Thermal conductivity modeling of MgO/EG nanofluids using experimental data and artificial neural network
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Author list: Hemmat Esfe M., Saedodin S., Bahiraei M., Toghraie D., Mahian O., Wongwises S.
Publisher: Springer Verlag (Germany) / Akadémiai Kiadó
Publication year: 2014
Journal: Journal of Thermal Analysis and Calorimetry (1388-6150)
Volume number: 118
Issue number: 1
Start page: 287
End page: 294
Number of pages: 8
ISSN: 1388-6150
eISSN: 1588-2926
Languages: English-Great Britain (EN-GB)
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Abstract
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 ฐC 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. ฉ 2014 Akad้miai Kiad๓, Budapest, Hungary.
Keywords
Nanofluids, Particle size, Thermal Conductivity
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