machine Learning, Addison-Wesley Publishing Co. Inc., Boston, MA, USA (1989).Search in Google Scholar

[24] L.Gosselin, M.Tye-Gingras, F.M.Potvin: Int. J. Heat Mass Transfer52 (2009) 2169. 10.1016/j.ijheatmasstransfer.2008.11.015Search in Google Scholar

[25] O.E.Canyurt, H.R.Kim, K.Y.Lee: Mech. Mater.40 (2008) 825. 10.1016/j.mechmat.2008.04.001Search in Google Scholar

[26] H.K.Cho, R.E.Rowlands: Compos. Sci. Technol.67 (2007) 2877. 10.1016/j.compscitech.2006.09.022Search in Google Scholar

[27] M.Zain-ul-abdein, D.Nélias, J.F.Jullien, A.I.Wagan: Mater. Des.31 (2010) 4302. 10.1016/j.matdes.2010.03.056Search in Google Scholar

[28] S.Azeem, M.Zain-ul-abdein: Int. J. Eng. Sci.52 (2012) 30. 10.1016/j.ijengsci.2011.12.002Search in Google Scholar

[29] ASTM Standard E1225-99: Annual Book of ASTM Standards, Vol. 14. 02, (1999).Search in Google Scholar

[30] M.Zain-ul-Abdein, S.Azeem, S.M.Shah: Int. J. Eng. Sci.56 (2012) 86. 10.1016/j.ijengsci.2012.03.035Search in Google Scholar

[31] L.C.Dunn, T.Dobhansky: Principles of Genetics, McGraw Hill, New York, USA (1950).Search in Google Scholar

Received: 2016-01-27
Accepted: 2016-03-18
Published Online: 2016-08-31
Published in Print: 2016-07-14

© 2016, Carl Hanser Verlag, München

Downloaded on 1.6.2023 from
Scroll to top button