• Earthquakes and Structures
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• v.12 no.6
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• pp.653-663
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• 2017

A seismic margin assessment evaluates how much margin exists for the system under beyond design basis earthquake events. Specifically, the seismic margin for the entire system is evaluated by utilizing a systems analysis based on the sub-system and component seismic fragility data. Each seismic fragility curve is obtained by using empirical, experimental, and/or numerical simulation data. The systems analysis is generally performed by employing a fault tree analysis. However, the current practice has clear limitations in that it cannot deal with the uncertainties of basic components and accommodate the newly observed data. Therefore, in this paper, we present a Bayesian-based seismic margin assessment that is conducted using seismic fragility data and fault tree analysis including Bayesian inference. This proposed approach is first applied to the pooltype nuclear research reactor system for the quantitative evaluation of the seismic margin. The results show that the applied approach can allow updating by considering the newly available data/information at any level of the fault tree, and can identify critical scenarios modified due to new information. Also, given the seismic hazard information, this approach is further extended to the real-time risk evaluation. Thus, the proposed approach can finally be expected to solve the fundamental restrictions of the current method.

• 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.

• 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.

• Journal of the Korea institute for structural maintenance and inspection
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• v.24 no.5
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• pp.77-85
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• 2020

In this study, the seismic fragility curve according to the boundary conditions is created for a two-pylon concrete cable-stayed bridge, and the effect of the boundary conditions on the seismic fragility of the target bridge is evaluated. An analysis model for the target bridge is constructed using Midas Civil, and a nonlinear time history analysis is performed by applying the fiber element, concrete and rebar material models. The boundary conditions between the pylon and the stiffened girder are classified into four types: rigid, unconstrained, pot bearing, and seismic isolation bearing, and the seismic fragility curves are created for each boundary condition. The plastic hinge section of the pylon, the connection part, and the cable are selected as weak members, and the earthquake vulnerability curve is created for them. As a result of the analysis, it is found that the seismic isolation bearing model shows the lowest damage probability in the pylon and the connection part, and the seismic fragility of the cable is less affected by the boundary conditions than other members.

• Structural Engineering and Mechanics
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• v.63 no.1
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• pp.47-53
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• 2017

The fundamental goal of this study is to minimize the uncertainty of the median fragility curve and to assess the structural vulnerability under earthquake excitation. Bayesian Inference with Markov Chain Monte Carlo (MCMC) simulation has been presented for efficient collapse response assessment of the independent intake water tower. The intake tower is significantly used as a diversion type of the hydropower station for maintaining power plant, reservoir and spillway tunnel. Therefore, the seismic fragility assessment of the intake tower is a pivotal component for estimating total system risk of the reservoir. In this investigation, an asymmetrical independent slender reinforced concrete structure is considered. The Bayesian Inference method provides the flexibility to integrate the prior information of collapse response data with the numerical analysis results. The preliminary information of risk data can be obtained from various sources like experiments, existing studies, and simplified linear dynamic analysis or nonlinear static analysis. The conventional lognormal model is used for plotting the fragility curve using the data from time history simulation and nonlinear static pushover analysis respectively. The Bayesian Inference approach is applied for integrating the data from both analyses with the help of MCMC simulation. The method achieves meaningful improvement of uncertainty associated with the fragility curve, and provides significant statistical and computational efficiency.

• Earthquakes and Structures
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• v.19 no.2
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• pp.79-90
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• 2020

4- and 8-storey reinforced-concrete frame buildings are analyzed under the suites of the near-fault pulse-like, and the corresponding spectrally equivalent far-fault ground-motion records. Seismic fragility curves for the slight, moderate, extensive, and complete damage states are developed, and the damage probability matrices, and the mean loss ratios corresponding to the Design Basis Earthquake and the Maximum Considered Earthquake hazard levels are compared, for the investigated buildings and sets of ground-motion records. It is observed that the spectrally equivalent far-fault ground-motion records result in comparable estimates of the fragility curve parameters, as that of the near-fault pulse-like ground-motion records. As a result, the derived damage probability matrices and mean loss ratios using two suites of ground-motion records differ only marginally (of the order of ~10%) for the investigated levels of seismic hazard, thus, implying the potential for application of the spectrally equivalent ground-motion records, for seismic fragility and risk assessment at the near-fault sites.

• Earthquakes and Structures
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• v.15 no.6
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• pp.605-616
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• 2018

In this paper, an extended Cloud analysis method is developed for seismic fragility assessment of existing highway bridges in the southeast Queensland region. This method extends the original Cloud analysis dataset by performing scaled Cloud analyses. The original and scaled Cloud datasets are then paired to generate seismic fragility curves. The seismic hazard in this region is critically reviewed, and the ground motion records are selected for the time-history analysis based on various record selection criteria. A parametric highway bridge model is developed in the OpenSees analysis software, and a sampling technique is employed to quantify the uncertainties of highway bridges ubiquitous in this region. Technical recommendations are also given for the seismic performance evaluation of highway bridges in such low-to-moderate seismic zones. Finally, a probabilistic fragility study is conducted by performing a total of 8000 time-history analyses and representative bridge fragility curves are generated. It is illustrated that the seismic fragility curves generated by the proposed extended Cloud analysis method are in close agreement with those which are obtained by the rigorous incremental dynamic analysis method. Also, it reveals that more than 50% of highway bridges existing in southeast Queensland will be damaged subject to a peak ground acceleration of 0.14 g.

• Smart Structures and Systems
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• v.14 no.5
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• pp.847-867
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• 2014

There are continuous efforts to mitigate structural losses from earthquakes and manage risk through seismic risk assessment; seismic fragility curves are widely accepted as an essential tool of such efforts. Seismic fragility curves can be classified into four groups based on how they are derived: empirical, judgmental, analytical, and hybrid. Analytical fragility curves are the most widely used and can be further categorized into two subgroups, depending on whether an analytical function or simulation method is used. Although both methods have shown decent performances for many seismic fragility problems, they often oversimplify the given problems in reliability or structural analyses owing to their built-in assumptions. In this paper, a new method is proposed for the development of seismic fragility curves. Integration with sophisticated software packages for reliability analysis (FERUM) and structural analysis (ZEUS-NL) allows the new method to obtain more accurate seismic fragility curves for less computational cost. Because the proposed method performs reliability analysis using the first-order reliability method, it provides component probabilities as well as useful byproducts and allows further fragility analysis at the system level. The new method was applied to a numerical example of a 2D frame structure, and the results were compared with those by Monte Carlo simulation. The method was found to generate seismic fragility curves more accurately and efficiently. Also, the effect of system reliability analysis on the development of seismic fragility curves was investigated using the given numerical example and its necessity was discussed.

• Journal of the Korean Geotechnical Society
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• v.33 no.7
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• pp.29-41
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• 2017

There are uncertainties about the seismic load caused by seismic waves, which cannot be predicted due to the characteristics of the earthquake occurrence. Therefore, it is necessary to consider these uncertainties by probabilistic analysis. In this paper, procedures to develop a fragility curve that is a representative method to evaluate the safety of a structure by stochastic analysis were proposed for cut slopes. Fragility curve that considers uncertainties of soil shear strength parameters was prepared by Monte Carlo Simulation using pseudo static analysis. The fragility curve considering the uncertainty of the input ground motion was developed by performing time-history seismic analysis using selected 30 real ground input motions and the Newmark type displacement evaluation analysis. Fragility curves are represented as the cumulative probability distribution function with lognormal distribution by using the maximum likelihood estimation method.

• Proceedings of the Earthquake Engineering Society of Korea Conference
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• 2006.03a
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• pp.261-268
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• 2006

This study represents results of fragility curve development for 3-span continuous bridge. To research the response of bridge under earthquake excitation, Monte Carlo simulation is performed to study nonlinear dynamic analysis. Because of limited number of real time histories from the Korean peninsula, a set of 150 synthetic time histories were generated. Fragility corves in this study are represented by lognormal distribution functions with two parameters and developed as a function of PGA. Five damage states were defined to express the condition of damage based on the actual experimental damage data of bridge column. As a result of this research, the value of damage probability corresponding to each damage state were determined. This approach may be used in constructing the fragility curves for all of bridge structure and, by extension, in constructing the seismic hazard map.