Review
A metric and frameworks for resilience analysis of engineered and infrastructure systems

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Highlights

  • While resilience is a useful concept, its diversity in usage complicates its interpretation and measurement.

  • We proposed a resilience analysis framework whose implementation is encapsulated within resilience metric incorporating absorptive, adaptive, and restorative capacities.

  • We have shown that our framework and metric can support the investigation of “deep” uncertainties in resilience assessment or analysis.

  • We have discussed the role of quantitative metrics in design for ecological versus engineered resilience in socio-technical systems.

  • Our resilience metric supports resilience conceived both as an epistemological and inherent system property.

Abstract

In this paper, we have reviewed various approaches to defining resilience and the assessment of resilience. We have seen that while resilience is a useful concept, its diversity in usage complicates its interpretation and measurement. In this paper, we have proposed a resilience analysis framework and a metric for measuring resilience. Our analysis framework consists of system identification, resilience objective setting, vulnerability analysis, and stakeholder engagement. The implementation of this framework is focused on the achievement of three resilience capacities: adaptive capacity, absorptive capacity, and recoverability. These three capacities also form the basis of our proposed resilience factor and uncertainty-weighted resilience metric. We have also identified two important unresolved discussions emerging in the literature: the idea of resilience as an epistemological versus inherent property of the system, and design for ecological versus engineered resilience in socio-technical systems. While we have not resolved this tension, we have shown that our framework and metric promote the development of methodologies for investigating “deep” uncertainties in resilience assessment while retaining the use of probability for expressing uncertainties about highly uncertain, unforeseeable, or unknowable hazards in design and management activities.

Introduction

Increased acknowledgment of the role of resilience in augmenting risk management practice has introduced some exciting changes into the systems engineering discipline. Despite an increased prominence of the role of system resilience in various sectors of systems engineering over the past few years, substantial diversity remains among the definitions of resilience. Consequently, frameworks adopted in order to quantitatively or qualitatively assess resilience exhibit little standardization and may offer unclear guidance to systems engineers and managers.

In this paper, we review the literature to provide guidance to infrastructure system engineers by comparing risk analysis to resilience analysis. We then propose a metric for resilience measurement that incorporates three resilience capacities, absorptivity, adaptability, recoverability, with the uncertainty in models of initiating events such as natural hazards or other disruptive events. We conclude the article by discussing the role of risk and resilience analysts in exploring deep uncertainty when managing complex engineered systems.

Section snippets

Risk assessment overview

In engineering, typically, there are two factors that play a central role in risk assessment: the likelihood an event deemed undesirable occurs and the consequences, given the occurrence of that event. Conditional on the occurrence of an event, the consequences are also characterized by a probability distribution over their severity. In risk assessment, the emphasis is often on assessing the expected harm from the event occurring while not necessarily emphasizing the accrual of benefits to

Resilience assessment framework

The evolution of the concept of resilience naturally yields the development of a resilience assessment framework. This framework, illustrated in Fig. 1, consists of five components: system identification, vulnerability analysis, resilience objective setting, stakeholder engagement and resilience capacities.

Measuring resilience

Although we have devoted most of our discussion to the management principles involved in resilience, a metric reflecting these principles is needed for decision support and design. It has been acknowledged that quantitative metrics are required to support resilience engineering. One approach identifies organizational resilience indicators such as top management commitment, Just culture, learning culture, awareness and opacity, preparedness, and flexibility [17]. While these indicators are

Measuring resilience: an electric power example

In this section, we demonstrate the proposed resilience metric by applying this metric to the electric power network of a fictional city called Micropolis [34]. The electric power network for Micropolis is illustrated in Fig. 4, and key descriptive statistics for the project area are reported in Table 2. Our example evaluates an infrastructure hardening decision in which planners consider whether to place overhead infrastructure east of the railroad (running next to the transmission line

Summary

In this paper, we have undertaken a review of various approaches to resilience definition and assessment. Based on this review, we have proposed an alternative metric for measuring resilience that incorporates knowledge uncertainty as an integral input into evaluating system resilience.

Despite our efforts, some important challenges and disagreements have not been addressed. Among these, we will discuss (i) the idea of resilience as an epistemological property of the system [7], [38]; and,

Acknowledgments

The authors acknowledge the George Washington University School of Engineering and Applied Science for the financial support of this work. This work was also partially supported by the District of Columbia Water Resources Research Institute (EENS20624N), DC Water (ECNS20766F), and a Johns Hopkins University subcontract on NSF Award #1031046.

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