• Magazine of the Korea Concrete Institute
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• v.7 no.6
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• pp.92-98
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• 1995

• Korean Journal of Construction Engineering and Management
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• v.6 no.5 s.27
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• pp.119-127
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• 2005

According to the recent systemic changes such as construction market reduction, five days per week system, introduction of construction duration reduction bidding system and post-construction sale system, the bidding competition have been enhanced. However, there are many construction schedule risks which could delay construction completion. Without the proper identification of construction schedule risks and the structured construction schedule risk management, the competitive advantages of construction project could not be made. Previous researches to solve the problem have been focused on the construction schedule categorization, construction schedule management, and the system development to manage the construction schedule risk. Therefore, this study selected the reinforeced concrete construction as the studied work due to the major impact characteristics on the total construction duration and the quite accident rate, and then proposed the real construction schedule risks of reinforced concrete construction and the construction risk management method based on the previous studies, many times of expert interviews and brainstorming.

• Proceedings of the Computational Structural Engineering Institute Conference
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• 2002.04a
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• pp.274-283
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• 2002

This paper presents an efficient models for reinforeced concrete structures using CART-ANFIS(classification and regression tree-adaptive neuro fuzzy inference system). a fuzzy decision tree parttitions the input space of a data set into mutually exclusive regions, each of which is assigned a label, a value, or an action to characterize its data points. Fuzzy decision trees used for classification problems are often called fuzzy classification trees, and each terminal node contains a label that indicates the predicted class of a given feature vector. In the same vein, decision trees used for regression problems are often called fuzzy regression trees, and the terminal node labels may be constants or equations that specify the Predicted output value of a given input vector. Note that CART can select relevant inputs and do tree partitioning of the input space, while ANFIS refines the regression and makes it everywhere continuous and smooth. Thus it can be seen that CART and ANFIS are complementary and their combination constitutes a solid approach to fuzzy modeling.

• Journal of the Korean Society of Hazard Mitigation
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• v.8 no.5
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• pp.7-13
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• 2008

This paper presents experimental and analysis studies about both the corroded steel expansion and the variation of poor bonding range between steel and concrete. A loss of overall bonding capacity at the concrete-steel interface is evaluated experimentally and crack patterns at the bottom of the concrete are presented here. Steel-concrete interface is covered by rubber due to present local loss of the concrete-steel interface bonding capacity. In case of crack analysis performed by commercial FEM programs. we investigated crack‘s pattern and location. Finally, it is concluded that overall flexural capacity of the reinforced concrete structure is increased by the corroded steel expansion and is dependent of the bonding range at the steel- concrete interface. These results give an important factor to decide a life of reinforced concrete structures.

• Journal of Digital Contents Society
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• v.18 no.7
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• pp.1457-1464
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• 2017

This paper is to introduce the a system which monitors and detects the object position in reinforced the concrete structure using UWB-RF. This system is able to check any changes in the inside of the concrete structure using its penetration and reflection characteristics and it can also numerically measure the position of rebar in the concrete structure. For the verification of the performance of this system, we set up the internal compositions of concrete in 3 different types of test-bed. On the other hand, for the measuring of the location of rebar, which varies depending on the type of structure, the software which shows the distance in the structure were used. The result shows that the position in the concrete could be measured within the tolerance of ${\pm}1{\sim}4mm$ depending on the type of structure in the concrete.