• International Journal of Air-Conditioning and Refrigeration
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• v.10 no.4
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• pp.220-228
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• 2002

The cool-down performance after soaking is very important in an automotive air-conditioning system and is considered as a key design variable. Therefore, transient characteristics of each system component are essential to the preliminary design as well as steady-state performance. The objective of this study is to develop a computer simulation model and ostinato theoretically the transient performance of an automotive air-conditioning system. To do that, the mathematical modelling of each component, such as compressor, condenser, receiver/drier, expansion valve, and evaporator, is presented first of all. The basic balance equations about mass and energy are used in modelling. For detailed calculation, condenser and evaporator are divided into many sub-sections. Each sub-section is an elemental volume for modelling. In models of expansion valve and compressor, dynamic behaviors are not considered in this analysis, but the quasisteady state ones are just considered, such as the relation between mass flow rate and pressure drop in expansion device, polytropic process in compressor, etc. Also it is assumed that there are no heat loss and no pressure drop in discharge, liquid, and suction lines. The developed simulation model is validated by comparing with the laboratory test data of an automotive air-conditioning system. The overall time-tracing properties of each component agreed well with those of test data in this case.

• Journal of the Korea Society of Computer and Information
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• v.29 no.8
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• pp.165-170
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• 2024

This study aims to verify the accuracy of the air quality management system in Yangju City using an artificial intelligence (AI) evaluation model. The consistency and reliability of fine dust data were assessed by comparing public data from the Ministry of Environment with data from Yangju City's air quality management system. To this end, we analyzed the completeness, uniqueness, validity, consistency, accuracy, and integrity of the data. Exploratory statistical analysis was employed to compare data consistency. The results of the AI-based data quality index evaluation revealed no statistically significant differences between the two datasets. Among AI-based algorithms, the random forest model demonstrated the highest predictive accuracy, with its performance evaluated through ROC curves and AUC. Notably, the random forest model was identified as a valuable tool for optimizing the air quality management system. This study confirms that the reliability and suitability of fine dust data can be effectively assessed using AI-based model performance evaluation, contributing to the advancement of air quality management strategies.

• Journal of the Korea Institute of Military Science and Technology
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• v.12 no.2
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• pp.175-181
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• 2009

All of the military aircrafts in Korea Air Force are administered and operated together in the same system regardless of whether they are equipped with the data communication capability or not. The absence of the data communication capability in some of the aircrafts might increase whole kill chain hour at the point of the Network Centric Warfare achievement. Network synergy effects cannot also be desired if the section which is not connected to the network influences to the whole tactical network. Equipping aircrafts with the data communication capability could be done by upgrading the aircrafts, but resulting in high costs and long updating time. This paper is a research about the design and implementation of the UMPC based Data Link System to aircrafts that do not have the data communication capability. The proposed system grafts the UHF-based wireless modem technology and the aircraft flight mission support software onto the off-the-shelf UMPC and GPS system. The employed UHF radio equipment allows communicating tactic data with another aircrafts on the air, the ground control point, and even the Tactical Air Control Party(TACP) control vehicle that achieve missions with aircrafts. It thereby increases such capabilities as navigation aid, situation awareness, quick target identification and attack. We also applied Closed Air Support(CAS) scenarios, which is very close to the real environment, to the experiments of the proposed system. The experimental results show that the proposed system could support the data communication capability effectively and the flight mission at low costs of money and time.

• 한국전산유체공학회:학술대회논문집
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• 2003.10a
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• pp.88-90
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• 2003

We implement Realtime Air Diffusion Prediction System which is designed for air diffusion simulations with four-dimensional data assimilation. For realtime running, we parallelize the system using MPI (Message Passing Interface) on distributed-memory parallel computers and build a cluster computer which links high-performance PCs with high-speed interconnection networks. We use 162­CPU nodes and a Myrinet network for the cluster

• Korean Journal of Air-Conditioning and Refrigeration Engineering
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• v.8 no.2
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• pp.240-253
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• 1996

The refrigeration cycle of automobile air-conditioners is simulated in an effort to provide a computational tool for optimum thermodynamic design. In the simulation, thermodynamic and heat transfer analysis was performed for the four major components : evaporator, condenser, compressor, and expansion valve. Effectiveness-NTU method was used for modeling both evaporator and condenser. The evaporator was divied into many subgrids and simultaneous cooling and dehumidifying analysis was performed for each grid to predict the performance accurately. Blance equations were used to model the compressor instead of using the compressor map. The performance of each component was checked against the measured data with CFC-12. Then, all the components were combined to yield the total system performance. Predicted cycle points were compared against the measured data with HFC-134a and the deviation was found to be less than 5% for all data. Finally, the system model was used to predict the performance of CFC-12 and HFC-134a for comparison. The results were very reasonable as compared to the trend deduced from the measured data.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.25 no.1
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• pp.8-19
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• 2021

The air pollution problem caused by industrialization in recent years is attracting great attention to both the country and the people. Domestic wide-area air pollution information is provided to the public through public data nationally, but regional air pollution information with different environmental variables is very insufficient. Therefore, in this study, we design and implement an air pollution analysis and prediction system based on regional environmental variables that can more accurately analyze and predict regional air pollution phenomena. In particular, the proposed system accurately analyzes and provides regional atmospheric information based on environmental data measured locally and public big data, and predicts and presents future regional atmospheric information using artificial intelligence algorithms. Furthermore, through the proposed system, it is expected that local air pollution can be prevented by accurately identifying the cause of regional air pollution.

• International journal of advanced smart convergence
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• v.7 no.4
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• pp.10-18
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• 2018

For the information services supporting requests of data items from a great number of mobile clients, wireless data broadcasting is an effective way because it can accommodate any number of clients. In the wireless data broadcasting, various air indexing schemes and data scheduling schemes have been developed in order to enable the clients to access their desired data items efficiently. The broadcasting system needs a method to simulate newly designed air indexing and scheduling schemes of the system, and to evaluate the performance parameters of the schemes. In this paper, we design an expandable and efficient simulation framework for the wireless data broadcasting based on the partition of data ID space. The framework can adopt regular and irregular space partition and evaluate various performance parameters of the broadcasting system. We implement a testbed of the broadcasting system using the framework, that adopts IIP, GDI and EXP as its air indexing schemes. We simulate the system using the testbed and evaluate the performance parameters of the system. Thus, we show the efficiency and expandability of the designed and implemented framework.

• Journal of Advanced Navigation Technology
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• v.22 no.2
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• pp.133-140
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• 2018

In recent years, model-based design techniques have been used as a way to support cost reduction and safety certification in the development of avionics systems. In order to support performance analysis and safety analysis of aircraft and avionics equipment (item) using model based design, we developed a multi-domain simulation environment that inter-works with heterogeneous simulators. We present a multi-domain simulation environment that can verify air data computers and integrated multi-function probes at the aircraft level. The model was developed by Simulink and the flight simulator X-Plane 10 was used to verify the model at the aircraft level. Avionics model functions were tested at the aircraft level and the air data errors of the model and flight simulator were measured within 0.1%.

• Journal of Electrical Engineering and Technology
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• v.6 no.5
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• pp.613-617
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• 2011

In the present paper, a new type of electrical actuator, an electromagnetic force driving actuator (EMFA), applicable to air circuit breaker is developed and analyzed. Transient analysis is performed to obtain the dynamic characteristics of EMFA. The distribution of static magnetic flux is obtained using the finite element method. The coupled problems of electrics and mechanics governing equations are solved using the time-difference method. According to the interception rate of each contactor, investigation of the contactor spring load condition is conducted and applied to the threelink system. Comparisons of the dynamic characteristics of the three-link simulation and experimental data are performed.

• The Journal of Korea Institute of Information, Electronics, and Communication Technology
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• v.14 no.4
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• pp.328-337
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• 2021

Air pollution, which is a class 1 carcinogen, such as asbestos and benzene, is the cause of various diseases. The spread of ultra-air pollution is one of the important causes of the spread of the corona virus. This paper analyzes and predicts fine dust and ultra-air pollution from 2015 to 2019 based on weather data such as average temperature, precipitation, and average wind speed in Seoul and atmospheric environment data such as SO2, NO2, and O3. Linear regression, SVM, and ensemble models among machine learning models were compared and analyzed to predict fine dust by grasping and analyzing the status of air pollution and ultra-air pollution by season and month. In addition, important features(attributes) that affect the generation of fine dust and ultra-air pollution are identified. The highest ultra-air pollution was found in March, and the lowest ultra-air pollution was observed from August to September. In the case of meteorological data, the data that has the most influence on ultra-air pollution is average temperature, and in the case of meteorological data and atmospheric environment data, NO2 has the greatest effect on ultra-air pollution generation.