Infrastructure systems are crucial for the development of communities as they provide essential services to the habitants. To improve the resilience of such systems, their intrinsic properties need to be understood and their resilience state needs be identified. In the literature, several methods to evaluate networks’ reliability and resilience can be found. However, the applicability of these methods is restricted to small-size networks due to several computational limitations. In this paper, the case of large scale networks is tackled. The transportation network of a virtual city is considered as a case study. First, the road map of the city is transformed into an undirected graph. A random removal of the roads is applied until the network’s failure point is reached. The network reliability is then calculated using the Destruction Spectrum (D-spectrum) approach. A Monte Carlo approach has been developed to generate failure permutations, which are necessary for the evaluation of the D-spectrum set. In addition, the Birnbaum Importance Measure (BIM) has been adopted in this study to determine the importance of the network’s components. Due to the large size of the network, several computational problems have been faced. To solve the problems, two coding algorithms have been introduced in the paper to evaluate both the reliability and the BIM indexes for large scale networks. The analysis concept adopted in this study is applicable to all network-based systems such as water, gas, transportation, etc.

RELIABILITY AND COMPONENT VULNERABILITY ANALYSIS OF CITY-SCALE NETWORKS: APPLICATION TO THE TRANSPORTATION SYSTEM OF A VIRTUAL CITY / Kammouh, Omar; Cardoni, Alessandro; Kim, H. U.; Cimellaro, GIAN PAOLO. - (2017). ((Intervento presentato al convegno International Workshop on Performance-Based Seismic Design of Structures.

RELIABILITY AND COMPONENT VULNERABILITY ANALYSIS OF CITY-SCALE NETWORKS: APPLICATION TO THE TRANSPORTATION SYSTEM OF A VIRTUAL CITY

Omar Kammouh;alessandro Cardoni;Gian Paolo Cimellaro
2017

Abstract

Infrastructure systems are crucial for the development of communities as they provide essential services to the habitants. To improve the resilience of such systems, their intrinsic properties need to be understood and their resilience state needs be identified. In the literature, several methods to evaluate networks’ reliability and resilience can be found. However, the applicability of these methods is restricted to small-size networks due to several computational limitations. In this paper, the case of large scale networks is tackled. The transportation network of a virtual city is considered as a case study. First, the road map of the city is transformed into an undirected graph. A random removal of the roads is applied until the network’s failure point is reached. The network reliability is then calculated using the Destruction Spectrum (D-spectrum) approach. A Monte Carlo approach has been developed to generate failure permutations, which are necessary for the evaluation of the D-spectrum set. In addition, the Birnbaum Importance Measure (BIM) has been adopted in this study to determine the importance of the network’s components. Due to the large size of the network, several computational problems have been faced. To solve the problems, two coding algorithms have been introduced in the paper to evaluate both the reliability and the BIM indexes for large scale networks. The analysis concept adopted in this study is applicable to all network-based systems such as water, gas, transportation, etc.
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11583/2709984
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