• Computers and Concrete
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• v.14 no.6
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• pp.727-743
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• 2014

The management of existing concrete bridges has become a major social concern in many developed countries due to the large number of bridges exhibiting signs of significant deterioration. This problem has increased the demand for effective maintenance and renewal planning. In order to implement an appropriate management procedure for a structure, a wide array of corrective strategies must be evaluated with respect to not only the condition state of each defect but also safety, economy and sustainability. This paper describes a new performance evaluation system for existing concrete bridges. The system evaluates performance based on load carrying capability and durability from the results of a visual inspection and specification data, and describes the necessity of maintenance. It categorizes all girders and slabs as either unsafe, severe deterioration, moderate deterioration, mild deterioration, or safe. The technique employs an expert system with an appropriate knowledge base in the evaluation. A characteristic feature of the system is the use of neural networks to evaluate the performance and facilitate refinement of the knowledge base. The neural network proposed in the present study has the capability to prevent an inference process and knowledge base from becoming a black box. It is very important that the system is capable of detailing how the performance is calculated since the road network represents a huge investment. The effectiveness of the neural network and machine learning method is verified by comparing diagnostic results by bridge experts.

• Journal of the Society of Disaster Information
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• v.16 no.4
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• pp.638-649
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• 2020

Purpose: The objective of this study is to evaluate the load carrying capacity of a target bridge structure based on the simple slab bridge of concrete over 20 years of public service. Method: By performing static loading test and dynamic loading test, the displacement, strain, impact factor, and natural frequency values were measured and evaluated through analysis method. Result: The main results of this study are as follows. First, the maximum displacement and maximum strain of S1 were assessed at 2.917 mm and 44.720 𝜇ε( tensile) and -13.760 𝜇ε(compression), respectively, with S2 maximum displacement and maximum strain being 2.100 mm and 4.870 𝜇ε(tensile), respectively. Second, the maximum measured impact factor was 0.191 in section S1 A-A, and the maximum measured impact factor was 0.155 in section S2 C-C. Third, the natural frequency was assessed at 6.086 Hz, and the measurement was found to be within the range of 6.152 Hz to 6.738 Hz. Conclusion: The tested bridge may be evaluated to show good behavior and characteristics for the design load.

• Proceedings of the Korea Concrete Institute Conference
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• 2005.05a
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• pp.39-42
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• 2005

This test program is to investigate the benefits of using headed bars to replace conventional stirrups and using steel fibers to reinforce in the disturbed regions in the dapped ended beam, This distribution of reinforcement was selected for aspects associated with the portion of beam section in bridge structures. The beams containing T-headed bars have a superior performance such as improved ductility, larger energy adsorption and enhanced post-peak load carrying capability. The capacity of DEB with steel fibers also show increase of ductility, shear strength, and crack.

• Journal of Korean Society of Steel Construction
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• v.18 no.6
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• pp.717-726
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• 2006

Traditional external post-tensioning method using either steel bars or tendons is commonly used as a retrofitting method for steel composite bridges. However, the method has some disadvantages such as stress concentration at anchorages and inefficient load-carrying capability of live loads. Multi-stepwise prestressing method using thermal expanded coverplate is a newly proposed prestressing method, which was originally developed for prestressing steel structures. A new retrofitting method for steel girder bridges founded on a simple concept of thermal expansion and contraction of cover plate, the method is a hybrid of and combines the advantages of external post-tensioning and thermal prestressing. In this paper, basic concepts of the method are presented and an illustrative experiment is introduced. From actual experimental data, the thermal prestressing effect was substantiated and the FEM approach for its analysis was verified. The retrofitting effects ofa single-span bridge were analyzed and the feasibility of the developed method was examined.

• Journal of the Korea Concrete Institute
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• v.19 no.4
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• pp.483-490
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• 2007

Traditional external post-tensioning method using either steel bars or tendons is commonly used as a retrofitting method for concrete bridges. However, the external post-tensioning method has some disadvantages such as stress concentration at anchorages and inefficient load carrying capability regarding live loads. Thermal prestressing method is a newly proposed method for strengthening and rehabilitation of concrete girder bridges. Founded on a simple concept of thermal expansion and contraction of steel, the method is a hybrid method of external post-tensioning and steel plate bonding, combining the merits of two methods. In this paper, basic concepts of the method are presented and an illustrative experiment is introduced. From actual experimental data, the thermal prestressing effect is substantiated and the FEM approach for its analysis is verified.

• Journal of the Korea institute for structural maintenance and inspection
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• v.28 no.3
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• pp.66-73
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• 2024

Stay-cable is one of the most important load carrying members in cable-stayed bridges. Monitoring structural integrity of stay-cables is crucial for evaluating the structural condition of the cable-stayed bridge. For stay-cables, tension and damping ratio are estimated based on modal properties as a measure of structural integrity. Since the monitoring system continuously measures the vibration for the long-term period, data acquisition systems should be stable and power-efficiency as the hardware system. In addition, massive signals from the data acquisition systems are continuously generated, so that automated analysis system should be indispensable. In order to fulfill these purpose simultaneously, this study presents an autonomous cable monitoring system based on domain-knowledge using IoT for continuous cable monitoring systems of cable-stayed bridges. An IoT system was developed to provide effective and power-efficient data acquisition and on-board processing capability for Edge-computing. Automated peak-picking algorithm using domain knowledge was embedded to the IoT system in order to analyze massive data from continuous monitoring automatically and reliably. To evaluate its operational performance in real fields, the developed autonomous monitoring system has been installed on a cable-stayed bridge in Korea. The operational performance are confirmed and validated by comparing with the existing system in terms of data transmission rates, accuracy and efficiency of tension estimation.