The application of nanofluids in energy systems is developing day by day. Before using a nanofluid in an energy system, it is necessary to measure the properties of nanofluids. In this paper, first the results of experiments on the thermal conductivity of MgO/ethylene glycol (EG) nanofluids in a temperature range of 25–55 °C and volume concentrations up to 5 % are presented. Different sizes of MgO nanoparticles are selected to disperse in EG, including 20, 40, 50, and 60 nm. Based on the results, an empirical correlation is presented as a function of temperature, volume fraction, and nanoparticle size. Next, the model of thermal conductivity enhancement in terms of volume fraction, particle size, and temperature was developed via neural network based on the measured data. It is observed that neural network can be used as a powerful tool to predict the thermal conductivity of nanofluids.
This is a preview of subscription content, access via your institution.
Buy single article
Instant access to the full article PDF.
Price excludes VAT (USA)
Tax calculation will be finalised during checkout.
Lorenzini G, Medici M, Alberto Oliveira Rocha L. Convective analysis of constructal T-shaped fins. J Eng Therm. 2014;23(2):98–104.
Mahian O, Kianifar A, Kalogirou SA, Pop I, Wongwises S. A review of the applications of nanofluids in solar energy. Int J Heat Mass Transf. 2013;57:582–94.
Rashidi I, Mahian O, Lorenzini G, Biserni C, Wongwises S. Natural convection of Al2O3/water nanofluid in a square cavity: effects of heterogeneous heating. Int J Heat Mass Transf. 2014;74:391–402.
Halelfadl S, Adham AM, Mohd-Ghazali N, Maré T, Estellé P, Ahmad R. Optimization of thermal performance and pressure drop of a rectangular microchannel heat sink using aqueous carbon nanotubes based nanofluid. Appl Therm Eng. 2014;62:492–9.
Witharana S, Palabiyik I, Musina Z, Ding Y. Stability of glycol nanofluids—the theory and experiment. Powder Technol. 2013;239:72–7.
Barbés B, Páramo R, Blanco E, Pastoriza-Gallego MJ, Piñeiro MM, Legido JL, Casanova C. Thermal conductivity and specific heat capacity measurements of Al2O3 nanofluids. J Therm Anal Calorim. 2013;11:1615–25.
Hemmat Esfe M, Saedodin S, Mahian O, Wongwises W. Thermal conductivity of Al2O3/water nanofluids: measurement, correlation, sensitivity analysis, and comparisons with literature reports. J Therm Anal Calorim. 2014;. doi:10.1007/s10973-014-3771-x.
Salehi JM, Heyhat MM, Rajabpour A. Enhancement of thermal conductivity of silver nanofluid synthesized by a one-step method with the effect of polyvinylpyrrolidone on thermal behavior. Appl Phys Lett. 2013;102:231907.
Halelfadl S, Maré T, Estellé P. Efficiency of carbon nanotubes water based nanofluids as coolants. Exp Therm Fluid Sci. 2014;53:104–10.
Yiamsawasd T, Selim Dalkilic A, Wongwises S. Measurement of the thermal conductivity of titania and alumina nanofluids. Thermochim Acta. 2012;545:48–56.
Longo GA, Zilio C. Experimental measurement of thermophysical properties of oxide–water nano-fluids down to ice-point. Exp Therm Fluid Sci. 2011;35:1313–24.
Kleinstreuer C, Feng Y. Experimental and theoretical studies of nanofluid thermal conductivity enhancement: a review. Nanoscale Res Lett. 2011;6:229.
Longo GA, Zilio C. Experimental measurements of thermophysical properties of Al2O3– and TiO2–ethylene glycol nanofluids. Int J Thermophys. 2013;34:1288–307.
Xie H, Yu W, Chen W. MgO nanofluids: higher thermal conductivity and lower viscosity among ethylene glycol-based nanofluids containing oxide nanoparticles. J. Exp Nanosci. 2010;5:463–72.
Xie H, Yu W, Li Y, Chen L. Discussion on the thermal conductivity enhancement of nanofluids. Nanoscale Res Lett. 2011;6:124.
Hemmat Esfe M, Saedodin S, Mahmoodi M. Experimental studies on the convective heat transfer performance and thermophysical properties of MgO-Water nanofluid under turbulent flow. Exp Therm Fluid Sci. 2013;52:68–78.
Kalogirou SA. Applications of artificial neural-networks for energy systems. Appl Energy. 2000;67:17–35.
Papari MM, Yousefi F, Moghadasi J, Karimi H, Campo A. Modeling thermal conductivity augmentation of nanofluids using diffusion neural networks. Int J Therm Sci. 2011;50:44–52.
Hojjat M, Etemad SGh, Bagheri R, Thibault J. Thermal conductivity of non-Newtonian nanofluids: experimental data and modeling using neural network. Int J Heat Mass Transf. 2011;54:1017–23.
Longon GA, Zilio C, Ceseracciu E, Reggiani M. Application of artificial neural network (ANN) for the prediction of thermal conductivity of oxide–water nanofluids. Nano Energy. 2012;1:290–6.
Yoo DH, Hong KS, Yang HS. Study of thermal conductivity of nanofluids for the application of heat transfer fluids. Thermochim Acta. 2007;455:66–9.
Challoner AR, Powell RW. Thermal conductivities of liquids: new determinations for seven liquids and appraisal of existing values. Proceedings Royal Society London A. 1956;238:90–106.
Kurt H, Kayfeci M. Prediction of thermal conductivity of ethylene glycol water solutions by using artificial neural networks. Appl Energy. 2009;86:2244–8.
Czarnetzki W, Roetzel W. Temperature oscillation techniques for simultaneous measurement of thermal diffusivity and conductivity. Int J Thermophys. 1995;16:413–22.
Cahill DG. Thermal conductivity measurement from 30 to 750 K: the 3w method. Rev Sci Instrum. 1990;61:802–8.
Iranidokht V, Hamian S, Mohammadi N, Behshad Shafii M. Thermal conductivity of mixed nanofluids under controlled pH conditions. Int J Therm Sci. 2013;74:63–71.
The authors would like to acknowledge the assistance provided by the nanofluid Laboratory of Semnan university science and technology Park for providing necessary instrumentation to carry out the sample preparation and helping in the analysis of samples to complete the article in time. The sixth author would like to thank the Thailand Research Fund, The National Science and Technology Development Agency, and the National Research University Project for the support. Also, the help and comments of Professor Clement Kleinstreuer at North Carolina State University are appreciated.
Rights and permissions
About this article
Cite this article
Hemmat Esfe, M., Saedodin, S., Bahiraei, M. et al. Thermal conductivity modeling of MgO/EG nanofluids using experimental data and artificial neural network. J Therm Anal Calorim 118, 287–294 (2014). https://doi.org/10.1007/s10973-014-4002-1
- Neural network
- Thermal conductivity
- Particle size