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.
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 home, businesses are without equipment, and recovery is delayed. On-going research by the PIs and their students seeks to reduce the time needed and improve the reliability of post-earthquake inspection by validating an image-based, cyber-physical method for assessing damage and collapse risk for concrete structures. Data were collected for concrete frame buildings damaged during the 2010 Haitian earthquake and used to advance this rapid inspection method. Intellectual Merit Comprehensive video, still-image and design data were collected for five buildings damaged during the Haitian earthquake. These data were used to advance an image-based, semi-automated method for assessing the collapse risk posed by damaged concrete buildings. Specifically, video and still-image data were used to advance and, ultimately, validate a procedure for automated characterization and quantification of damage. Additionally, still image and design data were used to characterize damage states for reinforced concrete columns subjected to earthquake loading. Broader Impacts The rapid assessment procedure described above offers to society the potential for increased safety for emergency responders and accelerated recovery from catastrophic events such as earthquakes. The data collection activities provided a tremendous educational experience for a small-group of graduate students who traveled to Haiti and observed first-hand the performance of buildings subjected to earthquake motion as well as the impact earthquake damage has on society. The comprehensive, image-based data sets retrieved have been made available to the community via NEEShub (https://nees.org/warehouse/project/872), these data offer the potential for earthquake engineering educators to provide an almost first-hand experience to students around the world.
