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Fig. 9. Experimental data and model prediction of volumetric mass transfer coefficient values as a function of superficial gas velocity for different non-Newtonian systems.

Figure 9 Experimental data and model prediction of volumetric mass transfer coefficient values as a function of superficial gas velocity for different non-Newtonian systems.

Related Figures (27)

Fig. 1. Relationship between OTR, volumetric mass transfer coefficient and hydrodynamic parameters in bioreactors at several levels
Fig. 1. Relationship between OTR, volumetric mass transfer coefficient and hydrodynamic parameters in bioreactors at several levels
Fig. 3. Schematic representation of the gas-liquid interface, concentrations and mass transfer coefficients K,, k, and kc according to film theory. Due to the difficulty of measuring k; and a separately, usually the product kya is measured and this parameter — called volumetric mass transfer coefficient - characterizes the transport from gas to liquid.
Fig. 3. Schematic representation of the gas-liquid interface, concentrations and mass transfer coefficients K,, k, and kc according to film theory. Due to the difficulty of measuring k; and a separately, usually the product kya is measured and this parameter — called volumetric mass transfer coefficient - characterizes the transport from gas to liquid.
Fig. 2. Steps and resistances for oxygen transfer from gas bubble to cell. (i) transfer from the interior of the bubble and gas film; (ii) movement across the gas-liquid interface (iii) diffusion through the relatively stagnant liquid film surrounding the bubble; (iv) transport through the bulk liquid; (v) diffusion through the relatively stagnant liquid filr surrounding the cells; (vi) movement across the liquid-cell interface; and (vii) transport through the cytoplasm to the site of biochemical reaction.
Fig. 2. Steps and resistances for oxygen transfer from gas bubble to cell. (i) transfer from the interior of the bubble and gas film; (ii) movement across the gas-liquid interface (iii) diffusion through the relatively stagnant liquid film surrounding the bubble; (iv) transport through the bulk liquid; (v) diffusion through the relatively stagnant liquid filr surrounding the cells; (vi) movement across the liquid-cell interface; and (vii) transport through the cytoplasm to the site of biochemical reaction.
Fig. 4. Schematic description of the dynamic technique desorption-absorption of oxygen for inert condition measurements. characteristic for the oxygen transport, 1/k,a, is of the same order than the response time of the electrode, defined as the time necessary to reach 63% of the final value measured when exposed to a step change of concentration (Van't Riet, 1979). The response time of the electrode can be determined by transferring the oxygen electrode from a solution with sodium sulfite (whose oxygen concentration is zero) to another dissolution saturated with air (100% of saturation). In the case when the electrode of oxygen has a high value of T, it would be necessary to introduce a correction in the response model (Eq. (6)); a good approach is a first order dynamic (Weiland and Onken, 1981; Godbole et al., 1984), according to:
Fig. 4. Schematic description of the dynamic technique desorption-absorption of oxygen for inert condition measurements. characteristic for the oxygen transport, 1/k,a, is of the same order than the response time of the electrode, defined as the time necessary to reach 63% of the final value measured when exposed to a step change of concentration (Van't Riet, 1979). The response time of the electrode can be determined by transferring the oxygen electrode from a solution with sodium sulfite (whose oxygen concentration is zero) to another dissolution saturated with air (100% of saturation). In the case when the electrode of oxygen has a high value of T, it would be necessary to introduce a correction in the response model (Eq. (6)); a good approach is a first order dynamic (Weiland and Onken, 1981; Godbole et al., 1984), according to:
Fig. 5. Schematic description of the direct measuring of OTR in bioprocess by the classical dynamic technique.
Fig. 5. Schematic description of the direct measuring of OTR in bioprocess by the classical dynamic technique.
Fig. 6. Evolution of oxygen concentration in the liquid-phase when the composition of the gas stream is modified changing from air to pure oxygen (absorption) or from pure oxygen to air (desorption). In Fig. 7, as an example, k,a values obtained by different methods as a function of stirrer speed in non-Newtonian solutions and 20 L vessel are compared (Vs=2- 107? m-s"! and [1,=8- 107? to 30-10? Pas). The kya values obtained by Ogut and Hatch (1988), using the sulfite measurement method, are much higher than those usually obtained for an electrolyte solution. The difference is greater for lower values of
Fig. 6. Evolution of oxygen concentration in the liquid-phase when the composition of the gas stream is modified changing from air to pure oxygen (absorption) or from pure oxygen to air (desorption). In Fig. 7, as an example, k,a values obtained by different methods as a function of stirrer speed in non-Newtonian solutions and 20 L vessel are compared (Vs=2- 107? m-s"! and [1,=8- 107? to 30-10? Pas). The kya values obtained by Ogut and Hatch (1988), using the sulfite measurement method, are much higher than those usually obtained for an electrolyte solution. The difference is greater for lower values of
Fig. 7. Comparison of k,a values obtained by different measuring methods as a function of stirrer speed in non-Newtonian solutions. Key: 1: chemical method, 2: dynamic method, 3: Kr measurement (adapted from Garcia-Ochoa and Gomez, 1998).
Fig. 7. Comparison of k,a values obtained by different measuring methods as a function of stirrer speed in non-Newtonian solutions. Key: 1: chemical method, 2: dynamic method, 3: Kr measurement (adapted from Garcia-Ochoa and Gomez, 1998).
Comparison of different methods for volumetric mass transfer coefficient evaluation Table 1
Comparison of different methods for volumetric mass transfer coefficient evaluation Table 1
Exponent values in Eq. (31) for stirred tank bioreactors — &dssO VISCOSITY TOG, Acronyms for Stirrers on Table 2: CBT: Curved Blade Turbine. CBP: Curved Blade Paddle. FBP: Flat Blade Paddle. FBT: Flat Blade Turbine. PBP: Pitched Blade Paddle. PBT: Pitched Blade Turbine. Two-6FBT: Two stirrers of the type indicated (6FBT, in the example). Table 2
Exponent values in Eq. (31) for stirred tank bioreactors — &dssO VISCOSITY TOG, Acronyms for Stirrers on Table 2: CBT: Curved Blade Turbine. CBP: Curved Blade Paddle. FBP: Flat Blade Paddle. FBT: Flat Blade Turbine. PBP: Pitched Blade Paddle. PBT: Pitched Blade Turbine. Two-6FBT: Two stirrers of the type indicated (6FBT, in the example). Table 2
Dimensionless correlations for prediction of k,a in Newtonian fluids in stirred tanks Table 3
Dimensionless correlations for prediction of k,a in Newtonian fluids in stirred tanks Table 3
Dimensionless correlations for prediction of kya in non-Newtonian fluids in stirred tanks
Dimensionless correlations for prediction of kya in non-Newtonian fluids in stirred tanks
Equations proposed for mass transfer coefficient prediction Table 7
Equations proposed for mass transfer coefficient prediction Table 7
Exponent values in Eq. (33) for bubble columns and airlifts Table 5
Exponent values in Eq. (33) for bubble columns and airlifts Table 5
Dimensionless correlations for prediction of kia in bubble columns and air-lifts in Newtonian and non-Newtonian fluids
Dimensionless correlations for prediction of kia in bubble columns and air-lifts in Newtonian and non-Newtonian fluids
Definition of k, in the different models of mass transfer Table 8 liquid interface during a contact or exposure time for mass transfer, t., the following equation can be obtained:
Definition of k, in the different models of mass transfer Table 8 liquid interface during a contact or exposure time for mass transfer, t., the following equation can be obtained:
Fig. 8. Experimental data and model prediction of volumetric mass transfer coefficient values as a function of power input per unit volume for Newtonian liquids. By combination of the equations for mass transfer coefficient, k;, (Eqs. (37)-(39)) and specific interfacial area, a, (Eq. (41)) from gas hold-up,¢, (Eq. (45)) and average bubble size, d,, (Eq. (50)) it is possible to predict the influence of operational conditions, properties of liquid and geometrical parameters of the vessels on the volumetric mass transfer coefficient, ka. The capability of prediction of those equations has been checked making a comparison of k,a experimental values and some data obtained from correlations published for stirred tank reactors of different geometries, for Newtonian and non- Newtonian fluids (Yagi and Yoshida, 1975; Van't Riet, 1979; Chan- drasekharan and Calderbank, 1981; Linek et al., 1991; Pedersen et al., 1994; Vasconcelos et al., 2000; Garcia-Ochoa and Gomez, 2001). As an example, in Fig. 8, k,a values predicted for Newtonian fluids for sparged stirred tank reactors for 50 L of volume are shown as a function of the power input per volume unit. In Fig. 9, the model predictions of k,a values for non-Newtonian systems are shown as a
Fig. 8. Experimental data and model prediction of volumetric mass transfer coefficient values as a function of power input per unit volume for Newtonian liquids. By combination of the equations for mass transfer coefficient, k;, (Eqs. (37)-(39)) and specific interfacial area, a, (Eq. (41)) from gas hold-up,¢, (Eq. (45)) and average bubble size, d,, (Eq. (50)) it is possible to predict the influence of operational conditions, properties of liquid and geometrical parameters of the vessels on the volumetric mass transfer coefficient, ka. The capability of prediction of those equations has been checked making a comparison of k,a experimental values and some data obtained from correlations published for stirred tank reactors of different geometries, for Newtonian and non- Newtonian fluids (Yagi and Yoshida, 1975; Van't Riet, 1979; Chan- drasekharan and Calderbank, 1981; Linek et al., 1991; Pedersen et al., 1994; Vasconcelos et al., 2000; Garcia-Ochoa and Gomez, 2001). As an example, in Fig. 8, k,a values predicted for Newtonian fluids for sparged stirred tank reactors for 50 L of volume are shown as a function of the power input per volume unit. In Fig. 9, the model predictions of k,a values for non-Newtonian systems are shown as a
Fig. 10. Comparison between k,a values predicted by the proposed model and experimental data given in the literature (adapted from Garcia-Ochoa and Gomez, 2004).
Fig. 10. Comparison between k,a values predicted by the proposed model and experimental data given in the literature (adapted from Garcia-Ochoa and Gomez, 2004).
Fig. 11. Schematic representation of the steady-state profile of oxygen and biomass concentrations in a bioprocess (adapted from Garcia-Ochoa and Gomez, 2005). several models with different cell concentration distribution have been used (Tsao, 1969; Merchuk, 1977; Ju and Sundararajan, 1992). Recently, Garcia-Ochoa and Gomez (2005) have proposed a model for the estimation of the biological enhancement factor in bioreactors. This model considers three layers in series; therefore, to describe the oxygen mass transport three mass transfer resistances are considered for the biological system (see Fig. 11): (i) the interfacial surfactant film resistance, (ii) the mono-layers of adsorbed microorganisms resistance, and (iii) the liquid film resistance. The different layer resistances are taken into account by the diffusion coefficient (D;) by the inside of the
Fig. 11. Schematic representation of the steady-state profile of oxygen and biomass concentrations in a bioprocess (adapted from Garcia-Ochoa and Gomez, 2005). several models with different cell concentration distribution have been used (Tsao, 1969; Merchuk, 1977; Ju and Sundararajan, 1992). Recently, Garcia-Ochoa and Gomez (2005) have proposed a model for the estimation of the biological enhancement factor in bioreactors. This model considers three layers in series; therefore, to describe the oxygen mass transport three mass transfer resistances are considered for the biological system (see Fig. 11): (i) the interfacial surfactant film resistance, (ii) the mono-layers of adsorbed microorganisms resistance, and (iii) the liquid film resistance. The different layer resistances are taken into account by the diffusion coefficient (D;) by the inside of the
Fig. 13. Biological enhancement factor: experimental and estimated values from Eq. (63) in culture of Candida bombicola: a) growth medium, b) production medium (adapted from Garcia-Ochoa and Gomez, 2005). The second bracket of Eq. (63) is <1, representing the physical blocking effect due to the absorbed surfactant film, the cell adsorption to the bubbles surface, considering those as semi-permeable solid par- ticles hindering the movement of diffusing oxygen molecules, and the liquid film. Depending on the relative values of both terms, the enhance- ment factor, E, can take values smaller than, equal to or bigger than 1.
Fig. 13. Biological enhancement factor: experimental and estimated values from Eq. (63) in culture of Candida bombicola: a) growth medium, b) production medium (adapted from Garcia-Ochoa and Gomez, 2005). The second bracket of Eq. (63) is <1, representing the physical blocking effect due to the absorbed surfactant film, the cell adsorption to the bubbles surface, considering those as semi-permeable solid par- ticles hindering the movement of diffusing oxygen molecules, and the liquid film. Depending on the relative values of both terms, the enhance- ment factor, E, can take values smaller than, equal to or bigger than 1.
Fig. 12. Biological enhancement factor: experimental and estimated values from Eq. (63) in cultures of: a) Xantomonas campestris b) Rhodoccocus erythropolis (adapted from Garcia-Ochoa and Gomez, 2005).
Fig. 12. Biological enhancement factor: experimental and estimated values from Eq. (63) in cultures of: a) Xantomonas campestris b) Rhodoccocus erythropolis (adapted from Garcia-Ochoa and Gomez, 2005).
Fig. 17. Evolution of biodesulphurization capability and volumetric mass transfer coefficient on the course of fermentation of Rhodococcus erythropolis (for different stirrer speeds) (adapted from Gomez et al., 2006).
Fig. 17. Evolution of biodesulphurization capability and volumetric mass transfer coefficient on the course of fermentation of Rhodococcus erythropolis (for different stirrer speeds) (adapted from Gomez et al., 2006).
Related topics:
EngineeringAlgorithmsTechnologyBiotechnologyIndustrial microbiologyBiological Wastewater TreatmentOxygen TransferBubble ColumnMass Transfer CoefficientOxygen uptake rate
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