Large-scale GPU based DEM modeling of mixing using irregularly shaped particles

Govender, N.; Wilke, Daniel N.; Wu, Chuan‐Yu; Rajamani, Raj K.; Khinast, Johannes G.; Glasser, Benjamin J.

doi:10.1016/j.apt.2018.06.028

Cited by 75 publications

(21 citation statements)

References 51 publications

(74 reference statements)

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“…Govender et al investigated the hopper discharge of irregular non-convex particle shapes using GPU-based DEM software [127]. Also, Govender et al studied the effect of particle shape (i.e., spheres, cubes, scaled hexagonal prism, bilunabirotunda, truncated tetrahedral and mixed particle system) on blending uniformity [128]. In this study, each particle shape was defined by GPU-based DEM software.…”

Section: Comprehensive Theory Of Discrete Element Methodsmentioning

confidence: 99%

Application of the Discrete Element Method for Manufacturing Process Simulation in the Pharmaceutical Industry

Yeom

Kim

et al. 2019

Pharmaceutics

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Process simulation using mathematical modeling tools is becoming more common in the pharmaceutical industry. A mechanistic model is a mathematical modeling tool that can enhance process understanding, reduce experimentation cost and improve product quality. A commonly used mechanistic modeling approach for powder is the discrete element method (DEM). Most pharmaceutical materials have powder or granular material. Therefore, DEM might be widely applied in the pharmaceutical industry. This review focused on the basic elements of DEM and its implementations in pharmaceutical manufacturing simulation. Contact models and input parameters are essential elements in DEM simulation. Contact models computed contact forces acting on the particle-particle and particle-geometry interactions. Input parameters were divided into two types—material properties and interaction parameters. Various calibration methods were presented to define the interaction parameters of pharmaceutical materials. Several applications of DEM simulation in pharmaceutical manufacturing processes, such as milling, blending, granulation and coating, were categorized and summarized. Based on this review, DEM simulation might provide a systematic process understanding and process control to ensure the quality of a drug product.

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Section: Comprehensive Theory Of Discrete Element Methodsmentioning

confidence: 99%

Application of the Discrete Element Method for Manufacturing Process Simulation in the Pharmaceutical Industry

Yeom

Kim

et al. 2019

Pharmaceutics

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“…Computing the volume of a convex hull, with a computationally efficient algorithm is not a trivial task. The details of volume computing are given in Govender et al (2018a;2018b;2018c). First, the bounding surfaces and their respective normal are determined.…”

Section: Contact Mechanicsmentioning

confidence: 99%

Verification of Polyhedral DEM with Laboratory Grinding Mill Experiments

Puga

Govender

Rajamani

2022

KONA

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The simulation of grinding mills with the discrete element method (DEM) has been advancing. First, it emerged as a method for studying charge motion with spherical balls and predicting the power draw of the mill. Subsequently, studies on liner wear, charge motion with ellipsoidal and polyhedral shaped particles simulated with three dimensional DEM followed. Further, the impact energy spectra computed in the DEM algorithm is leading to the development of models for the breakage of brittle particles in mills. The core elements in such simulations are the shape of particles in the mill charge and the power draw of the mill due to operating variables. To advance the field, we present a set of experimental data and the corresponding DEM validation results for a 90 × 13 cm mill. The DEM algorithm uses the volume-overlap method which is more realistic for multifaceted irregular particle collisions. Further, we use the scanned shape of the rock media and multifaceted spherical shape for the grinding media to represent as close as possible the actual charge in the mill. First, we present DEM validation for spherical grinding media-only experiments, rock-only experiments, and a mixture of spherical grinding media and rocks, as well as aluminum cubes only to represent the theme of particle shape. Finally, a discussion of the contact mechanics parameters in the four modes of experiments is given. Since the feed ore to plant scale mills can vary in shape, mill simulations with scanned shape of typical particles are the future for more accurate results.

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“…A curved wall boundary cannot be created by the staggered grid, and no useful model exists for the moving wall boundary. Apart from the problem regarding the wall boundary, industrial-scale DEM-CFD simulation has not been performed on a single PC, though latest multi-core processors such as central processing unit (CPU) and graphical processing unit (GPU) have been developed (Shigeto and Sakai, 2011;Govender et al, 2018). This is because the DEM-CFD simulations cannot be finished within practical calculation time when the number of the computational particles approaches to the actual one.…”

Section: Introductionmentioning

confidence: 99%

Recent Progress on Mesh-free Particle Methods for Simulations of Multi-phase Flows: A Review

Sakai

Mori

Sun

et al. 2020

KONA

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The discrete element method (DEM) and the moving particle semi-implicit (MPS) method are the most popular mesh-free particle methods in the discontinuum and continuum. This paper describes a state-of-the-art modeling on multi-phase flows using these mesh-free particle methods. Herein, a combinational model of the signed distance function (SDF) and immersed boundary method (IBM) is introduced for an arbitrary-shaped wall boundary in the DEM simulation. Practically, this model uses a simple operation to create the wall boundary. Although the SDF is a scalar field for the wall boundary of the DEM, it is useful for the wall boundary of the CFD through combination with the IBM. Validation tests are carried out to demonstrate the adequacy of the SDF/IBM wall boundary model. Regarding the mesh-free particle method for continuum, the phase change problem is one of the challenging topics, as the solid state is usually modeled by extremely high viscous fluid in the phase change simulation. The phase change simulation is shown to be efficiently performed through an implicit algorithm and a heat flux model in the MPS method. The adequacy of these models is verified by the numerical examples.

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Large-scale GPU based DEM modeling of mixing using irregularly shaped particles

Cited by 75 publications

References 51 publications

Application of the Discrete Element Method for Manufacturing Process Simulation in the Pharmaceutical Industry

Application of the Discrete Element Method for Manufacturing Process Simulation in the Pharmaceutical Industry

Verification of Polyhedral DEM with Laboratory Grinding Mill Experiments

Recent Progress on Mesh-free Particle Methods for Simulations of Multi-phase Flows: A Review

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