Inter-compartment interaction in multi-impeller mixing: Part I. Experiments and multiple reference frame CFD

An analysis of organism lifelines in an industrial bioreactor using Lattice-Boltzmann CFD

Euler-Lagrange CFD simulations, where the biotic phase is represented by computational particles (parcels), provide information on environmental gradients inside bioreactors from the microbial perspective. Such information is highly relevant for reactor scale-down and process optimization. One of the major challenges is the computational intensity of CFD simulations, especially when resolution of dynamics in the flowfield is required. Lattice-Boltzmann large-eddy simulations (LB-LES) form a very promising approach for simulating accurate, dynamic flowfields in stirred reactors, at strongly reduced computation times compared to finite volume approaches. In this work, the performance of LB-LES in resolving substrate gradients in large-scale bioreactors is explored, combined with the inclusion of a Lagrangian biotic phase to provide the microbial perspective. In addition, the hydrodynamic performance of the simulations is confirmed by verification of hydrodynamic characteristics (radial velocity, turbulent kinetic energy, energy dissipation) in the impeller discharge stream of a 29 cm diameter stirred tank. The results are compared with prior finite volume simulation results, both in terms of hydrodynamic and biokinetic observations, and time requirements.

Digital models in biotechnology: Towards multi-scale integration and implementation

Industrial biotechnology encompasses a large area of multi-scale and multi-disciplinary research activities. With the recent megatrend of digitalization sweeping across all industries, there is an increased focus in the biotechnology industry on developing, integrating and applying digital models to improve all aspects of industrial biotechnology. Given the rapid development of this field, we systematically classify the state-of-art modelling concepts applied at different scales in industrial biotechnology and critically discuss their current usage, advantages and limitations. Further, we critically analyzed current strategies to couple cell models with computational fluid dynamics to study the performance of industrial microorganisms in large-scale bioprocesses, which is of crucial importance for the bio-based production industries. One of the most challenging aspects in this context is gathering intracellular data under industrially relevant conditions. Towards comprehensive models, we discuss how different scale-down concepts combined with appropriate analytical tools can capture intracellular states of single cells. We finally illustrated how the efforts could be used to develop digitals models suitable for both cell factory design and process optimization at industrial scales in the future.

Investigating a Stirred Bioreactor: Impact of Evolving Fermentation Broth Pseudoplastic Rheology on Mixing Mechanisms

The culture medium in many fermentations is a non-Newtonian fluid. In bacterial alginate batch production, the broth becomes more pseudoplastic as the alginate concentration increases, which impairs the mixing process. This work characterizes the effect of the interaction between changing broth rheology and impeller mixing on a bioreactor fluid dynamics. Experimentally, a fermentation with evolving broth pseudoplastic rheology is reproduced. Three fermentation stages are mimicked using appropriate solutions of water and xanthan gum. Impeller torque measurements are reported. The weakening of the impellers’ interaction over the fermentation process is identified. To overcome the experimental limitations, CFD is applied to study the evolution of the fermentation fluid flow patterns, velocity field, dead zones, and vortical structures. Precessional vortex macro-instabilities are identified as being responsible for the unstable flow patterns identified at the earlier stages of the fermentation. A stable parallel flow pattern accounts for the weakest impellers’ interaction at the final stage. Overall, this work contributes with a complete workflow to adapt CFD models for characterization and aided design of stirred tanks with changing broth pseudoplastic rheology as well as an evolving flow regime.

Numerical Investigation on the Effects of Impeller Structures in Hot Metal Desulfurization Processes by Mechanical Stirring

With the increasing demand for high-quality steel, the requirements for the efficiency and stability of deep desulfurization are increasing too. The Kanbara Reactor (KR) is widely accepted around the world because of its high efficiency and economy. In order to destroy the rigid motion of molten iron in this area, two kinds of blade structures are designed and compared with traditional blades. In this study, a three-dimensional transient coupling mathematical model was established by using volume of fluid (VOF) and discrete phase model (DPM) to simulate the KR desulfurization process. The turbulence intensity of the molten iron, main vortex size and desulfurizing agent (DA) particle distributions for the three impeller models were investigated in detail. Model results showed that the staggered blade structure may improve the desulfurization efficiency of the KR process, and the desulfurization rate increases from 95.7% to 97.1% when compared with ordinary blades. The main reason for this can be attributed to the enhanced turbulence intensity of the molten iron, larger main vortex size and more uniform DA particle distributions. Plant tests also showed that the desulfurizer consumption per 1 ppm sulfur for the staggered blades was reduced by approximately 8.6%.

Validation of Novel Lattice Boltzmann Large Eddy Simulations (LB LES) for Equipment Characterization in Biopharma

Detailed process and equipment knowledge is crucial for the successful production of biopharmaceuticals. An essential part is the characterization of equipment for which Computational Fluid Dynamics (CFD) is an important tool. While the steady, Reynolds-averaged Navier–Stokes (RANS) k − ε approach has been extensively reviewed in the literature and may be used for fast equipment characterization in terms of power number determination, transient schemes have to be further investigated and validated to gain more detailed insights into flow patterns because they are the method of choice for mixing time simulations. Due to the availability of commercial solvers, such as M-Star CFD, Lattice Boltzmann simulations have recently become popular in the industry, as they are easy to set up and require relatively low computing power. However, extensive validation studies for transient Lattice Boltzmann Large Eddy Simulations (LB LES) are still missing. In this study, transient LB LES were applied to simulate a 3 L bioreactor system. The results were compared to novel 4D particle tracking (4D PTV) experiments, which resolve the motion of thousands of passive tracer particles on their journey through the bioreactor. Steady simulations for the determination of the power number followed a structured workflow, including grid studies and rotating reference frame volume studies, resulting in high prediction accuracy with less than 11% deviation, compared to experimental data. Likewise, deviations for the transient simulations were less than 10% after computational demand was reduced as a result of prior grid studies. The time averaged flow fields from LB LES were in good accordance with the novel 4D PTV data. Moreover, 4D PTV data enabled the validation of transient flow structures by analyzing Lagrangian particle trajectories. This enables a more detailed determination of mixing times and mass transfer as well as local exposure times of local velocity and shear stress peaks. For the purpose of standardization of common industry CFD models, steady RANS simulations for the 3 L vessel were included in this study as well.

Euler-Lagrangian Simulations: A Proper Tool for Predicting Cellular Performance in Industrial Scale Bioreactors

Eulerian-Lagrangian approach to investigate cellular responses in a bioreactor has become the center of attention in recent years. It was introduced to biotechnological processes about two decades ago, but within the last few years, it proved itself as a powerful tool to address scale-up and -down topics of bioprocesses. It can capture the history of a cell and reveal invaluable information for, not only, bioprocess control and design but also strain engineering. This way it will be possible to shed light on the actual environment that cell experiences throughout its lifespan. Lifelines of a microorganism in a bioreactor can serve as the missing link that encompasses the biological timescales and the physical timescales. For this purpose digitalization of bioreactors provides us with new insights that are not achievable in industrial reactors easily if at all, namely, substrate and product gradients; high-shear regions are among the most interesting factors that can be reproduced adequately with help of a digital twin. In this chapter basic principles of this method will be introduced, and later on some practical aspects of particle tracking technique will be illustrated. In the final section, some of the advantages and challenges associated with this method will be discussed.

The impact of clearance on mixing time for interface-added substrate

This study was carried out to find the optimum clearance (impeller to bottom distance) for Rushton and pitch-blade turbine impellers in a stirred tank bioreactor for improved substrate mixing time added at interface, taking advantage of computational fluid dynamics. In this regard, the time needed for a thin layer of liquid, resembling substrate-rich or poor part, getting homogenously dispersed within the tank was calculated. The mixing time calculated in this way is called the surface aeration related mixing time (SARMT). SARMT was calculated using two approaches and was compared with each other. For the pitch-blade turbine impeller, a criterion which guarantees accurate mixing time by simulation was not satisfied, so the SARMT profile against clearance was not achieved. For the Rushton impeller, a general descending order of SARMT against impeller-bottom clearance was observed.

Coupled metabolic-hydrodynamic modeling enabling rational scale-up of industrial bioprocesses

Metabolomics aims to address what and how regulatory mechanisms are coordinated to achieve flux optimality, different metabolic objectives as well as appropriate adaptations to dynamic nutrient availability. Recent decades have witnessed that the integration of metabolomics and fluxomics within the goal of synthetic biology has arrived at generating the desired bioproducts with improved bioconversion efficiency. Absolute metabolite quantification by isotope dilution mass spectrometry represents a functional readout of cellular biochemistry and contributes to the establishment of metabolic (structured) models required in systems metabolic engineering. In industrial practices, population heterogeneity arising from fluctuating nutrient availability frequently leads to performance losses, that is reduced commercial metrics (titer, rate, and yield). Hence, the development of more stable producers and more predictable bioprocesses can benefit from a quantitative understanding of spatial and temporal cell-to-cell heterogeneity within industrial bioprocesses. Quantitative metabolomics analysis and metabolic modeling applied in computational fluid dynamics (CFD)-assisted scale-down simulators that mimic industrial heterogeneity such as fluctuations in nutrients, dissolved gases, and other stresses can procure informative clues for coping with issues during bioprocessing scale-up. In previous studies, only limited insights into the hydrodynamic conditions inside the industrial-scale bioreactor have been obtained, which makes case-by-case scale-up far from straightforward. Tracking the flow paths of cells circulating in large-scale bioreactors is a highly valuable tool for evaluating cellular performance in production tanks. The "lifelines" or "trajectories" of cells in industrial-scale bioreactors can be captured using Euler-Lagrange CFD simulation. This novel methodology can be further coupled with metabolic (structured) models to provide not only a statistical analysis of cell lifelines triggered by the environmental fluctuations but also a global assessment of the metabolic response to heterogeneity inside an industrial bioreactor. For the future, the industrial design should be dependent on the computational framework, and this integration work will allow bioprocess scale-up to the industrial scale with an end in mind.

Correlation of Power Consumption of Double Impeller Based on Impeller Spacing in Laminar Region

Power consumption is an important parameter for the design of mixing equipment. The aim of this study is to develop a new correlation of the power consumption of a double impeller. The effect of impeller spacing on the double-impeller flow pattern and power consumption was investigated in the laminar region. As a result, the effect of impeller spacing on the flow pattern was described based on the ratio of impeller spacing to the impeller blade height. Moreover, the power consumption of a double impeller could be correlated with the same ratio.