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1. Being Prepared to be Unprepared: Meaning Making is Critical for the Resilience of Critical Infrastructure Systems

   JE Thomas, TP Seager ( August 2020 , Integral review)

   null (Ed.)

   Infrastructure is essential to provision of public health, safety, and well-being. Yet, even critical infrastructure systems cannot be designed, constructed, and operated to be robust to the myriad of surprising hazards they are likely to be subject to. As such, there has been increasing emphasis in Federal policy on enhancing infrastructure resilience. Nonetheless, existing research on infrastructure systems often overlooks the role of individual decision-making and team dynamics under the conditions of high ambiguity and uncertainty typically associated with surprise. Although evidence suggests that human factors correlating with resilience and adaptive capacity emerge in later stages of psychological development, there is an acute need for new knowledge about the human capacity to comprehend increasing levels of complexity in the context of rapidly evolving technological, ecological, and social stress conditions. Sometimes, it is this developmental capacity for meaning-making that is the difference between adaptive and maladaptive response. Thus, without a better understanding of the human capacity to develop and assign meaning to complex systems, unquestioned misconceptions about the human role may prevail. In this work, we examine the dynamic relationships between human and technological systems from a developmental perspective. We argue that knowledge of resilient human development can improve system resilience by aligning roles and responsibilities with the developmental capacities of individuals and groups responsible for the design, operation, and management of critical infrastructures. Taking a holistic approach that draws on both psychology and resilience engineering literature facilitates construction of an integrated model that lends itself to empirical verification of future research. 

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2. Using Biomimicry to Support Resilient Infrastructure Design

   https://doi.org/10.1029/2020EF001653  

   Helmrich, Alysha M. ; Chester, Mikhail V. ; Hayes, Samantha ; Markolf, Samuel A. ; Desha, Cheryl ; Grimm, Nancy B. ( December 2020 , Earth's Future)

   Infrastructure must be resilient to both known and unknown disturbances. In the past, resilient infrastructure design efforts have tended to focus on principles of robustness and recovery against projected failures. This framing has developed independently from resilience principles in biological and ecological systems. As such, there are open questions as to whether the approaches of natural systems that lead to adaptation and transformation are relevant to engineered systems. To improve engineered system resilience, infrastructure managers may benefit from considering and applying a set of “Life's Principles”—design principles and patterns drawn from the field of biomimicry. Nature has long withstood disturbances within and beyond previous experience. Infrastructure resilience theory and practice are assessed against Life's Principles identifying alignments, contradictions, contentions, and gaps. Resilient infrastructure theory, which emphasizes a need for flexible and agile infrastructure, aligns well with Life's Principles, addressing each principle and most sub‐principles (excluding “breakdown products into benign components” and “do chemistry in water”). Meanwhile, resilient infrastructure practice only occasionally aligns with Life's Principles and contradicts five out of six principles. As resilience theory advances, Life's Principles offer support in broadening how infrastructure managers approach resilience, and by using biomimicry, infrastructure managers can be better equipped to deploy resilience for complexity and uncertainty.

    

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3. Infrastructure autopoiesis: requisite variety to engage complexity

   https://doi.org/10.1088/2634-4505/ac4b48  

   Chester, Mikhail V. ; Allenby, Braden ( February 2022 , Environmental Research: Infrastructure and Sustainability)

   Infrastructure systems must change to match the growing complexity of the environments they operate in. Yet the models of governance and the core technologies they rely on are structured around models of relative long-term stability that appear increasingly insufficient and even problematic. As the environments in which infrastructure function become more complex, infrastructure systems must adapt to develop a repertoire of responses sufficient to respond to the increasing variety of conditions and challenges. Whereas in the past infrastructure leadership and system design has emphasized organization strategies that primarily focus on exploitation (e.g., efficiency and production, amenable to conditions of stability), in the future they must create space for exploration, the innovation of what the organization is and does. They will need to create the abilities to maintain themselves in the face of growing complexity by creating the knowledge, processes, and technologies necessary to engage environment complexity. We refer to this capacity asinfrastructure autopoiesis. In doing so infrastructure organizations should focus on four key tenets. First, a shift to sustained adaptation—perpetual change in the face of destabilizing conditions often marked by uncertainty—and away from rigid processes and technologies is necessary. Second, infrastructure organizations should pursue restructuring their bureaucracies to distribute more resources and decisionmaking capacity horizontally, across the organization’s hierarchy. Third, they should build capacity for horizon scanning, the process of systematically searching the environment for opportunities and threats. Fourth, they should emphasize loose fit design, the flexibility of assets to pivot function as the environment changes. The inability to engage with complexity can be expected to result in a decoupling between what our infrastructure systems can do and what we need them to do, and autopoietic capabilities may help close this gap by creating the conditions for a sufficient repertoire to emerge.

    

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4. Rethinking Resilience Analytics

   https://doi.org/10.1111/risa.13328  

   Eisenberg, Daniel ; Seager, Thomas ; Alderson, David L. ( May 2019 , Risk Analysis)

   The concept of “resilience analytics” has recently been proposed as a means to leverage the promise of big data to improve the resilience of interdependent critical infrastructure systems and the communities supported by them. Given recent advances in machine learning and other data‐driven analytic techniques, as well as the prevalence of high‐profile natural and man‐made disasters, the temptation to pursue resilience analytics without question is almost overwhelming. Indeed, we find big data analytics capable to support resilience to rare, situational surprises captured in analytic models. Nonetheless, this article examines the efficacy of resilience analytics by answering a single motivating question: Can big data analytics help cyber–physical–social (CPS) systems adapt to surprise? This article explains the limitations of resilience analytics when critical infrastructure systems are challenged by fundamental surprises never conceived during model development. In these cases, adoption of resilience analytics may prove either useless for decision support or harmful by increasing dangers during unprecedented events. We demonstrate that these dangers are not limited to a single CPS context by highlighting the limits of analytic models during hurricanes, dam failures, blackouts, and stock market crashes. We conclude that resilience analytics alone are not able to adapt to the very events that motivate their use and may, ironically, make CPS systems more vulnerable. We present avenues for future research to address this deficiency, with emphasis on improvisation to adapt CPS systems to fundamental surprise.

    

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5. Operationalizing resilience: A deductive fault-driven resilience index for enabling adaptation

   https://doi.org/10.1016/j.psep.2023.07.082  

   Amer, Lamis ; Erkoc, Murat ; Celik, Nurcin ; Andiroglu, Esber ( September 2023 , Process Safety and Environmental Protection)

   The impact of climate change and the dynamic nature of environmental conditions underscore the critical need to enhance resilience of systems and process safety considerations. The efficacy of such efforts primarily depends on how resilience is measured. Among the myriad efforts to quantify resilience, composite indicators have emerged as promising tools. However, these indicators typically employ statistical methods to derive weights for aggregation and rely on statistical homogeneity among indicators which can limit their scope and fidelity. In this study, we propose an alternative novel resilience index derived from a system’s structure and the essential conditions for safe operation during and after disruptions. The proposed measure reflects the systems’ ability to resist and respond to failures by addressing possibilities of impact propagation to other infrastructure systems. Moreover, it eliminates the need for weights and allows for compensability among its leading indicators. Using a case study based on the on-site wastewater treatment and disposal systems (OSTDS) in South Florida that faces increasing risks due to rising sea levels, we investigate the validity of the proposed index and perform a comparative analysis with statistically-driven measures. Furthermore, we demonstrate the adaptation of the proposed index for decision making within a generalized optimization framework. 

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