ReviewA metric and frameworks for resilience analysis of engineered and infrastructure systems
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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