## Abstract

Bubble columns are widely used in the chemical industry because

of their simple design and high efficiency. The scale-up of these

kinds of columns is challenging and time-consuming. Since high

throughput is targeted, they are operated in the heterogeneous bub-

bling regime where the flow is complex and turbulent. Large-scale

bubble columns can in principle be simulated using continuum

models (TFM/MFM) with closures from more detailed models

such as Front Tracking (FT) or Volume of Fluid (VOF). Multi-fluid

models are capable of predicting the flow field, but to accurately

describe mass transfer rates, an accurate interfacial area of the

bubbles is required as well as mass transfer coefficients for dense

bubble swarms. This requires the MFM to be coupled with models

that can predict bubble size distributions. The Discrete Bubble

Model (DBM) can be scaled up but the bubble-bubble interactions

make it computationally very intensive.

Stochastic Direct Simulation Monte Carlo (DSMC) methods treat

the bubbles in a discrete manner while more efficiently handling

the collisions compared to the DBM. The DSMC model has earlier

been used for very small particles in the size range of Angstroms

to microns where the particles are purely inertial at high Stokes

numbers. In the work of Pawar et al. (2014) this was used for

micrometer sized particles/droplets where this method proved to be

60 to 70 times faster than more classical methods like the Discrete

Particle Model (DPM).

In this work the DSMC method has been extended to finite sized

bubbles/particles in the order of millimeters. A 4-way cou-

pling (liquid-bubble-bubble) is achieved using the volume-averaged

Navier Stokes equations. The model is verified first for mono-

disperse impinging particle streams without gas. Then the model

is verified with the DBM of a 3D periodic bubble driven system.

The collision frequencies are all within 10 percent accuracy and the

speed up achieved per DEM time step is nearly 10 times compared

to the DBM, which facilitates simulation of large systems.

of their simple design and high efficiency. The scale-up of these

kinds of columns is challenging and time-consuming. Since high

throughput is targeted, they are operated in the heterogeneous bub-

bling regime where the flow is complex and turbulent. Large-scale

bubble columns can in principle be simulated using continuum

models (TFM/MFM) with closures from more detailed models

such as Front Tracking (FT) or Volume of Fluid (VOF). Multi-fluid

models are capable of predicting the flow field, but to accurately

describe mass transfer rates, an accurate interfacial area of the

bubbles is required as well as mass transfer coefficients for dense

bubble swarms. This requires the MFM to be coupled with models

that can predict bubble size distributions. The Discrete Bubble

Model (DBM) can be scaled up but the bubble-bubble interactions

make it computationally very intensive.

Stochastic Direct Simulation Monte Carlo (DSMC) methods treat

the bubbles in a discrete manner while more efficiently handling

the collisions compared to the DBM. The DSMC model has earlier

been used for very small particles in the size range of Angstroms

to microns where the particles are purely inertial at high Stokes

numbers. In the work of Pawar et al. (2014) this was used for

micrometer sized particles/droplets where this method proved to be

60 to 70 times faster than more classical methods like the Discrete

Particle Model (DPM).

In this work the DSMC method has been extended to finite sized

bubbles/particles in the order of millimeters. A 4-way cou-

pling (liquid-bubble-bubble) is achieved using the volume-averaged

Navier Stokes equations. The model is verified first for mono-

disperse impinging particle streams without gas. Then the model

is verified with the DBM of a 3D periodic bubble driven system.

The collision frequencies are all within 10 percent accuracy and the

speed up achieved per DEM time step is nearly 10 times compared

to the DBM, which facilitates simulation of large systems.

Original language | English |
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Title of host publication | Progress in Applied CFD – CFD2017 |

Subtitle of host publication | Proceedings of the 12th International Conference on Computational Fluid Dynamics in the Oil & Gas, Metallurgical and Process Industries, 30 May -1 June 2017, Trondheim, Norway |

Place of Publication | Blindern |

Publisher | SINTEF Academic Press |

ISBN (Electronic) | 978-82-536-1544-8 |

Publication status | Published - 2017 |