• Land and Housing Review
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• v.2 no.1
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• pp.61-68
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• 2011

In order to clarify the structural performances of Welded Deformed Steel Bar Mats (WDSBM), the research stated includes the tests for standard hook of top bars of slab in concrete slab-wall joints, the tests for embedment length of top bar of slab, and the development strength tests for standard hook. The test results are as follows; (1) For slab-wall joints using WDSBM as reinforcement in slab, if the top bars of WDSBM are spliced by ordinary bars with sufficient development length and size, it is enough for the strength and crack control. (2) When WDSBM of slab is spliced in joint, the strength is increased with the embedment of bars of this WDSBM into wall. Beyond peak strength, however, ductility is diminished to that as no splice due to pull-out failure. (3) For slab-wall system, ultimate strain of concrete for flexural compression zone in lower surface of slab seems much greater than that of normal concrete beam. The reason is that normal concrete beam has the joint with $180^{\circ}$, however slab-wall joint has the $90^{\circ}$ of which concrete can be confined.

• Journal of the Korea Concrete Institute
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• v.28 no.1
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• pp.75-84
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• 2016

The purpose of this study was to investigate the performance of solid reinforced concrete columns with triangular reinforcement details. The proposed reinforcement details has economic feasibility and rationality and makes construction periods shorter. A model of solid reinforced concrete columns with triangular reinforcement details was tested under a constant axial load and a quasi-static, cyclically reversed horizontal load. A computer program, RCAHEST (Reinforced Concrete Analysis in Higher Evaluation System Technology), for the analysis of reinforced concrete structures was used. The used numerical method gives a realistic prediction of performance throughout the loading cycles for several test specimens investigated. As a result, proposed triangular reinforcement details for material quantity reduction was superior to existing reinforcement details in terms of required performance.

• Journal of the Korea Concrete Institute
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• v.28 no.6
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• pp.713-722
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• 2016

The goal of this study was to assess the seismic performance of hollow cast-in-place and precast reinforced concrete bridge columns with triangular reinforcement details. The developed material quantity reduction details are economically feasible and rational, and facilitate shorter construction periods. By using a sophisticated nonlinear finite element analysis program, the accuracy and objectivity of the assessment process can be enhanced. The used numerical method gives a realistic prediction of seismic performance throughout the input ground motions for several hollow column specimens investigated. As a result, triangular reinforcement details were designed to be superior to the existing reinforcement details in terms of required seismic performance.

• Geotechnical Engineering
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• v.23 no.3
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• pp.40-45
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• 2007

• KSCE Journal of Civil and Environmental Engineering Research
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• v.43 no.4
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• pp.511-523
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• 2023

Research on the integration of unmanned aerial vehicles and deep learning for reinforced concrete damage detection is actively underway. Convolutional neural networks have a high impact on the performance of image classification, detection, and segmentation as backbones. The MobileNet, a pre-trained convolutional neural network, is efficient as a backbone for an unmanned aerial vehicle-based damage detection model because it can achieve sufficient accuracy with low computational complexity. Analyzing vanilla convolutional neural networks and MobileNet under various conditions, MobileNet was evaluated to have a verification accuracy 6.0~9.0% higher than vanilla convolutional neural networks with 15.9~22.9% lower computational complexity. MobileNetV2, MobileNetV3Large and MobileNetV3Small showed almost identical maximum verification accuracy, and the optimal conditions for MobileNet's reinforced concrete damage image feature extraction were analyzed to be the optimizer RMSprop, no dropout, and average pooling. The maximum validation accuracy of 75.49% for 7 types of damage detection based on MobilenetV2 derived in this study can be improved by image accumulation and continuous learning.

• 지반과기술
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• v.3 no.4
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• pp.68-71
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• 2006

• Journal of the Computational Structural Engineering Institute of Korea
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• v.18 no.2
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• pp.201-211
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• 2005

Due to the complex mechanism and various parameters that affect shear behavior of reinforced concrete (RC) members, models on shear tend to be complex and difficult to utilize for design of structural members, and empirical relationships formulated with limited test data often work lot members having a specific range of influencing parameters on shear. As an alternative approach tot solving this problem, artificial neural networks have been suggested by some researchers. In this paper, artificial neural networks were used to predict shear strengths of RC beams without shear reinforcement. Especially, a large database that consists of shear test results of 398 RC members without shear reinforcement was used for artificial neural network analysis. Three well known approaches for shear strength of RC members, ACI 318-02 shear provision, Zsutiy's equation, and Okamura's relationship, are also evaluated with test results in the shear database and compared with neural network approach. While ACI 318-02 provided inaccurate predictions for RC members without shear reinforcement, the empirical equations by Zsutty and Okamura provided more improved prediction of Shear strength than ACI 318-02. The artificial neural networks, however provided the best prediction of shear strengths of RC beams without shear reinforcement that was closest to test results.

• 기술세미나
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• s.3
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• pp.149-177
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• 2006

• The Journal of Korean Institute of Communications and Information Sciences
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• v.25 no.7B
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• pp.1226-1235
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• 2000

신호망에서의 지연은 망관리 행위의 응답시간에 직접적인 영향을 미치기 때문에 모든 제어정보는 가장 효과적으로 전송되어야 한다. 신호망이 효율적으로 운용되는지 뿐만 아니라 신호망의효과적인 설계를 위해서 신호시스템의 성능을 아는 것이 매우 중요하다. 본 논문에서는 공통선 신호 시스템의 신호망 기능부의 지연 성능을 분석하였다. 분석은 ITU-T 규격을 기반으로 다른 계층의 프로토콜에 독립적인 큐잉모델을 만들어 대기체계분석을 통하여 이루어졌다. 또한 신호망 기능부가 신호 메시지 처리부와 신호망 관리부로 나누어져 구성되는 것도 고려하여 모델링하였다.

• Proceedings of the Korea Concrete Institute Conference
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• 2009.05a
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• pp.61-62
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• 2009

There are many theoretical models and proposed equations for shear strength of reinforced concrete(RC) members. Because shear behavior is very complicated due to many influencing parameters, many equations have been empirically formulated and provide very different level of accuracy. ANN, therefore, have been studied by some researchers, as an alternative approach to solve this problem. In previous research, however, the number of data used in ANN analysis often were not sufficient enough to give reliable results. In this study, a database were established, containing a large number of shear test results on RC beams without transverse reinforcement, which was used for ANN analysis. The prediction results by ANN analysis were also compared with ACI 318 shear provision. The result indicates that ANN provides very good level of accuracy in the prediction of RC shear strength with a proper consideration on the effect of primary influencing parameters.