Abstract
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.
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