Comparison of DEM results and Lagrangian experimental data for the flow and mixing of granules in a rotating drum

A comprehensive review of the application of DEM in the investigation of batch solid mixers

Powder mixing is a vital operation in a wide range of industries, such as food, pharmaceutical, and cosmetics. Despite the common use of mixing systems in various industries, often due to the complex nature of mixing systems, the effects of operating and design parameters on the mixers’ performance and final blend are not fully known, and therefore optimal parameters are selected through experience or trial and error. Experimental and numerical techniques have been widely used to analyze mixing systems and to gain a detailed understanding of mixing processes. The limitations associated with experimental techniques, however, have made discrete element method (DEM) a valuable complementary tool to obtain comprehensive particle level information about mixing systems. In the present study, the fundamentals of solid-solid mixing, segregation, and characteristics of different types of batch solid mixers are briefly reviewed. Previously published papers related to the application of DEM in studying mixing quality and assessing the influence of operating and design parameters on the mixing performance of various batch mixing systems are summarized in detail. The challenges with regards to the DEM simulation of mixing systems, the available solutions to address those challenges and our recommendations for future simulations of solid mixing are also presented and discussed.

Chrono::GPU: An Open-Source Simulation Package for Granular Dynamics Using the Discrete Element Method

We report on an open-source, publicly available C++ software module called Chrono::GPU, which uses the Discrete Element Method (DEM) to simulate large granular systems on Graphics Processing Unit (GPU) cards. The solver supports the integration of granular material with geometries defined by triangle meshes, as well as co-simulation with the multi-physics simulation engine Chrono. Chrono::GPU adopts a smooth contact formulation and implements various common contact force models, such as the Hertzian model for normal force and the Mindlin friction force model, which takes into account the history of tangential displacement, rolling frictional torques, and cohesion. We report on the code structure and highlight its use of mixed data types for reducing the memory footprint and increasing simulation speed. We discuss several validation tests (wave propagation, rotating drum, direct shear test, crater test) that compare the simulation results against experimental data or results reported in the literature. In another benchmark test, we demonstrate linear scaling with a problem size up to the GPU memory capacity; specifically, for systems with 130 million DEM elements. The simulation infrastructure is demonstrated in conjunction with simulations of the NASA Curiosity rover, which is currently active on Mars.

Effects of size polydispersity on segregation of spherical particles in rotating drum

To get insight into the segregation process of a polydisperse granular materials flow, we numerically investigated the migration process of particles in a rotating drum operating in the rolling regime by means of the discrete element method. Particle migration is analyzed through the variation of the proportion of particles in different zones where the flow property is characterized. The proportion of particles in different zones of the drum shows to increase in the center of the flow radially and axially where a higher concentration of small particles is observed, while its decreases in other zones with a higher concentration of larger particles. Interestingly, we find that the migration process of particles leads to radial and axial segregation which is caused by a combination between the exerted fluctuation forces on particles and its surrounding pressure gradient.

Positron Emission Particle Tracking of Granular Flows

Positron emission particle tracking (PEPT) is a noninvasive technique capable of imaging the three-dimensional dynamics of a wide variety of powders, particles, grains, and/or fluids. The PEPT technique can track the motion of particles with high temporal and spatial resolution and can be used to study various phenomena in systems spanning a broad range of scales, geometries, and physical states. We provide an introduction to the PEPT technique, an overview of its fundamental principles and operation, and a brief review of its application to a diverse range of scientific and industrial systems.

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

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.