Link to Latest Report: April 2026 Progress Report
Background :
The researchers will test bridge columns near the critical intersection of shear and flexural failure that aims to help the prioritization of bridges for seismic retrofit. That testing, along with the terrestrial lidar equipment housed at the UW’s RAPID Facility, offer an opportunity to explore the use of lidar to map cracks and subsequently use the crack information to correlate with failure modes and remaining capacity of reinforced concrete bridge components. There are several algorithms in the literature and available through open repositories such as GitHub that use lidar-derived point clouds to identify, map and measure cracks. Such algorithms will not need to be developed as part of this project, but instead the existing ones will be utilized to identify and characterize the cracks in the test columns. This project will focus on developing the link between the cracking (pattern and magnitude), the likely failure mode (shear or flexural), and the remaining capacity. Such information may be generalized to help inspectors understand what types of cracks are most problematic and might lead to deteriorated structural capacity. That information is relevant to inspection of both existing and new construction.
Objective :
The research objective is to advance bridge evaluation by developing a framework to:
(i) capture cracking in bridge elements with lidar,
(ii) characterize the cracking geometry using automated algorithms, and
(iii) correlate the resulting cracking with remaining capacity and the potential for brittle shear failure of concrete bridge components.
- Capture cracking in bridge elements with LiDAR,
- Characterize the cracking geometry using automated algorithms, and
- Correlate the resulting cracking with remaining capacity and the potential for brittle shear failure of concrete bridge components.
Scope :
Task 1 – LiDAR Scanning of Reinforced Concrete Columns
The first step is to understand when bridge columns are shear critical, such that bridges can be prioritized for seismic retrofit or replacement. The new feature of these tests is that the columns will be subjected to a variety of deformation histories to assess differences between flexure-shear behavior during long-duration and short-duration earthquakes. This project involves testing of several columns under combined axial force and shear/flexure. For each test, the PI’s will utilize the laser scanners (terrestrial lidar) from the NSF supported NHERI RAPID Facility (https://rapid.designsafe-ci.org/) at the University of Washington to scan the specimen at several stages of loading. They will use the Facility’s Leica RTC 360 scanners, which capture one million points per second and complete a full scan in less than one minute with a single point accuracy of less than 1 mm. The scans will be registered together using software available at the RAPID facility to create full 3D models of each specimen at the various loading stages. Importantly, the scanner collects high-definition photos at the same time as the laser scans, which the software then uses to color the point cloud, but which also can be interrogated individually. The resulting 3D models are high resolution and high precision.
Task 2 – Application of Crack Detection Algorithms
Algorithms from the literature and open repositories will be tested for efficacy in crack detection from the point clouds for the tested columns. A substantial amount of research has been dedicated to detecting cracks in pavement from point clouds obtained from mobile lidar mounted on vehicles, some examples include: Guan et al. (2015), Zhong et al. (2020), and del Rio-Barral et al. (2022). Such algorithms may be easily applied to concrete structures and many are open source. Additionally, Jiang et al. (2018) and Cho et al. (2018) are examples of applications of crack detection applied to concrete structural components. This task of the research will review the available detection methods and implement them to illustrate crack detection and characterization (i.e., determining their size, orientation, and density) for the tested columns.
Task 3 – Assessing Remaining Capacity and Potential for Shear Failure
Crack size, orientation, and density are key factors in determining how close a concrete component may be to shear failure. Zanorac et al. (2019) provides a summary of methods available for estimating remaining capacity of concrete sections with cracking. These methods include empirically derived tools, theoretical models, fractal analysis and concrete mechanics. Studies such as Calvi et al. (2018), Veletzos et al. (2008) and Birrcher et al. (2009) have had success in using a combination of statistics and mechanics to estimate the likely failure mode of reinforced concrete panels, columns, and deep beams. Those methods will be compiled and used in Task 4 below to develop and test the complete evaluation framework on the column specimens tested in the UW Structural Research Laboratory.
Task 4 – Development of the Evaluation Framework
Using the results of Tasks 1, 2, and 3 the complete evaluation framework will be developed. This includes recommendations for equipment specifications for scanning of structural reinforced concrete elements, recommended algorithms for detecting and measuring cracks, and guidelines for determining the severity of the cracking with respect to the potential for brittle failure. The framework will be demonstrated and refined using the tested column specimens available via the WSDOT supported testing.
Task 5 – Dissemination
The research team will disseminate the lidar evaluation framework through journal papers and presentations at national conferences. The team will prepare a report on the framework development and its application to the tested bridge columns and applications for evaluating new and existing construction as is standard for IBT/ABC UTC projects.
Research Team :
Principal Investigator: Jeffrey W. Berman, Ph.D.
Previous progress reports: