• 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.

• Proceedings of the Earthquake Engineering Society of Korea Conference
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• 2003.09a
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• pp.334-343
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• 2003

본 논문의 목적은 스팅베어링의 기존교량과 납-고무베어링(Lead-Rubber Bearing)으로 내진 보강된 교량에 대해서 갭(Gap)의 크기가 교량의 지진 취약도에 미치는 영향에 대해서 평가하였다. 이를 위해서 다경간 단순교(Multi-Span Simply Supported Bridge)와 다경간 연속교(Muti-Span Continuous Bridge)를 대상으로 취약도 분석을 실시하였다 또한 다양한 크기의 갭사이즈를 도입하여 해석을 실시하였다. 이를 통해서 갭사이즈의 변화가 각 교량의 구성품에 미치는 영향을 확률적으로 평가할 수 있었고, 합성된 취약도 곡선을 이용하여 최적의 갭사이즈를 확정할 수 있었다.

• Proceedings of the Computational Structural Engineering Institute Conference
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• 2009.04a
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• pp.383-386
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• 2009

본 연구는 HAZUS에서 제시하고 있는 비보강 조적조 건축물의 구조적 손상상태에 대한 지진취약도함수와 관련하여 층간변위율 및 스펙트럼 변위 등의 매개변수를 평가하고 또한 국내 상황에 적합한 기존 비보강 조적조 건축물의 지진취약도곡선의 도출을 목적으로 하였다. 국내 상황을 고려한 지진피해를 추정하기 위하여 먼저 기존 비보강 조적조 건축물의 현황파악 및 지진취약도함수 산출방법을 분석하였다. 일반적으로 HAZUS에서 제시하고 있는 지진취약도함수는 역량스펙트럼을 변환시킨 가속도-변위응답 스펙트럼법을 기본적으로 사용하는 상황으로 국내 기존 비보강 조적조 건축물에 대한 지진취약도함수 개발을 위하여 Midas GEN Ver.741 구조해석프로그램을 사용하여 실제 23개동의 비보강 조적조 건축물을 대상으로 역량스펙트럼 해석을 수행하였다. 연구결과를 통하여 지진취약도함수의 주요 매개변수인 손상상태별 층간변위율 및 스펙트럼 변위를 제시하였다.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.38 no.5
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• pp.635-643
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• 2018

In the present study, influence of earthquake intensity range on seismic fragility analysis of a RC bridge has been evaluated. For this purpose, a RC bridge damaged by a past earthquake has been selected, and analytical model of the bridge has been developed for nonlinear dynamic time-history analysis. A total of 25 recorded earthquake motions have been employed for the nonlinear analysis from which maximum lateral drift ratio of piers are obtained. Then, seismic fragility analysis has been conducted for the bridge using the nonlinear analysis results. Probability of exceeding damage has been computed in terms of using the maximum likelihood estimation, and effect of earthquake intensity range of the motions on seismic fragility curves has been assessed analytically. Analytical predictions indicate that the earthquake intensity range is of utmost significance for rationale seismic fragility analysis reflecting a physical damage state of a bridge and seismic performance evaluation of such bridge.

• Journal of Korean Tunnelling and Underground Space Association
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• v.19 no.2
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• pp.143-159
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• 2017

A probabilistic fragility assessment procedure is developed in this paper to predict risks of damage arising from seismic loading to the two-cell RC box tunnel. Especially, the paper focuses on establishing a simplified methodology to derive fragility curves which are an indispensable ingredient of seismic fragility assessment. In consideration of soil-structure interaction (SSI) effect, the ground response acceleration method for buried structure (GRAMBS) is used in the proposed approach to estimate the dynamic response behavior of the structures. In addition, the damage states of tunnels are identified by conducting the pushover analyses and Latin Hypercube sampling (LHS) technique is employed to consider the uncertainties associated with design variables. To illustrate the concepts described, a numerical analysis is conducted and fragility curves are developed for a large set of artificially generated ground motions satisfying a design spectrum. The seismic fragility curves are represented by two-parameter lognormal distribution function and its two parameters, namely the median and log-standard deviation, are estimated using the maximum likelihood estimates (MLE) method.

• Journal of the Korea Concrete Institute
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• v.19 no.1
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• pp.91-102
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• 2007

Through lessons in recent earthquakes, the bridge engineering community recognizes the need for new seismic design methodologies based on the inelastic structural performance of RC bridge structures. This study represents results of performance-based fragility analysis of reinforced concrete (RC) bridge. Monte carlo simulation is performed to study nonlinear dynamic responses of RC bridge. Two-parameter log-normal distribution function is used to represent the fragility curves. These two-parameters, referred to as fragility parameters, are estimated by the traditional maximum likelihood procedure, which is treated each event of RC bridge pier damage as a realization of Bernoulli experiment. In order to formulate the fragility curves, five different damage states are described by two practical factors: the displacement and curvature ductility, which are mostly influencing on the seismic behavior of RC bridge piers. Five damage states are quantitatively assessed in terms of these seismic ductilities on the basis of numerous experimental results of RC bridge piers. Thereby, the performance-based fragility curves of RC bridge pier are provided in this paper. This approach can be used in constructing the fragility curves of various bridge structures and be applied to construct the seismic hazard map.

• Journal of Korean Tunnelling and Underground Space Association
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• v.25 no.3
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• pp.187-200
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• 2023

This study analyzed the seismic fragility of bored tunnels based on their surrounding conditions and suggested a representative seismic fragility model. By analyzing the existed seismic fragility models developed for bored tunnels, we developed weighted combination models for each surrounding conditions, such as ground conditions and depth of the tunnel. The seismic fragility curves use the peak ground acceleration (PGA) as a parameter. When the PGA was 0.3 g, the probability of damage exceeding minor or slight damage was 20% for depth of 50 m or less, 10% for depth between 50 m and 100 m, and 3% for depth of 100 m or more. It was also found that the probability of damage was higher for the same PGA and depth when the surrounding ground was rock rather than soil. The probability of damage decreases as the depth increase. This study is expected to be used for developing a comprehensive seismic fragility function for tunnels in the future.

• 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.

• Journal of the Earthquake Engineering Society of Korea
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• v.7 no.2
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• pp.93-102
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• 2003

A technique for the seismic reliability evaluation of electric power transmission network system(EPTS) was developed to evaluate reliability indices corresponding to the whole network system and to each node within. A network model with nodes and links for EPTS was established, and a seismic substation fragility curve obtained from seismic fragilities of power system facilities was derived. A point source model, the doubly truncated Gutenberg-Richter relationship, and earthquake intensity attenuation formula was applied to simulate seismic events. Using Monte-Carlo simulation method, the seismic reliability of EPTS was evaluated and, it appeared that seismic effect on EPTS of korea has to be considered.

• 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.