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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. 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)

   Abstract 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 as infrastructure 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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3. When Green Computing Meets Performance and Resilience SLOs.

   https://doi.org/10.1109/DSN-S60304.2024  

   Qiu, H; Mao, W; Wang, C; Jha, S; Franke, H; Narayanaswami, C; Kalbarczyk, ZT; Basar, T; Iyer, R_K (January 2024, Institute of Electrical and Electronics Engineers)

   nd (Ed.)

   This paper addresses the urgent need to transition to global net-zero carbon emissions by 2050 while retaining the ability to meet joint performance and resilience objectives. The focus is on the computing infrastructures, such as hyperscale cloud datacenters, that consume significant power, thus producing increasing amounts of carbon emissions. Our goal is to (1) optimize the usage of green energy sources (e.g., solar energy), which is desirable but expensive and relatively unstable, and (2) continuously reduce the use of fossil fuels, which have a lower cost but a significant negative societal impact. Meanwhile, cloud datacenters strive to meet their customers’ requirements, e.g., service-level objectives (SLOs) in application latency or throughput, which are impacted by infrastructure resilience and availability. We propose a scalable formulation that combines sustainability, cloud resilience, and performance as a joint optimization problem with multiple interdependent objectives to address these issues holistically. Given the complexity and dynamicity of the problem, machine learning (ML) approaches, such as reinforcement learning, are essential for achieving continuous optimization. Our study highlights the challenges of green energy instability which necessitates innovative MLcentric solutions across heterogeneous infrastructures to manage the transition towards green computing. Underlying the MLcentric solutions must be methods to combine classic system resilience techniques with innovations in real-time ML resilience (not addressed heretofore). We believe that this approach will not only set a new direction in the resilient, SLO-driven adoption of green energy but also enable us to manage future sustainable systems in ways that were not possible before. 

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4. Developing Human-Centered Urban Digital Twins for Community Infrastructure Resilience: A Research Agenda

   https://doi.org/10.1177/08854122221137861  

   Ye, Xinyue; Du, Jiaxin; Han, Yu; Newman, Galen; Retchless, David; Zou, Lei; Ham, Youngjib; Cai, Zhenhang (May 2023, Journal of Planning Literature)

   Urban digital twins (UDTs) have been identified as a potential technology to achieve digital transformative positive urban change through landscape architecture and urban planning. However, how this new technology will influence community resilience and adaptation planning is currently unclear. This article: (1) offers a scoping review of existing studies constructing UDTs, (2) identifies challenges and opportunities of UDT technologies for community adaptation planning, and (3) develops a conceptual framework of UDTs for community infrastructure resilience. This article highlights the need for integrating multi-agent interactions, artificial intelligence, and coupled natural–physical–social systems into a human-centered UDTs framework to improve community infrastructure resilience. 

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5. An approach to designing sustainable urban infrastructure

   https://doi.org/10.1557/mre.2018.14  

   Derrible, Sybil (January 2018, MRS Energy & Sustainability)

   This article offers a conceptual understanding and easily applicable guidelines for sustainable urban infrastructure design by focusing on the demand for and supply of the services provided by seven urban infrastructure systems. For more than 10,000 years, cities have evolved continuously, often shaped by the challenges they had to face. Similarly, we can imagine that cities will have to evolve again in the future to address their current challenges. Specifically, urban infrastructure will need to adapt and use less energy and fewer resources while becoming more resilient. In this article, starting with a definition of sustainability, two urban infrastructure sustainability principles (SP) are introduced: (i) controlling the demand and (ii) increasing the supply within reason, which are then applied to seven urban infrastructure systems: water, electricity, district heating and cooling and natural gas, telecommunications, transport, solid waste, and buildings. From these principles, a four-step urban infrastructure design (UID) process is compiled that can be applied to any infrastructure project: (i) controlling the demand to reduce the need for new infrastructure, (ii) integrating a needed service within the current infrastructure, (iii) making new infrastructure multifunctional to provide for other infrastructure systems, and (iv) designing for specific interdependencies and decentralizing infrastructure if possible. Overall, by first recognizing that urban infrastructure systems are inherently integrated and interdependent, this article offers several strategies and guidelines to help design sustainable urban infrastructure systems. 

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