Assessment of large eddy and RANS stirred tank simulations by means of LDA

Computational prediction of blend time in a large-scale viral inactivation process for monoclonal antibodies biomanufacturing

Viral inactivation (VI) is a process widely used across the pharmaceutical industry to eliminate the cytotoxicity resulting from trace levels of viruses introduced by adventitious agents. This process requires adding Triton X-100, a non-ionic detergent solution, to the protein solution and allowing sufficient time for this agent to inactivate the viruses. Differences in process parameters associated with vessel designs, aeration rate, and many other physical attributes can introduce variability in the process, thus making predicting the required blending time to achieve the desired homogeneity of Triton X-100 more critical and complex. In this study we utilized a CFD model based on the lattice Boltzmann method (LBM) to predict the blend time to homogenize a Triton X-100 solution added during a typical full-scale commercial VI process in a vessel equipped with an HE-3-impeller for different modalities of the Triton X-100 addition (batch vs. continuous). Although direct experimental progress of the blending process was not possible because of GMP restrictions, the degree of homogeneity measured at the end of the process confirmed that Triton X-100 was appropriately dispersed, as required, and as computationally predicted here. The results obtained in this study were used to support actual production at the biomanufacturing site.

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.

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.

Applying multiple approaches to deepen understanding of mixing and mass transfer in large-scale aerobic fermentations

Different methods are used at Corteva^® Agriscience to improve our understanding of mixing in large-scale mechanically agitated fermentors. These include (a) use of classical empirical correlations, (b) use of small-scale models, and (c) computational fluid dynamics (CFD). Each of these approaches has its own inherent strengths and limitations. Classic empirical or semi-empirical correlations can provide insights into mass transfer, blending, shear, and other important factors but are dependent on the geometry and condition used to develop the correlations. Laboratory-scale modelling can be very useful to study mixing and model the effect of heterogeneity on the culture, but success is highly dependent on the methodology applied. CFD provides an effective means to accelerate the exploration of alternative design strategies through physics-based computer simulations that may not be adequately described by existing knowledge or correlations. However, considerable time and effort is needed to build and validate these models. In this paper, we review the various approaches used at Corteva Agriscience to deepen our understanding of mixing in large-scale fermentation processes.

A General Review of the Current Development of Mechanically Agitated Vessels

The mixing process in a mechanically agitated vessel is a widespread phenomenon which plays an important role among industrial processes. In that process, one of the crucial parameters, the mixing efficiency, depends on a large number of geometrical factors, as well as process parameters and complex interactions between the phases which are still not well understood. In the last decade, large progress has been made in optimisation, construction and numerical and experimental analysis of mechanically agitated vessels. In this review, the current state in this field has been presented. It shows that advanced computational fluid dynamic techniques for multiphase flow analysis with reactions and modern experimental techniques can be used with success to analyse in detail mixing features in liquid-liquid, gas-liquid, solid-liquid and in more than two-phase flows. The objective is to show the most important research recently carried out.

In Silico Prediction of Large-Scale Microbial Production Performance: Constraints for Getting Proper Data-Driven Models

Industrial bioreactors range from 10.000 to 700.000 L and characteristically show different zones of substrate availabilities, dissolved gas concentrations and pH values reflecting physical, technical and economic constraints of scale-up. Microbial producers are fluctuating inside the bioreactors thereby experiencing frequently changing micro-environmental conditions. The external stimuli induce responses on microbial metabolism and on transcriptional regulation programs. Both may deteriorate the expected microbial production performance in large scale compared to expectations deduced from ideal, well-mixed lab-scale conditions. Accordingly, predictive tools are needed to quantify large-scale impacts considering bioreactor heterogeneities. The review shows that the time is right to combine simulations of microbial kinetics with calculations of large-scale environmental conditions to predict the bioreactor performance. Accordingly, basic experimental procedures and computational tools are presented to derive proper microbial models and hydrodynamic conditions, and to link both for bioreactor modeling. Particular emphasis is laid on the identification of gene regulatory networks as the implementation of such models will surely gain momentum in future studies.

Designing and optimizing a stirring system for a cold model of a lithium electrolysis cell based on CFD simulations and optical experiments

A new stirring system to separate lithium metal and chloride gas in lithium electrolysis cells has been designed and applied in cold model experiments.

Investigation of the Effect of Outlet Structures on the Jet Flow Characteristics in the Circulating Jet Tank

A revised numerical model of circulating jet tank (CJT) was constructed by adding four momentum sources. The radial distribution tendency of total pressure predicted by large eddy simulation had a good agreement with experimental results. The axial velocities at the center of downcomers have parabolic attenuation tendency with the increasing axial positions. The inductive and restrictive effects of outlets on the jet flow performances were evaluated by the parameters, such as jet velocity decay, spreading rate and energy dissipation. The optimum factor of outlet structures was proposed based on the ratio of spreading rate to energy dissipation. Numerical results show that the downcomers equipped with four symmetrical rectangular outlets contribute more to reduce the decay of jet centerline velocity and make good use of the entrainment between the jet and bulk liquid to generate the largest spreading rate. Furthermore, a nearly plug flow pattern and the maximum value of optimum factor are attained compared with other types of outlets. The optimum factors of rectangular outlets firstly increase then decrease with the increasing ratios of width to diameter of the downcomers. Rectangular outlets induce the jet to expand and get the largest dimensionless jet length and spreading rate when the ratios of width to diameter w/D1 approach 0.08.