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Optimization of operating parameters and performance evaluation of forced draft cooling tower using response surface methodology (RSM) and artificial neural network (ANN)

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Abstract

Optimization of cold water temperature in forced draft cooling tower with various operating parameters has been considered in the present work. In this study, response surface method (RSM) and an artificial neural network (ANN) were developed to predict cold water temperature in forced draft cooling tower. In the development of predictive models, water flow, air flow, water temperature and packing height were considered as model variables. For this propose, an experiment based on statistical five-level four factorial design of experiments method was carried out in the forced draft cooling tower. Based on statistical analysis, packing height, air flow and water flow were high significant effects on cold water temperature, with very low probability values (< 0.0001). The optimum operating parameters were predicted using RSM, ANN model and confirmed through experiments. The result demonstrated that minimum cold water temperature was optioned from the ANN model compared with RSM.

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Authors and Affiliations

  1. Department of Mechanical Engineering, Annamalai University, Annamalai Nagar, India

    Ramkumar Ramakrishnan & Ragupathy Arumugam

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  1. Ramkumar Ramakrishnan
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  2. Ragupathy Arumugam
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Correspondence to Ramkumar Ramakrishnan.

Additional information

Recommended by Associate Editor Ji Hwan Jeong.

R. Ramkumar received a B.E (Mechanical) degree from the University of Madras, Chennai in 1993 and M.E in Energy Engineering from Annamalai University in 2007. He has 10 years experience in power plant operations in the sugar, cement, textile and paper industries. He has completed courses in Energy Auditing (EA) and Boiler Operation Engineer (BOE). He is presently doing his research work in the area of cooling towers. His research interests are power plant operation and control.

A. Ragupathy received a B.E in Mechanical Engineering in 1989, a M.E in Thermal Engineering in 1994 and a Ph.D in Mechanical Engineering in 2008 from Annamalai University in Annamalai Nagar, Tamilnadu, India. Since 1992 he has worked on the faculty, now as Associate professor, in the Department of Mechanical Engineering at Annamalai University. He is a life member of ISTE. His research interests are Heat and Mass Transfer, Thermodynamics, and HVAC (Contact the Steam Laboratory of the Department of Mechanical Engineering at Annamalai University, Annamalai Nagar-608002, Tamil Nadu, and India.)

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Ramakrishnan, R., Arumugam, R. Optimization of operating parameters and performance evaluation of forced draft cooling tower using response surface methodology (RSM) and artificial neural network (ANN). J Mech Sci Technol 26, 1643–1650 (2012). https://doi.org/10.1007/s12206-012-0323-9

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  • DOI: https://doi.org/10.1007/s12206-012-0323-9

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