Three phase simulation bubble columns

In chap 8 the basic bubble column constructions and the principles of operation of these reactors are described. The classical models for two- and three phase simple bubble column reactors are defined based on heat and species mass balances. The state of the art on fluid djmamic modeling of bubble column reactors is then summarized including a few simulations of reactive flows. 

Matos EM, Guirardello R, Mori M, Nunhez JR. Modeling and simulation of a pseudo-three-phase slurry bubble column reactor applied to the process of petroleum hydrodesulfurization. CompuL Chem. Eng. 2009 33 1115-1122. 

FIGURE 11.13 Three phase simulation of bubble columns (from Krishna et al., 2000a). 

Computational fluid dynamics (CFD) is rapidly becoming a standard tool for the analysis of chemically reacting flows. For single-phase reactors, such as stirred tanks and empty tubes, it is already well-established. For multiphase reactors such as fixed beds, bubble columns, trickle beds and fluidized beds, its use is relatively new, and methods are still under development. The aim of this chapter is to present the application of CFD to the simulation of three-dimensional interstitial flow in packed tubes, with and without catalytic reaction. Although the use of... 

Krishna, R., van Eaten, J.M. and Ursenau, M.I. (2000a), Three-phase Eulerian simulations of bubble column reactors operating in the churn-turbulent regime a scale-up strategy, Chem. Eng. Sci., 55, 3275-3286. 

Padial, N.T., VanderHeyden, W.E., Rauenzahn, R.M. and Yarbro, S.L. (2000), Three-dimensional simulation of a three-phase draft-tube bubble column, Chem. Eng. Sci., 55, 3261-3273. 

Padial et al. [91] performed qualitative simulations of three-phase flow in a draff tube bubble column and compared the overall gas volume fraction and liquid circulation time for gas-liquid and gas-liquid-solid systems. Michele and Hempel [92] simulated flow air bubbles and PMMA particles (300 pm, 10 vol%) dispersed in water for superficial gas velocities in the range of 0.02-0.09 m/s. They compared their predictions with measured overall gas holdup and only a qualitative agreement... 

In a recent study Jakobsen et al. [71] examined the capabilities and limitations of a dynamic 2D axi-symmetric two-fluid model for simulating cylindrical bubble column reactor flows. In their in-house code all the relevant force terms consisting of the steady drag, bulk lift, added mass, turbulence dispersion and wall lift were considered. Sensitivity studies disregarding one of the secondary forces like lift, added mass and turbulent dispersion at the time in otherwise equivalent simulations were performed. Additional simulations were run with three different turbulence closures for the liquid phase, and no shear stress terms for the gas phase. A standard k — e model [95] was used to examine the effect of shear induced turbulence, case (a). In an alternative case (b), both shear- and bubble induced turbulence were accounted for by linearly superposing the turbulent viscosities obtained from the A — e model and the model of Sato and Sekoguchi [138]. A third approach, case (c), is similar to case (b) in that both shear and bubble induce turbulence contributions are considered. However, in this model formulation, case (c), the bubble induced turbulence contribution was included through an extra source term in the turbulence model equations [64, 67, 71]. The relevant theory is summarized in Sect. 8.4.4. 

Sha et al [130, 131] developed a similar multifluid model for the simulation of gas-liquid bubbly flow. To guarantee the conservation of mass the population balance part of the model was solved by the discrete solution method presented by Hagesaether et al [52]. The 3D transient simulations of a rectangular column with dimensions 150 x 30 x 2000 (mm) and the gas evenly distributed at the bottom were run using the commercial software CFX4.4. For the same bubble size distribution and feed rate at the inlet, the simulations were carried out as two, three, six and eleven phase flows. The number of population balance equations solved was 10 in all the simulations. It was stated that the higher the number of phases used, the more accurate are the results. 

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