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Innovative correlation for calculating thermal performance of counterflow wet-cooling tower

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  • Khamis Mansour, M.
  • Hassab, M.A.

Abstract

This paper presents an innovative correlation associating the effectiveness (ε) of the cooling tower with its number of transfer unit (NTU) and vice versa. The new correlations can be used simply to predict the performance of wet counterflow cooling tower. Those correlations are based on solving heat and mass-transfer equation “enthalpy potential method” coupling with energy equations simultaneously. The validity of the correlations was checked by experimental data reported in the available literature. The results obtained from those new correlations showed a very good agreement with deviation less than 10% with those obtained from the literature for a temperature difference between the inlet water temperature and inlet air wet-bulb temperature (Twi−Wbti) equal to or less than 10 K. The main advantages of those correlations are: (1) its simplicity to be implemented through simple calculations of input parameters; (2) it provides helpful guidelines for optimization of cooling tower performance during its operation coupling with the thermal system at which the tower is connected.

Suggested Citation

  • Khamis Mansour, M. & Hassab, M.A., 2014. "Innovative correlation for calculating thermal performance of counterflow wet-cooling tower," Energy, Elsevier, vol. 74(C), pages 855-862.
    • Handle: RePEc:eee:energy:v:74:y:2014:i:c:p:855-862
    DOI: 10.1016/j.energy.2014.07.059
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    Citations

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    Cited by:

    1. Ma, Keyan & Liu, Mingsheng & Zhang, Jili, 2021. "Online optimization method of cooling water system based on the heat transfer model for cooling tower," Energy, Elsevier, vol. 231(C).
    2. Ayoub, Ali & Gjorgiev, Blaže & Sansavini, Giovanni, 2018. "Cooling towers performance in a changing climate: Techno-economic modeling and design optimization," Energy, Elsevier, vol. 160(C), pages 1133-1143.
    3. Bornman, Waldo & Dirker, Jaco & Arndt, Deon C. & Meyer, Josua P., 2016. "Operational energy minimisation for forced draft, direct-contact bulk air cooling tower through a combination of forward and first-principle modelling, coupled with an optimisation platform," Energy, Elsevier, vol. 114(C), pages 995-1006.
    4. Cui, Haijiao & Li, Nianping & Peng, Jinqing & Cheng, Jianlin & Li, Shengbing, 2016. "Study on the dynamic and thermal performances of a reversibly used cooling tower with upward spraying," Energy, Elsevier, vol. 96(C), pages 268-277.
    5. Wei Yuan & Fengzhong Sun & Ruqing Liu & Xuehong Chen & Ying Li, 2020. "The Effect of Air Parameters on the Evaporation Loss in a Natural Draft Counter-Flow Wet Cooling Tower," Energies, MDPI, vol. 13(23), pages 1-16, November.
    6. Javadpour, Reza & Zeinali Heris, Saeed & Mohammadfam, Yaghoub, 2021. "Optimizing the effect of concentration and flow rate of water/ MWCNTs nanofluid on the performance of a forced draft cross-flow cooling tower," Energy, Elsevier, vol. 217(C).
    7. Wu, Zhiyong & Lu, Zhibin & Zhang, Bingjian & He, Chang & Chen, Qinglin & Yu, Haoshui & Ren, Jingzheng, 2022. "Stochastic bi-objective optimization for closed wet cooling tower systems based on a simplified analytical model," Energy, Elsevier, vol. 250(C).
    8. Guerras, Lidia S. & Martín, Mariano, 2020. "On the water footprint in power production: Sustainable design of wet cooling towers," Applied Energy, Elsevier, vol. 263(C).

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