• Journal of the Korea institute for structural maintenance and inspection
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• v.10 no.5
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• pp.179-186
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• 2006

In this study, Multi-Layer Perceptron(MLP) among models of Artificial Neural Network(ANN) is used for the development of a model that evaluates the bending capacities of reinforced concrete beams strengthened by FRP Rebar. And the data of the existing researches are used for materials of ANN model. As the independent variables of input layer, main components of bending capacities, width, effective depth, compressive strength, reinforcing ratio of FRP, balanced steel ratio of FRP are used. And the moment performance measured in the experiment is used as the dependent variable of output layer. The developed model of ANN could be applied by GFRP, CFRP and AFRP Rebar and the model is verified by using the documents of other previous researchers. As the result of the ANN model presumption, comparatively precise presumption values are achieved to presume its bending capacities at the model of ANN(0.05), while observing remarkable errors in the model of ANN(0.1). From the verification of the ANN model, it is identified that the presumption values comparatively correspond to the given data ones of the experiment. In addition, from the Sensitivity Analysis of evaluation variables of bending performance, effective depth has the highest influence, followed by steel ratio of FRP, balanced steel ratio, compressive strength and width in order.

• Journal of the Korea institute for structural maintenance and inspection
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• v.23 no.7
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• pp.66-71
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• 2019

In this paper, a study was conducted on the method of using GPR data to predict rebar thickness inside a facility. As shown in the cases of poor construction, such as the use of rebars below the domestic standard and the construction of reinforcement, information on rebar thickness can be found to be essential for precision safety diagnosis of structures. For this purpose, the B-scan data of GPR was obtained by gradually increasing the diameter of rebars by making specimen. Because the B-scan data of GPR is less visible, the data was converted into the heatmap image data through migration to increase the intuition of the data. In order to compare the results of application of commonly used B-scan data and heatmap data to CNN, this study extracted areas for rebars from B-scan and heatmap data respectively to build training and validation data, and applied CNN to the deployed data. As a result, better results were obtained for the heatmap data when compared with the B-scan data. This confirms that if GPR heatmap data are used, rebar thickness can be predicted with higher accuracy than when B-scan data is used, and the possibility of predicting rebar thickness inside a facility is verified.

• Construction Engineering and Management
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• v.11 no.3
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• pp.5-7
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• 2010

• Magazine of the Korea Concrete Institute
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• v.10 no.3
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• pp.209-218
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• 1998

본 연구에서는 콘크리트내 철근의 방식성을 검토하기 위하여 실제 구조물과 유사하도록 콘크리트 대형 패널 실험체를 제작하였으며, 실험체 제작시 콘크리트 내부에 염화물을 혼입하여 음극전기방식 공법을 도입한 실험체와 공법을 도입하지 않은 실험체의 염화물에 의한 철근방식효과를 비교 분석하였다. 실험에 사용된 음극전기방식은 비소모성 티타늄 양극망을 사용한 외부전원방식이며, 최근에 국내에서도 사용실적이 늘고 있는 리모트 모니터링 시스템을 적용하여 구조물의 유지관리상 연속성 있게 콘크리트내 철근의 방식정도를 확인할 수 있는지에 대해 검토하였다.

• Geotechnical Engineering
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• v.37 no.1
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• pp.13-20
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• 2021

• Proceedings of the Korean Geotechical Society Conference
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• 2007.09a
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• pp.115-123
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• 2007

설계 하중이 큰 대형 구조물의 기초로 많이 사용되는 현장타설말뚝은 현장에서 지반을 굴착하여 조립된 철근망을 삽입한 후, 콘크리트를 타설하여 제작되므로 복잡한 시공 과정과 현장의 특수한 지하수 및 지반 조건으로 인하여 현장타설말뚝의 내부에는 결함이 포함될 수 있다. 발생 가능한 대표적인 결함으로 연약한 말뚝 선단, 말뚝체 콘크리트의 품질 저하, 말뚝과 지반의 접촉 불량, 주 철근의 부식 등이 있으며, 이들 결함을 감지하기 위한 건전도 시험법으로 공대공초음파 검층, 충격반향시험, 충격응답시험, 감마-감마 검층법 등이 있다. 결함은 말뚝의 수평지지력을 감소시키며, 일반적으로 발생하는 비대칭단면 결함에 의한 응력 집중현상과 수평 하중에 의한 휨모멘트는 연직지지거동에 영향을 준다. 따라서 결함을 감지하고 평가하는 것이 현장타설말뚝의 품질관리에 있어 매우 중요하다.

• Proceedings of the Computational Structural Engineering Institute Conference
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• 2010.04a
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• pp.433-436
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• 2010

본 논문에서는 파일형 선박충돌 방호공에 선박이 충돌하였을 때 방호공의 거동을 해석하였다. 방호공의 구조는 상부슬래브, RCP 말뚝 및 이를 지지하는 지반은 비선형 지반스프링으로 모델링 하였다. 상부슬래브 8절점요소로 모델링 하였으며 철근과 콘크리트로 구성되어있다. RCP 말뚝은 철근망과 충진콘크리트로 구성되어있으며 충돌 시 파괴거동을 표현할 수 있는 Damaged Plasticity로 모델을 사용하였고 Shell 요소로 모델링 하였다. 선박충돌 시 선박의 강성에 따른 거동 특성을 파악하기 위해 선박을 강체모델과 실제모델에 대한 해석을 수행하였다. 선박과 교량의 충돌은 정면충돌로 고려하였으며, 충돌속도는 3.3m/sec로 가정하였다. 선박과 방호공과의 충돌 해석은 비선형 해석 프로그램인 ABAQUS/Explicit을 이용하여 수행하였으며, 이를 통하여 선박 충돌 시 방호공의 에너지 거동을 분석하였다. 해석결과 선박의 강성이 커질수록 슬래브의 변형 및 소산 에너지량이 커지는 것을 확인할 수 있었다.

• Journal of Digital Convergence
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• v.14 no.8
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• pp.211-221
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• 2016

The rapid trends toward outsourcing and collaboration have created complex multi-tier supply chains for construction and engineering industries. Working with suppliers and sub-suppliers requires continuous integration activities in order to maximize the performances of the entire supply chain. The purpose of this study is to identify the factors influencing the performances and long-term business relationship of second-tier suppliers in directed sourcing environment. This study proposes the asset specificity, trust, information-sharing and collaboration, as antecedents variables, and collected the survey responses from the second-tier suppliers in rebar manufacturing works. The statistical results indicate that the asset specificity, trust, information-sharing and collaboration have significant influences on the long-term business relationship of rebar manufacturing second-tier suppliers, but trust has no impact on the performances of second-tier suppliers at 5% significance level. Practical implications are also discussed.

• Magazine of the Korea Concrete Institute
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• v.22 no.5
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• pp.71-77
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• 2010

• Journal of the Computational Structural Engineering Institute of Korea
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• v.17 no.2
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• pp.131-140
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• 2004

It really needs fuzzy decision making of integrity assessment considering about both durability and load carrying capacity for maintenance and administration, such as repairing and reinforcing. This thesis shows efficient models about reinforced concrete structure using CART-ANFIS. It compares and analyzes decision trees parts of expert system, using the theory of fuzzy, and applying damage & diagnosis at reinforced concrete structure and decision trees of integrity assessment using established artificial neural. Decided the theory of reinforcement design for recovery of durability at damaged concrete ＆ the theory of reinforcement design for increasing load carrying capacity keep stability of damage and detection. It is more efficient maintenance and administration at reinforced concrete for using integrity assessment model of this study and can carry out predicting cost of life cycle.