In contrast to classical de-coupled multiscale modelling concepts, hybrid Eulerian/Lagrangian models consider discrete particles and a continuous solid phase concurrently within one simulation. In a first part of this lecture I will present this hybrid modelling concept and discuss its results. Due to the semi-discrete nature of this model, our hybrid Two Fluid Model can efficiently account for particle characteristics like particle size distribution, agglomeration or complex particle reactions.

The second part of this lecture will be dedicated to particulate processes with strongly separated time-scales. In fluidized bed processes the time-scales of flow dynamics can be for instance orders of magnitude smaller than the time-scales of particle conversion. For such processes efficient methods of time-extrapolation are needed, which e.g. exploit the recurrent nature of the process. By means of recurrence CFD (rCFD) we could e.g. simulation the heat transfer in a fluidized bed two orders of magnitude faster than with conventional full CFD simulations. Finally, we can gain another two orders of magnitude in speed-up, if we link the recurring flow pattern to recurring pattern of memory re-distribution. With this new version of rCFD we realized a Large Eddy Simulation on a 640k grid in 1.6 seconds, receiving very similar results as with full CFD (which lasted 26 hours).