RAPID: Urgent Collection of Perishable Condition Data from Structures Affected by the Haiti Earthquake

这项快速反应研究(RAPID)拨款的目的是开发一种快速、基于图像的半自动方法来评估钢筋混凝土结构的损坏和坍塌风险，以减少事件后检查所需的时间并提高可靠性。美国最近发生的地震表明，即使是影响大都市地区的中等强度地震，也可能需要几周或几个月的时间来检查受损的建筑，从而允许进入受损的建筑。在这段时间里，家庭无家可归，企业没有设施，恢复工作被推迟。该研究小组寻求通过开发一种快速、基于图像的半自动方法来评估钢筋混凝土结构的损坏和坍塌风险，从而减少事件后检查所需的时间并提高可靠性。使用这种方法，受损结构的视频被处理以识别和表征受损，这些受损数据被用来估计结构部件的性能状态，并最终评估结构的坍塌易损性。研究小组将前往海地，收集在最近的地震中受损的混凝土建筑的受损数据和设计信息。这些数据将用于验证图像处理算法和损坏评估技术，从而推进设想的快速检测方法。数据收集活动对研究团队的研究生成员来说是一次重要的教育经历。研究小组收集的基于图像的综合数据集将提供给世界各地的地震工程教育工作者和研究人员使用。

The objective of this Rapid Response Research (RAPID) grant is to develop a rapid, image-based, semi-automated method for assessing damage and collapse risk for reinforced concrete structures to both reduce the time needed for, and to improve the reliability of, post-event inspection. The aftermath of recent earthquakes in the United States suggests that for even a moderate intensity earthquake affecting a metropolitan area, it could take weeks or months to inspect, and thereby grant access to, damaged buildings. During this time, families are without homes, businesses are without facilities, and recovery is delayed. The research team seeks to both reduce the time needed for and improve the reliability of post-event inspection by developing a rapid, image-based, semi-automated method for assessing damage and collapse risk for reinforced concrete structures. Using this method, video of damaged structures is processed to identify and characterize damage and these damage data are used to estimate the performance state of structural components and, ultimately, the collapse vulnerability of the structure.The research team will travel to Haiti and collect damage data and design information for concrete buildings damaged during the recent earthquake. These data will be used to validate image processing algorithms and damage assessment techniques and, thereby, to advance the envisioned rapid inspection method. The data collection activities represent a significant educational experience for the graduate student members of the research team. The comprehensive, image-based data sets collected by the research team will be made available for use by earthquake engineering educators and researchers around the world.