ANALYSIS OF A NUCLEAR POWER PLANT FAILURE USING TEMPORAL NETWORKS

The recent thrust, from both the scientists and policy makers, to increase community resilience identifies lifelines as one of the most important field to intervene on. Lifelines are critical infrastructures which are highly interdependent to each other, and this interdependency can lead to cascading effects when a failure occurs. For this reason the interdependencies should be analyzed also taking into account the time effect. The aim of this paper is to introduce a suitable method for modeling the interdependencies of lifelines even in emergency situations, when the networks change over time. The methodology proposed relies on the Input-output Inoperability Model which has been modified according to the criteria of temporal networks. The critical infrastructures are modeled as graphs and the failure of the elements of the network propagates according to determined rules. Graphs are then interconnected in order to simulate the cascading effects. The Fukushima nuclear power plant disaster has been studied, as it is one of the most complete example of failure due to interdependencies and temporal effects. Results show that the developed methodology applied to a detailed model of the nuclear power plant is able to effectively describe the evolving situation. 1890 Available online at www.eccomasproceedia.org Eccomas Proceedia COMPDYN (2017) 1890-1903 © 2017 The Authors. Published by Eccomas Proceedia. Peer-review under responsibility of the organizing committee of COMPDYN 2017. doi: 10.7712/120117.5535.18284 Gian Paolo Cimellaro, Alessandro Cardoni, Stephen Mahin

[1]  Rae Zimmerman,et al.  Social Implications of Infrastructure Network Interactions , 2001 .

[2]  James P. Peerenboom,et al.  Identifying, understanding, and analyzing critical infrastructure interdependencies , 2001 .

[3]  James H. Lambert,et al.  Inoperability Input-Output Model for Interdependent Infrastructure Sectors. I: Theory and Methodology , 2005 .

[4]  Milos Manic,et al.  CIMS: A Framework for Infrastructure Interdependency Modeling and Analysis , 2006, Proceedings of the 2006 Winter Simulation Conference.

[5]  John E. Mitchell,et al.  Restoration of Services in Interdependent Infrastructure Systems: A Network Flows Approach , 2007, IEEE Transactions on Systems, Man, and Cybernetics, Part C (Applications and Reviews).

[6]  Jari Saramäki,et al.  Temporal Networks , 2011, Encyclopedia of Social Network Analysis and Mining.

[7]  Pengcheng Zhang,et al.  A generalized modeling framework to analyze interdependencies among infrastructure systems , 2011 .

[8]  Francesco Conte,et al.  Time-Varying Input-Output Inoperability Model , 2013 .

[9]  Vhance V. Valencia.  Network Interdependency Modeling for Risk Assessment on Built Infrastructure Systems , 2013 .

[10]  Min Ouyang,et al.  Review on modeling and simulation of interdependent critical infrastructure systems , 2014, Reliab. Eng. Syst. Saf..

[11]  Joost R. Santos,et al.  TIME-VARYING DISASTER RECOVERY MODEL FOR INTERDEPENDENT ECONOMIC SYSTEMS USING HYBRID INPUT–OUTPUT AND EVENT TREE ANALYSIS , 2014 .

[12]  Gian Paolo Cimellaro,et al.  Resilience-Based Design of Natural Gas Distribution Networks , 2015 .

[13]  G. Cimellaro,et al.  PEOPLES: A Framework for Evaluating Resilience , 2016 .

[14]  Gian Paolo Cimellaro,et al.  Urban Resilience for Emergency Response and Recovery: Fundamental Concepts and Applications , 2016 .

[15]  Ali Niknejad,et al.  A fuzzy dynamic inoperability input-output model for strategic risk management in global production networks , 2016 .