Measurable Resilience for Actionable Policy

Linkov, Igor; Eisenberg, Daniel A.; Bates, Matthew; Chang, Derek; Convertino, Matteo; Allen, Julia; Flynn, Stephen E.; Seager, Thomas P.

doi:10.1021/es403443n

Cited by 103 publications

(115 citation statements)

References 3 publications

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“…Therefore, an improved version of the definition should use the probabilities P hj ¼ P h t h recovery t max jevent#j À Á . These probabilities depend on the quality and detail of the disaster planning [see the ''plan/prepare'' cells in the resilience matrix method of Linkov et al (2013)], on the disaster management on site (corresponding to the ''absorb'' cells in the same paper), during and immediately after the disaster, and on the skills and talent of people on site to find fast solutions, possibly alternative, not-thought-of-before solutions to problems (see the discussion in the next Section).…”

Section: Some Further Issuesmentioning

confidence: 99%

Defining resilience using probabilistic event trees

Teodorescu

2015

Environ Syst Decis

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The concept of resilience and various aspects related to resilience enhancement and resilience calculus are addressed in the context of the broader theme of reliability and disaster mitigation. A definition of resilience is proposed, based on the assessment of event trees and the statistical determination of risks. Essentially, we apply standard probabilistic models with conditional probabilities, event trees and fault trees, where faults are not limited to technological ones, but cover lack of personnel as well, to define the resilience in a systematic manner. An essential aspect of the approach is the estimation of the probability of recovery in a specified time frame. The time to recovery and the level of recovery play key roles in the definition. The main assumptions underlying the calculations are discussed. A synthetic resilience indicator is introduced to offer a short, easy to grasp clue on the resilience level, with the aim to facilitate planning for resilience. An analysis methodology is suggested under general conditions, and several examples of applications are given.

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Section: Some Further Issuesmentioning

confidence: 99%

Defining resilience using probabilistic event trees

Teodorescu

2015

Environ Syst Decis

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“…Rosati et al (2015) introduce a three-tier approach to incorporating resilience into the US Army Corps of Engineers coastal engineering needs and programs. Fox-Lent et al (2015) describe application of this approach for coastal communities in a case study from Rockaway Peninsula using a stakeholder-driven resilience matrix framework adapted from Linkov et al (2013). Sikula et al (2015) focus on integrating resilience in the case of sustaining missions at military installations.…”

Section: President Obama's Executive Order and Presidentialmentioning

confidence: 99%

Concepts and approaches to resilience in a variety of governance and regulatory domains

2015

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President Obama's Executive Order and PresidentialDirective (E.O. 13636 2013; P.P.D. 21 2013) have called for resilience of the nation's infrastructure and environmental systems. Resilience has been defined by the US National Academy of Sciences as the ability to plan and prepare for, absorb, recover from, and adapt to adverse events (National Academy of Sciences 2012). There is increasing depth and variety of resilience-related research. There are differing approaches to quantifying resilience and a contrast between resilience and risk, which have implications for regulatory policies. Papers included in this Special Issue of Environment Systems & Decisions seek to characterize resilience methodologies and the applications across a variety of domains and topic areas. With many papers and special issues on resilience, the uniqueness of this issue is a tandem focus on quantifying resilience and contrasting of applications of resilience management in the US Federal Government.The issue starts with a review paper by Larkin et al. (2015) sampling efforts of the US Federal Government to address resilience. It is clear that multiple agencies attempt to formalize resilience and use it in their respective mission space. In many areas, the efforts are fragmented and divergent; more interagency collaboration and focus on developing comprehensive resilience management methodology are required. Part of the challenge in defining resilience is the complexity of agency mission space and diversity of needs. Several papers presented by scientists from the US Army illustrate the diversity of needs and applications including critical infrastructure and military installations. Rosati et al. (2015) introduce a three-tier approach to incorporating resilience into the US Army Corps of Engineers coastal engineering needs and programs. Fox-Lent et al. (2015) describe application of this approach for coastal communities in a case study from Rockaway Peninsula using a stakeholder-driven resilience matrix framework adapted from Linkov et al. (2013). Sikula et al. (2015) focus on integrating resilience in the case of sustaining missions at military installations. The paper argues for the enhancement of traditional engineering and risk approaches with socioeconomic system resilience principles. The proposed Military Installation Resilience Assessment aims to use resilience in the evaluation of both known and unknown hazards.The literature is exploring the relationship and contrast of risk and resilience. Risk is often calculated as a product of threat, vulnerability, and consequences. Risk analysis often underemphasizes the time domain. Resilience accounts for the time domain when considering the planning, stress absorbing, recovery, and adaptation stage of system evolution. Baum (2015) presents arguments for a close connection between risk and resilience. He describes how risk and resilience require supplementary information. He suggests giving balanced consideration to each of the concepts, which should be deployed in conjunction.The issue ...

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“…Such networks are resilient if the level of service during these different phases of resilience is maintained globally acceptable. In [26,27] the authors establish a "cyber resilience matrix" for cyber systems, i.e., a list of the main strategies to adopt at some stage of resilience in some given domain. On the one hand, they focused on four stages of resilience identified by the National Academy of Sciences (NAS) as the main steps of the event management cycle that a system needs to maintain to be resilient, i.e., prepare, absorb, recover and adapt.…”

Section: Position Of This Paper With Respect To Related Work 21 Resimentioning

confidence: 99%

“…Thus, the challenges typically addressed in the literature consist in elaborating resilient strategies for a system through an analysis of its past behaviour. Such strategies are usually domain-dependent [26,27,40,41,50].…”

Section: Introductionmentioning

confidence: 99%

Formalization of resilience for constraint-based dynamic systems

Schwind

Magnin

Inoue

et al. 2015

J Reliable Intell Environ

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Many researchers in different fields are interested in building resilient systems that can absorb shocks and recover from damages caused by unexpected large-scale events. Existing approaches mainly focus on the evaluation of the resilience of systems from a qualitative point of view, or pay particular attention to some domain-dependent aspects of the resilience. In this paper, we introduce a very general, abstract computational model rich enough to represent a large class of constraint-based dynamic systems. Taking our inspi- ration from the literature, we propose a simple parameterized property which captures the main features of resilience independently from a particular application domain, and we show how to assess the resilience of a constraint-based dynamic system through this new resilience property.

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Measurable Resilience for Actionable Policy

Cited by 103 publications

References 3 publications

Defining resilience using probabilistic event trees

Defining resilience using probabilistic event trees

Concepts and approaches to resilience in a variety of governance and regulatory domains

Formalization of resilience for constraint-based dynamic systems

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