278481 A Novel Mppic Methodology for Numerical Simulations of Gas-Solids Flows

Monday, October 29, 2012: 1:15 PM
Conference C (Omni )
Rahul Garg1,2, Jean-Francois Dietiker2,3 and Mehrdad Shahnam2, (1)URS Corp, Morgantown, WV, (2)National Energy Technology Laboratory, Morgantown, WV, (3)West Virginia University Research Corporation, Morgantown, WV

CFD simulations of gas-solids flows are done either using continuum representation for both gas and solid phases (Two-Fluid Method) or using continuum representation for gas phase and a discrete representation for solid phase (Continuum-Discrete Method). The CFD simulations of dense multiphase flow applications suffer from very high computational turnaround times. This is either due to severe numerical instabilities in the frictional stress regime observed in two fluid method or due to very small time steps in fully resolved collision operators (such as soft spring model) in continuum discrete method using real particles. In the MPPIC (Multi Phase – Particle In Cell) methodology, continuum representation is used for the gas-phase. The solids phase is represented by discrete entities that map the solids loading. These discrete entities are generally referred to as computational particles or parcels or notional particles. In this approach, multiple particles are clubbed together to form one parcel. The parcels trajectories are tracked in a Lagrangian frame and a frictional stress term is added in order to prevent solids loading over the theoretically allowed limits. So far, available MPPIC models implemented into commercial CFD solvers provide limited description of the exact form of frictional stress models used. In this study we present an MPPIC method with a novel frictional stress term that has been implemented in the open source reactive multiphase flow CFD solver MFIX (Multiphase Flow with Interface eXchange). The newly developed frictional stress model is based on a combination of a coloring function and four simple post-collision rules. The results of MPPIC simulations obtained from MFIX for chosen fluidized bed applications are compared with more accurate continuum discrete method and also the two-fluid method in order to assess the relative accuracy and computational efficiency of different numerical simulation methodologies.

Extended Abstract: File Not Uploaded