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Journal of Membrane Science 346 (2010) 71–85

Contents lists available at ScienceDirect

Journal of Membrane Science

journa l homepage: www.e lsev ier .com/ locate /memsci

iofouling in spiral wound membrane systems: Three-dimensional CFD modelased evaluation of experimental data

.S. Vrouwenveldera,b,∗, C. Picioreanub, J.C. Kruithofa, M.C.M. van Loosdrechtb

Wetsus, Centre of Excellence for Sustainable Water Technology, Agora 1, P.O. Box 1113, 8900 CC Leeuwarden, The NetherlandsDepartment of Biotechnology, Faculty of Applied Sciences, Delft University of Technology, Julianalaan 67, 2628 BC Delft, The Netherlands

r t i c l e i n f o

rticle history:eceived 18 June 2009eceived in revised form 7 September 2009ccepted 8 September 2009vailable online 15 September 2009

eywords:iofoulingD CFD modeleed spacer channel pressure dropluxembrane

a b s t r a c t

A three-dimensional (3D) computational model describing fluid dynamics and biofouling of feed channelsof spiral wound reverse osmosis and nanofiltration membrane systems was developed based on resultsfrom practice and experimental studies. In the model simulations the same feed spacer geometry asapplied in practice and the experimental studies was used. The 3D mathematical model showed thesame trends for (i) feed channel pressure drop, (ii) biomass accumulation, (iii) velocity distribution profile,resulting in regions of low and high liquid flow velocity also named channeling. The numerical modelpredicted a dominant biomass growth on the feed spacer, consistent with direct in situ observations onbiofouling of spiral wound membrane modules and monitors using Magnetic Resonance Imaging (MRI).The model confirms experimental results that feed spacer fouling is more important than membranefouling. The paper shows that mathematical modeling techniques have evolved to a stage that they canbe used hand-in-hand with experiments to understand the processes involved in membrane fouling.

anofiltrationeverse osmosisMRRIFO

© 2009 Elsevier B.V. All rights reserved.

oncentration polarizationiofilm

. Introduction

Worldwide, the drinking water demand is increasing and regu-ations on drinking water quality become stricter. High pressure

embrane filtration processes like reverse osmosis (RO) andanofiltration (NF) produce high quality drinking water. Declin-

ng costs of membrane processes stimulate the application ofembrane filtration processes in advanced water treatment prac-

ice [1,2]. Fouling affects the performance of the RO/NF systemsue to (i) increase in pressure drop across membrane elements

feed-concentrate channel), (ii) decrease in membrane perme-bility, (iii) increase in salt passage. These phenomena resultn the need to increase the feed pressure to maintain constantroduction and to clean the membrane elements chemically.

∗ Corresponding author at: Wetsus, Centre of Excellence for Sustainable Waterechnology, Agora 1, P.O. Box 1113, 8900 CC Leeuwarden, The Netherlands.el.: +31 58 2843000; fax: +31 58 2843001.

E-mail addresses: Hans.Vrouwenvelder@wetsus.nl (J.S. Vrouwenvelder),.Picioreanu@tudelft.nl (C. Picioreanu), J.C.Kruithof@wetsus.nl (J.C. Kruithof),.C.M.vanLoosdrecht@tudelft.nl (M.C.M. van Loosdrecht).

376-7388/$ – see front matter © 2009 Elsevier B.V. All rights reserved.oi:10.1016/j.memsci.2009.09.025

The major fouling mechanisms of RO and NF membranes arescaling, particulate and organic fouling and biofouling. Scal-ing by inorganic compounds is usually controlled using a scaleinhibitor, such as a polymer or an acid. Particulate fouling canbe controlled by extensive pretreatment, including ultrafiltra-tion. Thus, all types of fouling except biofouling and organicfouling – related types of fouling – are controllable. At themoment, biofouling is considered the major problem for RO andNF [2–11].

In spiral wound membrane modules, two types of pressure dropcan be discriminated: the trans-membrane pressure drop (TMP)and the feed spacer channel pressure drop (FCP), also named lon-gitudinal pressure drop. The trans-membrane pressure drop, thedifferential pressure between feed and permeate lines, is related tothe membrane flux (permeation rate). The definition of flux (per-meation rate) is the water volume passing the membrane per unitarea and time (L m−2 h−1). The FCP is the pressure drop between

the feed and concentrate lines. In practice, the FCP is critical foroperation.

Many authors mention a critical flux [12–15]. It has beenhypothesized that “below a critical flux no fouling should occur”.The critical flux has been studied extensively for the fouling of

7 of Mem

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2 J.S. Vrouwenvelder et al. / Journal

icrofiltration and ultrafiltration by colloidal particles [15]. Sev-ral studies propose the critical flux concept for spiral woundanofiltration and reverse osmosis membranes in relation to bio-

ouling [16–18] as well. The influence of biofouling on flux declinend FCP increase has been studied on monitor, test rig, pilot andull-scale for extensively pretreated water [19,20]. Irrespectivehether a flux was applied or not, the FCP and biofilm concen-

ration increased. A previous study showed that the critical fluxoncept, stating that “below a critical flux no fouling occurs”, isot a suitable approach to control biofouling of NF and RO systemsith extensive pretreatment [19]. It appears that in extensivelyretreated water of NF and RO, biofouling is a feed channel pressurerop problem [20].

Insight in biofilm formation and fluid dynamics is indispensable.uch an integrated model requires at least two essential compo-ents: a model for fluid flow (hydrodynamics or computationaluid dynamics, CFD) and a model for biofilm development. Thesewo models are coupled because on the one hand the fluid flowattern is influenced by the biofilm position. On the other hand,he biofilm growth is determined by the water flow which sup-orts the convective transport of nutrient and cell attachment andiofilm detachment are affected by the local shear stress. Cur-ently available two-dimensional (2D) and three-dimensional (3D)omputational fluid dynamics models on feed spacers in spiralound membrane modules focus predominantly on improvement

f mass transfer and flux [21–36]. While giving a detailed insightn local flow patterns around the spacer fibres, these CFD stud-es do not focus on the biofilm development and its influence oniofouling. 2D and 3D biofilm models, on the other hand, have

volved in the recent years to include the effects of flow andass transfer on biofilm formation not only on simple planar

urfaces [37–39], but also in complex geometries such as porousedia [40–42]. Because no models combining CFD and biofilm

rowth for spiral wound systems with spacers have been found in

ig. 1. Inventory of feed spacers commonly used in practice in commercially available spihe membrane module manufacturers are coded I to IV. The feed spacer thickness is comf all spacers.

brane Science 346 (2010) 71–85

literature, recently a 3D numerical model is developed to deter-mine hydrodynamics and biofouling in the feed spacer channel[43].

The main objective of this study was to qualitatively eval-uate the developed mathematical 3D model with experimentaldata and previously derived conceptual insights. When themodel matches with the experimental data, then 3D numer-ical simulations of biofilm formation and fluid dynamics willbe a suitable technique to understand membrane fouling pro-cesses.

2. Materials and methods

2.1. Feed spacer characterization

An inventory of feed spacers used in practice, produced by fourmajor global manufacturers of spiral wound NF and RO membranemodules, was made to determine spacer geometry and material(Fig. 1, manufacturers are coded I to IV). The feed spacers were madeof polypropylene. Spacer geometry was characterized with a stereomicroscope and a calibrated digital camera. The spacer thicknesswas determined with a sensitive accurate digital calliper (Mitutoyoabsolute, ID-C112BS).

The spacers commonly used in practice had a diamond-shapedstructure (Fig. 1) and thicknesses varying between 26 and 34 mil(1 mil equals 25.4 �m), according to manufacturer specifications.In some cases thicker spacer (45–50 mil) or spacers with aparallel-shaped structure were used. Membrane modules frommanufacturer II (Fig. 1) with feed spacer thickness 31 mil (780 �m)

were used in several membrane installations in the Netherlands.As being the most common, this spacer (Fig. 2A) was selected forour studies. Similar spacer dimensions were used in the model(Fig. 2B). An overview of spacer dimensions is presented in Table 1and Fig. 2.

ral wound NF and RO membrane modules by four global membrane manufacturers.monly expressed in mil (1 mil equals 25.4 �m). The bar length indicates the scale

J.S. Vrouwenvelder et al. / Journal of Membrane Science 346 (2010) 71–85 73

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ig. 2. Feed spacer geometry from practice (A) and model (B) with the same geomeC) The computational domain of 3 × 5 spacer frames: membranes on the top and box = 0) and liquid outlet (x = 20 mm). Adapted from Ref. [43].

Feed spacer porosity was determined with (i) a defined spacerheet surface area and volume measurements in a volumetric flasknd (ii) calculations based on average spacer strand diameter andtrand woven density. The determined porosity of the feed spaceras ∼0.85 (Table 1), matching the porosity in the model geometry

∼0.84).The specific surface area of feed spacers could not be determined

ccurately, even when using a confocal laser scanning microscopend coated spacer. However, from the model the feed spacer spe-ific surface area can be derived as 7700 m2 spacer m−3 spacer or230 m2 spacer m−3 total volume.

able 1ystem geometry and operation parameters in experimental conditions compared with t

Characteristic Unit

Feed spacer porosity m3 m−3

Specific surface area feed spacer m2 m−3

Specific surface area feed spacer per total volume m2 m−3

Thickness feed spacer �mThickness flow channel �mStructure feed spacer (non-woven) –Linear flow velocity m s−1

Membrane and spacer length mPressure drop over flow channelc kPaNormalized pressure drope kPa cm−1

.a. = not available.a Estimated value.b Membrane length in membrane module.c Under non-fouled conditions at 0.16 m s−1.d Indicative data for lead membrane modules from Ref. [44] and a consulting company

ccording membrane module manufacturers’ specifications. In membrane modules at thre clearly lower (like 7 kPa and 0.07 kPa cm−1 [44]).

e Normalized for system length.

ed spacer with thickness 31 mil from manufacturer II was selected for the studies.sides (z = 0 and 0.78 mm), periodic lateral boundaries (y = 0 and 12 mm), liquid inlet

2.2. Model description

The numerical model used in this study and water qualityparameters have been described [43]. Therefore, only the basicassumptions and features are summarized here.

The computational domain is a small area from the membraneseparation device of 2000 �m length (along main flow direction)

by 1200 �m width, with the membranes kept apart at 780 �m bythe spacer (Fig. 2C). The feed spacer geometry was derived fromfeed spacers used in practice in spiral wound membrane modules,using a stereo microscope and calibrated digital camera to deter-

he model input.

Practice Model Monitor MFS/(S-MFS)

0.85 0.84 0.85n.a. 7700 n.a.n.a. 1230 n.a.780 780 780780a 780 780Similar Similar Similar0.16 0.16 0.160.96b 0.02 0.20/(0.07)18 to ∼40d 0.80 3–80.2 to ∼0.4d 0.40 0.15–0.40

. The maximum pressure drop over the module flow channel can be up to 140 kPae end of a pressure vessel the pressure drop and normalized pressure drop values

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4 J.S. Vrouwenvelder et al. / Journal

ine spacer spatial dimensions. Spacer orientation in the modelas the same as applied in practice: 45◦ spacer rotation towards

eed flow direction (“diamond configuration”). The computationalomain contained five by three diamond spacer frames (Fig. 2C).eriodic boundary conditions were applied for the two sides ofhe domain (perpendicular to the main flow direction), both foruid flow and for biofilm formation. Using periodic boundary in amaller model, means that two domain sides are in open connec-ion with each other, improving model representativeness (sinceall effects of the model domain are excluded). The use of peri-

dic boundary conditions reduces the domain size needed to obtainuantitative information about a larger system [45,46], and there-ore the computational requirements. An industrial spiral wound

embrane module (8 in. diameter and 1 m length) can have upo 41 m2 membrane surface area and approximately 2 × 106 dia-

ond spacer frames distributed over several membrane envelopes,equiring massive computational efforts.

The hydrodynamic model includes a feed flow of water, enteringhe domain with an already established laminar flow profile (lin-ar velocity 0.16 m s−1). Navier–Stokes equations for steady-stateaminar flow are solved at several moments in time, for differenttages of biofilm growth, thus corresponding to different biofoul-ng states. The membrane and the spacer are no-slip (zero-velocity)

alls for the flow. The biofilm surface is also a no-slip wall, butts spatial position changes in time as new cells attach and as theiofilm grows.

The biofilm model includes microbial (biomass) attachmentn random positions on the membrane or spacer, but with anncreased attachment chance for decreasing values of shear stressn the walls. Further, the attached microbial cells grow andorm colonies (cellular automata algorithm from Picioreanu etl. [47,48]). Microbial growth and attachment are calculated inime increments of 3 h, in between which the flow pattern is re-alculated. For purpose of simplicity, it was assumed here thatubstrate and oxygen mass transport limitations are negligible andherefore the biomass can grow unlimited. However, the effect of

ass transport on biofilm formation was presented in Ref. [43].The model implementation [43] consists of a combina-

ion of MATLAB code (MATLAB 2007b, MathWorks, Natick,A, www.mathworks.com) as the main algorithm script, COM-

OL Multiphysics (COMSOL 3.5a, Comsol Inc., Burlington, MA,ww.comsol.com) finite element methods for solving the partialifferential equations governing the flow field and the solute massalances, and own Java routines for the biofilm model [47,48]. Thisybrid approach allows highly efficient model solution on commer-ially parallelized code and with the large memory requirementsnherent for 3D models. The 3D mesh for finite element solu-ion of the hydrodynamics and mass balances contained ∼430,000etrahedral elements (quadratic accuracy) with a maximum sizef 200 �m both in the volume and near the spacer boundaries.his means ∼2,100,000 equations were simultaneously solved forydrodynamics and ∼663,000 for the solute mass balance. TheD mesh for biomass and pseudo-viscosity distribution contained50 × 150 × 10 rectangular elements (cube size ∼80 �m). The com-utational code was run for all simulations on a workstation withwo parallel quad-core Intel Xeon E5430 processors, 32 GB DDR2

emory and Quadro 3700 FX graphics card.

.3. Experimental set-up

The development of biofouling in the feed channel was investi-

ated at two scales: (i) using a spiral wound membrane module [49]nd (ii) membrane fouling simulator (MFS [50]) with and withouteed spacer. Visual microscopic observations on fouling accumu-ation using the MFS window and in situ observations on foulingccumulation and velocity distribution profiles using Magnetic Res-

brane Science 346 (2010) 71–85

onance Imaging (MRI) were performed. In all modules and MFSstudies nanofiltration membranes and spacers from the same sup-plier were used. The NF membrane is a polyamide membrane. Thefeed spacer taken from the module was a 31 mil thick diamond-shaped polypropylene spacer with porosity 0.85 (Table 1). The feedspacers in the MFS had the same spatial orientation as in spiralwound membrane modules (45◦ rotation).

The membrane fouling simulator (MFS) is a tool developed tostudy and monitor fouling in spiral wound membranes [50,51].Using the MFS, fouling development can be monitored by (i)pressure drop measurements, (ii) in situ and non-destructive(visual) observations using the sight window and (iii) analysisof coupons sampled from the membrane and spacer sheet inthe monitor. The feed spacer channel dimensions of the MFS are0.00078 m × 0.040 m × 0.200 m. In the MFS, water flows throughthe spacer attached between a membrane sheet and the window.Membrane and spacer coupons of new and unused spiral woundnanofiltration membrane elements were placed in the MFS.

To quantify linear flow velocities in lead modules, an inventoryhas been made at several full-scale installations containing 8 in.diameter spiral wound NF or RO membrane modules [52]. Linearflow velocities in lead modules ranged between 0.07 and 0.20 m s−1.The same range of velocities was found for installations contain-ing 4 in. diameter lead modules. Biofouling was predominantlyobserved in lead modules with a high linear velocity. Therefore,a high linear flow velocity (0.16 m s−1) was selected for the studiesdescribed in the following sections.

Feed water for the MFSs was drinking water, distributed by adrinking water supply company without any disinfectant dosageor residual.

Substrate was dosed to the feed water of MFSs to stimulatebiomass growth. From a sterile vessel, containing a 5 L solutionof concentrated substrate, the substrate was dosed into the feedwater prior to the MFS by a peristaltic pump (Masterflex) at aflow of 0.03 L h−1. The dosage of substrate was checked periodi-cally by measuring the weight of the dosing bottle. The chemicalsNaCH3COO, NaNO3, and NaH2PO4 and were used with a ratio C:N:Pof 100:20:10 for the dosage solution. C was the growth limitingcompound. N and P were dosed to eliminate growth limiting condi-tions for N and P. The substrates were dissolved in ultrapure water.To restrict bacterial growth in the substrate dosage bottle, the solu-tion pH was set to 10.5 using NaOH. Dosage bottles were replacedevery 5 days. The substrate dosage (0.03 L h−1) was low comparedto the feed water flow rate (16 L h−1). Thus, the pH of the feed waterwas not measurably influenced by substrate dosage.

2.4. MRI study

Based on the principles of proton nuclear magnetic resonance(1H NMR), the evolution of spatial biofilm distribution and velocityfield can both be visualized by a technique called Magnetic Reso-nance Imaging (MRI). MRI has already been applied to study foulingwith biofilms in other systems such as circular pipes [53–56] andrecently in membranes [49,20]. Magnetic materials cannot be usedsince they interfere with the NMR signal. Therefore, a PVC versionof the MFS had to be developed, named S-MFS [20]. In order to fitin a 200 MHz super wide-bore magnet, the S-MFS had to be scaleddown to channel dimensions of 0.00078 m × 0.016 m × 0.040 m. Inthe S-MFS, the water flows through the spacer placed betweentwo membrane sheets. The S-MFS was produced with a manufac-turing accuracy of 20 �m. The feed spacer and membrane sheets

used in the NMR studies were taken from a new nanofiltrationmembrane module. The PVC flow cell was operated with the samelinear flow velocity and the same substrate dosage method wasapplied, as described for the MFS studies. For the determinationof the spatial flow velocity distribution, the flow was temporarily

J.S. Vrouwenvelder et al. / Journal of Membrane Science 346 (2010) 71–85 75

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unwrapped to visualize flow patterns and determine and quantifyaccumulated material.

ig. 3. Measured pressure drop in time (A), pressure drop increase (B) and biomass, and 5 days. Note the logarithmic scale in (B) and (C). The nutrient concentration.16 m s−1.

owered to 0.09 m s−1 (56% of the original linear flow velocity) forbout 45 min.

Two-dimensional velocity images of the superficial flow com-onent (axial direction) were acquired employing a standard phasehift velocity encoding pulse sequence with a size of 256 × 128 pix-ls resulting in a spatial resolution of ∼210 �m/pixel [49]. Moreetails on MRI velocimetry can be found elsewhere in the literature57].

.5. Pressure drop

A differential pressure transmitter (Endress+Hauser Deltabar S:MD70-AAA7FKYAAA) was used to determine the pressure differ-nce over the feed spacer channel of the (S-)MFS [44].

.6. Membrane autopsy

To characterize the accumulated fouling, 4 cm2 sections of mem-rane and feed spacers were taken from the (S-)MFS. The sections ofpacer and membrane were together placed in capped tubes filledith 30 mL of autoclaved tap water. To determine the amount of

iomass, the tubes with the membrane sections were placed inn ultrasonic cleaning bath (Bransonic, model 5510E-DTH, output

35 W, 42 kHz). The low energy sonic treatment (2 min) followedy mixing on a Vortex (few seconds) was repeated three times. Theiomass-water suspension from the tubes was used to determinective biomass in duplicate by measuring the adenosinetriphos-hate (ATP) concentration by luminescence [58]. The luminometer

ig. 4. Measured biomass distribution over length of spacer and membrane in theonitors operated in parallel under the same conditions and analyzed at different

unning times.

ulation (C) in monitors operated in parallel under identical conditions after 0, 1, 2,feed water was 0.60 mg acetate-C L−1 and linear flow velocity in the monitors was

(Celcis, model Advance) added 100 �L of LuminEX-B reagent (Cel-cis) to a 100 �L sample to release ATP from the bacterial cells.Subsequently, 100 �L of LumATE-PM (Celcis) was added for lightproduction. The amount of light produced was measured withthe luminometer (relative light units, RLU). The concentrationof ATP was derived from the RLU values using the conversionfactors of the linear relationship between RLU values and refer-ence ATP concentrations. The ATP concentrations of autoclaveddrinking water (<1 pg ATP mL−1) and two control solutions (2 and100 pg ATP mL−1) were determined as quality control.

Total organic carbon (TOC) of the accumulated biomass amountwas determined as non-purgeable organic carbon by infra-red gasanalysis. Sample pretreatment was identical as described for ATPanalysis except for the water type in the capped tubes, which wasdemineralized water for the TOC analysis.

A spiral wound membrane module was fed with tap water sup-plemented with substrate (1.00 mg acetate-C L−1). The centre tubeof the membrane was blocked during both fouling and MRI experi-ments to ensure that no permeate was produced [49]. A membranemodule from a full-scale installation suffering from an elevatedpressure drop caused by biofouling was cut open lengthwise and

The plot of the natural logarithm of biomass concentrationagainst time gave a straight line; the slope of the line is the specificbiomass growth rate.

Fig. 5. Compared pressure drop over feed spacer channel in time in computationalmodel with (model+S) and without substrate (model−S) and experimental data with(experiment+S) and without substrate (experiment−S) dosage. The horizontal linerepresents the maximum pressure drop reading of the differential pressure droptransmitter.

76 J.S. Vrouwenvelder et al. / Journal of Membrane Science 346 (2010) 71–85

Fig. 6. Compared time series of velocity profiles averaged over the channel height obtained with 3D-modeling (A–D) and NMR experiments (E–H). The flow channel containedspacers and the liquid was supplied with substrate to promote faster biofouling. Flow is from top to bottom. The images show the velocity values on colour scales differentbetween the model and NMR studies. Panels (E)–(H) adapted from Ref. [20].

Fig. 7. Measured 2D radial velocity images of a spiral wound membrane module measured before and after biofouling. The images show the z component of the flow velocityon a colour scale (adapted from Ref. [49]).

J.S. Vrouwenvelder et al. / Journal of Membrane Science 346 (2010) 71–85 77

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ig. 8. Unwound spiral wound membrane modules from full-scale installations sirection is from left to right. (A) Flow channels covering ∼50% of the feed inlet. In rend the membrane has a darker colour. (B) Flow channels covering ∼10% of the feedfew examples of flow channel locations. Inorganic material accumulated in the bi

. Results

.1. Inventory of feed spacers used in practice

Feed spacers used in practice in spiral wound nanofiltrationnd reverse osmosis membrane modules were characterized on aumber of aspects such as material type, structure and thickness.he feed spacers provided by 4 membrane manufacturers wereade of polypropylene. The spacers commonly used in practice

ad a diamond-shaped structure (Fig. 1) and thicknesses varyingetween 26 and 34 mil (1 mil equals 25.4 �m), according to manu-acturer specifications. In some cases thicker spacer (45–50 mil) orpacers with a parallel-shaped structure were used.

Membrane modules from manufacturer II (Fig. 1) with feedpacer thickness 31 mil (780 �m) were used in several membranenstallations in the Netherlands. Therefore, this spacer (Fig. 2) waselected for our studies. The determined porosity of the feed spaceras ∼0.85 (Table 1). The spatial dimensions of the feed spacerere determined using a stereo microscope with a calibrated digital

amera (Fig. 2A). Spatially identical spacer dimensions were usedn the model (Fig. 2B). The calculated porosity of the feed spacer inhe model was 0.84, matching the determined feed spacer porosity∼0.85). The specific surface area of the feed spacer was not deter-

ined experimentally. However, the feed spacer specific surfacerea (7700 m2 m−3, Table 1) can be derived from the model geom-try. The model feed spacer had very similar geometry to the feedpacer used in practice and experimental studies (Table 1, Fig. 2).

.2. Biomass growth parameters and pressure drop increase

The specific biomass growth rate (�max in day−1) is a key param-ter in the numerical model. To determine the biomass growthate, studies with five MFSs in parallel were performed with the

ame feed water substrate concentration (0.60 mg acetate-C L−1)nd same linear flow velocity in the MFS (0.16 m s−1). The monitorsere sampled after different operating periods to obtain informa-

ion about the biomass development after different running times.etermined were the pressure drop and biomass accumulation.

g from severe biofouling showing flow channels caused by biofouling. The flowc) the membrane is glued and has a lighter colour. In region (d) water was produced, resulting in displacement of the feed spacer (e). The arrows in the figures indicateenabled visual observation of the flow channels.

The biomass concentration increased exponentially (Fig. 3C).The biomass was equally distributed over the monitor width andlength (Fig. 4). Therefore, biomass concentrations averaged over themodule length were used for data evaluation. The average biomassconcentration increased exponentially (Fig. 3C) at least until day 3,indicating that biomass growth was not limited by substrate withinthis period. The derived net biomass growth rate �max = 2.8 d−1 wasused in the model. This is actually a lumped biomass accumulationrate, as the difference between the growth and the detachmentrates. The model does not explicitly include biomass detachment;therefore the experimental value was used as a net growth rate.

3.3. Comparison model with experimental data

The three-dimensional computational model [43] was based onspacer geometry, biomass growth rates and operating conditions(feed water quality, linear flow velocity) from practice (Table 1). Thelinear flow velocity was within the range as applied in practice [52].The effect of substrate in the feed water on biomass accumulation,caused by substrate utilization, was determined with the modeland experiments. In all model simulations we used default valuesfor the model parameters as mentioned by Picioreanu et al. [43].No parameter fitting or model calibration was done.

The pressure drop remained constant during the experimentswith monitors fed with water without substrate (Fig. 5). The pres-sure drop increased strongly in the presence of substrate in the feedwater, in relatively good agreement between model and experi-mental data. After 4 days, the model calculated a pressure dropthat deviated from the measured pressure drop (Fig. 5). Thereare two reasons for this overestimation of the pressure drop bythe model. First, substrate limitations appear when thick biofilmsdevelop in the modules, leading to a linear biomass growth ratevs. the unlimited exponential growth rate. Although the biomass

distribution along the module remained approximately the same(Fig. 4) indicating no growth limitations in the flow direction, sub-strate limitations can still occur in the biofilm depth. Herzbergand Elimelech [59] reported a higher distribution of active cellsin a Pseudomonas aeruginosa biofilm close a RO membrane sur-

78 J.S. Vrouwenvelder et al. / Journal of Membrane Science 346 (2010) 71–85

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ig. 9. Compared attachment and accumulation of biomass in time in model (A andere made using the sight window of the MFS during operation with dosage of a c

ccumulation.

ace; likely due to higher substrate levels induced by concentrationolarization effect caused by permeate production. In other words,he substrate concentration may be higher near the membrane.iomass detachment was not included in the model. The biofilmetachment certainly becomes important when the local flowelocities increase due to fouling. This leads to high shear stressnd biomass removal, affecting the pressure drop.

Velocity distribution profiles were (i) calculated using the math-matical model and (ii) determined experimentally using in situRI observations with an S-MFS flow cell designed for MRI stud-

es [20] and with a spiral wound membrane module [49]. The

alculated velocity field was averaged over the height of the compu-ational domain, i.e., the direction z between the two membranes.he 2D average velocity was relatively the same in all square ele-ents formed by spacer filaments before biomass accumulation

Fig. 6A). In time, the flow field profiles gradually changed to a dis-

in situ visual observations of the feed spacer channel (C and D). Visual observationsnd containing substrate. Analysis of the accumulated material confirmed biomass

torted flow field with flow channels (Fig. 6D). MRI measurementswith the S-MFS monitor showed that the average 2D flow velocityfield was relatively homogeneous (among the square spacer ele-ments) before substrate dosage (Fig. 6E). There was no flow at thespacer junctions and in the regions under the spacer filaments toflow was faster due to the reduction in the hydraulic area. In time,a distortion of the flow field (Fig. 6F and G) and eventually flowchannels (Fig. 6H) were observed, indicating flow heterogeneityacross the main flow direction (Fig. 6C). MRI measurements of afull-scale spiral wound membrane module showed that biofoulingled to a heterogeneous flow distribution also along the main flow

direction (Fig. 7). This also led to stagnant zones with low velocitiesand zones with high velocities to compensate for the low velocityregions (Fig. 7).

Flow channels can be observed during membrane autopsy, how-ever these are not always easily detected or often overlooked due

J.S. Vrouwenvelder et al. / Journal of Mem

Fig. 10. Compared pressure drop and pressure drop increase in time with and with-ow

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the pressure drop (Fig. 11). Although the same amount of biomass

ut feed spacer during experimental and model study. The pressure drop increaseas measured and calculated after 4 days of biofilm development.

o the opaque nature of biofilms. The effect of flow channel forma-ion has been clearly observed in cases where a high feed channelressure drop caused by major biofouling occurred (Fig. 8). Theiofilm entrapping inorganic compounds facilitated visual obser-ation of channel formation. The flow channels were mainly foundn the first 0.20–0.50 m of lead membrane modules from the instal-ation. The flow channels – caused by biofilm accumulation – werevenly distributed over the individual membrane leaves and overhe membrane envelope width (visual observations). The effectiveeed side membrane surface area was reduced by approximately0% (Fig. 8A) and 90% (Fig. 8B), most likely affecting the membraneux strongly. Displacement of the feed spacer was observed at thetrongly reduced (by ∼90%) effective feed side membrane surfacerea (Fig. 8B). Fig. 8A clearly shows the same fouling amount onhe glued edge of the membrane and on the membrane whereermeate production occurred. Since the glued edge was not pro-ucing permeate, this observation supports previous findings thatiofouling is predominantly a feed spacer channel related problem7,20].

The localization of biomass growth is predominantly at the feedide of membrane installations, in the first half of lead modules6,7,44,60]. Recently it has been clearly shown that biofouling is aroblem of biofilm growth and not a filtration effect leading to the

Fig. 11. Calculated overall pressure drop (A), biomass (B) and volume fract

brane Science 346 (2010) 71–85 79

accumulation of biomass on the membrane and spacer [61–64].In the model, biomass attached predominantly on the feed spacer(Fig. 9B) at linear flow velocities as applied in practice. Biomassattachment occurred at positions with low shear. Multiplication ofmicroorganisms resulted in a biomass volume increase, reducingthe water volume fraction. Experiments with the MFS showed thatbiomass accumulated mainly on the feed spacer, at the downstreamside of the spacer (Fig. 9D). Filamentous biofilm structures, calledstreamers, were observed and also reported earlier [20,50]. Thelongest streamers were attached to the spacer crosses. The modelshowed the same localization of biomass growth as in experimentalstudies using the MFS sight window (Fig. 9 [20,50] and MRI studies[49]).

3.4. Influence feed spacer: model and experimental data

Comparative studies were performed with and without feedspacer at the same cross flow velocity and substrate concentra-tion in the feed water to evaluate the influence of feed spacer onbiofouling development. As control, studies with and without feedspacer at the same cross flow velocity were done with and withoutsubstrate.

As expected, the feed channel pressure drop is strongly affectedby the presence of a feed spacer (Fig. 10). The feed spacer presenceincreased 10 times the pressure drop compared with the experi-ment without spacer, at the corresponding experimental flow ratesand without biofilm (clean device flow channels). In the absence ofsubstrate there was no biofilm growth and obviously no increase inthe pressure drop relative to the clean device flow channels. In thepresence of substrate a biofilm developed and the relative pressuredrop increased. The absolute FCP – sum of FCP and FCP increase –over the feed channel of the model domain determines the costscaused by fouling. With feed spacer, biofilm accumulation clearlyresulted in a stronger absolute FCP increase (Fig. 10). The modelsimulation matched rather well the experimental results in the caseof clean flow channels without biofilm, with (0.35–0.4 kPa cm−1)or without spacer (∼0.03 kPa cm−1). The current model predictedmore pressure drop after 4 days, but the difference is attributed tomore biofilm formation due to both absences of substrate limitationand biomass detachment in the model.

Modeling the overall pressure drop, biomass accumulation andvolume fractions in time showed that the same biomass concentra-tion in the system with and without spacer had different impact on

was formed with/without spacer (Fig. 11B), the overall pressuredrop increased more rapidly with biofilm formation when thespacer was present (Fig. 11A). With spacer the initial pressure dropwas 10 times higher, which cannot be explained by the 15% less

ions of liquid and biomass (C) in time with and without feed spacer.

80 J.S. Vrouwenvelder et al. / Journal of Membrane Science 346 (2010) 71–85

differ

vp

ddd

Fa

Fig. 12. Calculated pressure drop over the model domain length, at

olume liquid (Fig. 11C), but rather by the severely tortuous flowath imposed by the spacer [43].

With spacer, the pressure drop development over the modelomain length showed that the high biomass concentration after 3ays resulted in a stepwise decline of the pressure drop along theomain length (Fig. 12A). Without feed spacer, the pressure drop

ig. 13. Calculated flow velocity field at different times with (A–C) and without (D–F) feedre: (A and D) 6 h, (B and E) 42 h and (C and F) 80 h.

ent moments in time: (A) with spacer, and (B) without feed spacer.

was lower and a continuous (no stepwise) decline of pressure dropwas observed even at high biomass concentrations (Fig. 12B).

The simulated velocity fields in the feed spacer channel (heightis 780 �m) with and without spacer are presented in Figs. 13 and 14.The model results are shown in a section through the middle of theflow channel (390 �m, Fig. 13) and near the membrane (at 585 �m,

spacer, presented in sections at z = 390 �m (middle of the feed channel). The times

J.S. Vrouwenvelder et al. / Journal of Membrane Science 346 (2010) 71–85 81

F F) feet

iwscgfiwfststi(fha

fiacnrt

ig. 14. Calculated flow velocity field at different times with (A–C) and without (D–imes are: (A and D) 6 h, (B and E) 42 h and (C and F) 80 h.

.e., 195 �m from the membrane surface, Fig. 14). When a spaceras present the biomass accumulated predominantly on the feed

pacer (Fig. 13B and C). Without feed spacer, biomass attachmentould occur at the membrane only (Fig. 13D and E). The biomassrowth clearly affected the velocity field. The change in velocityeld distribution was much stronger with spacer (Fig. 13C) thanithout feed spacer (Fig. 13F). Clearly the effect of the spacer on bio-

ouling in membrane processes is predominant, despite that manytudies do not consider the presence of a spacer in their experimen-al set-up. At 75% of the channel height (585 �m) the velocity fieldhows a profile (Fig. 14) that differs strongly from the channel cen-re (Fig. 13). With spacer, nearer to the membrane the velocity flows mostly parallel to the spacer filaments present in this planar fieldFig. 14) which is not observed in the channel centre (Fig. 13). Theact that the velocity field shows great variations over the channeleight illustrates that 3D modeling is essential for fluid dynamicsnd biofouling studies in membrane systems.

In Fig. 6 a comparison is made between the computed velocityelds averaged over the channel height (Fig. 15) with the aver-

ge velocity field results from NMR studies with the S-MFS. Thealculated average velocity fields visualize the change in flow chan-els caused by biomass accumulation. With feed spacer, moreegions of higher flow velocities were observed (Fig. 15C) comparedo the simulations without feed spacer (Fig. 15F) with the same

d spacer, presented in sections at z = 585 �m (75% of the feed channel height). The

accumulated biomass amount (Fig. 11B). Comparison of the aver-age velocity field of the model and determined with MRI showedthe same distortion of flow field and channeling (Fig. 6). Alsothe spatial distributions of pressure and pressure drop are dif-ferent with or without spacer. The pressure drop over the modeldomain with spacer declines stepwise over the spacer strands, evenwhen biomass is not present (Fig. 16A). The differences in pressurebetween the spacer diamonds are more accentuated by the biofilmformation (Fig. 16B and C). Within the spacer diamonds the pres-sure does not change significantly, showing that the main pressuredrop is not due to the resistance to flow induced by the membranewalls but due to the spacer. In contrast, without spacer the pressuredrop decline is gradual over the domain length (Fig. 16D). In time,biomass accumulation increased the pressure drop and affected thepressure drop distribution over the domain (Fig. 16F).

In conclusion, experiments showed that (i) the FCP was stronglyaffected by the feed spacer (Fig. 10), (ii) flow channel formationoccurred in the presence of a feed spacer (Fig. 6), (iii) biomass accu-mulated predominantly on the spacer (Fig. 9), and (iv) the absolute

FCP was clearly higher with feed spacer compared to the moni-tor without spacer (Fig. 10), all consistent with results of the 3Dmodel studies. 3D modeling and experimental studies with andwithout feed spacer unambiguously illustrate that feed spacers playa crucial role in biofouling.

82 J.S. Vrouwenvelder et al. / Journal of Membrane Science 346 (2010) 71–85

F t time6

4

4

dfiflcNaf(Tiwbo

biomtmtd

ig. 15. Calculated flow velocity field averaged over the channel height, at differenh, (B and E) 42 h and (C and F) 80 h.

. Discussion

.1. Comparison model with practice

Compared to experimental studies, the 3D mathematical modeleveloped by Picioreanu et al. [43] showed the same developmentor (i) feed channel pressure drop (Fig. 5), (ii) biomass, (iii) veloc-ty distribution profile, resulting in regions of low and high liquidow velocity also named channeling (Figs. 6D and 14C). Channelingaused by biomass accumulation has been measured in situ withMR in spiral wound membrane modules (Fig. 7) and MFS (Fig. 6Gnd H) and observed during studies on membrane modules fromull-scale installations with elevated feed channel pressure dropFig. 8). Flow channel formation has been reported previously [5].he numerical model showed biomass growth occurred predom-nantly on the feed spacer (Figs 9A and B, 13 and 14), consistent

ith direct in situ observations on biofouling of spiral wound mem-rane modules and monitors using for example MRI [20,49] andbservations using the MFS sight window (Fig. 9C and D).

The numerical model proves suitable to describe the overalliomass accumulation and pressure drop in time as observed dur-

ng experiments. Moreover, the computed 3D spatial distributionsf biomass and flow velocity field agree qualitatively with the

easurements. This 3D model is based on generally accepted equa-

ions for the fluid flow and biofilm growth. The fact that someodel results deviate from the experimental data is partially due

o neglecting potentially important processes, such as biomassetachment and substrate mass transport limitation. On the other

s, with feed spacer (A–C) and without feed spacer (D–F). The times are: (A and D)

hand, the quality of model predictions depends also on the choiceof model parameters. No parameter optimization has been donein this study to fit the experimental data. All these facts underlinethat numerical tools have developed up to a stage where they canbe used to get reliable information on such complex processes asthe interaction between biofilm formation and hydraulics in RO andNF systems. This study and the study of Picioreanu et al. [43] clearlyshow that in order to make reliable predictions the exact geometryof the spacer and flow channel and 3D simulations need to be takeninto account fully.

4.2. Spacer relevance

Spiral wound membrane modules need spacers to separatemembrane envelopes and to promote the mass transfer alongthe membrane to minimize concentration polarization. The abso-lute FCP – sum of FCP and FCP increase – over the feed channelwill determine the operational costs. Both our model and exper-imental studies with and without feed spacer showed that theabsolute FCP is much higher in the presence of the feed spacer(Fig. 10). Moreover, the increase in FCP due to biofouling is strongerand faster with spacer. Given this important increase in pressuredrop, the feed spacer is therefore highly important for biofouling

[7,20,50,65,66]. The spacers not only influence the pressure dropbut also the flow profile (Fig. 15). This has a direct effect on the flowat the membrane surface and thereby will affect the extent of con-centration polarization. Promoting mass transfer by using a spacerseems therefore to come at the expense of higher operational costs.

J.S. Vrouwenvelder et al. / Journal of Membrane Science 346 (2010) 71–85 83

F t (D–Ft

wtotw

mcdsfitoasc

he

4

o

ig. 16. Calculated pressure distributions at different times with (A–C) and withouimes are: (A and D) 6 h, (B and E) 42 h and (C and F) 80 h.

Most biofouling studies in laboratory systems used flow cellsithout spacers. Very often these studies come to the conclusion

hat biomass accumulated on the membrane, thus affecting the fluxf permeate. The results we present here make it very likely thathe findings of studies without spacers would have been differenthen feed spacers had been present.

In practice, the increased feed channel pressure drop over theembrane module is a dominant reason for operational problems

aused by biofouling [7,20]. An increased feed channel pressurerop or channeling over the membrane unit at constant inlet pres-ure will also lead to less permeate production. Studies withouteed spacers are clearly not representative for biofouling studiesn RO and NF systems. Not only is the flow profile (and thus massransport to the membrane surface) different but also the amountf biomass growth on the membrane is strongly increased. In thebsence of a spacer the effect of fluid flow channeling is muchmaller. This again leads to an overemphasis of the role of con-entration polarization and neglect of flow channeling.

Representative conditions for practice like feed spacers andydrodynamics are considered essential for laboratory and mod-ling biofouling studies.

.3. Future studies and practical implications

Recent biofouling papers [67,68] refer to a biofilm-enhancedsmotic pressure strongly contributing to a flux decline and salt

) feed spacer, presented in sections at z = 390 �m (middle of the feed channel). The

passage increase. A flux decline was also found in a modelingstudy by Kim et al. [69] on the physical presence of exopolymericsubstances (EPS), which are produced and excreted by microorgan-isms. For a flux decline caused by biofouling, two mechanisms wereidentified: (i) an increase of the hydraulic resistance over the mem-brane and (ii) hindering the back diffusion of salts [67,68]. Herzbergand Elimelech [59] reported a higher distribution of active cells ina P. aeruginosa biofilm close a RO membrane surface; likely due tohigher substrate levels induced by concentration polarization effectcaused by permeate production. In practice, increased feed channelpressure drop over the membrane module is a frequent dominantoperational problem in RO and NF systems caused by biofouling[7,19,20,44]. Biofilm accumulation in NF and RO systems seem toeffect both the biofilm-enhanced concentration polarization andthe feed channel pressure drop, which may have synergistic nega-tive effect on membrane performance. Evidently, there is need tounravel all the effects of (bio)fouling on performance of RO and NFsystems (increase in feed spacer pressure drop, decrease in flux,and increase in salt passage) under representative conditions.

More insight in the biofouling process is needed to makeprogress in biofouling control. Direct in situ spatially resolved

information on biofilm accumulation, hydraulics and mem-brane performance is essential. The current 3D model needsto be extended to contain all membrane performance indi-cators with feed channel pressure drop, permeate production(trans-membrane pressure drop) and salt passage. Concentration

8 of Membrane Science 346 (2010) 71–85

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MFS membrane fouling simulatorMRI Magnetic Resonance ImagingNMR nuclear magnetic resonanceNF nanofiltration

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4 J.S. Vrouwenvelder et al. / Journal

olarization has to be included as well since this may con-ribute to biofouling, salt passage and scaling. Additionally, biomassetachment has to be incorporated in the model. The influencef parameters like spacer geometries, hydraulics and feed wateruality can be modeled to determine the effect on biomass accu-ulation, membrane performance indicators and cleanability. The

owadays commonly applied feed spacers restrict removal ofiomass from the membrane module during cleaning. Direct initu observations with NMR and MFSs can be used to validateodel results. The subsequent step may be pilot studies. Combina-

ion of 3D mathematical modeling and direct in situ observationssing, for example, NMR and MFSs is the key to make progress

n biofouling control. Moreover, the perspectives of combinedodeling-measuring approach are integral fouling control and

ptimized membrane performance at minimal costs.The development of membrane filtration processes less sus-

eptible to (bio)fouling and optimized for performance may haveonsequences for module and total installation design. The viabil-ty of such (bio)fouling tolerant membrane system should be shown

ith pilot plant studies and cost based evaluations. Use of math-matical modeling techniques are expected to help with reducinghe time and costs in developing new membrane and module con-gurations.

. Conclusions

1) Three-dimensional numerical simulations of biofilm formationand fluid flow are representative for experimental systems.Pressure drop development due to biofouling has been correctlydescribed by the model.

2) Biofilm accumulation resulted in channeling of fluid flow, indi-cating the essential role of feed spacers in membrane biofoulingstudies.

3) The perspectives of combining 3D modeling and experimen-tal measurements are integral fouling control and optimizedmembrane performance at minimal costs.

cknowledgements

This work was performed at Delft University of Technologynd Wetsus, centre of excellence for sustainable water technol-gy. The Delft University of Technology study was supported by theetherlands Organization for Scientific Research (NWO, VIDI grant64.06.003). Wetsus is funded by the Ministry of Economic Affairs.he authors like to thank the participants of the Wetsus theme ‘Bio-ouling’ for the fruitful discussions and their financial support. The

nput of Florian Beyer, Sarah Creber, Gertjan Euverink, Daniel Grafon der Schulenburg, Christoph Hinrichs, Harold Hollander, Mikeohns, Patrick Loulergue, Anna Sun, Bob van Bijnen, Maud Villainnd Arie Zwijnenburg is fully acknowledged.

Nomenclature

2D two-dimensional3D three-dimensionalATP adenosinetriphosphate [pg cm−2]CFD computational fluid dynamicsEPS exopolymeric substancesFCP feed channel pressure drop [kPa]Mil unit of length equal to one thousandth (10−3) of an

inch (0.0254 mm)

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RO reverse osmosisTOC total organic carbon [mg m−2]

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