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最初故障的后果，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（ICI）的基本理解。在该项目中开发的框架作为多基础设施建模，设计和仿真平台的未来计算的基础。该框架将现有的软件工具与各个基础设施连接起来，并支持工程设计和公共政策分析。此外，该项目开发的定量方法将工程学、计算机科学、社会和经济科学等学科联系起来，并创建了一个新的跨学科范式，为ICI弹性规划和设计提供了一个整体视角。该项目的主要重点是开发一个元网络系统框架，在单个基础设施内和多个ICI之间的网络和人类依赖性，并评估其对灾难性事件结果的影响。这一理论框架考虑了反馈回路、级联故障链和自我加重效应。网络结构或图案的识别提供了对弹性ICI设计的见解，并允许量化与弹性相关的指标。用于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，该平台不仅适合于设计工程弹性解决方案，而且适合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定量指标，如命中时间和平均故障时间。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强大的弹性规划计划，为工业信贷机构。

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.