RIPS: Type I: A Meta-Network System Framework for Resilient Analysis and Design of Interdependent Critical Infrastructures

关键基础设施系统和流程之间的相互依赖加剧了初始故障的后果，导致级联效应，并加剧了损害的传播。该项目通过提供理论指导，增强了对相互依赖的关键基础设施（ICIs）的基本理解。该项目开发的框架可作为未来多基础设施建模、设计和仿真平台计算的基础。该框架为单个基础设施连接现有的软件工具，并使工程设计和公共政策分析成为可能。此外，该项目中开发的定量方法将工程、计算机科学、社会和经济科学等学科联系起来，创造了一个新的跨学科范式，为ICI弹性规划和设计提供了一个全面的视角。该项目的主要重点是开发一个元网络系统框架，该框架可以捕获单个基础设施内和多个ici之间的物理、网络和人类依赖关系，并评估它们对灾难性事件结果的影响。该理论框架考虑了反馈回路、级联失败链和自加重效应。网络结构或基元的识别为弹性ici的设计提供了见解，并允许量化与弹性相关的指标。寻找元网络模型的多分辨率表示的技术提供了一个系统建模平台，该平台不仅适用于设计工程弹性解决方案，也适用于在组织行为的背景下检查社会经济政策和通信协议。事件驱动和基于网络的可靠性模型提供了诸如命中时间和平均故障时间之类的定量度量。控制和博弈论捕捉风险和不确定性，并协助设计风险敏感和稳健的ici弹性规划方案。

Interdependencies between critical infrastructure systems and processes exacerbate the consequences of initial failure, lead to cascading effects, and compound the propagation of damage. The project enhances the fundamental understanding of interdependent critical infrastructures (ICIs) by providing theoretical guidelines. The framework developed in the project serves as the basis of future computing for a multi-infrastructure modeling, design and simulation platform. This framework interfaces existing software tools for individual infrastructures and enables engineering design and public policy analysis. In addition, the quantitative methodologies developed in this project bridge the disciplines of engineering, computer science, social and economic sciences, and create a new interdisciplinary paradigm that provides a holistic view towards ICI resilience planning and design.The main focus of this project is to develop a meta-network system framework that captures the physical, cyber and human dependencies within an individual infrastructure and across multiple ICIs and to assess their effects on the outcomes of disastrous events. This theoretical framework considers feedback loops, cascading chains of failures and self-aggravating effects. The identification of network structures or motifs provides insights on the design of resilient ICIs and allows for the quantification of metrics relevant to resilience. The techniques for finding multi-resolution representations of meta-network models provide a system modeling platform that is appropriate not only for designing engineering resilient solutions but also for examining socio-economic policies and communication protocols in the context of organizational behaviors. An event-driven and network-based reliability model provides quantitative metrics such as hitting time and mean time to failure. Control and game theory capture risks and uncertainty and assist in the design of risk-sensitive and robust resilient planning schemes for ICIs.