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Common cause failures and cascading failures in technical systems: Similarities, differences and barriers
Published in Stein Haugen, Anne Barros, Coen van Gulijk, Trond Kongsvik, Jan Erik Vinnem, Safety and Reliability – Safe Societies in a Changing World, 2018
L. Xie, M.A. Lundteigen, Y.L. Liu
Cascading failure may be multiple failures, where initiated by the failure of one component in the system that results in a chain reaction, the so-called domino effect (Rausand and Øien, 1996). In power systems, cascading failure is referred to a sequence of dependent failures of individual components that successively weakens the systems (Baldick et al., 2008). It differs from the definition in infrastructures that limit the cascading failure to the propagation of failures between components (Rinaldi et al., 2001). Generally, we can find some same elements in the definitions that cascading failures are multiple failures initiated by one, and a sequential effect occurs.
Restoration and functionality assessment of a community subjected to tornado hazard
Published in Structure and Infrastructure Engineering, 2018
Hassan Masoomi, John W. van de Lindt
A community is a complex system that includes highly coupled networks. Any malfunction in a network or one or more of its components could result in a cascading failure, which, in turn, can cause a loss of functionality in all or part of the system. Therefore, in order to perform risk and resilience assessment at the community level, the topology of relevant community components needs to be modelled with enough dependencies and cross-dependencies included between components and networks to produce accurate results. The community considered in this study includes water and electric power networks in addition to buildings – specifically schools, residential buildings and industrial (business-related) structures. Each component in the water and electric power networks, as well as the school buildings, was modelled as a point within the topology of the community, and fragility curves for each component represent its intrinsic behaviour when subjected to a simulated tornado. However, residential and industrial buildings were only present in the model such that their location within the community allowed determination of the people affected from the functionality of the water network, electric power network and schools.
A resilience assessment of an interdependent multi-energy system with microgrids
Published in Sustainable and Resilient Infrastructure, 2021
Following a threat, hazard, or perturbation, various failures could be expected in MES. These failures have different impacts based on the failure pattern. Three most observable failure behaviors in MES are (Afrin et al., 2018): Cascading failures, which are known to have devastating damages. A cascading failure is often initiated by the partial or complete failure of one element, and the load is shifted to the neighboring elements in the system. The excess load from the failed element may cause overloading and eventual failure of the neighboring elements. Most cascading failures have a ripple effect. Cascading failures typically continue until all the elements in the system have failed or become disconnected.Random failures, which are failures occuring at no predefined time or condition. This type of failure does not necessarily have to be induced or triggered by another factor. A random failure has a property that it is known to happen, but not when it will happen. Thus, the occurrence of a random failure is typically said to follow the law of probability.Localized failures, which are failures that occur at a region or spot. This type of failure does not spread to another element in a system. A localized failure typically does not propagate immediately, unlike cascading failures. However, the impact of a localized failure may progressively degrade system performance over time, if not restored in a timely manner.
Changes in extreme events and the potential impacts on human health
Published in Journal of the Air & Waste Management Association, 2018
Jesse E. Bell, Claudia Langford Brown, Kathryn Conlon, Stephanie Herring, Kenneth E. Kunkel, Jay Lawrimore, George Luber, Carl Schreck, Adam Smith, Christopher Uejio
Extreme events can overburden or disrupt essential infrastructure access and functionality. Essential infrastructure includes public health facilities, transportation infrastructure such as roads and trains, energy grids, and water treatment. Depending on the severity and location of the extreme event, infrastructural systems can either act as a safeguard against excess health impacts or exacerbate potential health threats (Srinivasan, O’Fallon, and Dearry 2003). Disruptions of essential infrastructure can impede evacuation from hazardous areas, slow the delivery of essential health care, and add burden to individuals experiencing an extreme event (Deshmukh, Oh, and Hastak 2011; Skinner, Yantzi, and Rosenberg 2009). In addition, many infrastructure systems are reliant on one another, risking a cascading failure resulting from the disruption or failure of one system leading to the disruption of other interconnected systems (Bell et al. 2016). A commonly occurring cascading failure is when loss of electricity subsequently leads to failures in hospital facilities, public transportation, and water and sewage treatment systems (Klinger, Landeg, and Murray 2014). This was exemplified by the 2003 blackout related to a heat wave in the northeastern United States that led to failure of hospital emergency generators, untreated sewage, and food contamination from loss of refrigeration (Freese et al. 2006; Kile et al. 2005; Klein et al. 2007; Prezant et al. 2005), increasing the incidence of total mortality and gastrointestinal illnesses in New York City (Anderson and Bell 2012; Beatty et al. 2006; Lin et al. 2011). Although cascading failures can be local, it is important to understand that these failures can extend beyond the location of the extreme event to systems of the surrounding area.