Size distribution analysis of aggregates using LiDAR scan data and an alternate algorithm

[Display omitted] •The point cloud contains invaluable digital information that doesn’t require scaling.•Intergranular boundaries on the surface of piles are very sensitive to curvature.•Algorithm ensures surface correction without disturbing the shape of the grains.•Protrusion heights of the grains on the surface gives the grain size.•Size distribution measured using LiDAR is compatible with sieve analysis. In the fields of mining, construction, geology, material science and etc., the grain size or grain size distribution emerges as the most important parameter in understanding and controlling of various processes and also in determination of their success. Screening and image analysis are the most frequently used methods for this purpose. In this study, it is aimed to determine particle size distribution of aggregates by using point cloud data obtained by terrestrial laser scanning method and developed algorithm. For this purpose, aggregate mixtures with different particle sizes were prepared in the laboratory, then the surfaces of these mixtures were scanned with a laser scanner to obtain point cloud data. The point cloud data were analyzed with the developed algorithm and the particle size distribution curves of the mixtures were obtained. These curves were compared with those obtained by sieve analysis and found to be very compatible with each other.