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CRISP Type 2: Interdependent Network-based Quantification of Infrastructure Resilience (INQUIRE)

CRISP 类型 2：基于相互依赖网络的基础设施弹性量化（查询）

基本信息

批准号：
1735505
负责人：
Albert-Laszlo Barabasi
金额：
$ 250万
依托单位：
Northeastern 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：
2017-09-01 至 2022-02-28
项目状态：
已结题

来源：
https://www.nsf.gov/awardsearch/showAward?AWD_ID=1735505&HistoricalAwards=false
关键词：
CRISP Type Interdependent Network based

项目摘要

Critical infrastructure systems are increasingly reliant on one another for their efficient operation. This research will develop a quantitative, predictive theory of network resilience that takes into account the interactions between built infrastructure networks, and the humans and neighborhoods that use them. This framework has the potential to guide city officials, utility operators, and public agencies in developing new strategies for infrastructure management and urban planning. More generally, these efforts will untangle the roles of network structure and network dynamics that enable interdependent systems to withstand, recover from, and adapt to perturbations. This research will be of interest to a variety of other fields, from ecology to cellular biology.The project will begin by cataloging three built infrastructures and known interdependencies (both physical and functional) into a "network of networks" representation suitable for modeling. A key part of this research lies in also quantifying the interplay between built infrastructure and social systems. As such, the models will incorporate community-level behavioral effects through urban "ecometrics" -- survey-based empirical data that capture how citizens and neighborhoods utilize city services and respond during emergencies. This realistic accounting of infrastructure and its interdependencies will be complemented by realistic estimates of future hazards that it may face. The core of the research will use network-based analytical and computational approaches to identify reduced-dimensional representations of the (high-dimensional) dynamical state of interdependent infrastructure. Examining how these resilience metrics change under stress to networks at the component level (e.g. as induced by inundation following a hurricane) will allow identification of weak points in existing interdependent infrastructure. The converse scenario--in which deliberate alterations to a network might improve resilience or hasten recovery of already-failed systems--will also be explored.

关键基础设施系统的有效运作日益相互依赖。这项研究将开发一种定量的、预测性的网络弹性理论，该理论将考虑到已建成的基础设施网络与使用它们的人类和社区之间的相互作用。该框架有可能指导城市官员、公用事业运营商和公共机构制定基础设施管理和城市规划的新战略。更一般地说，这些努力将解开网络结构和网络动态的作用，使相互依赖的系统能够承受，恢复和适应扰动。这项研究将对从生态学到细胞生物学的各种其他领域产生兴趣。该项目将开始，将三个已建成的基础设施和已知的相互依赖性（物理和功能）编目为适合建模的“网络的网络”表示。这项研究的一个关键部分在于量化基础设施和社会系统之间的相互作用。因此，这些模型将通过城市“生态计量学”（基于调查的经验数据，捕捉公民和社区如何利用城市服务和在紧急情况下作出反应）纳入社区一级的行为影响。对基础设施及其相互依存关系的现实核算将辅之以对基础设施未来可能面临的危险的现实估计。研究的核心将使用基于网络的分析和计算方法来识别相互依赖的基础设施的（高维）动态状态的降维表示。研究这些弹性指标在组件级别的网络压力下如何变化（例如飓风后的洪水），将有助于确定现有相互依赖基础设施的弱点。也将探讨匡威的情况-对网络的故意改变可能会提高复原力或加速已经失败的系统的恢复。

项目成果

期刊论文数量（39）

专著数量（0）

科研奖励数量（0）

会议论文数量（0）

专利数量（0）

A Framework for Deep Learning Emulation of Numerical Models With a Case Study in Satellite Remote Sensing

DOI：
10.1109/tnnls.2022.3169958
发表时间：
2019-10
期刊：
IEEE Transactions on Neural Networks and Learning Systems
影响因子：
10.4
作者：
Kate Duffy;T. Vandal;Weile Wang;R. Nemani;A. Ganguly
通讯作者：
Kate Duffy;T. Vandal;Weile Wang;R. Nemani;A. Ganguly

Data Science for Weather Impacts on Crop Yield

DOI：
10.3389/fsufs.2020.00052
发表时间：
2020-05-19
期刊：
FRONTIERS IN SUSTAINABLE FOOD SYSTEMS
影响因子：
4.7
作者：
Konduri, Venkata Shashank;Vandal, Thomas J.;Ganguly, Auroop R.
通讯作者：
Ganguly, Auroop R.

Resilience of Urban Transport Network-of-Networks under Intense Flood Hazards Exacerbated by Targeted Attacks

DOI：
10.1038/s41598-020-66049-y
发表时间：
2020-06-25
期刊：
SCIENTIFIC REPORTS
影响因子：
4.6
作者：
Yadav, Nishant;Chatterjee, Samrat;Ganguly, Auroop R.
通讯作者：
Ganguly, Auroop R.

From residence to movement: The nature of racial segregation in everyday urban mobility

DOI：
10.1177/0042098020978965
发表时间：
2021-02-10
期刊：
URBAN STUDIES
影响因子：
4.7
作者：
Candipan, Jennifer;Phillips, Nolan Edward;Small, Mario
通讯作者：
Small, Mario

Robustness of interdependent geometric networks under inhomogeneous failures

DOI：
10.23919/wiopt.2018.8362877
发表时间：
2018-05
期刊：
2018 16th International Symposium on Modeling and Optimization in Mobile, Ad Hoc, and Wireless Networks (WiOpt)
影响因子：
0
作者：
Khashayar Kamran;Jianan Zhang;E. Yeh;E. Modiano
通讯作者：
Khashayar Kamran;Jianan Zhang;E. Yeh;E. Modiano