Three-dimensional Wadell roundness for particle angularity characterization of granular soils

Zheng, Junxing; He, Hantao; Alimohammadi, Hossein

doi:10.1007/s11440-020-01004-9

Cited by 71 publications

(10 citation statements)

References 86 publications

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“…the model allows for particle deformation which is modelled as an overlap of particles (interpreted as a local contact deformation). The role of the particle shape was highlighted in [28,74,75]. A linear elastic normal contact model was used only.…”

Section: D Dem Modelmentioning

confidence: 99%

3D DEM simulations of monotonic interface behaviour between cohesionless sand and rigid wall of different roughness

2020

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The paper deals with three-dimensional simulations of a monotonic quasi-static interface behaviour between cohesionless sand and a rigid wall of different roughness during wall friction tests in a parallelly guided direct shear test under constant normal stress. Numerical modelling was carried out by the discrete element method (DEM) using spheres with contact moments to approximately capture a non-uniform particle shape. The varying wall surface topography was simulated by a regular mesh of triangular grooves (asperities) along the wall with a different height, distance and inclination. The calculations were carried out with different initial void ratios of sand and vertical normal stress. The focus was to quantify the effect of wall roughness on the evolution of mobilized wall friction and shear localization, also to specify the ratios between slip and rotation and between shear stress/force and couple stress/moment in the sand at the wall. DEM simulations were generally in good agreement with reported experimental results for similar interface roughness. The findings presented in this paper offer a new perspective on the understanding of the wall friction phenomenon in granular bodies.

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Section: D Dem Modelmentioning

confidence: 99%

3D DEM simulations of monotonic interface behaviour between cohesionless sand and rigid wall of different roughness

2020

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“…One option is to use image analysis techniques. For example, image analysis techniques, together with photography or X-ray computed tomography, have been used to obtain realistic particle shapes 18,71,72 and compute key parameters of contact geometric features, including contact normal orientation, contact area, contact point, and so forth. [73][74][75] There are also attempts on the image analysis-based DEMs, such as the orientation discretization database solution 76,77 or the level set-DEM.…”

Section: Discussionmentioning

confidence: 99%

Machine‐learning‐enabled discrete element method: Contact detection and resolution of irregular‐shaped particles

Lai

Chen

Huang

2021

Num Anal Meth Geomechanics

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This paper presents a machine learning (ML)-enabled discrete element method (DEM) for the computational mechanics of irregular-shaped particles. MLenabled DEM, as with most conventional DEMs, encompasses four main steps in one typical calculation cycle, namely, (1) the detection and resolution of contacts, (2) the evaluation of contact behavior, (3) the calculation of particle motion, and (4) the updating of particle geometric descriptions. Unlike conventional DEMs, the proposed method constructs and employs neural networks to detect particle contacts and resolve contact geometric features. Neural networks take particle geometric descriptors as inputs and output the contact status and contact geometric features. Using two-dimensional elliptical particles as an example, the performance of the ML-enabled DEM is investigated through five numerical experiments and compared with analytical solutions or conventional DEM methods. A sixth numerical experiment involving irregular-shaped particles is also presented to showcase the potential and applicability of the proposed method for other particle shapes. ML-enabled DEM can accurately capture the trajectory and energy evolution of individual particles, the fabric characteristics of dense packing, and the mechanical behavior of packing under large loads, while demonstrating computational efficiency over conventional methods.

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“…Aggregate morphology including 3D form (or sphericity), angularity (or roundness), and surface texture (or roughness) characteristics (see Figure 6 a) has long been recognized as influential for compaction and mechanical properties. The 3D laser scanner shown in Figure 6 b was used to collect, analyze, and reconstruct the 3D geometries of individual coarse aggregate particles, from which particle morphology can be further quantified from reconstructed digital geometry [ 44 , 45 ]. As previously mentioned, the perimeter sphericity and convexity parameters were defined by Zheng [ 45 ] in Equations (3) and (4), respectively.…”

Section: Experimental Materials Equipment and Testing Programmentioning

confidence: 99%

“…The 3D laser scanner shown in Figure 6 b was used to collect, analyze, and reconstruct the 3D geometries of individual coarse aggregate particles, from which particle morphology can be further quantified from reconstructed digital geometry [ 44 , 45 ]. As previously mentioned, the perimeter sphericity and convexity parameters were defined by Zheng [ 45 ] in Equations (3) and (4), respectively.

where P c denotes the perimeter of the circle having the same projected area as the particle, P s denotes the perimeter of the particle, V x denotes the volume of the convex hull of the particle, and V i denotes the volume of the largest inscribed sphere of the particle.…”

Section: Experimental Materials Equipment and Testing Programmentioning

confidence: 99%

“…The 3D laser scanner shown in Figure 6b was used to collect, analyze, and reconstruct the 3D geometries of individual coarse aggregate particles, from which particle morphology can be further quantified from reconstructed digital geometry [44,45]. As previously mentioned, the perimeter sphericity and convexity parameters were defined by Zheng [45] in Equation (3) and Equation (4), respectively.…”

Section: Particle Shape Quantificationmentioning

confidence: 99%

See 1 more Smart Citation

Evaluating Gyratory Compaction Characteristics of Unbound Permeable Aggregate Base Materials from Meso-Scale Particle Movement Measured by Smart Sensing Technology

Xiao

Wang

et al. 2021

Materials

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The quality of compaction of unbound aggregate materials with permeable gradation plays a vital role in their field performance; however, there are currently few unanimously accepted techniques or quality control criteria available for ensuring adequate compaction of such materials in either laboratory or field applications. This paper presented testing results of a laboratory gyratory compaction study where the combinations of gyratory parameters were properly designed using the orthogonal array theory. Innovative real-time particle motion sensors were employed to record particle movement characteristics during the compaction process and provide a meso-scale explanation about compaction mechanisms. Particle abrasion and breakage were also quantified from particle shape digitized from the three-dimensional (3D) laser scanner before and after compaction. The optimal combination of gyratory parameters that yields the best compaction performance was determined from the orthogonal testing results with the relative importance of major influencing parameters ranked accordingly. Meso-scale particle movement at the upper center and center side positions of the specimen are promising indicators of compaction quality. The gyratory compaction process can be consistently divided into three distinct stages according to both macro-scale performance indicators and meso-scale particle movement characteristics. A statistically significant bi-linear relationship was found to exist between relative breakage index and maximum abrasion depth, whereas the quality of compaction and the extent of particle breakage appear to be positively correlated, thus necessitating the cost-effective balance between them. The results of this study could provide technical insights and guidance to field compaction of unbound permeable aggregates.

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Three-dimensional Wadell roundness for particle angularity characterization of granular soils

Cited by 71 publications

References 86 publications

3D DEM simulations of monotonic interface behaviour between cohesionless sand and rigid wall of different roughness

3D DEM simulations of monotonic interface behaviour between cohesionless sand and rigid wall of different roughness

Machine‐learning‐enabled discrete element method: Contact detection and resolution of irregular‐shaped particles

Evaluating Gyratory Compaction Characteristics of Unbound Permeable Aggregate Base Materials from Meso-Scale Particle Movement Measured by Smart Sensing Technology

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