Journal
INTERNATIONAL COMMUNICATIONS IN HEAT AND MASS TRANSFER
Volume 76, Issue -, Pages 209-214Publisher
PERGAMON-ELSEVIER SCIENCE LTD
DOI: 10.1016/j.icheatmasstransfer.2016.05.023
Keywords
Nanofluid; Relative viscosity; Empirical correlation; Artificial neural network
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Funding
- High Impact Research Grant, University of Malaya, Malaysia [UM.C/HIR/MOHE/ENG/23]
- Faculty of Engineering, University of Malaya, Malaysia
- Research Chair Grant National Science and Technology Development Agency (NSTDA)
- Thailand Research Fund (TRF)
- National Research University Project (NRU)
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In this paper, at first, a new correlation was proposed to predict the relative viscosity of MWCNTs-SiO2/AE40 nano-lubricant using experimental data. Then, considering minimum prediction error, an optimal artificial neural network was designed to predict the relative viscosity of the nano-lubricant. Forty-eight experimental data were used to feed the model. The data set was derived to training, validation and test sets which contained 70%, 15% and 15% of data points, respectively. The correlation outputs showed that there is a deviation margin of 4%. The results obtained from optimal artificial neural network presented a deviation margin of 1.5%. It can be found from comparisons that the optimal artificial neural network model is more accurate compared to empirical correlation. (C) 2016 Elsevier Ltd. All rights reserved.
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