CRISP Type 2: Identification and Control of Uncertain, Highly Interdependent Processes Involving Humans with Applications to Resilient Emergency Health Response

城市化步伐的不断加快，特别是沿海地区的城市化进程，再加上基础设施不健全、相互依赖性知之甚少，将使因海洋变暖和海平面上升而加剧的重大天气事件在不久的将来更有可能演变成灾难。超级风暴桑迪为这种情况提供了一个特别令人心酸的例子。这项关键弹性相互依存基础设施系统和流程 (CRISP) 2 类拨款将开创一种新方法，使社区能够抵御灾害并快速恢复。这将通过“预测、干预和适应”的主动弹性新范式来实现，而不是当前的发现、恢复和重新设计的反应循环。这项研究的一个独特之处是整合了工程（电气、工业、土木）、计算机科学和社会科学策略，以实现短期和长期的恢复力。教育被积极地融入到这个项目中，从针对城市中学生的夏季 STEM 课程开始，一直到大学水平的多学科项目，该项目利用弹性社区的中心隐喻将各种不同的学科联系起来。这种方法将有助于扩大代表性不足群体对研究的参与，并大幅改变工程和社会科学教育。这项研究旨在通过将弹性社区建模为部分工程化的网络网络物理人类系统，开发一个用于设计和运营弹性社区的综合框架。最终目标是为此类系统开发一个综合框架，能够保证最低水平的性能并在遇到中断时快速恢复功能。这一目标将通过在动态图形模型所代表的数据驱动识别和过程控制的背景下重塑问题来实现，其中节点和互连边都是动态系统，封装了问题的网络物理和人类方面。该方法允许以统一的方式处理问题的各个方面，利用优化、网络控制和基于代理的建模方面的最新进展来获得可扩展、计算上易于处理的解决方案。该框架的显着特征包括将基于代理的人类反应建模集成到机会约束优化框架中，该框架确定优化弹性的策略，使用数据驱动模型从极大的数据集中提取可操作的信息，以及通过新颖的基于熔断的设计技术实现对系统范围组件的有目的地操作。由此产生的框架将使用一个场景进行测试，该场景涉及对维持最低紧急医疗水平至关重要的四个系统：电力、通信、关键货物供应链和建筑环境。

The growing pace of urbanization, particularly along coasts, in conjunction with non-robust infrastructures with poorly understood interdependencies, will make major weather events, intensified by warming oceans and rising sea level, more likely to turn into disasters in the near future. Superstorm Sandy provided a particularly poignant example of this situation. This Critical Resilient Interdependent Infrastructure Systems and Processes (CRISP) Type 2 grant will pioneer a new approach to enable communities to withstand and bounce back quickly from hazards. This will be accomplished through a new paradigm of proactive resiliency through "prediction, intervention and adaptation," as opposed to the current reactive cycle of discovery, recovery and redesign. A unique feature of the this research is the integration of engineering (electrical, industrial, civil), computer science and social science strategies for achieving resilience over the short and long term. Education is proactively integrated into this project, starting with summer STEM courses for urban middle school students and continuing at the college level with a multi-disciplinary program that uses the central metaphor of resilient communities to link a full range of distinct subjects. This approach will help broaden participation of underrepresented groups in research and substantially transform engineering and social sciences education.This research seeks to develop a comprehensive framework for designing and operating resilient communities by modeling them as partially engineered networked cyber-physical-human systems. The ultimate goal is to develop a synthesis framework for such systems, capable of guaranteeing minimum levels of performance and rapid recovery of functionality in the face of disruptions. This goal will be accomplished by recasting the problem in the context of data-driven identification and control of processes represented by dynamical graphical models, where both the nodes and interconnecting edges are dynamical systems that encapsulate the cyber-physical and human aspects of the problem. The approach allows for treating all aspects of the problem in a unified way, leveraging recent advances in optimization, networked control and agent based modeling to obtain scalable, computationally tractable solutions. Salient features of this framework include the integration of agent based modeling of human responses into a chance constrained optimization framework that identifies strategies to optimize resilience, the use of data driven models to extract actionable information from extremely large data sets, and purposeful manipulation of system-wide components, enabled by novel fuse-based design techniques. The resulting framework will be tested using a scenario involving four systems critical to maintaining minimum levels of emergency medicine: power, communications, critical goods supply chain and built environment.