Seismic Fragility Curves for Un-Anchored On-Grade Steel Storage Tanks: Bayesian Approach

In this article, Bayesian approach is used for estimation of seismic fragility of un-anchored on‐grade steel storage tanks based on historical data and American Lifeline Alliance tanks database. The approach properly accounts for epistemic as well as aleatory uncertainties. The point and interval estimates of the fragility are formulated based on structural reliability method that implicitly or explicitly reflects the influence of epistemic uncertainty. The fragility curves developed herein are compared to corresponding relations currently available in the technical literature, the comparison suggest that actual tank performance is better than that predicted in the literature. Finally, application of fragilities in loss estimation methodology is investigated and showing a considerable scatter in the results corresponding to different fragilities.     

Bayesian Updating of Seismic Demand Models and Fragility Estimates for Reinforced Concrete Bridges with Two-Column Bents

Probabilistic models have been developed in a previous study by the authors to estimate the seismic deformation demands on structural components of reinforced concrete (RC) bridges with two-column bents. However, such models should be updated to reflect the latest laboratory of field data. Using a Bayesian approach, this article updates a currently available probabilistic model for the deformation demands of columns in bridges with two-column RC bents. The updated model incorporates information from newly available experimental data from shake table tests conducted based on a record of the 1994 Northridge Earthquake for a structural system with three bents with two columns per bent. The updated model is more accurate than the previous one in predicting the deformation demand of bridges with two-column RC bents and reduces the statistical uncertainty due to the addition of new data. As an application, fragility estimates for an example bridge are computed using the updated model both at the component (column) and system (bridge) levels.     

Analytical Fragility Curves for a Class of Horizontally Curved Box-Girder Bridges

Analytical fragility curves were developed for curved single-frame concrete box-girder bridges with seat-type abutments. The bridges incorporated the current seismic design considerations and modern details that were recently adopted by CALTRANS. Fragility curves demonstrated that columns were the most vulnerable components, while the modern seismic details successfully protected the abutment piles from damage during large earthquakes. Increasing the subtended angle affected the seismic vulnerability at both the component and system levels. Functional relationships were proposed to evaluate the seismic vulnerability of curved bridges. Moreover, fragility curve parameters were shown to depend on soil condition and spectral characteristics of ground motions.     

Regional Seismic Risk Assessment of Bridge Network in Charleston,South Carolina

This article presents the results of a seismic risk assessment of the bridge network in Charleston, South Carolina and the surrounding counties to support emergency planning efforts, and for prioritization of bridge retrofit. This study includes an inventory analysis of the approximately 375 bridges in the Charleston area, and convolution of the seismic hazard with fragility curves analytically derived for classes of bridges common to this part of the country. State-of-the-art bridge fragility curves and replacement cost estimates based on region-specific data are used to obtain economic loss estimates. The distribution of potential bridge damage and economic losses are evaluated for several scenario events in order to aid in the identification of emergency routes and assess areas for investment in retrofit. This article also evaluates the effect of uncertainty on the resulting predicted economic losses. The findings reveal that while the risk assessment is very sensitive to both the assumed fragility curves and damage ratios, the estimate of total expected economic losses is more sensitive to the vast differences in damage ratio models considered.     

The Impact of Flood-Induced Scour on Seismic Fragility Characteristics of Bridges

Earthquake in the presence of flood-induced scour is a critical multihazard scenario for bridges located in seismically-active, flood-prone regions. The present article evaluates seismic performance of four example reinforced concrete bridges when they are pre-exposed to regional flood hazards. Nonlinear time history analyses of the example bridges are performed for a suite of ground motion time histories in the presence and absence of scour expected from different intensity flood events. Fragility analysis is performed to develop seismic fragility curves of the example bridges for various scour depths. Results show nonlinear increase in bridge seismic fragility with increase in scour depth.     

Fragility-Based Performance Evaluation of Asymmetric Single-Story Buildings in Near Field and Far Field Earthquakes

Previous studies have shown that both distribution and intensity of response parameters in asymmetric buildings are dependent on their stiffnesses and strength distributions. The locations of centers of strength and rigidity relative to the center of mass provide suitable metrics for strength and stiffness distributions. In general, the proper locations of these centers are a function of earthquake ground motion characteristics and the level of building's nonlinear responses. In this article, using nonlinear response evaluation of single-story building models with a wide range of uncoupled torsional to lateral frequencies subjected to near field and far field earthquake excitations the proper location of building centers is studied . Diaphragm rotation, interstory drift, hinge plastic rotation, and ductility demand are selected as damage measure parameters. To compare the performance of models in each limit state, fragility representation of responses is used. It is concluded that proper configuration of building centers in a torsionally stiff building fundamentally depends on the chosen demand parameter. The proper configuration of centers in a torsionally stiff building for a specific demand parameter can converge the probability and distribution of related damages to those in the symmetric building counterpart. When the critical demand parameter for a case is identified, its corresponding arrangements of centers for a suitable seismic behavior may also be recognized. By rearranging the configuration of centers based on the attained configuration, the adverse effects of asymmetry can be avoided.     

Solution Strategies for Three Problems in Empirical Fragility Curve Derivation Using the Maximum Likelihood Method

Solution strategies are presented to address three potential problems in the empirical derivation of fragility functions from empirical data using the maximum likelihood method. The first strategy addresses the case of fragility curves that cross, the second strategy incorporates demand uncertainty in fragility derivation from post-earthquake reconnaissance data, and the third strategy provides a framework for the resolution of conflict between empirical data and expert opinions. The advantages and disadvantages of the proposed solution strategies are discussed and their use is demonstrated by way of suitable illustrative examples.     

A Simplified Drift-Based Assessment Procedure for Regular Confined Masonry Buildings in Seismic Regions

This article presents a simplified procedure for assessing the seismic performance of existing low-to-medium rise confined masonry (CM) buildings, which are a typical construction type in Latin-America. The procedure consists of the estimation of the peak roof and first-story inelastic drift demand of CM buildings. The expected peak inelastic displacement demand is related to drift-based fragility curves, which express the probability of being or exceeding two key damage states in the masonry panels, developed from a relatively large experimental database. The proposed procedure could be very useful for obtaining rapid estimates of expected performance during future earthquake events and for assessing the seismic vulnerability of regular confined masonry structures.     

FRAGILITY OF STANDARD INDUSTRIAL STRUCTURES BY A RESPONSE SURFACE BASED METHOD

National and international regulatory standards require industrial risk assessment, taking into account natural hazards including earthquakes, in the framework of Quantitative Risk Analysis (QRA). Seismic fragility analysis of industrial components may be carried out similarly as what has been done for buildings, even though some peculiar aspects require the development of specific tools. In the present paper a contribution to the definition of a rational procedure for seismic vulnerability assessment of standardised industrial constructions in a probabilistic framework is given. The method covers a range of components of the same structural type. Seismic reliability formulation for structures is used. Both seismic capacity and demand are considered probabilistic with the latter assessed by dynamic analyses. The application example refers to shell elephant foot buckling of unanchored sliding tanks. A regression-based method is applied to relate fragility curves to parameters varying in the domain of variables for structural design.     

Bayesian Estimation of Regional Production for CGE Modeling

Abstract Computable general equilibrium (CGE) models are often criticized for using restrictive functional forms and relying on external sources for parameter values in their calibration. CGE modelers argue that in many instances reliable econometric estimates of important model parameters are unavailable because they must be estimated using small numbers of time‐series observations. To address these criticisms, this paper uses a Bayesian approach to estimate the parameters of a translog production function in a regional computable general equilibrium model. Using priors from more reliable national estimates, and parameter restrictions required by neoclassical production theory, estimation is done by Markov chain Monte Carlo simulation. A stylized regional CGE model is then used to contrast policy responses of a Cobb‐Douglas specification with those from the estimated translog equation.     

Bayesian Spatial Filtering for Hedonic Models: An Application for the Real Estate Market

This article presents a Bayesian method based on spatial filtering to estimate hedonic models for dwelling prices with geographically varying coefficients. A Bayesian Adaptive Sampling algorithm for variable selection is used, which makes it possible to select the most appropriate filters for each hedonic coefficient. This approach explores the model space more systematically and takes into account the uncertainty associated with model estimation and selection processes. The methodology is illustrated with an application for the real estate market in the Spanish city of Zaragoza and with simulated data. In addition, an exhaustive comparison study with a set of alternatives strategies used in the literature is carried out. Our results show that the proposed Bayesian procedures are competitive in terms of prediction; more accurate results are obtained in the estimation of the regression coefficients of the model, and the multicollinearity problems associated with the estimation of the regression coefficients are solved.     

Comparison between the Seismic Performance of Integral and Jointed Concrete Bridges

This article presents a probabilistic fragility analysis for two groups of integral and jointed concrete bridges, with varying length and column height. The results show that the integral bridges perform consistently better from a seismic perspective than the jointed bridges. Comparisons are also drawn between the seismic fragility of different geometric configurations. The results show that for integral bridges, the seismic vulnerability increases with an increase in bridge length and decreases with an increase in column height. For the jointed bridge, it was found that geometric variation in column height and bridge length does not significantly affect its seismic vulnerability.     

FRAGILITY ASSESSMENT OF SLAB-COLUMN CONNECTIONS IN EXISTING NON-DUCTILE REINFORCED CONCRETE BUILDINGS

Fragility functions that estimate the probability of exceeding different levels of damage in slab-column connections of existing non-ductile reinforced concrete buildings subjected to earthquakes are presented. The proposed fragility functions are based on experimental data from 16 investigations conducted in the last 36 years that include a total of 82 specimens. Fragility functions corresponding to four damage states are presented as functions of the level of peak interstory drift imposed on the connection. For damage states involving punching shear failure and loss of vertical carrying capacity, the fragility functions are also a function of the vertical shear in the connection produced by gravity loads normalised by the nominal vertical shear strength in the absence of unbalanced moments. Two sources of uncertainty in the estimation of damage as a function of lateral deformation are studied and discussed. The first is the specimen-to-specimen variability of the drifts associated with a damage state, and the second the epistemic uncertainty arising from using small samples of experimental data and from interpreting the experimental results. For a given peak interstorey drift ratio, the proposed fragility curves permit the estimation of the probability of experiencing different levels of damage in slab-column connections.     

Probabilistic Performance Assessment of Retrofitted Skewed Multi Span Continuous Concrete I-girder Bridges

The unique dynamic response of skewed bridges causes them to experience more noticeable damage compared to straight bridges during seismic events. The effectiveness of different retrofit strategies on the fragility of skewed bridges can change with the skew angle. This article assesses the impact of skew angle and various retrofit strategies on the fragility of multi span continuous concrete I-girder bridges. The results indicate that the level of effectiveness of a retrofit strategy is highly dependent on the skew angle and damage state of interest and an appropriate retrofit strategy should be chosen based on the vulnerability of the components.     

ON THE ROLE OF ROAD NETWORKS IN REDUCING HUMAN LOSSES AFTER EARTHQUAKES

A road-network reliability analysis for a scenario seismic event is performed for a region of southern Italy characterised by a large number of small to medium municipalities quite close to each other and served by a dense network of roads. Among the many functions of the road network, whose links may fail after an earthquake due to the collapse of the bridges within them, the one selected for the present study is that of allowing rescue operations to be carried out at the sites of collapsed schools. For this to be possible, connection must be maintained between schools that survived, rescue centres and hospitals. Required elements for the study are the fragility curves of the bridges, the schools, the hospitals and the rescue centres. Output of the study is the expected value of the fraction of the total population in the area that is in need of assistance and cannot be hospitalised due to either failure of the network or other vulnerable components.     

Critical Assessment of Intensity Measures for Seismic Response of Italian RC Bridge Portfolios

The seismic assessment of a road network depends largely on the characterization of the fragility of its bridge components. The accuracy of bridge seismic demand estimates and the use of proper intensity measures (IM) will significantly influence such task. The available literature has mainly focused on buildings or a limited number of bridge configurations and IMs, which may not be representative for bridge portfolio assessment studies. In this paper, the correlation quality between a larger pool of traditional and innovative IMs and the nonlinear dynamic response of typical Italian RC bridges is investigated to identify the best-performing IMs.     

Seismic Reliability Assessment of a High-Voltage Disconnect Switch Using an Effective Fragility Analysis

This article deals with evaluation of the seismic vulnerability of a high-voltage vertical disconnect switch, one of the most vulnerable elements of electric substations. The main objective of the research is to evaluate the seismic fragility of the apparatus using a new effective method. By combining standard reliability methods for time-invariant problems with the response surface technique, this original procedure called “EFA” (Effective Fragility Analysis) permits the evaluation of fragility curves using a very limited number of numerical simulations. On the basis of experimental tests, to determine the mechanical characteristics of the disconnect switch components (ceramic, joints, etc.) the fragility curves of the equipment analyzed are carried out. The results are discussed and compared with the results of Monte Carlo simulations, which confirm the reliability of the procedure.     

LONG-TERM FORECASTING OF NONCOINTEGRATED AND COINTEGRATED REGIONAL AND NATIONAL MODELS*

ABSTRACT. Johansen's (1988) multivariate test for cointegration is first applied to four models involving quarterly state data and five variables, along with a national model based on Friedman and Kuttner's (1992) model of money demand, which uses three variables. Each regional model consists of frequently used national and state series, for which theory suggests the possible cointegration of several series pairs. Beginning with all five series, however, one state model is found to be cointegrated over each of 20 successive estimation intervals. The money demand model and one state model are not cointegrated over the same intervals. In the cointegrated case, five-year experimental forecasts show that error correction mechanism (ECM) and Bayesian ECM models outperform all other approaches. More importantly, forecasting performance improves further by respecifying the ECM model based on three cointegrated series pairs rather than the five-component cointegrating vector. For the two noncointegrated systems, the first-difference model suggested by the cointegration/ error correction literature is far superior to VAR in levels over both shortand long-term horizons.     

Sequential, Bayesian Geostatistics: A Principled Method for Large Data Sets

The principled statistical application of Gaussian random field models used in geostatistics has historically been limited to data sets of a small size. This limitation is imposed by the requirement to store and invert the covariance matrix of all the samples to obtain a predictive distribution at unsampled locations, or to use likelihood-based covariance estimation. Various ad hoc approaches to solve this problem have been adopted, such as selecting a neighborhood region and/or a small number of observations to use in the kriging process, but these have no sound theoretical basis and it is unclear what information is being lost. In this article, we present a Bayesian method for estimating the posterior mean and covariance structures of a Gaussian random field using a sequential estimation algorithm. By imposing sparsity in a well-defined framework, the algorithm retains a subset of " basis vectors " that best represent the " true " posterior Gaussian random field model in the relative entropy sense. This allows a principled treatment of Gaussian random field models on very large data sets. The method is particularly appropriate when the Gaussian random field model is regarded as a latent variable model, which may be nonlinearly related to the observations. We show the application of the sequential, sparse Bayesian estimation in Gaussian random field models and discuss its merits and drawbacks.     

Estimating the number of components in an OSL decay curve using the Bayesian Information Criterion

The optically stimulated luminescence (OSL) decay curve is assumed to consist of a number of first-order exponential components. Improper estimation of the number of components leads to under-or over-fitting of the curve under consideration. Hence, correct estimation of the number of components is important to accurately analyze an OSL decay curve. In this study, we investigated the possibility of using the Bayesian Information Criterion to estimate the optimal number of components in an OSL decay curve. We tested the reliability of this method using several hundred measured decay curves and three simulation scenarios. Our results demonstrate that the quality of the identification can be influenced by several factors: the measurement time and the number of channels; the variability of the decay constants; and the signal-to-noise ratios of a decaying component. The results also suggest that the Bayesian Information Criterion has great potential to estimate the number of components in an OSL decay curve with a moderate to high signal-to-noise ratio.