The Effect of Clusters on the Heat and Mass Transfer in Fluidized Gas-Particle Flows

Gas-particle flows play a crucial role in modern industrial applications. In times of an intense requirement of enormous energy savings in industrial reactors, simulation and modelling is an important tool to asses those processes. Still, computational resources are limited and the time needed to simulate even a few seconds of process time in full-scale reactors is unfeasible for the industry. Although CFD is a potent tool, which can uncover the flow inside the reactors and newer methods, such as the Discreet Element Method (DEM) for particles, enable potent descriptions of the micro-scale flow, the multi-scale nature of gas-particle flows hinders the use of coarse numerical grids, which can speed-up the simulation time. Essentially, it was observed that the meso-scale flow structures, such as particle clusters and streamers, have a crucial influence on the macro-scale flow properties and not accounting for them leads to a considerable overestimation of the drag as well as heat and mass transfer in the system.

In particular, the mass transfer between the phases is also greatly affected by the clustering of the system. We identify the main properties in the species transport equation by application of spatial filters. We find that the species diffusion, which is a function of the particle Reynolds number, is severely overestimated if the particle clustering is not considered. In accordance to the better-known drift velocity correction to the resolved drag force and the newly established drift temperature correction to the heat transfer, we propose another drift scalar approach in order to qualify and quantify the correction to the resolved mass transfer in coarse-grid CFD simulations. In the framework of multi-phase turbulence modelling, the drift scalar is then expressed as a covariance between the solid volume fraction and the species concentration and modelled using a dynamic test-filtering approach.