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설치환경 및 조건에 따른 양면수광형 태양광발전시스템의 기초 특성 연구
장주희(Jang Ju-Hee),권오현(Kwon Oh-Hyun),이상혁(Lee Sang-Hyuk),신민수(Shin Min-Su),이경수(Lee Kyung-Soo) 한국태양에너지학회 2018 한국태양에너지학회 논문집 Vol.38 No.6
Nowadays the bifacial PV system market and its applications are increasing rapidly. The performance of the bifacial PV system take advantage of its rear surface irradiance. Also, the ground albedo, PV module tilt and azimuth, PV module installation height, shading effect and module temperature are factors of bifacial PV system performance. This paper investigates how the performance of bifacial PV system is influenced by above factors. First, we analyzed the energy yield depending on PV module installation by simulation. Secondly, we compare energy performance evaluation of monofacial and bifacial module on different weather condition by experiment. Thirdly, we tested the albedo effect and checked operating characteristics using Dupont Tyvek material for the bifacial PV module. Fourthly, we check the shading effect of bifacial PV module on bypass diode operating. Finally, we applied the bifacial PV module in the nearby subway station for the noise reduction barrier using a qualified simulation program. In summary, we confirm that the energy performance superiority of the bifacial PV module has a lot of application use including road. Also, we have confirmed the bifacial module and inverter design should be considered by rear surface irradiance.
좌주간부 관상동맥 에 관한 혈류역학적 분석 (LCCA) (II)
문수연(Su-Yeon Moon),장주희(Ju-Hee Jang),박정수(Jung-Su Park),신세현(Seh-Yun Shin) 대한기계학회 2003 대한기계학회 춘추학술대회 Vol.2003 No.4
The distributions of blood pressure, blood flow, and blow volume in the left common artery (LCCA)<br/> were determined using the lumping parameter method. In order to develop a mathematical model for<br/> microcirculation in LCCA, the present study adopted preexisted set of measured morphological data on anatomy,<br/> mechanical properties of the coronary vessels, viscosity of blood, the basic laws of physics, and the appropriate<br/> boundary condition. Pressures and volumes of blood and flow resistance were expressed in terms of<br/> electrical voltages, current, and resistances, respectively, in the electrical analog model. The results of two<br/> mathematical models, symmetrical and asymmetrical models, were compared with other investigator's data.<br/> The present results were in good agreement with previous studies. It was found that the mean pressure<br/> profiles were similar in both models.
인공지능 기반 EL 이미지의 태양전지 및 모듈의 결함검출 연구
조선근(Jo Sun-Keun),박인두(Park In-Doo),장주희(Jang Ju-Hee),오원욱(Oh Wonwook) 한국태양에너지학회 2021 한국태양에너지학회 논문집 Vol.41 No.6
Currently, investment is being made in renewable energy for the transition to a low-carbon economy and society, and interest in solar energy is also increasing. In addition to the technological development of solar cells and photovoltaic (PV) modules, research in the field of convergence with artificial intelligence technology is being actively conducted. Defects occurring in the manufacturing process of solar cells and modules can be detected through electroluminescence (EL) measurements. In this study, we propose an artificial intelligence technology that can automatically detect defects in cells and modules in real time using EL image data of solar cells and modules in the manufacturing process. For EL defect detection, we propose an algorithm with high suitability in terms of speed and accuracy by applying deep learning-based object detection models and comparing and evaluating detection performance. In the case of the YOLO (you only look once) algorithm, which belongs to a one-step detector, it learns In the case of the YOLO (you only look once) algorithm, which belongs to a one-step detector, it learns through an optimization process to find information about the defect and the location information of the corresponding failure in the form of a bounding box, and then detects the failure based on this information. The introduction of a deep learning-based defect detection model in the manufacturing process is expected to reduce the time required for defect detection by solar cell and PV module manufacturers and contribute to productivity improvement.
섬모상 담체에 부착/ 생장하는 질산화 미생물의 Fluorescence in situ Hybridization에 의한 동정
황선진,장주희,장현섭 대한상하수도학회 2003 상하수도학회지 Vol.17 No.6
FISH (Fluorescence in situ Hybridization) technique was applied to the several nitrifiers in the bulk solution and on the Cilium media to promote nitrification process. It was confirmed by the results of Nso190 and NEU image analysis that ammonia oxidizer forms 'cluster' when they appears in both bulk and media. Another significant fact was that lots of microbial flocs were observed on the surface of the Cilium media substratum instead of biofilm. And from the results of NEU, it was known that Nitrosomonas europaea, Nitrosomonas eutopha and Nitrococcus mobilis or one or two of these three were the dominant ammonia oxidizers. The fact that no Nitrobacter sp. was detected with NIT3 probe means naturally that nitrite oxidizer in the nitrification reactor was not composed of Nitrobacter sp. but with other nitrite oxidizers like Nitrospira sp. etc. In order to detect these nitrite oxidizers, suitable probes must be tested.