Rapid concrete surface roughness assessment with smartphone LiDAR

Concrete surface roughness is integral to interface shear resistance and overall integrity between concrete cast at different times, influencing structure safety. This interface is found at common construction joints that enable composite action between precast and cast-in-place concrete elements or monolith behaviour between two cast-in-place pours. Traditional on-site roughness evaluation relies on qualitative methods, such as visual comparison with predefined surface profiles. These assessment methods are subjective, time-consuming, and inconsistent. The absence of quantitative methods creates a notable gap in the data-to-decision framework. Recent advancements in smartphone LiDAR technology hold potential to provide a solution. Our study introduces a novel method that leverages smartphone LiDAR technology to precisely measure concrete roughness quantitatively. Data is acquired from the LiDAR system in the form of a point cloud, which captures the three-dimensional (3D) structure of the surface. Our study comprises comprehensive laboratory experiments to assess LiDAR operability, followed by on-site experiments for roughness quantification across five sites with varying levels of concrete roughness. The LiDAR data are compared with ground truth 3D data collected using a structured light sensor. The results demonstrate that the proposed method presents a reliable alternative for measuring concrete surface roughness in the field.