Systems resilience assessments: a review, framework and metrics

Cheng, Yao; Elsayed, Elsayed A.; Huang, Zhiyi

doi:10.1080/00207543.2021.1971789

Cited by 43 publications

(12 citation statements)

References 267 publications

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“…Many resilience assessment models have been developed based on the above two categories of methods, by assessing the risk of each component of the system or describing the process of disasters (Tong, 2021;Cheng et al, 2022). In addition, these models consider the factors that affect the system's ability to cope with risk, recover from it, and learn and innovate.…”

Section: A Brief Overview Of Current Resilience Assessment Methodsmentioning

confidence: 99%

A disaster-damage-based framework for assessing urban resilience to intense rainfall-induced flooding

Zhang¹,

Mao²,

Gong³

et al. 2023

Urban Climate

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Section: A Brief Overview Of Current Resilience Assessment Methodsmentioning

confidence: 99%

A disaster-damage-based framework for assessing urban resilience to intense rainfall-induced flooding

Zhang¹,

Mao²,

Gong³

et al. 2023

Urban Climate

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“…Review on multi-scale resilience of complex systems. Many performance-based methods have been proposed to quantify the macro resilience of systems in different domains with different metrics 9,10 . But the loss of resilience of complex system with large number of components in complex natural and man-made system is still difficult to predict.…”

Section: Uncertainty Quantification Of Multi-scale Resilience In Netw...mentioning

confidence: 99%

Uncertainty quantification of multi-scale resilience in networked systems with nonlinear dynamics using arbitrary polynomial chaos

Zou

Fragonara

Qiu

et al. 2023

Sci Rep

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Complex systems derive sophisticated behavioral dynamics by connecting individual component dynamics via a complex network. The resilience of complex systems is a critical ability to regain desirable behavior after perturbations. In the past years, our understanding of large-scale networked resilience is largely confined to proprietary agent-based simulations or topological analysis of graphs. However, we know the dynamics and topology both matter and the impact of model uncertainty of the system remains unsolved, especially on individual nodes. In order to quantify the effect of uncertainty on resilience across the network resolutions (from macro-scale network statistics to individual node dynamics), we employ an arbitrary polynomial chaos (aPC) expansion method to identify the probability of a node in losing its resilience and how the different model parameters contribute to this risk on a single node. We test this using both a generic networked bi-stable system and also established ecological and work force commuter network dynamics to demonstrate applicability. This framework will aid practitioners to both understand macro-scale behavior and make micro-scale interventions.

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“…System resilience can also be distinguished in terms of time, and is classified in literature as the prehazard, hazard, and recovery periods (Cheng et al, 2022). Substantial conditions during the pre-hazard period are design configuration, functionality, and the reliability of constituents.…”

Section: Characteristics Of Disaster-resilient Hospitalsmentioning

confidence: 99%

Hospital Disaster Resilience: a Conceptual Framework

Paulikienė¹

2022

Regional Formation and Development Studies

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This article analyses the concept of hospital resilience to natural disasters (earthquakes, global warming, pandemics, and man-made disasters such as war, conflict and cyber-attacks) in the context of theoretical insights in scholarly articles on the concept of resilience, and elements of its perception and other aspects. The research conducted identified that the concept of a resilient hospital encompasses its ability to maintain functionality at minimal resource costs, and reduce the likelihood of shock in the event of various disasters. This capacity to withstand hazard can be of various types, for example, constructive, infrastructural or administrative. The following four elements are most commonly identified levels of resilience: context, disturbance, capacity to deal with disturbance, and reaction to disturbance. A resilient hospital maintains the following characteristics: rapidity, robustness, redundancy, resourcefulness, awareness, diversity, self-regulation, unity and adaptiveness. A variety of means are used to amplify resilience to distinct disasters and it is relevant to manage different types of resilience, but the human factor is indisputably essential in this framework.

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Systems resilience assessments: a review, framework and metrics

Cited by 43 publications

References 267 publications

A disaster-damage-based framework for assessing urban resilience to intense rainfall-induced flooding

A disaster-damage-based framework for assessing urban resilience to intense rainfall-induced flooding

Uncertainty quantification of multi-scale resilience in networked systems with nonlinear dynamics using arbitrary polynomial chaos

Hospital Disaster Resilience: a Conceptual Framework

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