Probabilistic study of cascading failures in complex interdependent lifeline systems

Hernandez-Fajardo, Isaac; Dueñas‐Osorio, Leonardo

doi:10.1016/j.ress.2012.10.012

Cited by 139 publications

(61 citation statements)

References 36 publications

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“…L i , where λ i > 1, is the tolerance parameter. Note that this model has been used in a complex network and power grid evaluation [5,8,9,25,[27][28][29].…”

Section: Introductionmentioning

confidence: 99%

System Reliability Evaluation in Water Distribution Networks with the Impact of Valves Experiencing Cascading Failures

Shuang

Liu

Tang

et al. 2017

Water

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Abstract:Water distribution networks (WDNs) represent a class of critical infrastructure networks. When a disaster occurs, component failures in a WDN may trigger system failures that result in larger-scale reactions. The aim of the paper is to evaluate the evolution of system reliability and failure propagation time for a WDN experiencing cascading failures, and find the critical pipes which may reduce system reliability dramatically. Multiple factors are considered in the method such as network topology, the balance of water supply and demand, demand multiplier, and pipe break isolation. The pipe-based attack with multiple failure scenarios is simulated in the paper. A case WDN is used to illustrate the method. The results show that the lowest capacity gets stronger when a WDN is short of supply, becoming the dominant factor that decides the evolution of system reliability and failure propagation time. The valve ratio (VR) and system reliability present a flattened S curve relationship, and there are two turning points in VR. The critical pipes can be identified. With the fixed 5% valves, a WDN can improve system reliability and resist cascading failures effectively. The findings provide insights into the system reliability and failure propagation time for WDNs experiencing cascading failures. It is proven to be useful in future studies focused on the operation and management of water services.

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“…L i , where λ i > 1, is the tolerance parameter. Note that this model has been used in a complex network and power grid evaluation [5,8,9,25,[27][28][29].…”

Section: Introductionmentioning

confidence: 99%

System Reliability Evaluation in Water Distribution Networks with the Impact of Valves Experiencing Cascading Failures

Shuang

Liu

Tang

et al. 2017

Water

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“…The test systems represent simplified yet realistic networks serving Shelby County, TN, USA. 38 The power network has 60 nodes and 121 links, while the water network has 49 nodes and 71 links. The description of the topologies and general properties of the interdependent networks is based on the work by Duenas-Osorio et al 39 Since the objective of this analysis is to showcase the application of our framework in seismic analyses, we consider component fragilities as depicted in Table 2.…”

Section: Case Study: Risk Of Interdependent Network Artificially Posmentioning

confidence: 99%

Decomposition algorithms for system reliability estimation with applications to interdependent lifeline networks

Paredes

Dueñas‐Osorio

Hernandez-Fajardo³

2018

Earthq Engng Struct Dyn

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Summary Reliability and risk assessment of lifeline systems call for efficient methods that integrate hazard and interdependencies. Such methods are computationally challenged when the probabilistic response of systems is tied to multiple events, as performance quantification requires a large catalog of ground motions. Available methods to address this issue use catalog reductions and importance sampling. However, besides comparisons against baseline Monte Carlo trials in select cases, there is no guarantee that such methods will perform or scale well in practice. This paper proposes a new efficient method for reliability assessment of interdependent lifeline systems, termed RAILS, that considers systemic performance and is particularly effective when dealing with large catalogs of events. RAILS uses the state‐space partition method to estimate systemic reliability with theoretical bounds and, for the first time, supports cyclic interdependencies among lifeline systems. Recycling computations across an entire seismic catalog with RAILS considerably reduces the number of system performance evaluations in seismic performance studies. Also, when performance estimate bounds are not tight, we adopt an importance and stratified sampling method that in our computational experiments is various orders of magnitude more efficient than crude Monte Carlo. We assess the efficiency of RAILS using synthetic networks and illustrate its application to quantify the seismic risk of realistic yet streamlined systems hypothetically located in the San Francisco Bay Region.

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“…Adapted from Hernandez-Fajardo and Duenas-Osorio, (32) the term cascading effects used throughout this article refers to the inoperability that occurs internally to a network, often induced by flow redistribution resulting from capacity exceedances, and the term interdependent effects refers to the inoperability that occurs external to the network as a result of a disruption to the network, often experienced in other infrastructure and industry sectors. This work integrates the resilience paradigm of Equation (2) with a risk-informed interdependency model to quantify the economic impact of a disruptive event on the interdependent industries that rely on the directly impacted and disrupted network.…”

Section: Model Of Interdependent Behaviormentioning

confidence: 99%

Inherent Costs and Interdependent Impacts of Infrastructure Network Resilience

et al. 2014

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Recent studies in system resilience have proposed metrics to understand the ability of systems to recover from a disruptive event, often offering a qualitative treatment of resilience. This work provides a quantitative treatment of resilience and focuses specifically on measuring resilience in infrastructure networks. Inherent cost metrics are introduced: loss of service cost and total network restoration cost. Further, "costs" of network resilience are often shared across multiple infrastructures and industries that rely upon those networks, particularly when such networks become inoperable in the face of disruptive events. As such, this work integrates the quantitative resilience approach with a model describing the regional, multi-industry impacts of a disruptive event to measure the interdependent impacts of network resilience. The approaches discussed in this article are deployed in a case study of an inland waterway transportation network, the Mississippi River Navigation System.

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Probabilistic study of cascading failures in complex interdependent lifeline systems

Cited by 139 publications

References 36 publications

System Reliability Evaluation in Water Distribution Networks with the Impact of Valves Experiencing Cascading Failures

System Reliability Evaluation in Water Distribution Networks with the Impact of Valves Experiencing Cascading Failures

Decomposition algorithms for system reliability estimation with applications to interdependent lifeline networks

Inherent Costs and Interdependent Impacts of Infrastructure Network Resilience

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