• 한국산학기술학회논문지
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• 제18권6호
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• pp.742-752
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• 2017

본 논문은 중공슬래브 교량의 장점을 극대화하여 프라캐스트로 제작된 PSC-I거더의 단순한 조립을 통해 중공슬래브를 형성시키는 교량공법을 제안하고 이를 검증하였다. 하천이나 단지 내 교량과 같이 저형고 거더교가 요구되는 현장에 고가인 강합성 계열의 교량이 적용되어 과도한 공사비가 소요되고 있으며, 다양한 장점을 갖는 중공슬래브 교량이 콘크라트의 현장타설로 인해 중공부에 구조적 균열이 발생하여 그 적용성이 확장되지 못하고 있는 실정이다. 따라서, 본 연구를 통해 새로운 거더공법을 대안으로 제시하고 설계기준에 따른 강도와 응력검토, 제작을 위한 거푸집의 설계, 시공단계별 절차 등 현업적용을 위한 기반기술을 개발하였으며, 조립된 거더가 일체로 거동하도록 각 거더의 횡방향 연결을 위한 다양한 공법을 제시하고 적정성을 검토하였다. 또한, 실물크기의 실험체 거더 2본을 제작하고 시공과정에서의 문제점들을 도출하였으며, 하중재하 실험을 수행하여 거더의 성능과 적용성을 검토하였다. 실험결과, 하중의 편측 재하시 발생한 수직변위 계측을 통해 두 거더가 일체로 거동하는 것을 확인하였으며, 설계하중 내에서 선형탄성 휨 거동을 보이며 예상된 설계 강도를 넘어서는 우수한 성능을 나타내었다.

• 한국주거학회논문집
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• 제17권3호
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• pp.41-49
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• 2006

Precast concrete apartments were main stream of domestic industrialized housing around 90's, and Steel Houses applying Steel Stud technique with light weighted steel have been dominant portion since 1995. On the other hand, various building techniques including Steel Stud method and highly prefabricated and industrialized Unit method are prevailing in developed countries like Japan. Steel stud and unit box have their own merits and demerits, but the more crucial aspect is that the constant design standard should be applied in each design procedure. It entails the necessity of industrial housing development on the open system basis. In this study, the design standard for unit house will be established coping with the established preparing standard for design specifications defined by architectural law and promotion law of housing construction. That is for design standard of industrialized private housing on the open system basis. This study attempts to propose the design automation, with the method of unit construction of which the rate of pre-fabrication is the biggest, that can cope with the demand of user on the basis of open-system. Ticky-tacky is the biggest technical problem in suppling industrialization housing. Therefore, we will suggest a basic plan for design automation of unit modular housing which can raise the productivity of industrialization housing by applying open system, utilized by DB of component and unit, and solve the problem concerned about ticky-tacky.

• Steel and Composite Structures
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• 제45권1호
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• pp.101-118
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• 2022

The seismic performance of the reinforced concrete (RC) special-shaped column to steel beam connections with steel jacket used in the RC column to steel beam fabricated frame structures was investigated in this study. The three full-scale specimens were subjected to cyclic loading. The failure mode, ultimate bearing capacity, shear strength capacity, stiffness degradation, energy dissipation capacity, and strain distribution of the specimens were studied by varying the steel jacket thickness parameters. Test results indicate that the RC special-shaped column to steel beam connection with steel jacket is reliable and has excellent seismic performance. The hysteresis curve is full and has excellent energy dissipation capacity. The thickness of the steel jacket is an important parameter affecting the seismic performance of the proposed connections, and the shear strength capacity, ductility, and initial stiffness of the specimens improve with the increase in the thickness of the steel jacket. The calculation formula for the shear strength capacity of RC special-shaped column to steel beam connections with steel jacket is proposed on the basis of the experimental results and numerical simulation analysis. The theoretical values of the formula are in good agreement with the experimental values.

• 국제학술발표논문집
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• The 9th International Conference on Construction Engineering and Project Management
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• pp.1243-1244
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• 2022

In recent years, the growing interest in off-site construction has led to factories scaling up their manufacturing and production processes in the construction sector. Consequently, continuous large-scale site monitoring in low-variability environments, such as prefabricated components production plants (precast concrete production), has gained increasing importance. Although many studies on computer vision-based site monitoring have been conducted, challenges for deploying this technology for large-scale field applications still remain. One of the issues is collecting and transmitting vast amounts of video data. Continuous site monitoring systems are based on real-time video data collection and analysis, which requires excessive computational resources and network traffic. In addition, it is difficult to integrate various object information with different sizes and scales into a single scene. Various sizes and types of objects (e.g., workers, heavy equipment, and materials) exist in a plant production environment, and these objects should be detected simultaneously for effective site monitoring. However, with the existing object detection algorithms, it is difficult to simultaneously detect objects with significant differences in size because collecting and training massive amounts of object image data with various scales is necessary. This study thus developed a large-scale site monitoring system using edge computing and a small-object detection system to solve these problems. Edge computing is a distributed information technology architecture wherein the image or video data is processed near the originating source, not on a centralized server or cloud. By inferring information from the AI computing module equipped with CCTVs and communicating only the processed information with the server, it is possible to reduce excessive network traffic. Small-object detection is an innovative method to detect different-sized objects by cropping the raw image and setting the appropriate number of rows and columns for image splitting based on the target object size. This enables the detection of small objects from cropped and magnified images. The detected small objects can then be expressed in the original image. In the inference process, this study used the YOLO-v5 algorithm, known for its fast processing speed and widely used for real-time object detection. This method could effectively detect large and even small objects that were difficult to detect with the existing object detection algorithms. When the large-scale site monitoring system was tested, it performed well in detecting small objects, such as workers in a large-scale view of construction sites, which were inaccurately detected by the existing algorithms. Our next goal is to incorporate various safety monitoring and risk analysis algorithms into this system, such as collision risk estimation, based on the time-to-collision concept, enabling the optimization of safety routes by accumulating workers' paths and inferring the risky areas based on workers' trajectory patterns. Through such developments, this continuous large-scale site monitoring system can guide a construction plant's safety management system more effectively.