Performance Prediction of Mechanical Draft Wet Cooling Tower Using Artificial Neural Network

Zhe Tian Xu; Jia Chen Mao; Yi Qun Pan; Zhi Zhong Huang

doi:10.4028/www.scientific.net/AMR.1070-1072.1994

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HomeAdvanced Materials ResearchAdvanced Materials Research Vols. 1070-1072Performance Prediction of Mechanical Draft Wet...

Performance Prediction of Mechanical Draft Wet Cooling Tower Using Artificial Neural Network

Abstract:

This paper proposed a prediction approach for the performance of the mechanical draft wet cooling tower based on artificial neural network (ANN). The inlet water temperature, the ambient wet bulb temperature and the ratio of water to air mass flow rate in the cooling tower were selected as the input parameters of a four-layer back propagation neural network (BPNN) to predict the temperature of the water at the tower outlet. After the test of the available data set, the BPNN results in a correlation coefficient of 0.9 between the predicted and experimental values. Thus the prediction performance is good and such prediction approach proves to be feasible and effective.

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Periodical:

Advanced Materials Research (Volumes 1070-1072)

Pages:

1994-1997

DOI:

https://doi.org/10.4028/www.scientific.net/AMR.1070-1072.1994

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Online since:

December 2014

Authors:

Zhe Tian Xu*, Jia Chen Mao, Yi Qun Pan, Zhi Zhong Huang

Keywords:

Artificial Neural Network (ANN), Performance Prediction, Wet Cooling Tower

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