382418 Agglomerate Size Distribution in Wet Gas Fluidized Systems

Tuesday, November 18, 2014
Galleria Exhibit Hall (Hilton Atlanta)
Ziv Greidinger1, Matthew Girardi2, Stefan Radl3, Benjamin J. Glasser4, Sankaran Sundaresan2 and Avi Levy5, (1)Princeton University, Princeton, NJ, (2)Department of Chemical and Biological Engineering, Princeton University, Princeton, NJ, (3)Institute for Process and Particle Engineering, Graz University of Technology, Graz, Austria, (4)Chemical and Biochemical Engineering, Rutgers University, Piscataway, NJ, (5)Mech. Eng., Ben-Gurion University of the Negev, Beer Sheva, Israel

Wet fluidized beds in which the solids are wetted by a liquid prior to or during fluidization by a gas are common in energy, chemical, food and pharmaceutical industries. Colliding wet particles form liquid bridges, promoting agglomeration, which is desirable in some contexts such as granulation, but is undesirable in others.

When a gas fluidizes pre-wetted particles, the resulting agglomerate particle size distribution (PSD) influences important physical processes such as momentum, mass and energy transfer between the particles and the gas. In order to probe the effect of liquid bridge characteristics on PSD and fluidization behavior, we perform Euler-Lagrange simulations of wet-particle fluidization in small periodic domains. Specifically, the averaged equations of motion for the gas phase are solved on an Eulerian grid (commonly referred to as Computational Fluid Dynamics of the gas phase) along with Newton’s equations for all the particles (via Discrete Element Method) (Kloss. 2012, Zhou 2010). The liquid bridge characteristics are introduced through algebraic models for the capillary force due to the bridge and the bridge rupture distance (Mikami 1998, Willett 2000), which introduces two dimensionless groups: Bond number and dimensionless liquid bridge volume.

In this presentation, we examine the PSDs obtained for a range of particle volume fractions and liquid bridge characteristics, by first establishing a dynamic, but statistically steady, fluidized state and then analyzing many snapshots gathered at different times. The PSD changes with the Bond number and liquid bridge volume in a systematic manner, which is quantified. These results provide an initial peek into meso-scale structures in wet-fluidized beds and how they affect the slip motion between the gas and the agglomerates. This presentation will describe sample results and discuss how the PSD shifts with fluidization conditions.


Kloss C. , Goniva C., Hager A., Amberger S., Pirker Stefan, 2012. Models, algorithms and validation for opensource DEM and CFD-DEM, Progress in Computational Fluid, v. 12, No. 2-3. pp. 140-152.

Mikami, T., Kamiya, H. & Horio, M., 1998. Numerical simulation of cohesive powder behavior in a fluidized bed.. Chem. Eng. Sci., 53(10), pp. 1927–1940.

Willett, C. D., Adams, M. J., Johnson, S. A. & Seville, J. P. K., 2000. Capillary Bridges between Two Spherical Bodies. Langmuir, v. 16, pp. 9396-9405.

Zhou Z. Y., Kuang S. B., Chu K. W., Yu A. B., 2010. Discrete particle simulation of particle–fluid flow: model formulations and their applicability. J. Fluid Mech., v. 661, pp. 482-510.

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