CRISP 2.0 Type 2: Collaborative Research: Integrated Socio-Technical Modeling Framework to Evaluate and Enhance Resiliency in Islanded Communities (ERIC)

CRISP 2.0 类型 2：协作研究：评估和增强岛屿社区复原力的综合社会技术建模框架 (ERIC)

• 批准号: 2317990
• 负责人: Jorge Gonzalez
• 金额: $ 163.09万
• 依托单位: SUNY at Albany
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2022
• 资助国家: 美国
• 起止时间: 2022-12-15 至 2024-08-31
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=2317990&HistoricalAwards=false
• 关键词: CRISP; 2.0; Type; Collaborative; Research

Recent catastrophic events in the coastal tropics and sub-tropics highlight the impact of the interdependencies of critical infrastructure systems and how those interdependencies cause failures of physical assets, leading to adverse impacts on the health and socio-economic wellbeing of the communities in those regions. Islanded communities, defined as remote, self-contained regions, with low or intermittent physical (or cyber) connectivity, are especially vulnerable to natural disasters. A recent example is the extraordinary case of the island of Puerto Rico (PR), in the direct path of Hurricane Maria, and the near total failure of lifeline infrastructures. This event also exemplifies how extreme events compound endemic physical, social and economic vulnerabilities often present in remote or isolated communities. The associated cascading impacts, prior to and after Hurricane Maria, are clear evidence of our limited knowledge and readiness to anticipate risks in these complex engineered, physical and human systems. This reveals the urgent need to develop scientific and social frameworks and methodologies by which islanded communities can assess their existing preparedness to extreme climatic events, and through a multi-stakeholder engagement process and engineering analysis, evaluate and implement alternative measures to enhance the resiliency of such communities. Using PR as the case study, this Critical Resilient Interdependent Infrastructure Systems and Processes (CRISP) project will develop a data-driven modeling framework for understanding the complex physical and social vulnerabilities, and interdependencies that can and have resulted in near total failure of infrastructure systems.The research questions that will be addressed include: a) How do socio-economic stability, governance and baseline conditions of infrastructure impact performance and resiliency of critical interdependent infrastructure systems in extreme weather conditions? b) What knowledge and methods are needed to guide strategies for enhancing system resiliency and restoration in islanded communities? c) How can experts and stakeholders be engaged and informed about enhancing resiliency and effective failure mitigation strategies? The plan to achieve these objectives is by first implementing a data-driven process of gathering human narratives as social data and a source of information to recreate the timeline and experience of Hurricane Maria, before, during and after the event. Next, the project team will develop an integrated modeling and simulation framework, based on multi-layer distribution network theory. This framework will include structural-based assessment results in the modeling of infrastructure behavior during and after a disaster. The focus of study will be on the interdependencies of the electrical power, water distribution and communications systems. An objective is to recreate, via simulation, the event using a combination of system network models, geophysical data, and community data, to capture the sequence of the cascading failures and the corresponding societal impact as the event unfolded and during post-event recovery efforts. The project team seeks to arrive at a level of understanding of this system of systems that will lead to informed solutions and recommendations that will minimize adverse impact, disruption, loss of life and suffering, in the face of future extreme events. The research builds on a wealth of expertise in weather and climate processes in the Caribbean, understanding of local critical infrastructure, experience in mining community narrative, and from proven methodologies for rebuilding resilient communities in post-Hurricane Sandy in the New York and New Jersey Metro Area.This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.

最近在沿海热带和亚热带地区发生的灾难性事件凸显了关键基础设施系统相互依赖性的影响，以及这些相互依赖性如何导致实物资产故障，从而对这些地区社区的健康和社会经济福祉产生不利影响。岛屿社区被定义为偏远、自给自足的地区，物理（或网络）连接水平低或间歇性，特别容易受到自然灾害的影响。最近的一个例子是波多黎各岛（PR）的特殊案例，该岛位于飓风玛丽亚的直接路径上，生命线基础设施几乎完全瘫痪。这一事件还体现了极端事件如何加剧偏远或孤立社区中经常存在的地方性物理、社会和经济脆弱性。飓风玛丽亚之前和之后相关的连锁影响清楚地表明，我们对这些复杂的工程、物理和人类系统中的风险的预测和准备能力有限。这表明迫切需要制定科学和社会框架和方法，使岛屿社区能够评估其对极端气候事件的现有准备情况，并通过多方利益相关者参与过程和工程分析，评估和实施替代措施，以增强此类事件的抵御能力。社区。以 PR 作为案例研究，这个关键弹性相互依赖基础设施系统和流程 (CRISP) 项目将开发一个数据驱动的建模框架，用于了解复杂的物理和社会脆弱性以及可能导致基础设施系统几乎完全故障的相互依赖关系将解决的研究问题包括： a) 基础设施的社会经济稳定性、治理和基线条件如何影响极端天气条件下关键的相互依赖的基础设施系统的性能和弹性？ b) 需要哪些知识和方法来指导增强岛屿社区系统弹性和恢复的战略？ c) 专家和利益相关者如何参与并了解增强弹性和有效的故障缓解策略？实现这些目标的计划是首先实施一个数据驱动的流程，收集人类叙述作为社交数据和信息源，以重建飓风玛丽亚事件之前、期间和之后的时间线和经历。接下来，项目团队将开发基于多层配电网络理论的集成建模和仿真框架。该框架将包括灾难期间和灾难后基础设施行为建模中基于结构的评估结果。研究的重点将是电力、供水和通信系统的相互依赖性。目标是通过模拟，结合系统网络模型、地球物理数据和社区数据来重建事件，以捕获级联故障的顺序以及事件展开时和事件后恢复工作期间相应的社会影响。项目团队力求对这个系统系统有一定程度的了解，从而提出明智的解决方案和建议，从而在未来发生极端事件时最大限度地减少不利影响、破坏、生命损失和痛苦。该研究建立在加勒比地区天气和气候过程方面丰富的专业知识、对当地关键基础设施的了解、采矿社区叙述的经验以及纽约和新泽西州飓风桑迪后重建弹性社区的行之有效的方法基础上领域。该奖项反映了 NSF 的法定使命，并通过使用基金会的智力价值和更广泛的影响审查标准进行评估，被认为值得支持。

项目成果

A socio-technical approach for the assessment of critical infrastructure system vulnerability in extreme weather events

评估极端天气事件中关键基础设施系统脆弱性的社会技术方法

• DOI: 10.1038/s41560-023-01315-7
• 发表时间: 2023
• 期刊: Nature Energy
• 影响因子: 56.7
• 作者: Montoya-Rincon, Juan P.;Mejia-Manrique, Said A.;Azad, Shams;Ghandehari, Masoud;Harmsen, Eric W.;Khanbilvardi, Reza;Gonzalez-Cruz, Jorge E.
• 通讯作者: Gonzalez-Cruz, Jorge E.

Evaluation of Power Transmission Lines Hardening Scenarios Using a Machine Learning Approach

使用机器学习方法评估输电线路加固场景

• DOI: 10.1115/1.4063012
• 发表时间: 2023
• 期刊: Part B: Mechanical Engineering
• 作者: Montoya-Rincon, Juan P.;Gonzalez-Cruz, Jorge E.;Jensen, Michael P.
• 通讯作者: Jensen, Michael P.