• 한국방재학회:학술대회논문집
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• 2008.02a
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• pp.505-508
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• 2008

When it grasps a total property losses and relationship of damage factors, there is possibility of reducing the natural disaster damage which is a yearly repeated. Also, checking and supply to vulnerability should be presupposed. This study aims to find out a damage factor vulnerability using a natural disaster database by Park et al(2007). And added 2005 year data to database. Total 10 damage factors are deaths(person, including missing person) injury(person), victims(person), building(thousand), vessel(thousand), cultivated land(thousand), public facilities(thousand), others(thousand), total property losses(thousand). We analyzed of correlation analysis, ratio, population, area, regional character etc for damage factors.

• Journal of the Architectural Institute of Korea Structure & Construction
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• v.34 no.2
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• pp.3-10
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• 2018

Damage location and extent of structure could be detected by the inverse analysis on dynamic response properties such as frequencies and mode shapes. In practice the measured difference of natural frequencies represent the stiffness change reliably, however the measured mode shape is insensitive for stiffness change, but provides spatial information of damage. The damage detection index on shear building structures is formulated in this study. The damage detection index could be estimated from mode shape and srory stiffness of undamaged structure and frequency difference between undamaged and damaged structure. For the verification of the observed damage detection method, the numerical analysis of Matlab and MIDAS and shacking table test were performed. In results, the damage index of damaged story was estimated so higher than undamaged stories that indicates the damaged story apparently.

• Transactions of the Korean Society of Mechanical Engineers A
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• v.24 no.2 s.173
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• pp.455-463
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• 2000

In order to develop nondestructive techniques for the quantitative estimation of creep damage a series of crept copper samples were prepared and their ultrasonic velocities were measured. Velocities measured in three directions with respect to the loading axis decreased nonlinearly and their anisotropy increased as a function of creep-induced porosity. A progressive damage model was described to explain the void-velocity relationship, including the anisotropy. The comparison of modeling study showed that the creep voids evolved from sphere toward flat oblate spheroid with its minor axis aligned along the stress direction. This model allowed us to determine the average aspect ratio of voids for a given porosity content. A novel technique, the back propagation neural network (BPNN), was applied for estimating the porosity content due to the creep damage. The measured velocities were used to train the BP classifier, and its accuracy was tested on another set of creep samples containing 0 to 0.7 % void content. When the void aspect ratio was used as input parameter together with the velocity data, the NN algorithm provided much better estimation of void content.

• Magazine of the Korea Concrete Institute
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• v.3 no.3
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• pp.111-119
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• 1991

Most of the conventional aseismic design methods for reinforced concrete structures, based on the strong¬column weak-beam design concept, do not necessarily the state of damage distribution over the entire frame. This paper introduces a seismic damage-controlled design method for RC frames which aim at individual member damage indices. Three design parameters, namely the longitudinal steel ratio, the confinement steel ratio and the frame member depth, were studied for their influence on the frame response to an earthquake. The usefulness of this design method will be demonstrated with a three-bay four-story building frame so that, on the one hand, the method will reduce the damage as measured by the global damage index under the same earthquake and, on the other hand, will lead to a larger capacity enabling stronger earthquakes to be accom¬odated .

• Journal of the Korean Society of Hazard Mitigation
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• v.2 no.4 s.7
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• pp.77-85
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• 2002

Korean government compensates 100% for natural disaster relief fund to public facilities, and provides 70 percents to crops through unit price calculation. This study estimated disaster damage according to the standard production cost of crops. Disaster damage was estimated according to the unit price of crops. Those crops are lettuce, pumpkin, red pepper, spinach, tomato and cucumber. As a result, the ratio of natural disaster relief fund to damage was revealed as $3.3%{\sim}13.8%$ with present method, 5.7%{$\sim}34.1%$ with suggested method. Suggested method is the first one considered damage ratio of crops, producer price and raising period.

• Structural Engineering and Mechanics
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• v.70 no.4
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• pp.457-466
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• 2019

This study develops a damage detection method based on neural networks. The performance of the method is numerically and experimentally verified using a three-story shear building model. The framework is mainly composed of two hierarchical stages to identify damage location and extent using artificial neural network (ANN). The normalized damage signature index, that is a normalized ratio of the changes in the natural frequency and mode shape caused by the damage, is used to identify the damage location. The modal parameters extracted from the numerically developed structure for multiple damage scenarios are used to train the ANN. The positive alarm from the first stage of damage detection activates the second stage of ANN to assess the damage extent. The difference in mode shape vectors between the intact and damaged structures is used to determine the extent of the related damage. The entire procedure is verified using laboratory experiments. The damage is artificially modeled by replacing the column element with a narrow section, and a stochastic subspace identification method is used to identify the modal parameters. The results verify that the proposed method can accurately detect the damage location and extent.

• Smart Structures and Systems
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• v.29 no.1
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• pp.167-179
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• 2022

This article develops a long-term condition assessment method for stay cables in cable stayed bridges using the monitored cable tension forces under operational condition. Based on the concept of influence surface, the matched cable tension ratio of two cables located at the same side (either in the upstream side or downstream side) is theoretically proven to be related to the condition of stay cables and independent of the positions of vehicles on the bridge. A sensor grouping scheme is designed to ensure that reliable damage detection result can be obtained even when sensor fault occurs in the neighbor of the damaged cable. Cable forces measured from an in-service cable-stayed bridge in China are used to demonstrate the accuracy and effectiveness of the proposed method. Damage detection results show that the proposed approach is sensitive to the rupture of wire damage in a specific cable and is robust to environmental effects, measurement noise, sensor fault and different traffic patterns. Using the damage sensitive feature in the proposed approach, the metrics such as accuracy, precision, recall and F1 score, which are used to evaluate the performance of damage detection, are 97.97%, 95.08%, 100% and 97.48%, respectively. These results indicate that the proposed approach can reliably detect the damage in stay cables. In addition, the proposed approach is efficient and promising with applications to the field monitoring of cables in cable-stayed bridges.

• Structural Engineering and Mechanics
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• v.16 no.5
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• pp.581-595
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• 2003

Since the conventional direct approaches are hard to be applied for damage diagnosis of complex large-scale structures, a two-step approach for diagnosing the joint damage of framed structures is presented in this paper by using artificial neural networks. The first step is to judge the damaged areas of a structure, which is divided into several sub-areas, using probabilistic neural networks with natural Frequencies Shift Ratio inputs. The next step is to diagnose the exact damage locations and extents by using the Radial Basis Function (RBF) neural network with the second Element End Strain Mode of the damaged sub-area input. The results of numerical simulation show that the proposed approach could diagnose the joint damage of framed structures induced by earthquake action effectively and has reliable anti-jamming abilities.

• Structural Engineering and Mechanics
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• v.32 no.4
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• pp.489-500
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• 2009

The aim of this paper is to compare wavelet, kurtosis and pseudofractal based techniques for structural health monitoring in the presence of measurement noise. A detailed comparison and assessment of these techniques have been carried out in this paper through numerical experiments for the calibration of damage extent of a simply supported beam with an open crack serving as an illustrative example. The numerical experiments are deemed critical due to limited amount of experimental data available in the field of singularity based detection of damage. A continuous detectibility map has been proposed for comparing various techniques qualitatively. Efficiency surfaces have been constructed for wavelet, kurtosis and pseudofractal based calibration of damage extent as a function of damage location and measurement noise level. Levels of noise have been identified for each technique where a sudden drop of calibration efficiency is observed marking the onset of damage masking regime by measurement noise.

• Journal of the Korean Society of Safety
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• v.13 no.1
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• pp.104-111
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• 1998

Statistical analyses of occupational accidents associated with construction work were carried out to explore the basic statistical characteristics of their damage consequences. Emphasis was placed upon the probabilistic and statistical analyses to clarify, in particular, the relationship between frequency of labour accidents and their damage consequences. Damage consequences were classified into two categories such as the number of workdays lost due to accidents and the number of injured workers involved in one accident. Two types of accident data were collected for the analyses. From the analyses, it was found that the relation between damage due to accidents and their frequencies can be represented by a simple power function which indicates a log-log linear relation. By making use of this relationship, various probabilistic evaluations such as the estimation of the mean time periods between accidents, expected damage consequences, and expected damage ratio between different mean time period of accidents were conducted.