Date Approved
6-9-2026
Embargo Period
6-8-2028
Document Type
Dissertation
Degree Name
Ph.D. Civil Engineering
Department
Civil and Environmental Engineering
College
Henry M. Rowan College of Engineering
Advisor
Adriana Trias-Blanco, Ph.D.
Committee Member 1
Islam Mantawy, Ph.D.
Committee Member 2
Abdulkadir Hassen, Ph.D.
Committee Member 3
Hooman Ghasemi, Ph.D.
Committee Member 4
Nathaniel Dubbs, Ph.D.
Keywords
Bridge Deflection;Non-Contact Measurement;Structural Behavior;Structural Health Monitoring;Terresterial Laser Scanning;Vibration Monitoring
Disciplines
Civil and Environmental Engineering | Civil Engineering | Engineering
Abstract
Bridge inspections are critical to public safety, yet traditional methods are time-consuming, labor-intensive, and, while accurate and reliable, are also limited in their ability to capture full-field structural response data. Traditional methods collect data via contact sensors, limiting the number of devices that can be deployed on the structure. To improve current practice, the industry could benefit from full-field data-collection devices and leverage technology cooperation to achieve comprehensive structural analysis. This dissertation investigates Light Detection and Ranging (LiDAR) sensors as a fast, contactless screening tool for structural health monitoring of bridges. A scaled four-girder aluminum bridge was tested under multiple support conditions and loading scenarios to evaluate spatial and temporal point clouds captured via LiDAR for measuring engineering metrics such as deflection, settlement, and inferring load path, which refers to the support reaction distribution across the system. LiDAR results were validated against string traditional sensors, with mean absolute errors of 1.87 mm, 2.61 mm, and 3.57 mm, for deflection, settlement, and vibration, respectively; translated into allowable serviceability deflection as applicable for targeting bridges with span lengths >16 m, to maintain a signal-to-noise ratio of 10. These findings position LiDAR sensors as screening tools that can inform the need for further structural inspections, saving time and money by targeting a larger number of bridges than traditional sensors can.
Recommended Citation
Vrabel, John Edward, "EVALUATION OF THE EFFECTIVENESS OF SPATIAL AND TEMPORAL POINT CLOUD DATA FOR SUPPORTING STRUCTURAL HEALTH MONITORING" (2026). Theses and Dissertations. 3532.
https://rdw.rowan.edu/etd/3532
