Full-Scale Shake Table Test Damage Data Collection Using Terrestrial Laser-Scanning Techniques
Publication: Journal of Structural Engineering
Volume 147, Issue 3
Abstract
This paper presents the use of modern survey techniques, particularly light detection and ranging (LiDAR) scanning, to collect time-sensitive information before and after shake table experiments. Two full-scale, three-story residential buildings were tested simultaneously on the largest shake table in the world. The focus of this study is on the use of LiDAR to document observations during these tests. The challenges experienced during this study prompted the development of a formalized survey procedure using LiDAR scanning techniques, which can be used by other researchers when planning to collect such time-sensitive data from similar experimental programs. In this paper, damage assessment through visual inspection, which is commonly performed during full-scale tests, is compared to postexperiment assessments using postprocessed LiDAR-derived point clouds. Various examples of damage to structural and nonstructural components, including columns, bracing, partition walls, and façades, are illustrated through postshaking visual inspections as well as LiDAR-derived point clouds. The feasibility of making accurate measurements using LiDAR point clouds, and automatically detecting damage using the point-to-point cloud comparison, is presented. Finally, the relationship between observations through traditional instruments (e.g., accelerometers and laser meters) and LiDAR is discussed. In one example, the measurements from eight laser meters around the buildings are used to validate the measurements obtained using LiDAR point clouds. It is concluded that observations through LiDAR are complementary to those from traditional instruments, while permanent/residual displacements after the tests can be measured from both traditional and modern instruments.
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Data Availability Statement
Some or all data, models, or code that support the findings of this study are available from the corresponding author upon reasonable request.
Acknowledgments
This study is funded by the US National Science Foundation (NSF) under Award Nos. CMMI 1829433 and 1829412. This financial support is greatly appreciated. Data was collected in part using equipment provided by the NSF as part of the RAPID Facility, a component of the Natural Hazards Engineering Research Infrastructure (NHERI) under Award No. CMMI 1611820. Any opinions, findings, conclusions, and recommendations presented in this paper are those of the authors and do not necessarily reflect the views of NSF. The authors would also like to acknowledge the Japanese team, led by Professor Takuya Nagae, for their collaboration and support during the testing phase.
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Published In
Journal of Structural Engineering
Volume 147 • Issue 3 • March 2021
Copyright
© 2020 American Society of Civil Engineers.
History
Received: Mar 23, 2020
Accepted: Sep 3, 2020
Published online: Dec 29, 2020
Published in print: Mar 1, 2021
Discussion open until: May 29, 2021
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