Data Collection Using Terrestrial Laser Scanners from the Shake-Table Test of a Full-Scale Reinforced Concrete Building
Publication: Journal of Structural Engineering
Volume 150, Issue 2
Abstract
Shake-table tests of a full-scale 3-story reinforced concrete frame building were performed at the E-Defense facility (Miki City, Japan) as part of the Tokyo Metropolitan Resilience Project. Building data were collected before and after each shake-table experiment, using light detection and ranging (lidar) scanning technology. Three-dimensional point clouds were generated and processed to investigate the damage features that can be extracted, which are important for postdisaster structural assessment purposes. To this end, this paper discusses aspects pertaining to lidar data processing and registration, calculation of residual displacements and interstory drifts, and concrete cracking and spalling identification and measurement. Most notably, this paper deals with very large data sets, processed to extract structural response information at both global and local scales. Limited multiscale work has been done in the past, and the different sets of challenges that arise have typically been addressed separately. Evidently, this gap needs to be filled before lidar can be effectively used in the field for structural assessment applications. A series of examples in which lidar data are processed and analyzed to assess specific structural components is illustrated, showing that point cloud data can indeed be processed to obtain measurements of global residual drifts or of the extent of visible damage (e.g., crack width and spalling). Although preliminary in nature, the results presented in this paper indicate that collecting postdisaster data using terrestrial lidar scanners has the potential to contribute improving how buildings are assessed in the aftermath of seismic events.
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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. All lidar data are available in DesignSafe.
Acknowledgments
This study is funded by the US National Science Foundation (NSF) under Award No. 2000478. This financial support is greatly appreciated. Data were 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) operating under NSF Award 1611820. Thus, the authors would like to acknowledge the RAPID Facility staff. In addition, the authors would like to acknowledge the Japanese team for their collaboration and support during the testing phase, in particular Professor Kusunoki and Dr. Yeow.
Disclaimer
Any opinions, findings, conclusions, and recommendations presented in this paper are those of the authors and do not necessarily reflect the views of NSF.
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Published In
Journal of Structural Engineering
Volume 150 • Issue 2 • February 2024
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© 2023 American Society of Civil Engineers.
History
Received: Mar 28, 2023
Accepted: Sep 20, 2023
Published online: Nov 23, 2023
Published in print: Feb 1, 2024
Discussion open until: Apr 23, 2024
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