doi: 10.7763/IJCEA.2012.V3.165
Prediction of the Heat Transfer in an Air Cooler Equipped with Classic Twisted Tape Inserts using Artificial Neural Network (ANN)
A. Amiri1
,
A. M. Karami2 ,
S. F. Seyedpour1 ,
E. Rezaei2
- 1Department of Chemical Engineering, Kermanshah University of Technology, Kermanshah, Iran.
- 2Department of Mechanical Engineering, Kermanshah University of Technology, Kermanshah, Iran
Abstract
Abstract—The present study is conducted in order to demonstrate the capability of the artificial neural network (ANN) in predicting the heat transfer in an air cooled heat exchanger equipped with classic twisted tape inserts. The effects of the twist ratio of classic inserts (Y) and Reynolds number (Re) variation on average heat transfer in the air cooler are considered via this prediction. The training data for optimizing the ANN structure is based on available experimental data. The Levenberg-Marquardt back propagation algorithm is used for ANN training. The proposed ANN is developed using MATLAB functions. For the best ANN structure obtained in this investigation, the mean relative errors of 0.457% and 0.478% were reached for the training and test data respectively. The results show that predicted values are very close to experimental values.
Keywords
- Air
- cooled
- heat
- exchanger;
- classic
- twisted
- tape
- inserts;
- twist
- ratio;
- modeling;
- artificial
- neural
- network
- (ANN)
How to Cite
A. Amiri, A. M. Karami, S. F. Seyedpour, and E. Rezaei, "Prediction of the Heat Transfer in an Air Cooler Equipped with Classic Twisted Tape Inserts using Artificial Neural Network (ANN)," International Journal of Chemical Engineering and Applications, vol. 3, no. 2, pp. 81-85, 2012. https://doi.org/10.7763/IJCEA.2012.V3.165
Copyright & License
Copyright © 2012 by the authors. This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited (CC BY 4.0).
