Scale-up of aerated bioreactors: CFD validation and application to the enzyme production by Trichoderma reesei

Analyzing of hydrodynamic stress and mass transfer requirements of a fermentation process carried out in a coaxial bioreactor: a scale-up study

Fluid hydrodynamic stress has a deterministic effect on the morphology of filamentous fungi. Although the coaxial mixer has been recognized as a suitable gas dispersion system for minimizing inhomogeneities within a bioreactor, its performance for achieving enhanced oxygen transfer while operating at a reduced shear environment has not been investigated yet, specifically upon scale-up. Therefore, the influence of the impeller type, aeration rate, and central impeller retrofitting on the efficacy of an abiotic coaxial system containing a shear-thinning fluid was examined. The aim was to assess the hydrodynamic parameters, including stress, mass transfer, bubble size, and gas hold-up, upon conducting a scale-up study. The investigation was conducted through dynamic gassing-in, tomography, and computational fluid dynamics combined with population balance methods. It was observed that the coaxial bioreactor performance was strongly influenced by the agitator type. In addition, coaxial bioreactors are scalable in terms of shear environment and oxygen transfer rate.

Effect of Mass Transport by Convective Flow on the Distribution of Dissolved Carbon Monoxide in a Stirred Tank

The dissolved gas concentration in a stirred tank has significant importance in the chemical and biological processing industries as mass transfer from the injected gas to an aqueous solution must occur for the gas to be usable. As the solubility of the gas in the solution is low and there are no probes for measuring dissolved gas concentration, a volumetric mass transfer coefficient is selected as a criterion of design for the scale-up of stirred reactors. However, it is difficult to accurately predict the non-equilibrium state dissolved gas distribution using only the volumetric mass transfer coefficient. In this study, computational fluid dynamics (CFD)-based numerical analysis was conducted to systematically evaluated the effects of mass transport by convective flow on the distribution of dissolved carbon monoxide in a stirred tank. The dissolved carbon monoxide distribution and the volumetric mass transfer coefficient were compared at various rotational speeds of the impellers. At a rotational speed of 900 RPM, the Pearson correlation coefficient was about 0.52, which denotes a moderate correlation. In contrast, Pearson correlation coefficients less than 0.20 were obtained for speeds less than 700 RPM, indicating a weak correlation. By considering the dissolved carbon monoxide transport that occurs during convective flow in stirred tanks, we can provide more accurate information about the dissolved carbon monoxide distribution.

Microfluidic Reproduction of Dynamic Bioreactor Environment Based on Computational Lifelines

The biotechnological production of fine chemicals, proteins and pharmaceuticals is usually hampered by loss of microbial performance during scale-up. This challenge is mainly caused by discrepancies between homogeneous environmental conditions at laboratory scale, where bioprocesses are optimized, and inhomogeneous conditions in large-scale bioreactors, where production takes place. Therefore, to improve strain selection and process development, it is of great interest to characterize these fluctuating conditions at large-scale and to study their effects on microbial cells. In this paper, we demonstrate the potential of computational fluid dynamics (CFD) simulation of large-scale bioreactors combined with dynamic microfluidic single-cell cultivation (dMSCC). Environmental conditions in a 200 L bioreactor were characterized with CFD simulations. Computational lifelines were determined by combining simulated turbulent multiphase flow, mass transport and particle tracing. Glucose availability for Corynebacterium glutamicum cells was determined. The reactor was simulated with average glucose concentrations of 6 g m−3, 10 g m−3 and 16 g m−3. The resulting computational lifelines, discretized into starvation and abundance regimes, were used as feed profiles for the dMSCC to investigate how varying glucose concentration affects cell physiology and growth rate. In this study, each colony in the dMSCC device represents a single cell as it travels through the reactor. Under oscillating conditions reproduced in the dMSCC device, a decrease in growth rate of about 40% was observed compared to continuous supply with the same average glucose availability. The presented approach provides insights into environmental conditions observed by microorganisms in large-scale bioreactors. It also paves the way for an improved understanding of how inhomogeneous environmental conditions influence cellular physiology, growth and production.

Gas Dispersion in Non-Newtonian Fluids with Mechanically Agitated Systems: A Review

Gas dispersion in non-Newtonian fluids is encountered in a broad range of chemical, biochemical, and food industries. Mechanically agitated vessels are commonly employed in these processes because they promote high degree of contact between the phases. However, mixing non-Newtonian fluids is a challenging task that requires comprehensive knowledge of the mixing flow to accurately design stirred vessels. Therefore, this review presents the developments accomplished by researchers in this field. The present work describes mixing and mass transfer variables, namely volumetric mass transfer coefficient, power consumption, gas holdup, bubble diameter, and cavern size. It presents empirical correlations for the mixing variables and discusses the effects of operating and design parameters on the mixing and mass transfer process. Furthermore, this paper demonstrates the advantages of employing computational fluid dynamics tools to shed light on the hydrodynamics of this complex flow. The literature review shows that knowledge gaps remain for gas dispersion in yield stress fluids and non-Newtonian fluids with viscoelastic effects. In addition, comprehensive studies accounting for the scale-up of these mixing processes still need to be accomplished. Hence, further investigation of the flow patterns under different process and design conditions are valuable to have an appropriate insight into this complex system.

A novel scale-up strategy for cultivation of BHK-21 cells based on similar hydrodynamic environments in the bioreactors

The scale-up of animal cell cultivation is important but remains complex and challenging. In the present study, we propose a novel scale-up strategy for baby hamster Syrian kidney-21 (BHK-21) cell cultivation based on similar hydrodynamic environments. The hydrodynamic characteristics of the different scale bioreactors were determined by computational fluid dynamics (CFD) and further correlated with the agitation speed. The optimal hydrodynamic environment for cell cultivation and vaccine production was determined from the cultivation experiments of BHK-21 cells in 5-L laboratory-scale bioreactors equipped with different impellers at various agitation speeds. BHK-21 cell cultivation was scaled up from 5-L to 42-, 350-, and 1000-L bioreactors by adjusting the agitation speed to make the hydrodynamic features similar to those in the 5-L bioreactor, especially for the shear rate in the impeller zone (γimp) and energy dissipation rate in the tank bulk zone (εtan). The maximum cell density and cell aggregation rate in these scaled-up bioreactors were in the range of 4.6 × 106 ~ 4.8 × 106 cells/mL and 16 ~ 20%, which are comparable to or even better than those observed in the 5-L bioreactor (maximum cell density 4.8 × 106 cells/mL, cell aggregation rate 21%). The maximum virus titer of 108.0 LD50/mL achieved in the 1000-L bioreactor was close to 108.3 LD50/mL that obtained in the 5-L bioreactor. Hence, the scale-up strategy proposed in this study is feasible and can efficiently facilitate the scale-up processes of animal cell cultivation.

Parametric numerical study and optimization of mass transfer and bubble size distribution in a gas-liquid stirred tank bioreactor equipped with Rushton turbine using computational fluid dynamics

Designing and optimizing a bioreactor can be an especially challenging process. Computational modelling is an effective tool to investigate the effects of various operating parameters on bioreactor performance and identify the optimum ones. In this work, a computational fluid dynamics-population balance model (CFD-PBM) was developed to elucidate the effect of different geometrical and operating parameters on the hydrodynamics and mass transfer coefficient of a batch stirred tank bioreactor. The validated model was projected to predict the effect of different parameters including the gas flow rate, the impeller off-bottom clearance, the number of agitator blades, and rotational speed of the impeller on the velocity profiles, air volume fraction, bubble size distribution, and the local gas mass transfer coefficient (K l a) in the bioreactor. Air bubble breakup and coalescence phenomena were considered in all simulations. Factorial experimental design approach was employed to statistically investigate the impacts of the aforementioned operating and geometrical parameters on K l a and bubble size distribution in the bioreactor in order to determine the most significant parameters. This can give an essential insight into the most impactful factors when it comes to designing and scaling up a bioreactor.

Influence of Interfacial Force Models and Population Balance Models on the kLa Value in Stirred Bioreactors

Optimal oxygen supply is vitally important for the cultivation of aerobically growing cells, as it has a direct influence on cell growth and product formation. A process engineering parameter directly related to oxygen supply is the volumetric oxygen mass transfer coefficient kLa. It is the influences on kLa and computing time of different interfacial force and population balance models in stirred bioreactors that have been evaluated in this study. For this investigation, the OpenFOAM 7 open-source toolbox was utilized. Firstly, the Euler–Euler model with a constant bubble diameter was applied to a 2L scale bioreactor to statistically examine the influence of different interfacial models on the kLa value. It was shown that the kL model and the constant bubble diameter have the greatest influence on the calculated kLa value. To eliminate the problem of a constant bubble diameter and to take effects such as bubble breakup and coalescence into account, the Euler–Euler model was coupled with population balance models (PBM). For this purpose, four coalescence and five bubble breakup models were examined. Ultimately, it was established that, for all of the models tested, coupling computational fluid dynamics (CFD) with PBM resulted in better agreement with the experimental data than using the Euler–Euler model. However, it should be noted that the higher accuracy of the PBM coupled models requires twice the computation time.