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Non-Newtonian Behavior Effect on Gas-liquid Mass Transfer using an Anchor Impeller for CSTR Bioreactors:A CFD Approach


Affiliations
1 Department of Chemical Engineering, Universidad de Antioquia. Carrera 53 N.° 61-30. Medellín, Colombia
2 Department of Environment, Universidad Francisco de Paula Santander. Av. Gran Colombia 12E-96, Cúcuta, Colombia
 

Objectives: kLa mass transfer coefficient was predicted using CFD (computational fluid dynamics) for analyzing non-newtonian effects on gas liquid mass transfer in a 10 L bioreactor stirred with an Anchor Impeller. Methods/Statistical Analysis: The set up bioreactor configurations were defined by typical culturing conditions used for fungi organism. Bubble breakage frequency and coalescence rate were simulated using Luo - Colaloglou and Tavlarides models and PBM approaches, respectively. Simulated results from different shear rates due to non-newtonian behaviour are compared by analyzing its influences in bubble size and power input. Findings: A clear relationship between high levels of shear rates and small bubble sizes is found in this work. The later is also associated with the high values of kLa simulated (270 h-1) and compared to levels found at low shear rates (62 h-1). Application/Improvements: Impressed by these findings new design optimizations for non-newtonian bioprocessing applications would be improved using CFD.
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  • Ni-o L, Pe-uela M, Gelves GR. CFD simulations for improving gas liquid mass transfer in a spin filter bioreactor. International Journal of Applied Engineering Research. 2016; 11(9):6097–108.
  • Olsvik E, Kristiansen B. Rheology of filamentous fermentations. Biotechnology Advances. 1994; 12(1):1–39. https://doi.org/10.1016/0734-9750(94)90288-7
  • Ni-o L. Gelves R. Simulating gas-liquid mass transfer in a spin filter bioreactor. Revista Facultad de Ingeniería Universidad de Antioquia. 2015; 75:163–74.
  • Peixoto SMC, Nunhez JR, Duarte CG. Characterizing the flow of stirred vessels with anchor type impellers. Brazilian Journal of Chemical Engineering. 2000; 17(4–7):925–36. https://doi.org/10.1590/S0104-66322000000400057
  • Jenne M, Reuss M. A critical assessment on the use of k–e turbulence models for simulation of the turbulent liquid flow induced by Rushton turbine in baffled stirred-tank reactors. Chemical Engineering Science. 1999; 54:3921–41. https://doi.org/10.1016/S0009-2509 (99)00093-7
  • Luo J, Issa RI, Gosman AD. Prediction of impeller induced flows in mixing vessels using multiple frames of reference. Institution of Chemical Engineers Symposium Series.1994; 136:549–56. PMid:7532484
  • Micale G, Brucat A, Grisafi F. Prediction of flow fields in a dual-impeller stirred tank. AICHE Journal. 1999; 45(3):445–64. https://doi.org/10.1002/aic.690450303
  • Bakker, Van Den Akker H. A computational model for the gas–liquid flow in stirred reactors. Transactions of IChemE. 1994; 72(4):594–606.
  • Gelves R, Dietrich A, Takors R. Modeling of gasliquid mass transfer in a stirred tank bioreactor agitated by a Rushton turbine or a new pitched blade impeller. Bioprocess and Biosystems Engineering. 2014; 37(3):365–75. https://doi.org/10.1007/s00449-013-1001-8. PMid:23828243
  • Kasat R, Pandit GR. Simulation of Gas-Liquid Flows in a Reactor Stirred by Dual Rushton Turbines. International Journal of Chemical Reactor Engineering. 2008; 6(1):1–28. https://doi.org/10.2202/1542-6580.1628
  • Gabelle J, Jourdier E, Licht RB, Chaabane B, Henaut I, Morchain J, Augier J. Impact of rheology on the mass transfer coefficient during the growth phase of in stirred bioreactors. Chemical Engineering Science. 2012; 75: 408–17. https://doi.org/10.1016/j.ces.2012.03.053
  • Hounslow MJ, Ryall RL, Marschall VR. A Discretized Population Balance for Nucleation, Growth and Aggregation. AIChE Journal. 1988; 34(11):1821–32. https://doi.org/10.1002/aic.690341108
  • Ramkrishna D. Population Balances: Theory and Applications to Particulate Systems in Engineering. Academic Press, San Diego; 2000. PMid:11027180
  • Coulaloglou CA, Tavlarides LL. Description of interaction processes in agitated liquid-liquid dispersions. Chemical Engineering Science. 1977; 32(11):1289 –97. https://doi.org/10.1016/0009-2509(77)85023-9
  • Dhanasekharan K, Sanyal J, Jain A, Haidari A. A generalized approach to model oxygen transfer in bioreactors using population balances and computational fluid dynamics. Chemical Engineering Science. 2005; 60(1):213–18. https://doi.org/10.1016/j.ces.2004.07.118

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  • Non-Newtonian Behavior Effect on Gas-liquid Mass Transfer using an Anchor Impeller for CSTR Bioreactors:A CFD Approach

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Authors

Lilibeth Nino
Department of Chemical Engineering, Universidad de Antioquia. Carrera 53 N.° 61-30. Medellín, Colombia
Mariana Penuela
Department of Chemical Engineering, Universidad de Antioquia. Carrera 53 N.° 61-30. Medellín, Colombia
Germán Ricardo Gelves
Department of Environment, Universidad Francisco de Paula Santander. Av. Gran Colombia 12E-96, Cúcuta, Colombia

Abstract


Objectives: kLa mass transfer coefficient was predicted using CFD (computational fluid dynamics) for analyzing non-newtonian effects on gas liquid mass transfer in a 10 L bioreactor stirred with an Anchor Impeller. Methods/Statistical Analysis: The set up bioreactor configurations were defined by typical culturing conditions used for fungi organism. Bubble breakage frequency and coalescence rate were simulated using Luo - Colaloglou and Tavlarides models and PBM approaches, respectively. Simulated results from different shear rates due to non-newtonian behaviour are compared by analyzing its influences in bubble size and power input. Findings: A clear relationship between high levels of shear rates and small bubble sizes is found in this work. The later is also associated with the high values of kLa simulated (270 h-1) and compared to levels found at low shear rates (62 h-1). Application/Improvements: Impressed by these findings new design optimizations for non-newtonian bioprocessing applications would be improved using CFD.

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DOI: https://doi.org/10.17485/ijst%2F2018%2Fv11i43%2F129357