Decision Support System for smart urban management: resilience against natural phenomena and aerial environmental assessment

A new concept of Decision Support System (DSS) is presented. It is able to account for and support all phases of the risk analysis process: event forecast, prediction of reliable and accurate damage scenarios, estimate of their impact on Critical Infrastructures (CI), estimate of the possible consequences. It also provides an estimate of the consequences in terms of service degradation and of impact on citizens, on urban area and on production activities, essential for the mitigation of the adverse events. It can be used in two different modes, either in an operational mode (on a 24/7 basis) or in a simulation mode to produce risk analysis, setting up synthetic natural hazards and assessing the resulting chain of events (damages, impacts and consequences). Among the various possible external data sources an aerial, drone based one is presented. The system may capture both thermal and visual images of CI, processing them into 3D models or collect chemical pollutants concentrations for the monitoring of dangerous air quality due to catastrophic events such as volcano eruptions or large fires. The obtained models and the chemical data can be easily displayed within the framework of the DSS

Towards a Decision Support Tool for Assessing, Managing and Mitigating Seismic Risk of Electric Power Networks

Recent seismic event worldwide proved how fragile the electric power system can be to seismic events. Decision Support Systems (DSSs) could have a critical role in assessing the seismic risk of electric power networks and in enabling asset managers to test the effectiveness of alternative mitigation strategies and investments on resilience. This paper exemplifies the potentialities of CIPCast, a DSS recently created in the framework of the EU-funded project CIPRNet, to perform such tasks. CIPCast enables to perform risk assessment for Critical Infrastructures (CI) when subjected to different natural hazards, including earthquakes. An ad-hoc customization of CIPCast for the seismic risk analysis and management of electric power networks is featured in this paper. The international literature describes effective and sound efforts towards the creation of software platforms and frameworks for the assessment of seismic risk of electric power networks. None of them, unfortunately, achieved the goal of creating a user-friendly and ready available DDS to be used by asset managers, local authorities and civil protection departments. Towards that and building on the international literature, the paper describes metrics and methods to be integrated within CIPCast for assessing the earthquake-induced physical and functional impacts of the electric power network at component and system level. The paper describes also how CIPCast can inform the service restoration process