RAPID: Collection of Perishable Data on Wind- and Surge-Induced Residential Building Damage in Texas during 2017 Hurricane Harvey

在美国，风暴和风暴潮等相关灾害通常是造成建筑物损坏最多的自然灾害。为了减轻这种损害，重要的是要了解风速及其特征与由此造成的建筑物损害之间的关系。2017年8月25日，飓风哈维以4级飓风的形式袭击了德克萨斯州海岸，罕见地出现了高风速和显著风暴潮的组合。初步调查显示，在遭受哈维飓风冲击的德克萨斯州沿海社区，住宅建筑的性能变化很大，即使是类似的建筑类型，也应该经历类似的风速和风暴潮水平。这种可变性表明，人们对飓风灾害与建筑物破坏之间关系的基本认识存在差距。这项快速反应研究拨款（Rapid）将支持在哈维飓风期间收集住宅建筑性能的现场数据，以便通过直接观察正式评估飓风危害与建筑破坏的关系来填补这些空白。更好地了解危险与损害的关系以及影响这种关系的因素，可以用来推进抗飓风的建筑设计方法和社会对风暴的抵御能力。在实地工作中获得的所有数据将通过美国国家科学基金会支持的自然灾害工程研究基础设施（NHERI）数据库与工程研究界共享，该数据库可在https://www.designsafe-ci.org上获得。收集到的建筑物性能数据与风速观测或估计相匹配，将提供一个工程案例研究图书馆，用于课堂上教育下一代工程师和建筑师飓风对建筑物的影响。目前的建筑设计和损害预测方法假设风暴损害主要是标准化风速级、当地地形和建筑特征的函数，隐含地忽略了相同给定风速下极端风事件类型之间的潜在差异，以及风暴潮等潜在共存危害的任何影响。RAPID项目的目标是：1)收集飓风哈维期间住宅建筑性能的代表性空间参考数据库；2)根据收集到的现场数据开发风的飓风脆弱性函数；3)建立一个框架，用于评估增强的危险条件（如飓风眼壁内的风暴潮或中涡）以及强风和其他极端风事件（如龙卷风）的影响。关于风与损害的关系。来自奥本大学、伊利诺伊大学厄巴纳-香槟分校和马里兰大学的一组研究人员和研究生将从受影响的德克萨斯州海岸线沿线有大量建筑的主要地区收集住宅建筑损坏数据。在一个大的空间区域内，将采用引导集群抽样方法，对单户住宅结构进行详细的地面调查，并附有地理标记的照片和实地记录。收集的数据将包括所有主要建筑构件的损坏率、建筑材料和楼层数等建筑特征，以及可用于估计风速或风暴潮高度的任何证据。从经验数据中开发的脆弱性函数将用于促进风与损害关系之间的比较，展示在仅风、风和风暴潮以及龙卷风事件中预期建筑性能的差异。

Windstorms and associated hazards, such as storm surge, routinely cause the most building damage of any natural hazard in the United States. To mitigate this damage, it is important to understand the relationship between wind speed and its characteristics and the resulting building damage. On 25 August 2017, Hurricane Harvey struck the coast of Texas as a Category 4 hurricane with a rare combination of high wind speeds and significant storm surge. Preliminary reconnaissance showed that residential building performance in coastal communities in Texas exposed to the brunt of Hurricane Harvey's impacts was highly variable, even for similar building types that should have experienced similar wind speeds and storm surge levels. This variability demonstrates gaps in the fundamental knowledge of the relationship between hurricane hazards and building damage. This Grant for Rapid Response Research (RAPID) will support field data collection on residential building performance during Hurricane Harvey in order to fill these gaps by formally evaluating the hurricane hazard-to-building damage relationship through direct observation. A better understanding of the hazard-to-damage relationship and the factors that influence it can be used to advance hurricane-resistant building design methodologies and society's resilience to windstorms. All data acquired during the field work will be shared with the engineering research community through the NSF-supported Natural Hazards Engineering Research Infrastructure (NHERI) Data Depot available at https://www.designsafe-ci.org. The collected building performance data, matched with wind speed observations or estimates, will provide a library of engineering case studies for use in the classroom to educate the next generation of engineers and architects on the impacts of hurricanes on buildings.Current building design and damage prediction methods assume that windstorm damage is primarily a function of standardized wind speed magnitude, local terrain, and building characteristics, implicitly ignoring any potential differences between extreme wind event types for the same given wind speed, and any effects from potentially coexisting hazards such as storm surge. The goals of this RAPID project are to 1) collect a representative, spatially-referenced database of residential building performance during Hurricane Harvey, 2) develop hurricane fragility functions for wind based on the field data collected, and 3) establish a framework for evaluating the effects of enhanced hazard conditions, such as storm surge or mesovortices within the hurricane eyewall, in addition to high winds, and other extreme wind events such as tornadoes, on the wind-to-damage relationship. Residential building damage data will be collected, from major areas with significant building stock along the impacted Texas coastline, by a team of researchers and graduate students from Auburn University, University of Illinois at Urbana-Champaign, and University of Maryland. A guided cluster sampling approach over a large spatial area will be used to conduct detailed, ground-based surveys of single-family residential structures with geo-tagged photographs and field notes. The collected data will include the damage ratios for all major building components, characteristics of the building such as construction material and number of stories, and any evidence that could be used to estimate wind speed or storm surge height. The fragility functions developed from the empirical data will be used to facilitate the comparisons between wind-to-damage relationships, demonstrating differences in expected building performance during wind-only, wind and storm surge, and tornado events.