Resilience is emerging as the preferred way to improve the protection of infrastructure systems beyond established risk management practices. Massive damages experienced during tragedies like Hurricane Katrina showed that risk analysis is incapable to prevent unforeseen infrastructure failures and shifted expert focus towards resilience to absorb and recover from adverse events. Recent, exponential growth in research is now producing consensus on how to think about infrastructure resilience centered on definitions and models from influential organizations like the US National Academy of Sciences. Despite widespread efforts, massive infrastructure failures in 2017 demonstrate that resilience is still not working, raising the question: Are the ways people think about resilience producing resilient infrastructure systems?



This dissertation argues that established thinking harbors misconceptions about infrastructure systems that diminish attempts to improve their resilience. Widespread efforts based on the current canon focus on improving data analytics, establishing resilience goals, reducing failure probabilities, and measuring cascading losses. Unfortunately, none of these pursuits change the resilience of an infrastructure system, because none of them result in knowledge about how data is used, goals are set, or failures occur. Through the examination of each misconception, this dissertation results in practical, new approaches for infrastructure systems to respond to unforeseen failures via sensing, adapting, and anticipating processes. Specifically, infrastructure resilience is improved by sensing when data analytics include the modeler-in-the-loop, adapting to stress contexts by switching between multiple resilience strategies, and anticipating crisis coordination activities prior to experiencing a failure.

Overall, results demonstrate that current resilience thinking needs to change because it does not differentiate resilience from risk. The majority of research thinks resilience is a property that a system has, like a noun, when resilience is really an action a system does, like a verb. Treating resilience as a noun only strengthens commitment to risk-based practices that do not protect infrastructure from unknown events. Instead, switching to thinking about resilience as a verb overcomes prevalent misconceptions about data, goals, systems, and failures, and may bring a necessary, radical change to the way infrastructure is protected in the future.

Resilient infrastructure research has produced a myriad of conflicting definitions and analytic frameworks, highlighting the difficulty of creating a foundational theory that informs disciplines as diverse as business, engineering, ecology, and disaster risk reduction. Nevertheless, there is growing agreement that resilience is a desirable property for infrastructure systems – i.e., that more resilience is always better. Unfortunately, this view ignore that the fact that a single concept of resilience is insufficient to ensure effective performance under diverse and volatile stresses. Scholarship in resilience engineering has identified at least four irreducible resilience concepts, including: rebound, robustness, graceful extensibility, and sustained adaptability.

In this paper, we clarify the meaning of the word resilience and its use, explain the advantages of the pluralistic approach to advancing resilience theory, and clarify two of the four conceptual understandings: robustness and graceful extensibility. Furthermore, we draw upon examples in electric power, transportation, and water systems that illustrate positive and negative cases of resilience in infrastructure management and crisis response. The following conclusions result:

1. Robustness and graceful extensibility are different strategies for resilience that draw upon different system characteristics.
2. Neither robustness nor extensibility can prevent all hazards.
3. While systems can perform both strategies simultaneously, their drawbacks are different.

Robust infrastructure systems fail when policies and procedures become stale, or when faced with overwhelming surprise. Extensible systems fail when a lack of coordination or exhaustion of resources results from decompensation. Consequently, resilience is found neither only in robustness, nor only in extensibility, but in the capacity apply both and switch between them at will.