Particle-volume tracking-assisted discrete digital volume correlation for kinematics analysis of particles - Xiang, Zou; Bing, Pan (Granular matter, 2023)
Accurate tracking of the discrete particle kinematics (i.e., particle displacement and rotation) is helpful for analyzing the macroscopic mechanical behavior of granular materials. When particle motion/rotation is small, existing discrete digital volume correlation (discrete DVC) or particle tracking method can correctly measure the particle kinematics by matching particle intensity information or geometric information under different states. However, when the particles move acutely (i.e., the displacement and rotation are large), these methods become inefficient, inaccurate or even fail in the calculation. To enhance the robustness and accuracy of kinematics analysis of particles, we propose a generalized particle-volume (PV) tracking-assisted discrete DVC method. In this method, the geometric information (i.e., centroid position, volume and principal axes’ orientation) of discrete particles in reference and deformed volume images is first extracted through image processing. Then based on the obtained geometric information, the PV tracking method is used to find all the potential moving particles and corresponding initial guesses for each reference particle. Finally, a discrete DVC algorithm using the state-of-the-art 3D inverse compositional Gauss-Newton (IC-GN) algorithm is employed to determine the true target particle from all potential moving particles and refine the true initial guess using the intensity information for each reference particle. Compared with existing methods, the proposed method makes full use of both the geometric information and intensity information of discrete particles, thus it can achieve efficient and accurate motion measurement of particles even with large motion and rotation. The effectiveness of the proposed method is validated using numerical and real experiments.