• Journal of Korea Multimedia Society
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• v.14 no.9
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• pp.1138-1151
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• 2011

Sensor network clustering scheme is an efficient method that prolongs network lifetime. However, when it is applied to an environment in which collected data of the sensor nodes easily overlap, sensor node unnecessarily consumes energy. Accordingly, we proposed a data prediction scheme that sensor node can predict current data to exclude redundant data transmission and to minimize data transmission among the cluster head node and member nodes. Our scheme excludes redundant data collection by neighbor nodes. Thus it is possible that energy efficient data transmission. Moreover, to alleviate unnecessary data transmission, we introduce data prediction graph whether transmit or not through analyze between prediction and current data. According to the result of performance analysis, our method consume less energy than the existing clustering method. Nevertheless, transmission efficiency and data accuracy is increased. Consequently, network lifetime is prolonged.

• Transactions of the Korean Society of Mechanical Engineers A
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• v.35 no.7
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• pp.753-758
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• 2011

The Ni-base super-heat-resistant alloy, GTD-111, is employed in gas turbines because of its high temperature strength and oxidation resistance. It is important to predict the fatigue life of this superalloy in order to improve the efficiency of gas turbines. In this study, low-cycle fatigue tests are performed as variables of total strain range and temperature. The relationship between the strain energy density and number of cycles to failure is examined in order to predict the low-cycle fatigue life of the GTD-111 superalloy. The fatigue life predicted by using the strain-energy methods is found to coincide with that obtained from the experimental data and from the Coffin-Manson method.

• Explosives and Blasting
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• v.26 no.1
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• pp.15-21
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• 2008

In case of estimating the shocking vibration during the blasting demolitions, the weight and falling height of the structure, that is a potential energy, had been considered. But, this study presented a new equation which used the impulse concerning a falling weight instead of potential energy as a method of predicting the shock vibration. In this experiment, the data of the impulse were compared with the data of the potential energy by performing the free-fall, and all data were comparatively analyzed by the regression analysis method. Also, the method of the superposition theory, which is calculated by the diminution ratio according to distance, the free-fall difference according to height, and the time giving the shock to the ground according to the breakdown pattern, was compared with the previous vibration data occurring from the blasting demolitions in the same conditions. As a result, this study suggests that the impulse and the method of superposition theory be applied as a method of predicting the shocking vibration. Therefore, these results could be expected to estimate the shocking vibration more accurately than the previous method.

• Journal of the Korean Society for Railway
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• v.20 no.2
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• pp.182-189
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• 2017

Photovoltaic power generation systems make up a large part of the low carbon energy trend. The purpose of this study is to utilize PVsyst, a commercial forecasting program, to forecast research on the design stages of photovoltaic power generation for wider applications of this system in railroads and to consider prospective issues for photovoltaic power plants that are currently being operated. Given this, we will compare the forecast value of generated photovoltaic power, derived from foreign weather forecast information provided by NASA, along with information from Meteonorm, and the forecast values derived from the KMA weather information. By comparing these values with amounts actually generated by KPX, this research aims to secure propriety rights for wider application of photovoltaic power generation systems in railroads, and to contribute to low carbon energy for the new climate of the future.

• Journal of the Korean Solar Energy Society
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• v.32 no.6
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• pp.37-43
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• 2012

Long-term variations in wind speed and capacity factor(CF) on Seongsan wind farm of Jeju Island, South Korea were derived statistically. The selected areas for this study were Subji, having a year wind data at 30m above ground level, Sinsan, having 30-year wind data at 10m above ground level and Seongsan wind farm, where long-term CF was predicted. The Measure-Correlate-Predict module of WindPRO was used to predict long-tem wind characteristics at Seongsan wind farm. Eachyear's CF was derived from the estimated 30-year time series wind data by running WAsP module. As a result, for the 30-year CFs, Seongsan wind farm was estimated to have 8.3% for the coefficien to fvariation, CV, and-16.5% ~ 13.2% for the range of variation, RV. It was predicted that the annual CF at Seongsan wind farm varied within about ${\pm}4%$.

• 한국신재생에너지학회:학술대회논문집
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• 2010.06a
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• pp.182.1-182.1
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• 2010

현재 전 세계적으로 가장 널리 개발하고 보급되어지고 있는 풍력산업의 시장 규모는 매년 확대되고 있다. 특히 소형 풍력발전 시스템은 낙도 등의 전력 공급이 어려운 지역에 경제성 있는 전력 보급을 가능하게 한다. 국내의 미전화 지역과 일반 가정에서 풍력 에너지 자원을 적극 활용 개발하기 위해서 보다 우수한 성능의 풍력발전기용 블레이드를 설계하고자, 공기역학적인 최적설계에 대해 연구함으로써 추후 보급형 풍력발전 시스템의 개발에 필요한 설계 기술을 확립하고자한다. 본 연구는 설계된 블레이드의 유동해석 및 성능예측을 위하여 경제적으로 많은 지원이 필요한 대규모 풍동실험이 아닌 상용 CFD를 사용하여 보다 효율적으로 우수한 성능을 가지는 풍력 터빈을 설계함에 있다. Reynolds Averaged Navier-Stokes 방정식에 기반을 둔 CFD의 경우 이론적으로 명확한 해석이 가능하고, 실제 터빈의 운전 환경과 동일한 다양한 물리적 변수를 입력 데이터로서 활용할 수 있는 장점이 있기 때문에 풍력 터빈의 설계 과정에서 반영된 미소한 블레이드 형상변화 및 운전 조건의 변화에 따른 유동장의 변화 및 풍력터빈 성능을 정확히 예측할 수 있는 장점을 가지고 있다.

• Journal of Advanced Navigation Technology
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• v.2 no.2
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• pp.107-115
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• 1998

In this paper, we propose a robust moving object tracking(MOT) method based on motion energy and prediction. MOT consists of two steps: moving object extraction step(MOES) and moving object tracking step(MOTS). For MOES, we use improved motion energy method. For MOTS, we predict the next location of moving object based on distance and direction information among previous instances, so that we can reduce the search space for correspondence. We apply the method to both synthetic and real world sequences and find that the method works well even in the presence of occlusion and disocclusion.

• Journal of Advanced Marine Engineering and Technology
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• v.36 no.1
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• pp.51-56
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• 2012

This paper reports the generation efficiency and the thermal performance of a thermoelectric generator (TEG) harvesting energy from the waste heat of high power electronic components. A thermoelectric (TE) model containing thermal boundary resistances is used to predict generation efficiency and junction temperature of a high power electronic component. The predicted results are verified with measured values, and the discrepancy between prediction and measurement is seen to be moderate. The verified TE model predicts generation efficiencies, junction temperatures of the component, and temperature differences across a TEG at various source heat flows associated with various electrical load resistances. This study explores effects of the load resistance on the generation efficiency, the temperature difference across a TEG, and the junction temperature.

• Journal of the Korean Solar Energy Society
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• v.31 no.5
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• pp.9-18
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• 2011

태양광열 복합 시스템(photovoltaic/thermal hybrid solar system, PV/T)은 태양광 모듈 및 태양열 집열판의 단일화를 통한 전기 및 열에너지의 동시 생산이 가능하도록 구성되고 기존 태양광 모듈의 온도 상승에 따른 효율 저하의 문제점을 보완 및 발생하는 열을 회수하여 온수 생산이 가능한 장치이다. 본 연구에서는 액체형 PV/T 시스템의 대표적인 두 형태인 박스형과 튜브형의 성능 검증을 위하여 수학적 모델링을 통한 두 시스템의 열 및 전기적 성능을 비교 분석하였다. 모델링은 에너지 평형식을 이용하여 시간에 따른 각 부분의 온도의 변화를 예측할 수 있도록 수립되었으며 계산된 결과를 기준으로 전기, 열, 및 전체효율을 도출해 내고, 이를 바탕으로 두 시스템의 성능을 분석하였다. 시뮬레이션 결과를 바탕으로, 박스형 PV/T 시스템의 최고 온수 온도는 $52^{\circ}C$로 예측되었고, 반면에 튜브형은 $48^{\circ}C$에 머물렀다. 또한 열효율은 박스형이 최대 51%, 튜브형이 41%, 전기효율은 박스형이 약 14%, 그리고 튜브형이 13%로 나타났으며, 전체효율은 박스형이 73%, 그리고 튜브형이 64%로 나타나 박스형 PV/T 시스템이 튜브형보다 더 나은 성능을 가지는 것으로 예측되었다. 이는 박스형이 튜브형보다 태양광 모듈과 온수와의 접촉면적이 넓어 더 많은 열전달이 발생하기 때문으로 사료된다.

• Korean Journal of Air-Conditioning and Refrigeration Engineering
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• v.25 no.6
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• pp.310-316
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• 2013

This study was designed to investigate a method for short-term, real-time energy demand prediction, to cope with changing loads for the effective operation and management of buildings. Through a case study, a novel methodology for real-time energy demand prediction with the use of weather forecasting data was suggested. To perform the input and output operations of weather data, and to calculate solar radiation and EnergyPlus, the BCVTB (Building Control Virtual Test Bed) was designed. Through the BCVTB, energy demand prediction for the next 24 hours was carried out, based on 4 real-time weather data and 2 solar radiation calculations. The weather parameters used in a model equation to calculate solar radiation were sourced from the weather data of the KMA (Korea Meteorological Administration). Depending on the local weather forecast data, the results showed their corresponding predicted values. Thus, this methodology was successfully applicable to anywhere that local weather forecast data is available.