CRISP Type 2/Collaborative Research: Probabilistic Resilience Assessment of Interdependent Systems (PRAISys)

CRISP 类型 2/协作研究：相互依赖系统的概率弹性评估 (PRAISys)

• 批准号: 1541177
• 负责人: Paolo Bocchini
• 金额: $ 190.32万
• 依托单位: Lehigh University
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2015
• 资助国家: 美国
• 起止时间: 2015-09-01 至 2020-08-31
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=1541177&HistoricalAwards=false
• 关键词: CRISP; Type; Collaborative; Research; Probabilistic

After a disruptive extreme event, such as an earthquake or severe storm, the socio-economic recovery of the affected region depends on the recovery of its infrastructure systems. Lifelines, such as power and water distribution systems, transportation networks, communication systems, and critical buildings have a primary role in disaster response, management, and long-term recovery. The failure to rapidly restore the services required for personal, social, and commercial activities leads to continued socio-economic losses and progressive depopulation. This collaborative project brings together scholars in Civil Engineering, Systems Engineering, Computer Science, Economics, Urban Planning, and Policy Making. Its purpose is to establish and demonstrate a comprehensive framework that combines models of individual infrastructure systems with models of their interdependencies for the assessment of interdependent infrastructure system resilience for extreme events under uncertainty. The "PRAISys" platform (Probabilistic Resilience Assessment of Interdependent Systems) will emphasize a probabilistic approach that permeates all aspects of the models, including the interdependencies. Some types of uncertainties that were not considered before (e.g., the possibility of using contingency plans that provide services without functioning infrastructure) will be classified; while mathematical and computational tools will be devised to capture their characteristics. PRAISys will enable better management and design of next generation infrastructure, more resilient to extreme events and to component failures under normal conditions. This will reduce the likelihood of extreme events becoming catastrophic in terms of casualties and injuries, long-lasting socio-economic losses, and environmental impact. The results of the research will be disseminated to the public in various forms: through series of seminars for professionals and administrators; by participating in Lehigh University's STAR academy program for disadvantaged middle and high school students; through scientific publications and presentation; and by curriculum development.The development, calibration, and validation of PRAISys will enable research on stochastic interdependencies among infrastructure systems in the wake of an extreme event. This requires advancements in several disciplines. For instance, a new hybrid reliability model, which combines graph theory for network analysis and classic system reliability to model the probabilistic dependencies among infrastructures will be studied. The new concept of "uncertain dependencies," which are rigorously modeled and include "contingency plans" will be introduced. Advancements in stochastic network optimization will be sought, to predict the optimal strategies and to inform the disaster management. Social network data will be used as an additional source of information on the recovery of a region, in real time, mining public posts. A comprehensive decision framework will combine the results of the simulation platform with expert opinions and surveys to identify the importance of various aspects of recovery. Finally, new techniques for the collection of large sets of data from utility companies, local government and other authorities will be studied.

经过破坏性的极端事件，例如地震或严重风暴，受影响地区的社会经济恢复取决于其基础设施系统的恢复。电力和水分配系统，运输网络，通信系统和关键建筑物等寿命在灾难响应，管理和长期恢复中具有主要作用。未能迅速恢复个人，社会和商业活动所需的服务导致社会经济损失和逐步人口减少。这个协作项目汇集了土木工程，系统工程，计算机科学，经济学，城市规划和政策制定方面的学者。其目的是建立并展示一个综合框架，将单个基础设施系统的模型与其相互依存模型相结合，以评估相互依存的基础设施系统对不确定性下极端事件的相互依存基础设施的弹性。 “ Praisys”平台（相互依存系统的概率弹性评估）将强调一种概率方法，该方法渗透到模型的各个方面，包括相互依存关系。某些以前未考虑的不确定性（例如，使用提供服务而无需运行基础架构的服务计划的可能性）将被分类；虽然将设计数学和计算工具以捕获其特征。 Praisys将实现下一代基础架构的更好管理和设计，对极端事件和在正常条件下的组件失败更具弹性。这将减少极端事件的可能性在伤亡和伤害，持久的社会经济损失和环境影响方面变得灾难性。研究结果将以各种形式传播给公众：通过针对专业人士和管理员的一系列研讨会；通过参加利哈伊大学的《星际学院》计划，涉及处境不利的中学生和高中生；通过科学出版物和演讲；通过课程的开发，PRAISYS的开发，校准和验证将在极端事件发生后对基础设施系统之间的随机相互依赖性进行研究。这需要几个学科的进步。例如，将研究一个新的混合可靠性模型，该模型将网络分析的图理论和经典系统可靠性结合在一起，以模拟基础架构之间的概率依赖性。将引入严格建模并包括“应急计划”的“不确定依赖性”的新概念。将寻求随机网络优化的进步，以预测最佳策略并为灾难管理提供信息。社交网络数据将用作实时采矿公共帖子的区域恢复的附加信息来源。一个全面的决策框架将将模拟平台的结果与专家意见和调查结合在一起，以确定恢复各个方面的重要性。最后，将研究从公用事业公司，地方政府和其他当局收集大量数据的新技术。