Journal
PHYSICA E-LOW-DIMENSIONAL SYSTEMS & NANOSTRUCTURES
Volume 85, Issue -, Pages 90-96Publisher
ELSEVIER SCIENCE BV
DOI: 10.1016/j.physe.2016.08.020
Keywords
Thermal conductivity; Hybrid nanofluid; Artificial neural network; Experimental data; MgO-MWCNTs
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In this paper, the thermal conductivity ratio of MgO-MWCNTs/EG hybrid nanofluids has been predicted by an optimal artificial neural network at solid volume fractions of 0.05%, 0.1%, 0.15%, 0.2%, 0.4% and 0.6% in the temperature range of 25-50 degrees C. In this way, at the first, thirty six experimental data was presented to determine the thermal conductivity ratio of the hybrid nanofluid. Then, four optimal artificial neural networks with 6, 8,10 and 12 neurons in hidden layer were designed to predict the thermal conductivity ratio of the nanofluid. The comparison between four optimal ANN results and experimental showed that the ANN with 12 neurons in hidden layer was the best model. Moreover, the results obtained from the best ANN indicated the maximum deviation margin of 0.8%. (C) 2016 Elsevier B.V. All rights reserved.
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