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

This paper presents a novel technique that jointly uses structural fragility analysis, network flow analysis, and random field theory to assess the correlation among damage levels of bridges in a transportation network under extreme events, and to estimate the sensitivity of network performance to the correlation distance. A stochastic computational framework for combining individual bridge damage due to extreme events with bridge network performance evaluation is introduced. Random field theory is used to simulate bridge damage so that its correlation can be directly controlled for parametric analysis. Two numerical examples with bridges in parallel and series configurations (e.g., under earthquakes) show that the correlation distance of the damage can strongly affect network performance indicators, indicating that correlation should be explicitly considered in network analyses under extreme events.

Paolo Bocchini, Dan M. Frangopol