Simulation‐Based Seismic Risk Assessment of Gas Distribution Networks

Abstract

The basic function of a gas distribution sys- tem, essentially composed of buried pipelines, reduc- tion stations, and demand nodes, is to deliver gas from sources to end users. The objective of the article is to discuss the evaluation of seismic risk of gas networks in compliance with the performance-based earthquake en- gineering framework adapted to spatially distributed sys- tems. In particular, three issues are addressed: (1) spatial seismic hazard characterization in terms of ground shak- ing and permanent ground deformation; (2) analysis of system’s vulnerability via fragility curves; (3) seismic per- formance evaluation via computer-aided simulation. As an application, the seismic risk analysis of L’Aquila (cen- tral Italy) gas distribution network, a 621-km mid- and low-pressure pipeline system was considered. The anal- yses were performed with reference to the mid-pressure part of the network, through an object-oriented software, specific for risk assessment of lifelines, developed by the authors. Results in terms of connectivity-based per- formance indicators are presented and discussed, along with a performance disaggregation analysis carried out to evaluate the contribution of the components of the sys- tem to the risk

Vulnerability Mitigation of Multiple Spatially Localized Attacks on Critical Infrastructure Systems

“…In the literature, scholars have studied CIS vulnerability under different types of disruptive events, including (1) random failures, which are modeled by randomly selecting a certain fraction of system components to make them fail (Motter and Lai, ; Crucitti et al., ; Albert et al., ; Yazdani and Jeffrey, ; Dobson et al., ; Ouyang and Dueñas‐Osorio, ; Carreras et al., ; Dobson et al., ; Ren and Dobson, ; Ouyang et al., ; Newman, ; Hong et al., ); (2) natural hazards, whose scenarios are simulated by hazard generation models (FEMA, ) and their impacts on system components are described by fragility curves (Dueñas‐Osorio et al., ; Adachi and Ellingwood, ; Esposito et al., ; Franchin and Cavalieri, ; Cavallaro et al., ; FEMA, ; Ouyang and Dueñas‐Osorio, ); (3) malicious attacks, which are simulated by removing important components (Hines et al., ; Holmgren, ; Rosas‐Casals et al., ; Holme et al., ; Bompard et al., ; Mishkovski et al., ; Zio et al., ; Alderson et al., ; Ouyang et al., ; Wang et al., ; Afshari Rad and Kakhki, ; Hasani and Khosrojerdi, ; Newell, ; Bogloee et al. ); and (4) some combinations of the above events (Levitin and Hausken, ; Levitin, ; Miller‐Hooks et al., ).…”

“…In the literature, scholars have studied CIS vulnerability under different types of disruptive events, including (1) random failures, which are modeled by randomly selecting a certain fraction of system components to make them fail (Motter and Lai, 2002;Crucitti et al, 2004;Albert et al, 2004;Yazdani and Jeffrey, 2011;Dobson et al, 2007;Carreras et al, 2004;Dobson et al, 2004;Ren and Dobson, 2008;Newman, 2003;Hong et al, 2017); (2) natural hazards, whose scenarios are simulated by hazard generation models (FEMA, 2015) and their impacts on system components are described by fragility curves (Dueñas-Osorio et al, 2007;Adachi and Ellingwood, 2008;Esposito et al, 2015;Franchin and Cavalieri, 2015;Cavallaro et al, 2014;FEMA, 2015;Ouyang and Dueñas-Osorio, 2014);…”

A compositional demand/supply framework to quantify the resilience of civil infrastructure systems (Re-CoDeS)

“…Systemic disaster risk evaluation of CISs has attracted continuous attention in the scientific literature in recent decades (e.g. Adachi & Ellingwood, 2008;Cavalieri, Franchin, Buritica Cortes, & Tesfamariam, 2014;Dueñas-Osorio & Rojo, 2011;Esposito et al, 2014;Jayaram & Baker, 2010;Mieler, Stojadinovic, Budnitz, Comerio, & Mahin, 2015;Pitilakis, Alexoudi, Argyroudis, Monge, & Martin, 2006;Reed, Powell, & Westerman, 2010;Song, Der Kiureghian, & Sackman, 2007;Wang, Au, & Fu, 2010).…”

A Spatial Network Model for Civil Infrastructure System Development

“…The downside to this is that our reliance on these systems is now so great that their disruption can lead to disproportionate consequences for the communities that rely on them (Bocchini et al, 2014;Cavalieri et al, 2014;Cavallaro et al, 2014;Duenas-Osorio and Rojo, 2011;Faturechi and Miller-Hooks, 2014;Wilkinson et al, 2013;Wilkinson et al, 2012a). Although it is well recognized that resilient networks are crucial to communities, the features of a resilient network are only partially understood (Argyroudis et al, 2015;Buldyrev et al, 2010;Esposito et al, 2015;Franchin and Cavalieri, 2015;Fu et al, 2014a;O'Rourke et al, 2005).…”