Nanofluids enhance thermal conductivity and thereby, increase cooling capacity of cooling tower. Hence, it is necessary to analyze the cooling capacity with performance prediction of a cooling tower accurately. Therefore, an intelligent approach using fuzzy expert system (FES) of a cooling tower is employed in this study. FES links between volumetric concentration (VC), mass flow rate of liquid to air ratio (L/G) and flow rate (FR) and cooling efficiency (CE) and range (CR). Values are obtained from experiments on an induced draft cooling tower with nanofluids in different VC of 0%, 0.06%, 0.18% and 0.30%, respectively. FES model has been developed for the prediction of cooling efficiency and range with nanofluids in different VC. The developed model has been verified using various numerical statistical formulas. The relative errors are found to be less than the acceptable limit (10%). The goodness of fit found as 0.960, and 0.987, respectively, are close to 1.0 as expected.

cooling tower, nanofluid, heat transfer, FES.

Received: November 3, 2020; Accepted: December 30, 2020; Published: January 22, 2021

How to cite this article: Habibur Rahman, Altab Hossain and Mohammad Ali, Heat transfer performance prediction of a cooling tower with nanofluid using fuzzy expert system, JP Journal of Heat and Mass Transfer 22(1) (2021), 1-12. DOI: 10.17654/HM022010001

This Open Access Article is Licensed under Creative Commons Attribution 4.0 International License

[1] M. Gao, F. Sun, K. Wang, Y. Shi and Y. Zhao, Experimental research of heat transfer performance on natural draft counter flow wet cooling tower under cross-wind conditions, International Journal of Thermal Sciences 47(7) (2008), 935-941.
[2] S. Y. Yoo, J. H. Kim and K. H. Han, Thermal performance analysis of heat exchanger for closed wet cooling tower using heat and mass transfer analogy, Journal of Mechanical Science and Technology 24(4) (2010), 893-898.
[3] B. K. Naika, V. Choudharya, P. Muthukumara and C. Somayaji, Performance assessment of a counter flow cooling tower-unique approach, Energy Procedia 109 (2017), 243-252.
[4] S. P. Fisenko and A. A. Brin, Simulation of a cross-flow cooling tower performance, International Journal of Heat and Mass Transfer 50 (2007), 3216-3223.
[5] T. Jagadeesh and K. S. Reddy, Performance analysis of the natural draft cooling tower in different seasons, IOSR Journal of Mechanical and Civil Engineering 7(5) (2013), 19-23.
[6] J. C. Maxwell, A Treatise on Electricity and Magnetism, Oxford University, UK: Clarendon Press, 1873.
[7] A. Khairul, R. Saidur, M. M. Rahman, M. A. Alim, A. Hossain and Z. Abdin, Heat transfer and thermodynamic analyses of helically coiled heat exchanger using different type of nanofluids, International Journal of Heat and Mass Transfer 67 (2013), 398-403.
[8] F. M. Nasir and A. Y. Mohamad, Heat transfer of Cuo-water based nanofluids in a compact heat exchanger, ARPN Journal of Engineering and Applied Sciences 11 (2016), 2517-2523.
[9] I. Palabiyik, Z. Musina, S. Witharana and Y. Ding, Dispersion stability and thermal conductivity of propylene glycol-based nanofluids, Journal Nanoparticle Research 13 (2011), 5049-5055.
[10] X.-Q. Wang and A. S. Mujumdar, Heat transfer characteristics of nanofluids: a review, Int. J. Thermal Sciences 46 (2007), 1-19.
[11] M. A. Khairul, A. Hossain, R. Saidur and M. A. Alim, Prediction of heat transfer performance of CuO/water nanofluids flow in spirally corrugated helically coiled heat exchanger using fuzzy logic technique, Computers & Fluids 100 (2014), 123-129.
[12] M. Hosoz, H. M. Ertunc and H. Bulgurcu, Performance prediction of a cooling tower using artificial neural network, Energy Conversion and Management 48(4) (2007), 1349-1359.
[13] J. Wu, G. Zhang, Q. Zhang, J. Zhou, Y. Guo and W. Shen, A reversibly used cooling tower with adaptive neuro-fuzzy inference system, J. Cent. South Univ. Technol. 19 (2012), 715-720.
[14] H. Jaber and R. L. Webb, Design of cooling towers by the effectiveness-NTU method, J. Heat Transfer 111(4) (1989), 837-843.
[15] H. Rahman, A. Hossain and M. Ali, Experimental analysis on heat transfer performance of cooling tower with nanofluid, AIP Conference Proceedings 2121 2019, pp. 070011.
[16] L. A. Zadeh, Fuzzy sets, Information and Control 8 (1965), 338-353.
[17] A. Hossain, A. Rahman and A. K. M. Mohiuddin, Fuzzy evaluation for an intelligent air-cushion tracked vehicle performance investigation, Journal of Terramechanics 49 (2012), 73-80.