Correlation for oxygen transfer coefficient for high cell density yeast and analysis of mixing in bioreactors using computational fluid dynamics

Date

2024-11-11

Author

Koyuncu, Alper

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Bioreactor operation conditions are important for production of biomolecules. Herein; oxygen transfer at laboratory scale and mixing at industrial and laboratory scale bioreactors were analysed. In oxygen transfer, a model was proposed to predict oxygen transfer coefficient (k_La) in high-cell-density cultures. The effect of Saccharomyces cerevisiae concentration, superficial gas velocity (v_s), liquid apparent viscosity (\mu_a), the gassed power input per liquid working volume (P_G/V), and stirrer speed (N) on k_La were investigated. The k_La values were measured using dead cell-based dynamic method for non-Newtonian and Newtonian media. k_La was determined at the cell concentrations of C_x= 0 – 125 g L-1 to create non-Newtonian and Newtonian environments, at v_s= 4 x 10-4 – 3.2 x 10-3 m s-1, N= 250 – 900 min-1, P_G/V= 60 – 9600 W{\ m}^{-3}. We calculated power input using five correlations and then proposed k_La models for each power input model. Best-fitted model makes predictions with standard deviation (SD) of 7.7% for Newtonian and non-Newtonian fluids. Considering best-fitted power input model and calculated viscosity values, we proposed dimensionless model with SD of 8.74%. In mixing, mixing time by computational fluid dyanmics (CFD) in lab and industrial scale bioreactors were conducted. Two simulations were conducted with models supplied by M-Star simulation and results were compared with two cases, a study of Guillard & Trägårdh (2003) and Hadijev et al. (2006) to verify accuracy of results. Analysis of industrial-scale bioreactor with 8 m^3 working volume has SD of 10.12%. Analysis of lab-scale bioreactor with 0.005 m^3 working volume has SD of 22.31%.

Subject Keywords

Pharmaceuticals, Bioprocessing, Volumetric Mass Transfer Coefficient, Mixing, Computational Fluid Dynamics

URI

https://hdl.handle.net/11511/112675

Collections

Graduate School of Natural and Applied Sciences, Thesis