Motivation

The design of novel apparatuses can benefit from numerical simulations. These allow for greater insight into the process, rapid evaluation of design variants and enable scale-up after lab-scale vavalidation, reducing the need for costly experiments.

Methodology

The state of the art in granular flow simulation is the Computational Fluid Dynamics-Discrete Element Method (CFD-DEM) which allows for the accurate description of all granular flow phenomena. The fluid phase is described using the Navier-Stokes equations while the granular phase is described using discrete particles obeying the Newtonian equations of motion, with momentum exchange modelled by a drag closure.

The degree of accuracy and applicability requires the resolution of small-scale phenomena like particle collisions and clustering which result in small timesteps and high computational demand. To allow for the treatment of large-scale systems, coarse-graining techniques are applied that attempt to reproduce the bulk behavior by tracking representative computational parcels instead of all individual particles. The Lagrangian nature of CFD-DEM preserves particle identities and enables tracking of physical or chemical processes occurring within the particle, thereby predicting product quality.

Based on these highly-resolved simulations, time extrapolation can be performed using Recurrence CFD (rCFD). This novel approach captures pseudo-periodic flow patterns like bubbling or spouting to allow for the long-term description of transport processes within the system and its constituents.

Objectives

• Implementation of Recurrence CFD in OpenFOAM.
• Development and implementation of a new communication scheme for scaling the CFD-DEM software CFDEMcoupling to hundreds of cores.
• Modelling of heat and mass transfer within pilot scale fluidized and spouted bed granulators.
• Investigation of intra-particle transport processes over the course of granulation.