Bayesian regularization optimization algorithm for the experimental thermophysical property for 80:20% water and ethylene glycol based ZrO2 nanofluids

Bayesian regularization optimization algorithm for the experimental thermophysical property for 80:20% water and ethylene glycol based ZrO2 nanofluids

M. Manzoor Hussain, L. Syam Sundar, Feroz Shaik

download PDF

Abstract. In the current study, water and ethylene glycol (W/EG 80:20%) are used as the base fluid, and sodium dodecyl benzene sulfonate is used as a surfactant to create nanofluids using ZrO2 nanoparticles prepared using the sol-gel technique. For temperatures ranging from 20 oC to 60 oC and various volume loadings of nanoparticles, 0.2, 0.4, 0.6, 0.8, and 1.0%, respectively, the thermal conductivity, dynamic viscosity, density, and viscosity of these ZrO2 nanofluids are experimentally evaluated. Artificial neural network based Bayesian regularization algorithm was used to find the correlation coefficient R2 and root-mean square error. New correlations were also suggested for each of the thermophysical properties. Experiments show that temperatures and concentrations of nanoparticles have a significant impact on the thermophysical properties of nanofluids. In fact, it is shown that, at 20 oC and 60 oC, respectively, increasing the thermal conductivity of nanofluids by 1.0 vol% leads to increases of almost 10.16% and 24.53%. Additionally, at 1.0 vol and 20 oC to 60 oC, the dynamic viscosity is reduced from 61.94% to 50.79%. The correlations and outcomes of the developed artificial neural network are in perfect agreement with the experimental data.

Water and Ethylene Glycol, Thermophysical Properties, Bayesian Regularization Approach, Correlations

Published online 8/10/2023, 11 pages
Copyright © 2023 by the author(s)
Published under license by Materials Research Forum LLC., Millersville PA, USA

Citation: M. Manzoor Hussain, L. Syam Sundar, Feroz Shaik, Bayesian regularization optimization algorithm for the experimental thermophysical property for 80:20% water and ethylene glycol based ZrO2 nanofluids, Materials Research Proceedings, Vol. 31, pp 437-447, 2023


The article was published as article 45 of the book Advanced Topics in Mechanics of Materials, Structures and Construction

Content from this work may be used under the terms of the Creative Commons Attribution 3.0 license. Any further distribution of this work must maintain attribution to the author(s) and the title of the work, journal citation and DOI.

[1] S.U.S. Choi, Enhancing thermal conductivity of fluids with nanoparticles. Developments and Applications of Non-Newtonian Flows FED-vol. 231/MD-vol. 66, (1995) 99-105.
[2] R. Saidur, K.Y. Leong, H.A. Mohammad, A review on applications and challenges of nanofluids, Renewable and Sustainable Energy Reviews, 15(3) (2011) 1646 -1668.
[3] L.S. Sundar, M.T. Naik, K.V. Sharma, M.K. Singh, T.Ch. Siva Reddy, Experimental investigation of forced convection heat transfer and friction factor in a tube with Fe3O4 magnetic nanofluid, Exp. Therm. Fluid Sci. 37 (2012) 65-71.
[4] L.S. Sundar, M.K. Singh, I. Bidkin, A.C.M. Sousa, Experimental investigations in heat transfer and friction factor of magnetic Ni nanofluid flowing in a tube, Int. J. Heat and Mass Transfer 70 (2014) 224-234.
[5] L.S. Sundar, K.V. Sharma, Thermal conductivity enhancement of nanoparticles in distilled water, Int. J. Nanoparticles 1 (2008) 66-77.
[6] X. Wang, X. Xu, S.U.S. Choi, Thermal conductivity of nanoparticle-fluid mixture, J. Thermophysics and Heat Transfer 13 (1999) 474-480.
[7] S.M.S. Murshed, K.C. Leong, C. Yang, Investigations of thermal conductivity and viscosity of nanofluids, Int. J. Thermal Science 47 (2008) 560-568.
[8] M.S. Liu, M.C.C. Lin, I.T. Huang, C.C. Wang, Enhanced thermal conductivity with CuO for nanofluids, Chemical Engineering and Technology 29 (2006) 72-77.
[9] H.A. Mintsa, G. Roy, C.T. Nguyen, D. Doucet, New temperature dependent thermal conductivity data for water-based nanofluids, Int. J. Thermal Science 48 (2009) 363-371.
[10] ASHRAE, in: Handbook-Fundamentals, 2009, pp. 31.1-31.13.
[11] R.S. Vajjha, D.K. Das, Experimental determination of thermal conductivity of three nanofluids and development of new correlations, Int. J. Heat and Mass Transfer 52 (2009) 4675-4682.
[12] L.S. Sundar, Md. Hashim Farooky, S.N. Sarada, M.K. Singh, Experimental thermal conductivity of ethylene glycol and water mixture based low volume concentration of Al2O3 and CuO nanofluids, Int. Comm. Heat and Mass Transfer 41 (2013) 41-46.
[13] A. Banisharif, M. Aghajani, S.V. Vaerenbergh, P. Estellé, A. Rashidi, Thermophysical properties of water ethylene glycol (WEG) mixture-based Fe3O4 nanofluids at low concentration and temperature, J. Molecular Liquids, 302 (2020) 112606.
[14] N.A. Usri, W.H. Azmi, R. Mamat, K. Abdul Hamid, G. Najafi, Thermal conductivity enhancement of Al2O3 nanofluid in ethylene glycol and water mixture, Energy Procedia 79 ( 2015 ) 397-402.
[15] O.A. Alawi, A.R. Mallah, S.N. Kazi, M.N.M. Zubir, C.S. Oon, Thermal transport feasibility of (water + ethylene glycol)- based nanofluids containing metallic oxides: Mathematical approach, IOP Conf. Series: Materials Science and Engineering 854 (2020) 012023.
[16] L.S. Sundar, E.V. Ramana, M.K. Singh, A.C.M. Sousa, Thermal conductivity and viscosity of stabilized ethylene glycol and water mixture Al2O3 nanofluids for heat transfer applications: An experimental study, Int. Comm. Heat and Mass Transfer 56 (2014) 86-95.
[17] L.S. Sundar, M.K. Singh, A.C.M. Sousa, Thermal conductivity of ethylene glycol and water mixture based Fe3O4 nanofluid, Int. Comm. Heat and Mass Transfer 49 (2013) 17-24.
[18] J.C. Maxwell, A treatise on electricity and magnetism, 2nd Edition, Oxford University Press, Cambridge, UK, 1904.
[19] R.L. Hamilton, O.K. Crosser, Thermal conductivity of heterogeneous two component systems, Ind. Eng. Chem. Fundamental. 1 (3) (1962) 187-191.
[20] F.J. Wasp, Solid-Liquid Slurry Pipeline Transportation, Trans, Tech, Berlin, 1977.
[21] W. Yu, S.U.S. Choi, The role of interfacial layers in the enhanced thermal conductivity of nanofluids: a renovated maxwell model, J. Nanoparticle Research 5 (2003) 167-171.
[22] Y. Xuan, Q. Li, W. Hu, Aggregation structure and thermal conductivity of nanofluids, AIChE J. 49 (4) (2003) 1038-1043.
[23] C.H. Chon, K.D. Kihm, S.P. Lee, S.U.S. Choi, Empirical correlation finding the role of temperature and particle size for nanofluid (Al2O3) thermal conductivity enhancement, Appl. Phys. Lett. 87 (15) (2005) 153107.
[24] E.V. Timofeeva, A.N. Gavrilov, J.M. McCloskey, Y.V. Tolmachev, Thermal conductivity and particle agglomeration in alumina nanofluids: Experiment and theory, Physical Review 76 (2007) 061203.
[25] G.K. Batchelor, The effect of Brownian motion on the bulk stress in a suspension of spherical particles, J. Fluid Mechanics 83 (1977) 97-117.
[26] A. Einstein, A new determination of molecular dimensions, Annalen der Physik 19 (1906) 289-306.
[27] H.C. Brinkman, The viscosity of concentrated suspensions and solution, J. Chemical Physics 20 (1952) 571-581.
[28] X. Wang, X. Xu, S.U.S Choi, Thermal conductivity of nanoparticles-fluid mixture, J. Thermophysics Heat Transfer 13 (4) (1999) 474-480.
[29] P.K. Namburu, D.K. Das, K.M. Tanguturi, R.K. Vajjha, Numerical study of turbulent flow and heat transfer characteristics of nanofluids considering variable properties, Int. J. Thermal Sciences 48 (2009) 290-302.
[30] A.V. Minakov, Valery Ya. Rudyak, Maxim I. Pryazhnikov, Systematic experimental study of the viscosity of nanofluids, Heat Transfer Engineering 42 (2021) 1024-1040.