Search Results (58)

This study addresses the parallel operation of multiple compressor units in the gas injection process of gas storage facilities. A multi-objective optimization model based on the NSGA-II algorithm is proposed to maximize gas injection volume while minimizing energy consumption. Thermodynamic models of compressors and flow–heat transfer models of air coolers are established. The influence of key factors, including inlet and outlet pressures, temperatures, and natural gas composition, on compressor performance is analyzed using the control variable method. The results indicate that the first-stage inlet pressure has the most significant impact on gas throughput, and higher compression ratios lead to increased specific energy consumption. The NSGA-II algorithm is applied to optimize compressor start–stop strategies and air cooler speed matching under high, medium, and low compression ratio conditions. This study reveals that reducing the compression ratio significantly enhances the energy-saving potential. Under the investigated conditions, adjusting air cooler speed can achieve approximately 2% energy savings at high compression ratios, whereas at low compression ratios, the energy-saving potential reaches up to 8%. This research provides theoretical guidance and technical support for the efficient operation of gas storage compressor units. Full article

In this study, a numerical model of a microchannel gas cooler was developed using a segment-by-segment approach for thermohydraulic performance evaluation. State-of-the-art heat transfer and pressure drop correlations were used to determine the air and refrigerant side heat transfer coefficients and friction factors. The developed model was validated against a wide range of experimental data and was found to accurately predict the gas cooler capacity (Q) and pressure drop (ΔP) within an acceptable margin of error. Furthermore, advanced machine learning algorithms such as extreme gradient boosting (XGB), random forest (RF), support vector regression (SVR), k-nearest neighbors (KNNs), and artificial neural networks (ANNs) were employed to analyze their predictive capability. Over 11,000 data points from the numerical model were used, with 80% of the data for training and 20% for testing. The evaluation metrics, such as the coefficient of determination (R², 0.99841–0.99836) and mean squared error values (0.09918–0.10639), demonstrated high predictive efficacy and accuracy, with only slight variations among the models. All models accurately predict the Q, with the XGB and ANN models showing superior performance in ΔP prediction. Notably, the ANN model emerges as the most accurate method for refrigerant and air outlet temperatures predictions. These findings highlight the potential of machine learning as a robust tool for optimizing thermal system performance and guiding the design of energy-efficient heat exchange technologies. Full article

CFD simulations of annular coolers have often been performed on a single trolley, making it difficult for the method to provide reliable and accurate data for the optimum design of annular coolers. The present paper establishes a three-dimensional model of the entire annular cooler, uses sliding mesh to approach the actual working conditions, and through UDF, realizes the simulations of the continuous feeding process of the annular cooler, and obtains complete data for one run of the annular cooler. By comparing the simulated data with the actual measured data, the reliability of the model was verified. The temperature distribution inside the annular cooler and the temperature variation at the outlet of the waste heat recovery as well as the flow rate are also explored in detail. Subsequently, the temperature distribution inside the annular cooler, the flue gas flow, and the changes in temperature at each outlet were studied under different material layer thicknesses, and the discharge temperature under different thicknesses was obtained. Based upon the proposed method, a lot of data that cannot be obtained by traditional calculation methods can be obtained, thus shortening the cycle of optimizing the design and development of the structure and operating parameters of annular coolers. Full article

This paper presents a study on the ring formation phenomenon in lime kilns using simulation. The research focuses on the chemical recovery cycle integrated into the pulp production process at a pulp mill, with particular emphasis on the calcium cycle within the lime kilns. Lime kilns are critical components, as their unavailability can significantly impact the overall cost-effectiveness of the facility. The calcination of lime sludge occurs in a rotary kiln, where calcium carbonate in the lime sludge is converted into calcium oxide (lime). Under certain conditions, material can progressively accumulate, leading to ring formation and eventual kiln clogging, resulting in operational downtime. To investigate this issue, the authors developed a physics-based model using a finite-dimensional, one-dimensional approach that considers only longitudinal variation. Several approximations were made to maintain a reasonable simulation time without compromising accuracy. Simulations based on real operational data identified fluctuations in fuel flow rate and sulfur content from non-condensable gases as key contributors to ring formation. The results showed that these fluctuations caused instability in the temperature profiles of the solids and gas beds, leading to periods of cooling before the lime sludge reaches the outlet to the coolers. This cooling promotes the recarbonation of lime and, consequently, the formation of rings. The findings highlight that stabilizing fuel flow and managing sulfur content could mitigate ring formation and improve kiln efficiency. The developed model provides a valuable tool for predictive analysis and process optimization, potentially supporting the development of a digital twin to enhance real-time monitoring and operational control. Full article

With ambitious targets set by the EU for the reduction of emissions from the energy sector by 2030, there is a need to design and develop more building projects using renewable energy sources. Even though in Europe, heating and cooling share from renewable resources is increasing, and in 2021, the total share in this sector in Croatia was at 38%, the share of heat production by heat pumps is rather low. One possibility to increase this share is to install energy piles when constructing a building, which is becoming an increasingly common practice. This case study focuses on such a system designed for a large, non-residential building in Zagreb, Croatia. The complex was designed as 13 separate dilatations, with central heating and cooling of all facilities, covered by 260 energy piles (130 pairs in serial connection), with a length of the polyethylene pipe of 20 m in a double loop inserted within the pile. The thermo-technical system was designed as a bivalent parallel system, with natural gas covering peak heating loads and a dry cooler covering cooling peak loads when the loads cannot be covered only by ground-source heat pumps. In the parallel bivalent system, the geothermal source will work with a much higher number of working hours at full load than is the case for geothermal systems that are dimensioned to peak consumption. Therefore, the thermal response test was conducted on two energy piles, connected in series, to obtain thermogeological parameters and determine the heat extraction and rejection rates. The established steady-state heat rate defines the long-term ability to extract heat energy during constant thermal load, with the inlet water temperature from the pile completely stabilized, i.e., no significant further sub-cooling is achieved in the function of the geothermal field operation time. Considering the heating and cooling loads of the building, modeling of the system was performed in such a manner that it utilized renewable energy as much as possible by finding a bivalent point where the geothermal system works efficiently. It was concluded that the optimal use of the geothermal field covers total heating needs and 70% for cooling, with dry coolers covering the remaining 30%. Additionally, based on the measured thermogeological parameters, simulations of the thermal response test were conducted to determine heat extraction and rejection rates for energy piles with various geometrical parameters of the heat exchanger pipe and fluid flow variations. Full article

As an important part of industrial production, the optimization of circulating water systems is of great significance for improving energy efficiency and reducing operating costs. However, traditional optimization methods lack real-time and dynamic adjustment capabilities and often cannot fully cope with the complex and changeable industrial environment and energy demands. Advances in computer technology can enable people to use machine learning models to process information and data and ultimately help simplify simulation and optimization. In this paper, the circulating water system of a Fluid Catalytic Cracking (FCC) unit is optimized and evaluated based on process simulation and machine learning, adopting 284 sets of industrial operating data. The cooler network of the system is modified from a parallel structure to a series mode, and the effect is clarified using the ASPEN HYSYS software V12. Meanwhile, the fan power of the cooling tower is predicted by employing an optimized Gradient Boosting Regression (GBR) model, and the influence of the parallel-to-series transformation on the fan power is discussed. It is shown that the computer modeling results are in coincidence with the industrial data. Converting the parallel design to a series arrangement of the cooler network can significantly decrease the water consumption, with a reduction of 11%. The fan power of the cooling tower is also reduced by 8% after the optimization. Considering the changes in both water consumption and fan power, the saved total economic cost is 8.65%, and the decreased gas emission is 2142.06 kg/h. By building the optimization prediction system, the real-time sequencing and monitoring of equipment parameters are realized, which saves costs and improves process safety. Full article

This study seeks to improve the performance of a low-temperature differential free-piston Stirling air conditioner (FPSAC). To achieve this, a novel approach is proposed, which replaces the conventional simple harmonic drive with a multi-harmonic drive. This modification aims to optimize the motion of the driving piston, bringing it closer to the ideal movement pattern. The research involves both thermodynamic and dynamic coupling simulations of the FPSAC, complemented by experimental verification of its key performance parameters. A thermodynamic model for the gas medium, employing a quasi-one-dimensional dynamic approach for compressible fluids, and a nonlinear two-dimensional vibration dynamic model for the solid piston are developed, focusing on the low-temperature differential FPSAC physical model. The finite difference method is employed to numerically simulate the entire system, including the electromagnetic thrust of the multi-harmonic-driven linear oscillating motor, fluid transport equations, and the nonlinear dynamic equations of the power and gas control pistons. Variations in displacement, velocity, and pressure for each control volume at any given time are obtained, along with the indicator and temperature–entropy diagrams after the system stabilizes. The simulation results show that, in cooling mode, assuming no heat loss or mechanical friction, the Stirling cooler operates at a frequency of 80 Hz. Using the COP_sin value for the simple harmonic drive as a baseline, performance is improved by altering the driving method. Under the multi-harmonic drive, the COP_c5 increased by 10.03% and COP_c7 by 14.23%. In heating mode, the COP under the multi-harmonic drive improved by 0.51% for COP_h5 and 2.61% for COP_h7. Performance experiments were conducted on the low-temperature differential FPSAC, and the key parameter test results showed good agreement with the simulation outcomes. The maximum deviation at the trough was found to be less than 2.45%, while at the peak, the maximum error did not exceed 3.61%. When compared to the simple harmonic drive, the application of the multi-harmonic drive significantly enhances the overall efficiency of the FPSAC, demonstrating its superior performance. The simulation analysis and experimental results indicate a significant improvement in the coefficient of performance of the Stirling cooler under the multi-harmonic drive at the same power level, demonstrating that the multi-harmonic drive is an effective approach for enhancing FPSAC performance. Furthermore, it should be noted that the method proposed in this study is applicable to other types of low-temperature differential free-piston Stirling air conditioners. Full article

This study investigates the efficiency of cold storage warehouses and contributes to sustainable supply chain management by integrating eco-friendly practices into storage operations. In facilities for milk and its derivatives, unregulated order handling significantly increases energy consumption due to frequent door openings in the cooler. To address this challenge, we developed a novel mathematical model aimed at optimizing order sequences and minimizing energy costs, addressing a previously unexplored gap in the literature. A genetic algorithm (GA) was employed to solve this model, with careful consideration of carbon emissions generated during the algorithm’s execution. We utilized the Yates notation, an experimental design technique, to systematically optimize the GA’s parameters, ensuring robust and statistically valid results. This methodology enabled a thorough analysis of the factors influencing energy consumption. The findings enhance energy efficiency in cold storage warehouses, leading to reduced carbon dioxide emissions and fostering sustainable practices within supply chain management. Ultimately, this study successfully integrates green practices into cold storage operations, supporting broader sustainability objectives. Full article

In the early construction of an underground gas storage facility in an oil and gas field in southwest China, the increasing gas injection volume led to a continuous rise in energy consumption, which affects the economic sustainability of gas injection and extraction. In order to improve efficiency and reduce energy consumption, optimization of the pressurization process was carried out. An optimization model for the process of pressurization in underground gas storage has been established. Based on the model, a joint optimization approach is applied, where MATLAB is responsible for the iterative process of finding the optimal parameter combinations and HYSYS is responsible for the establishment of the process and calculation of the results of the process parameters. The key parameters include the outlet parameters of the compressor and the air cooler, which are critical in determining the overall energy consumption and operational performance of the system. Accordingly, the results related to the optimal parameter combinations for two-stage compression and three-stage compression were obtained in the case study. Compared with one-stage compression, two-stage and three-stage compression can diminish energy consumption by 1,464,789 kJ/h and 2,177,319 kJ/h, respectively. The reduced rate of energy consumption of three-stage compression was 16.10%, which was higher than that of two-stage compression by 10.83%. Although the construction costs of three-stage compression were higher than those of two-stage compression, from the perspective of long-term operation, three-stage compression had lower operating costs and superior economy and applicable value. The research results provided scientific references and new ideas for the optimization and adjustment of the pressurization process in underground gas storage. Full article

The automotive industry is increasingly focused on developing more energy-efficient and eco-friendly air-conditioning systems. In this context, CO₂ microchannel gas coolers (MCGCs) have emerged as promising alternatives due to their low global warming potential (GWP) and environmental benefits. This paper explores the application of machine learning (ML) algorithms to predict the thermohydraulic performance of MCGCs in automotive air-conditioning systems. Using data generated from an experimentally validated numerical model, this study compares various ML techniques, including both linear and nonlinear regression models, to forecast key performance metrics such as refrigerant outlet temperature, pressure drop, and heat transfer rate. Spearman’s correlation was employed to develop performance maps, whereas the R² and MSE metrics were used to evaluate the models’ predictive accuracy. The linear models gave around 70% forecasting accuracy for pressure drop across the gas cooler and 97% accuracy for refrigerant outlet temperature, whereas the nonlinear models achieved more accurate predictions, with an accuracy ranging from 71% to 99%. This implies that nonlinear regression generally performs better than linear regression models in assessing the overall thermohydraulic performance of microchannel gas coolers. This research brings forth new ideas on how ML methods can be applied to enhance efficiency and effectiveness in gas coolers, contributing to the development of more eco-friendly automotive air-conditioning systems. Full article

Thermal management technology based on loop heat pipes (LHPs) has broad application prospects in heat transfer control for aerospace and new energy vehicles. LHPs offer excellent heat transfer performance, reliability, and flexibility, making them suitable for high-heat flux density, high-power heat dissipation, and complex thermal management scenarios. However, due to limitations in heat source temperature and heat transfer power range, LHP-based thermal management systems still face challenges, especially in thermohydraulic modeling, component design, and optimization. Steady-state models improve computational efficiency and accuracy, while transient models capture dynamic behavior under various conditions, aiding performance evaluation during start-up and non-steady-state scenarios. Designs for single/multi-evaporators, compensation chambers, and wick materials are also reviewed. Single-evaporator designs offer compact and efficient start-up, while multi-evaporator designs handle complex thermal environments with multiple heat sources. Innovations in wick materials, such as porous metals, composites, and 3D printing, enhance capillary driving force and heat transfer performance. A comprehensive summary of working fluid selection criteria is conducted, and the effects of selecting organic, inorganic, and nanofluid working fluids on the performance of LHPs are evaluated. The selection process should consider thermodynamic properties, safety, and environmental friendliness to ensure optimal performance. Additionally, the mechanism and optimization methods of the start-up behavior, temperature oscillation, and non-condensable gas on the operating characteristics of LHPs were summarized. Optimizing vapor/liquid distribution, heat load, and sink temperature enhances start-up efficiency and minimizes temperature overshoot. Improved capillary structures and working fluids reduce temperature oscillations. Addressing non-condensable gases with materials like titanium and thermoelectric coolers ensures long-term stability and reliability. This review comprehensively discusses the development trends and prospects of LHP technology, aiming to guide the design and optimization of LHP. Full article

This article presents modeling results and a comprehensive analysis of evaporative cooling systems designed for electric motors using the refrigerants R744 (trans-critical), R134a, R600a, and R290. This study aims to determine the most suitable refrigerant for use in a cooling system, optimize the system design, and calculate the maximum achievable motor power while adhering to specified temperature constraints. The modeling was validated by an experimental setup, which had the cooling system’s configuration featuring three circuits for motor housing, stator, and rotor cooling, respectively. The modeling of an evaporative system was used to present the cooling efficiency under varying loads and external temperature conditions. Mathematical modeling encompasses complex algorithms to simulate heat transfer phenomena, accounting for fluid dynamics and refrigeration cycle dynamics. The analyses revealed trends in winding temperature, rotor temperature, air temperature inside the motor, heat transfer coefficient, coefficient of performance (COP), and motor power across different operating conditions while using different cooling refrigerants. The maximal heat transfer coefficients were calculated for all the refrigerants for winding temperatures in the range from 32 to 82 °C, while air temperature and rotor temperatures were between 42 and 105 °C and 76 and 185 °C, respectively. Lowering the evaporation temperature of the coolant to −35 °C resulted in a significant decrease in the winding temperature to 15 °C, air temperature to 38 °C, and maximum rotor temperature to 118 °C at a motor power of 90 kW. Refrigerant R744 emerged as a promising option, offering high heat transfer coefficients and achieving high motor power within temperature limits. At the same time, the COP was lower when compared with other working fluids because of the high ambient temperature on the gas cooler side. Full article

Hot gas around a supermassive black hole (SMBH) should be captured within the gravitational “sphere of influence”, characterized by the Bondi radius. Deep Chandra observations have spatially resolved the Bondi radii of five nearby SMBHs that are believed to be accreting in hot accretion mode. Contrary to earlier hot accretion models that predicted a steep temperature increase within the Bondi radius, none of the resolved temperature profiles exhibit such an increase. The temperature inside the Bondi radius appears to be complex, indicative of a multi-temperature phase of hot gas with a cooler component at about 0.2–0.3 keV. The density profiles within the Bondi regions are shallow, suggesting the presence of strong outflows. These findings might be explained by recent realistic numerical simulations that suggest that large-scale accretion inside the Bondi radius can be chaotic, with cooler gas raining down in some directions and hotter gas outflowing in others. With an angular resolution similar to Chandra and a significantly larger collecting area, AXIS will collect enough photons to map the emerging accretion flow within and around the “sphere of influence” of a large sample of active galactic nuclei (AGNs). AXIS will reveal transitions in the inflow that ultimately fuels the AGN, as well as outflows that provide feedback to the environment. This White Paper is part of a series commissioned for the AXIS Probe Concept Mission; additional AXIS White Papers can be found at the AXIS website. Full article

Domestic heating systems across northern Europe are responsible for a substantial fraction of their countries’ carbon footprints. In the UK, the vast majority of home space heating is via natural gas boilers with ‘wet’ hydronic radiator systems. Most of those use TRVs (thermostatic radiator valves) for micro-zoning, to avoid overheating, improve comfort and save energy. To meet Net Zero targets, 20 million such UK gas systems may be retrofitted with heat pumps. Heat pump system designers and installers are cautious about retaining TRVs in such systems in part because of worries that TRV temperature setbacks that lower heat demand may raise heat pump electricity demand in a “bad setback effect”, thus wasting energy. This paper presents a new view of heat pump control and provides the first exploration of this issue through the development of a simple physics-based model. The model tests an installation industry claim about the negative effect of TRVs, and finds that though real it should not apply to typical UK retrofits with weather compensation. The energy efficiency benefits of TRVs for older and partly occupied homes, and to keep bedrooms cooler, remain valid. Comfort-seeking householders and installers should know that setting ‘stiff’ temperature regulation may invoke the bad setback effect and cost dearly in energy and carbon footprint. Full article

This article presents an analysis of three different approaches to the identification of the thickness of the fouling layer inside the pipes of natural gas (NG) coolers. At present, there is no existing simple analytical procedure for the identification of the fouling layer thickness. The authors of this article describe in detail the balance method, which required the use of a large number of physical parameters, changes in their sizes depending on the output temperature of the gas, the temperature of the cooling air, the air quantity, as well as the physical properties of both media. The computational model was robust, and its disadvantage was the iterative computation. The second analysed method was a dimensional analysis. It was applied using the Buckingham’s theorem to express the individual similarity criteria. In this method, 10 simplexes and two complexes were created. The fouling layer thickness, expressed using a derived criterial equation, exhibited real results. The third analysed method was based on analysing selected physical parameters with the use of a multiple regression analysis in MinitabX 18 software. The analysis showed that the fouling layer thickness depended on fewer parameters than the number of parameters assumed in the dimensional analysis or the balance method. The standard deviation that was identified in the multiple linear regression for a double crossflow cooler was 0.0667 and the value of reliability (the coefficient of determination of the multiple linear regression) R² was 0.9985. Full article