A geometry-based algorithm for cloning real grains 2.0

Abstract

We introduce an improved version of a computational algorithm that "clones"/generates an arbitrary number of new digital grains from a real sample of real digitalized granular material. Our improved algorithm produces "cloned" grains that more accurately approach the morphological features displayed by their parents. Now, the "cloned" grains were also included in a Discrete Element Method simulation of a tri-axial test and showed similar mechanical behavior compared to the displayed by the original (parent) sample. Thus, the present work is divided in four parts. First, we compute multivariable probability density functions (PDF) from the parents' morphological parameters (morphological DNA), i.e., aspect ratio, roundness, volume-surface ratio, and particle diameter. Second, an improved, now parallelized and better tuned version of the Geometric Stochastic Cloning (GSC) algorithm [13], which is based on the aforementioned multivariable distributions, and that, in the same way, introduces an enhanced radii sampling process, as well as a new quality control test based on the volume-surface ratio is discussed. Third, morphological DNA of the grains (i.e., aspect ratio, roundness, volume-surface ratio and particle diameter) is also extracted from the new "cloned" grains and compared to the one obtained from the parent sample. Fourth, clones and parents are subjected to a tri-axial compression tests using a Level Set (LS) in Discrete Element scheme (3DLS-DEM), and then, compared in terms of their mechanical response. Finally, the error of the "clones" in the morphology and mechanical behavior is analyzed and discussed for future improvements.

The influence of water content on selected physical properties of cereal seeds to improve the precision of DEM simulation

“…This means that the seed volume can be used as a parameter to improve the DEM simulation process. This fact was confirmed in a study on the volumetric scaling of rice seeds with the discrete element method (DEM) 46 and in a study where the volume-to-surface ratio was used to describe and control particles 47 .…”

Characterization and Generation of 3D Realistic Geological Particles with Metaball Descriptor based on X-Ray Computed Tomography

“…It is necessary to consider its coupling scheme when using a descriptor. Although level-set function has an excellent characterization fidelity, it still has a reliance on computational resources due to the look-up table mechanism in coupling mechanical models (mainly in contact detection of DEM) [33,34,35]. To relieve the efficiency problem in coupling, Zhao and Zhao [35,36] developed a poly-superellipsoid based descriptor yet at the cost of certain constraints on the expressed shape(such as smoothness and complexity).…”

“…the distributions of surface area and volume [43,44], (2) intractable problems in obtaining particles with specific morphological features [49], (3) involving complex mixture models, which are costly in computations and require specialized personal [50] and (4) requiring bridging or transformation into other descriptors before practical simulations, which often results in a trade-off between accuracy and efficiency [51]. Another interesting attempts are geometry-based algorithms [52,34,49,53]. It requires some shape feature distributions as "morphological DNA".…”

“…It requires some shape feature distributions as "morphological DNA". Then, geometric stochastic cloning algorithms [52,34] or the genetic algorithm [49,53] are implemented to generate particles based on those distilled DNA. Although with advance in performance, this type of method still has an reliance on the computational and human resources, which can not be obtained easily by all individuals or institutions.…”

A coupled thermo-mechanical model for the simulation of discrete particle systems in advanced manufacturing.

“…In this technique, disks are subsequent added to conform a cluster in order to capture the shape from a binary image of the particle. In the same line, Jerves et al [28] and Medina and Jerves [29] proposed another approach by the so-called "cloning algorithm", where a set of particles are created following the same morphological parameters, such as aspect ratio, roundness, principal geometric directions, and spherical radius of a sample of real grains that have been previously digitalized. Another type of nonspherical shape is the superquadric (or superquadratic in 3D) geometry, which is an extension of spheres and ellipsoids.…”