Digital Twin of an Open Cooling Tower: Experimental Studies and Numerical Validation

Increasing dynamics in surface water bodies and all-time low groundwater levels, both a consequence of global warming, put high stress on the water supply chain and require a re-evaluation of all water uses. Industry uses a significant amount of water for cooling, often in open cooling towers. We developed a digital twin for an evaporative open cooling tower, focusing on the hydrochemistry to optimize water consumption and use of inhibitor chemicals to prevent scaling. The model is based on the USGS hydrochemical standard model PhreeqC, which is controlled by Python scripts. The digital twin implements evaporation in the cooling tower, recharge of water with added inhibitors, and desalination to avoid corrosion. In contrast to previous operation strategies, which rely on a thickening ratio that can be measured using the electrical conductivity, the model allows prediction of the behavior of the cooling tower based on the saturation index for the mineral precipitates. Additionally, the digital twin offers the option of controlling the cooling tower. We present a workflow to adapt the digital twin to the actual cooling tower and to parametrize the chemicals used for the prevention of mineral scaling. The optimization objectives were to reduce the consumption of inhibitors while maintaining stable hydrochemical conditions and a benign corrosion behavior. Additionally, the digital twin should reveal possibilities for demand-driven load balancing. After site-specific adaptation of flow and evaporation rates, volumes, temperatures, and equilibrium constants for the inhibitors, the model was able to forecast the hydrochemical conditions in the cooling tower. The parameter and sensitivity analyses revealed that the total volume of water in the system and the thickening ratio have a large effect on water consumption. While slightly increased concentrations of the inhibitor would allow for significantly higher thickening ratios and slightly lower water consumption, the corrosion stability of the materials in the cooling system puts limits on this approach. Evaporation remains the main factor in water consumption. For the reference site, the digital twin revealed that the implemented operation scheme was already close to optimal conditions, considering water consumption and the use of inhibitors.

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Publication Details

Journal
ACS Engineering Au
Published
2025-06-18
DOI
https://doi.org/10.1021/acsengineeringau.4c00052
Citations
2
Primary Topic
Building Energy and Comfort Optimization
Type
article
Field-Weighted Citation Impact
2.01

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article

Digital Twin of an Open Cooling Tower: Experimental Studies and Numerical Validation

Thomas Baumann, Lilly Zacherl
2 citations
ACS Engineering Au
Building Energy and Comfort Optimization
2.01
article

Digital Twin of an Open Cooling Tower: Experimental Studies and Numerical Validation

Thomas Baumann, Lilly Zacherl
article en
2 citations

Abstract

Increasing dynamics in surface water bodies and all-time low groundwater levels, both a consequence of global warming, put high stress on the water supply chain and require a re-evaluation of all water uses. Industry uses a significant amount of water for cooling, often in open cooling towers. We developed a digital twin for an evaporative open cooling tower, focusing on the hydrochemistry to optimize water consumption and use of inhibitor chemicals to prevent scaling. The model is based on the USGS hydrochemical standard model PhreeqC, which is controlled by Python scripts. The digital twin implements evaporation in the cooling tower, recharge of water with added inhibitors, and desalination to avoid corrosion. In contrast to previous operation strategies, which rely on a thickening ratio that can be measured using the electrical conductivity, the model allows prediction of the behavior of the cooling tower based on the saturation index for the mineral precipitates. Additionally, the digital twin offers the option of controlling the cooling tower. We present a workflow to adapt the digital twin to the actual cooling tower and to parametrize the chemicals used for the prevention of mineral scaling. The optimization objectives were to reduce the consumption of inhibitors while maintaining stable hydrochemical conditions and a benign corrosion behavior. Additionally, the digital twin should reveal possibilities for demand-driven load balancing. After site-specific adaptation of flow and evaporation rates, volumes, temperatures, and equilibrium constants for the inhibitors, the model was able to forecast the hydrochemical conditions in the cooling tower. The parameter and sensitivity analyses revealed that the total volume of water in the system and the thickening ratio have a large effect on water consumption. While slightly increased concentrations of the inhibitor would allow for significantly higher thickening ratios and slightly lower water consumption, the corrosion stability of the materials in the cooling system puts limits on this approach. Evaporation remains the main factor in water consumption. For the reference site, the digital twin revealed that the implemented operation scheme was already close to optimal conditions, considering water consumption and the use of inhibitors.

ACS Engineering AuVol. 5(4)
Technical University of Munich (DE)
Bayerisches Staatsministerium für Wissenschaft und Kunst
Sustainable cities and communities
Openalex Percentile: Top 14%
Building Energy and Comfort Optimization
2.01
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