Fan filter is the main component of modern clean room air conditioner. Its parts include DC brushless motor, motor driver, centrifugal fan, box flow channel, and high-efficiency filter. This paper identifies the practical mathematical model of this component, which is used to upgrade the design of the whole machine and the parameter setting of the motor driver. The identification method adopts the parameterization of the mathematical model, and then identifies the parameter value through the measurement data. The measurement data such as runner wind speed, fan blade pressure difference, motor current, etc. are intercepted and stored, and then digital signal processing is performed, and then through reverse operation, the undetermined parameters in the parameterized model are identified. The identified electromechanical model is also used to discuss the energy-saving upgrade of the fan filter unit. Using the electromechanical efficiency as an indicator, the energy-saving matching of the driver, motor, and fan is reviewed.
Keywords: fan filter unit, parameterization, parameter identification, electromechanical efficiency
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In the vapor compression heat pump system, the power consumption of the compressor determines the overall power consumption. If a good compressor control technology can be developed, huge energy costs can be saved. This paper is based on the experimental method research, and develops a heat pump system of variable screw compressor Vi, which uses the modulation Vi to control the compression ratio of the matching system operating conditions, the compressor variable frequency control and the expansion valve opening degree control to optimize the system operation. , the experimental benchmark conditions are established by using the field design maximum hot water outlet temperature of 55 ℃, the properties of R134a refrigerant, and the different compression ratios of each working condition with the compressor modulation Vi and other conditions.
The linear trend results of the experimental study show that when the system compression ratio is less than 3.5, the average adiabatic compression efficiency of Vi2.4 is better than Vi3.0 by about 5.08% and Vi3.5 by about 10.56%; it is better than Vi3.0 by about 2.98% And Vi3.5 about 10.77%; and when the system compression ratio is 4.5, the adiabatic compression efficiency of Vi3.5 is better than Vi2.4 about 7.09% and Vi3.0 about 0.10%, better than Vi2.4 about 11.38% and Vi3.0 is about 9.40%. At 55°C hot water outlet temperature, the power consumption of Vi3.5 compressor is about 2.76% less than that of Vi3.0, and about 7.57% less than that of Vi2.4.
In recent years, with the vigorous development of science and technology, people gradually began to rely on computers and various electronic devices to process a large amount of information, and data centers process a large amount of data behind this information every day, accompanied by a large amount of power consumption and environmental impact. of destruction. In order to explore the energy-saving plan of the data center, this study uses the computational fluid dynamics software ANSYS Fluent to simulate the flow field in the data center, and uses the Taguchi method for analysis. Each factor has three levels of change, so an orthogonal table is selected, and nine groups of cases are simulated according to the orthogonal table.
In order to increase the return water temperature of the cooling system, three quality characteristics, the average temperature of the hot air duct, the temperature difference between the highest and the lowest temperature in the hot air duct, and the average temperature difference between the hot and cold air ducts, are selected as the optimization targets, and the grey relational theory is used to find out the quality characteristics under various quality characteristics. , and finally simulate and verify the optimization results. The results show that the factor levels of the optimized case are that the server position is concentrated at the bottom, the air is supplied from the bottom, the air supply flow rate is 800CMH, and the air supply temperature is 288.15K. The temperature difference between the highest and lowest temperature = 2.52K and the average temperature difference between the hot and cold air ducts = 11.06K.
Keywords: data center, computational fluid dynamics, Taguchi method, grey relational analysis
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The team built a small heated suction dryer to test the state of the air flow in and out of the system when compressed air is dehumidified with any adsorption desiccant, and developed an algorithm to calculate the same desiccant used in suction dryers of any capacity. The energy consumption value of the system. In this paper, the energy consumption value of two desiccants is evaluated by this method: activated alumina and a metal organic framework (MOF) material developed by our team. According to the analysis results, 7 kg/cm2. The energy consumption of using the metal-organic framework of our team is about 92% of the alumina used when the compressed air is dried to the pressure dew point ≦ -20°C after preliminary dehumidification by the cold dryer. The reason for this should be that the regeneration temperature required for the metal organic framework is lower than that of alumina.
Keywords: suction dryer, metal organic framework, activated alumina, energy saving
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Activated carbon is the most known material for adsorbing ozone. However, initiating carbonization by ozone is often used to produce activated carbon, which requires advanced technology. capabilities and professional equipment. Granular activated carbon and activated carbon fiber cloth are oxidized through nitric acid treatment or bleaching treatment (NaOCl), and the original and oxidized materials are exposed in ozone stream until saturated. When comparing original activated carbon, nitric acid modified activated carbon, and ACFC, ACFC has the highest adsorption capacity, while original activated carbon has the highest adsorption capacity. Oxidation of carbon can lead to higher degradation capacity. The ozone removal performance of carbon nanotube/quartz fiber film is 1.6 times better than that of traditional activated carbon. Under certain conditions, peak ozone concentrations were reduced by 38% to 56% when the test chamber had activated carbon. Under the same conditions, when coffee powder (new When fresh or residue), the peak ozone concentration will be reduced by 25% to 43%.
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After decades of rapid development, computer computational fluid dynamics (CFD) has reached an astonishing degree of maturity. Regardless of convenience, accuracy, and speed, it has matured to the point where it can effectively assist various engineering designs. In the aviation, vehicle, shipbuilding industries, and even the electronics industry where CFD was first applied, it has long been standard daily work. Relatively speaking, in the construction and air-conditioning industries, the overall understanding and utilization of CFD still lags behind other industries; many people still believe that CFD is exclusive to academic research and is not closely related to actual practice; or think that it requires extreme specialization Only qualified people can use CFD; or they think CFD is not accurate and reliable enough, etc. These are all different from the current situation of CFD.
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In this study, the non-conductive fluids FC-72 and HFE-7100 were used to investigate the condensation heat transfer performance outside the tubes, and to simulate the condensation conditions of the immersion computer cooling system. There are four types of tubes: round tube, smooth elliptical tube, reinforced round tube and reinforced elliptical tube, and the condensation phenomenon is observed by visual cavity. The cooling water flow in the tube is 1.5 and 2LPM. The experimental results show that FC-72 and HFE-7100 have the highest condensation heat transfer coefficient in the elliptical reinforced tube. Overall, the condensation heat transfer of FC-72 is better than that of HFE-7100, and the highest condensation heat of FC-72 and HFE-7100. The transmission coefficient can reach 3400 and 2491W/m respectively2K. Compared with the surface type, the condensation heat transfer coefficient of the reinforced tube is higher than that of the smooth tube; compared with the cross-sectional shape of the tube, the condensation heat transfer coefficient of the elliptical tube is higher than that of the circular tube; because of the large curvature of the wall surface, the condensation film on the tube wall Affected by gravity, it is easier to detach from the surface of the condensing pipe, so that the condensing pipe is not easy to thicken due to the increase of condensation amount, and can maintain better heat transfer performance.
The ice water system is composed of main equipment such as ice water host, cooling water tower and water pump. It is a huge and complex system. Each equipment interacts with each other through the circulation pipeline; and the same equipment also has different operating characteristics. Traditionally, thermodynamic formulas are often used, combined with traditional optimization search methods, to estimate parameters and find the best energy-saving operating point. However, the system operation mode established by this method is quite different from the actual complex ice-water system, and it is bound to be difficult to find the real optimal energy-saving point of the ice-water system. This study makes full use of the operation big data of the ice water system, introduces deep learning technology, and establishes the operation model of each subsystem of the ice water main engine, cooling water tower, and cooling water pump. Through the relationship between the input and output of each model, the optimal ice water host load rate, condenser inlet and outlet water temperature difference and cooling water tower cooling water outlet temperature are found, so that the overall ice water system can work at the lowest energy consumption point. And then achieve the purpose of energy saving. This article uses the actual operation data of the ice water system provided by Taiwan's AU Optronics panel factory as an example. The calculation results show that in terms of energy efficiency, compared with the total power consumption of the panel factory in 2019, the optimization of cooling water circulation parameters saved 0.89%. The ice water host load allocation optimization saves 0.33% of power consumption. In addition, the optimization of the total ice water temperature of the ice water host can help the panel factory's ice water system save 1.2% of power consumption in weather conditions where the dry bulb temperature is 25.8 and the wet bulb temperature is 19.4. This energy saving benefit will vary depending on the weather and the heat load of the factory area.
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This article explains the calculation and analysis method of dry and wet tube fin heat exchangers; and uses the tube row size and operating conditions actually used by a panel factory to calculate and compare the performance of oval tube rows and circular tube rows under the same windward surface area. , designed to replace the original circular tube row with an elliptical tube row. According to the calculation model analysis results of this study, under the same water flow rate in the pipe and air volume outside the pipe, replacing the round pipe with an oval pipe with the same circumference can reduce the air side pressure loss by about 31%, but the ice water side pressure loss in the pipe It will be doubled, and the heat transfer rate is increased by about 5% compared to the circular tube; if the original circular tube with an outer diameter of 12.7mm is replaced by an oval tube with a slightly larger circumference (long axis 20.15mm, short axis 8.5mm) shaped tube, the fin spacing is changed from 2.5mm to 2.92mm, the air side pressure loss can be reduced by approximately 35%, the ice water side pressure loss in the tube can be reduced by approximately 4%, and the heat transfer capacity can be increased by approximately 6%. The original operating conditions of the air conditioning system can be maintained and the heat exchanger can be directly replaced to achieve energy saving effects of reducing air side pressure loss and windmill energy consumption.
Keywords: fin heat exchanger, air conditioning system, energy saving
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