Experimentally Validated Stochastic Numerical Framework to Generate Multi-Dimensional Fragilities for Hurricane Resilience Enhancement of Transmission Systems

经过实验验证的随机数值框架可生成多维脆弱性以增强传输系统的飓风弹性

• 批准号: 1635569
• 负责人: Abdollah Shafieezadeh
• 金额: $ 52.98万
• 依托单位: Ohio State University
• 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: 2016-08-01 至 2021-07-31
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=1635569&HistoricalAwards=false
• 关键词: Experimentally; Validated; Stochastic; Numerical; Framework

The electric power transmission infrastructure in the United States, especially in coastal areas, faces substantial risk from hurricanes. Considering the significant size of the transmission grid, the cost of upgrading the entire infrastructure to achieve acceptable performance levels against hurricanes would be extremely high. The objective of this research is to investigate a framework to reliably identify vulnerable transmission line systems and provide cost-effective retrofit solutions to reduce their likelihood of damage and loss of functionality during hurricanes and their recovery time following the event. For this purpose, this project will develop multi-dimensional fragility models for transmission tower-line systems using experimentally validated numerical models. This will enable characterization of the effects of various significant factors on the wind performance of these systems. Outcomes of this research will aid in minimizing societal disruptions due to loss of functioning of critical infrastructure and facilities caused by power outages. The project will actively engage stakeholders to facilitate technology transfer and implementation of novel design and retrofit solutions for transmission systems. The research findings will be integrated into courses at Ohio State University and Florida International University (FIU). In addition, underrepresented undergraduate and K-8 students will be trained in research on infrastructure systems to prepare the next generation of engineers to enhance the hurricane resilience of communities.The research will produce a state-of-the-art experimentally validated stochastic numerical framework to generate multi-dimensional fragility models for hurricane resilience enhancement of transmission systems. The research will involve a series of aeroelastic wind tunnel studies on the wind response of multi-span transmission systems at the National Science Foundation-supported Natural Hazards Engineering Research Infrastructure Wall of Wind (WOW) Experimental Facility at FIU. These novel sets of experimental data, together with high-fidelity three-dimensional nonlinear finite element models of tower-conductor-insulator-foundation systems, will provide new and critical insights into various complex wind-induced behaviors of these systems. The WOW tests will also enable characterization of dynamic boundary effects from neighboring spans. The multi-dimensional fragility surfaces, based on validated numerical models, will provide component- and system-level structural and functional failure probabilities for units of transmission tower-lines. The generated reliability models, combined with recovery models, will be integrated into optimization frameworks to provide optimal design and retrofit solutions based on hazard and environmental factors, which will facilitate optimal management of transmission systems against hurricane hazards to enhance their resilience in response to extreme events.

美国的电力传输基础设施，特别是沿海地区的电力传输基础设施，面临着飓风的巨大风险。考虑到输电网的巨大规模，升级整个基础设施以达到可接受的飓风性能水平的成本将非常高。本研究的目的是研究一个框架，以可靠地识别脆弱的输电线路系统，并提供具有成本效益的改造解决方案，以减少飓风期间损坏和功能丧失的可能性，以及飓风过后的恢复时间。为此，本项目将利用实验验证的数值模型为输电塔线系统开发多维脆弱性模型。这将使表征对这些系统的风力性能的各种重要因素的影响。这项研究的结果将有助于最大限度地减少因停电造成的关键基础设施和设施功能丧失而造成的社会破坏。该项目将积极吸引利益相关者参与，促进技术转让和实施输电系统的新设计和改造解决方案。研究结果将被纳入俄亥俄州立大学和佛罗里达国际大学（FIU）的课程。此外，代表性不足的本科生和K-8学生将接受基础设施系统研究方面的培训，以培养下一代工程师，提高社区的飓风抵御能力。该研究将产生一个最先进的实验验证的随机数值框架，为增强输电系统的飓风恢复能力生成多维脆弱性模型。该研究将涉及在美国国家科学基金会支持的自然灾害工程研究基础设施风墙（WOW）实验设施中对多跨传输系统的风响应进行一系列气动弹性风洞研究。这些新颖的实验数据集，以及高保真的塔-导体-绝缘子-基础系统的三维非线性有限元模型，将为这些系统的各种复杂风致行为提供新的和关键的见解。WOW测试还将能够表征来自相邻跨度的动态边界效应。基于验证数值模型的多维脆弱性曲面将为输电塔线路单元提供组件和系统级结构和功能失效概率。生成的可靠性模型与恢复模型相结合，将集成到优化框架中，以提供基于危害和环境因素的最佳设计和改造解决方案，这将促进传输系统对飓风危害的最佳管理，以增强其对极端事件的响应能力。

项目成果

Value of Information Analysis via Active Learning and Knowledge Sharing in Error-Controlled Adaptive Kriging

• DOI: 10.1109/access.2020.2980228
• 发表时间: 2020-02
• 期刊: IEEE Access
• 影响因子: 3.9
• 作者: Chi Zhang;Zeyu Wang;A. Shafieezadeh

Wind Reliability of Transmission Line Models using Kriging-Based Methods

• DOI: 10.22725/icasp13.211
• 发表时间: 2019-05
• 作者: Y. Darestani;Zeyu Wang;A. Shafieezadeh

Intelligent hurricane resilience enhancement of power distribution systems via deep reinforcement learning

• DOI: 10.1016/j.apenergy.2020.116355
• 发表时间: 2021-03
• 期刊: Applied Energy
• 影响因子: 11.2
• 作者: Nariman L. Dehghani;Ashkan B. Jeddi;A. Shafieezadeh

Error Quantification and Control for Adaptive Kriging-Based Reliability Updating with Equality Information

• DOI: 10.1016/j.ress.2020.107323
• 发表时间: 2021-03
• 期刊: Reliab. Eng. Syst. Saf.
• 作者: Chi Zhang-;Zeyu Wang;A. Shafieezadeh

Effect of modelling complexities on extreme wind hazard performance of steel lattice transmission towers

• DOI: 10.1080/15732479.2019.1673783
• 发表时间: 2020-06
• 期刊: Structure and Infrastructure Engineering
• 影响因子: 3.7
• 作者: Yousef Mohammadi Darestani;A. Shafieezadeh;Kyunghwa Cha