Modeling of thermal conductivity of ZnO-EG using experimental data and ANN methods
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Author list: Hemmat Esfe M., Saedodin S., Naderi A., Alirezaie A., Karimipour A., Wongwises S., Goodarzi M., Dahari M.B.
Publisher: Elsevier
Publication year: 2015
Journal: International Communications in Heat and Mass Transfer (0735-1933)
Volume number: 63
Start page: 35
End page: 40
Number of pages: 6
ISSN: 0735-1933
eISSN: 1879-0178
Languages: English-Great Britain (EN-GB)
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Abstract
In the present study, the thermal conductivity of the ZnO-EG nanofluid has been investigated experimentally. For this purpose, zinc oxide nanoparticles with nominal diameters of 18. nm have been dispersed in ethylene glychol at different volume fractions (0.000625, 0.00125, 0.005, 0.01, 0.015, 0.02, 0.03, 0.04, and 0.05) and temperatures (24-50. ฐC). The two-step method is used to disperse nanoparticles in the base fluid. Based on the experimental data, an experimental model has been proposed as a function of solid concentration and temperature. Then, the feedforward multilayer perceptron neural network has been employed for modeling thermal conductivity of ZnO-EG nanofluid. Out of 40 measured data obtained from experiments, 28 data were selected for network training, while the remaining 12 data were used for network testing and validating. The results indicate that both model and ANN outputs are in good agreement with the experimental data. ฉ 2015 Elsevier Ltd.
Keywords
MgO-EG
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