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Data for "CAIT-UTC-REG52: Bridge Deck Surface Profile Evaluation for Rapid Screening and Deterioration Monitoring"

Harvard Dataverse (Africa Rice Center, Bioversity International, CCAFS, CIAT, IFPRI, IRRI and WorldFish)

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Title Data for "CAIT-UTC-REG52: Bridge Deck Surface Profile Evaluation for Rapid Screening and Deterioration Monitoring"
 
Identifier https://doi.org/10.7910/DVN/6JEQJZ
 
Creator Trias, Adriana
 
Publisher Harvard Dataverse
 
Description The assessment of bridge deck condition demands the development of rapid and efficient diagnosis, prognosis, and repair techniques to safely and cost-effectively extend the life-cycle of our transportation infrastructure. Without the ability to identify and characterize deficiencies at their early stages, prognosis and various repair strategies simply cannot be brought to bear effectively. Therefore, there is a pressing need for the implementation of wireless, non-contact, or remote sensors that can provide rapid and cost-effective data. LiDAR sensors have the ability to capture dense point clouds that define the geometry of objects in a remote (non-contract) manner. This project evaluates the impact of capturing point cloud data of bridge deck top surfaces to enable a rapid screening method by identifying characteristics of early stage deterioration.
 
Subject Engineering
 
Contributor Stiesi, Ryan