Journal
INTERNATIONAL COMMUNICATIONS IN HEAT AND MASS TRANSFER
Volume 39, Issue 8, Pages 1279-1285Publisher
PERGAMON-ELSEVIER SCIENCE LTD
DOI: 10.1016/j.icheatmasstransfer.2012.06.008
Keywords
Helically coiled tube; Artificial neural network; Heat transfer; Friction factor
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In this study, Artificial Neural Network (ANN) models were developed to predict the heat transfer and friction factor in helically coiled tubes. The experiments were carried out with hot fluid in coiled tubes which placed in a cold bath. Coiled tubes with various curvature ratios and coil pitches (nine Layouts) were used. The output data of the ANNs were Nusselt number and friction factor. The validity of the method was evaluated through a test data set, which were not employed in the training stage of the network. Moreover, the performance of the ANN model for estimating the Nusselt number and friction factor in the coiled tubes was compared with the existing empirical correlations. The results of this comparison show that the ANN models have a superior performance in predicting Nusselt number and friction factor in the coiled tubes. (C) 2012 Elsevier Ltd. All rights reserved.
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