Photogrammetry-Based Volume Measurement Framework for the Particle Density Estimation of LECA

Abstract

This paper presents a photogrammetry-based volume measurement framework for the particle density estimation of Lightweight expanded clay aggregate (LECA). The results are compared with computed tomography (CT) and Archimedes' method measurements. All of the steps required in order to apply the proposed approach are explained. Next, we discuss how the interpretation of open pores affects the results of volume measurements. We propose to process the shapes obtained from different methods by applying an Ambient Occlusion algorithm with the same threshold, t = 0.175. The difference between the CT and SfM methods is less than 0.006 g/cm³, proving that the photogrammetry-based approach is accurate enough. The Archimedes' method significantly overestimates the density of the particles. Nevertheless, its accuracy is acceptable for most engineering purposes. Additionally, we evaluate the accuracy of shape reconstruction (in terms of the Hausdorff distance). For 95% of the grain's surface, the maximum error is between 0.073 mm and 0.129 mm (depending on the grain shape). The presented approach is helpful for measuring the particle density of porous aggregates. The proposed methodology can be utilized in order to estimate intergranular porosity, which is valuable information for the calibration of DEM models.

Keywords: computed tomography; lightweight clay aggregate; particle density; photogrammetry; volume measurement.

Figure 1

Six LECA grains selected for analysis: two subangular (A1,A2), two subrounded (B1,B2), and two rounded (C1,C2).

Figure 2

Influence of the Ambient Occlusion threshold on the determined CT model’s envelope: (a) Cross-section of grain C1’s full CT model, (b) External surface of grain C1 obtained after the simplification with the threshold $t=0.05$ (left) and $t=0.175$ (right).

Figure 3

LECA prepared for image acquisition.

Figure 4

LECA grain immersed in water.

Figure 5

Visualization of the potential dense packing of three particles.

Figure 6

Difference between the CT-based and photogrammetry-based models measured as the Hausdorff distance (area-weighted histograms and error distribution on the grain surfaces) for samples (A1–C2).

Figure 6

Difference between the CT-based and photogrammetry-based models measured as the Hausdorff distance (area-weighted histograms and error distribution on the grain surfaces) for samples (A1–C2).