Investigation of a method to decrease water consumption and enhance productivity in wet cooling towers using dynamic time-related modeling for industrial experimental applications
Author:
Funder
Materials and Energy Research Center
Zar industrial group
Publisher
Springer Science and Business Media LLC
Link
https://link.springer.com/content/pdf/10.1007/s00231-024-03494-9.pdf
Reference30 articles.
1. Deng W, Sun F, Chen K, Zhang X (2022) New retrofit method to cooling capacity improvement of mechanical draft wet cooling tower group. Int J Heat Mass Trans 188:122589. https://doi.org/10.1016/j.ijheatmasstransfer.2022.122589
2. Zargar A, Kodkani A, Peris A et al (2022) Numerical analysis of a counter-flow wet cooling tower and its plume. Int J Thermofluids 4:100139. https://doi.org/10.1016/j.ijft.2022.100139
3. Chen K, Sun F, Zhang L et al (2022) A sensitivity-coefficients method for predicting thermal performance of natural draft wet cooling towers under crosswinds. Appl Therm Eng 206:118105. https://doi.org/10.1016/j.applthermaleng.2022.118105
4. Li X, Gurgenci H, Guan Z, Sun Y (2018) Experimental study of cold inflow effect on a small natural draft dry cooling tower. Appl Therm Eng 128:762–771. https://doi.org/10.1016/j.applthermaleng.2017.09.071
5. Zheng C, Chen X, Zhu L, Shi J (2018) Simultaneous design of pump network and cooling tower allocations for cooling water system synthesis. Energy 150:653–669. https://doi.org/10.1016/j.energy.2018.02.150
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