A quantitative method for assessing resilience of interdependent infrastructures

Nan, Cen; Sansavini, Giovanni

doi:10.1016/j.ress.2016.08.013

Cited by 351 publications

(211 citation statements)

References 35 publications

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“…The authors believe that measuring intrinsic resilience of a system based on this definition needs to evaluate the fundamental resilience capabilities (attributes) synthetically. This idea is also supported by Nan and Sansavini [54] and Francis and Bekera [55]. Thus, in this study, these four capabilities are considered as the "customer needs" for the resilience measure.…”

Section: Criteria For Literature Reviewmentioning

confidence: 85%

“…Meanwhile, resilience capabilities (e.g., withstanding, absorptive, restorative, and adaptive capabilities) can be characterized by functionality transitions following system disruptions [54]. Integrated and balanced improvements of the capabilities are needed to improve system resilience with effective investments [55].…”

Section: Discussion On System Functionality In Pre-and Post-disruptionmentioning

confidence: 99%

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A Systematic Review of Quantitative Resilience Measures for Water Infrastructure Systems

Shin

Lee

Judi

et al. 2018

Water

149

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Abstract:Over the past few decades, the concept of resilience has emerged as an important consideration in the planning and management of water infrastructure systems. Accordingly, various resilience measures have been developed for the quantitative evaluation and decision-making of systems. There are, however, numerous considerations and no clear choice of which measure, if any, provides the most appropriate representation of resilience for a given application. This study provides a critical review of quantitative approaches to measure the resilience of water infrastructure systems, with a focus on water resources and distribution systems. A compilation of 11 criteria evaluating 21 selected resilience measures addressing major features of resilience is developed using the Axiomatic Design process. Existing gaps of resilience measures are identified based on the review criteria. The results show that resilience measures have generally paid less attention to cascading damage to interrelated systems, rapid identification of failure, physical damage of system components, and time variation of resilience. Concluding the paper, improvements to resilience measures are recommended. The findings contribute to our understanding of gaps and provide information to help further improve resilience measures of water infrastructure systems.

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Section: Criteria For Literature Reviewmentioning

confidence: 85%

Section: Discussion On System Functionality In Pre-and Post-disruptionmentioning

confidence: 99%

A Systematic Review of Quantitative Resilience Measures for Water Infrastructure Systems

Shin

Lee

Judi

et al. 2018

Water

149

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“…Resistance (R m ): Resistance should be a total measure of the capability to resist the negative impact caused by a disturbance with the capability to maintain the LoP immediately after that occurrence. It is an aggregated outcome of system's overall ability to prevent negative effects of shocks, which could be approximated as the minimum LoP P(t event ) during the entire process from t pre to t post (Nan and Sansavini, 2017) plus the maintaining effects contributed from the robustness range. This measure identifies the maximum impact of disruptive events, and use the remaining capacities as a proxy for the system's current ability to resist.…”

Section: Quantification Of Elemental Functionsmentioning

confidence: 99%

Quantitative evaluation of consecutive resilience cycles in stock market performance: A systems-oriented approach

Tang¹,

Heinimann²,

Khoja³

2019

Physica A: Statistical Mechanics and its Applications

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Financial markets can be seen as complex systems that are constantly evolving and sensitive to external disturbance, such as systemic risks and economic instabilities. Analysis of resilient market performance, therefore, becomes useful for investors. From a systems perspective, this paper proposes a novel function-based resilience metric that considers the effect of two faulttolerance thresholds: the Robustness Range (RR) and the Elasticity Threshold (ET). We examined the consecutive resilience cycles and their dynamics in the performance of two stock markets, NASDAQ and SSE. The proposed metric was also compared with three well-documented resilience models. The results showed that this new metric could satisfactorily quantify the time-varying resilience cycles in the multi-cycle volatile performance of stock markets while also being more feasible in comparative analysis. Furthermore, analysis of dynamics revealed that those consecutive resilience cycles in market performance were distributed non-linearly, following a power-law behavior in the upper tail. Finally, sensitivity tests demonstrated the large-value resilience cycles were relatively sensitive to changes in RR. In practice, RR could indicate investors' psychological capability to withstand downturns. It supports the observation that perception on the market's resilient responses may vary among investors. This study provides a new tool and valuable insight for researchers, practitioners, and investors when evaluating market performance.

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“…In addition, other properties related to interdependent networks have also been studied, such as propagation [34][35][36][37], competition [38], resilience [39] and gaming [40].In the end, for the theory to model the cascading failures in interdependent networks, spreading process and in particular, mean-field approximation [41,42] has been recently studied, in addition to the commonly used generating functions and percolation theory.…”

Section: Introductionmentioning

confidence: 99%

On the Robustness of No-Feedback Interdependent Networks

et al. 2018

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Abstract:The continuous operation of modern society is dominated by interdependent networks, such as energy networks, communication networks, and traffic networks. As a result, the robustness of interdependent networks has become increasingly important in recent years. On the basis of past research, a no-feedback interdependent networks model is introduced. Compared with previous work, this model is more consistent with the characteristics of real interdependent systems. In addition, two types of failure modes, unilateral failure and bilateral failure, are defined. For each failure mode, the influence of coupling strength and dependency strength on the robustness of no-feedback interdependent networks was analyzed and discussed in relation to various giant component sizes. The simulation results indicated that the robustness of the no-feedback interdependent networks was inversely proportional to coupling strength and dependency strength, and the effect of coupling strength and dependency strength on the robustness was equivalent. These conclusions are beneficial for helping researchers and engineers to build more robust interdependent systems.

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A quantitative method for assessing resilience of interdependent infrastructures

Cited by 351 publications

References 35 publications

A Systematic Review of Quantitative Resilience Measures for Water Infrastructure Systems

A Systematic Review of Quantitative Resilience Measures for Water Infrastructure Systems

Quantitative evaluation of consecutive resilience cycles in stock market performance: A systems-oriented approach

On the Robustness of No-Feedback Interdependent Networks

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