Quantifying the resilience of an urban traffic-electric power coupled system

Fotouhi, Hossein; Moryadee, Seksun; Miller-Hooks, Elise

doi:10.1016/j.ress.2017.01.026

Cited by 91 publications

(35 citation statements)

References 21 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Interconnected networks: Fotouhi et al (2017), Kong and Simonovic (2019) community-country Bruneau et al (2003), Cimellaro et al (2016), Matthews et al (2014), Ayyub (2014), Franchin (2018), Zhang et al (2019) resilience metrics and criteria Gay and Sinha (2013), Ouyang and Wang (2015), Mebarki et al (2016), Hosseini et al (2016) The robustness to hazard actions is usually quantified through fragility functions, which give the probability of the asset exceeding defined limit states, e.g. serviceability and ultimate, for a given hazard intensity, e.g.…”

Section: Level Of Analysis Referencementioning

confidence: 99%

Resilience assessment framework for critical infrastructure in a multi-hazard environment: Case study on transport assets

Argyroudis

Mitoulis

Hofer

et al. 2020

Science of The Total Environment

201

View full text Add to dashboard Cite

The exposure of critical infrastructure to natural and human-induced hazards has severe consequences on world economies and societies. Therefore, resilience assessment of infrastructure assets to extreme events and sequences of diverse hazards is of paramount importance for maintaining their functionality. Yet, the resilience assessment commonly assumes single hazards and ignores alternative approaches and decisions in the restoration strategy. It has now been established that infrastructure owners and operators consider different factors in their restoration strategies depending on the available resources and their priorities, the importance of the asset and the level of damage. Currently, no integrated framework that accounts for the nature and sequence

show abstract

Section: Level Of Analysis Referencementioning

confidence: 99%

Resilience assessment framework for critical infrastructure in a multi-hazard environment: Case study on transport assets

Argyroudis

Mitoulis

Hofer

et al. 2020

Science of The Total Environment

201

View full text Add to dashboard Cite

show abstract

“…[15], [22], [24], [31]- [33], [47], [48]), and the value of services provided (e.g. [23], [36], [49]- [53]). In this paper, we use a performance measure based on the value of service provision because it has the following advantages: First, a value-based performance measure is most relevant from a societal perspective, as it captures the quantity and quality of services provided by infrastructure systems to meet a certain demand.…”

Section: Resilience Measuresmentioning

confidence: 99%

“…For instance, Holden et al [20] use a linear production function that defines the quantities of input resources required for the production of another good. Fotouhi et al [23] add delays to road links if traffic signals fail, depending on whether the junctions are subsequently unregulated or regulated manually by police officers. While such modelling techniques achieve tailor-made solutions to capture specific aspects of infrastructure systems, a more generic approach is needed that can represent the many different interactions between network flows and physical infrastructure assets.…”

Section: Introductionmentioning

confidence: 99%

“…Fotouhi et al [23] introduce constraints that a repair site must be accessible from a depot via the (potentially disrupted) road network and Sharkey et al [37] model dependencies between repair tasks with different types of precedence constraints. However, there exist further aspects of optimal repair resource deployment not captured in currently existing models, for example partial repair.…”

Section: Introductionmentioning

confidence: 99%

See 1 more Smart Citation

Resilience assessment for interdependent urban infrastructure systems using dynamic network flow models

Goldbeck

Angeloudis

Ochieng

2019

Reliability Engineering & System Safety

147

View full text Add to dashboard Cite

Critical infrastructure systems are becoming increasingly interdependent, which can exacerbate the impacts of disruptive events through cascading failures, hindered asset repairs and network congestion. Current resilience assessment methods fall short of fully capturing such interdependency effects as they tend to model asset reliability and network flows separately and often rely on static flow assignment methods. In this paper, we develop an integrated, dynamic modelling and simulation framework that combines network and asset representations of infrastructure systems and models the optimal response to disruptions using a rolling planning horizon. The framework considers dependencies pertaining to failure propagation, system-of-systems architecture and resources required for operating and repairing assets. Stochastic asset failure is captured by a scenario tree generation algorithm whereas the redistribution of network flows and the optimal deployment of repair resources are modelled using a minimum cost flow approach. A case study on London's metro and electric power networks shows how the proposed methodology can be used to assess the resilience of city-scale infrastructure systems to a local flooding incident and estimate the value of the resilience loss triangle for different levels of hazard exposure and repair capabilities.

show abstract

“…Fotouhi et al 2017). Additionally, new vulnerability data will improve knowledge on the cumulative effects of multiple hazards -important for disaster risk reduction measures.…”

mentioning

confidence: 99%

Framework for developing volcanic fragility and vulnerability functions for critical infrastructure

Wilson

Deligne

et al. 2017

J Appl. Volcanol.

View full text Add to dashboard Cite

Volcanic risk assessment using probabilistic models is increasingly desired for risk management, particularly for loss forecasting, critical infrastructure management, land-use planning and evacuation planning. Over the past decades this has motivated the development of comprehensive probabilistic hazard models. However, volcanic vulnerability models of equivalent sophistication have lagged behind hazard modelling because of the lack of evidence, data and, until recently, minimal demand. There is an increasingly urgent need for development of quantitative volcanic vulnerability models, including vulnerability and fragility functions, which provide robust quantitative relationships between volcanic impact (damage and disruption) and hazard intensity. The functions available to date predominantly quantify tephra fall impacts to buildings, driven by life safety concerns. We present a framework for establishing quantitative relationships between volcanic impact and hazard intensity, specifically through the derivation of vulnerability and fragility functions. We use tephra thickness and impacts to key infrastructure sectors as examples to demonstrate our framework. Our framework incorporates impact data sources, different impact intensity scales, preparation and fitting of data, uncertainty analysis and documentation. The primary data sources are post-eruption impact assessments, supplemented by laboratory experiments and expert judgment, with the latter drawing upon a wealth of semi-quantitative and qualitative studies. Different data processing and function fitting techniques can be used to derive functions; however, due to the small datasets currently available, simplified approaches are discussed. We stress that documentation of data processing, assumptions and limitations is the most important aspect of function derivation; documentation provides transparency and allows others to update functions more easily. Following our standardised approach, a volcanic risk scientist can derive a fragility or vulnerability function, which then can be easily compared to existing functions and updated as new data become available. To demonstrate how to apply our framework, we derive fragility and vulnerability functions for discrete tephra fall impacts to electricity supply, water supply, wastewater and transport networks. These functions present the probability of an infrastructure site or network component equalling or exceeding one of four impact states as a function of tephra thickness.

show abstract

Quantifying the resilience of an urban traffic-electric power coupled system

Cited by 91 publications

References 21 publications

Resilience assessment framework for critical infrastructure in a multi-hazard environment: Case study on transport assets

Resilience assessment framework for critical infrastructure in a multi-hazard environment: Case study on transport assets

Resilience assessment for interdependent urban infrastructure systems using dynamic network flow models

Framework for developing volcanic fragility and vulnerability functions for critical infrastructure

Contact Info

Product

Resources

About