• Journal of the Korea Academia-Industrial cooperation Society
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• v.17 no.9
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• pp.724-731
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• 2016

As the structural damage caused by earthquakes has been gradually increasing, estimating the seismic fragility of structures has become essential for earthquake preparation. Seismic fragility curves are widely used as a probabilistic indicator of structural safety against earthquakes, and many researchers have made efforts to develop them in a more accurate and effective manner. However, most of the previous research studies used simplified 2D analytical models when deriving fragility curves, mainly to reduce the numerical simulation time; however, in many cases 2D models are inadequate to accurately evaluate the seismic behavior of a structure and its seismic vulnerability. Thus, this study provides a way to derive more accurate, but still effective, seismic fragility curves by using 3D analytical models. In this method, the reliability analysis software, FERUM, is integrated with the structural analysis software, ZEUS-NL, enabling the automatic exchange of data between these two software packages, and the first order reliability method (FORM), which is not a sampling-based method, is utilized to calculate the structural failure probabilities. These tools make it possible to conduct structural reliability analyses effectively even with 3D models. By using the proposed method, this study conducted a seismic vulnerability assessment of RC frame structures with their 3D analytical models.

• Journal of the Society of Disaster Information
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• v.14 no.3
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• pp.379-386
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• 2018

Purpose: This study was to the fragility evaluation of I-shape curved beam structure subjected to strong ground motions including Gyeongju and Pohang earthquakes Method: In particular, to conduct the analytical model, ABAQUS and ANSYS platform was used in this study. Furthermore, the analytical model using 3D Finite Element Model (FEM) was validated, in comparison to the theoretical solutions at the location of 025L, 05L, and 0.75L in static loading condition. In addition, in order to evaluate the seismic fragility of the curved beam structure, 20 seismic ground motions were selected and Monte-Carlo Simulation was used for the empirical fragility evaluation from 0.2g to 1.5g. Result: It was interesting to find that the probability of the system failure was found at 0.2g, as using 190 MPa limit state and the probability of the failure using 390 MPa limit state was starting from 0.6g. Conclusion: This study showed the comparison of the theoretical solution with analytical solution on I-shaped curved beam structures and it was interesting to note that the system subjected to strong ground motions was sensitive to high frequency earthquake. Further, the seismic fragility corresponding to the curved beam shapes must be evaluated.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.17 no.5
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• pp.325-331
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• 2016

This research developed a flood fragility curve of bridges considering the debris impacts. Damage and failures of civil infrastructure due to natural disasters can cause casualties as well as social and economic losses. Fragility analysis is an effective tool to help better understand the vulnerability of a structure to possible extreme events, such as earthquakes and floods. In particular, flood-induced failures of bridges are relatively common in Korea, because of the mountainous regions and summer concentrated rainfall. The main failure reasons during floods are reported to be debris impact and scour; however, research regarding debris impacts is considered challenging due to various uncertainties that affect the failure probability. This study introduces a fragility analysis methodology for evaluating the structural vulnerability due to debris impacts during floods. The proposed method describes how the essential components in fragility analysis are considered, including limit-state function, intensity measure of the debris impact, and finite element model. A numerical example of the proposed fragility analysis is presented using a bridge pier system under a debris impact.

• Journal of the Korea institute for structural maintenance and inspection
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• v.10 no.4
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• pp.135-144
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• 2006

In performing a risk analysis of structures under earthquakes, it is imperative to identify the vulnerability of structures associated with various damage stages considering structural properties, soil-structure interactions, site condition, and so on. In this paper, the method to derive a representative fragility curve of seismic isolated LRB(lead rubber bearing) bridges is proposed. In which, the curve is assumed log-normally distribution with two parameters. The risk analysis of seismic isolated LRB bridges considering earthquake effects such as PGA, PGV, SA, SV, and SI is also performed to assure the earthquake resisting capability of the structures. An practical way for constructing the representative fragility curves is also recommended combining fragility curves of structures.

• Journal of the Korean Geotechnical Society
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• v.37 no.10
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• pp.41-54
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• 2021

In this study, probabilistic steady seepage behavior of soil foundation beneath water retaining structures according to the location of cutoffs was studied. A Monte Carlo Simulation based on the random finite element method that considers the uncertainty and spatial variability of soil permeability was performed to evaluate the probabilistic seepage behavior. Fragility curves were developed by calculating the failure probability conditional on the occurrence of a given water level from the probability distribution obtained from Monte Carlo simulations. The fragility curve was prepared for the flow quantities such as flow rate through foundation soil, uplift force on the base of structure, and exit gradient in downstream to examine the reliability of the water retaining structure and the foundation soil. From the fragility curves, the effect of the location of cutoff wall on the reliability of water retaining structure and foundation soil according to the rise in water level was studied.

• Journal of the Korean Geotechnical Society
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• v.32 no.11
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• pp.31-42
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• 2016

Usually the seismic stability analysis of slope uses the pseudostatic analysis considering the inertial force by the earthquake as a static load. Geostructures such as slope include the uncertainty of soil properties. Therefore, it is necessary to consider probabilistic method for stability analysis. In this study, the probabilistic stability analysis of slope considering the uncertainty of soil properties has been performed. The fragility curve that represents the probability of exceeding limit state of slope as a function of the ground motion has been established. The Monte Carlo Simulation (MCS) has been implemented to perform the probabilistic stability analysis of slope with pseudostatic analysis. A procedure to develop the fragility curve by the pseudostatic horizontal acceleration has been presented by calculating the probability of failure based on the Artificial Neural Network (ANN) based response surface technique that reduces the required time of MCS. The results showed that the proposed method can get the fragility curve that is similar to the direct MCS-based fragility curve, and can be efficiently used to reduce the analysis time.

• Journal of the Society of Disaster Information
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• v.18 no.4
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• pp.899-907
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• 2022

Purpose: Although many studies on seismic fragility analysis of general bridges have been conducted using machine learning methods, studies on curved bridge structures are insignificant. Therefore, the purpose of this study is to analyze the seismic fragility of bridges with I-shaped curved girders based on the machine learning method considering the material property and geometric uncertainties. Method: Material properties and pier height were considered as uncertainty parameters. Parameters were sampled using the Latin hypercube technique and time history analysis was performed considering the seismic uncertainty. Machine learning data was created by applying artificial neural network and response surface analysis method to the original data. Finally, earthquake fragility analysis was performed using original data and learning data. Result: Parameters were sampled using the Latin hypercube technique, and a total of 160 time history analyzes were performed considering the uncertainty of the earthquake. The analysis result and the predicted value obtained through machine learning were compared, and the coefficient of determination was compared to compare the similarity between the two values. The coefficient of determination of the response surface method was 0.737, which was relatively similar to the observed value. The seismic fragility curve also showed that the predicted value through the response surface method was similar to the observed value. Conclusion: In this study, when the observed value through the finite element analysis and the predicted value through the machine learning method were compared, it was found that the response surface method predicted a result similar to the observed value. However, both machine learning methods were found to underestimate the observed values.

• 한국방재학회:학술대회논문집
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• 2011.02a
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• pp.185-185
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• 2011

기존 장대레일 궤도의 안정성 평가는 궤도 매개변수에 대하여 고정된 안전측의 값을 사용하는 결정론적인 해석에 의존해서 평가되어져 왔다. 그러나 실제현장의 궤도조건은 많은 영향인자들에 의해 그 특성이 불확실하게 변하고 있다. 따라서 온도하중에 의한 궤도 좌굴에 영향을 미치는 궤도 구성인자들의 불확실성 및 임의성을 보다 합리적으로 고려하기 위해서 확률론적 기법을 적용하는 것이 필수적이다. 본 연구에서는 기존 본 연구진에 의해 개발된 장대레일 궤도의 좌굴확률 평가시스템을 이용하여 좌굴 취약도 곡선을 나타내었으며, 궤도 좌굴에 영향을 미치는 주요변수 중 하나인 도상횡저항력에 대한 영향을 분석하였다. 좌굴확률 평가시스템에서는 장대레일 궤도의 좌굴확률을 산정하기 위하여 구조물의 안정과 파괴를 판단할 수 있는 기준을 한계상태방정식으로 표현하고, 이 한계상태방정식으로부터 확률론적 기법 중 하나인 AFOSM(Advanced First Order Second Moment) 방법을 이용하여 파괴확률의 간접적인 지표인 신뢰도지수(${\beta}$)를 통해 좌굴확률을 계산한다. 한계상태방정식에서 구조물의 강도(보유성능)에 해당하는 부분은 궤도의 허용좌굴온도이고, 하중(요구성능)에 해당하는 부분은 레일온도하중으로써 현재 레일온도와 중립온도의 차로 반영된다. 허용좌굴온도 산정에 고려되는 주요변수는 곡선반경(Radius), 도상횡저항력(Lateral Ballast Resista nce), 연직도상강성(Vertical Ballast Stiffness), 궤도 틀림량(Misalignment), 틀림길이(Half Wave Length), 열차운행속도(Velocity)이다. 각 확률변수들이 갖는 확률분포는 모두 정규분포로 가정하였다. 궤도의 기하학적 특성은 곡선반경 5,000m에 대해 고려하였으며, 열차는 KTX의 제원을 사용하여 정지된 상태에서 고려하였다. 틀림량과 틀림길이는 이에 대한 통계적 특성자료가 부족하여 확률변수로 고려하지 않고 결정론적 값으로 취급하였다. 레일온도의 통계적 특성치는 본 연구진에 의해 구축된 기후요소 및 레일온도 DB를 근거로 결정하였으며, 중립온도는 선로관리지침에 따라 $25{\pm}3^{\circ}C$를 기준으로 결정하였다. 또한 도상횡저항력은 실측 데이터를 참고로 하여 평균값에서 10%의 변동량을 갖는 것으로 보고 통계적 특성치를 결정하였다. 도상횡저항력이 좌굴확률에 미치는 영향을 매우 큰 것을 알 수 있었으며, 레일온도 $60^{\circ}C$일 때 도상횡저항력이 증가하면서 감소되는 좌굴확률이 도상저항력이 커질수록 그 감소량이 작아지는 것을 알 수 있었다.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.36 no.2
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• pp.59-66
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• 2018

This study examined the correlation among topography, forest type, soil and geology in Inje area where landslides occurred during heavy rainfall from July 11 to July 18, 2006 to assess the landslide susceptibility. In order to assess the susceptibility of future landslides, landslides occurred in Inje area were classified into slide type and flow type, and slope angle, aspect, curvature, ridge and valley were extracted from the area. The landslide susceptibility was assessed by applying diameter class, age class, density, and forest type to Bayesianbased LR (Logistic Regression) model and WOE (Weight of Evidence) model, and the fitness of modeling was verified by predict rate curve. As the results of susceptibility assessment, using all landslides without no distintion, it was found that 75% of the LR model and 73% of the WOE model were fit in terms of the top 20% of the landslides. According to slide type and flow type in the top 20% of the landslides, it was found that 71% of the LR model and 69% of the WOE model were fit in terms of the slide type. Whereas, it was found that 86% of the LR model and 82% of the WOE model were fit in terms of the flow type. That is, the results of the LR model showed higher fitness than the results of the WOE model, and the fitness of the flow type was higher than that of the slide type. Consequently, it suggests that it is reasonable to assess and verify the landslide susceptibility according to the types of landslides.

• Journal of the Korean Society of Hazard Mitigation
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• v.7 no.4
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• pp.1-12
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• 2007

A method for assessing fatigue vulnerability of steel bridge members considering corrosion and truck traffic variation with time is proposed to evaluate the reduction of fatigue strength in steel bridge members. A fatigue limit state function including corrosion and traffic variation effect is established. The interaction between the average corrosion depth and the fatigue strength reduction factor is applied to the limit state function as the reduction term of strength. Three types of truck traffic change is modeled for representing real traffic change trend. Monte-Carlo simulation method is used for reliability analysis which provides the data to obtain fatigue vulnerability curves. The estimation method proposed was verified by comparing with the results of reference study and applying to the steel bridges in service.