Performance Of Cooling Tower Research Articles

Study on the operation strategy of the water cooling system in the single-phase immersion cooling data center considering cooling tower performance

Energy analysis from an entire systems perspective can further improve the energy efficiency of single-phase immersion cooling technology. In this study, a water cooling system for the single-phase immersion data center was developed using a combination of FLOWNEX SE and FLUENT software. Firstly, the energy consumption analysis was carried out from the perspective of cooling system, and an optimal operation strategy was identified to minimize energy consumption. Furthermore, the influence of ambient temperature and chip power on the operation strategy and energy consumption were analyzed, and the optimal operation strategy under different conditions was given. Finally, a comparison was made between the two operating modes of the water cooling system. The analysis results showed that there was an optimal operation strategy which should be adapted based on ambient temperature and chip power to reduce the power consumption. Moreover, it was noted that when the environmental temperature rises above 22 °C, the PUE of the water cooling system surpasses 1.2, indicating that the water cooling system becomes unsuitable for single-phase immersion data centers in such conditions. In addition, the excessive cooling of the chip can be avoided through the optimal operation strategy. And when the chip power was 600 W, the optimal operation strategy can reduce the PUE by 16 % and save 5.71 kW energy.

Performance analysis of natural draft power plant cooling tower: Mathematical modeling of cross-flow type, application in capital cities of Iranian provinces

Cooling towers are heat exchangers that reduce the hot water temperature produced by process equipment through heat and mass transfer between water and air stream. This study investigates the performance of cross-flow cooling towers under various geometrical, physical, and environmental conditions. For this purpose, thermodynamic modeling of the cross-flow cooling tower was conducted, and the governing equations were numerically solved using the finite difference method. Unlike previous studies, the effects of water droplet deformation into an elliptical shape during its fall along the cooling tower were also considered. This deformation, which influences the drag coefficient, Reynolds number of the water droplets, droplet surface area, and its cross-section area, along with the incorporation of buoyancy force in the droplet momentum equation, led to an improvement in the results. Consequently, the maximum computational error in this case was reduced to 1.97 %, compared to the scenario where droplet deformation and buoyancy force were neglected. The change in geometrical parameters of the tower in Tehran and Rasht was investigated, revealing that increasing the outlet radius of the tower from 20 m to 22.5 m decreased the outlet water temperature by 1.21 °C and 0.67 °C and increased the thermal efficiency of the tower by 4.94 % and 2.88 % respectively, while increasing the tower height from 100 m to 120 m, only decreased the outlet water temperature by 0.47 °C and 0.26 °C, and increased the thermal efficiency of the tower by 1.89 % and 1.09 % respectively. Additionally, the cooling tower performance was assessed in the centers of different provinces .of Iran. Results showed that with an initial droplet radius of 1 mm and an inlet water temperature of 50 °C, the maximum and minimum temperature reductions occurred in Shahrekord by 20.16 °C and Bandarabbas by 12.37 °C, respectively.

Study on circulating cooling water pre-mixing for thermal performance improvement of twin thermal power units sharing one dry cooling tower

For an advanced power plant of twin thermal power units sharing one dry cooling tower, power production is easily impacted by variations in cooling tower performance. Circulating cooling water pre-mixing (CCWPM) was proposed to maximize cooling potential of the tower under varying working conditions, thereby enhancing power generation for the whole power plant. An integrated simulation model was established to capture cooling behaviors of the shared tower and operating characteristics of both power units before and after implementing CCWPM. Simulation results indicated that CCWPM effectively mitigates the uneven distribution of airflow temperature inside the shared tower and reduces the high-temperature area. As power load of one specified unit drops, both units experience a decline in power cycle efficiency, and the implementation of CCWPM further decreases the efficiency of this unit while increasing the efficiency of the adjacent unit. The whole power plant benefits from CCWPM in power generation, particularly when the unit with radiators directly facing the crosswind operates at a low power load. Power generation efficiency achieves an absolute increase of 0.43 % via CCWPM for the upwind unit and its adjacent unit operating at 40 % and 100 % power loads and the shared tower working at 8 m/s crosswind speed.

Machine learning-based optimization and performance analysis of cooling towers

In the present study, a machine learning technique was employed to select parameters and optimize the performance of a cooling tower used in a building. Input parameters and the output response values have been selected in an unstructured and structured manner. Air velocity, water flow rate and nanoparticle concentration have been considered as the input variables whereas range, cooling efficiency and energy consumption are the output variables. A Central Composite design (CCD) based technique has been adopted to structure the input-output relations. A multilayer perceptron-based ANN model has been built using both unstructured and structured combinations of data points. PSO optimization has been performed by creating the objective functions from the developed ANN models. Optimum results obtained by using the structured combination are better than those obtained by the unstructured combination. Optimum cooling tower performance was noticed for an air velocity of 14.67 m/s, water flow rate of 3.87 LPM and nanoparticle volume concentration of 1.84 vol (%).

Passive cooling and thermal comfort performance of Passive Downdraught Evaporative Cooling (PDEC) towers in a Saudi library: An on-site study

In the hot arid climate of Saudi Arabia, where air conditioning, primarily fueled by fossil fuels, accounts for a significant portion of energy consumption, the implementation of Passive Downdraught Evaporative Cooling (PDEC) towers presents a sustainable solution. This study conducts an extensive evaluation of PDEC towers in a public library, focusing on their effectiveness in reducing reliance on conventional cooling and enhancing thermal comfort. Through detailed field measurements, the study examines the influence of wind speed on the towers' cooling performance, correlating it with internal environmental conditions. The research extends to a comparative analysis of two prominent thermal comfort models: the Predicted Mean Vote (PMV) and the Adaptive Thermal Comfort (ATC) model. Findings indicate a notable interaction between wind speed and indoor air temperature, where increased wind speeds correspond to higher indoor temperatures. Despite this, the PDEC towers demonstrate a significant reduction in temperature, maintaining cooling effectiveness between 70 % and 75 %. The comparative study of thermal comfort models reveals that the ATC model provides a more relevant assessment of comfort levels in naturally ventilated spaces, with 71 % of the recorded temperatures falling within the comfortable range during the monitoring period. The research highlights the PDEC tower's potential in delivering effective passive cooling, adaptable to wind speed changes, and contributing to a sustainable and energy-efficient building environment in hot arid climates.

Investigation of the simultaneous effect of fouling and ambient conditions on cooling performance and water consumption of a wet cooling tower

The cooling performance and water consumption of the wet cooling tower are two important parameters that must be balanced to achieve the optimum performance of this industrial component in its operating condition. The performance of the wet cooling towers can be analyzed by the thermodynamic models. On the other hand, fouling can drastically affect the cooling tower performance. In the present research, a thermodynamic model is developed and validated with numerical and experimental results in order to investigate the wet cooling tower's water consumption and cooling performance under various weather conditions. The model includes an accurate cooling tower model, considering the buoyancy force and droplets evaporation in the rain and spray zones. To achieve accurate results, an optimization algorithm is also utilized to solve the equations. This model was then applied to analyze the water consumption and cooling performance of a small cooling tower during the hottest months of Iran (July/August) in Ahvaz, Tabriz, and Yazd with different climate conditions. The non-dimensional parameter of the fill performance index (ηF) was used to describe the fouling in the packing. So, considering the simultaneous effects of the buoyancy force and droplet evaporation in the rain and spray zones and fouling in packing in the developed model, with utilizing a new and accurate method to solve the model's equation to analyze the performance of the wet cooling towers under different conditions, are the novelty of this study. Based on the results, a rise in fouling decreases the fill performance index. A decline in the fill performance index from 2.4 to 1.2 increases the monthly average of the cooling tower outlet water temperature from 24.24, 21.21, and 21.19 °C to 25.94, 24.14, and 24.11 °C in Ahvaz, Tabriz, and Yazd, respectively, while the monthly water consumption decreases from 1.74, 1.87, and 2.22 m3h to 0.99, 1.10, and 1.29 m3h in the mentioned cities, respectively. The maximum outlet water temperature was observed in case ηF=1.2, while the maximum water consumption occurred in ηF=2.4. So, ambient conditions and fouling simultaneously affect the performance of the cooling tower, which is well predicted by the suggested model.

Cooling Tower Performance Efficiency in Water Treatment Unit at PT. X Sukowati

Cooling Tower Performance Efficiency in Water Treatment Unit at PT. X Sukowati

Numerical study on heat and mass transfer performance of a natural draft wet cooling tower based on baffle optimization

In the natural draft wet cooling towers (NDWCTs), the resistance of the packing layer to air and the effect of the circular design of its cross-section, the air reaches the tower center area to overcome the maximum resistance. The air velocity in the center of the tower is low and the heat transfer is poor. To improve the performance of the cooling tower, the optimized design of the cooling tower distribution pipe surface with baffles is firstly investigated. Then, the three-dimensional numerical model of NDWCTs is developed and validated with power plant data. Finally, the effect of plates on cooling tower performance is analyzed through the influence of baffles on the cooling tower air field and combined with the circulating water temperature drop, evaporation, and ventilation. Results show that the air field uniformity inside the cooling tower is effectively improved by adding baffles. The cooling efficiency of the circulating water inside the cooling tower is improved. The air velocity in the packing zone is significantly increased by adding the a1a2 type baffle and the air temperature and circulating water in the central area of the tower decreases significantly and the a1a2 baffles performed best in terms of circulating water temperature drop in the packing zone and were able to significantly improve the cooling effect. The cooling tower with pro-wall baffles can cool the circulating water better than the conventional cooling tower. This study provides ideas for subsequent structural and energy efficiency studies.

Experimental and numerical analysis of the forced draft wet cooling tower

Cooling towers are essentially large boxes designed to maximize the evaporation of water. The inlet water temperature and water to air mass flow rate ratio (L/G) significantly affect the performance of the cooling tower. The number of a transfer unit (NTU), Merkel number (Me), Lewis number (Le), and efficiency of the cooling tower define the performance of the forced cooling tower. In this research paper, different inlet water temperatures ranging from 28 °C to 42 °C and (L/G) ranging from 0.5, 1, and 1.5 were used to investigate the performance of the forced cooling tower. Mathematical modeling equations were used to calculate NTU, Me, Le, and efficiency at different inlet water temperatures and (L/G). Engineering equation solver (EES) software was used to solve these mathematical modeling equations. Further, an experimental investigation was carried to find forced cooling tower performance at different inlet water temperatures and (L/G), and results were compared with the theoretical results. The results revealed that increasing the inlet water temperature, NTU, Me, Le, and efficiency increased and were directly related to each other. Further, NTU and efficiency were increased by increasing (L/G). At the same time, the Me and Le reduced with (L/G). Finally, an acceptable and better agreement has been obtained between experimental and theoretical results. Based on obtained results, it has been concluded that higher values of inlet water temperature and (L/G) provided the higher performance of the forced cooling tower.

Studi Performa Cooling Tower berdasarkan Kualitas Air Pendingin

Cooling water is used to cool fluids with a high temperature in a closed system, such as a cooling tower or heat exchanger. Sometimes, the cooling water is specified in a long tube, which risks fouling and rusk. This research will study cooling water quality as Total Dissolved Solid (TDS), chlorine concentration, and antiscale. In the design of the cooling tower at PLTGU Tanjung Uncang, the range or limit of the permitted TDS is 50,000. If this figure has been reached, the cooling tower must be blown down. Blowdown is water in the cooling tower that is deliberately removed to avoid the concentration of impurities during heat evaporation. At PLTGU Tanjung Uncang, the permitted chlorine concentration is in the range of 0.2-0.5. Chlorine flow in the cooling tower at PLTGU Tanjung Uncang is reversed with Cl concentration and TDS. Inject Antiscale aims to maintain cooling tower performance, which aims to be anti-rust.

A liquid desiccant-assisted free-cooling system for energy-efficient data centers in hot and humid climates

Air conditioning and cooling are essential to ensure the reliable operation of data centers. Several studies have been conducted regarding the use of free cooling for energy-efficient cooling. However, free cooling faces challenges when used in hot and humid environments, which can lead to a decline in cooling tower performance. To address this issue, we propose a cooling system that utilizes a liquid desiccant to lower the humidity and improve the performance of the cooling tower, thereby reducing the energy consumption of the refrigeration system. Simulations were conducted in areas where the data centers were located, considering hot and humid climates. According to the simulation results, it was possible to achieve an average reduction of 35.12 % in cooling energy consumption by improving the performance of the cooling tower.

Recent Progress in Fill Media Technology for Wet Cooling Towers

Cooling towers are extensively utilized in diverse industries for efficient heat dissipation. Fill media are a critical component, facilitating heat and mass exchange between water and air, impacting overall cooling tower efficiency. Given its vital importance, this study comprehensively reviews recent advancements in fill media technology, illuminating cooling tower technology progress and exploring the effects of different fill media configurations and materials on cooling tower performance. It should be noted that the majority of research is focused on the Range of 2.5 °C to 25 °C and Approach of 1 °C to 9 °C. Through comprehensive analysis and evaluation, the effects of various fill media on heat transfer efficiency, water cooling capacity, and energy consumption are intensively summarized. By understanding these effects, engineers and designers can make rational decisions to optimize cooling tower performance and ensure efficient heat dissipation. Notably, in some reported cases, new fill media enhanced cooling range, effectiveness, and the Merkel number by 28%, 85%, and 131%, respectively. Ultimately, this paper serves as a valuable resource for academics, researchers, and professionals in the field of cooling tower design and thermal management. The insights provided in this study can help industries achieve greater energy efficiency, sustainability, and overall operational excellence.

Analysis of the Effect of Packing Materials (Fills) and Flow Rate on the Range and Efficiency of a Forced Draft Evaporative Cooling Tower

In the present study, experimental investigation is carried out on two different kinds of packing materials (fills). PVC fills that are traditionally used in the industry are compared and analyzed against the cellulose-based paper fills. Different mass flow rates of air are used to study the effect of the flow rate of air on the forced draft cooling tower. The volume flow rate of water also varied, and the range of the cooling tower, along with efficiency, was analyzed. Along with these two parameters, the effect of inlet water temperature on the performance of the tower was studied. Cooling tower efficiency was plotted against different L/G ratios ranging from 0.95 to 7.67. Results showed that the type of packing has a significant impact on the cooling tower performance. Paper fills gave a maximum cooling tower efficiency and range equal to 93.12% and 16.5 °C, respectively. The optimal L/G ratio range of 0.96 to 1.44 was identified as the point at which the cooling tower demonstrated its highest performance. The effect of the mass flow rate of water on the performance of the tower was far greater compared to the volume flow rate of water and inlet water temperature. The paper fills are found to be most effective under current experimental conditions, and the same can be implemented in the industrial towers under a wide spectrum of inlet water temperatures, mass flow rates of air, and volume flow rates of water.

Assessing parallel path cooling tower performance via artificial neural networks

Real-time monitoring of a research nuclear reactor, a system in which all generated power is dissipated to the environment, can be performed via analysis of the heat rejection from the cooling system. Given an inlet water temperature and flow rate, the reactor power can be well-approximated from the outlet water temperature; however, the instrumentation to measure outlet conditions may not be robust or accurate. If we know how a cooling tower performs from historical data, but cannot measure the outlet temperature, a mathematical representation of the system can be inverted to obtain the outlet water temperature that describes the cooling capacity. Unfortunately, model inversion processes are computationally expensive. To address this, an artificial neural network (ANN) is implemented to assess the performance of a multi-cell cooling tower for a nuclear reactor. This approach leverages the Merkel model to obtain an extensive data set describing performance of the cooling tower cells throughout a wide array of potential operating conditions. The Merkel model is expressed as a function of four parameters: the inlet and outlet water temperatures, inlet air wet bulb temperature, and ratio of liquid-to-gas mass flow rates (L/G), which together provide a non-dimensional number indicative of cooling tower performance, called the Merkel integral. Computing a 4-dimensional data structure that describes finite combinations of the Merkel integral, an inverse model is then generated using an ANN to determine the cell outlet water temperature from the other three model parameters along with the computed Merkel integral. Compared to traditional model inversion methods, the ANN reduces the computational time by approximately 4 orders of magnitude, with effectively no sacrifice to solution accuracy, and could be applied for different cooling towers in the event the performance curve is known. Three use cases of the ANN are then reviewed: (1) determining the cell outlet water temperatures when gas flow at rated conditions (GFRC) is known, (2) performing the prior case without knowledge of the GRFC, and (3) assessing performance differences between the individual tower cells.

Numerical study identifies the interaction between two adjacent dry cooling towers on fluid flow and heat transfer performances of the radiators at different points of each tower

A reliable thermal power plant in arid area usually has twin power-generating units equipped with two dry cooling towers. For a twin-tower configuration, a three-dimensional numerical model was built to capture thermo-hydraulic characteristics of both towers and distribution patterns of heat transfer performances of their radiators. Results showed that the interaction between two adjacent towers is a combination of negative blocking effect and positive wind-breaking effect of one tower to another, and its influences on radiators of different orientations are distinct and dependent on wind direction and speed. As wind attack angle increases, the overall cooling performance of the upstream tower improves and its sensibility to wind speed declines, while performance variation of the downstream tower shows a decrease followed by an increase. The downstream tower performs worse than the upstream tower in most crosswind cases, except for the wind situation where the downstream tower is almost entirely blocked by the upstream one. For a given wind speed of 12 m/s, cooling efficiency of the upstream (downstream) tower rises from 69.4% to 73.7% (91.7%) as wind attack angle varies from 0° to 90°, causing condenser pressure of the associated power unit to reduce from 23.5 kPa to 20.5 kPa (14.4 kPa). As the tower spacing increases, the tower interaction mitigates and cooling performance difference between the two towers narrows. The decrease of ambient temperature barely impacts cooling efficiency of the tower, but does cause a drop in condenser pressure of the unit without changing the sensitivity of condenser pressure to crosswind. The increase in condenser heat load helps to improve cooling tower performance and reduces its sensitivity to crosswind. Whereas, the growth in condenser heat load dominates the increases in condenser pressure and its sensitivity to crosswind.

Cooling tower performance and the ambiguity of the L/G ratio scheme in optimization: A single cell control volume approach

Present optimization schemes and innovative operation strategies of the cooling tower often encounter unexpected results, which may derail the effort for better efficiency. In some instances, the practice may even cause energy and water wastage. In this study, the single-cell approach is performed numerically, translating the full cooling tower fill into the smallest fundamental state of control volume to investigate the performance ambiguity attributed to the L/G ratio scheme. Two types of surface are proposed to investigate the surface effect. The actual fluid rate inside the fill varies by 20–50% between the two fill surfaces, which is relatively higher on the multi-faceted single cell. The Merkel number is integrated into the analysis by examining the liquid-gas interface for heat transfer assessment. The lower fluid rate on the circular single cell generates a higher Merkel number than the multi-faceted single cell. Even though the 32% increase in Merkel number is achieved under various liquid loads on the multi-faceted single cell, approximately half of the operating liquid load leads to decreasing Merkel number. Meanwhile, the reaction axis is introduced to characterize the surface fill under the effect of the liquid load. It is symmetrical on the circular single cell, indicating a positive linear effect to increasing liquid load. On the contrary, the reaction axis is asymmetrical on the multi-faceted single cell suggesting a negative linear effect which also leads to excess unproductive fluid rate.

ANALISIS PERFORMANCE COOLING TOWER TIPE INDUCED DRAFT COUNTER FLOW PLTP KAMOJANG UNIT 5

Cooling tower is a heat exchanger used to cool water from the condenser. The process is carried out by contacting water with air directly and discharged into the atmosphere using air fluid that is flowed naturally or flowed by a fan. Cooling tower type used in PLTP Kamojang Unit 5 is Induced draft Counter Flow. This equipment more important in increasing turbine efficiency, therefore special treatment is needed by knowing and observing the performance of the Cooling tower so that it can be analyzed in actual conditions and make decision steps in carrying out further repairs and maintenance, this is the basis of research that will be carried out by looking for value and the Cooling tower performance trendline. The calculation method uses the standard ASME PTC 23-2003 and CTI ATC-105 where the results are the calculation baseline and the historical trendline of Cooling tower performance based on the parameters of the 3-cell Cooling tower operating conditions. The parameters tested are by taking 5 valid data on PLTP KMJ Unit 5, then the Tower Capability performance values are obtained as follows, namely in the initial commissioning conditions the performance value is 92,1%, Q1 2021 is 78,8%, Q3 2021 is 74, 3%, Q4 2021 is 84,7%, and Q1 2022 is 83,8%. There was a decrease in Q3 2021. Then there was an increase in the trend in Q4 2021 due to previous overhaul activities on the Cooling tower. Keywords: Cooling tower, trendline, overhaul, tower capability

Calculation of Nuclear Reactor Cooling Tower Performance With Limited Data Streams

AbstractMonitoring of cooling tower performance in a nuclear reactor facility is necessary to ensure safe operation; however, instrumentation for measuring performance characteristics can be difficult to install and may malfunction or break down over long duration experiments. This paper describes employing a thermodynamic approach to quantify cooling tower performance, the Merkel model, which requires only five parameters, namely, inlet water temperature, outlet water temperature, liquid mass flowrate, gas mass flowrate, and wet bulb temperature. Using this model, a general method to determine cooling tower operation for a nuclear reactor was developed in situations when neither the outlet water temperature nor gas mass flowrate are available, the former being a critical piece of information to bound the Merkel integral. Furthermore, when multiple cooling tower cells are used in parallel (as would be in the case of large-scale cooling operations), only the average outlet temperature of the cooling system is used as feedback for fan speed control, increasing the difficulty of obtaining the outlet water temperature for each cell. To address these shortcomings, this paper describes a method to obtain individual cell outlet water temperatures for mechanical forced-air cooling towers via parametric analysis and optimization. In this method, the outlet water temperature for an individual cooling tower cell is acquired as a function of the liquid-to-gas ratio (L/G). Leveraging the tight tolerance on the average outlet water temperature, an error function is generated to describe the deviation of the parameterized L/G to the highly controlled average outlet temperature. The method was able to determine the gas flowrate at rated conditions to be within 3.9% from that obtained from the manufacturer’s specification, while the average error for the four individual cooling cell outlet water temperatures were 1.6 °C, −0.5 °C, −1.0 °C, and 0.3 °C.

Numerical Investigation of Cooling Tower Performance under Constant Heat Load

Numerical Investigation of Cooling Tower Performance under Constant Heat Load

Off-design optimization for solar power plant coupling with a recompression supercritical CO2 Brayton cycle and a turbine-driven main compressor

• Regression learner is utilized to predict the cooling tower performance. • Off-design optimization is performed for solar power tower with a turbine-driven compressor. • The proposed off-design control scheme improves yearly power output by 1.02%. • The high ambient temperature causes a loss of 0.66% of the yearly power output. The recompression supercritical carbon dioxide Brayton cycle is one of the most promising candidate power blocks for the solar power tower plant. As an important component, the main compressor can be driven by an electric motor or a turbine. The layout with the turbine-driven main compressor has the advantages of low cost, high efficiency, and safety during loss-of-load conditions. For such a system, the main compressor and the turbines are connected with the synchronous generator and assumed to be operated with a constant shaft speed, which has a big challenge for the operation under off-design conditions with various ambient temperatures, and the corresponding optimal operation parameters and control schemes are lacking. Especially in the condition of low ambient temperature, the traditional control scheme, which usually maintains the main compressor inlet temperature at the design-point value, obviously underestimates the efficiency of the solar power tower system. In the present study, an integrated model of solar power tower coupling with the Brayton power cycle is developed, and the particle swarm optimization algorithm is utilized to search for the optimal operation parameters and control schemes under off-design conditions with various ambient temperatures. Finally, annual performance analyses are conducted to investigate the actual effects of the proposed control schemes. The results indicate that: in the case with low ambient temperature, the proposed control scheme improves the power cycle efficiency by 0.78%; the total power output of 390 MW·h (accounting for 1.02% of the yearly power output) can be saved. In the case with high ambient temperature, the power cycle efficiency experiences an inevitable decrease, which causes the total wasted power output of 253 MW·h (accounting for 0.66% of the yearly power output); the losses caused by high ambient temperature are restrained in a small range by the proposed control schemes.