Low-cost LiDAR scanning data for geometric and volume analysis of 3D-printed concrete-plastic elements.

Abstract

This dataset presents experimental data on the use of low-cost LiDAR scanners (integrated with iPads and iPhones) to evaluate the deformation of plastic-concrete specimens with fractal-based cross-sections. The specimens were created using 3D printed lost formwork and concrete. The dataset includes mesh models acquired using low-cost LiDAR technology and photogrammetry before and after the loading tests. This allows for the evaluation of geometric deformations and volume changes in specimens of varying cross-sectional complexity. The measurements were performed in a controlled laboratory environment, where LiDAR-based volume calculations were compared with high-precision photogrammetric reference data. The dataset includes information on scanning conditions, point cloud processing techniques, and measurement errors, providing insight into the accuracy and repeatability of low-cost LiDAR technology in structural assessment. This dataset is valuable to researchers investigating low-cost metrology, LiDAR-based strain monitoring, and the application of consumer-grade scanning technology in civil engineering and materials science. It enables further analysis of the accuracy of mobile LiDAR for measuring complex geometries and deformations of structures.