CFD-PBE coupled model for size-driven segregation in polydisperse granular flows

Mixtures of granular materials made of different-sized particles may segregate when subjected to vibration or shear rate and in the presence of a gravitational field. This leads to highly inhomogeneous mixtures, which are undesirable in many industrial processes. This work focuses on size-driven segregation in polydisperse mixtures. We described the evolution of the particle size distribution through a Population Balance Equation (PBE), which we solved numerically with the Direct Quadrature Method of Moments. To allow segregation and micromixing to occur, we closed the size-conditioned velocity of the particles with a segregation- mixing model. The PBE was then included in an Eulerian-Eulerian model and solved in a commercial Computational Fluid Dynamics (CFD) code. We used the model to study granular flows down inclined planes. The numerical results were then compared with those obtained from Discrete Element Method simulations. The CFD-PBE model predicts well segregation and micromixing in packed beds of polydisperse powders

MercuryDPM:A fast and flexible particle solver part a: Technical advances

MercuryDPM is an open-source particle simulation tool—fully written in C++—developed at the University of Twente. It contains a large range of contact models, allowing for simulations of complex interactions such as sintering, breaking, plastic deformation, wet-materials and cohesion, all of which have important industrial applications. The code also contains novel complex wall generation techniques, that can exactly model real industrial geometries. Additionally, MercuryDPMs’ state-of-the-art built-in statistics package constructs accurate three-dimensional continuum fields such as density, velocity, structure and stress tensors, providing information often not available from scaled-down model experiments or pilot plants. The statistics package was initially developed to analyse granular mixtures flowing over inclined channels, and has since been extended to investigate several other granular applications. In this proceeding, we review these novel techniques, whereas its applications will be discussed in its sequel.</p