Collaborative Research: Downburst Fragility Characterization of Transmission Line Systems Using Experimental and Validated Stochastic Numerical Simulations

合作研究：使用实验和验证的随机数值模拟来表征传输线系统的下击暴脆性

• 批准号: 1762918
• 负责人: Abdollah Shafieezadeh
• 金额: $ 20.96万
• 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: 2018
• 资助国家: 美国
• 起止时间: 2018-08-01 至 2024-07-31
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=1762918&HistoricalAwards=false
• 关键词: Collaborative; Research; Downburst; Fragility; Characterization

Downbursts, referring to downward high intensity winds associated with thunderstorms, pose a major threat to power transmission grids in many parts of the United States. Considering the distributed size of the power transmission infrastructure, significant investments will be needed in order to upgrade the existing systems and properly design new infrastructure to resist downburst wind forces. The goal of this research is to develop an integrative experimental and numerical framework that is capable of characterizing the extent of vulnerability of the power transmission infrastructure against downbursts, and identify the most critical components. The framework will provide knowledge that can help reduce outage-induced societal disruptions caused by downbursts, and thus enable continued national prosperity and welfare following a downburst event. Using this framework, various significant factors for the downburst performance of transmission systems and potential causes of past failures will be investigated. Moreover, this research will develop the first generation of downburst fragility models for transmission tower-line systems (TLSs) using experimentally validated numerical models. These fragility models are crucial for risk-informed decision making for design and management of the transmission grid in order to mitigate future failures and enhance the resiliency of the grid against extreme weather events. The numerical and experimental studies will provide the knowledge needed to enhance design methodologies to include downburst wind loads for transmission line systems. The research findings will be integrated into undergraduate and graduate courses at Florida International University (FIU) and The Ohio State University to better prepare the future generation of infrastructure engineers. Project data will be archived and publicly shared in the NSF-supported Natural Hazards Engineering Research Infrastructure (NHERI) Data Depot (https://www.DesignSafe-ci.org/). This research will develop an integrative experimental and numerical framework to characterize the fragility of transmission line systems against downbursts. The experimental research will involve developing a versatile downburst simulator at the NSF-supported NHERI Wall of Wind (WOW) Experimental Facility (EF) at FIU. Using this simulator, a scaled, aeroelastic multi-span TLS will be tested; the results will be used to experimentally validate high-fidelity finite element models of coupled transmission tower-insulator-conductor-foundation systems. Through these experimental and numerical investigations, new knowledge will be gained with regard to the aerodynamic behavior of conductors and drag and shielding effects on lattice tower sections under non-synoptic downburst wind fields. Moreover, these investigations will reveal extreme nonlinear behaviors of transmission line systems in post-elastic regimes when towers are damaged or conductors fail. The research also will provide new physics-based insights into the role of uncertainties in the downburst performance of TLSs. Failure modes that are unique to or are more likely to occur under non-synoptic downburst loadings, as compared to those under synoptic hurricane loadings, will be identified and characterized. The produced data and models will be integrated to develop the first generation of multi-dimensional demand and fragility surfaces for TLSs under downbursts at component- and system-levels using highly efficient and accurate machine learning techniques. In addition, the experimental downburst simulator at the NHERI WOW EF at FIU will provide the natural hazards community with a unique testbed with dual simulation capabilities to generate both non-synoptic and synoptic winds and analyze the impacts on buildings and other structural systems.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.

下暴指的是与雷暴相关的向下高强度风，对美国许多地区的输电网构成重大威胁。考虑到电力传输基础设施的分布规模，将需要大量投资，以升级现有系统并适当设计新的基础设施，以抵御下暴风。这项研究的目标是开发一个综合的实验和数值框架，能够表征电力传输基础设施对下击暴流的脆弱性程度，并确定最关键的部件。该框架将提供知识，帮助减少由下击暴流造成的停电引起的社会混乱，从而使国家在下击暴流事件后继续繁荣和福利。使用该框架，将调查影响传输系统下行猝发性能的各种重要因素以及过去故障的潜在原因。此外，本研究将利用经过实验验证的数值模型来开发第一代输电塔-线路系统(TLSS)的下击暴流易损性模型。这些脆弱性模型对于输电电网设计和管理的风险决策至关重要，以减少未来的故障并增强电网对极端天气事件的弹性。数值和实验研究将提供必要的知识，以改进设计方法，以包括输电线路系统的下击暴风荷载。研究成果将被整合到佛罗里达国际大学(FIU)和俄亥俄州立大学的本科和研究生课程中，以更好地培养未来一代基础设施工程师。项目数据将在国家科学基金会支持的自然灾害工程研究基础设施(NHERI)数据仓库(https://www.DesignSafe-ci.org/).)中存档并公开共享这项研究将开发一个综合的实验和数值框架，以表征输电线路系统对下击暴流的脆弱性。实验研究将包括在美国国家科学基金会支持的NSF支持的NHERI风墙(WOW)实验设施(EF)上开发一个通用的下击暴流模拟器。利用该模拟器对一个比例的气动弹性多跨TLS进行了试验，试验结果将用于验证输电塔-绝缘子-导体-地基耦合系统的高保真有限元模型。通过这些实验和数值研究，将对非天气下击暴流风场中导线的气动行为以及格构塔截面上的阻力和屏蔽效应有新的认识。此外，这些研究还将揭示输电线路系统在杆塔损坏或导线失效时在后弹性区域的极端非线性行为。这项研究还将提供基于物理的新见解，以了解不确定因素在TLSS下击暴流性能中的作用。将确定和描述在非天气下击暴流加载下，与天气飓风加载相比，在非天气下击暴流加载下发生的或更有可能发生的故障模式。所产生的数据和模型将被整合起来，利用高效和准确的机器学习技术，在部件和系统层面上为下暴流下的TLSS开发第一代多维需求和脆弱性表面。此外，FIU NHERI WOW EF的实验下击暴流模拟器将为自然灾害社区提供一个独特的试验台，具有生成非天气风和天气风并分析对建筑和其他结构系统的影响的双重模拟能力。该奖项反映了NSF的法定使命，并通过使用基金会的智力优势和更广泛的影响审查标准进行评估，被认为值得支持。

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

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

Highly efficient Bayesian updating using metamodels: An adaptive Kriging-based approach

使用元模型的高效贝叶斯更新：基于自适应克里金法的方法

• DOI: 10.1016/j.strusafe.2019.101915
• 发表时间: 2020
• 期刊: Structural Safety
• 影响因子: 5.8
• 作者: Wang, Zeyu;Shafieezadeh, Abdollah
• 通讯作者: Shafieezadeh, Abdollah

Real-time high-fidelity reliability updating with equality information using adaptive Kriging

• DOI: 10.1016/j.ress.2019.106735
• 发表时间: 2020-03
• 期刊: Reliab. Eng. Syst. Saf.
• 作者: Zeyu Wang;A. Shafieezadeh