Tuesday, November 6, 2007 - 3:55 PM
286b

Effect Of Intra-Bed Flow Maldistribution On Chemical Conversion In Microfibrous Materials Using Computational Fluid Dynamics

Ravi Duggirala1, Chris J. Roy1, Ranjeeth Kalluri2, Hongyun Yang2, Donald Cahela3, and Bruce J. Tatarchuk4. (1) Aerospace Engineering, Auburn University, Auburn, AL 36832, (2) Chemical Engineering, Auburn University, 371 West Glenn Avenue, Auburn, AL 36832, (3) Center for Microfibrous Materials Manufacturing, Department of Chemical Engineering, Auburn University, AL 36849, (4) Center for Microfibrous Materials Manufacturing, 230 Ross Hall, Dept. of Ch. E., Auburn, AL 36849-5127

In packed beds at low Reynolds numbers, flow maldistribution can adversely affect the chemical conversion rates due to the fluid's tendency to preferentially flow through open regions of the bed. These effects can be minimized by increasing the voidage and allow uniform flow distribution. High voidages and uniform flow distribution are possible by using Microfibrous entrapped sorbents (MFES). MFES consists of small particles (100-200 µm) of adsorbent entrapped in sintered bonded micro-fibers (2-10 µm). These materials have been developed by Auburn's Center for Microfibrous Materials Manufacturing (CM3) using a simple wet-layup process. These materials showed improvement in chemical conversion rates over packed beds. Computational Fluid Dynamics (CFD) is being used to understand the physical and chemical phenomena involved in the enhancement of chemical conversion rates. In this study, particles are uniformly clustered in all directions in the material to analyze the effects of flow maldistribution. Clustering of particles is varied by using a dimensionless parameter called clustering parameter which goes from 0 (uniformly distributed particles) to 1 (highly clustered particles). The effect of flow maldistribution on chemical conversion is studied by varying the dimensionless numbers which characterize different gas-phase reactions: viscosity, diffusivity, and reaction rates. The dimensionless numbers that are varied in this study are Reynolds number, Peclet number, and Damkohler number.