CRISP Type 1/Collaborative Research: Population-Infrastructure Nexus: A Heterogeneous Flow-based Approach for Responding to Disruptions in Interdependent Infrastructure Systems

CRISP 类型 1/协作研究：人口-基础设施关系：一种基于异构流的方法，用于响应相互依赖的基础设施系统的中断

• 批准号: 1541136
• 负责人: Guangqing Chi
• 金额: $ 15万
• 依托单位: Pennsylvania State Univ University Park
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2016
• 资助国家: 美国
• 起止时间: 2016-01-01 至 2018-12-31
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=1541136&HistoricalAwards=false
• 关键词: CRISP; Type; Collaborative; Research; Population

Reducing the instability and vulnerability of our nation's critical and complex population-infrastructure system is essential for a more efficient, resilient, and vital society. Recent catastrophic events, such as the Northeast Blackout of 2003 and Hurricane Sandy in 2012, shut down or interrupted essential and interdependent components of our national infrastructure, such as electric networks, fuel supplies, and transportation systems. This vulnerability is exacerbated by changing population dynamics. Those dynamics impose serious challenges to the capacity of the individual components of our infrastructure system to efficiently respond to both moderate disturbances and extreme events. The ultimate goal of this Critical Resilient Interdependent Infrastructure Systems and Processes (CRISP) collaborative research project is to increase the resilience of the interdependent population-infrastructure system during disturbances of various magnitudes (including operational uncertainties and disastrous disruptions). This research will benefit infrastructure system planning and operations by developing "smart communities/cities" where multiple stakeholders can work together to promote mutual interests. This research will also develop innovative educational and training modules to give future generations and practitioners a vision of efficient, resilient and socially vital built environments and means to approach it. Overall, the outcome of this interdisciplinary research will benefit society through energy savings and economic enhancement by means of better infrastructure design and communication systems.The purpose of this interdisciplinary research is to develop a distributed heterogeneous flow-based modeling framework to quantify the critical and complex interdependence of multiple infrastructure systems and population groups. The framework will also assist in analyzing short-term mobility behaviors and long-term social and demographic evolution of the critical connection between population and infrastructure. These objectives will be achieved by: 1) quantifying the interactions of different demographic groups with multiple infrastructures, 2) characterizing infrastructure facilities in several interconnected yet diverse systems, 3) modeling and optimizing the interdependent population-infrastructure system in a self-organized distributed system in which various infrastructure and population agents communicate on a cyber-platform, and 4) analyzing the important theoretical properties of this integrated model (e.g., system equilibrium and stability). This research makes three key intellectual contributions. First, a heterogeneous-flow-based network modeling method will define the dynamics and equilibria of several interdependent infrastructure systems. Second, the infrastructure model in a nexus with population characteristics allows examination of the two-way interactions between heterogeneous infrastructure facilities and different population groups. Third, this model will be integrated with a distributed cyber-communication platform based on self-organized "swarm intelligence" to create a realistic system in which multiple parties behave autonomously by communicating their respective available information.

减少我们国家关键而复杂的人口基础设施系统的不稳定性和脆弱性，对于一个更高效、更有弹性和更有活力的社会至关重要。最近的灾难性事件，如2003年的东北停电和2012年的飓风桑迪，关闭或中断了我们国家基础设施的重要和相互依赖的组成部分，如电力网络，燃料供应和运输系统。人口动态的变化加剧了这种脆弱性。这些动态对我国基础设施系统各个组成部分有效应对中度扰动和极端事件的能力构成严重挑战。这个关键的弹性相互依赖的基础设施系统和过程（CRISP）合作研究项目的最终目标是提高相互依赖的人口基础设施系统在各种程度的干扰（包括运营不确定性和灾难性中断）的弹性。这项研究将有利于基础设施系统的规划和运营，通过开发“智能社区/城市”，多个利益相关者可以共同努力，促进共同利益。这项研究还将开发创新的教育和培训模块，为子孙后代和从业者提供高效、有弹性和对社会至关重要的建筑环境的愿景以及实现这一目标的方法。总体而言，这项跨学科研究的成果将通过更好的基础设施设计和通信系统来节省能源和提高经济效益，造福社会。这项跨学科研究的目的是开发一种分布式异构基于流的建模框架，以量化多个基础设施系统和人口群体的关键和复杂的相互依赖性。该框架还将有助于分析人口与基础设施之间关键联系的短期流动行为以及长期社会和人口演变。这些目标将通过以下方式实现：1）量化不同人口群体与多个基础设施的相互作用，2）表征若干互连但不同的系统中的基础设施设施，3）在自组织分布式系统中建模和优化相互依赖的人口基础设施系统，其中各种基础设施和人口代理在网络平台上通信，以及4）分析该集成模型的重要理论特性（例如，系统平衡与稳定性）。这项研究做出了三个关键的智力贡献。首先，基于异质流的网络建模方法将定义几个相互依赖的基础设施系统的动态和平衡。第二，在一个与人口特征的关系的基础设施模型允许检查异构基础设施和不同的人口群体之间的双向互动。第三，该模型将与基于自组织“群体智能”的分布式网络通信平台相结合，以创建一个现实的系统，在该系统中，多方通过交流各自的可用信息自主行事。

项目成果

Evaluating the Representativeness in the Geographic Distribution of Twitter User Population

评估 Twitter 用户群体地理分布的代表性

• DOI: 10.1145/3281354.3281360
• 发表时间: 2018
• 期刊: ACM SIGSPATIAL
• 作者: Yin, Junjun;Chi, Guangqing;Van Hook, Jennifer
• 通讯作者: Van Hook, Jennifer

Intercity Passenger Rails: Facilitating the Spatial Spillover Effects of Population and Employment Growth in the United States, 2000–2010

城际客运铁路：促进美国人口和就业增长的空间溢出效应，2000 年至 2010 年

• DOI: 10.1061/(asce)up.1943-5444.0000477
• 发表时间: 2018
• 期刊: Journal of Urban Planning and Development
• 影响因子: 2.5
• 作者: Kasu, Bishal Bhakta;Chi, Guangqing
• 通讯作者: Chi, Guangqing

Neighbourhood built environment and walking behaviours: Evidence from the rural American South

社区建筑环境和步行行为：来自美国南部农村的证据

• DOI: 10.1177/1420326x17695858
• 发表时间: 2017
• 期刊: Indoor and Built Environment
• 影响因子: 3.6
• 作者: Li, Chuo;Chi, Guangqing;Jackson, Robert
• 通讯作者: Jackson, Robert

A multi-modal approach towards mining social media data during natural disasters - a case study of Hurricane Irma

• DOI: 10.1016/j.ijdrr.2020.102032
• 发表时间: 2021-01
• 期刊: International journal of disaster risk reduction : IJDRR
• 作者: S. Mohanty;B. Biggers;S. SayedAhmed;Nastaran Pourebrahim;E. Goldstein;Rick L. Bunch;G. Chi;F. Sadri;Tom P. McCoy;A. Cosby

Park access affects physical activity: new evidence from geolocated Twitter data analysis

• DOI: 10.1080/13574809.2022.2118698
• 发表时间: 2022-09
• 期刊: Journal of Urban Design
• 影响因子: 2.1
• 作者: Chuo Li;Jing Zhao;Junjun Yin;G. Chi