Jayadipta Ghosh

Seismic Reliability Assessment of Aging Highway Bridge Networks with Field Instrumentation Data and Correlated Failures, II: Application

The bridge reliability in networks (BRAN) methodology introduced in the companion paper is applied to evaluate the reliability of part of the highway bridge network in South Carolina under a selected seismic scenario. The case study demonstrates Bayesian updating of deterioration parameters across bridges after spatial interpolation of data acquired from limited instrumented bridges. The updated deterioration parameters inform aging bridge seismic fragility curves through multi-dimensional integration of parameterized fragility models, which are utilized to derive bridge failure probabilities. The paper establishes the correlation structure among bridge failures from three information sources to generate realizations of bridge failures for network-level reliability assessments by Monte Carlo analysis. Positive correlations improve the reliability of the case study network, as predicted from network topology. The benefits of the BRAN methodology are highlighted in its applicability to large networks, while addressing some of the existing gaps in bridge network reliability and prioritization studies.

Bridge retrofit prioritisation for ageing transportation networks subject to seismic hazards

The deteriorating state of highway bridges is traditionally ignored in estimating the seismic reliability of transportation networks. In this study, the present day seismic reliability of ageing bridges in highway networks is evaluated through a time-dependent seismic fragility analysis of typical bridge classes. An efficient algorithm based on finite-state Markov Chain Monte Carlo simulations is also presented to assess the reliability of large ageing highway bridge networks without the need to simplify the network topology. The criticality of ageing bridges is then assessed through different proposed ranking strategies to arrive at an optimised seismic retrofit prioritisation. A case study on an existing bridge network with 515 bridges in the state of South Carolina, USA reveals striking differences between results of the proposed ranking strategies and those from state-of-the-practice methods. Such differences emphasise the significance of accounting for network-level importance in seismic retrofit programs of ageing transportation networks.

Effects of liquefiable soil and bridge modelling parameters on the seismic reliability of critical structural components

This study investigates the sensitivity of seismic fragility estimates for bridge components to variation in structural and liquefiable soil modelling parameters. A rigorous sensitivity analysis is conducted to evaluate the relative importance of 13 random variables that reflect uncertainty in the seismic performance assessment of bridges in regions with liquefiable soils. The results indicate that the fixed and expansion bearings and bent piles tend to be sensitive to the greatest number of modelling parameters for the case study system, while the abutments are less sensitive. The most significant modelling parameters affecting the seismic fragility include such parameters as undrained shear strength of soil, structural damping ratio, soil shear modulus, gap between deck and abutment, ultimate capacity of soil and fixed and expansion bearing coefficients of friction. The 5% and 95% confidence intervals reveal wide bounds on the seismic fragility curves, particularly for more vulnerable bridge components such as the piles or expansion bearings. The results offer insights to improve seismic reliability assessment in liquefaction susceptible regions and provide a basis for efficient bridge network reliability analyses. The findings guide future uncertainty treatment, management of computational resources and investment in refined modelling parameter estimates through field testing or other means.

Seismic Damage Accumulation in Highway Bridges in Earthquake-Prone Regions

Civil infrastructures, such as highway bridges, located in seismically active regions are often subjected to multiple earthquakes, including multiple main shocks during their service life or main shock–aftershock sequences. Repeated seismic events result in reduced structural capacity and may lead to bridge collapse, causing disruption in the normal functioning of transportation networks. This study proposes a framework to predict damage accumulation in structures subjected to multiple shock scenarios after developing damage index prediction models and accounting for the probabilistic nature of the hazard. The versatility of the proposed framework is demonstrated on a case-study highway bridge located in California for two distinct hazard scenarios: (1) multiple main shocks during the service life and (2) multiple aftershock earthquake occurrences following a single main shock. Results reveal that in both cases there is a significant increase in damage index exceedance probabilities due to repeated shocks within the time window of interest.

Influence of traffic loading on the seismic reliability assessment of highway bridge structures

Traditionally, the impacts of traffic and earthquake loading have been considered independently when assessing bridge reliability. This paper presents a framework for joint seismic and live-load fragility assessment of highway bridges. Full probabilistic analyses accounting for variation in bridge parameters, ground motion, and truck load and position are proposed to develop bridge system fragility curves and to identify the critical truck position that renders the bridge most vulnerable to earthquakes. A fragility surface is derived for the critical truck position at which the failure probability is conditioned on the governing vehicle weight in addition to ground motion intensity, thus depicting the impact of truck load on bridge seismic fragility. This fragility surface is convolved with the governing vehicle weight distribution (obtained from weigh-in-motion data) and probability of truck occurrence (function of truck flow rate) to determine traffic-informed conditional seismic reliability estimates. The proposed methodology is demonstrated on a case study of a multispan continuous steel girder bridge in the central and southeastern United States. The framework can find ready extensions to assess the joint impact of earthquake and live loads for other bridges and hazard conditions and can offer a basis for deriving reliability-based load combinations consistent with emerging trends in bridge design.

Life Cycle Performance Metrics for Aging and Seismically Vulnerable Bridges

Bridge infrastructure faces both continued aging and deterioration throughout its lifetime, as well as potential exposure to natural hazards such as earthquakes in hazard prone regions. Consequential damage requires increased monetary investments, energy spent on subsequent repair/replacement, as well as carbon dioxide (CO2) emissions associated with the manufacture/transport of repair materials. This paper will derive and compare estimates of three important metrics associated with the life cycle performance of aging bridges given seismic exposure, namely, life cycle cost, embodied energy and associated CO2 emissions. A case study is presented for a representative multi-span simply supported (MSSS) concrete girder bridge to evaluate the life cycle sustainability metrics of the corroded bridge system given uncertain performance and repair under lifetime exposure to seismic hazards. The results underscore the importance of capturing the effects of time dependent structural deterioration when conducting life cycle analysis of bridges based on different indicators. The proposed framework is also anticipated to help guide the selection of optimal rehabilitation or retrofit measures for bridge infrastructure based on target sustainability metrics related to life cycle cost, energy usage, and harmful emissions.

Sensitivity of Dynamic Response of Bridges under Multiple Hazards to Aging Parameters

Continued aging and deterioration of bridges poses a threat to bridge performance not only under regular service loads, but also results in pronounced vulnerability under extreme dynamic loads, such as seismic or hurricane induced surge and wave loading. In fact, aging of bridges in the form of corrosion attacks load paths critical under dynamic loads, including the superstructure-substructure connection elements and the reinforcing steel in column plastic hinge zones. This paper investigates the effect of aging on the dynamic response of multiple span concrete girder bridges when subjected to seismic as well as coupled surge and wave loading induced by hurricanes. The paper highlights the key differences and similarities in the nature of loads under the two natural hazards, the demand placed on key components, and the resulting dynamic response and failure modes of aging bridges. Nonlinear dynamic analysis is conducted using 3- dimensional bridge models with time-varying model parameters due to corrosion of reinforcing bars in decks and columns and degradation of elastomeric bearings with steel dowels. The sensitivity of component response, such as column demands, bearing deformations, or deck displacement, to variation in aging parameters is investigated in the study. Findings indicate that while the nonlinear dynamic behavior and select failure modes of the bridges may differ between the seismic and surge/wave loading cases, there is some consistency in the impact and criticality of aging parameters affecting dynamic response under the extreme loading cases, such as corrosion of bearing dowels and column reinforcement. These results form the foundation for multi-hazard vulnerability assessment of bridges considering the present in field condition.

Uncertainty propagation in seismic reliability evaluation of aging transportation networks

Uncertainty quantification is an integral part of many fields of science and engineering, but its application to seismic reliability and risk assessment in highway transportation networks is still in its infancy. This study identifies major known sources of uncertainties associated with seismic loss assessments in aging transportation networks, including hazards, structures, aging parameters, and network topology sources, while quantifying the impact of a subset of them on mean network-level reliability estimates. The uncertainty tracking process is illustrated with a case study network in South Carolina, USA. The source-to-response uncertainties are propagated and errors aggregated as they emerge with the adoption of surrogate seismic response models at both bridge and network levels. The observed range of uncertainties from the considered sources suggests that uncertainty quantification must become a standard procedure for reliability and risk assessment in transportation networks. Moreover, while the bridge surrogate models contribute significantly to overall uncertainties, network surrogate model’s contribution is found to be the least of all considered variables. Future opportunities exist to further identify key sources that should be targeted for improved confidence in risk estimates.