• Journal of Information Technology Applications and Management
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• v.28 no.6
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• pp.87-95
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• 2021

Recently interest for air pollution is gradually increasing. However, according to the environmental assessment of air quality, the level of air pollution in the nation is quite serious, and air pollutants measuring facilities are also not enough. In this paper, a secure air pollutants sensor system based low power wireless communication is designed and implemented. The proposed system is composed of three parts: air pollutants measuring sensors module, LoRa-based data transmission module, and monitoring module. In the air pollutants measuring module, the MSP430 board with six big air pollutants measuring sensors are used. The air pollutants sensing data is transmitted to the control server in the monitoring system using LoRa transmission module. The received sensing data is stored in the database of the monitoring system, and visualized in real-time on the map of the sensor locations. The implemented air pollutant sensor system can be used for measuring the level of air quality conveniently in our daily lives.

• Journal of the Korea Institute of Military Science and Technology
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• v.23 no.6
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• pp.639-649
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• 2020

Air data systems measure airspeed, pressure altitude, angle of attack and angle of sideslip. These measurements are essential for operating flight control laws to ensure safe flights. Since the loss or corruption of air data measurements is considered as catastrophic, a high level of operational reliability needs to be achieved for air data systems. In the case of unmanned air vehicles, failure of any of air data sensors is more critical due to the absence of onboard pilot decision aid. This paper presents design of a dual redundancy air data system and the integration process for an unmanned air vehicle. The proposed dual-redundant architecture is based on two independent air data probes and redundancy management by central processing in two independent flight control computers. Starting from unit testing of single air data sensor, details are provided of system level tests used to meet overall requirements. Test results from system integration demonstrate the efficiency of the proposed process.

• Proceedings of the SAREK Conference
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• 2008.11a
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• pp.487-492
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• 2008

The cooling of data centers has emerged as a significant challenge as the density of IT server increases. Server installations, along with the shrinking physical size of servers and storage systems, has resulted in high power density and high heat density. The introduction of high density enclosures into a data center creates the potential for "hot spots" within the room that the cooling system may not be able to address, since traditional designs assume relatively uniform cooling patterns within a data center. The cooling system for data center consists of a CRAC or CRAH unit and the associated air distribution system. It is the configuration of the distribution system that primarily distinguishes the different types of data center cooling systems, this is the main subject of this paper.

• 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.

• Korean Journal of Air-Conditioning and Refrigeration Engineering
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• v.14 no.7
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• pp.560-566
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• 2002

The fault detection and diagnosis technology may be applied in order to decrease the energy consumption and the maintenance cost of the air-conditioning system. In this study, two different types of faults in the air-conditioning system, such as the condenser fouling and the evaporator fan slowdown, were considered. The neural network algorithm combined with data preprocessor was developed and applied to detect the faults of the real system. Test results show that this method is very effective to detect the faults in the air-conditioning system. Therefore, this developed method can be used for the development of the air-conditioner fault detection system.

• Proceedings of the SAREK Conference
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• 2005.11a
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• pp.427-432
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• 2005

This study developed a program for detecting charged refrigerant amount in system air-conditioner. System air-conditioner is an air-conditioning system with multiple indoor units. Due to the complexity of the system, it is more difficult to detect the refrigerant amount charged in system air-conditioner than in a general single air-conditioner. Experiments were performed for 6 HP outdoor units with 3 indoor units in a psychrometric calorimeter. The experimental amount of charged refrigerant were ranged from 60% to 140% with 10% increasement. Fuzzy algorithm were emploeed for detecting the charged refrigerant amount in a system air-conditioner. The experimental data were used for curve fitting for general ranges for indoor and outdoor temperature conditions. membership function were determined for whole ranges of experimentally measured data and rulebase were defined for each amount of refrigerant charge. Developed program successfully predicted the measured data within 10% resolution range.

• Proceedings of the SAREK Conference
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• 2007.11a
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• pp.328-333
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• 2007

The purpose of this study is modelling of system air-conditioner for TRNSYS. System air-conditioner is operated by a variable capacity compressor and accommodated by multiple evaporators. By reason of these feature, realizing performance of system air-conditioner for TRNSYS was incomplete. In this study performance data of system air-conditioner and control logics are used to make system air-conditioner module for TRNSYS. Performance data contains total capacity, power input and capacity index of system air-conditioner. The simulation was carried out in a mode of temperature level control using TRNSYS 16. The simulation shows that the system air-conditioner model operate variable capacity and can compute capacity index and power input of system.

• Korean Journal of Air-Conditioning and Refrigeration Engineering
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• v.26 no.4
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• pp.145-150
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• 2014

Many studies are being conducted with the aim of reducing the energy consumption in data centers, which are one of the highest consumers of energy. The use of an air-side economizer system that uses external air during intermediate and winter seasons is being considered for reducing the energy consumption of air conditioners. In this study, using the energy simulation, we evaluated the energy performance of a central chilled water cooling system and air-side economizer system in domestic data centers. Further, the cost-effectiveness of the air-side economizer was analyzed through Life-Cycle Cost Analysis. The results showed that with the use of air-side economizer systems, the energy costs increased as the applied filter grade increased; however, unlike existing central chilled water systems, it would break even within 2 years.

• International journal of advanced smart convergence
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• v.4 no.1
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• pp.45-53
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• 2015

This paper is proposed mathematical load modelling based on system identification approach of energy consumption of residential air conditioning. Due to air conditioning is one of the significant equipment which consumes high energy and cause the peak load of power system especially in the summer time. The demand response is one of the solutions to decrease the load consumption and cutting peak load to avoid the reservation of power supply from power plant. In order to operate this solution, mathematical modelling of air conditioning which explains the behaviour is essential tool. The four type of linear model is selected for explanation the behaviour of this system. In order to obtain model, the experimental setup are performed by collecting input and output data every minute of 9,385 BTU/h air-conditioning split type with $25^{\circ}C$ thermostat setting of one sample house. The input data are composed of solar radiation ($W/m^2$) and ambient temperature ($^{\circ}C$). The output data are power and energy consumption of air conditioning. Both data are divided into two groups follow as training data and validation data for getting the exact model. The model is also verified with the other similar type of air condition by feed solar radiation and ambient temperature input data and compare the output energy consumption data. The best model in term of accuracy and model order is output error model with 70.78% accuracy and $17^{th}$ order. The model order reduction technique is used to reduce order of model to seven order for less complexity, then Kalman filtering technique is applied for remove white Gaussian noise for improve accuracy of model to be 72.66%. The obtained model can be also used for electrical load forecasting and designs the optimal size of renewable energy such photovoltaic system for supply the air conditioning.

• Journal of the Korea Institute of Military Science and Technology
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• v.21 no.3
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• pp.403-412
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• 2018

In this study, a three-dimensional variational(3DVAR) data assimilation system was developed for the operational numerical weather prediction(NWP) system at the Republic of Korea Air Force Weather Group. The Air Force NWP system utilizes the Weather Research and Forecasting(WRF) meso-scale regional model to provide weather information for the military service. Thus, the data assimilation system was developed based on the WRF model. Experiments were conducted to identify the nested model domain to assimilate observations and the period appropriate in estimating the background error covariance(BEC) in 3DVAR. The assimilation of observations in domain 2 is beneficial to improve 24-h forecasts in domain 3. The 24-h forecast performance does not change much depending on the estimation period of the BEC in 3DVAR. The results of this study provide a basis to establish the operational data assimilation system for the Republic of Korea Air Force Weather Group.