A methodology for calibration of DEM input parameters in simulation of segregation of powder mixtures, a special focus on adhesion

Abstract

Conducting a numerical simulation for cohesive granular mixtures that is well comparable with experiments has always been a challenge. In this study, a systematic methodology is proposed for increasing the fidelity of Discrete Element Method (DEM) simulations of cohesive powder mixtures. Segregation of granules during heap formation of a ternary powder mixture is simulated as a proof of concept. The mixture contains three model particles, one of which is an enzyme placebo granule (EP), in order to simulate the segregation of the actual enzyme granules used in detergent formulations. These granules are at a low content level (wt) and are highly prone to segregation. In this study the segregation tendency of the EP granules is mitigated by coating them with Polyethylene Glycol 400 (PEG 400). The resulting adhesion is expressed in terms of equivalent interfacial energy for the DEM numerical simulations, and is tuned by careful calibration using the concept of the angle of repose. The Cohesion number is used to scale material stiffness or changing the particle size for faster simulation. The particles shapes in DEM are modelled as clumped spheres based on the X-ray tomograms of the real particles. The rest of the DEM input parameters are also selected and tuned based on the particles physical and mechanical properties. Considerable reduction in segregation tendency of the low level ingredient granules is observed as a result of coating its surfaces by PEG400. Following the proposed calibration strategy, the DEM simulations have predicted the experimental trends closely and a reasonable agreement is achieved. It is observed that using the Cohesion number for scaling the interfacial energy can significantly reduce the number of calibration trials.

Calibration and Verification of Dynamic Particle Flow Parameters by the Back-Propagation Neural Network Based on the Genetic Algorithm: Recycled Polyurethane Powder

“…Figure 4b–d denote that the PU powder pile exhibits good symmetry. Alizadeh et al [15] proposed that the high material is generally 10%–90% to avoid large fluctuations in the boundary contour of the material particles during stacking. For fitting the final boundary contour, the contour is read using the computer image processing technology and then processed by gradation and binarization; the boundary is subsequently extracted, and the boundary point is linearly fitted using the least-squares method to obtain the left and right boundaries of the powder particle stack.…”

“…In addition, the equivalent surface energy is calculated by increasing the particle size and reducing the shear modulus. In addition, Alizadeh et al [15] used this method. For example, the average surface energy of the PU particles is 0.0214 J/m 2 [28]; when this value is substituted into Equation (2), the cohesion number is observed to be 0.000622.…”

“…They used quartz sand particles to optimize the model accuracy and simulation time and demonstrated that the contact parameters of the materials can be accurately calibrated within the optimal simulation time. Simultaneously, coarse granulation is the most common modeling approach for the calibration of the discrete element parameters of special particles (including wet particles and ultrafine polymer powders), as demonstrated by Alizadeh et al [15] for polyethylene glycol 400 (PEG 400). In a study investigating the coating treatment of the EP particles, the concept of cohesive number was used in the DEM numerical simulation to measure the shear modulus of the material or to change the particle size to ensure that the surface energy could be rapidly scaled and that the calibration time could be substantially reduced.…”

Assessment of blending performance of pharmaceutical powder mixtures in a continuous mixer using Discrete Element Method (DEM)

“…where and are the radii of the spheres, and are their Young's moduli, and and are their Poisson's ratios. This method of scaling has been used in other researches successfully [53][54][55].…”

Mechanical properties of coordination polymer-based dietary supplements

“…Blending and granulation processes are also highly influenced by crystal morphology, mechanical and surface properties. The segregation in mixtures (e.g., API and excipient) is commonly induced by the difference of particles size, density and surface energy [44,45]. The segregation of API and excipient can result in undesired product qualities, such as over-or underdosing.…”