• Steel and Composite Structures
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• 제23권4호
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• pp.421-433
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• 2017

Experimental and numerical studies of a newly developed Reduced Beam Section (RBS) connection, called Tubular Web RBS connection (TW-RBS) have been recently conducted. This paper presents experimental and numerical results of extending the plastic hinge length on the beam flange to increase energy dissipation of a proposed version of the TW-RBS connection with two pipes, (TW-RBS(II)), made by replacing a part of flat web with two steel tubular web at the desirable location of the beam plastic hinge. Two deep-beam specimens with two pipes are prepared and tested under cyclic loads. Obtained results reveal that the TW-RBS(II) like its type I, increases story drift capacity up to 6% in deep beam much more than that stipulated by the current seismic codes. Based on test results, the proposed TW-RBS(II) helps to dissipate imposed energy up to 30% more than that of the TW-RBS(I) specimens at the same story drift and also reduces demands at the beam-to-column connection up to 30% by increasing plastic hinge length on the beam flange. The TW-RBS(II) specimens are finally simulated using finite element method showing good agreement with experimental results.

• 한국전산구조공학회논문집
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• 제20권6호
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• pp.699-708
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• 2007

일반적으로 깊은 보의 개구부 보강을 할 경우 개구부 주변의 부족한 내력에 대해 수직, 수평, 대각, 혹은 혼합된 배근 형태를 사용하게 되는데, 경제성과 구조적 안전성을 고려하기 위해서는 각 배근 형태 및 방법에 따른 깊은 보의 거론 평가와 적절한 조합에 관한 연구가 절실히 필요하다. 이에 본 연구에서는 개구부 보강방법을 변수로 한 simulation 모델을 통해 수직, 수평 보강의 효과에 대해 해석적으로 검증을 한 후, 각 규준에서 제시하고 있는 개구부가 있는 깊은 보의 전단 내력식을 분석하고 해당 식을 보완하여 단순지지 1경간 및 연속 경간에 적용 가능한 전단 내력 산정식을 제안하고자 한다.

• 반도체디스플레이기술학회지
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• 제21권4호
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• pp.121-125
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• 2022

This paper deals with the development of a deep-learning-based robot that recognizes various types of stairs and performs a mission to go up to the target floor. The overall motion sequence of the robot is performed based on the ROS robot operating system, and it is possible to detect the shape of the stairs required to implement the motion sequence through rapid object recognition through YOLOv4 and Cuda acceleration calculations. Using the ROS operating system installed in Jetson Nano, a system was built to support communication between Arduino DUE and OpenCM 9.04 with heterogeneous hardware and to control the movement of the robot by aligning the received sensors and data. In addition, the web server for robot control was manufactured as ROS web server, and flow chart and basic ROS communication were designed to enable control through computer and smartphone through message passing.

• Smart Structures and Systems
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• 제30권2호
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• pp.145-157
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• 2022

The design of safe and economical structures depends on the reliable live load from load survey. Live load surveys are traditionally conducted by randomly selecting rooms and weighing each item on-site, a method that has problems of low efficiency, high cost, and long cycle time. This paper proposes a deep learning-based method combined with Internet big data to perform live load surveys. The proposed survey method utilizes multi-source heterogeneous data, such as images, voice, and product identification, to obtain the live load without weighing each item through object detection, web crawler, and speech recognition. The indoor objects and face detection models are first developed based on fine-tuning the YOLOv3 algorithm to detect target objects and obtain the number of people in a room, respectively. Each detection model is evaluated using the independent testing set. Then web crawler frameworks with keyword and image retrieval are established to extract the weight information of detected objects from Internet big data. The live load in a room is derived by combining the weight and number of items and people. To verify the feasibility of the proposed survey method, a live load survey is carried out for a meeting room. The results show that, compared with the traditional method of sampling and weighing, the proposed method could perform efficient and convenient live load surveys and represents a new load research paradigm.

• 한국정보통신학회논문지
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• 제25권8호
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• pp.1005-1012
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• 2021

최근 웹에서 지도(Map)를 이용한 Location based Services 기반의 다양한 위치정보시스템 활용이 점점 확대되고 있으며 에너지 절약을 위한 대안으로 전력 수요 현황을 실시간으로 확인할 수 있는 모니터링 시스템의 필요성이 요구되고 있다. 본 연구에서는 딥러닝과 같은 기계학습을 이용하여 전력 수요 데이터의 특성을 분석하고 예측하는 모듈을 개발하여 지역 단위별 전력 에너지 사용 현황과 예측 추세를 실시간으로 확인할 수 있는 오픈소스 기반 지도 서비스를 이용한 딥러닝 실시간 가상 전력수요예측 웹 시스템을 개발하였다. 특히 제안한 시스템은 LSTM 딥러닝 모델을 이용하여 지역적으로 전력 수요량과 예측 분석이 실시간으로 가능하고 분석된 정보를 가시화하여 제공한다. 향후 제안된 시스템을 통해 지역별 에너지의 수급 및 예측 현황을 확인하고 분석하는데 활용될 수 있을 뿐만 아니라 다른 산업 에너지에도 적용될 수 있을 것이다.

• Structural Engineering and Mechanics
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• 제4권4호
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• pp.437-450
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• 1996

A study on the behaviour of fibre reinforced concrete deep beams with and without web openings is carried out using nonlinear finite element analysis. Eight node isoparametric plane stress elements are employed to model the fibre reinforced concrete materials. Steel bars are treated using a compatible three node truss elements. The constitutive equations for fibre reinforced concrete materials take into account the softening effect of co-existing shear strains. Element stiffness at each step is formulated based on the tangent modulus at the current level of principal strains. Transformation between principal directions and global coordinate system is imposed. Comparison of analytical results with experimental values indicates reasonably good agreement. The proposed numerical model can be used to study the behaviour of this composite structures of practically any geometries.

• Computers and Concrete
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• 제11권5호
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• pp.399-410
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• 2013

A nonlinear finite element analysis of R/C hybrid deep T-beam with web opening subjected to pure torsion is presented. Hexahedral 8-nodes and space truss element were used for modeling concrete and reinforcement. The reinforcement was assumed perfectly bonded to the corresponding nodes of the concrete element. The constitutive relations for concrete and reinforcement are based on the modified field theory and elastic perfectly plastic. The smear crack approach was adopted for modeling the crack. The torque-twist angle relationship curve based on the finite element analysis was compared to the experimental results. The comparison shows that the curve of torque-twist angle predicted by the nonlinear finite element analysis is linear before cracking and close to the experimental result. After cracking, the curve becomes nonlinear and stiffer compared to the experimental result.

• International Journal of Advanced Culture Technology
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• 제9권4호
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• pp.295-301
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• 2021

Digital media technology is gradually developing with the development of convergence quaternary industrial technology and mobile devices. The combination of deep learning and augmented reality can provide more convenient and lively services through the interaction of 3D virtual images with the real world. We combine deep learning-based pose prediction with augmented reality technology. We predict the eight vertices of the bounding box of the object in the image. Using the predicted eight vertices(x,y), eight vertices(x,y,z) of 3D mesh, and the intrinsic parameter of the smartphone camera, we compute the external parameters of the camera through the PnP algorithm. We calculate the distance to the object and the degree of rotation of the object using the external parameter and apply to AR content. Our method provides services in a web environment, making it highly accessible to users and easy to maintain the system. As we provide augmented reality services using consumers' smartphone cameras, we can apply them to various business fields.

• International Journal of Computer Science & Network Security
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• 제24권4호
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• pp.211-221
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• 2024

Pakistan is a top producer and exporter of high-quality rice, but traditional methods are still being used for detecting rice diseases. This research project developed an automated rice blast disease diagnosis technique based on deep learning, image processing, and transfer learning with pre-trained models such as Inception V3, VGG16, VGG19, and ResNet50. The modified connection skipping ResNet 50 had the highest accuracy of 99.16%, while the other models achieved 98.16%, 98.47%, and 98.56%, respectively. In addition, CNN and an ensemble model K-nearest neighbor were explored for disease prediction, and the study demonstrated superior performance and disease prediction using recommended web-app approaches.

• 한국콘크리트학회:학술대회논문집
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• 한국콘크리트학회 1996년도 봄 학술발표회 논문집
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• pp.280-285
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• 1996

The shear behavior of reinforced concrete deep beams with web opennings has been scrutinized experimentally to verify the influences of the structural parameters such as size, shape, location and reinfrocements of web openings, and shear span ratio. A total of 22 specimens has been tested under one or two point loading conditions at the laboratory. In the tests most specimens have shown shear failures with inclined cracks from the loacing points to the supports through openings. The ultimate strengths of the specimens measured from the tests have shown wide differences depending on the locations of the openings which deter the formation of the compression struts between the loading points and the supports. The effects of the reinforcements and the geomtry of the openings on the shear strengths and the crack developments have been carefully checked and analyzed.