(261a) Numerical Modeling of Deagglomeration of Cohesive Particles By Turbulence

The transport and deposition of fine particulates in turbulent flows play important roles in many engineering and medical systems. Examples include dry powder inhalers for drug delivery and fluidized bed reactors. Micron-sized particles tend to form aggregates due to inter-particle cohesion. The dynamical evolution and morphology of these aggregates involve a complex interplay between turbulent stresses and inter-particle cohesive forces. As a result, particle clumping can arise under various circumstances, which is known to compromise the performance of the aforementioned systems. Of particular interest to the present study is turbulence-induced breakup of fine particulate aggregates. Solid particles with diameters smaller than the Kolmogorov length scale (d_p < η) are initially aggregated into a spherical ‘clump’ of diameter D > η and placed in homogeneous isotropic turbulence. Parameters are chosen relevant to powder suspended in air such that cohesion due to van der Waals is important. Simulations are performed using a CFD-DEM framework that models two-way coupling between the fluid and solid phases and resolves particle-particle interactions. Aggregate breakup is investigated for different Adhesion numbers Ad, Taylor micro-scale Reynolds numbers Re_λ and nondimensional clump sizes D/d_p. The intermittency of turbulence is found to play a key role on the early-stage breakup process, which can be characterized by a turbulent Adhesion number Ad_η that relates the potential energy of the van der Waals force to turbulent shear stresses. A scaling analysis shows that the time rate of breakup for each case collapses when scaled by Ad_η and an aggregate Reynolds number proportional to D. A phenomenological model of the breakup process is proposed that acts as a granular counterpart to the Taylor Analogy Breakup (TAB) model commonly used for droplet breakup. Such a model is useful for predicting particle breakup in coarse-grained simulation frameworks, such as Reynolds-averaged Navier–Stokes, where relevant spatial- and temporal-scales are not resolved.