Probabilistic Connectivity Analysis for a Road Network Due To Seismically-Induced Disruptions

Abstract eng:
In the immediate aftermath of a strong earthquake, the road networks play a crucial role in rescue and recovery operations. The damaged infrastructure may lose their transitability (fully or partially) leading to disruption of road links. The consequences in most cases go beyond the disruption of the road links. In fact, the disruption of a road link often influences the connectivity of the whole network. The connectivity (the connection between two specific points) is used herein in order to measure the post-event health status of a road network and to highlight its critical points. Connectivity in its simplest form (from point A to point B) is used as an index of overall system performance. That is, the probability that the connectivity from point A to B is lost has been interpreted as a measure of system vulnerability (i.e., reduction in reliability). Moreover, the expected value of the number of alternative routes from point A to point B is a measure of system's redundancy or robustness. Defining the connectivity between two given points as a binary logical statement with logical values TRUE or FALSE, the network reliability is formulated as a standard link-set formulation. Such formulation, in the general case where the connectivity of the alternative routes are not independent cannot be easily solved; hence, a simulation based approach has been adopted. In this work the disruption cause considered is due to an earthquake event and the network connectivity problem has been solved in a fully simulation-based manner. For a given earthquake scenario, a seismic intensity field has been generated taken into account spatial correlations in the residuals of the adopted ground motion prediction equation. On the other hand, also the seismic capacity of the vulnerable infrastructure given seismic intensity for a transitability limit state is simulated based on a joint probability distribution (considering the spatial correlations in the vulnerability of the infrastructure) and based on simplified working assumptions. Therefore, for each simulation, the ratio of the number of connected routes to total number of alternative routes is calculated. This results in information such as, the probability of the loss of connectivity between points A and B and the probability distribution (and statistics such as the expected value and the standard deviation) for the number of connected routes. The entire methodology has been demonstrated as an application to a real case-study for the road network infrastructure in the Campania Region (Italy).

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