• Proceedings of the Korea Concrete Institute Conference
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• 2006.05a
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• pp.334-337
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• 2006

Generally, fragility curve has been used in predicting failure of structures due to seismic actions. In this research, the method of drawing fragility curve has been applied to evaluating success/failure of structures and satisfactory/unsatisfactory of concrete mixture performance based on material parameters. In the paper, a detailed explanation of the procedure of drawing fragility curve based on material parameter has been introduced. Fragility curve generating procedure includes generation of virtual data points from limited number of actual data points by bell curve implementation, determination of success/failure status of each data point by assigned criterion, and completion of final fragility curve. For practical applications, workability of concrete mixture content based on "unit water" has been used to obtain fragility curve. Detailed explanation of fragility curve drawing procedure for material parameters is presented.

• Geomechanics and Engineering
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• v.21 no.2
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• pp.179-186
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• 2020

Investigating damage potential of the railway infrastructure requires either large amount of case histories or in-depth numerical analyses, or both for which large amounts of effort and time are necessary to accomplish thoroughly. Rather than performing comprehensive studies for each damage case, in this study we collect and analyze a case history of the high-speed railway system damaged by the 2004 M6.6 Niigata Chuetsu earthquake for the development of the seismic fragility curve. The development processes are: 1) slice the railway system as 200 m segments and assigned damage levels and intensity measures (IMs) to each segment; 2) calculate probability of damage for a given IM; 3) estimate fragility curves using the maximum likelihood estimation regression method. Among IMs considered for fragility curves, spectral acceleration at 3 second period has the most prediction power for the probability of damage occurrence. Also, viaduct-type structure provides less scattered probability data points resulting in the best-fitted fragility curve, but for the tunnel-type structure data are poorly scattered for which fragility curve fitted is not meaningful. For validation purpose fragility curves developed are applied to the 2016 M7.0 Kumamoto earthquake case history by which another high-speed railway system was damaged. The number of actual damaged segments by the 2016 event is 25, and the number of equivalent damaged segments predicted using fragility curve is 22.21. Both numbers are very similar indicating that the developed fragility curve fits well to the Kumamoto region. Comparing with railway fragility curves from HAZUS, we found that HAZUS fragility curves are more conservative.

• Proceedings of the Earthquake Engineering Society of Korea Conference
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• 2005.03a
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• pp.161-168
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• 2005

Torsional behavior of eccentric structure under seismic loading may cause the stress and/or deformation concentration. Hence it is hard to estimate the seismic behavior of the structure with plan irregularity. This study suggests the method to setup the seismic fragility curve of the torsionally irregular structures. The suggested fragility curve may be acquired from the fragility surface defined on the D-R plan according to the estimated torsional behavior. The torsional behavior is predicted considering the inelastic region by adapting the inelastic stiffness of each wall. Finally the system displacement is converted to the spectral acceleration and the fragility curve for the seismic excitation level is presented. In addition, the fragility curve considering the excitation direction is proposed.

• Proceedings of the Korea Concrete Institute Conference
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• 2006.11a
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• pp.101-104
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• 2006

In the past study, the fragility curve for the evaluation of earthquake resistance and earthquake-related damage of concrete bearing wall structures were studied. The fragility curve represents the probability of being in or exceeding a given damage state such as Slight, Moderate, Extensive or Complete structural damage state, and is defined as a cumulative lognormal distribution. Each fragility curve is characterized by median and lognormal standard deviation values. We performed parametric pushover analysis for typical 12 and 24 stories apartment buildings. Based on the results, the fragility curves of concrete wall structures were standardized. Using the fragility curve, engineers can directly evaluate the probability of a damage state to a spectral displacement of interest.

• Earthquakes and Structures
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• v.17 no.1
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• pp.91-99
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• 2019

Fragility analysis is an effective tool that is frequently used for seismic risk assessment of bridges. There are three different approaches to derive a fragility curve: experimental, empirical and analytical. Both experimental and empirical methods to derive fragility curve are based on past earthquake reports and expert opinions which are not suitable for all bridges. Therefore, analytical fragility analysis becomes important. Nonlinear time history analysis is commonly used which is the most reliable method for determining probabilistic demand models. In this study, to determine the probabilistic demand models of bridges, time history analyses were performed considering both material and geometrical nonlinearities. Serviceability limit states for three different service velocities were considered as a performance goal. Also, support displacements, component yielding and collapse limits were taken into account. Both serviceability and component fragility were derived by using maximum likely hood methods. Finally, the seismic performance and critical members of the bridge were probabilistically determined and clearly presented.

• Journal of the Earthquake Engineering Society of Korea
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• v.25 no.6
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• pp.267-274
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• 2021

Seismic fragility analysis of a structure is generally performed for the expected critical component of a structure. The seismic fragility analysis assumes that all the components behave independently in a structural system. A bridge system consists of many inter-connected components. Thus, for an accurate evaluation of the seismic fragility of a bridge, the seismic fragility analysis requires the composition of probabilities considering the correlation between structural components. This study presented a procedure to obtain the seismic fragility curve of a bridge system, considering the correlation between bridge components. Seismic fragility analysis was performed on a PSC bridge that is considered as the central infrastructure. The analysis results showed that the probability of the seismic fragility curve of the bridge system was higher than that of each bridge component.

• Journal of the Korean Geotechnical Society
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• v.38 no.11
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• pp.19-30
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• 2022

Developing a fragility curve for the levee requires calculating the probability of failure according to the water level for each failure mode. Since probabilistic analysis requires iterative analysis to account for variability in geotechnical parameters, the fragility curve development inevitably requires many iterative calculations. Therefore, approximate probabilistic analysis techniques are usually applied to reduce the amount of calculation in developing the levee fragility curve. However, their accuracy has not been determined clearly. This study calculated the failure probability of slope and piping failure mode for an actual levee through probabilistic methods, such as FOSM, PEM, and MCS. Then, the fragility curve of the levee according to the water level was developed. The results of the approximate methods: FOSM and PEM, were compared with those of MCS to evaluate the applicability to the fragility curve for slope and piping failure mode.

• Journal of the Earthquake Engineering Society of Korea
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• v.15 no.4
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• pp.1-12
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• 2011

Seismic fragility analysis has been developed to evaluate the seismic performance of existing nuclear power plants, but now its applicability has been extended to buildings and bridges. In general, the seismic fragility curves are evaluated from the nonlinear time-history analysis (THA) using many earthquake ground motions. Seismic fragility analysis using the nonlinear THA requires a time consuming process of structural modeling and analysis. To overcome this shortcoming of the nonlinear THA, simplified methods such as the displacement coefficient method (DCM) and the capacity spectrum method (CSM) are used for the seismic fragility analysis. In order to evaluate the accuracy of the seismic fragility curve calculated by the DCM and the CSM, the seismic fragility curves of a reinforced concrete shear wall structure calculated by the DCM and CSM are compared with those calculated by the nonlinear THA. In order to construct a numerical fragility curve, 190 artificially generated ground motions corresponding to the design spectrum and the methodology proposed by Shinozuka et al. are used.

• Journal of the Earthquake Engineering Society of Korea
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• v.27 no.5
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• pp.213-220
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• 2023

Seismic fragility curves play a crucial role in assessing potential seismic losses and predicting structural damage caused by earthquakes. This study compares non-sampling-based methods of seismic fragility curve derivation, particularly the probabilistic seismic demand model (PSDM) and finite element reliability analysis (FERA), both of which require employing sophisticated finite element analysis to evaluate and predict structural damage caused by earthquakes. In this study, a three-dimensional finite element model of API 5L X65, a buried gas pipeline widely used in Korea, is constructed to derive seismic fragility curves. Its seismic vulnerability is assessed using nonlinear time-history analysis. PSDM and a FERA are employed to derive seismic fragility curves for comparison purposes, and the results are verified through a comparison with those from the Monte Carlo Simulation (MCS). It is observed that the fragility curves obtained from PSDM are relatively conservative, which is attributed to the assumption introduced to consider the uncertainty factors. In addition, this study provides a comprehensive comparison of seismic fragility curve derivation methods based on sophisticated finite element analysis, which may contribute to developing more accurate and efficient seismic fragility analysis.

• Structural Engineering and Mechanics
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• v.69 no.3
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• pp.317-326
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• 2019

This research aims to assess the tight seismic risk curve of the intake tower at Geumgwang reservoir by considering the recorded historical earthquake data in the Korean Peninsula. The seismic fragility, a significant part of risk assessment, is updated by using Bayesian inference to consider the uncertainties and computational efficiency. The reservoir is one of the largest reservoirs in Korea for the supply of agricultural water. The intake tower controls the release of water from the reservoir. The seismic risk assessment of the intake tower plays an important role in the risk management of the reservoir. Site-specific seismic hazard is computed based on the four different seismic source maps of Korea. Probabilistic Seismic Hazard Analysis (PSHA) method is used to estimate the annual exceedance rate of hazard for corresponding Peak Ground Acceleration (PGA). Hazard deaggregation is shown at two customary hazard levels. Multiple dynamic analyses and a nonlinear static pushover analysis are performed for deriving fragility parameters. Thereafter, Bayesian inference with Markov Chain Monte Carlo (MCMC) is used to update the fragility parameters by integrating the results of the analyses. This study proves to reduce the uncertainties associated with fragility and risk curve, and to increase significant statistical and computational efficiency. The range of seismic risk curve of the intake tower is extracted for the reservoir site by considering four different source models and updated fragility function, which can be effectively used for the risk management and mitigation of reservoir.