CFD and Experimental Characterization of a Bioreactor: Analysis via Power Curve, Flow Patterns and k L a

Abstract

Mixing operations in biological processes is of utmost importance due to its effect on scaling-up and heat and mass transfer. This paper presents the characterization of a bench-top bioreactor with different impeller configurations, agitation and oxygen transfer rates, using CFD simulations and experimental procedures. Here, it is demonstrated that factors such as the type of impeller and the flow regime can drastically vary the operation as in the preparation of cultures. It was observed that the bioreactor equipped with a Rushton generates a k L a of 0.0056 s−1 for an agitation velocity and airflow rate of 250 RPM and 5 L/min, respectively. It is suitable result for the dissolved oxygen (DO) but requires a considerable amount of power consumption. It is here where the importance of the agitator’s diameter can be observed, since, in the case of the two propeller types studied, lower energy consumption can be achieved with a smaller diameter, as well as a much smaller shear cup 2.376 against 0.723 s−1 by decreasing by 4 cm the standard diameter of an agitated tank (10 cm). Finally, the k L a values obtained for the different configurations are compared with the maximum shear rate values of different cell cultures to highlight the impact of this study and its applicability to different industries that use agitation processes for cell growth.

Simulation of two‐phase air–liquid flows in a closed bioreactor loop: Numerical modeling, experiments, and verification

“…Due to increasing demand on effective technological solutions in the field of production of microbial biomass from natural gas, [40][41][42][43][44][45] the current manuscript provides actual information and applicable decisions valued not only for the general fundamental research in the field but also concerning its applications in developing energy-efficient bioreactors. In order to choose the reasonable experimental setup and analytical tools of the hydrodynamic model, the number of classical approaches 17,18,[46][47][48] as well as recent advanced methods for developing and scaling up industrial biotechnological processes 21,[49][50][51] were studied. Based on the validation results, we got a satisfactory match between the computed and experimental velocity profiles of the fluid flow corresponding to the beginning of the transition to turbulent flow over the flow.…”

“…4,6 The experimental information about the flow structure, its averaged, and pulsation properties is essential both for computer analysis of the two-phase gas-liquid medium motion inside a large class of process devices and for controlling the state of two-phase flows that determine the hydrodynamic environment and mass transfer processes, in particular, in bioreactors. [17][18][19][20][21][22][23][24][25] The development of integro-differential models and using them to simulate complexly interacting carrier and dispersed phase is an urgent interdisciplinary task. The new models allow for a broader fundamental understanding and management of the hydrodynamic environment in bioreactor circuits [26][27][28][29][30] and can provide the basis for comprehensive systematic microbiological studies of the behavior of microorganisms in local apparatus, such as fermentation devices that implement aerobic biosynthesis processes.…”

“…The most modern methods of analysis and scaling of process solutions based on achievements of practical physics, chemistry, and biotechnology are based on computational fluid dynamics (CFD) tools 4,6 . The experimental information about the flow structure, its averaged, and pulsation properties is essential both for computer analysis of the two‐phase gas–liquid medium motion inside a large class of process devices and for controlling the state of two‐phase flows that determine the hydrodynamic environment and mass transfer processes, in particular, in bioreactors 17–25 . The development of integro‐differential models and using them to simulate complexly interacting carrier and dispersed phase is an urgent interdisciplinary task.…”

CFD modelling of a wave-mixed bioreactor with complex geometry and two degrees of freedom motion

“…It is known that for unstructured meshes like the ones created with SNAPPYHEXMESH, there are higher GCI results, compared to structured meshes (Liu et al, 2015). Since typically three meshes are compared, two cases were distinguished (Jiang et al, 2018;Ramírez et al, 2020). First, meshes 1-3 were compared and second, meshes 2-4.…”

“…10). The determination of the GCI was performed analogously to the calculations of Baker et al (2020), Ramírez et al (2020) and Pappalardo et al (2021) (Eqs. 11, 12).…”