A Lattice-Boltzmann CFD study of the hydrodynamics relevant for industrial fermentation processes

Abstract

Fermentation processes are considered to be essential to decrease our reliance on fossil fuel based products. However, the scale-up from lab-scale to industrial-scale has proven to be difficult. Computational Fluid Dynamics (CFD) has the potential to be a tool to optimize the scale-up and to help engineers understand the relevant hydrodynamics inside such reactors. However, traditional CFD simulations are computationally intensive and it is not uncommon that simulations can take several months to compute a few minutes of flow-time. Due to the recent development of GPU-based hardware, the Lattice-Boltzmann method (LBM) has been gaining much interest as this meant an orders-of-magnitude decrease of needed computational time compared to conventional CFD methods. In order to calibrate the models underlying the simulations, the obtained results of said simulations should be validated against experimentally obtained data, which is exceptionally scarce for industrial-scaled reactors. Hence the aim of this thesis is to to investigate the applicability of the LBM in high gas-flow, industrial sized reactors by studying three benchmark cases. Using Large Eddy Simulations (LES) and Euler-Lagrangian tracking of bubble parcels, the models provided by M-Star (MStar Simulations, LLC) are validated by replicating a small-scale reactor of which the LBM has already been successfully applied to. The industrial-scaled case consists of the simulation of the 22m3 industrial reactor located in Stavanger, which is an exception regarding the scarcity of experimental data for industrial sized reactors. As this data set did not encompass all the relevant data for aerated stirred tanks, the suitability of the LBM and provided models are also tested for a smaller scaled tank of which the Bubble Size Distribution (BSD) throughout the vessel is known. The applicability of the provided models will be tested by comparing the obtained gas hold-up, BSD and power consumption with experimental data sets. Although the LBM is suitable for industrial-scaled reactors, the provided models by M-Star are not sufficient to predict the gas hold-up and power consumption at high superficial gas velocities. The provided Free Particle drag correlation is not sufficient to describe the dispersion of bubbles throughout the vessel, leading to a significantly under-estimated gas hold-up. In addition, the parcel approach leads to the formation of large bubbles in the vessel. And although enforcing a maximum coalescence diameter does improve the BSD, the gas hold-up is not significantly influenced by the presence of large bubbles. Furthermore, the Euler-Lagrangian way of modeling bubble particles did not lead to the formation of gas cavities, which resulted in an insignificant drop in power consumption. Nevertheless, the current work provides a foundation for subsequent research.