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EAGER: SSDIM: Ensembles of Interdependent Critical Infrastructure Networks

EAGER：SSDIM：相互依赖的关键基础设施网络的集合

基本信息

批准号：
1927791
负责人：
Madhav Marathe
金额：
$ 11.87万
依托单位：
University of Virginia Main Campus
依托单位国家：
美国
项目类别：
Standard Grant
财政年份：
2019
资助国家：
美国
起止时间：
2019-02-21 至 2022-08-31
项目状态：
已结题

来源：
https://www.nsf.gov/awardsearch/showAward?AWD_ID=1927791&HistoricalAwards=false
关键词：
EAGER SSDIM Ensembles Interdependent Critical

项目摘要

The need to represent and analyze socially coupled interdependent infrastructure networks poses significant scientific and technical challenges. A central challenge is the lack of realistic data sets that represent the networks, their interactions, and the points of connection with consumers. This EArly-concept Grant for Exploratory Research (EAGER) project will develop ensembles of such coupled systems, along with methods to assess concerns of data quality and validity. Ensembles of coupled power and communication networks will provide realistic data for algorithm development. The tools and techniques developed under the project will also be disseminated to the broader community of analysts and researchers interested in the science and engineering of complex networks. The work will result in unique open-access realistic data sets for the academic and other interested communities. This project will develop mathematical techniques and associated algorithms for generating ensembles of infrastructure networks and social interactions. It will also yield methods for the validation and verification of these interdependent synthetic populations and network ensembles. A key focus will be on large, realistic power and communication networks. This work will lead to highly scalable, data-driven, dynamic methods for sensitivity analysis, uncertainty quantification, and verification and validation. The research will provide data to support new ways of characterizing and assessing vulnerabilities inherent in today's societal infrastructures. The ensemble of realistic networks will facilitate the study of vulnerabilities resulting from interdependencies among infrastructures as well as from vulnerabilities and risks that result from interaction of individuals with the infrastructure as well with each other.

代表和分析社会耦合的相互依赖的基础设施网络的需要提出了重大的科学和技术挑战。一个核心挑战是缺乏代表网络、网络交互以及与消费者连接点的真实数据集。这个早期概念的探索性研究资助（EAGER）项目将开发这样的耦合系统的集合，沿着评估数据质量和有效性的方法。集成的耦合电力和通信网络将提供现实的数据算法的发展。在该项目下开发的工具和技术也将传播给对复杂网络的科学和工程感兴趣的更广泛的分析师和研究人员。这项工作将为学术界和其他感兴趣的社区提供独特的开放式现实数据集。该项目将开发数学技术和相关算法，用于生成基础设施网络和社会互动的集合。它还将产生用于验证和验证这些相互依赖的合成群体和网络集合的方法。一个关键的重点将是大型，现实的电力和通信网络。这项工作将导致高度可扩展的，数据驱动的，动态的方法，灵敏度分析，不确定性量化，以及验证和确认。这项研究将提供数据，以支持确定和评估当今社会基础设施固有脆弱性的新方法。现实网络的集合将有助于研究基础设施之间的相互依赖性所产生的脆弱性以及个人与基础设施以及相互之间的相互作用所产生的脆弱性和风险。

项目成果

期刊论文数量（4）

专著数量（0）

科研奖励数量（0）

会议论文数量（0）

专利数量（0）

SIMULATING RESIDENTIAL ENERGY DEMAND IN URBAN AND RURAL AREAS

DOI：
10.1109/wsc.2018.8632203
发表时间：
2018-12
期刊：
2018 Winter Simulation Conference (WSC)
影响因子：
0
作者：
S. Thorve;S. Swarup;A. Marathe;Youngyun Chungbaek;E. Nordberg;M. Marathe
通讯作者：
S. Thorve;S. Swarup;A. Marathe;Youngyun Chungbaek;E. Nordberg;M. Marathe

A Reliability-aware Distributed Framework to Schedule Residential Charging of Electric Vehicles

用于安排电动汽车住宅充电的可靠性感知分布式框架

DOI：
10.24963/ijcai.2022/710
发表时间：
2022
期刊：
Proceedings of the Thirty-First International Joint Conference on Artificial Intelligence
影响因子：
0
作者：
Meyur, Rounak;Thorve, Swapna;Marathe, Madhav;Vullikanti, Anil;Swarup, Samarth;Mortveit, Henning
通讯作者：
Mortveit, Henning

Two-Mode Threshold Graph Dynamical Systems for Modeling Evacuation Decision-Making During Disaster Events.

用于灾害事件期间疏散决策建模的双模式阈值图动态系统。