Bridge Support Assessment Through Deflection Analysis Captured via LiDAR

Status: Complete 2026

Funding Agency: Graduate Assistance in Areas of National Need (US Department of Education)

Abstract: Bridge inspections are critical for ensuring structural safety, and Structural Health Monitoring (SHM) provides continuous information on bridge performance. Traditional SHM methods rely on physical contact sensors or visual inspection, which may not capture the full extent of structural behavior. This study investigates the use of Light Detection and Ranging (LiDAR) as a noncontact technique for measuring bridge deflection and settlement. Unlike single-point instruments, LiDAR provides a full-field view of the structure, enabling spatially continuous measurements of girder and support behavior. A scaled bridge model was constructed using aluminum I-beams and plywood decking, supported by concrete masonry blocks to simulate abutments. Support conditions were varied from all pins to all springs across eleven tests. LiDAR measurements were compared against control baselines obtained from string potentiometers, a laser reference method, and reaction scales. Results showed that LiDAR captured deflections within an overall average difference of 1.8 mm across the four-girder system and measured settlement with 89.7% accuracy, corresponding to a maximum difference of 5.00 mm. Load-path deflection analysis demonstrated 71.5% accuracy, within the LiDAR system’s ±1 mm tolerance. Importantly, LiDAR revealed opposite support-condition trends compared to single-point sensors, demonstrating higher sensitivity and the ability to capture displacement across planes rather than at isolated points. These findings confirm that LiDAR can reliably capture deflection and settlement behavior, reflecting changes in loading scenarios and support conditions, and demonstrate its potential as a scalable tool for SHM applications.

Principal Investigators: Dr. Adriana Trias Blanco, PhD., Dr. John Vrabel Jr., PhD.

Link to Publications: 

• Vrabel Jr, J., & Trias Blanco, A. (2026). Full field LiDAR-based measurement of deflection and support condition effects in a scaled bridge model: comparison with traditional point sensors. Advances in Bridge Engineering, 7(1), 24. https://link.springer.com/article/10.1186/s43251-026-00213-8