Search Results (129)

Traditional greenhouse cooling often relies on single-pass evaporative systems that exhaust valuable moisture and CO₂ into the atmosphere. This research introduces a sustainable alternative by developing a laboratory-scale greenhouse that utilizes a closed-loop ducting system to recycle cool, humidified exhaust air back through the evaporative felt pads and water reservoir. Central to this design is an automated control architecture powered by an Arduino Uno and an SCD-30 NDIR sensor module. This low-cost integration enables real-time monitoring and autonomous regulation of fans and water pumps to maintain internal temperature, relative humidity, and CO₂ concentration within optimal physiological limits. The system’s performance was evaluated against a conventional greenhouse model lacking recirculation and automated controls. Experimental results demonstrated that the modified model (smart) significantly outperformed the standard setup (traditional), achieving an improved temperature reduction by a higher rate of 1.45 °C, compared to only 1.03 °C in the traditional model, and a significant increase in relative humidity, reaching about 9.30%, compared to only 3.36% in the traditional model. While the traditional model experienced CO₂ dissipation, the experimental system successfully retained and regulated Carbon Dioxide levels, increasing concentrations from 497 to 552 ppm. These findings suggest that integrating smart automation with air-recirculation infrastructure represents a potential trail for improving resource management in controlled greenhouse environments under arid conditions. Full article

This paper presents the results of research on an innovative, integrated IACMS (Intelligent Integrated Automation, Control, and Monitoring System), developed for energy-efficient operation of auxiliary machinery in ship engine rooms. The system, validated both in the laboratory and during full-scale operation on the MF Skania Ro-Pax ferry, integrates process monitoring, diagnostics, predictive maintenance, and intelligent energy optimization within a unified control architecture. This approach enables a significant reduction in electricity consumption while maintaining thermal safety and operational reliability. Laboratory tests focused on a pump cooling system with PLC and frequency converter control, achieving a 90.5% reduction in energy consumption compared to conventional constant-speed operation. During full-scale validation, the IACMS managed the seawater pump via adaptive frequency control (30–60 Hz). Two consecutive voyages demonstrated energy savings of 84.6% and 86.0%, with a daily energy reduction of 0.84 MWh, resulting in a decrease of approximately 0.5 tons of CO₂ emissions per day. Additionally, an observed reduction of about 6–7% in daily generator-set energy was recorded during the analyzed period; this vessel-level value is indicative, as the generator supplies multiple onboard consumers. All trials confirmed stable cooling system temperatures, and comprehensive diagnostics revealed no negative impact of inverter control on the technical condition of equipment. The findings indicate that IACMS is a universal and scalable tool for improving energy efficiency and enabling predictive maintenance in ship engine room auxiliary systems. The system was positively validated in commercial operation and certified by the Polish Register of Shipping, confirming its technological maturity and readiness for widespread adoption in the maritime industry. The results pave the way for further deployments of intelligent energy management solutions in shipping, supporting maritime decarbonization goals. Full article

The barrier fluid system in subsea boosting pumps primarily serves to seal and cool the pumps, representing a critical auxiliary system in subsea oil and gas development. Throughout their entire service life, these pumps experience both steady-state and transient operating conditions, making the monitoring of key parameters in the barrier fluid system essential. However, existing sensor configurations are relatively limited, hindering comprehensive monitoring of various components of the system, which constrains performance evaluation and optimal design. To address the sealing and cooling requirements of subsea boosting pumps, this paper establishes a system-level simulation model of the barrier fluid system based on the AMESim 2021.1 platform. The model captures the flow and pressure relationships among different components and incorporates the pump’s cooling circuit to investigate the thermal management efficiency of the barrier fluid system. Furthermore, integrated control algorithms enable automatic valve operation. The model’s accuracy is validated against measured data, and it can be used for parametric optimization to improve design and enhance overall system performance. Based on the analysis results, the model can identify optimal parameters for the subsea boosting pump barrier fluid system, providing a theoretical foundation for preventing potential issues in subsea boosting operations. Full article

This study examines the impact of chilled water supply parameters on the energy efficiency of an office building’s HVAC system located in a temperate European climate. Two cooling system variants were analyzed: (1) a traditional low-temperature system using fan-coil units and (2) a high-temperature system with chilled beams for sensible cooling. In the latter, moisture removal is performed entirely by the air handling unit, where outdoor air is dehumidified before being supplied to the space. Hourly simulations were carried out for the summer period using typical meteorological year data. Detailed heat gain calculations included transmission, occupancy, equipment, lighting, and solar radiation. Based on the cooling loads, chilled water production and distribution systems were selected, and their electricity consumption was assessed. The total energy use of chillers, ventilation units, circulation pumps, and auxiliary equipment was compared for both systems. The findings highlight the energy-saving potential of high-temperature chilled water systems, especially when integrated with centralized ventilation capable of latent load control. Additionally, results show that increasing the chilled water supply temperature significantly enhances the Energy Efficiency Ratio (EER) of chillers. Full article

Ejector-based cooling systems have gathered scientific interest as a low-cost alternative for solar-assisted cooling applications, especially in regions with solar abundance. This work presents the experimental investigation of a solar ejector cooling prototype system. The system, developed at the National Technical University of Athens, includes a custom-made ejector and is powered by a 48 m² flat plate solar collector field, assisted by an auxiliary natural gas boiler. Experimental testing under varying operating conditions was conducted to assess the system’s performance, focusing on the influence of evaporation and condensation temperatures. The maximum coefficient of performance (COP) was measured at approximately 0.160–0.165, corresponding to an entrainment ratio of 0.19 at an evaporation temperature of 9 °C and condensation temperatures of 26–27 °C. Ejector performance substantially declined with increased condensation temperatures. However, the influence of the evaporator pressure on system performance was less significant. These findings demonstrate the feasibility of ejector-based solar cooling as a sustainable solution for reducing electricity use in cooling applications, highlighting the critical influence of operating parameters in the system’s performance optimization. Full article

Optimizing chiller load (OCL) distribution in multi-chiller HVAC systems is critical for energy efficiency, yet existing algorithms often struggle with accuracy and convergence. This challenge is compounded by the fact that existing research predominantly focuses on chiller-centric optimization, often neglecting the significant energy consumption of auxiliary components. To address this gap, this study proposes a novel method utilizing Modelica/Simulink co-simulation to accurately model the entire refrigeration system, including chillers, pumps and cooling towers, thereby eliminating complex mathematical derivations and enhancing real-world applicability. To solve this holistic optimization problem, an Improved Particle Swarm Optimization (IPSO) algorithm is developed, which integrates a Phased Adaptive Decreasing Inertia Weight (PADIW) strategy, adaptive learning factors, and a mutation operator to enhance its global search capability and robustness. A case study of a shopping mall demonstrates the approach’s efficacy: over a six-month period, the optimization method reduces total refrigeration system consumption by 25.5% compared to the strategy of distributing the load equally and 15.5% compared to the human experience strategy. Notably, this case revealed that the water pumps, while accounting for less than 20% of total consumption, held a disproportionately large energy-saving potential of over 25%. Comparative experiments and Monte Carlo simulations further confirm the proposed IPSO’s superior convergence and robustness over standard PSO and other common metaheuristics. This study demonstrates that the synergy of Modelica/Simulink co-simulation and the IPSO algorithm is crucial for realizing the full energy-saving potential of the entire system, particularly from previously overlooked components like the water pumps. Full article

Addressing the challenges of high cost and complex configuration in conventional circulating fluidized bed (CFB) gasification-boiler systems, which stem from their reliance on auxiliary cooling and pressurization units, this paper proposes a novel solution. The approach involves the direct feeding of high-temperature syngas from a biomass CFB gasifier into a gas-fired boiler for combustion. This design not only fundamentally circumvents the problem of tar condensation but also renders the auxiliary systems unnecessary, resulting in a significant reduction in investment and operational expenses. Taking a biomass CFB gasifier coupled with a 20 t/h gas-fired steam boiler system (in Jiangsu Province, China) as a case study, this paper analyzes the main problems encountered during the commissioning period in the gasifier and gas-fired boiler, including slagging in the gas-fired boiler furnace, ash deposition on the tail heating surface of the gas-fired boiler and elevated exhaust gas temperature, air leakage at the lower part of the gasifier’s secondary cyclone separator, and insufficient capacity of the spiral ash cooler. Effective improvement measures are proposed. These findings provide valuable references for coupling biomass CFB gasifiers with industrial boilers and offer practical guidance for scaling up biomass CFB gasification technology. Full article

Auxiliary systems, particularly HVAC and thermal management, significantly influence electric vehicle (EV) range under diverse weather conditions. Accurate prediction of auxiliary power demand remains challenging due to nonlinear temperature dependencies and driving dynamics. Here we develop an integrated physics-based decomposition combined with an XGBoost machine learning model trained on 95,028 real-world measurements from EVs operating across multi-seasonal conditions (−8 °C to +33.5 °C). The model achieves an R² of 0.9986 and a mean absolute error of 35 W, revealing that auxiliary loads contribute variably from 75% while idle to 12% during highway driving, with heating power dominating cooling by a 7:1 ratio and increasing 44-fold at low temperatures. Feature importance analysis identifies accelerator pedal position and heating efficiency per temperature differential as primary predictors, indicating coupling between propulsion and auxiliary loads. These findings underscore the necessity of context-aware auxiliary power prediction to enhance EV energy management and range forecasting, particularly in cold climates where heating demands critically impact efficiency. Full article

The health and productivity of rabbits are highly sensitive to the environmental conditions within the rabbit house, particularly to fluctuations and deviations in temperature, relative humidity, and carbon dioxide (CO₂) concentration. However, owing to the thermal inertia and residual evaporation effects inherent in ventilation and cooling systems, environmental changes often exhibit delayed responses, rendering real-time control inadequate. Accurate prediction of key environmental parameters is indispensable for formulating effective environmental control strategies, as it enables consideration of their future dynamics and thereby enhances the rationality of regulation in rabbit farming. Existing prediction models often exhibit unsatisfactory accuracy and weak generalization, which restricts the incorporation of prediction into effective environmental control strategies. To address these limitations, summer indoor and outdoor environmental data were collected from rabbit houses in Nanping, Fujian; Jiyuan, Henan; and Qingyang, Gansu, China—three climatically distinct regions—forming three datasets. Based on these datasets, a multi-parameter time-series prediction model, Patch and Cross-Attention Enhanced Transformer for Rabbit House Prediction (PatchCrossFormer-RHP), is introduced, integrating patching and attention mechanisms. The model partitions the sequences of rabbit house temperature, relative humidity, and CO₂ concentration into patches and incorporates auxiliary parameters, such as indoor air velocity and outdoor temperature and humidity, to enhance feature representation. Furthermore, it applies cross-attention with differentiated encoding to disentangle multi-parameter relationships and improve predictive performance. This study used the Fujian dataset as the primary benchmark. On this dataset, PatchCrossFormer-RHP achieved root mean square error (RMSE) values of 0.290 °C, 1.554%, and 38.837 ppm for rabbit house temperature, humidity, and CO₂ concentration, respectively, with corresponding R² values of 0.963, 0.956, and 0.838, consistently outperforming RNN, GRU, and LSTM. Transfer experiments with single- and multi-source pretraining followed by fine-tuning on Fujian demonstrated that strong cross-regional generalization can be achieved with only limited target-domain data. Full article

Roadway anti-icing requires low-carbon alternatives to chloride salts and electric heating. This study evaluated a seasonal thermal energy storage system that couples a geothermal hydronic heated pavement (HHPS-G) with borehole thermal energy storage (BTES), operated without auxiliary heat. A coupled transient HHPS-G–BTES model was developed and validated against independent experimental data. A continuous cycle was then simulated, consisting of three months of summer pavement heat harvesting and BTES, followed by three months of winter heat discharge. A parametric analysis varied borehole depth (10, 20, and 40 m) and number of units (1, 2, and 4). Results indicated that depth is consistently more effective than unit number. Deeper fields produced larger summer pavement surface cooling with less long-term drift and yielded more persistent winter anti-icing performance. The 40 m 4-unit case lowered the end-of-summer surface temperature by 3.8 °C relative to the no-operation case and kept the surface at or above 0 °C throughout winter. In contrast, the 10 m–1-unit case was near 0 °C by late winter. A depth-first BTES design, supplemented by spacing or edge placement to limit interference, showed practical potential for anti-icing without auxiliary heat. Full article

Fuel cell trucks are a promising solution to reduce the disproportionately high greenhouse gas emissions of heavy-duty long-haul transportation. However, unlike conventional diesel vehicles, they lack combustion engine waste heat for cabin heating. As a result, electric heaters are often employed, which increase auxiliary energy consumption and reduce driving range. To address this challenge, advanced control strategies are needed to improve heating efficiency while maintaining passenger comfort. This study proposes and validates a methodology for implementing Model Predictive Control (MPC) in the cabin heating system of a fuel cell truck. Vehicle experiments were conducted to characterize dynamic heating behavior, passenger comfort indices, and to provide validation data for the mathematical models. Based on these models, an MPC strategy was developed in a Model-in-the-Loop simulation environment. The proposed approach achieves energy savings of up to 8.1% compared with conventional control using purely electric heating, and up to 21.7% when cabin heating is coupled with the medium-temperature cooling circuit. At the same time, passenger comfort is maintained within the desired range (PMV within ±0.5 under typical winter conditions). The results demonstrate the potential of MPC to enhance the energy efficiency of fuel cell trucks. The methodology presented provides a validated foundation for the further development of predictive thermal management strategies in heavy-duty zero-emission vehicles. Full article

Decentralized renewable energy sources will become fundamental to future energy systems. The energy transition toward decentralized energy sources creates opportunities and challenges for district heating companies. One of the proposed solutions for advancing decentralization is implementing hybrid district heating substations (HDHSs) into modern and future district heating networks. This paper reviews HDHS configurations and operational strategies for heating and cooling purposes described in the literature. Similar district heating systems have been compared, and their differences are discussed in this paper. This article explores the applicability of hybrid district heating substations from the perspective of district heating companies. This study demonstrates that the hybrid district heating substations could be successfully implemented into district heating systems under certain conditions. It is necessary to determine the role of the hybrid substations in the district heating system and properly select the auxiliary energy sources. This study highlights the importance of selecting an appropriate control strategy for hybrid district heating substations due to external factors, e.g., specific customer behavior or variability in the electricity market. Full article

This study presents a comprehensive experimental investigation into the frictional pressure drop of two-phase flows—boiling and condensation—in horizontal minichannels, emphasizing its impact on the energy efficiency of vapor compression systems. A total of 3553 data points were obtained using six low-GWP refrigerants (R32, R134a, R290, R410A, R513A, and R1234yf) across a wide range of operating conditions in multiport aluminum tubes with hydraulic diameters of 0.715 mm and 1.16 mm. The dataset covers mass fluxes from 200 to 1230 $\mathrm{kg}{\mathrm{m}}^{-2}{\mathrm{s}}^{-1}$, saturation temperatures between 5 °C and 55 °C, and vapor qualities from 0.05 to 0.95. Results showed a strong dependence of frictional pressure gradient on vapor quality, mass flux, and channel size. Boiling flows generated higher frictional losses than condensation, and high-density refrigerants such as R32 exhibited the largest pressure penalties, which can directly translate into increased compressor power demand. Conversely, higher saturation temperatures were associated with lower frictional losses, highlighting the role of thermophysical properties in improving energy performance. Additionally, an inverse correlation between saturation temperature and frictional pressure gradient was observed, attributed to variations in thermophysical properties such as viscosity and surface tension. Existing correlations from the literature were assessed against the experimental dataset, with notable deviations observed in several cases, particularly for R134a under high-quality conditions. Consequently, a new empirical correlation was developed for predicting the frictional pressure drop in two-phase flow through minichannels. The proposed model, formulated using a power-law regression approach and incorporating dimensionless parameters, achieved better agreement with the experimental data, reducing prediction error to within ±20%, improving the accuracy for the majority of cases. This work provides a robust and validated dataset for the development and benchmarking of predictive models in compact heat exchanger design. By enabling the more precise estimation of two-phase pressure drops in compact heat exchangers, the findings support the design of refrigeration, air-conditioning, and heat pump systems with minimized flow resistance and reduced auxiliary energy consumption. This contributes to lowering compressor workload, improving coefficient of performance (COP), and it ultimately advances the development of next-generation cooling technologies with enhanced energy efficiency. Full article

Crystallization is one of the approximately twenty unit operations and is considered to be among the most important due to the large number of chemical compounds it produces, as well as due to the enormous quantities of these substances being manufactured around the world. This article aims to present a mathematical model for the shortcut design of a cooling crystallization unit consisting of the crystallizer and auxiliary equipment, such as an evaporator with its preheater and condenser, a heat pump that acts as the cooling system of the crystallizer, and a crystallizer pressure regulator modeled as an expansion valve. The model estimates an extensive series of variables, including mass and volume flow rates of the streams, heat duties of each piece of equipment, sizing variables such as heat transfer areas of heat exchangers and volumes of the vessels, and product flow rates for each specific feed. It embraces equations for the calculation of a series of stream properties, such as density, specific heat capacity, and latent heat of vaporization. For the sizing of the crystallizer, which is the main equipment of the unit, both flow rates and crystallization kinetics are taken into account. The latter is estimated by experimental data taken in a laboratory crystallizer and includes the crystal’s growth rate as a function of residence time. Full article

The energy requirements for conditioning spaces have been increasing primarily due to population growth and climate change. This paper shows a comparison between an adsorption (ADC) and absorption cooling (ABC) systems to keep a building below the 25 °C set-point in dynamic conditions, utilizing a latent heat storage tank with MgCl₂·6H₂O and erythritol, and employing evacuated tube and parabolic trough collectors. The storage tank geometry is a plate heat exchanger. An auxiliary system was incorporated to control the temperature range of the solar cooling systems. The results showed that the coefficient of performance was kept around 0.40–0.60 and 0.70 for adsorption and absorption cooling, respectively. The latent heat storage tank with erythritol captured more solar energy than MgCl₂·6H₂O. A maximum solar fraction of 0.96 was obtained with MgCl₂·6H₂O, a thickness of 0.15 m, 20 m² of parabolic trough collector area, and absorption cooling, while the energy supply was fully satisfied with a solar collector with erythritol, a thickness of 0.1 m, 13 m² of parabolic trough area, and absorption cooling. In general, erythritol obtained better results of solar collector fractions than MCHH; however, it has less thermal stability than MgCl₂·6H₂O, and the cost is higher. Full article