Field Testing of Concrete Buildings for Damage and Collapse Assessment

Ohio State University, The, Columbus OH

Investigators

Abstract

Many existing buildings in the United States are in danger of partial or complete collapse after one or more columns fail during low probability or extraordinary events such as blast, earthquake, fire or impact. In this award, multiple data collection systems will be used to monitor the damage progression and dynamic behavior of two reinforced concrete parking garage structures while several columns are physically removed from the structures prior to their scheduled demolition on the Ohio State University campus. Data from drones, a stereo camera data collection system, and various sensors will be used to capture the movement and change in dynamic response of the structures after each column loss. There is limited experimental research on collapse because it is difficult to construct and test full-scale building specimens in the laboratory, and such large-scale testing is expensive. This project will advance current structural damage and collapse assessment procedures using the collected experimental data, thus filling a critical gap in current state of knowledge. The research results will be disseminated through publications and presentations and transferred to the community through interactions with professional organizations developing technical documents and guidelines for building collapse assessment and structural design. Project data will be archived and made publicly available in the NSF-supported Natural Hazards Engineering Research Infrastructure Data Depot (https://www.DesignSafe-CI.org). This award will contribute to NSF's role in the National Earthquake Hazards Reduction Program (NEHRP). Recent advancements in data fusion and machine vision-based methods enable automatic detection of damage and monitoring of dynamic response of structures. The experimental data collected by drones, cameras, LiDAR, displacement sensors, and strain gauges will be fused to capture the change in dynamic characteristics of the test structures after each column loss. Three-dimensional (3D) load redistribution within a building is poorly understood because of lack of test data and the difficulty in analyzing this phenomenon from field observations. This project will: 1) develop simplified structural models to characterize stability and load redistribution mechanisms after one or more columns are suddenly lost in a building, 2) introduce data fusion techniques for damage detection and monitoring, and 3) develop 4D or time-dependent 3D mapping of the buildings to advance engineering understanding of dynamic performance and collapse mechanism of buildings. 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.