• Proceedings of the Korea Concrete Institute Conference
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• 2004.11a
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• pp.663-666
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• 2004

An analysis of the annual frequency of collapse(AF) is performed for each bridge pier exposed to ship collision. AF is computed for each bridge component and vessel classification. The summation of AFs computed over all of the vessel classification intervals for a specific component should equal the annual frequency of collapse of the component. The designer should use judgment in developing a distribution of the vessel frequency data based on discrete groupings or categories of vessel size by DWT. In the present study the effect of vessel classification on the annual frequency of collapse in the ship collision risk assessment is investigated by illustrative numerical examples based on the vessel frequency data of the domestic harbor. The DWT interval for larger vessels has more effect on the ship collision risk. Therefore the expert judgement in determining the larger DWT interval is required because the design impact lateral resistances of bridge components depend on the ship collision risk.

• International conference on construction engineering and project management
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• 2007.03a
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• pp.810-819
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• 2007

Usually the status of a bridge is determined by its structural capability and material strength. Consequently a lot of researchers have studied the failure, the fatigue, and the deterioration of the structure in terms of the structural function of a bridge. However, the overall performance of a bridge may be affected simply by the damage of one of its components. Therefore this study utilized a systematic classification and statistical analysis based on the existing bridge inspection data collected in Taiwan to reach the following goals: (1) assess the performance distribution and deterioration rate for bearing and expansion joint of bridge; (2) find out the right time to do the preventive and essential maintenance for the component of bridge with an empirical method, and to decide what time and which component of a bridge will receive preventive maintenance or regular maintenance.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.41 no.6
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• pp.751-760
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• 2021

Most bridges in Korea are over 20 years old, and many problems linked to their deterioration are being reported. The current practice for bridge inspection mainly depends on expert evaluation, which can be subjective. Recent studies have introduced data-driven methods using building information modeling, which can be more efficient and objective, but these methods require manual procedures that consume time and money. To overcome this, this study developed an image-based automaticbridge component classification network to reduce the time and cost required for converting the visual information of bridges to a digital model. The proposed method comprises two convolutional neural networks. The first network estimates the type of the bridge based on the superstructure, and the second network classifies the bridge components. In avalidation test, the proposed system automatically classified the components of 461 bridge images with 96.6 % of accuracy. The proposed approach is expected to contribute toward current bridge maintenance practice.

• Proceedings of the KSR Conference
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• 2002.10b
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• pp.1041-1046
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• 2002

A railway open deck plate girder bridge without ballast should support relatively heavier vehicle loads compared with its self-weight. For such a reason, actual dynamic response of the bridge is considerably differing with normal prediction because additional masses added from vehicle to a bridge have an effect on the dynamic characteristics of the bridge. These differences affect to the estimation of a natural frequency change that adopted for one of the evaluation technique of strength decrease, and these make trouble to the analysis of a natural frequency from the field test data that measured at the bridge subjected to a running vehicle. In this study, classification of mass participation ratio for each component of open deck plate girder bridge without ballast and the comparison according to the change of vibration characteristics for the case of subjected to a running vehicle were accomplished.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.40 no.2
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• pp.239-245
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• 2020

Recently, BIM (Building Information Modeling) are widely being utilized in Construction industry. However, most structures that have been constructed in the past do not have BIM. For structures without BIM, the use of SfM (Structure from Motion) techniques in the 2D image obtained from the camera allows the generation of 3D model point cloud data and BIM to be established. However, since these generated point cloud data do not contain semantic information, it is necessary to manually classify what elements of the structure. Therefore, in this study, deep learning was applied to automate the process of classifying structural components. In the establishment of deep learning network, Inception-ResNet-v2 of CNN (Convolutional Neural Network) structure was used, and the components of bridge structure were learned through transfer learning. As a result of classifying components using the data collected to verify the developed system, the components of the bridge were classified with an accuracy of 96.13 %.

• 한국방재학회:학술대회논문집
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• 2011.02a
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• pp.39-39
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• 2011

This study presents an effective vision-based system for cable bridge damage detection. In theory, cable bridges need to be inspected the outer as well as the inner part. Starting from August 2010, a new research project supported by Korea Ministry of Land, Transportation Maritime Affairs(MLTM) was initiated focusing on the damage detection of cable system. In this study, only the surface damage detection algorithm based on a vision-based system will be focused on, an overview of the vision-based cable damage detection is given in Fig. 1. Basically, the algorithm combines the image enhancement technique with principal component analysis(PCA) to detect damage on cable surfaces. In more detail, the input image from a camera is processed with image enhancement technique to improve image quality, and then it is projected into PCA sub-space. Finally, the Mahalanobis square distance is used for pattern recognition. The algorithm was verified through laboratory tests on three types of cable surface. The algorithm gave very good results, and the next step of this study is to implement the algorithm for real cable bridges.

• Journal of the Society of Disaster Information
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• v.12 no.1
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• pp.19-31
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• 2016

The purpose of this study was to establish the initial computerized management database which can be applied to a universal project management computer system for managing universal project management and operation. Database construction model presented in this paper suggested the model of organization, activity and operation of bridge construction(two abutment-three-span) based on the organization information classification system of the facility classification, functional component classification, work classification, resource classification. Database model established in this study are considered to be able to take advantage of a very systematic and scientific management for future universal project management and operations.

• Journal of the Computational Structural Engineering Institute of Korea
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• v.20 no.3
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• pp.393-404
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• 2007

A concept of multi-layered database is proposed for the integrated operation of bridge information in this study. The multi-layered database is a logically integrated database composed of standardized information layers. The standardized information layers represent the data sets that can be unified, and they are defined by standardized information models. Classification system of bridge component was used as a basis of the multi-layered database, and code system based on the classification system was employed as a key integrator to manipulate the distributed data located on the different information layers. In addition, data level indicating priorities of information layers was defined to support strategic planning of the multi-layered database construction. As a proof of concept, a prototype of multi-layered database for object-oriented 3-D shape information and structural calculation document was built. Data consistency check of the semantically same data in the two different information layer was demonstrated, It is expected that the proposed concept can assure the integrity and consistency of information in the bridge information management.