A stochastic computational framework for the joint transportation network fragility analysis and traffic flow distribution under extreme events

Abstract

This paper deals with a novel technique that jointly uses structural fragility analysis, network flow analysis, and random field theory to assess the correlation among the damage levels of bridges in a transportation network under extreme events, and to estimate the sensitivity of the network performance to the correlation distance. A stochastic computational framework for the combined use of the individual bridge damage level due to extreme events and the bridge network performance evaluation is presented. Random field theory is used to simulate the bridge damage level, so that it is possible to directly control its correlation and perform a parametric analysis. Two numerical examples that involve bridges in parallel and series configurations subject to extreme events (e.g. earthquakes) show that the correlation distance of the damage can strongly affect the network performance indicators. Therefore, this correlation should be taken into account for every analysis that involves the network performance assessment.