• Earthquakes and Structures
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• v.22 no.6
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• pp.609-623
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• 2022

To study the empirical seismic fragility of a reinforced concrete girder bridge, based on the theory of numerical analysis and probability modelling, a regression fragility method of a rapid fragility prediction model (Gaussian first-order regression probability model) considering empirical seismic damage is proposed. A total of 1,069 reinforced concrete girder bridges of 22 highways were used to verify the model, and the vulnerability function, plane, surface and curve model of reinforced concrete girder bridges (simple supported girder bridges and continuous girder bridges) considering the number of samples in multiple intensity regions were established. The new empirical seismic damage probability matrix and curve models of observation frequency and damage exceeding probability are developed in multiple intensity regions. A comparative vulnerability analysis between simple supported girder bridges and continuous girder bridges is provided. Depending on the theory of the regional mean seismic damage index matrix model, the empirical seismic damage prediction probability matrix is embedded in the multidimensional mean seismic damage index matrix model, and the regional rapid prediction matrix and curve of reinforced concrete girder bridges, simple supported girder bridges and continuous girder bridges in multiple intensity regions based on mean seismic damage index parameters are developed. The established multidimensional group bridge vulnerability model can be used to quantify and predict the fragility of bridges in multiple intensity regions and the fragility assessment of regional group reinforced concrete girder bridges in the future.

• Computers and Concrete
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• v.32 no.3
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• pp.313-326
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• 2023

The seismic safety of the shear wall structure can be assessed through seismic fragility analysis, which requires high computational costs in estimating seismic demands. Accordingly, machine learning methods have been applied to such fragility analyses in recent years to reduce the numerical analysis cost, but it still remains a challenging task. Therefore, this study uses the ensemble machine learning method to present an improved framework for developing a more accurate seismic demand model than the existing ones. To this end, a rank-based selection method that enables determining an excellent model among several single machine learning models is presented. In addition, an index that can evaluate the degree of overfitting/underfitting of each model for the selection of an excellent single model is suggested. Furthermore, based on the selected single machine learning model, we propose a method to derive a more accurate ensemble model based on the bagging method. As a result, the seismic demand model for which the proposed framework is applied shows about 3-17% better prediction performance than the existing single machine learning models. Finally, the seismic fragility obtained from the proposed framework shows better accuracy than the existing fragility methods.

• Earthquakes and Structures
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• v.13 no.6
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• pp.599-611
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• 2017

This paper improves seismic fragility of a typical steel-concrete composite bridge with the deck-to-pier connection joint configuration at the concrete crossbeam (CCB). Based on the quasi-static test on a typical steel-concrete composite bridge model under the SEQBRI project, the damage states for both of the critical components, the CCB and the pier, are identified. The finite element model is developed, and calibrated using the experimental data to model the damage states of the CCB and the bridge pier as observed from the experiment of the test specimen. Then the component fragility curves for both of the CCB and the pier are derived and combined to develop the system fragility curves of the bridge. The uncertainty associated with the mean system fragility has been discussed and quantified. The study reveals that the CCB is more vulnerable than the pier for certain damage states and the typical steel-concrete composite bridge with CCB exhibits desirable seismic performance.

• Geomechanics and Engineering
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• v.36 no.3
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• pp.277-293
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• 2024

Shored Mechanically Stabilized Earth (SMSE) walls are types of soil retaining structures that increase soil stability under static and dynamic loads. The damage caused by an earthquake can be determined by evaluating the probabilistic seismic response of SMSE walls. This study aimed to assess the seismic performance of SMSE walls and provide fragility curves for evaluating failure levels. The generated fragility curves can help to improve the seismic performance of these walls through assessing and controlling variables like backfill surface settlement, lateral deformation of facing, and permanent relocation of the wall. A parametric study was performed based on a non-linear elastoplastic constitutive model known as the hardening soil model with small-strain stiffness, HSsmall. The analyses were conducted using PLAXIS 2D, a Finite Element Method (FEM) program, under plane-strain conditions to study the effect of the number of geogrid layers and the axial stiffness of geogrids on the performance of SMSE walls. In this study, three areas of damage (minor, moderate, and severe) were observed and, in all cases, the wall has not completely entered the stage of destruction. For the base model (Model A), at the highest ground acceleration coefficient (1 g), in the moderate damage state, the fragility probability was 76%. These values were 62%, and 54%, respectively, by increasing the number of geogrids (Model B) and increasing the geogrid stiffness (Model C). Meanwhile, the fragility values were 99%, 98%, and 97%, respectively in the case of minor damage. Notably, the probability of complete destruction was zero percent in all models.

• Proceedings of the Earthquake Engineering Society of Korea Conference
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• 2002.03a
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• pp.220-227
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• 2002

This study introduces the fragility analysis method for the safety evaluation of reinforced concrete pier subject to earthquake. Damage probability is calculated instead of the failure probability from definition of the damage state in the fragility curve. Not only the damage model determined by the response of structure subject to earthquake, but also the plastic-damage model which can represent the local damage is applied to fragility analysis. The evaluation method of damage state by damage variable in global structure is defined by this procedure. This study introduces the fragility analysis method considering the features of nonlinear time history behavior of reinforced concrete element and the plastic behavior of materials. At last, This study gives one of the approach method for seismic margin evaluation with the result of fragility analysis to design seismic load.

• Earthquakes and Structures
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• v.15 no.3
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• pp.253-261
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• 2018

This article details a bridge-specific fragility method developed to enhance the seismic design and resilience of bridges. Current seismic design processes provide guidance for the design of a bridge that will not collapse during a design hazard event. However, they do not provide performance information of the bridge at different hazard levels or due to design changes. Therefore, there is a need for a supplement to this design process that will provide statistical information on the performance of a bridge, beyond traditional emphases on collapse prevention. This article proposes a bridge-specific parameterized fragility method to enable efficient estimation of various levels of damage probability for alternative bridge design parameters. A multi-parameter demand model is developed to incorporate bridge design details directly in the fragility estimation. Monte Carlo simulation and Logistic regression are used to determine the fragility of the bridge or bridge component. The resulting parameterized fragility model offers a basis for a bridge-specific design tool to explore the influence of design parameter variation on the expected performance of a bridge. When used as part of the design process, these tools can help to transform a prescriptive approach into a more performance-based approach, efficiently providing probabilistic performance information about a new bridge design. An example of the method and resulting fragility estimation is presented.

• 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.

• Journal of the Earthquake Engineering Society of Korea
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• v.21 no.2
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• pp.87-93
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• 2017

Many studies are conducted in several fields for fragility analysis of structures or elements which is a probabilistic seismic safety analysis in consideration with uncertainty of seismic loading. It is hard to directly conduct fragility analysis for an infrastructure with social importance due to its size. Therefore, a fragility analysis for an infrastructure mainly conducted in element level or conducted with scaled model built in accordance with similarity law. In this article, fragility analysis for prototype and scaled model of reinforced concrete column was conducted with numerical models which had been updated by the results of shaking table test and pseudo dynamic test. As a result, response stress from the numerical analysis result of prototype model was higher than that from scaled model due to different stiffness ratios between steel and concrete. However, the probability of failure for scaled model was higher than that for prototype model because failure criteria for scaled model was down due to similarity law. Also it was evaluated that probability of failure by using log normal standard deviation of response stresses by spectrum matched accelerograms was more reliable than probability of failure by using existing coefficient of variation normally used.

• Structural Engineering and Mechanics
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• v.65 no.5
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• pp.633-644
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• 2018

This paper presents the results of an assessment of the seismic fragility of a long, curved multi-frame bridge under multi-support earthquake excitations. To achieve this aim, the numerical model of columns retrofitted with elliptical steel jackets was developed and validated using existing experimental results. A detailed nonlinear numerical model of the bridge that can capture the inelastic response of various components was then created. Using nonlinear time-history analyses for a set of stochastically generated spatially variable ground motions, component demands were derived and then convolved with new capacity-based limit state models to obtain seismic fragility curves. The comparison of failure probabilities obtained from uniform and multi-support excitation analyses revealed that the consideration of spatial variability significantly reduced the median value of fragility curves for most components except for the abutments. This observation indicates that the assumption of uniform motions may considerably underestimate seismic demands. Moreover, the spatial correlation of ground motions resulted in reduced dispersion of demand models that consequently decreased the dispersion of fragility curves for all components. Therefore, the spatial variability of ground motions needs to be considered for reliable assessment of the seismic performance of long multi-frame bridge structures.

• Nuclear Engineering and Technology
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• v.51 no.3
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• pp.894-903
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• 2019

An approach for collapse risk assessment is proposed to evaluate the vulnerability of electric cabinet in nuclear power plants. The lognormal approaches, namely maximum likelihood estimation and linear regression, are introduced to establish the fragility curves. These two fragility analyses are applied for the numerical models of cabinets considering various boundary conditions, which are expressed by representing restrained and anchored models at the base. The models have been built and verified using the system identification (SI) technique. The fundamental frequency of the electric cabinet is sensitive because of many attached devices. To bypass this complex problem, the average spectral acceleration $S_{\bar{a}}$ in the range of period that cover the first mode period is chosen as an intensity measure on the fragility function. The nonlinear time history analyses for cabinet are conducted using a suite of 40 ground motions. The obtained curves with different approaches are compared, and the variability of risk assessment is evaluated for restrained and anchored models. The fragility curves obtained for anchored model are found to be closer each other, compared to the fragility curves for restrained model. It is also found that the support boundary conditions played a significant role in acceleration response of cabinet.