(476g) Computational Fluid Dynamics for the Analysis and Optimization of a Lab-Scale Stirred Tank Reactor With Catalytic Basket
AIChE Annual Meeting
2013
2013 AIChE Annual Meeting
Catalysis and Reaction Engineering Division
Computational Fluid Dynamics in Chemical Reaction Engineering
Wednesday, November 6, 2013 - 2:10pm to 2:30pm
Lab-scale stirred tank reactors with catalytic baskets are used in petroleum and biofuels R&D to perform kinetic studies and primary screening tests for the selection of shaped catalysts (beads and extrudates). Different reactive systems, liquid-solid and gas-liquid-solid, are studied in these kind of reactors: selective hydrogenations, hydroconversions, transesterifications, etc. With the increasing catalysts efficiency and the use of complex fluids like heavy crude feedstocks or biomass derived, tests and catalyst selection in lab-scale stirred tank reactors are often hindered by hydrodynamics and mass transport limitations. Achieving a kinetically controlled operational regime is particularly important for fast or consecutive-competitive reactions.
For the study and optimization, the present work concerns the development of a 3D Computational Fluid Dynamics (CFD) model of the gas-liquid-solid flow in catalytic basket reactors. A commercial lab-scale reactor with a radial six-bladed self-inducing hollow impeller and a fixed annular basket was selected for the study. Turbulence in the tank was simulated with the k-ε model and the MRF approach was chosen to deal the impeller motion. The flow in the basket filling was simulated as a homogeneous porous medium with the Brinkman-Forchheimer equations and the basket walls were simulated as semi-permeable zero-thickness surfaces with a pressure drop. The Eulerian model was chosen for the simulation of the gas-liquid multiphase flow. Numerical results were compared with experimental data from Particle Image Velocimetry and a bubble tracking imaging technique.
CFD simulations provided the velocity field and the gas volume fraction in each point of the domain for different operational conditions, which were used for the prediction of the mass transfer rates (kS and kLa). The developed CFD flow model can then be used as an optimization tool for the improvement of reactor configuration or to set optimal operational conditions for kinetic and screening tests.