Dependency effects between Critical Infrastructure (CI) elements represent key information needed to predict and analyze the impact of natural (or man-made) disturbances. The dependency links among CI elements and their associated weight are data whose availability is often complex to determine and are usually not available. Leveraging on several data supporting US and EU Directives for the Resilience and the Protection of CIs, the objective of the present work is to define a dependency network of elements of critical sectors extracted from available open-data. The resulting network is then studied in terms of its basic topological properties. The analysis of the network provides interesting clues about the properties and locations of critical points that can cause cascading failures. In addition, this information can form the basis for planning actions that mitigate the risk of cascading effects.
Modeling Networks of Interdependent Infrastructure in Complex Urban Environments Using Open-Data
Di Pietro A.;Rosato V.;
2024-01-01
Abstract
Dependency effects between Critical Infrastructure (CI) elements represent key information needed to predict and analyze the impact of natural (or man-made) disturbances. The dependency links among CI elements and their associated weight are data whose availability is often complex to determine and are usually not available. Leveraging on several data supporting US and EU Directives for the Resilience and the Protection of CIs, the objective of the present work is to define a dependency network of elements of critical sectors extracted from available open-data. The resulting network is then studied in terms of its basic topological properties. The analysis of the network provides interesting clues about the properties and locations of critical points that can cause cascading failures. In addition, this information can form the basis for planning actions that mitigate the risk of cascading effects.I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.

