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Performance prediction of seawater shower cooling towers

Author

Listed:
  • Qi, Xiaoni
  • Liu, Yongqi
  • Guo, Qianjian
  • Yu, Jie
  • Yu, Shanshan

Abstract

The salt content in seawater results in many considerable engineering problems, including salt deposition, corrosion, and fill blockage. Seawater cooling towers are a promising potential remedy, but the lack of progress in cooling tower design technology calls for a more systematic investigation into this topic. In this study, a shower cooling tower without packing was used in seawater circulating cooling system, and a complete mathematical model of the shower cooling tower's performance was developed. The model describes the experimental data with an accuracy of about 5%. This study also conducted a comparative prediction of the outlet water temperature between freshwater and seawater in a shower cooling tower; results showed that cooling performance decreases as inlet water temperature increases. The results also show that cooling performance degrades as droplet diameter and salt concentration increase. When the air-to-water ratio increases, cooling efficiency improves, and when seawater concentration is reduced, air moisture increases at a higher rate. These results altogether provide a valuable theoretical basis for improving seawater cycling and cooling technologies in the future.

Suggested Citation

  • Qi, Xiaoni & Liu, Yongqi & Guo, Qianjian & Yu, Jie & Yu, Shanshan, 2016. "Performance prediction of seawater shower cooling towers," Energy, Elsevier, vol. 97(C), pages 435-443.
    • Handle: RePEc:eee:energy:v:97:y:2016:i:c:p:435-443
    DOI: 10.1016/j.energy.2015.12.125
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    References listed on IDEAS

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    1. Yajima, Satoshi & Givoni, Baruch, 1997. "Experimental performance of the shower cooling tower in Japan," Renewable Energy, Elsevier, vol. 10(2), pages 179-183.
    2. Givoni, B., 1997. "Performance of the “shower” cooling tower in different climates," Renewable Energy, Elsevier, vol. 10(2), pages 173-178.
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    Cited by:

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    3. Cui, Haijiao & Li, Nianping & Wang, Xinlei & Peng, Jinqing & Li, Yuan & Wu, Zhibin, 2017. "Optimization of reversibly used cooling tower with downward spraying," Energy, Elsevier, vol. 127(C), pages 30-43.
    4. Xiaoqing Wei & Nianping Li & Jinqing Peng & Jianlin Cheng & Jinhua Hu & Meng Wang, 2017. "Performance Analyses of Counter-Flow Closed Wet Cooling Towers Based on a Simplified Calculation Method," Energies, MDPI, vol. 10(3), pages 1-15, February.
    5. Li, Hailong & Wang, Bin & Yan, Jinying & Salman, Chaudhary Awais & Thorin, Eva & Schwede, Sebastian, 2019. "Performance of flue gas quench and its influence on biomass fueled CHP," Energy, Elsevier, vol. 180(C), pages 934-945.
    6. Zhou, Yuekuan & Zheng, Siqian & Hensen, Jan L.M., 2024. "Machine learning-based digital district heating/cooling with renewable integrations and advanced low-carbon transition," Renewable and Sustainable Energy Reviews, Elsevier, vol. 199(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).

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