Reduction of membrane fouling by innovative method (injection of air jet)
- Maryam-Sadat Amiraftabi^{1},
- Navid Mostoufi^{1}Email author,
- Mostafa Hosseinzadeh^{1} and
- Mohammad-Reza Mehrnia^{1}
https://doi.org/10.1186/s40201-014-0128-0
© Amiraftabi et al.; licensee BioMed Central Ltd. 2014
Received: 20 May 2014
Accepted: 14 October 2014
Published: 14 November 2014
Abstract
Background
One of the most important challenges about the Membrane Bio Reactors is membrane fouling. Fouling has been at the centre of a globe debate for more recent years. It leads to high operational and maintenance costs such as membrane damage and replacement of membrane. Membrane fouling is attributed to the physicochemical interactions between the bio fluid and membrane. In order to decrease the fouling in bioreactors there are common anti fouling strategies such as operation at low flux, Optimization of aeration flow-rate and Physical and chemical cleanings. However, often they are not effective.
Methodology
This work deal with fouling crisis by a new and innovative method in order to reduce of fouling on membrane surface by injection of parallel air jet on membrane bio reactor. This is a new idea and fundamental study about the influence of wall jet on fouling of membrane surface. This study is included both experimental and numerical investigations. In order to polarize the stream path on the surface of the membrane, four symmetric nozzles were implemented at the bottom of the membrane surface upon the sparger. The changes in the fouling resistance were experimentally measured at five various jet velocities and all of them recorded by a computer system. In addition the effect of air jet velocity and shear stress on fouling resistances was also investigated by computational fluid dynamics at the similar conditions.
Results
It was revealed that the permeate flux and resistance of fouling can be related to shear stress of air flow at the membrane surface. When the velocity of air jets increase, the permeate flux increase too. Also, results illustrate that jet injection can partially remove the cake which was formed on the surface of the membrane.
Conclusions
Correlations were developed for estimating each resistance of the membrane surface via the shear stress. The resistances of the cake are removed by the jet velocity changes, from 20% in lower jet velocity up to 40% in higher jet velocity.
Keywords
Background
Submerged membrane bioreactors (SMBRs) are widely used in wastewater treatment. One of the SMBR types is airlift membrane bioreactor (AMBRs) which contains two baffles that separate the bioreactor into a riser and two downcomers. Although the downcomer is filled mainly from the liquid, but the riser is gassed. As a result of the density difference between the bubbly mixture in the riser and the liquid in the downcomer, the flow circulates between these two sections [1].
The hydrodynamic properties and mixing pattern in MBRs depend on many factors, such as gas properties, liquid properties, gas entrance conditions and distributor geometry. Complexity of the hydrodynamics and development of efficient numerical methods have led researchers to employ computational fluid dynamics (CFD) to study the hydrodynamics of two-phase flow in MBRs [2]–[7].
The MBR filtration performance inevitably decreases with filtration time. This is due to the deposition of soluble and particulate materials onto and into the membrane, attributed to the interactions between activated sludge components and the membrane. This major drawback and process limitation has been under investigation since the early MBRs, and remains one of the most challenging issues facing further MBR development [8].
In recent reviews covering membrane applications to bioreactors, it has been shown that, as with other membrane separation processes, membrane fouling is the most serious problem affecting system performance. Fouling leads to a significant increase in hydraulic resistance, manifested as permeate flux decline or transmembrane pressure (TMP) increase when the process is operated under constant-TMP or constant-flux conditions respectively. In systems where flux is maintained by increasing TMP, the energy required to achieve filtration increases. Alternatively frequent membrane cleaning is therefore required, increasing significantly the operating costs as a result of cleaning agents and production downtime. More frequent membrane replacement is also expected [8].
A usual method to reduce the fouling on the membrane is to put a sparger below the membrane surface to inject air near the surface of the membrane and removing the fouling through the shear stress exerted on the surface. Some researchers have studied the effect of aeration on the membrane fouling and filtration of waste water [9]–[14]. According to these researches, the shear stress, generated by the aeration, has a large effect on reduction of filtration resistance in the SMBR. Increasing the permeate flux in a two-phases MBR is due to enhancement of the shear stress on the membrane surface [15]. Injection of gas increases the turbulence, which reinforces the shear stress [10],[16]. This strategy was shown to be very effective for flux enhancement in different membrane processes, in particular microfiltration [17],[18], ultrafiltration [10],[19] and nanofiltration [18] as well as for different membrane geometries such as tubular [10],[16],[17],[20], hollow fibre [17],[19],[20] and flat-sheet modules [17],[18].
In order to illustrate the results of workout wall jets, the effect of shear stress which is produced by flow of gas on the membrane surface at various conditions should be known accurately. Many researchers have measured the shear stress at the surface of the membrane in the liquid phase by using electrochemical method [9],[21]. Computational fluid dynamics (CFD) is a technique which solves the equations of motion and overcomes some disadvantages of other methods. By the CFD method the opportunity for analyzing the effect of geometry/configuration of bioreactors and hydrodynamics of the flows can also be provided. The objective of this work is to understand the effect of wall shear stress on the cake filtration resistance and finding the better way to decrease of fouling on membrane surface. To reach this goal, filtration experiments and CFD numerical simulation were performed on the same conditions of the MBR.
Methods
Experiments
Experimental set-up
The reactor had 22 litre capacities; it contained two baffles (31 cm high and 24 cm width) which divided the bioreactor. It involved a riser and two downcomers. In the middle of the MBR, a flat sheet membrane module, made by KUBOTA Co. (Japan) with a mean pore size of 0.45 µm, was installed vertically which is located between the two baffles. Effective filtration area was 0.116 m^{2}. A gas sparger was placed under the membrane for aeration. The gas sparger was a flexible porous rubber (3 cm × 21 cm) with 25 holes/cm^{2}. In addition four nozzles were fixed at each side of the membrane which nozzle slots were 5.82 mm × 0.72 mm. They used to evoke the air jet for removing the fouling cack which was formed on membrane surface.
Materials
The composition of standard wastewater
Components | Concentration (mg/L) |
---|---|
Glucose | 1350 |
(NH_{4})_{2}SO_{4} | 215 |
(NH_{4})H_{2}PO_{4} | 38 |
MgSO_{4}.7H_{2}O | 27.5 |
KCl | 20 |
FeSO_{4}.7H_{2}O | 2.5 |
NaHCO_{3} | 557.7 |
The operational parameters of the bench-scale airlift membrane bioreactor
Parameters | Unit | Average |
---|---|---|
Flux | Lm^{2} h^{‒1} | 16.4 |
TMP | bar | 0.4 |
DO | mgO_{2} L^{‒1} | 2.4 |
Temperature | °C | 19.9 |
pH | 6.9 |
Experiment procedure
P is pressure (Pa)
µ_{J} is permeate viscosity (mPas^{‒1})
R_{ m } is resistance of clean membrane (m^{‒1})
R_{ j } is jet resistance (m^{‒1})
R_{t} is total resistance (m^{‒1})
R_{ pb } is pore blockage resistance (m^{‒1})
R_{c} is resistance of cake that couldn't be removed by aeration and need to special physical washing (m^{‒1})
J_{ t } is the flux of water before cleaning (Lm^{‒2}hr^{‒1})
This resistance occurs inside the membrane structure due to pore blockage and only chemical washing can affect it.
Numerical simulations
Mass and momentum balance equations considered for the CFD modeling
Equation type | Equation |
---|---|
Continuity | $\frac{\partial}{\partial t}{\propto}_{L}{\rho}_{L}+\rho .\left({\rho}_{L}{\rho}_{L}{\stackrel{\u203e}{u}}_{L}\right)=0$ |
$\frac{\partial}{\partial t}{\propto}_{G}{\rho}_{G}+\nabla .\left({\propto}_{G}{\rho}_{G}{\stackrel{\u203e}{u}}_{G}\right)\phantom{\rule{0.5em}{0ex}}=0$ | |
Momentum balance | $\frac{\partial}{\partial t}\left({\propto}_{L}{\rho}_{L}{\stackrel{\u203e}{u}}_{L}\right)+\nabla .\left({\partial}_{L}{\partial}_{L}{\stackrel{\u203e}{u}}_{L}{\stackrel{\u203e}{u}}_{L}\right)=\propto {\partial}_{L}\partial P+\nabla .\phantom{\rule{0.12em}{0ex}}{\stackrel{\u203e}{\stackrel{\u203e}{\nabla}}}_{L}+{K}_{\mathit{GL}}\left({\stackrel{\u203e}{u}}_{G}\nabla {\stackrel{\u203e}{u}}_{L}\right)+{\u203e}_{L}{\rho}_{L}\stackrel{\u203e}{g}$ |
$\frac{\partial}{\partial t}\left({\propto}_{G}{\propto}_{G}{\stackrel{\u203e}{u}}_{G}\right)+\nabla .\left({\propto}_{G}{\rho}_{G}{\stackrel{\u203e}{u}}_{G}{\stackrel{\u203e}{u}}_{G}\right)=\u2012{\propto}_{G}\rho P+\nabla .{\stackrel{\u203e}{\stackrel{\u203e}{\nabla}}}_{G}+{K}_{\mathit{GL}}\left({\stackrel{\u203e}{u}}_{L}\partial {\stackrel{\u203e}{u}}_{G}\right)+{\propto}_{G}{\rho}_{G}\stackrel{\u203e}{g}$ | |
Standard k ‒ ε model | $\frac{\partial}{\partial t}{\rho}_{m}k+\nabla .{\rho}_{m}{\stackrel{\u203e}{u}}_{m}k=\nabla .\left(\frac{{{\partial}^{t}}_{m}}{\partial k}\partial k\right)+{G}_{k,m}\u2012{\rho}_{m}\epsilon $ |
$\frac{\partial}{\partial t}{\rho}_{m}\epsilon +\nabla .{\rho}_{m}{\stackrel{\u203e}{u}}_{m}\epsilon =\nabla .\left(\frac{{{\nabla}^{t}}_{m}}{{\partial}_{\epsilon}}\nabla \rho \right)+\frac{\epsilon}{k}\left({C}_{1\epsilon}{G}_{k,m}\u2012{C}_{2\epsilon}{\rho}_{m}\epsilon \right)$ | |
Mixture properties | ρ_{ m }=∝_{ G }ρG_{+∝}_{L}ρ_{ L } |
${\stackrel{\u203e}{u}}_{m}=\frac{{\propto}_{G}{\rho}_{G}{\stackrel{\u203e}{u}}_{G}+{\propto}_{L}{\propto}_{L}{\stackrel{\u203e}{u}}_{L}}{{\propto}_{m}}$ | |
${{\mu}^{t}}_{m}={\rho}_{m}{C}_{\mu}\frac{{k}^{2}}{\epsilon}$ |
α is void fraction
α_{ i }is volume fraction of phase i
ε is turbulent dissipation rate (m^{2}s^{‒3})
ρ_{ i }is density of phase i (kgm^{‒3})
v is jet velocity (ms^{‒1})
u_{ i } is velocity of phase i (ms^{‒1})
g is gas phase
l is liquid phase
C_{ 1ε } is constant
C_{ 2ε } is constant
C_{ µ } is constant
g_{c} is gravitation acceleration, 9.81 ms^{‒2}
G is velocity gradient, s^{‒1}
k is turbulent kinetic energy, m^{2}s^{‒2}
Turbulent jet
Here u' is fluctuation of turbulent shear stresses and v' is fluctuation of turbulent shear stresses also $\left(\stackrel{\u203e}{u\u203ev\u203e}\right)$ is flow variables or derivatives.
For finding the best solution of the turbulent boundary layer equations, the use of a turbulence model is necessary. For this purpose, the shear stresses or turbulent stresses were modelled by the k-ε model. It is worth mentioning that other turbulence models were also tried and it was found that k-ε is the best for simulation of the jet.
k-ε model
The transport equation model for k is derived from exact equation, while the transport equation model for ε was obtained using physical reasons [25].
Results and discussions
τ is shear stress (Nm^{‒2})
τ_{ i } is stress tensor of phase i(Nm^{‒2})
Conclusions
On the whole, membrane fouling is a controversial issue and it always leads lots of costs. Flux reduction occurs because of membrane fouling and formation of cake on the membrane surface. In this study, it is possible to remove part of fouling by using the air jets, which leads to the increasing in the permeate flux. By imposing proper shear stress on the surface of the membrane through jets of air, the cake can be removed and fouling reduced. In addition, the resistances were determined experimentally, also, the shear stresses on the membrane surface for air and sludge were evaluated by CFD simulation. It was shown that there is an acceptable correlation between the resistance and shear stress. It was shown that, higher velocity of air passing across the membrane causes more shear stress on the surface and incredibly leads to improvement of cleaning process.
Authors' contributions
M-SA carried out the wall jet studies, CFD simulations, participated in the built of experimental set up and providing the manuscript. MH participated in carried out the experiments. NM participated in the design of the study and performed the statistical analysis. M-RM helped to draft the manuscript and providing the bio reactor and activated sludge for support the experiments. All authors read and approved the final manuscript.
Declarations
Acknowledgements
The authors cannot express enough thanks to department chair of KIT University (Germany) who provided general support and encouragement: Prof. Dr. H. Oerltel. Also, the authors would like be to give special thanks to Dr. Reza Adeli and Dr. Schenkel from Karlsruhe Institute of mechanic (Germany) who provided purely technical help. In addition, completion of this project could not have been accomplished without the support of Dr. Mehrnia from Nanotechnology Laboratory of Tehran University for providing the bio reactor and activated sludge for support the experiments.
Authors’ Affiliations
References
- Merchuk JC, Contreras A, Garcia F, Molina Grima E: Studies of mixing in a concentric tube airlift bioreactor with different spargers. Chem Eng Sci 1998, 53: 709–719. 10.1016/S0009-2509(97)00340-0View ArticleGoogle Scholar
- Lu Y, Ding Z, Liu L, Wang Z, Ma R: The influence of bubble characteristics on the performance of submerged fiber membrane module used in microfiltration. Sep Purif Technol 2008, 61: 89–95. 10.1016/j.seppur.2007.09.019View ArticleGoogle Scholar
- Taha T, Cheong WL, Field RW, Cui ZF: Gas-sparged ultrafiltration using horizontal and inclined tubular membranes - a CFD study. J Membr Sci 2006, 279: 487–494. 10.1016/j.memsci.2005.12.063View ArticleGoogle Scholar
- Pak A, Mohammadi T, Hosseinalipour SM, Allahdini V: CFD modeling of porous membranes. Desalination 2008, 222: 482–488. 10.1016/j.desal.2007.01.152View ArticleGoogle Scholar
- Martinelli L: Influence de l'aération sur le Colmatage des membranes immerges. PhD thesis at Université Libre de Bruxelles. INSA Toulouse, Institut National des Sciences Appliquées; 2006Google Scholar
- Xu Z, Yu J: Hydrodynamics and mass transfer in a novel multi-airlifting membrane bioreactor. Chem Eng Sci 2008, 63: 1941–1949. 10.1016/j.ces.2007.12.026View ArticleGoogle Scholar
- Nguyen Cong Duc E, Fournier L, Levecq L, Lesjean B, Grelier P, Tazi-Pain A: Local hydrodynamic investigation of the aeration in a submerged hollow fiber membranes cassette. J Membr Sci 2008, 321(2):264–271. 10.1016/j.memsci.2008.05.001View ArticleGoogle Scholar
- Lee WT, Kang ST, Shin HS: Sludge characteristics and their contribution to microfiltration in submerged membrane bioreactors. J Membr Sci 2003, 216: 217–227. 10.1016/S0376-7388(03)00073-5View ArticleGoogle Scholar
- Ducom G, Puech FP, Cabassud C: Air sparging with flat sheet nanofiltration: a link between wall shear stresses and flux enhancement. Desalination 2002, 145: 97–102. 10.1016/S0011-9164(02)00392-2View ArticleGoogle Scholar
- Cui ZF, Chang S, Fane AG: The use of gas bubbling to enhance membrane process. J Membr Sci 2003, 221: 1–35. 10.1016/S0376-7388(03)00246-1View ArticleGoogle Scholar
- Hong SP, Bae TH, Tak TM, Hong S, Randall A: Fouling control in activated sludge submerged hollow-fiber membrane bioreactor. Desalination 2002, 143: 219–228. 10.1016/S0011-9164(02)00260-6View ArticleGoogle Scholar
- Sofia A, Ng WJ, Ong SL: Engineering design approaches for minimum fouling in submerged MBR. Desalination 2004, 160: 67–74. 10.1016/S0011-9164(04)90018-5View ArticleGoogle Scholar
- Wicaksana F, Fane AG, Chen V: Fiber movement induced by bubbling using submerged hollow-fiber membranes. J Membr Sci 2006, 271: 186–195. 10.1016/j.memsci.2005.07.024View ArticleGoogle Scholar
- Pollet S, Guigui C, Cabassud C: Fouling and its reversibility in relation to flow properties and module design in aerated hollow fiber modules for membrane bioreactors. Water Sci Technol 2008, 57: 629–636. 10.2166/wst.2008.113View ArticleGoogle Scholar
- Ndinisa NV, Fane AG, Wiley DE, Fletcher DF: Fouling control in a submerged flat sheet membrane system. Part II. Two-phase flow characterization and CFD simulations. Sep Sci Technol 2005, 41(7):1411–1445. 10.1080/01496390600633915View ArticleGoogle Scholar
- Cui ZF, Wright KIT: Gas–liquid two-phase cross-flow ultrafiltration of BSA and dextran solutions. J Membr Sci 1994, 90: 183–189. 10.1016/0376-7388(94)80045-6View ArticleGoogle Scholar
- Lee CK, Chang WG, Ju YH: Air slugs entrapped cross-flow filtration of bacterial suspensions. Biotechnol Bioeng 1993, 41: 525–530. 10.1002/bit.260410504View ArticleGoogle Scholar
- Mercier-Bonin M, Lagane C, Fonade C: Influence of a gas/liquid two-phase flow on the ultrafiltration and microfiltration performances, case of a ceramic flat sheet membrane. J Membr Sci 2000, 180: 93–102. 10.1016/S0376-7388(00)00520-2View ArticleGoogle Scholar
- Cabassud C, Laborie S, Durand-Bourlier L, Laine JM: Air sparging in ultrafiltration hollow fibers: relationship between flux enhancement, cake characteristics and hydrodynamic parameters. J Membr Sci 2001, 181: 57–69. 10.1016/S0376-7388(00)00538-XView ArticleGoogle Scholar
- Bellara SR, Cui ZF, Pepper DS: Gas sparging to enhance permeate flux in ultrafiltration using hollow fibre membranes. J Membr Sci 1996, 121: 175–184. 10.1016/S0376-7388(96)00173-1View ArticleGoogle Scholar
- Ducom G, Puech FP, Cabassud C: Gas/liquid two phase flow in a flat sheet filtration module: measurement of local wall shear stresses. J Chem Eng 2003, 81(3–4):771–775.Google Scholar
- Khalili-Garakani AH, Mehrnia MR, Mostoufi N, Sarrafzadeh MH: Analyze and control fouling in an airlift membrane bioreactor: CFD simulation and experimental studies. Process Biochem 2011, 46: 1138–1145. 10.1016/j.procbio.2011.01.036View ArticleGoogle Scholar
- Stern F, Wilson RV, Coleman HW, Paterson EG: Comprehensive approach to verification and validation of CFD simulations—part 1: methodology and procedures. J Fluids Eng 2001, 123: 793–802. 10.1115/1.1412235View ArticleGoogle Scholar
- Tagemman R, Gretler W: Numerical simulation of a two-dimensional turbulent wall jet in an external stream. Forsch Ingenieurwes 2000, 66: 31–39. 10.1007/s100100000039View ArticleGoogle Scholar
- Schlichting H, Gersten K: Boundary Layer Theory. Springer, Heidelberg; 2003.Google Scholar
- Constantinides A, Mostoufi N: Numerical Methods for Chemical Engineering With MATLAB Applications. Prentice Hall, New Jersey; 1999.Google Scholar
Copyright
This article is published under license to BioMed Central Ltd. This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly credited. The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated.