RII Track-2 FEC: Artificial Intelligence on Sustainable Energy Infrastructure Network (AI SUSTEIN) and Beyond towards Industries of the Future
RII Track-2 FEC: Artificial Intelligence on Sustainable Energy Infrastructure Network (AI SUSTEIN) and Beyond towards Industries of the Future
批准号:
2119691
负责人:
Ying Huang
金额:
$597.75万
依托单位国家:
美国
项目类别:
Cooperative Agreement
财政年份:
2021
资助国家:
美国
项目状态:
未结题
起止时间:
2021-10-01 至 2025-09-30
中文摘要
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英文摘要
A sustainable energy supply is a critical driver for our nation’s continued industrial and economic growth. Therefore, it is necessary to make current and future energy infrastructures more responsive and resilient. This Research Infrastructure Improvement Track-2 Focused EPSCoR Collaborations (RII Track-2 FEC) award, led by North Dakota State University with collaborators: University of Arkansas - Fayetteville, University of Nevada - Las Vegas, and Nueta Hidatsa Sahnish College, aims to enhance technological progress and economic growth of the jurisdiction states and the nation, while creating a new generation of workforce ready for the era of AI. The unique challenges faced by the jurisdiction states, including dispersed populations, extreme weather conditions, weak positions in energy networks and/or agriculture-based economies, motivate the team to explore an AI-based framework capable of identifying the vulnerable elements in the energy and related infrastructure networks, quantifying the health of the energy infrastructure, and providing automated resilience strategies against the impacts of catastrophic failures for a secured energy supply. This project will overcome critical regional and national issues related to vulnerable energy systems by creating holistic solutions against the negative impacts of energy disruptions on complex interdependent infrastructure networks via the exploration of innovative AI, engineering, economics, and operations research methodologies. The interdisciplinary team, consisting of experts in industrial engineering, civil and environmental engineering, computer science (especially AI), electrical engineering (especially power systems), public policy and economics, will explore the related methodologies that will be widely disseminated and implemented in a broad cross-section of industries where AI can contribute. The collaborative effort will promote AI as an industry of the future and generate immediate tangible impacts on industries in desperate need of an AI-proficient workforce by offering an AI-related associate degree and minor programs. The team will also support early career faculty, postdocs, graduate and undergraduate students, especially Native American and Hispanic participants from tribal and minority serving institutions. The intellectual merit goal of the Artificial Intelligence on Sustainable Energy Infrastructure Network (AI SUSTEIN) is to establish a collaborative research program to investigate the potential of AI as a driving force for bringing about radical changes to critical infrastructures and industries. AI SUSTEIN will conduct the following research activities: (1) understand and quantify the interdependency in infrastructure networks and perform risk and economic impact assessment on both the industrial and economic aspects using AI; (2) develop a decentralized AI-based health monitoring and failure prediction system of energy infrastructure using real-time data; and (3) create a strategic framework for improving the resilience of energy infrastructure and local industries via AI-enhanced maintenance planning, optimization, and decision-making. The broader impact goals of AI SUSTEIN are to 1) serve as a vital source of information and resources; 2) partner with all the stakeholders especially industries to ultimately form a research center in AI and data analytics, and 3) develop diverse workforce and empower them with necessary AI skills. AI SUSTEIN will engage in the following workforce development/educational efforts: (1) develop an interdisciplinary team-taught course on AI and data analytics in critical infrastructure and provide research training to students from tribal and minority serving institutions; (2) mentor and support junior faculty; (3) create and offer a technical assistance program for infrastructure industry on AI and big data approaches for real-time condition monitoring, maintenance planning, and reliability issues and partner with the industries to secure their commitment and support for establishing an NSF Industry-University Cooperative Research Center; and (4) facilitate and coordinate the formation of an associate degree program on AI at a tribal college and offer an AI minor at the participating universities.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.
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DOI:
10.1109/bigdata55660.2022.10020610
发表时间:
2022-12
期刊:
2022 IEEE International Conference on Big Data (Big Data)
影响因子:
--
作者:
[Karuna Bhaila;Yongkai Wu;Xintao Wu]
通讯作者:
Karuna Bhaila;Yongkai Wu;Xintao Wu
Performance Evaluation of Bifacial PV Systems in Distribution Networks Operation: A CVR Study Considering Smart PV Inverter Control
双面光伏系统在配电网运行中的性能评估:考虑智能光伏逆变器控制的 CVR 研究
DOI:
10.1109/naps56150.2022.10012205
发表时间:
2022
期刊:
2022 North American Power Symposium (NAPS
影响因子:
--
作者:
[Ahanch, Mojtaba, Rouholamini, Mahdi, McCann, Roy, Wang, Caisheng]
通讯作者:
Wang, Caisheng
DOI:
10.1117/12.2665241
发表时间:
2023-06
期刊:
影响因子:
--
作者:
[Luyang Xu;Shuomang Shi;Xingyu Wang;Fei Yan;Ying Huang]
通讯作者:
Luyang Xu;Shuomang Shi;Xingyu Wang;Fei Yan;Ying Huang
DOI:
10.1061/9780784484876.023
发表时间:
2023-06
期刊:
International Conference on Transportation and Development 2023
影响因子:
--
作者:
[Melika Ansarinejad;Ying Huang;Aaron Qiu]
通讯作者:
Melika Ansarinejad;Ying Huang;Aaron Qiu
DOI:
10.3390/su15064953
发表时间:
2023-03
期刊:
Sustainability
影响因子:
3.9
作者:
[Yasir Mahmood;Tanzina Afrin;Ying Huang;Nita Yodo]
通讯作者:
Yasir Mahmood;Tanzina Afrin;Ying Huang;Nita Yodo
共 14 条
CAREER: Intelligent Corrosion Mitigation System of Steel Structures with Duplex Coating
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批准号:1750316
-
项目类别:Standard Grant
-
资助金额:$50.0万
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财政年份:2018
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负责人:Ying Huang
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依托单位:
Mathematical Sciences: Studies in Linear and Nonlinear Analysis
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批准号:9410557
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项目类别:Standard Grant
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资助金额:$1.75万
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财政年份:1994
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负责人:Ying Huang
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依托单位:
海外基金