{"title":"Digital Twin of an Open Cooling Tower: Experimental Studies and Numerical Validation","authors":"Lilly Zacherl, and , Thomas Baumann*, ","doi":"10.1021/acsengineeringau.4c00052","DOIUrl":null,"url":null,"abstract":"<p >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.</p>","PeriodicalId":29804,"journal":{"name":"ACS Engineering Au","volume":"5 4","pages":"347–358"},"PeriodicalIF":5.1000,"publicationDate":"2025-06-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://pubs.acs.org/doi/pdf/10.1021/acsengineeringau.4c00052","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"ACS Engineering Au","FirstCategoryId":"1085","ListUrlMain":"https://pubs.acs.org/doi/10.1021/acsengineeringau.4c00052","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q2","JCRName":"ENGINEERING, CHEMICAL","Score":null,"Total":0}
引用次数: 0
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.
期刊介绍:
)ACS Engineering Au is an open access journal that reports significant advances in chemical engineering applied chemistry and energy covering fundamentals processes and products. The journal's broad scope includes experimental theoretical mathematical computational chemical and physical research from academic and industrial settings. Short letters comprehensive articles reviews and perspectives are welcome on topics that include:Fundamental research in such areas as thermodynamics transport phenomena (flow mixing mass & heat transfer) chemical reaction kinetics and engineering catalysis separations interfacial phenomena and materialsProcess design development and intensification (e.g. process technologies for chemicals and materials synthesis and design methods process intensification multiphase reactors scale-up systems analysis process control data correlation schemes modeling machine learning Artificial Intelligence)Product research and development involving chemical and engineering aspects (e.g. catalysts plastics elastomers fibers adhesives coatings paper membranes lubricants ceramics aerosols fluidic devices intensified process equipment)Energy and fuels (e.g. pre-treatment processing and utilization of renewable energy resources; processing and utilization of fuels; properties and structure or molecular composition of both raw fuels and refined products; fuel cells hydrogen batteries; photochemical fuel and energy production; decarbonization; electrification; microwave; cavitation)Measurement techniques computational models and data on thermo-physical thermodynamic and transport properties of materials and phase equilibrium behaviorNew methods models and tools (e.g. real-time data analytics multi-scale models physics informed machine learning models machine learning enhanced physics-based models soft sensors high-performance computing)