• Journal of the Korea institute for structural maintenance and inspection
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• v.13 no.2 s.54
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• pp.231-242
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• 2009

The baseline distribution of a structure represents the statistical distribution of dynamic response feature from the healthy state of the structure. Generally, damage-sensitive dynamic response feature of a structure manifest themselves near the tail of a baseline statistical distribution. In this regard, some researchers have paid attention to extreme value distribution for modeling the tail of a baseline distribution. However, few researches have been conducted to theoretically understand the extreme value distribution from a perspective of statistical damage assessment. This study investigates the asymptotic convergence of domain of attraction in extreme value distribution through parameter estimation, which is needed for reliable statistical damage assessment. In particular, the asymptotic convergence of a domain of attraction is quantified with respect to the sample size out of which each extreme value is extracted. The effect of the sample size on false positive alarms in statistical damage assessment is quantitatively investigated as well. The validity of the proposed method is demonstrated through numerically simulated acceleration data on a two span continuous truss bridge.

• Journal of Korea Water Resources Association
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• v.50 no.8
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• pp.513-520
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• 2017

In order to analyze flood damage mitigation effects, it is necessary not only to analyze inundation areas and depth through hydraulic and hydrological analysis but also to estimate flood damages. Flood damages of structure and contents of buildings are generally analyzed according to the flood depth. In this study, we developed and applied flood depth-damage functions for the school buildings based on actual damage data. In addition, the development and modification procedure of flood depth-damage functions for school buildings is presented in this paper, and the developed damage functions are verified by comparing them with the existing method. It is expected that the process of developing and applying flood depth-damage functions presented in this study can be used in the cost benefit analysis of flood damage mitigation measures.

• Journal of Korean Association for Spatial Structures
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• v.10 no.4
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• pp.16-22
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• 2010

• Journal of Korean Tunnelling and Underground Space Association
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• v.26 no.1
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• pp.1-17
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• 2024

Analyzing the tunnel excavation behavior and its effect on the surrounding ground involves large deformation behavior. Therefore, in order to properly simulate the tunnel excavation process and rigorously investigate the actual effect of excavation on surrounding ground and tunnel structure large deformation analysis method is required. In this study, two major numerical approaches capable of considering large deformations behavior were applied to investigate the effect of tunnel boring machine excavation on the surrounding ground: coupled Eulerian-Lagrangian (CEL) and the automatic remeshing (AR) method. Relative performance of both approaches was evaluated through the ground response due to TBM excavation. The ground response will be quantified by estimating the range of the excavation damaged zone (EDZ). By comparing the results, the range of the EDZ will be suggested on the vertical and horizontal direction along the TBM excavation surface. Based on the computed results, it was found that the size of EDZ around the excavation surface and the tendencies was in good agreement among the two approaches. Numerical results clearly show that the size of the EDZ around the tunnel tends to be larger for rock with higher RMR rating. The size of the EDZ is found to be direct proportional to the tunnel diameter, whereas the depth of the tunnel is inversely proportional due to higher confinement stress around the excavation surface.

• Proceedings of the Computational Structural Engineering Institute Conference
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• 2011.04a
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• pp.676-679
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• 2011

인공신경망(Artificial Neural Network)을 이용하여 RC Mock-up 구조물의 손상위치 및 손상정도를 단계적으로 추정하였다. 대상 구조물은 가진실험을 통하여 구조물의 응답을 취득하고 구조물식별기법(Structural System Identification)을 통하여 구조물의 동특성을 찾았다. 유한요소해석프로그램을 사용하여 동특성이 계측치와 가장 유사한 기본해석모델을 만든 후 이 기본해석모델을 이용하여 학습데이터를 생성하였다. 기존 인공신경망을 이용한 손상탐지를 개선하고자 본 연구에서는 인공신경망 학습데이터를 분석하였고 효과적인 손상탐지를 위하여 학습데이터를 가공하였다. 가공된 학습데이터를 사용하여 단계별 손상탐지를 실시하였고 기존 손상탐지 방법보다 좋은 결과를 유도하였다.

• Proceedings of the Computational Structural Engineering Institute Conference
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• 2010.04a
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• pp.335-338
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• 2010

구조물의 상태평가는 구조물 고유의 동특성을 분석함으로써 평가할 수 있다. 구조물은 태풍, 지진 및 기타 외적 환경 등에 의하여 손상이 발생하고 이러한 구조물의 손상은 강성의 변화로 이어져 구조물의 동특성에 변화를 일으킨다. 따라서 손상 발생 전후의 동적응답을 각각 계측한 후 구조물 식별(Structural System Idetification)을 통하여 고유진동수 및 모드형상을 추출하고 수학적인 기법을 사용하여 구조물을 구성하고 있는 개별 부재 혹은 부재 그룹의 강성을 비교함으로써 손상의 발생여부 및 손상정도를 추정할 수 있다. 본 연구에서는 지붕트러스 구조물에 대하여 손상평가를 수행하고 이를 검증할 수 있는 Mock-up 구조물을 설계 및 시공하였다.

• Journal of the Earthquake Engineering Society of Korea
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• v.1 no.2
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• pp.1-15
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• 1997

This paper presents substructural identification methods for the assessment of local damages in complex and large structural systems. For this purpose, an auto-regressive and moving average with stochastic input (ARMAX) model is derived for a substructure to process the measurement data impaired by noises. Using the substructural methods, the number of unknown parameters for each identification can be significantly reduced, hence the convergence and accuracy of estimation can be improved. Secondly, the damage index is defined as the ratio of the current stiffness to the baseline value at each element for the damage assessment. The indirect estimation method was performed using the estimated results from the identification of the system matrices from the substructural identification. To demonstrate the proposed techniques, several simulation and experimental example analyses are carried out for structural models of a 2-span truss structure, a 3-span continuous beam model and 3-story building model. The results indicate that the present substructural identification method and damage estimation methods are effective and efficient for local damage estimation of complex structures.

• Journal of Broadcast Engineering
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• v.5 no.2
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• pp.167-175
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• 2000

Compressed bitstreams generated by an MPEG-2 video encoder (or digital TV picture transmission are quite sensitive to channel errors. Due to the coding structure of the MPEG-2 video compression algorithm, a single bit error can affect not only the current Picture frame but also succeeding frames. Error concealment algorithms attempt to repair damaged portions of the picture by exploiting spatial and temporal redundancies in the correctly received and reconstructed video frames. In this paper, we analyze the effect of channel errors in MPEG-2 video bitstreams and estimate lost motion vectors by exploiting temporal redundancies in the video frames. Motion vectors can be estimated from the vertically adjacent extended region of lost macroblocks. Finally, we conceal the damaged macroblocks by compensating the displacement with the estimated motion vectors. Simulation results demonstrate that both the weighted sum algorithm and the extension matching algorithm achieve good performance in terms of PSNR values as well as subjective image quality.

• Journal of the Korea institute for structural maintenance and inspection
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• v.19 no.2
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• pp.92-98
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• 2015

Recently, buildings tend to be large size, complex shape and functional. As the size of buildings is becoming massive, the need for structural health monitoring (SHM) technique is increasing. Various SHM techniques have been studied for buildings which have different dynamic characteristics and influenced by various external loads. "Abnormal behavior point" is a moment when the structure starts vibrating abnormally and this can be detected by comparing between before and after abnormal behavior point. In other words, anomalous behavior is a sign of damage on structures and estimating the abnormal behavior point can be directly related to the safety of structure. Abnormal behavior causes damage on structures and this leads to enormous economic damage as well as damage for humans. This study proposes an estimating technique to find abnormal behavior point using Hilber-Huang Transform which is a time-frequency signal analysis technique and the proposed algorithm has been examined through laboratory tests with a bridge model using a shaking table.

• Journal of the Computational Structural Engineering Institute of Korea
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• v.13 no.4
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• pp.395-404
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• 2000

A damage detection and assessment algorithm is developed by measuring accelerations at limited locations of a structure under forced vibrations. The developed algorithm applies a time-domain system identification (SI) method that identifies a structure by solving a linearly constrained nonlinear optimization problem for optimal structural parameters. An equation error of the dynamic equilibrium of motion is minimized to estimate optimal parameters. An adaptive parameter grouping scheme is applied to localize damaged members with sparse measured accelerations. Damage is assessed in a statistical manner by applying a time-windowing technique to the measured time history of acceleration. Displacements and velocities at the measured degrees of freedom (DOF) are computed by integrating the measured accelerations. The displacements at the unmeasured DOF are estimated as additional unknowns to the unknown structural parameters, and the corresponding velocities and accelerations we computed by a numerical differentiation. A numerical simulation study with a truss structure is carried out to examine the efficiency of the algorithm. A data perturbation scheme is applied to determine the thresholds lot damage indices and to compute the damage possibility of each member.