• Steel and Composite Structures
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• v.23 no.4
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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.

• Journal of the Computational Structural Engineering Institute of Korea
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• v.20 no.6
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• pp.699-708
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• 2007

Reinforced concrete deep beams are general structural members used as transfer-girder, pile cap, foundation wall and so on. They have a complex stess formation. Generally, failure mechanisms differ from either continuous deep beams or simple supported deep beams. In continuous deep beams, a negative moment is occurred over intermediate support and the location of maximum moment coincide with high shear force. Therefore, failure usually occurs at this region. While on the other hand, in simple supported deep beam, the region of high shear coincides with the region of low moment. The web opening of deep beams for accepting a facility makes shear behaviors of deep beams more complex and gives rise to an expansion of crack around the opening and a decline of shear capacity of deep beams. Therefore, Engineers must determine a delicate reinforcement method to control a crack and increase a shear capacity. The purpose of this report is a computation of an effective reinforcement method through non-linear finite element method by means of adopting various reinforcement method as variables and a computation of shear capacity formula taking an effectiveness of reinforcement into consideration.

• Journal of the Semiconductor & Display Technology
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• v.21 no.4
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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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• v.30 no.2
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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.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.25 no.8
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• pp.1005-1012
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• 2021

Recently, the use of various location-based services-based location information systems using maps on the web has been expanding, and there is a need for a monitoring system that can check power demand in real time as an alternative to energy saving. In this study, we developed a deep learning real-time virtual power demand prediction web system using open source-based mapping service to analyze and predict the characteristics of power demand data using deep learning. In particular, the proposed system uses the LSTM(Long Short-Term Memory) deep learning model to enable power demand and predictive analysis locally, and provides visualization of analyzed information. Future proposed systems will not only be utilized to identify and analyze the supply and demand and forecast status of energy by region, but also apply to other industrial energies.

• Structural Engineering and Mechanics
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• v.4 no.4
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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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• v.11 no.5
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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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• v.9 no.4
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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.

• Proceedings of the Korea Concrete Institute Conference
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• 1996.04a
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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.

• Structural Engineering and Mechanics
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• v.30 no.1
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• pp.77-97
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• 2008

In this paper, a strut-and-tie model approach has been proposed to directly calculate the amount of reinforcements in deep beams, and the force transfer mechanisms for this approach were investigated using linear finite element analysis. The proposed strut-and-tie model provides quite similar force transfer mechanisms to the results of linear finite element analysis for the 28 deep beams. The load-carrying capacities calculated from the proposed method are both accurate and conservative with little scatter or trends for the 214 deep beams. The deep beams have different concrete strengths including high-strength, various combinations of web reinforcements, and wide range of and a/d ratios. Good accuracy was also obtained using VecTor2, nonlinear finite element analysis tool based on the Modified Compression Field Theory. Since the proposed method provides a safe and reliable means for design of deep beams, this can serve to improve design provisions in future adjustments and development of design guidelines.