Analysis of Influencing Factors on Water Use of Mechanical Draft Cooling Towers in China

Mechanical draft cooling towers are among the most critical water-consuming equipment in industries such as thermal power and petrochemicals. Strengthening their water usage performance is therefore crucial for alleviating China’s water resource pressure. To this end, this study employs the makeup water rate indicator to analyze the core factors influencing water-use efficiency in mechanical draft cooling towers, utilizing Spearman’s rank correlation coefficient analysis and partial least squares regression (PLSR) methods. The results reveal that ambient temperature and inlet pressure exhibit significant negative correlations with the makeup water rate, while blowdown pressure and concentration multiple show significant positive correlations. Gray correlation analysis indicates that blowdown pressure (correlation degree: 0.923) and concentration multiple (correlation degree: 0.897) are the key driving factors. The PLSR-based prediction model for the makeup water rate demonstrates a strong goodness of fit, with explanatory power exceeding 80%. This research provides a modeling foundation for optimizing the operational control of mechanical draft cooling towers, thereby promoting sustainable management of industrial water use.

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Publication Details

Journal
Processes
Published
2025-10-28
DOI
https://doi.org/10.3390/pr13113465
Primary Topic
Adsorption and Cooling Systems
Type
article
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article

Analysis of Influencing Factors on Water Use of Mechanical Draft Cooling Towers in China

Xue Bai, Mengting Hu, Rong Cai, Lingsi Kong
Processes
Adsorption and Cooling Systems
article

Analysis of Influencing Factors on Water Use of Mechanical Draft Cooling Towers in China

Xue Bai, Mengting Hu, Rong Cai, Lingsi Kong
article en

Abstract

Mechanical draft cooling towers are among the most critical water-consuming equipment in industries such as thermal power and petrochemicals. Strengthening their water usage performance is therefore crucial for alleviating China’s water resource pressure. To this end, this study employs the makeup water rate indicator to analyze the core factors influencing water-use efficiency in mechanical draft cooling towers, utilizing Spearman’s rank correlation coefficient analysis and partial least squares regression (PLSR) methods. The results reveal that ambient temperature and inlet pressure exhibit significant negative correlations with the makeup water rate, while blowdown pressure and concentration multiple show significant positive correlations. Gray correlation analysis indicates that blowdown pressure (correlation degree: 0.923) and concentration multiple (correlation degree: 0.897) are the key driving factors. The PLSR-based prediction model for the makeup water rate demonstrates a strong goodness of fit, with explanatory power exceeding 80%. This research provides a modeling foundation for optimizing the operational control of mechanical draft cooling towers, thereby promoting sustainable management of industrial water use.

ProcessesVol. 13(11)
China National Institute of Standardization (CN)
Openalex Percentile: Top 68%
Adsorption and Cooling Systems
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