CRISP Type 2/Collaborative Research: Critical Transitions in the Resilience and Recovery of Interdependent Social and Physical Networks

CRISP 类型 2/合作研究：相互依赖的社会和物理网络的弹性和恢复的关键转变

• 批准号: 1638311
• 负责人: Satish Ukkusuri
• 金额: $ 220.42万
• 依托单位: Purdue University
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2017
• 资助国家: 美国
• 起止时间: 2017-01-01 至 2022-12-31
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=1638311&HistoricalAwards=false
• 关键词: CRISP; Type; Collaborative; Research; Critical

Understanding the recovery of communities after disruptions has important implications for efficiently allocating resources, better planning for disasters, and reducing time and cost of recovery. Virtually all communities are embedded in highly interdependent social and physical infrastructure. This coupling between social and physical networks can lead to complex cascading effects that cannot be understood by looking at these networks in isolation. The full implications of these interdependencies for the resilience of communities and their ability to recover after disasters are not currently understood. This research seeks an understanding of the underlying factors that lead to resilience and recovery of interdependent social and physical networks after disasters. The researchers will collect data from communities impacted by Hurricane Sandy to create and test modeling approaches for improved knowledge of both social and physical factors that lead to recovery. It will also lead to a better understanding of the interdependencies between the social and physical systems, and will identify potential tipping points where small changes in the social and physical systems significantly impact the recovery of the overall system. The findings from the study will allow governmental and emergency agencies to take actions that will accelerate system recovery and enhance its resilience. Students and underrepresented groups working on this project will gain exposure and experience working with a multi-disciplinary research team, thereby preparing them for tackling complex, systems-related challenges in their future careers. A workshop will be organized to disseminate the findings to the scientific community and various stakeholders who are involved in recovery processes.The modeling of resilience in interdependent social and physical networks will be conducted using an interdisciplinary approach. First, the researchers will collect data pertaining to complex interdependencies that influence post-disaster recovery and decision-making. Second, the project will leverage insights gleaned from the data to identify utility functions that influence the decision-making of households, and formulate mathematical techniques based on game theory and network science for modeling and analyzing the tipping points that lead to recovery across social and physical networks. Third, the research effort will create novel state-estimation techniques using publicly available citizen data and develop multi-agent simulation models that will provide new decision-support tools for governmental agencies and emergency response organizations to model, test and predict the effects of recovery actions. The research will identify the role of network structure and function in the movement of the overall system towards better recovery states, and characterize the different events that transpire during community re-entry and recovery processes.

了解中断后社区的恢复对于有效分配资源、更好地规划灾难以及减少恢复时间和成本具有重要意义。几乎所有社区都有高度相互依存的社会和物质基础设施。社交网络和物理网络之间的这种耦合可能会导致复杂的级联效应，这些效应无法通过孤立地看待这些网络来理解。这些相互依存关系对社区的复原力及其灾后恢复能力的全面影响目前尚不清楚。这项研究旨在了解导致灾后相互依存的社会和物质网络的复原力和恢复的根本因素。研究人员将从受飓风桑迪影响的社区收集数据，以创建和测试建模方法，以改善对导致恢复的社会和物理因素的了解。它还将导致更好地理解社会和物理系统之间的相互依存关系，并将确定潜在的临界点，在那里，社会和物理系统的微小变化会对整个系统的恢复产生重大影响。研究结果将使政府和应急机构能够采取行动，加快系统恢复并增强其复原力。参与该项目的学生和代表性不足的群体将获得与多学科研究团队合作的机会和经验，从而为他们在未来的职业生涯中应对复杂的系统相关挑战做好准备。将举办一次研讨会，向科学界和参与恢复进程的各利益攸关方传播研究结果，并将采用跨学科方法，建立相互依存的社会和物理网络的复原力模型。首先，研究人员将收集有关影响灾后恢复和决策的复杂相互依赖关系的数据。其次，该项目将利用从数据中收集的见解来确定影响家庭决策的效用函数，并制定基于博弈论和网络科学的数学技术，用于建模和分析导致社会和物理网络恢复的临界点。第三，研究工作将使用公开的公民数据创建新的状态估计技术，并开发多代理仿真模型，为政府机构和应急响应组织提供新的决策支持工具，以模拟，测试和预测恢复行动的影响。该研究将确定网络结构和功能在整个系统向更好的恢复状态运动中的作用，并描述在社区重新进入和恢复过程中发生的不同事件。

项目成果

Support and barriers in long-term recovery after Hurricane Sandy: improvisation as a communicative process of resilience

桑迪飓风后长期恢复的支持和障碍：即兴创作作为复原力的沟通过程

• DOI: 10.1080/00909882.2020.1797142
• 发表时间: 2020
• 期刊: Journal of Applied Communication Research
• 影响因子: 2.3
• 作者: Lee, Seungyoon;Benedict, Bailey C.;Jarvis, Caitlyn M.;Siebeneck, Laura;Kuenanz, Britt-Janet
• 通讯作者: Kuenanz, Britt-Janet

Returning home after Superstorm Sandy: phases in the return-entry process

超级风暴桑迪后返回家园：返回过程的各个阶段

• DOI: 10.1007/s11069-020-03869-1
• 发表时间: 2020
• 期刊: Natural Hazards
• 影响因子: 3.7
• 作者: Siebeneck, Laura;Schumann, Ronald;Kuenanz, Britt-Janet;Lee, Seungyoon;Benedict, Bailey C.;Jarvis, Caitlyn M.;Ukkusuri, Satish V.
• 通讯作者: Ukkusuri, Satish V.

Understanding post-disaster population recovery patterns

• DOI: 10.1098/rsif.2019.0532
• 发表时间: 2020-02
• 期刊: Journal of the Royal Society Interface
• 影响因子: 3.9
• 作者: T. Yabe;K. Tsubouchi;N. Fujiwara;Y. Sekimoto;S. Ukkusuri

Unsupervised Translation via Hierarchical Anchoring: Functional Mapping of Places across Cities

• DOI: 10.1145/3394486.3403335
• 发表时间: 2020-07
• 期刊: Proceedings of the 26th ACM SIGKDD International Conference on Knowledge Discovery & Data Mining
• 作者: T. Yabe;K. Tsubouchi;Toru Shimizu;Y. Sekimoto;S. Ukkusuri

Quantifying the economic impact of disasters on businesses using human mobility data: a Bayesian causal inference approach

• DOI: 10.1140/epjds/s13688-020-00255-6
• 发表时间: 2020-04
• 期刊: EPJ Data Science
• 影响因子: 3.6
• 作者: T. Yabe;Yunchang Zhang;S. Ukkusuri