The annual energy consumption of air conditioners has been a topic of interest in the air conditioning industry. Improving the annual performance factor (APF), which indicates the energy efficiency at rated, half-load and minimum-load cooling and heating conditions, is therefore required. To achieve this, a high efficiency compressor that operates at half-load and minimum-load conditions is necessary because compressors account for most of the energy consumption of air conditioners. For scroll compressors, it is necessary to reduce leakage loss and heating loss at half-load and minimum-load conditions with low rotational speed. To reduce these losses, it is important to supply the optimized amount of oil to each of suction chamber and compression chamber. This paper describes development of the high efficiency scroll compressor with the new oil supply structure to control the amount of oil supply to each of bearings and suction chamber and compression chamber independently. In this paper, the relationship between the efficiency of compressor and parameters such as the back pressure, the amount of oil supply to compression chamber and the amount of oil supply to suction chamber is reported. As a result, we optimized these parameters and improved APF by 0.8%.
The aim of this study was to determine the responses of strawberry fruit growth to environmental factors in a plant factory with artificial lighting (PFAL). June-bearing strawberry ‘Beni hoppe’ was grown in a growth chamber under a 12-h light/12-h dark photoperiod. Three temperature treatments were applied: 1) temperature decrease from 20°C to 10°C (decreased by 5°C every 4 h during the dark period); 2) temperature increase from 15°C to 25°C (increased by 5°C every 4 h during the light period); and 3) temperature decrease from 25°C to 15°C (decreased by 5°C every 4 h during the light period). The fruit diameter was measured using a contact-type digital displacement sensor and the relative rate of change in the fruit volume (R-RCFVt) was calculated as the fruit growth rate. The R-RCFVt temporarily increased or decreased in response to the rapid change in vapor pressure deficit (VPD) when the air temperature switched to a lower or higher setpoint. The R-RCFVt remained almost constant when the air temperature and VPD were kept constant. Regression analyses indicated that R-RCFVt was positively correlated with the air temperature in both dark and light periods.
Erythritol slurry is a promising heat transport medium in the mid/low-temperature range. The pressure drop of an erythritol slurry flowing in a horizontal circular tube was measured, and a fluid model for estimating the pressure drop was studied. The Bingham model was found to be effective as a simple model that does not consider the flow pattern. A composite model, which can be applied to various slurries by considering the flow pattern, is also discussed. In the composite model, we focused on the distribution in the solid fraction in the pipe, which occurs at low flow velocities, and quantitatively determined the flow pattern of the erythritol slurry, by applying a line approximation to the relationship between shear stress and shear rate. Furthermore, it was shown that the power law model is suitable for homogeneous flows, while the separation model is suitable for heterogeneous flows.
Long short term memory network was applied to predict the dynamic refrigerant behaviors in an air conditioning system. The transitions of refrigerant distributions in four elements were predicted under different compressor starting speeds and charging amounts of the refrigerant. The network can predict the behavior of refrigerant distribution precisely within 4% error when a sufficient number of training data is used. Although the lack in training data leads to prediction error of 8.5%, introduction of conventional design knowledge of the refrigerant system to the network enables to improve the prediction accuracy up to 5.4% error.
Reducing refrigerant leakage from refrigeration and air-conditioning equipment is one of the essential issues to solve the global warming problem. Many countries are enacting laws requiring owners of large refrigeration and air-conditioning equipment to carry out regular inspections for refrigerant leaks and to repair any leaks that are detected. There are two inspection methods: direct inspections using visual checks or a gas sensor leak detector, and indirect inspections using equipment operating data to detect leakages. However, large equipment has many inspection points, and manual inspection using the direct method is very time-consuming and labor-intensive, placing a heavy burden on both the equipment owner and inspector. Furthermore, when the leakage rate is small, it is difficult to detect leakage by direct method due to the limitation of sensor sensitivity, etc. On the other hand, many countries offer incentives such as exemption from inspections or halving the number of inspections by installing a leak detection system with continuous monitoring. The authors are developing a highly accurate and continuous refrigerant leakage detection system using indirect method based on machine learning techniques. In this paper, the developed leak detection method is applied to VRFs and chillers, and the evaluation shows that the detection performance can be significantly improved compared to the conventional method.
Evaluating thermal performance in impingement food-freezer is important to optimize the thermal design. In this study, Computational Fluid Dynamics (CFD) was applied for an impingement jet freezer to estimate the thermofluid behavior between air and food freezing model. First, the heat transfer coefficient on the surface of food freezing model was calculated by two dimensional CFD simulations with SST k-ω turbulence model. Then, the heat conduction equation including phase change of Tylose gel was calculated. As a result, predicted freezing time from CFD showed a good agreement with the experimental freezing time of the food freezing model. It is concluded that the CFD model can be a useful to understand the complicated behavior of thermo-fluid inside the freezer with high accuracy and low calculating cost of CFD simulation.
This research presents an assessment technique based on the evolutionary optimization of heat exchanger circuitries for the performance evaluation of next-generation refrigerants. To this aim, a finned-tube heat exchanger simulator is structured around a bijective mathematical representation of the refrigerant circuitry (Tube-Tube Adjacency Matrix) and the formulation of the related constraints for ensuring coherence and feasibility of the circuitry during the evolutionary search. The “thermal path generator”, a novel evolutionary algorithm for refrigerant circuitry optimization, is developed. This novel technique was able to handle the implementation of genetic operators to complex circuitries with unrestrained number and location of splitting and merging nodes, hence, expanding the search space of previous optimization studies. The performance of three refrigerants representative of air conditioning applications, namely R32, R410A, and R454C is assessed for optimized circuitries of a 36- tube evaporator. Larger COP improvements (up to 7.26%) are achieved for zeotropic refrigerant mixtures, such as R454C, where the proper matching of the temperature glide with the temperature variation of the air yields the possibility of further reducing the required compression ratio at corresponding operative conditions. It is thus demonstrated that low-GWP zeotropic mixtures with temperature glide may achieve higher performance than R410A and comparable to R32, while previous drop-in performance analyses yielded the opposite conclusion.
In this study, a replica method using a combination of two types of resins is developed, which is expected to be applicable to various environmental conditions. It is confirmed that the present method can preserve the frost shape during the replica fabrication process. The three dimensional structures of the replica were observed by X ray μ-CT, and the images were processed by machine learning. It is confirmed that the local three-dimensional structures of the frost can be effectively reconstructed by the replica method.