CRISP Type 1: Multi-Scale Modeling Framework for the Assessment and Control of Resilient Interdependent Critical Infrastructure Systems

该项目将创建一个新的建模框架来评估和控制相互依赖的关键基础设施系统（ici）。基础设施系统对我们社会的运作至关重要，它们提供的服务构成了我们国家健康、安全和保障的支柱。这些系统是复杂的，由许多相互依赖的组件组成。此外，这些系统是相互依赖的，一个系统的性能依赖于一个或多个其他系统的性能。这使得ICIs容易受到各种自然和人为危害的影响。该项目将研究如何提高这些系统的弹性，并认识到实现弹性将是利益相关者的共同责任。同时，越来越多的数据可用于评估ici在正常条件下和随时间变化的状态。该项目将采用多学科方法，将工程、计算和政策整合在一起，创建一个强大的利益相关者驱动的框架，该框架可以跨规模对ici进行建模，并利用跨来源的数据来评估基础设施的现状，并对其性能和可靠性进行预测。研究人员将特别研究三个ICIs：交通、电力和通信基础设施，并将该框架应用于两个特定社区的ICIs研究，一个是城市，一个是农村。该框架将与开发新流程一起创建，以实现利益相关者的支持和政策采纳，以支持新技术与政策的集成。通过快速算法来解决框架模型和实时（或近实时）数据收集能力，一个强大的弹性基础设施管理系统可以对即将发生的灾难做出反应、适应，甚至主动采取预防措施。该项目的成果还将被纳入广泛的课堂和教育研究活动，培训下一代科学家、工程师和政策制定者，让他们了解关键基础设施弹性的重要性，以及开发新的多学科方法和工具来实现弹性。

This project will create a novel modeling framework to assess and control interdependent critical infrastructure systems (ICIs). Infrastructure systems are critical to the functioning of our society, and the services they deliver form the backbone of the health, safety, and security of our nation. These systems are complex, comprised of many interdependent components. Further, these systems are interdependent, with the performance of one system dependent on the performance of one or more of the others. This leaves ICIs vulnerable to a variety of hazards, both natural and manmade. This project will study how to improve the resilience of these systems, with the recognition that achieving resilience will be a shared responsibility among stakeholders. At the same time, more and more data is becoming available to assess the states of ICIs both under normal conditions and over time.This project will take a multidisciplinary approach, integrating across engineering, computation, and policy to create a powerful stakeholder-driven framework that models ICIs across scales and utilizes data across sources to evaluate the current status of infrastructures and make predictions on their performance and reliability. The researchers will study three ICIs in particular: transportation, power, and communications infrastructure, applying the framework to the study of these ICIs in two specific communities, one urban and one rural. The framework will be created in conjunction with the development of new processes to achieve stakeholder buy-in and policy adoption to support integration of the new technology with policy. With fast algorithms to solve the models of the framework and real-time (or near-real-time) data collection capabilities, a powerful resilient infrastructure management system that can react, adapt, and even proactively take precautionary actions in anticipation of impending disasters is envisioned. The results of this project will also be integrated into extensive classroom and educational research activities, training the next generation of scientists, engineers, and policymakers on the importance of critical infrastructure resilience and in the development of new multi-disciplinary methods and tools to achieve resilience.