RAPID/Collaborative Research: Multi-Platform 3-D Data Preservation of Tornado Damage to Engineered Structures in Texas during November 16-17, 2015

2015年11月16日至17日，一场罕见的龙卷风爆发在德克萨斯州、俄克拉荷马州和堪萨斯产生了至少17场龙卷风，其中包括一场增强型藤田（EF）EF3龙卷风，该龙卷风破坏了德克萨斯州潘帕附近油田服务设施的一组工程结构和附近的工程中心枢纽灌溉系统结构。 可以估计这些结构的结构阻力，从而能够估计与损坏相关的龙卷风风速。 这一快速反应研究项目将通过保存龙卷风对油田设施和灌溉系统结构造成损害的三维数字数据，调查龙卷风的风结构和估计风速。 保存这些三维结构损伤数据将使未来的研究人员能够通过物理建模、计算机建模和其他预测损伤建模（例如，损失估计和风险评估建模）来验证风害预测模型。 利用一套遥感数据收集方法，项目团队将通过摄影和摄影测量、激光扫描、无人机视觉成像和卫星成像快速收集高分辨率的三维结构损伤数据。 从该项目收集的数据可以作为合作的基础，多学科研究强调准确和高度详细地保存龙卷风造成的结构损坏，提高对龙卷风复杂风结构的理解，验证或改进龙卷风风速估计，以及开发更具弹性的基础设施。 本科生将参与数据收集，然后使用这些数据与来自三个机构的研究生和教师研究人员一起合作进行未来的研究，从而培养未来的领导者减轻自然灾害的损害。

During November 16-17, 2015, a rare tornado outbreak produced at least 17 tornadoes in Texas, Oklahoma, and Kansas, including an Enhanced Fujita (EF) EF3 tornado, which damaged a group of engineered structures at an oilfield services facility near Pampa, Texas and nearby engineered center-pivot irrigation system structures. Structural resistances for these structures can be estimated, enabling the estimation of tornado wind speeds associated with the damage. This rapid response research (RAPID) project will investigate tornado wind structure and estimated wind speeds through three-dimensional (3-D), digital data preservation of the tornado damage to the oilfield facility and irrigation system structures. Preservation of this 3-D structural damage data will enable future researchers to validate wind-damage prediction models, via physical modeling, computer modeling, and other predictive damage modeling (for example, loss estimation and risk assessment modeling). Using a suite of remote-sensing data collection methods, the project team will rapidly collect high-resolution, 3-D structural damage data through photography and photogrammetry, laser scanning, unmanned aerial vehicle visual imaging, and satellite imaging. The data collected from this project can serve as the basis for collaborative, multi-disciplinary studies emphasizing the accurate and highly detailed preservation of structural damage from tornadoes, heightened understanding of the complex wind structures of tornadoes, validation or refinement of tornado wind speed estimates, and development of more resilient infrastructure. Undergraduate students will participate in data collection and then use this data to collaborate on future research alongside graduate students and faculty researchers from three institutions, thus training future leaders in the mitigation of natural hazards damage.