A multivariate regression parametric study on DEM input parameters of free-flowing and cohesive powders with experimental data-based validation

Abstract

One of the key challenges in the implementation of discrete element method (DEM) to model powder's flow is the appropriate selection of material parameters, where empirical approaches are mostly applied. The aim of this study is to develop an alternative systematic numerical approach that can efficiently and accurately predict the influence of different DEM parameters on various sought macroscopic responses, where, accordingly, model validation based on experimental data is applied. Therefore, design of experiment and multivariate regression analysis, using an optimized quadratic D-optimal design model and new analysis tools, i.e., adjusted response and Pareto graphs, are applied. A special focus is laid on the impact of six DEM microscopic input parameters (i.e., coefficients of static and rolling friction, coefficient of restitution, particle size, Young's modulus and cohesion energy density) on five macroscopic output responses (i.e., angle of repose, porosity, mass flow rate, translational kinetic energy and computation time) using angle of repose tests applied to free-flowing and cohesive powders. The underlying analyses and tests show, for instance, the substantial impact of the rolling friction coefficient and the minor role of the static friction coefficient or the particle size on the angle of repose in cohesive powders. In addition, in both powders, the porosity parameter is highly influenced by the static and rolling friction coefficients.

Crystallographic tomography and molecular modelling of structured organic polycrystalline powders

“…These physical chemical force vectors provide a missing but vital link between knowledge of the crystal morphology 48 and crystal-crystal interactions at a condensed matter scale. 61,62 This should lead to better predictive models of hexamine behaviour, which would be useful for example in optimising industrial scale processes. 56 In the present study, the fraction (83 vol%) of the hexamine powder bed that is agglomerated is high, but there are a number of different mechanisms for fused agglomerate formation.…”

Review: The Calibration of DEM Parameters for the Bulk Modelling of Cohesive Materials

“…Although the lifting cylinder test is the most commonly used angle of repose test, other methods, such as the pouring method, are available. Material is poured from a funnel, hopper, or bin at a fixed or variable height onto a pile, from where the angle can be measured; see [93,[97][98][99][100][101][102][103][104] for examples. However, compared to the lifting cylinder test, these tests might be even less suited for cohesive materials.…”

An offline multi‐scale unsaturated poromechanics model enabled by self‐designed/self‐improved neural networks

“…The databases for the ML‐based prediction models are constructed based on a representative volume element (RVE) generated from the discrete element model (DEM). References and details about the DEM equations and application can be found in, for example, El‐Kassem et al 75,76 . The DEM RVE serves as a platform to perform both the single‐ and multi‐phase flow simulations, such that the resultant permeability tensor and water retention curves can be stored in each database (Figure 2).…”