Comprehensive treatment of uncertainties in risk‐targeted performance‐based seismic design and assessment of bridges

Abstract

AbstractThis study complements and extends a recent work on the development of a rigorous framework for risk‐targeted performance‐based seismic design/assessment of ordinary standard bridges (OSBs) in California. Rooted in the formulation of this framework is an updated fully probabilistic performance‐based earthquake engineering (PBEE) assessment methodology wherein metrics of structural performance are formulated in terms of the mean return periods of exceedances for several strain‐based limit‐states (LSs). The originally proposed framework explicitly considering: (1) the uncertainty in the seismic input, and (2) the uncertainty in the capacity of the various LSs, is extended in this study to account for the following additional pertinent sources of uncertainty: (i) the aleatory uncertainty associated with finite element (FE) model parameters, and (ii) the epistemic parameter estimation uncertainty associated with using finite datasets to estimate the parameters of the probability distributions characterizing the FE model parameters and LS fragilities. These additional sources of uncertainty are commonly omitted or neglected in PBEE often by invoking that the earthquake ground motion uncertainty is the predominant source of uncertainty. However, their inclusion and consistent propagation in seismic performance‐based assessment of OSBs is imperative to obtain a more complete picture of seismic performance, thereby leading to a more comprehensive, transparent, and reliable design of these simple, yet essential bridges which represent an integral part of lifeline infrastructure systems especially in earthquake‐prone regions. The analytical and computational framework previously assembled is extended via modular incorporation of these additional sources of uncertainty. Four OSB testbeds and their risk‐targeted re‐designed versions are analyzed with and without these additional sources of uncertainty to evaluate their significance.