Optimization of operating parameters and performance evaluation of forced draft cooling tower using response surface methodology (RSM) and artificial neural network (ANN)-Reference-Cited by-同舟云学术

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

Published:2012-05 Issue:5 Volume:26 Page:1643-1650
ISSN:1738-494X
Container-title:Journal of Mechanical Science and Technology
language:en
Short-container-title:J Mech Sci Technol

Author:

Ramakrishnan Ramkumar,Arumugam Ragupathy

Publisher

Springer Science and Business Media LLC

Subject

Mechanical Engineering,Mechanics of Materials

Link

http://link.springer.com/content/pdf/10.1007/s12206-012-0323-9.pdf

Reference29 articles.

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4. R. G. Barile, J. L. Dengler and T. A. Hertwig, Performance and design of a turbulent bed cooling tower, AIChE Symposium Series, 70 (1974) 154–162.

5. S. V. Bedekar, P. Nithiarasu and K. N. Seethatamu, Experimental investigation of the performance of a counter flow packed bed mechanical cooling tower, Energy, 23 (1998) 943–947.

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