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Computational fluid dynamics simulation of a novel bioreactor for sophorolipid production
Computational fluid dynamics simulation of a novel bioreactor for sophorolipids production Xiaoqiang Jia, Lin Qi, Yaguang Zhang, Xue Yang, Hongna Wang, Fanglong Zhao, Wenyu Lu PII: DOI: Reference:
S1004-9541(16)30408-6 doi:10.1016/j.cjche.2016.09.014 CJCHE 698
To appear in: Received date: Revised date: Accepted date:
4 May 2016 23 August 2016 30 September 2016
Please cite this article as: Xiaoqiang Jia, Lin Qi, Yaguang Zhang, Xue Yang, Hongna Wang, Fanglong Zhao, Wenyu Lu, Computational fluid dynamics simulation of a novel bioreactor for sophorolipids production, (2016), doi:10.1016/j.cjche.2016.09.014
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ACCEPTED MANUSCRIPT Computational fluid dynamics simulation of a novel bioreactor for
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sophorolipids production
Xiaoqiang Jia1,2,3, Lin Qi1, Yaguang Zhang1, Xue Yang1, Hongna Wang1, Fanglong
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Zhao1, Wenyu Lu1,2,3
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1 Department of Biochemical Engineering, School of Chemical Engineering and Technology, Tianjin University, Tianjin 300072, PR China. 2 Key Laboratory of Systems Bioengineering (Tianjin University), Ministry of Education, Tianjin 300072, PR China. 3 Synthetic Biology Platform, Collaborative Innovation Center of Chemical Science and Engineering (Tianjin), Tianjin 300072, PR China.
Corresponding author. Tel.: +86-22-27892132; fax: +86-22-27400973. E-mail address: [email protected] (Wenyu Lu)
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* Supported by the National Key Basic Research Program of China (No. 2014CB745100), National Natural Science Foundation of China (No. 21576197), Tianjin Research Program of Application Foundation and Advanced Technology (No. 14JCQNJC06700), Technological Research and Development Programs of the China Offshore Environmental Services Ltd. (CY-HB-10-ZC-055).
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This paper describes three-dimensional computational fluid dynamics (CFD)
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simulations of gas-liquid flow in a novel laboratory-scale bioreactor contained dual
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ventilation-pipe and double sieve-plate bioreactor (DVDSB) used for sophorolipids (SLs) production. To evaluate the role of hydrodynamics in reactor design, the comparisons between conventional fed-batch fermenter and DVDSB on the
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hydrodynamic behavior are predicted by the CFD methods. Important hydrodynamic parameters of the gas-liquid two-phase system such as the liquid phase velocity field,
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turbulent kinetic energy and volume-averaged overall and time-averaged local gas holdups were simulated and analyzed in detail. The numerical results were also validated by experimental measurements of overall gas holdups. The yield of
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in the new reactor.
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sophorolipids was significantly improved to 484 g·L-1 with a 320 h fermentation period
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Keywords: Bioreactors; Gas Hold-UP; Computational Fluid Dynamics (CFD); Hydrodynamics; Sophorolipids Production.
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1. Introduction
Surfactants are a group of amphiphilic chemicals consisting of both hydrophilic and hydrophobic regions that partition preferentially at the interface between fluid phases [1, 2]. Annual consumption of surfactants in the world is more than 13 million tons, and most of them are synthesized by chemical methods. The large majority of the currently used surfactants are petroleum-based and are produced by chemical means. Biosurfactants, mainly produced by microorganisms, have advantages over chemical surfactants for their lower toxicity, higher biodegradability, better environmental compatibility and higher selectivity[3, 4]. Biosurfactants are grouped as glycolipids, lipopeptides, phospholipids, fatty acids, neutral lipids, polymeric and
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particulate compounds[5]. Sophorolipids is a kind of extracellular glycolipids biosurfactants which comprise a hydrophilic carbohydrate section and a hydrophobic
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fatty acid chain [6]. Sophorolipids is widely used in the environmental remediation and
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cleaning industries for the advantages of biodegradability, high surfactivity, low
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ecotoxicity and the production on renewable-resource substrates [4, 7, 8]. In the environmental remediation area, SLs is amongst one of the most promising biosurfactants for heavy metal removal from soil sediments. Experiments have indicated
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that sophorolipids could enhance biodegradation of the insoluble aromatic compounds like phenanthrene through enhanced solubilization [9-11]. In addition, SLs have been
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successfuly applied in the petroleum industry such as secondary oil recovery, remove hydrocarbons from drill material, and the regeneration of hydrocarbons from dregs and muds [12].
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For the required characteristics and great potential to replace the existing chemical
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surfactants, many studies have focused on reducing production costs or improving the
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yield of SLs to make it competitive with existing chemical surfactants[3, 4]. As the SLs production is a complex, multiphase chemical, biological and physical process, a lot of research has been performed on the optimization of the fermentation process, including
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fermentation type, culture conditions, carbon sources, medium components, and so on. Ribeiro et al. [13] observed that the production of SLs was favoured when culture media was supplied with avocado, argan, sweet almond and jojoba oil or when NaNO3 was supplied instead of urea, which indicated the potential of the selective production of SLs based on the selection of carbon and nitrogen sources to culture media. Ma et al. [14] used cell lysate of C. curvatus, oleic acid, and delignined corncob residue hydrolysate (DCCRH)/detoxified DCCRH as nitrogen and carbon sources and results demonstrated that renewable DCCRH can be utilized for the production of high-value SLs. Daverey et al. [15] studied low cost media based on sugarcane molasses and three different oils for the production of sophorolipids (SLs) from the yeast Candida bombicola in batch shake flasks. However, hardly any work has been published on the
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physical characteristics affecting the efficiency of SLs production. During recent decades, many studies have been made including structural
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improvement, hydrodynamic conditions optimization, in order to further improve
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various types of bioreactors to meet the demands of microorganism cultures and
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industrialized application. As the hydrodynamic behavior such as gas volume fraction, velocity fields, distributions of shear stresses, turbulent intensity that significantly affect the growth of microorganisms and the production of fermentation product. Klein et al.
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[16] assess the effect of operational conditions (air-flow rate, biomass concentration) on hydrodynamic behavior of an airlift bioreactor and the results on hydrodynamics can be
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used a priori or during the bioprocess to optimize operational parameters to avoid the occurrence of undesirable bioreactor stalling and to maximize the process productivity. The rheological properties of a fermentation with the fungus Beauveria bassiana under
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different hydrodynamic conditions were studied and the simulated results will be
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helpful in the optimization of scale-up production of these fungi[17]. Hence, it is
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necessary to investigate the hydrodynamic phenomena involved in SLs production for the industrial scale application. Research of SLs production from the perspective of bioreactor design and separation process optimization will be interesting and promising.
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As the laboratory-scale yeast-bioreactor system for the production of SLs [18], traditional semi-empirical approach to bioreactor design is time-consuming and the application of experimental techniques are limited to large amount spend on investigating flow fields, mass concentration fields, etc. Numerical simulation based on computational fluid dynamics (CFD) calculations can provide a feasible way to explain the hydrodynamic behavior of bioreactors under different conditions and have been employed to optimize the design of bioreactor by researchers [19-21]. Ding et al. [22] applied CFD simulations to evaluate the role of hydrodynamics in reactor design and optimize the reactor configuration in a laboratory-scale continuous stirred-tank reactor used for biohydrogen production. Liu et al. [23]developed a two-dimensional CFD model for optimizing the structure design of an airlift sonobioreactor for hairy root
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culture. The aims of the present work are to investigate the flow characteristics of a new
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bioreactor with dual ventilation-pipe and double sieve-plate (DVDSB), in which the
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semi-continuous fermentation of SLs was achieved and established. using CFD
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simulation and experimental validation. The hydrodynamic behavior including the velocity field, volume-averaged overall and time-averaged local gas volume fraction and liquid phase turbulent kinetic energy was predicted. Comparisons were then made
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between conventional fed-batch fermenter and DVDSB of hydrodynamic behavior on SLs production was predicted and validated.
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2. Materials and methods
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2.1 Reactor configuration and culture conditions
The dual ventilation-pipe and double sieve-plate bioreactor (DVDSB) with a total
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volume of 5.7L was operated in a semi-continuous flow mode for SLs fermentation [Fig.1]. Compared with the conventional fermenter, there is a sieve-plate in the middle of new designed bioreactor. The reactor is divided into cylinder part and cone part by
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the sieve-plate. The upper cylinder part and the tank of traditional reactor is the same, while the lower conical part is mainly for the sedimentation and collection of SLs. Furthermore, there are two ventilation pipelines in the novel reactor. The main oxygen supply pipeline and assistant oxygen pipeline are in the cone area and cylinder area respectively. The main oxygen supply pipeline can provide oxygen for the whole reactor while the assistant oxygen pipeline only supplies oxygen for the cylinder area.
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Figure.1 Schematic diagram of the new Bioreactor with dual ventilation pipe and double sieve-plate
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(DVDSB) (unit: mm).（a:side view; b:top view; c:the detail of sieve）
Candida albicans O-13-1 obtained from the Ocean University of China was used in this study. The temperature was maintained at 30℃ throughout the fermentation
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process . Seed medium contains: 100 g·L-1 of glucose, 10 g·L-1 of yeast extract, 1 g·L-1 of (NH2)2CO, pH is 6.0. The initial fermentation medium contains: 120 g·L-1 of glucose, 120 g·L-1 of oleic acid, 3.5 g·L-1 of yeast extract, 0.5 g·L-1 of peptone, 5 g·L-1 of sodium citrate, 4 g·L-1 of MgSO4·7H2O, 2 g·L-1 of (NH4)2SO4, 1 g·L-1 of KH2PO4, 0.1 g·L-1 of NaCl, 0.1 g·L-1 of CaCl2·2H2O [24]. Supplemented medium contains: 200 g·L-1 of glucose, 5 g·L-1 of yeast extract, 2 g·L-1 of (NH2)2CO. In the first twenty hours to maintain the pH at 5.8-6.2, then maintained at 3.5-4.0. The airflow rate was 8 L·min-1, and the stirring speed was 450 rpm. The same operation and fermentation conditions as mentioned above were operated in new bioreactor and conventional fermenter. 2.2 Analytical methods
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The key parameters including temperature, pH, dissolved oxygen concentration, cell population, SLs concentration, was observed during SLs fermentation. The content
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of yeast cells was determined by the dry weight method and the microscopic counting
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method [25, 26]. An oxygen electrode (Hamilton FDA 120, Bonaduz, Switzerland) was
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equipped in the bioreactor to monitor the concentrations of dissolved oxygen. The concentration of SLs in the culture was measured according to previous studies [8].
3. Computational fluid dynamic model
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3.1 Model assumption
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Repeated three times for every experiment.
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In this study, we assume that yeast cells distribute uniformly in liquid. And yeast
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cells and the mixture of the medium are regarded as one liquid phase, while the fluid phase characteristic such as density and viscosity were specified according to
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measurement results. From the above assumptions, there are two phase in the reactor (one gas phase and one liquid phase), and an Eurlerian-Eurlerian multiphase model in
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ANSYS CFX is appropriate to describe the flow behaviors of two different phases. 3.2 Governing equations
The Eulerian approach was adopted to describe flow behaviors of the gas and liquid phases, which were considered to be the dispersed and continuous phases, respectively. The two phase holdups satisfied the compatibility condition:
g l 1
(1)
Where g and l are volume fraction of gas phase and liquid phase, respectively. The continuity equations are:
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i i ii ui 0 t
(2)
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subscript i g and l represents the gas and liquid.
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Here t , , u i are the time, density and velocity of each phase, respectively. The
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The gas-liquid two phase momentum conservation equations are: i i ui T i i ui ui i p i eff,i ui ui t
g M i
i
I,li
(3)
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Note that p , eff,i , g and M I,li are the pressure, effective viscosity for phase i ,
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3.3 Inter-phase momentum transfer
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gravity acceleration vector, inter-phase momentum transfer force.
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In this study, drag force and lift force between the continuous phase and dispersed
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phase were considered among the inter-phase momentum transfer forces, while virtual mass force and turbulent dispersion force was neglected, as adding of them did not bring any obvious refinement to the current simulation results, but only convergence
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difficulties[27].
Drag force exerted by the dispersed phase on the continuous phase was calculated by:
M D,l g M D,gl
3 CD,lg l g ug ul ug ul 4 dg
(4)
Here, M D , CD , d g are the interphase drag force, drag coefficients and bubble diameter, respectively. Drag coefficient exerted by the gas phase on the liquid phase was obtained by the Ishii-Zuber drag model: 2 24 8 2 CD ,lg max 1 0.15Rem0.687 , min Eo0.5 E g , 1 g 3 3 Rem
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(5)
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Note that Rem , Eo and E g
are the mixture Reynolds number, Eotvos
number, correction term.
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(8)
(9)
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1 17.67 f g
(7)
18.67 f g
0.5 l 1 g m
(10)
(11)
are the gas-liquid mixture velocity, surface tension between
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Here, m , , E g
(6)
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f g
g l g dg2
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E g
2.5 *
g 0.4l g l
*
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m
m l 1 g
Eo=
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l d g u g u l
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Re m
liquid phase and gas phase and correction term, respectively [27]. Lift force acting perpendicular to the direction of relative motion of two phases was given by:
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M L,lg CL l g ug ul ul
(12)
And CL is the dimensionless lift coefficient with a value of 0.5.
3.4 Initial and boundary conditions Transient calculation started from assuming that gas holdup was zero in the reactor. It was also assumed that the gas bubbles supplied by the oxygen pipeline were distributed in the mixture with a fixed mean diameter of 5 mm. The multiple reference frame (MRF) boundary condition was adopted at the motion region around the impeller and the reactor was divided into a rotating domain and a stationary domain. The boundary condition for reactor inwalls was defined as no-slip for the liquid phase and
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free-slip for the gas phase. At the top of the computational domain a degassing condition was defined for the outlet boundary so that only gas phase can leave the
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domain.
3.5 Numerical solution
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A commercial computational fluid dynamics code ANSYS CFX 13.0 was used to establish the model to investigate hydrodynamics in two bioreactors. The geometry and
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the unstructured grid of the bioreactors were generated by ANSYS ICEM. The number of nodes and tetrahedral cells generated for the conventional fed-batch fermenter was 41370 and 204566, while for the new bioreactor was 51055 and 258953, respectively.
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Preliminary simulations were performed to ensure that the simulation results were
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independent of mesh size with this number of cells. The mesh layout for reactors geometry is shown in Fig. 2. The total simulation time for each three-dimensional
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transient CFD case was 120s.
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Figure.2 Unstructured mesh layout for reactors geometry
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4. Results and discussion 4.1 Model validation
Considering the limitation of available experimental techniques, overall gas holdups ( ) was measured by the volume expansion method during the steady state condition in the bioreactor (Equation 13).
Vg l Vl Vg l
100%
(13)
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Fig.3 Model simulated and experimental measured volume-averaged overall gas holdups in the conventional fermenter and new bioreactor with DVDSB
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As far as the CFD model validation is concerned, Fig. 3 presents a comparison between the experimentally measured and the simulated values of the total gas holdups at fixed agitation speed of 450 r·min-1 and varied inlet air flow rate of 2,4,6,8 L·min-1. It was noticed that model simulations were in very good agreement with experimental measurements, which indicated the reliability of the CFD model.
4.2 Hydrodynamics simulation
Gas holdup is defined as the fraction of gas volume in gas-liquid dispersion and is commonly used to characterize oxygen mass transfer and mixing of aerated vessels [28]. Fig. 4 shows the model simulated volume-averaged overall gas phase
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volume fraction in two bioreactors under fixed inlet air flow rate of 8 L·min-1 and agitation speed of 450 r·min-1. After 20s of agitation and aeration, the gas phase volume
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fraction distribution in reactors reaches steady state. The gas phase volume fraction in
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the new bioreactor present higher than conventional fermenter. As the two reactors
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operate under same conditions, this could be attributed to the design of the cone area and sieve plate. It contributes to increasing the moving distance of the air from the main oxygen supply pipeline to outlet (as shown in Fig. 1), and the mean residence time of
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gas in the reactor is increased with the increase of reactor height. This provides sufficient resident time of the water in reactor to permit the injected oxygen gas to
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transition into the dissolved state prior to reaching the top of the reactor, which is meaningful for the enhancement of the utilization ratio of oxygen for the
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microorganisms’ cultivation.
Figure.4 Model simulated reactor volume-averaged overall gas holdups along time in the conventional fermenter and new bioreactor with DVDSB
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Fig. 5 shows the transversal distributions of time-averaged local gas holdups at five
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different vertical positions. Considering the geometry symmetry of the reactors (Fig. 2),
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half of the vertical section (Z= 0 mm, X= 20-80 mm) was presented in this figure and
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five typical vertical positions were selected: 5 mm below the lower impeller (Y= 30 mm), 5 mm above the lower impeller (Y= 60 mm), 5 mm below the upper impeller (Y= 170 mm), 5 mm above the upper impeller (Y= 200 mm), middle of the lower and upper
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impellers (Y= 115 mm). It was evident from the figure that the local gas holdups in two reactors concentrate in the zone close to center axis and disperse in horizontal direction.
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And the local gas phase volume fraction was also influenced by vertical height and the largest local gas phase volume fraction was at the position below the lower impeller (Y= 30 mm). It might be that air from the inlet are hard to be brought to the tank under
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current agitation speed of 450 r·min-1 which results in the bubbles accumulation near
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impeller. And the increase in agitation speed would have a significant effect on
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increasing local gas holdup which was proven in our previously published work[27]. Also, the local gas holdups in the new reactor is higher than that in the conventional reactor at similar position, which is consistent with the previous conclusion about total
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gas holdup. A more uniform distribution of gas phase in the new reactor are important under such circumstances which is efficient and beneficial to the utilization of microorganisms.
Fig.5 Model simulated time-averaged local gas holdups along transversal course (Z= 0 mm, X=
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20-80 mm) at five vertical positions (Y= 30, 60, 115, 170, 200 mm) in the conventional fermenter and
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new bioreactor with DVDSB
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The three-dimensional CFD model was also used to predict transient gas holdup
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distributions at vertical sections (X= 0 mm) as shown in Fig.6, with three time points selected: t= 10, 60, 110 s (from left to right). It can be seen that the values of gas phase volume fraction around the central axis is higher than those in the bulk flow region, and
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the feed air and the corresponding dissolved oxygen get a wider distribution with the agitation of two impellers in the horizontal direction. It is same for traditional reactor
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and the cylinder area of the novel reactor for the same air flow rate and agitation speed. The difference is that due to the isolation of sieve plate, the ventilation from the bottom plays a great role in increasing gas phase concentration in cone area. Also, it can be seen
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that the vertical distance for the air injected from the main oxygen supply pipeline is
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total gas holdup.
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vertically oriented and longitudinally extended, which conduces to improve the reactor
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Fig.6 Model predictions of transient gas phase volume fraction distributions at the vertical sections (Z= 0 mm) in the conventional fermenter and new bioreactor with DVDSB with t= 10, 60,110 s
The transient gas holdup distributions at five typical horizontal sections: Y= 30, 60, 115, 170, 200mm (from left to right) were carried out as shown in Fig. 7, with a specified time point: t= 60 s. From the comparison of transient local gas holdup distributions of five typical horizontal sections, it can be found that regions near the impellers had a better gas dispersion compared with regions middle of the lower and upper impellers, which indicates that the design and location of impeller have an obvious effect on the gas holdup distributions.
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Fig.7 Model predictions of transient gas holdup distributions at the horizontal sections (Y= 30, 60, 115, 170, 200 mm) in the conventional fermenter and new bioreactor with DVDSB with t = 60 s.
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The transient liquid phase velocity distributions at vertical sections (X= 0 mm) as
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shown in Fig.8, with several time points selected: t= 10, 60, 110 s (from left to right). The flow characteristics, e.g. the presence of vortices, recirculation zones, dead zones
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etc., which were important for the mixing of substrate, microbial cell and oxygen all over the tank in fermentation processes, should be concerned. It can be seen that the two reactor generates powerful vortex area and liquid recirculation was observed in regions
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of bottom of the tank, which was often considered to be ‘‘dead’’ regions, and it could ensure better mixing of fermentation substrates and gas and promise higher mass-transfer efficiency in the reactor. But the velocity in cone area in the new reactor is dramatically lower than cylinder area which could be interpreted as an obvious ‘‘dead’’ zones. The dead zones meant the mixing was poor in this area whose volume should be reduced, but it provides good conditions for the separation of sophorolipids during the fermentation process.
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Figure.8 Model predictions of transient liquid velocity distributions at the vertical sections (Z = 0 mm) in the conventional fermenter and new bioreactor with DVDSB with t = 10, 60,110 s
As sophorolipids are heavier than water and the solubility of the sophorolipids is very low in the acidic fermentation environment. The sophorolipids would sedimentate onto the bottom of the tank naturally once the concentration reaches the saturation in the stationary state. Thus a semicontinuous fermentation process of sophorolipids was established in the new designed bioreactor, during which the production and the product separation were combined successfully.
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In addition, the simulated distributions contour of turbulent kinetic energy ( k ) shows that the values of turbulent kinetic energy in the lower impeller region were
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higher than those in the bulk flow region (Fig. 9), which is similar in the two reactors
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for the same stirring power.
Figure.9 Turbulence kinetic energy distribution contour of model in the conventional fermenter and new bioreactor with DVDSB
4.3 Effect on fermentation results of SLs
Fig.10 summarizes the comparison of the sophorolipids fermentation results between new bioreactor and conventional fermenter. Compared with 96 hours in the traditional reactor, the fermentation period in the new bioreactor was dramatically prolonged to 320 hours. The fermentation yield of SLs and the product formation rate in the DVDSB was increased significantly to 484 g·L-1 and 1.51 g·L-1·h-1 compared with
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the traditional reactor of 120 g·L-1 and 1.25 g·L-1·h-1, respectively. In addition, the conversion efficiency of carbon source of the new reactor was 60.0 %, while the
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traditional reactor is 51.0%.
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By integrating with the previous results of simulation, a qualitative relationship
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between hydrodynamics and sophorolipids production can be obtained. As the overall gas holdup in the new reactor is improved, along with the increase of local gas holdup, the yield of sophorolipids increase in the DVDSB. But the velocity distribution in the
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new reactor are inhomogeneous, especially the formation of “dead zones’’ in the cone area. It would negatively affect the mass-transfer efficiency, but it is obvious convenient
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for the naturally sedimentation for SLs. What more, it is noteworthy that the DVDSB can be operated under different conditions on hydrodynamic behaviors, eg: with higher agitation speed or relatively larger amount of air flow to a more dispersed gas
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distribution all over the whole reactor; however, this would have a negative effect on
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cultivation of microorganism. Thus, further investigation on the relationship between
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hydrodynamics and sophorolipids production are necessary.
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Figure.10 Comparison of the sophorolipids fermentation results in new bioreactor with conventional fermenter
5. Conclusions
The flow characteristics of the novel bioreactor with DVDSB for the SLs production were investigated and compared with conventional fed-batch fermenter 21
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rectors by using CFD simulation and experimental validation. The comparisons results on the hydrodynamic behavior show that due to the design of the sieve plate, the new
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bioreactor generates a better gas-liquid dispersion characteristics than the conventional
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fed-batch fermenter. And the fermentation yield of SLs and the product formation rate in
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the DVDSB was increased significantly to 484 g·L-1 and 1.51 g·L-1·h-1 compared with the traditional reactor of 120 g·L-1 and 1.25 g·L-1·h-1, respectively. The results on hydrodynamics behaviors in the DVDSB can be used to optimize
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operational parameters and the design of bioreactor to maximize the product productivity and indicates the DVDSB has the potential for application on a bigger scale
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fermentation of SLs.
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6. Acknowledgements
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The authors specially thank Dr. Shengkang Liang from Ocean University of China
7. References
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who provided the Candida albicans O-13-1.
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hydrodynamics and rheology of flocculating yeast suspensions in a high-cell-density airlift bioreactor", Biotechnology & Bioengineering, 89 (4), 393-399 (2005). 17 Núñezramírez, D.M., Medinatorres, L., Valencialópez, J.J., Calderas, F., López, M.J., Medranoroldán,
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H., Solíssoto, A., "Study of the rheological properties of a fermentation broth of the fungus Beauveria bassiana in a bioreactor under different hydrodynamic conditions", Journal of Microbiology & Biotechnology, 22 (11), 1494-1500 (2012). 18 Daverey, A., Pakshirajan, K., "Treatment of dairy wastewater containing high amount of fats and oils using a yeast-bioreactor system under batch, fed-batch and continuous operation", Desalination
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& Water Treatment, 1-7 (2015). 19 Nagarajan, V., Ponyavin, V., Chen, Y., Vernon, M.E., Pickard, P., Hechanova, A.E., "CFD modeling and experimental validation of sulfur trioxide decomposition in bayonet type heat exchanger and chemical decomposer for different packed bed designs", International Journal of Hydrogen Energy, 34 (6), 2543-2557 (2009). 20 Murthy, B.N., Ghadge, R.S., Joshi, J.B., "CFD simulations of gas-liquid-solid stirred reactor: Prediction of critical impeller speed for solid suspension", Chemical Engineering Science, 62 (24), 7184-7195 (2007). 21 Zhu, F., Huang, J., Chen, J., Yuanguang, L.I., "CFD simulation and optimization of an open raceway photo-bioreactor", Chemical Industry & Engineering Progress, 32 (4), 922-941 (2012). 22 Jie, D., Xu, W., Xue-Fei, Z., Nan-Qi, R., Wan-Qian, G., "CFD optimization of continuous stirred-tank (CSTR) reactor for biohydrogen production", Bioresource Technology, 101 (18), 7016-7024 (2010). 23 Liu, R., Liu, Y., Liu, C.Z., "Development of an efficient CFD-simulation method to optimize the structure parameters of an airlift sonobioreactor", Chemical Engineering Research & Design, 91 (2), 211-220 (2013).
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24 Xue, Y., Zhu, L., Xue, C., Yu, C., Liang, Q., Lu, W., "Recovery of purified lactonic sophorolipids by spontaneous crystallization during the fermentation of sugarcane molasses with Candida albicans O-13-1", Enzyme & Microbial Technology, 51 (6-7), 348-353 (2012). 25 Pan, W., Perrotta, J.A., Stipanovic, A.J., Nomura, C.T., Nakas, J.P., "Production of
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polyhydroxyalkanoates by Burkholderia cepacia ATCC 17759 using a detoxified sugar maple
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hemicellulosic hydrolysate", Journal of Industrial Microbiology, 39 (3), 459-469 (2012). 26 Szeszenia-Dąbrowska, N., Sobala, W., Świątkowska, B., Stroszejn-Mrowca, G., Wilczyńska, U.,
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"Environmental asbestos pollution — Situation in Poland", International Journal of Occupational Medicine & Environmental Health, 25 (1), 3-13 (2012). 27 Wang, H., Jia, X., Wang, X., Zhou, Z., Wen, J., Zhang, J., "CFD modeling of hydrodynamic characteristics of a gas-liquid two-phase stirred tank", Applied Mathematical Modelling, 38 (1),
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S1004-9541(16)30408-6 doi:10.1016/j.cjche.2016.09.014 CJCHE 698
To appear in: Received date: Revised date: Accepted date:
4 May 2016 23 August 2016 30 September 2016
Please cite this article as: Xiaoqiang Jia, Lin Qi, Yaguang Zhang, Xue Yang, Hongna Wang, Fanglong Zhao, Wenyu Lu, Computational fluid dynamics simulation of a novel bioreactor for sophorolipids production, (2016), doi:10.1016/j.cjche.2016.09.014
This is a PDF file of an unedited manuscript that has been accepted for publication. As a service to our customers we are providing this early version of the manuscript. The manuscript will undergo copyediting, typesetting, and review of the resulting proof before it is published in its final form. Please note that during the production process errors may be discovered which could affect the content, and all legal disclaimers that apply to the journal pertain.
ACCEPTED MANUSCRIPT Computational fluid dynamics simulation of a novel bioreactor for
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sophorolipids production
Xiaoqiang Jia1,2,3, Lin Qi1, Yaguang Zhang1, Xue Yang1, Hongna Wang1, Fanglong
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Zhao1, Wenyu Lu1,2,3
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1 Department of Biochemical Engineering, School of Chemical Engineering and Technology, Tianjin University, Tianjin 300072, PR China. 2 Key Laboratory of Systems Bioengineering (Tianjin University), Ministry of Education, Tianjin 300072, PR China. 3 Synthetic Biology Platform, Collaborative Innovation Center of Chemical Science and Engineering (Tianjin), Tianjin 300072, PR China.
Corresponding author. Tel.: +86-22-27892132; fax: +86-22-27400973. E-mail address: [email protected] (Wenyu Lu)
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* Supported by the National Key Basic Research Program of China (No. 2014CB745100), National Natural Science Foundation of China (No. 21576197), Tianjin Research Program of Application Foundation and Advanced Technology (No. 14JCQNJC06700), Technological Research and Development Programs of the China Offshore Environmental Services Ltd. (CY-HB-10-ZC-055).
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This paper describes three-dimensional computational fluid dynamics (CFD)
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simulations of gas-liquid flow in a novel laboratory-scale bioreactor contained dual
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ventilation-pipe and double sieve-plate bioreactor (DVDSB) used for sophorolipids (SLs) production. To evaluate the role of hydrodynamics in reactor design, the comparisons between conventional fed-batch fermenter and DVDSB on the
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hydrodynamic behavior are predicted by the CFD methods. Important hydrodynamic parameters of the gas-liquid two-phase system such as the liquid phase velocity field,
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turbulent kinetic energy and volume-averaged overall and time-averaged local gas holdups were simulated and analyzed in detail. The numerical results were also validated by experimental measurements of overall gas holdups. The yield of
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in the new reactor.
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sophorolipids was significantly improved to 484 g·L-1 with a 320 h fermentation period
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Keywords: Bioreactors; Gas Hold-UP; Computational Fluid Dynamics (CFD); Hydrodynamics; Sophorolipids Production.
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1. Introduction
Surfactants are a group of amphiphilic chemicals consisting of both hydrophilic and hydrophobic regions that partition preferentially at the interface between fluid phases [1, 2]. Annual consumption of surfactants in the world is more than 13 million tons, and most of them are synthesized by chemical methods. The large majority of the currently used surfactants are petroleum-based and are produced by chemical means. Biosurfactants, mainly produced by microorganisms, have advantages over chemical surfactants for their lower toxicity, higher biodegradability, better environmental compatibility and higher selectivity[3, 4]. Biosurfactants are grouped as glycolipids, lipopeptides, phospholipids, fatty acids, neutral lipids, polymeric and
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particulate compounds[5]. Sophorolipids is a kind of extracellular glycolipids biosurfactants which comprise a hydrophilic carbohydrate section and a hydrophobic
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fatty acid chain [6]. Sophorolipids is widely used in the environmental remediation and
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cleaning industries for the advantages of biodegradability, high surfactivity, low
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ecotoxicity and the production on renewable-resource substrates [4, 7, 8]. In the environmental remediation area, SLs is amongst one of the most promising biosurfactants for heavy metal removal from soil sediments. Experiments have indicated
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that sophorolipids could enhance biodegradation of the insoluble aromatic compounds like phenanthrene through enhanced solubilization [9-11]. In addition, SLs have been
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successfuly applied in the petroleum industry such as secondary oil recovery, remove hydrocarbons from drill material, and the regeneration of hydrocarbons from dregs and muds [12].
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For the required characteristics and great potential to replace the existing chemical
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surfactants, many studies have focused on reducing production costs or improving the
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yield of SLs to make it competitive with existing chemical surfactants[3, 4]. As the SLs production is a complex, multiphase chemical, biological and physical process, a lot of research has been performed on the optimization of the fermentation process, including
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fermentation type, culture conditions, carbon sources, medium components, and so on. Ribeiro et al. [13] observed that the production of SLs was favoured when culture media was supplied with avocado, argan, sweet almond and jojoba oil or when NaNO3 was supplied instead of urea, which indicated the potential of the selective production of SLs based on the selection of carbon and nitrogen sources to culture media. Ma et al. [14] used cell lysate of C. curvatus, oleic acid, and delignined corncob residue hydrolysate (DCCRH)/detoxified DCCRH as nitrogen and carbon sources and results demonstrated that renewable DCCRH can be utilized for the production of high-value SLs. Daverey et al. [15] studied low cost media based on sugarcane molasses and three different oils for the production of sophorolipids (SLs) from the yeast Candida bombicola in batch shake flasks. However, hardly any work has been published on the
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physical characteristics affecting the efficiency of SLs production. During recent decades, many studies have been made including structural
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improvement, hydrodynamic conditions optimization, in order to further improve
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various types of bioreactors to meet the demands of microorganism cultures and
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industrialized application. As the hydrodynamic behavior such as gas volume fraction, velocity fields, distributions of shear stresses, turbulent intensity that significantly affect the growth of microorganisms and the production of fermentation product. Klein et al.
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[16] assess the effect of operational conditions (air-flow rate, biomass concentration) on hydrodynamic behavior of an airlift bioreactor and the results on hydrodynamics can be
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used a priori or during the bioprocess to optimize operational parameters to avoid the occurrence of undesirable bioreactor stalling and to maximize the process productivity. The rheological properties of a fermentation with the fungus Beauveria bassiana under
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different hydrodynamic conditions were studied and the simulated results will be
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helpful in the optimization of scale-up production of these fungi[17]. Hence, it is
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necessary to investigate the hydrodynamic phenomena involved in SLs production for the industrial scale application. Research of SLs production from the perspective of bioreactor design and separation process optimization will be interesting and promising.
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As the laboratory-scale yeast-bioreactor system for the production of SLs [18], traditional semi-empirical approach to bioreactor design is time-consuming and the application of experimental techniques are limited to large amount spend on investigating flow fields, mass concentration fields, etc. Numerical simulation based on computational fluid dynamics (CFD) calculations can provide a feasible way to explain the hydrodynamic behavior of bioreactors under different conditions and have been employed to optimize the design of bioreactor by researchers [19-21]. Ding et al. [22] applied CFD simulations to evaluate the role of hydrodynamics in reactor design and optimize the reactor configuration in a laboratory-scale continuous stirred-tank reactor used for biohydrogen production. Liu et al. [23]developed a two-dimensional CFD model for optimizing the structure design of an airlift sonobioreactor for hairy root
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culture. The aims of the present work are to investigate the flow characteristics of a new
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bioreactor with dual ventilation-pipe and double sieve-plate (DVDSB), in which the
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semi-continuous fermentation of SLs was achieved and established. using CFD
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simulation and experimental validation. The hydrodynamic behavior including the velocity field, volume-averaged overall and time-averaged local gas volume fraction and liquid phase turbulent kinetic energy was predicted. Comparisons were then made
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between conventional fed-batch fermenter and DVDSB of hydrodynamic behavior on SLs production was predicted and validated.
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2. Materials and methods
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2.1 Reactor configuration and culture conditions
The dual ventilation-pipe and double sieve-plate bioreactor (DVDSB) with a total
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volume of 5.7L was operated in a semi-continuous flow mode for SLs fermentation [Fig.1]. Compared with the conventional fermenter, there is a sieve-plate in the middle of new designed bioreactor. The reactor is divided into cylinder part and cone part by
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the sieve-plate. The upper cylinder part and the tank of traditional reactor is the same, while the lower conical part is mainly for the sedimentation and collection of SLs. Furthermore, there are two ventilation pipelines in the novel reactor. The main oxygen supply pipeline and assistant oxygen pipeline are in the cone area and cylinder area respectively. The main oxygen supply pipeline can provide oxygen for the whole reactor while the assistant oxygen pipeline only supplies oxygen for the cylinder area.
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Figure.1 Schematic diagram of the new Bioreactor with dual ventilation pipe and double sieve-plate
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(DVDSB) (unit: mm).（a:side view; b:top view; c:the detail of sieve）
Candida albicans O-13-1 obtained from the Ocean University of China was used in this study. The temperature was maintained at 30℃ throughout the fermentation
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process . Seed medium contains: 100 g·L-1 of glucose, 10 g·L-1 of yeast extract, 1 g·L-1 of (NH2)2CO, pH is 6.0. The initial fermentation medium contains: 120 g·L-1 of glucose, 120 g·L-1 of oleic acid, 3.5 g·L-1 of yeast extract, 0.5 g·L-1 of peptone, 5 g·L-1 of sodium citrate, 4 g·L-1 of MgSO4·7H2O, 2 g·L-1 of (NH4)2SO4, 1 g·L-1 of KH2PO4, 0.1 g·L-1 of NaCl, 0.1 g·L-1 of CaCl2·2H2O [24]. Supplemented medium contains: 200 g·L-1 of glucose, 5 g·L-1 of yeast extract, 2 g·L-1 of (NH2)2CO. In the first twenty hours to maintain the pH at 5.8-6.2, then maintained at 3.5-4.0. The airflow rate was 8 L·min-1, and the stirring speed was 450 rpm. The same operation and fermentation conditions as mentioned above were operated in new bioreactor and conventional fermenter. 2.2 Analytical methods
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The key parameters including temperature, pH, dissolved oxygen concentration, cell population, SLs concentration, was observed during SLs fermentation. The content
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of yeast cells was determined by the dry weight method and the microscopic counting
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method [25, 26]. An oxygen electrode (Hamilton FDA 120, Bonaduz, Switzerland) was
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equipped in the bioreactor to monitor the concentrations of dissolved oxygen. The concentration of SLs in the culture was measured according to previous studies [8].
3. Computational fluid dynamic model
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3.1 Model assumption
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Repeated three times for every experiment.
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In this study, we assume that yeast cells distribute uniformly in liquid. And yeast
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cells and the mixture of the medium are regarded as one liquid phase, while the fluid phase characteristic such as density and viscosity were specified according to
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measurement results. From the above assumptions, there are two phase in the reactor (one gas phase and one liquid phase), and an Eurlerian-Eurlerian multiphase model in
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ANSYS CFX is appropriate to describe the flow behaviors of two different phases. 3.2 Governing equations
The Eulerian approach was adopted to describe flow behaviors of the gas and liquid phases, which were considered to be the dispersed and continuous phases, respectively. The two phase holdups satisfied the compatibility condition:
g l 1
(1)
Where g and l are volume fraction of gas phase and liquid phase, respectively. The continuity equations are:
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i i ii ui 0 t
(2)
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subscript i g and l represents the gas and liquid.
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Here t , , u i are the time, density and velocity of each phase, respectively. The
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The gas-liquid two phase momentum conservation equations are: i i ui T i i ui ui i p i eff,i ui ui t
g M i
i
I,li
(3)
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Note that p , eff,i , g and M I,li are the pressure, effective viscosity for phase i ,
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3.3 Inter-phase momentum transfer
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gravity acceleration vector, inter-phase momentum transfer force.
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In this study, drag force and lift force between the continuous phase and dispersed
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phase were considered among the inter-phase momentum transfer forces, while virtual mass force and turbulent dispersion force was neglected, as adding of them did not bring any obvious refinement to the current simulation results, but only convergence
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difficulties[27].
Drag force exerted by the dispersed phase on the continuous phase was calculated by:
M D,l g M D,gl
3 CD,lg l g ug ul ug ul 4 dg
(4)
Here, M D , CD , d g are the interphase drag force, drag coefficients and bubble diameter, respectively. Drag coefficient exerted by the gas phase on the liquid phase was obtained by the Ishii-Zuber drag model: 2 24 8 2 CD ,lg max 1 0.15Rem0.687 , min Eo0.5 E g , 1 g 3 3 Rem
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(5)
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Note that Rem , Eo and E g
are the mixture Reynolds number, Eotvos
number, correction term.
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(8)
(9)
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1 17.67 f g
(7)
18.67 f g
0.5 l 1 g m
(10)
(11)
are the gas-liquid mixture velocity, surface tension between
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Here, m , , E g
(6)
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f g
g l g dg2
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2.5 *
g 0.4l g l
*
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m
m l 1 g
Eo=
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l d g u g u l
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Re m
liquid phase and gas phase and correction term, respectively [27]. Lift force acting perpendicular to the direction of relative motion of two phases was given by:
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M L,lg CL l g ug ul ul
(12)
And CL is the dimensionless lift coefficient with a value of 0.5.
3.4 Initial and boundary conditions Transient calculation started from assuming that gas holdup was zero in the reactor. It was also assumed that the gas bubbles supplied by the oxygen pipeline were distributed in the mixture with a fixed mean diameter of 5 mm. The multiple reference frame (MRF) boundary condition was adopted at the motion region around the impeller and the reactor was divided into a rotating domain and a stationary domain. The boundary condition for reactor inwalls was defined as no-slip for the liquid phase and
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free-slip for the gas phase. At the top of the computational domain a degassing condition was defined for the outlet boundary so that only gas phase can leave the
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domain.
3.5 Numerical solution
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A commercial computational fluid dynamics code ANSYS CFX 13.0 was used to establish the model to investigate hydrodynamics in two bioreactors. The geometry and
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the unstructured grid of the bioreactors were generated by ANSYS ICEM. The number of nodes and tetrahedral cells generated for the conventional fed-batch fermenter was 41370 and 204566, while for the new bioreactor was 51055 and 258953, respectively.
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Preliminary simulations were performed to ensure that the simulation results were
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independent of mesh size with this number of cells. The mesh layout for reactors geometry is shown in Fig. 2. The total simulation time for each three-dimensional
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transient CFD case was 120s.
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Figure.2 Unstructured mesh layout for reactors geometry
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4. Results and discussion 4.1 Model validation
Considering the limitation of available experimental techniques, overall gas holdups ( ) was measured by the volume expansion method during the steady state condition in the bioreactor (Equation 13).
Vg l Vl Vg l
100%
(13)
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Fig.3 Model simulated and experimental measured volume-averaged overall gas holdups in the conventional fermenter and new bioreactor with DVDSB
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As far as the CFD model validation is concerned, Fig. 3 presents a comparison between the experimentally measured and the simulated values of the total gas holdups at fixed agitation speed of 450 r·min-1 and varied inlet air flow rate of 2,4,6,8 L·min-1. It was noticed that model simulations were in very good agreement with experimental measurements, which indicated the reliability of the CFD model.
4.2 Hydrodynamics simulation
Gas holdup is defined as the fraction of gas volume in gas-liquid dispersion and is commonly used to characterize oxygen mass transfer and mixing of aerated vessels [28]. Fig. 4 shows the model simulated volume-averaged overall gas phase
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volume fraction in two bioreactors under fixed inlet air flow rate of 8 L·min-1 and agitation speed of 450 r·min-1. After 20s of agitation and aeration, the gas phase volume
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fraction distribution in reactors reaches steady state. The gas phase volume fraction in
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the new bioreactor present higher than conventional fermenter. As the two reactors
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operate under same conditions, this could be attributed to the design of the cone area and sieve plate. It contributes to increasing the moving distance of the air from the main oxygen supply pipeline to outlet (as shown in Fig. 1), and the mean residence time of
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gas in the reactor is increased with the increase of reactor height. This provides sufficient resident time of the water in reactor to permit the injected oxygen gas to
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transition into the dissolved state prior to reaching the top of the reactor, which is meaningful for the enhancement of the utilization ratio of oxygen for the
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microorganisms’ cultivation.
Figure.4 Model simulated reactor volume-averaged overall gas holdups along time in the conventional fermenter and new bioreactor with DVDSB
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Fig. 5 shows the transversal distributions of time-averaged local gas holdups at five
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different vertical positions. Considering the geometry symmetry of the reactors (Fig. 2),
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half of the vertical section (Z= 0 mm, X= 20-80 mm) was presented in this figure and
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five typical vertical positions were selected: 5 mm below the lower impeller (Y= 30 mm), 5 mm above the lower impeller (Y= 60 mm), 5 mm below the upper impeller (Y= 170 mm), 5 mm above the upper impeller (Y= 200 mm), middle of the lower and upper
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impellers (Y= 115 mm). It was evident from the figure that the local gas holdups in two reactors concentrate in the zone close to center axis and disperse in horizontal direction.
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And the local gas phase volume fraction was also influenced by vertical height and the largest local gas phase volume fraction was at the position below the lower impeller (Y= 30 mm). It might be that air from the inlet are hard to be brought to the tank under
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current agitation speed of 450 r·min-1 which results in the bubbles accumulation near
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impeller. And the increase in agitation speed would have a significant effect on
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increasing local gas holdup which was proven in our previously published work[27]. Also, the local gas holdups in the new reactor is higher than that in the conventional reactor at similar position, which is consistent with the previous conclusion about total
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gas holdup. A more uniform distribution of gas phase in the new reactor are important under such circumstances which is efficient and beneficial to the utilization of microorganisms.
Fig.5 Model simulated time-averaged local gas holdups along transversal course (Z= 0 mm, X=
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20-80 mm) at five vertical positions (Y= 30, 60, 115, 170, 200 mm) in the conventional fermenter and
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new bioreactor with DVDSB
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The three-dimensional CFD model was also used to predict transient gas holdup
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distributions at vertical sections (X= 0 mm) as shown in Fig.6, with three time points selected: t= 10, 60, 110 s (from left to right). It can be seen that the values of gas phase volume fraction around the central axis is higher than those in the bulk flow region, and
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the feed air and the corresponding dissolved oxygen get a wider distribution with the agitation of two impellers in the horizontal direction. It is same for traditional reactor
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and the cylinder area of the novel reactor for the same air flow rate and agitation speed. The difference is that due to the isolation of sieve plate, the ventilation from the bottom plays a great role in increasing gas phase concentration in cone area. Also, it can be seen
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that the vertical distance for the air injected from the main oxygen supply pipeline is
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total gas holdup.
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vertically oriented and longitudinally extended, which conduces to improve the reactor
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Fig.6 Model predictions of transient gas phase volume fraction distributions at the vertical sections (Z= 0 mm) in the conventional fermenter and new bioreactor with DVDSB with t= 10, 60,110 s
The transient gas holdup distributions at five typical horizontal sections: Y= 30, 60, 115, 170, 200mm (from left to right) were carried out as shown in Fig. 7, with a specified time point: t= 60 s. From the comparison of transient local gas holdup distributions of five typical horizontal sections, it can be found that regions near the impellers had a better gas dispersion compared with regions middle of the lower and upper impellers, which indicates that the design and location of impeller have an obvious effect on the gas holdup distributions.
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Fig.7 Model predictions of transient gas holdup distributions at the horizontal sections (Y= 30, 60, 115, 170, 200 mm) in the conventional fermenter and new bioreactor with DVDSB with t = 60 s.
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The transient liquid phase velocity distributions at vertical sections (X= 0 mm) as
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shown in Fig.8, with several time points selected: t= 10, 60, 110 s (from left to right). The flow characteristics, e.g. the presence of vortices, recirculation zones, dead zones
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etc., which were important for the mixing of substrate, microbial cell and oxygen all over the tank in fermentation processes, should be concerned. It can be seen that the two reactor generates powerful vortex area and liquid recirculation was observed in regions
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of bottom of the tank, which was often considered to be ‘‘dead’’ regions, and it could ensure better mixing of fermentation substrates and gas and promise higher mass-transfer efficiency in the reactor. But the velocity in cone area in the new reactor is dramatically lower than cylinder area which could be interpreted as an obvious ‘‘dead’’ zones. The dead zones meant the mixing was poor in this area whose volume should be reduced, but it provides good conditions for the separation of sophorolipids during the fermentation process.
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Figure.8 Model predictions of transient liquid velocity distributions at the vertical sections (Z = 0 mm) in the conventional fermenter and new bioreactor with DVDSB with t = 10, 60,110 s
As sophorolipids are heavier than water and the solubility of the sophorolipids is very low in the acidic fermentation environment. The sophorolipids would sedimentate onto the bottom of the tank naturally once the concentration reaches the saturation in the stationary state. Thus a semicontinuous fermentation process of sophorolipids was established in the new designed bioreactor, during which the production and the product separation were combined successfully.
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In addition, the simulated distributions contour of turbulent kinetic energy ( k ) shows that the values of turbulent kinetic energy in the lower impeller region were
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higher than those in the bulk flow region (Fig. 9), which is similar in the two reactors
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for the same stirring power.
Figure.9 Turbulence kinetic energy distribution contour of model in the conventional fermenter and new bioreactor with DVDSB
4.3 Effect on fermentation results of SLs
Fig.10 summarizes the comparison of the sophorolipids fermentation results between new bioreactor and conventional fermenter. Compared with 96 hours in the traditional reactor, the fermentation period in the new bioreactor was dramatically prolonged to 320 hours. The fermentation yield of SLs and the product formation rate in the DVDSB was increased significantly to 484 g·L-1 and 1.51 g·L-1·h-1 compared with
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the traditional reactor of 120 g·L-1 and 1.25 g·L-1·h-1, respectively. In addition, the conversion efficiency of carbon source of the new reactor was 60.0 %, while the
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traditional reactor is 51.0%.
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By integrating with the previous results of simulation, a qualitative relationship
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between hydrodynamics and sophorolipids production can be obtained. As the overall gas holdup in the new reactor is improved, along with the increase of local gas holdup, the yield of sophorolipids increase in the DVDSB. But the velocity distribution in the
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new reactor are inhomogeneous, especially the formation of “dead zones’’ in the cone area. It would negatively affect the mass-transfer efficiency, but it is obvious convenient
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for the naturally sedimentation for SLs. What more, it is noteworthy that the DVDSB can be operated under different conditions on hydrodynamic behaviors, eg: with higher agitation speed or relatively larger amount of air flow to a more dispersed gas
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distribution all over the whole reactor; however, this would have a negative effect on
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cultivation of microorganism. Thus, further investigation on the relationship between
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hydrodynamics and sophorolipids production are necessary.
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Figure.10 Comparison of the sophorolipids fermentation results in new bioreactor with conventional fermenter
5. Conclusions
The flow characteristics of the novel bioreactor with DVDSB for the SLs production were investigated and compared with conventional fed-batch fermenter 21
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rectors by using CFD simulation and experimental validation. The comparisons results on the hydrodynamic behavior show that due to the design of the sieve plate, the new
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bioreactor generates a better gas-liquid dispersion characteristics than the conventional
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fed-batch fermenter. And the fermentation yield of SLs and the product formation rate in
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the DVDSB was increased significantly to 484 g·L-1 and 1.51 g·L-1·h-1 compared with the traditional reactor of 120 g·L-1 and 1.25 g·L-1·h-1, respectively. The results on hydrodynamics behaviors in the DVDSB can be used to optimize
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operational parameters and the design of bioreactor to maximize the product productivity and indicates the DVDSB has the potential for application on a bigger scale
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fermentation of SLs.
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6. Acknowledgements
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The authors specially thank Dr. Shengkang Liang from Ocean University of China
7. References
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who provided the Candida albicans O-13-1.
1 Elshafie, A.E., Joshi, S.J., Al-Wahaibi, Y.M., Al-Bemani, A.S., Al-Bahry, S.N., Al-Maqbali, D.A., Banat,
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