Particle-volume tracking-assisted discrete digital volume correlation for kinematics analysis of particles

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 trackin...

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Veröffentlicht in:Granular matter Jg. 25; H. 1; S. 5
Hauptverfasser: Xiang, Zou, Bing, Pan
Format: Journal Article
Sprache:Englisch
Veröffentlicht: Berlin/Heidelberg Springer Berlin Heidelberg 01.02.2023
Springer Nature B.V
Schlagworte:
Algorithms
Centroids
Complex Fluids and Microfluidics
Engineering Fluid Dynamics
Engineering Thermodynamics
Foundations
Geoengineering
Granular materials
Heat and Mass Transfer
Hydraulics
Image processing
Industrial Chemistry/Chemical Engineering
Integrated circuits
Kinematics
Materials Science
Mechanical properties
Original Paper
Particle intensity
Particle tracking
Physics
Physics and Astronomy
Robustness (mathematics)
Rotation
Soft and Granular Matter
Digital volume correlation
Large displacement
Granular material
Particle tracking
Large rotation
ISSN:1434-5021, 1434-7636
Online-Zugang:Volltext
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Zusammenfassung: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.
Bibliographie:ObjectType-Article-1
SourceType-Scholarly Journals-1
ObjectType-Feature-2
content type line 14
ISSN:1434-5021
1434-7636
DOI:10.1007/s10035-022-01292-w