RAPID/Collaborative Research: Performance of Low-Rise Large-Volume Buildings in Florida during 2018 Hurricane Michael

RAPID/协作研究：2018 年迈克尔飓风期间佛罗里达州低层大体量建筑的性能

• 批准号: 1904327
• 负责人: Jeffrey Berman
• 金额: $ 2.7万
• 依托单位: University of Washington
• 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: 2018-11-15 至 2019-10-31
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=1904327&HistoricalAwards=false
• 关键词: RAPID; Collaborative; Research; Performance; Low

Low-rise, large-volume (LRLV) metal buildings are a critical component to community and national resilience, often functioning as school auditoriums or gymnasiums, military or civilian aircraft hangars, distribution centers, supermarkets, churches, industrial and manufacturing buildings, and storage facilities protecting high-value property. Unfortunately, many of these structures suffered catastrophic collapses or irreparable damage following Hurricane Michael, which made landfall south of Panama City, Florida on October 10, 2018, as a Category 4 hurricane. Preliminary assessments by the NSF-supported Structural Extreme Events Reconnaissance network found that damage to these structures was common and often disproportionate to surrounding buildings, indicating a knowledge gap in the understanding of the dynamic loads on these structures and/or the mechanisms of structural response to these loads during extreme wind events. This Grant for Rapid Response Research (RAPID) will support field deployments to quickly and precisely capture the post-hurricane damage state of LRLV buildings in the form of high-resolution 3D point clouds, by means of terrestrial and airborne LIDAR and photogrammetry, and forensic structural engineering analysis. Post-processing and analysis of the data will inform advanced computational models of wind load and structural response for these buildings, which will ultimately enable safer and more efficient designs. By enabling a better understanding of the complex dynamic behavior of these buildings under wind loads, the findings from this project can inform future designs to reduce the frequency of LRLV building failures in future extreme wind events. The field reconnaissance and analysis will train undergraduate and graduate engineers in forensic engineering methods and provide high quality case studies that can be used by the engineering education community. Data collected from this award will be archived in the NSF-supported Natural Hazards Engineering Research Infrastructure (NHERI) Data Depot (https://www.DesignSafe-CI.org). During hurricane-force winds, the dimensions of LRLV metal buildings can exceed the integral length scales of the turbulent flow, producing incoherent gust structures over the surface of the building. The effects of this phenomenon on peak structural forces, and particularly the internal pressure response, are not well understood. The goals of this project are to: 1) preserve the precise post-hurricane condition of LRLV buildings impacted by Hurricane Michael prior to cleanup, 2) assess the extreme wind conditions to which the LRLV buildings were subjected, 3) conduct preliminary assessments of the primary drivers of LRLV building failures, and 4) position future research efforts for conducting advanced wind load and structural analysis simulations to address the key knowledge gaps that have led to large failure rates. Data gathering excursions (3-5 days) in Florida will use multiple sensing technologies to quickly gather detailed structural information on target structures including terrestrial LIDAR and measurements, and drone-based LIDAR and imagery. After reducing the data into 3D models, the analysis process will focus on parameters including building volume, unprotected opening size, building orientation with respect to primary wind direction, resonance of internal pressure, structural system (gravity and lateral), structure age, and pre-event condition. This study will address a key knowledge gap in hurricane-induced wind loads on LRLV buildings while simultaneously investigating the structural system response to these loads. The holistic approach will advance scientific understanding of the phenomena driving the failures of these systems and inform more resilient building designs for future events.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.

低层，大容量（LRLV）金属建筑是社区和国家韧性的关键组成部分，通常是学校礼堂或体育馆，军事或民用飞机机库，分销中心，超市，教堂，工业和制造建筑以及存储保护高价值物业的设施。不幸的是，在迈克尔飓风飓风之后，这些结构中的许多结构遭受了灾难性的崩溃或无法弥补的损害，该飓风于2018年10月10日成为佛罗里达州巴拿马城以南的登陆，成为4级飓风。 NSF支持的结构性极端事件进行初步评估发现，对这些结构的损害很普遍，并且通常与周围建筑物不成比例，这表明在理解这些结构的动态载荷和/或结构响应机制上对结构性响应的动态负载有差距这些在极端风事件中的负载。这项用于快速响应研究的赠款（快速）将支持现场部署，以通过陆地和空中灯光和摄影测量法和法医，以高分辨率3D点云的形式快速，精确地以高分辨率3D点云的形式捕获LRLV建筑物的损害状态。结构工程分析。对数据的后处理和分析将为这些建筑物的风负载和结构响应的高级计算模型提供信息，这最终将实现更安全，更有效的设计。通过更好地了解这些建筑物在风载下的复杂动态行为，该项目的发现可以为将来的设计提供信息，以减少未来极端风事件中LRLV建筑物故障的频率。现场侦察和分析将培训法医工程方法的本科和研究生工程师，并提供高质量的案例研究，可以由工程教育社区使用。 该奖项收集的数据将存档在NSF支持的自然危害工程研究基础设施（NHERI）数据仓库（https://www.designsignsafe-ci.org）中。 在飓风中，LRLV金属建筑物的尺寸可以超过湍流的整体长度尺度，从而在建筑物表面产生不连贯的阵风结构。这种现象对峰结构力，尤其是内部压力反应的影响尚不清楚。该项目的目标是：1）保留在清理之前受到飓风迈克尔飓风影响的LRLV建筑物的精确后灌肠后条件，2）评估LRLV建筑物所对LRLV建筑物的极端风条件，3）进行初步评估LRLV建筑故障的主要驱动因素，以及4）对进行先进的风负荷和结构分析模拟的未来研究工作的定位，以解决导致较大失败率的关键知识差距。佛罗里达州的数据收集游览（3-5天）将使用多种传感技术来快速收集有关目标结构的详细结构信息，包括陆地激光雷达和测量，以及基于无人机的激光雷达和图像。将数据减少为3D模型后，分析过程将重点关注参数，包括建筑物量，未保护的开放尺寸，相对于主要风向的建筑定位，内部压力的共振，结构系统（重力和横向），结构年龄以及PRE PRE - 事件状况。这项研究将解决LRLV建筑物飓风引起的风负载的关键知识差距，同时研究对这些负载的结构系统响应。整体方法将进一步了解推动这些系统失败的现象的科学理解，并为未来事件提供更有弹性的建筑设计。该奖项反映了NSF的法定任务，并被认为是值得通过基金会的知识分子和更广泛的影响评论来获得支持的。标准。