RAPID: Examining the Performance of Historic Masonry Structures after the December 2021 Midwest Tornadoes
RAPID: Examining the Performance of Historic Masonry Structures after the December 2021 Midwest Tornadoes
批准号:
2222849
负责人:
Rebecca Napolitano
金额:
$8.82万
依托单位国家:
美国
项目类别:
Standard Grant
财政年份:
2022
资助国家:
美国
项目状态:
未结题
起止时间:
2022-04-01 至 2025-02-28
中文摘要
2021年12月10日至11日,“四州”龙卷风摧毁了肯塔基州、阿肯色州、密苏里州和田纳西州的建筑物。该快速反应研究基金(RAPID)将在肯塔基州梅菲尔德市进行为期四天的现场调查,记录这一事件中受损和未受损的砖石结构,目的是提供有关龙卷风荷载期间砖石结构性能的新知识和数据。许多历史悠久的砖石结构目前被排除在最新版本的龙卷风建筑规范要求之外。在这项研究中收集的详细的文本和图像数据将有助于了解龙卷风期间砖石建筑类型和建筑损坏之间的关系,可以帮助社区更好地准备自然灾害事件并对其进行恢复,并可以为未来的建筑规范要求提供信息。从该奖项收集的数据将保存在国家科学基金会支持的自然灾害工程研究基础设施数据仓库(https://www.DesignSafe-CI.org).)中这一奖项将有助于国家科学基金会在国家减少风暴影响计划(NWIRP)中发挥作用。这项研究的重点是1)评估翻新和适应性重复使用的砖石结构的效果,2)阐明美国其他历史建筑的潜在弱点,3)为未来的翻新和增建确定弹性砌体连接类型。这项研究将为龙卷风加载过程中某些类型的砖石结构(风险类别1和2)提供新的知识和数据。这方面的知识可以改善历史建筑结构的性能,因为许多历史建筑结构在最近增加的龙卷风建筑设计标准(美国土木工程师学会7-22,建筑和其他结构的最小设计荷载和相关标准)中没有涉及。实地勘察将产生一个独特的数据集,其中将包括陆基和无人机照片以及陆基详细结构调查,重点是由于翻新或增加建筑物而产生的连接类型。数据将使用华盛顿大学由NSF支持的NHERI侦察(RAPID)设施的现场设备收集。这项工作的优点在于生成了详细的数据集,其中包括50个砖石结构的3D点云模型、图像和建筑图纸。这一更详细的数据集将有助于量化不同翻新和加固方法的有效性,为未来的解决方案和建筑法规要求提供信息。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。
英文摘要
On December 10-11, 2021, the “Quad-State” tornadoes damaged structures across Kentucky, Arkansas, Missouri, and Tennessee. This Grant for Rapid Response Research (RAPID) will conduct a four-day field survey to document damaged and undamaged masonry structures from this event in Mayfield, Kentucky, with the goal to provide new knowledge and data about the performance of masonry structures during tornadic loading. Many historic masonry structures are presently excluded in recent versions of tornadic building code requirements. The detailed textual and image data collected during this research will contribute to understanding the relationship between masonry construction types and building damage during tornadoes, can help communities to better prepare for and be resilient from natural hazard events, and can inform future building code requirements. Data collected from this award will be archived in the National Science Foundation (NSF)-supported Natural Hazards Engineering Research Infrastructure (NHERI) Data Depot (https://www.DesignSafe-CI.org). This award will contribute to the NSF role in the National Windstorm Impact Reduction Program (NWIRP). The focus of this research is 1) to evaluate the efficacy of retrofit and adaptively reused masonry structures, 2) to elucidate potential weaknesses in other historic structures across the United States, and 3) to identify resilient masonry connection typologies for future retrofits and additions. This research will provide new knowledge and data concerning certain types of masonry structures (Risk Categories 1 and 2) during tornadic loading. This knowledge can lead to improving the performance of historic masonry structures, as many historic masonry structures are not addressed in recent additions to tornadic building design criteria (American Society of Civil Engineers 7-22, Minimum Design Loads and Associated Criteria for Buildings and Other Structures). The field reconnaissance will generate a unique data set that will include ground-based and drone-based photos and ground-based detailed structural surveys focusing specifically on connection typologies due to retrofitting or building additions. Data will be collected using field equipment from the NSF-supported NHERI Reconnaissance (RAPID) Facility at the University of Washington. The merit of this work lies in the detailed data set generated, which will encompass 3D point cloud models, images, and architectural drawings for 50 masonry structures. This more detailed data set will help quantify the efficacy of different retrofitting and strengthening methods to inform future solutions and building code requirements.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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Understanding the Performance of Historic Masonry Structures in Mayfield, KY after the 2021 Tornadoes
了解 2021 年龙卷风过后肯塔基州梅菲尔德历史砖石结构的性能
DOI:
10.1016/j.culher.2023.07.002
发表时间:
2023
期刊:
Journal of Cultural Heritage
影响因子:
3.1
作者:
[Kaushal, Saanchi S., Gutierrez Soto, Mariantonieta, Napolitano, Rebecca]
通讯作者:
Napolitano, Rebecca
Raw data collected during the RAPID reconnaissance mission to Mayfield in March 2022:RAPID: Mayfield, KY Post-Tornado Building Reconnaissance
2022 年 3 月 RAPID 梅菲尔德侦察任务期间收集的原始数据:RAPID:肯塔基州梅菲尔德龙卷风后建筑物勘察
DOI:
10.17603/ds2-kwmz-ke11
发表时间:
2023
期刊:
Designsafe-CI
影响因子:
--
作者:
[Kaushal, Saanchi Singh, Gutierrez Soto, Mariantonieta, Napolitano, Rebecca]
通讯作者:
Napolitano, Rebecca
Research Experiences for Undergraduates (REU), NHERI 2022: Post-Tornado Historic Masonry Building Reconstruction
本科生研究经验 (REU),NHERI 2022:龙卷风后历史砖石建筑重建
DOI:
10.17603/ds2-s0g7-ed50
发表时间:
2022
期刊:
Designsafe-CI
影响因子:
--
作者:
[Patelski, Keely, Kaushal, Saanchi Singh, Napolitano, Rebecca]
通讯作者:
Napolitano, Rebecca
STRUCTURAL ANALYSIS OF POST-DISASTER MASONRY STRUCTURES MODELED USING CLOUD2FEM SOFTWARE
使用 Cloud2FEM 软件建模的灾后砌体结构的结构分析
DOI:
10.5194/isprs-archives-xlviii-m-2-2023-827-2023
发表时间:
2023
期刊:
Remote Sensing and Spatial Information Sciences
影响因子:
--
作者:
[Kaushal, S. S., Gutierrez Soto, M., Napolitano, R.]
通讯作者:
Napolitano, R.
Research Experiences for Undergraduates (REU), NHERI 2023: Mayfield Clothing Mill Deviation Analysis and Conversion of Point Cloud Model to FEM
本科生研究经验 (REU),NHERI 2023:梅菲尔德服装厂偏差分析以及点云模型到 FEM 的转换
DOI:
10.17603/ds2-f3pq-dn68
发表时间:
2023
期刊:
Designsafe-CI
影响因子:
--
作者:
[Whitesides, Elanor, Kaushal, Saanchi Singh, Napolitano, Rebecca, Wartman, Joseph]
通讯作者:
Wartman, Joseph
共 6 条
Collaborative Research: HDR DSC: Infusion of data science and computation into engineering curricula
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批准号:2123343
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项目类别:Continuing Grant
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资助金额:$112.8万
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财政年份:2021
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负责人:Rebecca Napolitano
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依托单位:
海外基金