(398f) An Adhesive CFD–DEM Model for Simulating Nanoparticle Fluidization | AIChE

(398f) An Adhesive CFD–DEM Model for Simulating Nanoparticle Fluidization


Liu, D. - Presenter, Delft University of Technology
van Wachem, B. G. - Presenter, Imperial College London
Mudde, R. F. - Presenter, Delft University of Technology
Chen, X. - Presenter, Southeast University
van Ommen, J. R. - Presenter, Delft University of Technology

fluidization is an efficient technique to disperse and process nanoparticles
[1]. Previous studies show that it works, because we do not fluidize individual
nanoparticles, but nanoparticle agglomerates as hierarchical fractal structures
[2]. In this study, an adhesive CFD?DEM (Computational Fluid Dynamics ?
Discrete Element Modelling) model is developed, in which we use as the discrete
element the simple agglomerate, which roughly represent the smallest clusters that
are not broken during fluidization. We show that both the particle contact
model and drag force interaction in the conventional CFD?DEM model need
modification for properly simulating fluidization of nanoparticle agglomerates.
The adhesive contact model includes energy dissipation from the
elastic/plastic, cohesive and viscoelastic forces, and the drag force is
corrected by a scale factor resulting from particle agglomeration. The model is
tested for different cases, including the normal impact, response of angle,
agglomerate formation, and fluidization. The simulation results are promising. Figure
1 shows examples of solid particle flow patterns in a fluidized bed under
different adhesive forces. With increasing particle adhesive force, the
fluidized bed goes from a uniform fluid-like regime, to an agglomerate bubbling
regime, and finally to defluidization. The current study provides a tool for
gaining insights into characteristics of nanoparticle fluidization.

Figure 1. Snapshots
of solid particle flow patterns. The ratio of the particle adhesive force over
the particle weight is 0, 20, 50, and 100, respectively.


[1] van Ommen, J.R., Valverde, J.M. and
Pfeffer, R. (2012) J. Nanopart. Res. 14, 737

[2] de Martin, L. and van Ommen, J.R. (2013) J.
Nanopart. Res
. 15,