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, USA, 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 multidimensional
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 assessment by Monte Carlo analysis.
Positive correlations improve the reliability of the case study network, also predicted
from the 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 studies
