Search

Machine- and deep-learning methods are used for industrial applications in prognostics and health management (PHM) for semiconductor processing and equipment anomaly detection to achieve proactive equipment maintenance and prevent process interruptions or equipment downtime. This study proposes a Pruning Quantized Unsupervised Meta-learning DegradingNet Solution (PQUM-DNS) for the fast training and retraining of new equipment or processes with limited data for anomaly detection and the prediction of various equipment and process conditions. This study utilizes real data from a factory chiller host motor, the Paderborn current and vibration open dataset, and the SECOM semiconductor open dataset to conduct experimental simulations, calculate the average value, and obtain the results. Compared to conventional deep autoencoders, PQUM-DNS reduces the average data volume required for rapid training and retraining by about 75% with similar AUC. The average RMSE of the predictive degradation degree is 0.037 for Holt–Winters, and the model size is reduced by about 60% through pruning and quantization which can be realized by edge devices, such as Raspberry Pi. This makes the proposed PQUM-DNS very suitable for intelligent equipment management and maintenance in industrial applications. [ABSTRACT FROM AUTHOR]

• A novel method modifying suction port based on non-uniform pressure was proposed. • The suction delay was studied with different radial ports and speeds. • The effect mechanism of suction bearing distance was clarified. • Two modified machines with new suction arrangement were tested to prove the method. To improve the efficiency of the twin-screw refrigeration compressor at a high speed of about 3000 rpm, the suction arrangement was investigated in this paper. Several simplified CFD models of a twin-screw refrigeration compressor for chillers were established to parametrically analyze the influence of the suction delay, rotor wrap angle, and suction bearing distance. The parametric studies showed that the volumetric efficiency could be improved by 3 % by a suction delay of 18°, and more volumetric efficiency could be improved by shortening the length of it. The optimal delay angle was found to be linear with the rotational speed. Increasing the wrap angle from 300° to 330°, the volumetric efficiency decreased by 2–3 %, and the adiabatic efficiency increased by about 0.2 %. By increasing the distance between the suction bearings and the rotor end face from 5 mm to 80 mm, the isentropic efficiency increases by about 1.4 %. Based on the parametric studies, two modified machines were built and tested by experiments. Experimental results showed that the volumetric efficiency of machines #1 and #2 increased by 1.5 % at 3000 rpm. The isentropic efficiency of machine #2 increased by 0.78 % at 3000 rpm and 1.27 % at 3300 rpm. [ABSTRACT FROM AUTHOR]

The present study focuses on modeling the solid oxide fuel cell power plant combined with an absorption-ejection refrigeration cycle. First, a comparison is made between the absorption chiller refrigeration cycle and the absorption-ejection chiller to connect the superior cycle to the solid oxide fuel cell as an auxiliary cycle. Then, the solid oxide fuel cell cycle, the combustion of the output product, the heat recovery unit combined with the refrigeration cycle, and freshwater production are modeled. Next, the sensitivity analysis is presented in order to study the effect of the design parameters on objective functions, which simplifies the justification of the optimization results based on the genetic algorithm. In order to perform optimization, machine learning methods have been employed to reduce computational time and cost. The optimization of this cycle shows that the exergy efficiency is enhanced up to 68%, whereas the overall cost rate is in within 9.7–10.4 dollars per hour. • An integrated gSOFC cycle power plant is proposed, modeled, and designed. • A parametric study is conducted to study the effect of design variables. • Using ejector absorption chiller to increase the efficiency. • Optimal design is performed through a multi-objective optimization method. [ABSTRACT FROM AUTHOR]

The latent heat storage of phase change materials (PCMs) can be used in refrigeration and air conditioning systems. Storing cool energy during the nighttime (off-peak hours) and releasing the cool energy during the daytime (on-peak hours) to reduce the number of starts of the chiller and pumps is a practical approach for achieving energy saving and carbon reduction. Therefore, selecting PCMs is vital for improving energy efficiency and preventing future energy shortages. However, selecting PCMs is complicated by their unique characteristics and types. The purpose of this study was to establish a PCM selection model by combining the Delphi, analytic hierarchy process (AHP), and VIseKriterijumska Optimizacija I Kompromisno Resenje (VIKOR) methods to select the optimal PCM type applied in cold storage. A numerical example was used to verify the model's usability, confirming that A9 is the optimal PCM for the cold storage of an air conditioning system. This three-stage PCM selection model combining the Delphi, AHP, and VIKOR approaches provides a more suitable selection model and considers the selection method of material criteria. Moreover, it can solve the problem of difficult PCM selection. Simultaneously, it considers mechanisms to incorporate a company's primary considerations into material selection for real-world applications. These results can facilitate material evaluation and selection during system design and material qualification, helping companies achieve the goals of energy saving, carbon reduction, and sustainable management in the future. [ABSTRACT FROM AUTHOR]

Featured Application: Electric Vehicle, Data Center, Simulink, etc. This study examines the use of meta-heuristic algorithms, specifically particle swarm optimization and genetic algorithms, for optimizing thermal systems, addressing a research gap on their efficacy in larger systems. Utilizing MATLAB's Simulink and Simscape, the research initially targets an electric vehicle thermal system model, emphasizing the optimization of a Li-ion battery pack and associated cooling components, like chillers, pumps, and cooling plates, during operation. One consideration is the use of a glycerol–water mixture in the chiller pump, which demands the use of an optimal control algorithm that adjusts to outdoor temperatures and control strategies. This study focuses on computational efficiency reflecting the complexity of system simulations. Challenges related to applying particle swarm optimization and genetic algorithms to these systems are scrutinized, leading to the establishment of a new objective function to pinpoint target values for system optimization. This research aims to refine design methodologies for engineers by harmonizing optimal design with computational expediency, thereby enhancing the engineering design process in thermal management. This integrative approach promises to yield practical insights, benefiting engineers dedicated to the advancement of thermal system design and optimization. The results show that, compared to the base model, 1% of the overall state of charge could be saved, and the battery temperature could also be cooled by more than 4 °C compared to the initial temperature. [ABSTRACT FROM AUTHOR]

• Characteristics of non-uniform pressure in a twin-screw compressor are revealed. • A new phenomenon of pressure waves inside a twin-screw compressor is discovered. • A fast method to estimate the influence of pressure waves is proposed. • A novel direction for the compressor design is suggested. To achieve higher efficiency of twin-screw compressors for refrigeration, the non-uniform internal pressure distribution in the rotor chamber and the flat section in the p-θ diagram were investigated in this paper. A three-dimensional CFD model of a twin-screw refrigeration compressor for chillers was established to analyze the generating mechanism of the flat section in the p-θ diagram. The p-θ diagrams of the compressor were compared under different rotational speeds and working fluids. Analysis results showed that the flat section in the p-θ diagram is caused by the periodic pressure wave propagation and reflection along the working chamber, and the pressure along the chamber is non-uniform when the sound speed is relatively slow compared with the chamber length in one compression cycle. A dimensionless ratio of chamber length and pressure wave travel distance is proposed to estimate the pressure distribution in the working chamber, based on which the flat section is prone to appear in large-scale compressors with low sound speed refrigerants like R134a. Some improvement directions were put forward to avoid efficiency losses, i.e., appropriately delaying the suction end angle and modifying the discharge port to match the pressure distribution. [ABSTRACT FROM AUTHOR]

Cogeneration and trigeneration systems have been broadly employed as part of the strategies oriented toward rational energy use. The assessment of these systems must include simultaneous considerations of costs, irreversibility, energy losses, and their causes. This work presents a step-by-step thermoeconomic analysis of a microcogeneration unit, composed of an internal combustion engine and an NH3-water single-effect absorption refrigeration chiller. The research employed the Theory of Exergetic Cost method to determine monetary and energy costs and the exergy efficiency of equipment. It is therefore, possible to identify which pieces of equipment present the highest impact and focus on these to improve the overall performance of the energy system. Although not part of the Theory of Exergetic cost, exergoeconomic parameters can be calculated to expand the assessment further. The highest specific exergy cost is associated with the endothermic reaction inside the absorber (282 $/GJ), while the lowest specific exergy cost is due to electricity consumed by the pump of the refrigeration system (2.16 $/GJ). The highest exergy efficiency was identified at the condenser (almost 90%, while values under 40% were obtained for the engine, pump, and absorber. The combined analysis of exergoeconomic results indicates that the lowest performances are related to the generator, the absorber, the evaporator, and the regenerator. [ABSTRACT FROM AUTHOR]

Dehumidification is one of the key challenges facing the air conditioning (AC) industry in the treatment of moist air. Over many decades, the dual role of heat exchangers of AC chillers for the sensible and latent cooling of space has hindered the thermal-lift reduction in the refrigeration cycle due to the requirements of water vapor removal at dew-point and heat rejection to the ambient air. These practical constraints of AC chillers have resulted in the leveling of energy efficiency of mechanical vapor compressors (MVC) for many decades. One promising approach to energy efficiency improvement is the decoupling of dehumidification from sensible processes so that innovative but separate processes can be applied. In this paper, an advanced microwave dehumidification method is investigated in the laboratory, where the microwave (2.45 GHz) energy can be irradiated onto the dipole structure of water vapor molecules, desorbing rapidly from the pores of adsorbent. Results show a significant improvement in performance for microwave dehumidification, up to fourfold, as compared to data available in the literature. [ABSTRACT FROM AUTHOR]

The energy consumption prediction of the chiller is an important means to reduce the energy consumption of buildings. Therefore, a novel energy consumption prediction model for chillers based on an improved support vector machine (ICA-DE-SVM) is proposed. The imperialist competitive algorithm (ICA) is used to optimize the penalty coefficient and kernel function width of SVM, greatly improving the generalization ability and prediction accuracy of the SVM model. The assimilation process is very important in ICA. Colonies of empires move randomly toward imperialists during the assimilation process in ICA, which decreases population diversity and can lead to premature convergence. Therefore, to create more new locations for colonies and increase population diversity, the idea of differential mutation proposed by differential evolution (DE) was applied to ICA. The established model was experimentally verified in an actual multi-chiller system in a building, and the results showed that the ICA-DE-SVM model could obtain good prediction results. Finally, the proposed model was compared with SVM model, PSO-SVM model, GA-SVM model, WOA-SVM model, and ICA-SVM model. With an MAPE of 0.6%, an MSE of 2.3, and an R2 of 0.9998, the findings demonstrate that the ICA-DE-SVM model has a greater prediction accuracy than the other models. [ABSTRACT FROM AUTHOR]

Copyright of Chinese Journal of Refrigeration Technology is the property of Shanghai Society of Refrigeration and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Central air-conditioning systems account for the largest share of energy consumption in public buildings, wherein the chiller room is the main source. The current empirical strategies of chiller room group control have difficulty realizing integrity, timeliness, and equipment adjustment accuracy and lead to energy wastage. Therefore, the operation strategy optimization model is of great value for achieving energy savings. This study proposed a stepwise optimization method for central air-conditioning systems, which is divided into the chilled side (the chiller and chilled water pump) and the cooling side (the chiller, cooling water pump, and cooling tower). The optimal points of the two sides are calculated sequentially and integrated as the global optimization result. To construct the stepwise optimization model, mathematical power models of the equipment in use were established to provide mathematical support for objective functions, and a short-term load prediction model with a matching optimization step size was established for energy constraints. The TRNSYS simulation model was developed to verify the energy-saving effects of the stepwise optimization model according to the energy-saving rates of 6.41% and 13.56% attained in both cases. The stepwise optimization strategy can more effectively guide practical applications and provide another way of thinking with respect to the group control optimization of chiller rooms in public buildings. [ABSTRACT FROM AUTHOR]

Considering vibration of centrifugal air-conditioning chillers at working conditions of 300Hz and 386Hz, a vibration reduction method for centrifugal air-conditioning chillers based on particle damping is proposed. Firstly, the vibration transfer path of the chillers is determined based on dynamic characteristics analysis of the chillers. Secondly, the vibration sensitive area of the compressor is determined by finite element analysis. Then the energy dissipation is calculated by the discrete element method (DEM) to determine the optimal installation scheme of the damper. Finally, the vibration reduction effect of the chillers after arranging the damper is verified by experiments. [ABSTRACT FROM AUTHOR]

The operation of chillers plant in the HVAC system is not ideally efficient in major academic buildings because the chillers are operated without accounting for the cooling load demand of the air-conditioning area of the building. The current operation of the chillers plant may fall under two cooling effects, namely excessive cooling effect that will reduce the efficiency of the chillers and inadequate cooling effect that may create an unpleasant environment inside the air-conditioning area. This is because the cooling load demand of the air-conditioning area of the building is unknown and is not numerically measured. The main aim of this study is to find the optimal operation of chillers plant in HVAC system by formulating an optimization framework with the main goal of minimizing energy consumption and electricity costs. The formulation of the optimization framework for chillers plant operation is modelled as Linear Programming (LP) to establish real representation of the chillers plant. The energy consumption profile, cooling load demand, cooling capacity and COP can be obtained by using historical data analysis. The optimization framework is modelled in GAMS v38.2.1 and solved by CPLEX solver to obtain the optimum input for the chillers plant in the HVAC system. The minimum total power consumption can be achieved by optimally coordinating the operation of chillers, cooling towers and AHUs while maintaining room temperature. From the cost comparison analysis between the current and optimal chillers plant, considerable cost reduction is expected to be less than 5 % if the chillers plant is operating efficiently or greater than 30 % if the chillers plant is not functioning effectively. Therefore, this study is beneficial to the administration of academic building to find a strategic action plan to promote cost optimization in the operation of the chillers plant. [ABSTRACT FROM AUTHOR]

A low-cost medium-power carbon dioxide (CO2) laser system is designed, constructed, and characterized to produce coherent, monochromatic laser radiation in the infrared region. The laser cavity is simulated and designed by using ZEMAX optic studio. A switch-mode high-tension pump source is designed and constructed using a flyback transformer and simulated using NI Multisim to study the voltage behavior at different node points. A prototype cooling system/chiller is designed and built using thermo-electric coolers (TEC) to remove the excess heat produced during laser action. Various parameters, such as pumping mechanism, chiller stability, efficiency, output power, and current at different applied voltages, are studied. The chiller efficiency at different output powers of the laser is analyzed, which clearly shows that the chiller's cooling rate is good enough to compensate for the heat generated by the laser system. The center wavelength of the carbon dioxide laser is 10.6 μm with an FWHM of 1.2 nm simulated in the ZEMAX optic studio. The output beam penetration through salt rock (NaCl), wood, and acrylic sheet (PMMA) at various output powers is analyzed to measure the penetration depth rate of the CO2 laser. [ABSTRACT FROM AUTHOR]

Aiming at the issues of unreasonable cooperation schemes and inappropriate setting of parameters of the refrigeration system with multi-chiller plants, this paper presents a cooperative optimization method to improve the energy performance of the system composed of water-cooled chillers and air-cooled heat pumps. The cooperative optimization process includes scheme optimization and parameter optimization. To content the dynamic cooling load, the working sequence of air-cooled heat pumps and water-cooled chillers with variable frequency chilled water pumps is first optimized. Based on the optimal scheme, a back-propagation neural network (BPNN) coupled with particle swarm optimization (PSO) is implemented to explore the preferred operating parameters of multiple chiller plants corresponding to the best coefficient of performance (COP). Compared with the performance of the initial operation module, the energy consumption of the water pump and fan decreases by over 50%, and the COP of the refrigeration system is improved by 16% (COP = 3.85) through the scheme operation. After parameter optimization, the total energy consumption is reduced by 21.7%, and COP is increased by 26.5% (COP = 4.20). Therefore, the proposed cooperative optimization method can provide useful operation guidance for the refrigeration system with multi-chiller plants. [ABSTRACT FROM AUTHOR]

In building HVAC systems, a chilled water flowmeter is an important sensor. Its reading can be used to measure the real-time cooling load, which is a critical variable for the automated control of building HVAC systems, especially central chiller plants. To maintain accurate reading data, fault detection and diagnosis (FDD) of flowmeters are necessary. The available FD/FDD methods for chilled water flowmeters have several common disadvantages: (1) high requirements on sensor integrity: multiple sensors are usually involved in the construction of energy balance models; (2) complex methodology: the fault of any monitored sensor could trigger a detection hit, and a diagnosis procedure must be used to isolate the faulty sensor; and (3) the more sensors that are involved, the more difficult it is to collect fault-free historical data for the establishment of a fault-free benchmark. To address these problems, a user-friendly fault detection (FD) method for building chilled water flowmeters is proposed in this study. The proposed method requires three types of variables to function: the pump frequency, the pump power, and the measured chilled water flow rate on the header pipe. The real-time pump frequency and electrical power data that are collected by VFDs/power meters are used to estimate the true value of the chilled water flow rate with random forest regressor. An auxiliary alarm rule is proposed to tackle the tradeoff issue between detector sensitivity and false alarm rate. Field data of a real HVAC system are used in a case study to evaluate the performance of the proposed method in comparison with three existing FD methods. The results of the validation case study suggest that compared to existing FD methods, which are based on the physical pump model, ensemble learning and clustering techniques, the proposed method could realize higher hit rates and higher alarm rates when confronting different faults (bias, noise and drift) at various levels. Besides, due to the proposed alarm rule, false alarms caused by occasional data errors are completely evaded. Sensitivity analysis to the proposed method indicates that the random forest with default hyperparameters is good enough for the FD task. In brief, the good features of the proposed method (i.e., the simple workflow, low sensor requirements, accessible robust input variable data, handy estimation model, auxiliary alarm rule with tight detection threshold) render the proposed method feasible and user-friendly for engineering practice. [ABSTRACT FROM AUTHOR]

This article provides an insight into the numerical simulation of an ammonia-water solution-based plate heat absorber, which is a crucial part of an absorption chiller. These chillers could be used as part of a stratified chilled-water storage tank configuration for coupling to a small modular reactor. The common approach utilized in the process of designing the chiller is to call the absorber a "black box" without considering the processes inside. It follows that the resulting design must be highly oversized to ensure reliable operation of the system. This article focuses on the obstacles that needs to be overcome in order to simulate the processes inside the absorber, such as stream breakup into separate droplets or absorption of ammonia. Unfortunately, we do not have any experimental data we could use to validate our simulations and thus this article should be looked at as a "proof of concept" and a possible guideline for simulations of similar phenomenon. [ABSTRACT FROM AUTHOR]

Several faults affect heating, ventilation, and air conditioning (HVAC) chiller systems, leading to energy wastage, discomfort for the users, shorter equipment life, and system unreliability. Early detection of anomalies can prevent further deterioration of the chiller and energy wastage. In this work, a data-driven approach is used in order to detect faults that usually plague chiller systems. In particular, the proposed approach employs a kernel principal component analysis (KPCA) in order to capture the normal operative conditions of the system; the learning method turns out to be effective in handling nonlinear phenomena through the use of the Gaussian kernel, which, by means of a self-tuning procedure, ensures good accuracy properties while maintaining enough generalization characteristics. The effectiveness of the proposed fault detection method is evaluated by means of tests on emulated and real chiller data. The KPCA approach is first proved to exhibit better detection performances than linear PCA, and then, it is corroborated through the comparison with local outlier factor, one-class support vector machine, and isolation forest. [ABSTRACT FROM AUTHOR]

This paper presents a case study for measuring and simulating the vibration and radiated sound for a large complex industrial chiller. We describe a simulation framework based on statistical energy analysis (SEA), which is populated using a hybrid mix of analytic, numerical, and measurement techniques. This hybrid approach was motivated by preliminary measurements of vibration and sound from the operating chiller, as well as a series of vibroacoustic transfer functions measured during quiescent non-operating conditions. Some components, like the chiller condenser shell, are modally dense and well suited to statistical estimates of SEA parameters like modal density and coupling between the shell modes and internal and external acoustic spaces. Other components, like the discharge pipe between the compressor and condenser shell, have only a few well separated modes with low damping. This component is better modeled using mobilities either measured or calculated using finite element analysis. We estimate other parameters like internal and coupling loss factors using a mix of analytics and measurements where appropriate. We validate the general model by comparing simulated and measured transfer functions between the discharge pipe and condenser shell — the components that radiated the most sound. We estimate structure-borne and fluid-borne input powers from the compressor using inference techniques based on transfer function measurements at quiescent conditions and averaged surface vibrations measured at operating conditions. This inference approach allows for estimating input powers over any chiller operating condition. Simulated vibrations and radiated sound are generally within 3 dB of measurements for several operating conditions. This case study provides a useful general methodology for modeling and measuring the vibroacoustics of chillers and other complex machinery. [ABSTRACT FROM AUTHOR]

[Display omitted] • The solar still by PCM, HP and HPET methods was assessed. • These methods increase thermal efficiency and productivity of the solar stills. • Comparing various solar stills using CO 2 , SO 2 and NO reduction was studied. • CPL and produced water of SSHP-PCM-2 was about 0.0458 $/L and 2248 ml/m2. This study comparatively assesses the efficiency of various single-slope solar stills employing thermosyphon and pulsating heat pipe evacuated solar collectors, integrated with phase change material. The evaporator of the thermosyphon/pulsating heat pipe system is affixed to the evacuated tube, while the condenser is immersed in water to assist the transfer the solar irradiation heat energy. Paraffin wax is utilized as the PCM, positioned at two filling ratios within the thermosyphon/pulsating heat pipe evacuated tube at two filling ratios of 50 % and 100 %, to investigate its impact on water production during periods of low solar irradiation. The thermal energy of the solar radiation stored in the PCM and remove it to the thermosyphon/pulsating heat pipe system. The findings demonstrate that the highest daily freshwater production was 2248 ml/m2, showcasing a notable 40.7 % increase in productivity compared to conventional solar stills (CSSs). Moreover, the system employing pulsating heat pipe and full PCM showcased significant reductions in CO 2 , SO 2 , and NO emissions, approximating 19.53 tons, 117.1 tons, and 449.2 tons, respectively. Additionally, solar stills utilizing heat pipes (SSTHP) and solar stills employing pulsating heat pipes (SSPHP) exhibited energy efficiencies of 19.4 % and 20.3 %, respectively. Furthermore, the exergy-economic factors for CSS, SSTHP, and SSPHP were approximately 1.27 kWh/$, 1.56 kWh/$, and 1.62 kWh/$, respectively. [ABSTRACT FROM AUTHOR]

• Stirling engine and ICE are combined in a CCHP system to produce power. • COP of absorption chiller is improved by weak solution recycling to absorber. • Net electrical efficiency of over 37 % and total efficiency > 60 % can be achieved. • Payback period is < 6 years if the rotational speed is > 4000 rpm and the working time is > 4000 h/year. This work proposes a combined cooling, heating and power (CCHP) system based on biomass gasification with an internal combustion engine (ICE), a Stirling engine and an absorption chiller. The energy and exergy efficiencies and economic performance of the CCHP are evaluated under different working conditions by thermodynamic model and net present value method. The Stirling engine recovers the high temperature potential of syngas during cooling process and improves the CCHP output power by 14 % along with ICE, while the thermal efficiency of ICE reaches 39 % at 5000 rpm. In this work, about half of the total exergy destruction comes from ICE rather than gasifier due to the utilization of Stirling engine as an additional mover to produce electricity. The recycling of weak solution in absorber is adopted in order to increase the COP (Coefficient of performance) of single-effect absorption chiller. The COP could be increased by 7 % and reach 76 % as half of the weak solution recycling to absorber. The electric efficiency and total CCHP efficiency of this system reach 37 % and more than 60 %, respectively. The payback period is estimated to be less than 6 years at an ICE rotational speed of over 4000 rpm and an operation time of more than 4000 h/year. [ABSTRACT FROM AUTHOR]

The aim of the study was to analyze the total microflora in aerobically packed buffalo meat stored under chiller (4±1oC) condition using chemical indicators of spoilage. Buffalo meat was kept in chiller (4±1oC) and analyzed on alternate days from 1st day to 7th day. Various chemical indicators analyzed were pH, TVBN, free amino acids (FAA), FDA hydrolysis and D-glucose concentration. Standard plate count (SPC) values of meat sample were also evaluated on each experimental day. Except D-glucose concentration, all other parameters including SPC increased significantly (P<0.05) as storage advanced. The SPC values of buffalo meat increased from 3.44 log cfu/g on day zero to 6.96 log cfu/g on day 7. The SPC showed a correlation coefficient (r) of 0.943 with both pH and TVBN, 0.953 with FAA, 0.978 with FDA hydrolysis and -0.919 with D-glucose concentration. Further. regressions equations were generated to predict SPC using correlated chemical indicators. Based on correlation coefficient and standard error of estimate, the suitability of regression equation to predict SPC using various chemical parameters as independent variable was found to be, FDAFAApH=TVBND-glucose. [ABSTRACT FROM AUTHOR]

• Development of an improved (torque free using VRF) solar powered milk cooling system. • Thermal calculation of cooling load for various milk cooling systems. • Determination of PV, battery bank and inverter capacities for solar milk cooling. • A comparative study for three vapor compression technologies in terms of power, torque load and chilling time. • T-s and p-h diagrams plotting by experimentally evaluating the developed solar milk chiller refrigeration system. The improper post milking handling and storage results in a complete wastage due to the microorganisms and bacterial multiplication present in raw milk. The torque load minimalizing in the chilling unit using a solar photovoltaic (PV) is indeed a challenging task for the smooth functioning of the milk chilling system especially for the conventional (reciprocating) type of compressors. The variable refrigerant flow (VRF) technology not only solves the toque load problem but also reduces the size of peak power requirement of PV array. The present study enables the design of an improved solar chilling system consists of a chilling tank (200 L capacity) coupled with one tonne of refrigeration unit powered by PV panels (2 kWp) and employing VRF technology to make system more energy efficient by reducing the torque load. Experiments were conducted using different batch sizes (50, 100, 150 and 200 L) to decrease the raw milk temperature from 30 °C to 4 °C. During optimization phase the comparative power required to run various types of compressors (reciprocating, rotary with capacitor and rotary with VRF) were found to be 1.8 kW, 1.2 kW and 0.8 kW, respectively whereas the torque loads were noted to be 3.3 kW, 1.6 kW and zero kW for respective compressor type. The experimental and modeled predicted power consumption and chilling time under different batch sizes revealed excellent correlation coefficient (R2 = 0.99, P < 0.0001). Around one tonne of refrigeration unit is sufficient to chill 200 L of milk up to 4 °C within less than two hours. [ABSTRACT FROM AUTHOR]

Conventional solar heat-driven single stage two bed chillers demand a large area for installation of solar thermal collector to activate the chiller, but in a highly populated tropical country open spaces is insufficient. In the intention to utilize accessible solar energy with better performance, a mathematical investigation is carried out with a three bed adsorption cooling unit working with silica gel-water pair. The studied chiller is powered by direct solar heat collected by a series of compound parabolic concentrator solar thermal collectors without any heat or mass recovery. The working principal of the chiller is, in principle, the same as the conventional two-bed adsorption chiller. However, instead of two half cycles, there are three one third cycles in the proposed chiller in which at every cycle the former desorber is kept in the precooling mode and as an adsorber for the next two one third cycles, respectively. As desorption kinetic is faster than the adsorption kinetics, this longer precooling mode helps the silica gel granules to adsorb more water molecules and increase evaporation rate. Hence, a better cooling effect of at least 1°C can be observed, increases chiller working hour after sunset for almost a further one hour. [ABSTRACT FROM AUTHOR]

• Dimensionless energy-matching parameters and map are established, respectively. • ESR, CO 2 ER and CostR of two cooling supply modes based systems are compared. • FOL strategy is proposed and the comprehensive operation strategy maps are drawn. • Boundaries (ESR > 15%) of the suitable user demands in different seasons are applied. Albeit some studies discussing the performance of the hybrid chiller based CCHP systems and the only an absorption chiller (AC) based CCHP systems from different perspectives, however, there is still lack of theoretical studies focus on the comparison of these two types CCHP systems and screen out the suitable users for CCHP systems. In this research, instead of the case study, the dimensionless energy-matching parameters and map are extracted and designed to quantitative analyses the matching performance for these two systems. Energy saving rate (ESR), CO 2 emission reduction (CO 2 ER), and operation cost reduction (CostR) for these two systems under different operation strategies are compared based on two situations: 1) the redundant electricity that systems produced neither can sold back to the grid, nor can used by the electric chiller; 2) the redundant electricity can used by the electric chiller. According to the comparison, the comprehensive operation strategy maps are drawn to guide systems running in the off-design condition, which are suitable for different energy-matching performance in ESR, CO 2 ER, and CostR. Meanwhile, an optimisation operation strategy (FOL) is proposed for the hybrid chiller based CCHP systems and its suitable application scenario is also calculated based on the operation strategy map. Finally, boundaries of suitable user demands for CCHP systems (ESR > 15%) in China are applied during summers and winters. [ABSTRACT FROM AUTHOR]

Chillers are responsible for nearly 30–40% of the energy consumption of an HVAC system. To enhance the efficiency of HVAC systems, it is necessary to optimize the operation of chillers. Conventional chiller operation strategies are mostly intended to save energy by suitably distributing the chiller cooling load in accordance with the measured cooling system data, which is typically considered noise-free. In other words, the uncertainty of the cooling system measurement and the necessity of customized optimization—as different buildings require different tradeoffs between energy-saving and indoor comfort—are usually not considered. This paper proposes a stochastic optimized chiller operation strategy based on multi-objective optimization and measurement uncertainty. The strategy consists of five steps: (1) Quantify the indoor comfort utility and energy consumption utility by using utility functions; (2) integrate these two utilities into one comprehensive utility using user-defined weights; (3) specify the measurement uncertainty distribution in the cooling system; (4) traverse each possible operation plan, and calculate the mean value (i.e., mathematical expectation) of its corresponding comprehensive utility (expected utility, EU); and (5) determine the optimal operation plan to be the one corresponding to the maximum EU value. The performance of the proposed strategy is validated by establishing a cooling system model on TRNSYS and comparing the findings with those of two conventional chiller operation strategies commonly adopted in Shanghai: the cooling load control strategy and coefficient of performance (COP) optimization strategy. Moreover, the robustness of the proposed strategy is validated by performing a comparison with the deterministic multi-objective strategy, which assumes that the measured system data is noise-free. The simulation results suggest that the proposed strategy can be customized to satisfy different optimization requirements such as less energy consumption or a high level of indoor comfort. [ABSTRACT FROM AUTHOR]

Only few studies have used Near-Infrared (NIR) spectroscopy to assess meat quality traits directly in the chiller. The aim of this study was therefore to investigate the ability of a handheld NIR spectrometer to predict marbling scores on intact meat muscles in the chiller. A total of 829 animals from 2 slaughterhouses in France and Italy were involved. Marbling was assessed according to the 3G (Global Grading Guaranteed) protocol using 2 different scores. NIR measurements were collected by performing 5 scans at different points of the Longissimus thoracis. An average MSA marbling score of 330–340 was obtained in the two countries. The prediction models provided a R2 in external validation between 0.46 and 0.59 and a standard error of prediction between 83.1 and 105.5. Results did provide a moderate prediction of the marbling scores but can be useful in the European industry context to predict classes of MSA marbling. [ABSTRACT FROM AUTHOR]