A multivariate regression parametric study on DEM input parameters of free-flowing and cohesive powders with experimenta
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A multivariate regression parametric study on DEM input parameters of free‑flowing and cohesive powders with experimental data‑based validation Bilal El‑Kassem1,2 · Nizar Salloum2 · Thomas Brinz2 · Yousef Heider1 · Bernd Markert1 Received: 25 September 2019 / Revised: 10 December 2019 / Accepted: 10 January 2020 © The Author(s) 2020
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. Keywords Discrete element method · Free-flowing powder · Cohesive powder · Design of experiment · Multivariate regression analysis · Angle of repose
1 Introduction One of the big challenges in the pharmaceutical industry is to optimize the powder solid handling process performance. This significantly relies on the flowability of the granular material in different process stages including hopper discharge, powder feeding, blending, mixing and die filling. Flowability, which describes the behavior of powder, is dependent on a range of fundamental powder properties. The flow properties of powders can be affected by various essential particle properties, including mean particle size and distribution, particle shape, surface roughness and * Yousef Heider [email protected]‑aachen.de 1
Institute of General Mechanics, RWTH Aachen University, Templergraben 64, 52062 Aachen, Germany
Robert Bosch Packaging Technology GmbH, Stuttgarter Str. 130, 71332 Waiblingen, Germany
2
moisture content. Powder flow also depends on the interparticle interactions where, for instance, flowability decreases with increasing cohesiveness of the powder. According to Parker et al. [1], cohesion is defined as the bonding or joining of two particles of
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