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Authors: Argyroudis, S* 
Selva, J.* 
Ghel, P* 
Pitilakis, K.* 
Title: Systemic seismic risk assessment of road networks in urban areas
Issue Date: 2015
Series/Report no.: 7/30(2015)
DOI: 10.1111/mice.12136
Keywords: Systemic vulnerability
Subject Classification04. Solid Earth::04.06. Seismology::04.06.11. Seismic risk 
Abstract: This article presents an integrated approach for the probabilistic systemic risk analysis of a road network considering spatial seismic hazard with correlation of ground motion intensities, vulnerability of the network components, and the effect of interactions within the network, as well as, between roadway components and built environment to the network functionality. The system performance is evaluated at the system level through a global connectivity performance indicator, which depends on both physical damages to its components and induced functionality losses due to interactions with other systems. An object-oriented modeling paradigm is used, where the complex problem of several interacting systems is decomposed in a number of interacting objects, accounting for intra- and interdependencies between and within systems. Each system is specified with its components, solving algorithms, performance indicators and interactions with other systems. The proposed approach is implemented for the analysis of the road network in the city of Thessaloniki (Greece) to demonstrate its applicability. In particular, the risk for the road network in the area is calculated, specifically focusing on the short-term impact of seismic events (just after the earthquake). The potential of road blockages due to collapses of adjacent buildings and overpass bridges is analyzed, trying to individuate possible criticalities related to specific components/subsystems. The application can be extended based on the proposed approach, to account for other interactions such as failure of pipelines beneath the road segments, collapse of adjacent electric poles, or malfunction of lighting and signaling systems due to damage in the electric power network.
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