artículo_redalyc_43038630016

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TRANSFERENCIA DE MASA

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    Revista Facultad de IngenieríaUniversidad de AntioquiaISSN: 0120-6230revista.ingenieria@udea.edu.coUniversidad de AntioquiaColombiaNiño-López, Lilibeth Caridad; Gelves-Zambrano, Germán RicardoSimulating gas-liquid mass transfer in a spin filter bioreactorRevista Facultad de Ingeniería Universidad de Antioquia, núm. 75, junio, 2015, pp. 163-174Universidad de AntioquiaMedellín, Colombia Available in: http://www.redalyc.org/articulo.oa?id=43038630016  How to cite Complete issue More information about this article Journal's homepage in redalyc.orgScientific Information SystemNetwork of Scientific Journals from Latin America, the Caribbean, Spain and PortugalNon-profit academic project, developed under the open access initiative  163   Rev. Fac. Ing. Univ. Antioquia N. º 75 pp. 163-174, June, 2015 Simulating gas-liquid mass transfer in a spin lter bioreactor Simulación de la transferencia de masa en un biorreactor de perfusión operado con un ltro rotativo  Lilibeth Caridad Niño-López, Germán Ricardo Gelves-Zambrano * Grupo de Bioprocesos, Departamento de Ingeniería Química, Universidad de Antioquia. Carrera 53 N.° 61-30. Medellín, Colombia. (Received July 30, 2014; accepted March 17, 2015) Abstract Computational uid dynamics (CFD) and population balance model (PBM) model have been used to simulate hydrodynamics and mass transfer in a 0.014 m 3 Spin Filter Bioreactor. The operating conditions chosen were dened by typical settings used for culturing plant cells. Turbulence, rotating ow, bubbles breakage and coalescence were simulated by using the k-e, MRF (Multiple Reference Frame) and PBM approaches, respectively. The numerical results from different operational conditions are compared with experimental data obtained from measurements and good tting data is achieved. Interested by these simulated and experimental results CFD simulations are qualied as a very promising tool not only for predicting gas-liquid hydrodynamics but also for nding design requirements that must  be implemented to optimize an aerobic bioprocessing useful for plant cell culture applications which are characterized by the constrain of achieving relatively high mass transfer conditions and avoiding cellular damage due to hydrodynamic conditions. ----------Keywords:   bioreactor, scale up, multiple reference frame (MRF), population balance model (PBM), spin flter  Resumen Mediante dinámica de uidos computacional (CFD) y métodos de balance  poblacional (PBM) se simuló la hidrodinámica líquido-gaseosa y la transferencia de masa en un biorreactor de 0,014 m 3  operado con un Spin Filter para cultivos en modo perfusión. Las condiciones de operación fueron denidas con base en los requerimientos para células vegetales * Corresponding author: Germán Ricardo Gelves Zambrano, e-mail: german.gelves@udea.edu.co DOI: 10.17533/udea.redin.n75a16  164 Rev. Fac. Ing. Univ. Antioquia N.° 75. June, 2015 en suspensión. Los fenómenos de turbulencia, ujo giratorio, ruptura y coalescencia de burbujas fueron simulados utilizando los modelos k-e, MRF (Multiple Reference Frame) y PBM. Se logra una predicción aceptable mediante la comparación entre los resultados numéricos de las diferentes condiciones de operación y los datos experimentales de los valores del coeciente de transferencia de masa Con la motivación de estos resultados simulados y validados experimentalmente, se observa que CFD puede ser una herramienta muy prometedora, no sólo para la predicción de la hidrodinámica líquido-gaseosa, sino también para encontrar los requisitos de diseño que se deben implementar para optimizar un proceso biológico aerobio útil  para aplicaciones de cultivos celulares de plantas, que son comúnmente caracterizados por el requerimiento de mantener condiciones relativamente altas tasa de transferencia de masa y simultáneamente evitar el daño celular debido a las condiciones hidrodinámicas. ----------Palabras clave: biorreactor, escalado, marco de referencia múltiple, método de balance poblacional, fltro rotativo Introduction Global productivity in large scale processes depends on gas-liquid conditions. Supplying adequate oxygen levels in aerobic cell culturing is a common problem in fermentation technology. This problem is increased in high cell density  bioreactors due to oxygen transfer rate limitations affecting cell growth and productivity. Such limitations are common in perfusion cell cultures leading to anoxic process, cellular damage and therefore loss of cell viability [1]. Perfusion technology is used for increasing the  productivity of such compounds. One of the most common devices for perfusion processes is the Spin-Filter, which is used for animal and plant cell cultures in continuous production processes. Such bioreactors incorporate a rotating lter device into a stirred tank reactor. Cells are inoculated and cultivated by continuous addition of fresh nutrient medium. The spin-lter device minimizes the loss of cells through the bioreactor harvest. Consequently biomass productivity is increased substantially compared to batch or fed  batch mode [1]. However oxygen requirements are proportional to cell density causing mass transfer limitations. There has been rapid progress in the modeling of large-scale performance by the application of computational uid dynamics (CFD). Successful examples are given covering the range from agitation systems, including models from single phase rotating impeller systems [2-6] to the use of population balance models [7-14]. The main purpose of these approaches is the knowledge of the ow elds in conventional stirred tanks (hydrodynamics) related to mass transfer proles. Spin-lters (SF) were proposed as cell retention devices for animal cell culture several decades ago [15] and became a popular device for  perfusion cultivations both for small-scale studies and large-scale processes [16-18]. Although several works have dealt with the understanding ow eld and particle dynamics of these devices, gas-liquid mass transfer  phenomena and hydrodynamics has not yet  been studied. To the authors knowledge CFD simulations for gas-liquid hydrodynamics in Spin Filter Bioreactor had never been used previously for evaluating mass transfer prediction. For this reason detailed understanding of hydrodynamic  behavior can be useful not only for identifying mass transfer limitations but also for nding design requirements that must be implemented to optimize an aerobic bioprocessing. Hence it is  165   Simulating gas-liquid mass transfer in a spin lter bioreactor the motivation of this work to simulate gas-liquid hydrodynamics in a Spin Filter bioreactor using a CFD approach for mass transfer. Materials and methods Bioreactor setup A Spin Filter stirred tank bioreactor (New Brunswick Celligen 310) with 0.008 m 3  working volume (T = 0.21 m) was used in this study. The mixing is driven by a conventional Pitched Blade Impeller (D = 0.1 m) mounted on a 0.02 m diameter shaft and placed at the center line of the  bioreactor. The gas is supplied through a 0.02 m diameter cylinder micro-sparger. The operating conditions chosen were dened by typical settings used for culturing plant cells: N i  = 70, 140 and 210 rpm, aeration rate = 0.04 vvm. The properties used in the primary phase (water) are: ρ L : 998.2 kgm −3 ; μ L : 0.001 kgm −1  s −1 . σ: 0.07 Nm −1 . Secondary  phase properties (air) are: ρ G : 1.225 kgm −3 , μ G  = 1.789 10 −5  kgm −1  s −1 [19]. Computational Fluid Dynamic Model Multiphase Flow Equations The gas and liquid phase are treated as interpenetrating continua and conservation of mass and momentum equations are solved for each phase. The conservation equations for each  phase are derived to obtain a set of equations, which have similar structure for all phases [13, 20-25]. The Eulerian model is the most complex multiphase model in ANSYS FLUENT 13.0. It solves a system of n -momentum and continuity equations for each phase. The coupling is achieved through pressure and interfacial exchange coefcients. The mass conservation equation for each phase is shown (Eq. 1): (1)Where , represent the density, volume fraction and mean velocity, respectively, of phase  i  (L or G). It is assumed that the liquid phase and the gaseous phase share space proportional to their volume, such that their volume fractions sum up to unity in the cell domain (Eq. 2):  (2) The momentum equation for phase i  is described  below (Eq. 3):  (3) is the pressure shared by both phases and represents the interfacial momentum exchange. The term represents the Coriolis and centrifugal forces expressed in the MRF (Multiple Reference Frame) model for rotating ows and is represented as (Eq. 4):  (4) is the angular velocity, is the position vector. The Reynolds stress tensor (Eq. 5) is related to the mean velocity gradients through the Boussinesq hypothesis [20]: (5) is the molecular viscosity of phase i, , is the strain tensor. Interfacial Momentum Exchange The most important interphase force is the drag force acting on the bubbles. This force (Eq. 6) depends on friction, pressure, cohesion, and other hydrodynamic effects [26]. (6)
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