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

城市化的步伐不断加快，特别是沿着城市化的步伐，加上基础设施不健全，相互依存关系知之甚少，将使重大天气事件在不久的将来更有可能演变成灾害，而海洋变暖和海平面上升又加剧了这种情况。超级风暴桑迪为这种情况提供了一个特别尖锐的例子。这项关键弹性相互依赖基础设施系统和流程（CRISP）第2类赠款将开创一种新方法，使社区能够承受灾害并迅速从灾害中恢复过来。这将通过“预测、干预和适应”的积极复原力新模式来实现，而不是目前的发现、恢复和重新设计的被动循环。这项研究的一个独特之处是工程（电气，工业，民用），计算机科学和社会科学战略的整合，以实现短期和长期的弹性。教育被积极地融入到这个项目中，从城市中学生的夏季STEM课程开始，并在大学一级继续进行多学科课程，该课程使用弹性社区的中心隐喻来连接各种不同的学科。这一方法将有助于扩大代表性不足的群体在研究中的参与，并大大改变工程和社会科学education.This研究旨在开发一个全面的框架，设计和运营弹性社区建模为部分工程网络的网络物理人类系统。最终目标是为这些系统制定一个综合框架，能够保证最低水平的性能，并在出现中断时迅速恢复功能。这一目标将通过在动态图形模型所代表的过程的数据驱动的识别和控制的背景下重铸问题来实现，其中节点和互连边缘都是封装问题的网络物理和人类方面的动态系统。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的最新进展，以获得可扩展的，计算上易于处理的解决方案。该框架的突出特点包括集成的代理人为基础的建模的人类反应到一个机会约束优化框架，确定战略，以优化弹性，使用数据驱动的模型，以提取可操作的信息，从非常大的数据集，和有目的的操纵系统范围内的组件，使新的基于保险丝的设计技术。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水平的紧急医疗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.