431671 Active Contour Tracking of Individual Bubbles in CFD Simulation of Fluidized Beds

Tuesday, November 10, 2015
Ballroom F (Salt Palace Convention Center)
M Helal Uddin1, M Arafat H. Khan2 and Charles J. Coronella1, (1)Chemical & Materials Engineering, University of Nevada, Reno, Reno, NV, (2)Civil and Environmental Engineering, University of Nevada Reno, Reno, NV

In many Geldart B fluidized bed reactors, important reaction phenomena are dominated by bubbling behavior, including rates of heat and mass transfer, solids elutriation, wall erosion, etc. Thus, design and scale-up of bubbling fluidized bed reactors requires accurate prediction of bubble size, frequency, and velocity. This leads to minimal uncertainties in later scale-up, and can ensure that scaled down beds accurately simulate the bubble hydrodynamics  used to describe the gas-solids contact. It is necessary that the bubble be identifiable definable from its source at the distributor all the way up to the bed surface. Empirical models can be used to predict average bubble size and velocity, suitable in some instances. However, a more detailed description of bubbles can be found by CFD simulation. In this study, two- and three-dimensional fluidized beds of 300 mm Geldart B particles are numerically simulated using modern tools of CFD.  The interpenetrating two-fluid model using Eulerian-Eulerian flow field method employed in the open source MFIX software is used to simulate the fluidized bed. The complete set of mass and momentum balance equations are solved to obtain gas and particulate flow fields. Contour plots of bed voidage readily show the characteristics of bubble formation, motion, and eruption at the bed surface, but by themselves are not easily quantified.

This work is comprised of three sections: The first section is the identification of bubble bubbles from the contour maps resulting from MFIX simulations. In this section, we use an adaptive filtering technique to identify and to locate the position of discrete bubbles in the bed at any moment of time. The second section is evaluation of parameters used to identify bubbles . In this section, we compare the computed values of bubble diameter and number of bubbles by specifying different values for the minimum gas volume fraction in each bubble. This provides a general guideline to define a bubble in fluidized beds. The third section is comparing the bubble diameters calculated both from a 2D and 3D simulation using similar physical properties of fluidized bed.

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