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Journal of Membrane Science 231 (2004) 81–90 Numerical simulation of the flow in a plane-channel containing a periodic array of cylindrical turbulence promoters C.P. Koutsou, S.G. Yiantsios, A.J. Karabelas∗ Department of Chemical Engineering, Chemical Process Engineering Research Institute, Aristotle University of Thessaloniki, P.O. Box 361, GR 570 01, Thermi, Thessaloniki, Greece Received 26 August 2003; accepted 14 November 2003 Abstract This work is aimed at obtaining a better understanding of transport phenomena in membrane elements, where feed-flow spacers (employed to separate membrane sheets and create flow channels) tend to enhance mass transport characteristics, possibly mitigating fouling and concentration polarization phenomena, while augmenting pressure drop. A model flow geometry is considered consisting of a plane-channel, where a regular array of cylinders is inserted, acting as turbulence promoters. Direct numerical simulations using the Navier–Stokes equations are performed over a range of Reynolds numbers typical of such membrane modules. The results show that the flow becomes unstable at a critical Reynolds number of 60, and progressively tends to a chaotic state. Qualitative flow features, such as the development and separation of boundary layers, vortex formation, the presence of high-shear regions and recirculation zones, and the underlying mechanisms are examined. In addition, quantitative statistical characteristics such as time-averaged velocities, Reynolds stresses, wall-shear rates and pressure drop are obtained, which are directly related to mass transport enhancement. © 2003 Elsevier B.V. All rights reserved. Keywords: Membrane spacers; CFD; Direct numerical simulation 1. Introduction Membrane processes are among the most advanced methods in water treatment and desalination. Spirally wound membrane modules are predominantly employed in reverse osmosis and nanofiltration, and they also find use in ultrafiltration and microfiltration. A characteristic of this type of modules is the presence of spacers in the feed-flow and permeate channels. The feed-flow spacers, in particular, which have the form of non-woven crossed cylinders, serving to separate adjacent membrane leaves and create flow passages, tend to promote turbulence and enhance mass transport. The term “turbulence promoters” has been accepted in the literature, although in reality the unstable flows may not necessarily manifest the characteristics of fully developed turbulence. In this way, the undesirable fouling and concentration polarization phenomena are mitigated. In parallel, however, the presence of spacers leads to increased pressure drop, as ∗ Corresponding author. Tel.: +30-2310-996201; fax: +30-2310-996209. E-mail address: karabaj@cperi.certh.gr (A.J. Karabelas). 0376-7388/$ – see front matter © 2003 Elsevier B.V. All rights reserved. doi:10.1016/j.memsci.2003.11.005 well to the formation of localized stagnation or dead zones, where the above phenomena may be intensified. Thus, in recent years the important role of membrane spacers has been recognized, and several experimental and theoretical studies have appeared aiming at understanding the underlying phenomena and optimizing spacer configurations. Shock and Miquel [1] studied experimentally various commercial spacers, both for the feed and permeate channels, and obtained correlations for the friction and the mass transfer coefficients. On the basis of the results obtained, they analyzed the effect of permeate flow channel length and concluded that there is an optimum number of membrane leaves to minimize pressure losses in the permeate channel. Zimmerer and Kottke [2] studied experimentally the effect of geometrical spacer characteristics on flow patterns, fluid residence times, pressure drop and mass transfer coefficients and proposed optimal configurations that would improve mass transfer at acceptable energy costs due to increased pressure drop. Today, with the development of powerful computational tools and high accuracy numerical methods, direct numerical simulation of turbulent flows in complex geometries 82 C.P. Koutsou et al. / Journal of Membrane Science 231 (2004) 81–90 is feasible for Reynolds numbers on the order of a few thousands. Thus, CFD is becoming a useful tool to assist in such studies. Karniadakis et al. [3] in a theoretical study of turbulence promoters for heat transfer enhancement studied the flow in a plane-channel, where a periodic array of small-diameter cylinders is placed. They report that the presence of the small cylinders leads to the destabilization of the flow by essentially the same mechanisms as in a plane-channel, namely formation of Tollmien–Schlichting waves, but at greatly reduced Reynolds numbers. These are close to 150, as compared to 5772 for a plane-channel according to linear hydrodynamic stability theory [4]. Relevant to turbulence promotion are also the studies of Chen et al. [5] and Zovatto and Pedrizzetti [6], who treat various geometric configurations of a single cylinder located in a plane-channel and analyze flow features and stability. Several theoretical studies have focused closer to membrane spacer configurations. Karode and Kumar [7] performed three-dimensional simulations. However, they employed a k–ε turbulence model, which is of questionable usefulness in such a complex geometry. Furthermore, spatial resolution appeared not to be adequate. Cao et al. [8] studied two-dimensional flow in a short channel containing two cylinders at various arrangements. Turbulence modeling was employed in that study as well. Schwinge et al. [9,10] performed direct numerical simulations of flow and mass transfer in channels containing five cylinders. The effect of various configurations on flow characteristics such as pressure drop, eddy formation, wall-shear stresses, and mass transfer was examined. Li et al. [11] presented a study of flow and mass transfer by performing a three-dimensional direct numerical simulation in a geometry closely representing membrane spacers. Periodic boundary conditions were employed, thus enabling them to simulate just one cell of the pattern formed by the spacer. The effect of spacer geometrical characteristics was studied and optimal parameters were proposed. Although no information about the spatial and temporal resolution of these results was provided, limited experimental data on average mass transfer coefficients appeared to support their simulations. The aim of the present study is to obtain a better understanding of the flow behavior, features and structures, as well as statistical characteristics in a model two-dimensional geometry which resembles membrane spacer configurations. This understanding is expected to facilitate spacer configuration optimization studies, where three-dimensional simulations and more realistic geometries need to be con- sidered. In the next section the model problem and the numerical techniques as well as computational resources are described. Subsequently, the results obtained as regards the dominant flow features and the underlying mechanisms are discussed. In addition, statistical flow characteristics relevant to mass transfer optimization are described. Furthermore, the temporal and spatial resolution of the numerical procedures employed is discussed. Finally, a short discussion is provided of the issue of periodic boundary conditions employed in the flow simulations. 2. Problem formulation and numerical method The flow geometry consists of a plane-channel of thickness H, in which an array of equally spaced cylinders is inserted, as shown in Fig. 1. The cylinders, of diameter D, are separated by a distance L, and are located symmetrically in the channel. The channel is infinite in extend in the streamwise and spanwise directions and the flow is assumed to be fully developed and two-dimensional. The ratios L/D and H/D are nominal parameters of the problem under consideration. However in this study, taking into account typical characteristics of membrane spacers, these ratios are fixed to the values of 6 and 2, respectively. The fluid is assumed to be Newtonian and incompressible and the flow is governed by the Navier–Stokes and the continuity equations: ∂u 1 2 + u · ∇u = −∇P + ∇ u ∂t Re (1a) ∇ ·u=0 (1b) The cylinder diameter, D, which is half of the channel thickness, is chosen as a length scale, and the average velocity U0 as the velocity scale, defined by  1 H/2 u(x, y, t)dy (2) U0 = H −H/2 Then, the time scale t0 is D/U0 , and the Reynolds number is Re = U0 D/ν, where ν is the kinematic viscosity of the fluid. It may be noted that various definitions of Reynolds number have been used in the literature, e.g. taking into account the porosity of the channel due to the presence of the inserts [1]. The boundary conditions are the no-slip and no-penetration conditions on the cylinder and channel surfaces. In addition, the flow is assumed to be periodic in the streamwise Fig. 1. Schematic of the flow geometry of a plane-channel and a periodic array of turbulence-promoting cylinders. C.P. Koutsou et al. / Journal of Membrane Science 231 (2004) 81–90 direction with periodicity L. Thus, for the velocity u(x + L, y, t) = u(x, y, t) (3) Similarly, the pressure is composed of a constant mean pressure gradient and a periodic part:   dP P(x, y, t) = x + P̂(x, y, t) (4a) dx P̂(x + L, y, t) = P̂(x, y, t) (4b) The assumption of periodicity, which is a typical practice in direct numerical simulations of turbulent flow (i.e. [12]), as well as in other applications of computational methods (i.e. molecular dynamics), allows the computational domain to be restricted to just one cell containing one cylinder. This issue is further discussed in the next section. 83 It may be emphasized that the results in this study were obtained through a direct numerical simulation (DNS) of the Navier–Stokes equations, without the introduction of any approximation by turbulence modeling. The numerical simulations covered the range of Reynolds numbers up to 200, which is representative of the operation of spirally wound membrane modules. In typical desalination membrane applications the feed-flow channel Reynolds number does not exceed 1000. However, this is defined on the basis of the channel hydraulic diameter, which is four times the cylinder diameter used in the present definition of Reynolds number. A CFD code (FLUENT, v. 6.0.12), which employs the finite-volume method, was used. During each simulation the governing equations were integrated in time by imposing a constant mean pressure gradient until the flow reached a statistically steady state, that is when all mean variables such as velocities and Reynolds stresses reach steady values. Time was advanced by a second-order Adams–Moulton scheme and the convective terms were discretized by a second-order upwind scheme. In all the simulations the dimensionless time step was less than 0.0015. The computational grid was chosen to be finer near the cylinder and the solid surfaces, in order to closely capture boundary layers and high-shear zones. By numerical experimentation it was found that a grid containing 5400 nodes was adequate for the range of Reynolds numbers covered in this study. This issue is discussed in more detail in the next section. 3. Results and discussion 3.1. Flow features and structures For Reynolds numbers up to 60 the flow is steady and symmetric with respect to the channel symmetry plane. As may be seen from Fig. 2, the boundary layers which develop Fig. 2. Steady flow-streamfunction (a and b) and vorticity (c and d) contours at Reynolds numbers of 55 (a and c) and 60 (b and d). Fig. 3. Unsteady flow instantaneous streamfunction (a) and vorticity (b) contours at Re = 70. 84 C.P. Koutsou et al. / Journal of Membrane Science 231 (2004) 81–90 2 Re=70 Re=90 Re=110 Re=170 v 1 0 -1 -2 Fig. 4. Instantaneous streamfunction contours of the fluctuating part of the flow field, at two different instances in time (a and b), at Re = 70. Red and purple points correspond to the minimum and maximum values, respectively. (Please refer to colour version on Science Direct). 0 2 4 6 8 10 12 14 t Fig. 5. Fluctuations of the normal velocity component as a function of time for various Reynolds numbers, at a position midway between two consecutive cylinders on the channel symmetry plane. Fig. 6. Instantaneous streamfunction contours at various time intervals during an eddy turnover period T, for Re = 170. C.P. Koutsou et al. / Journal of Membrane Science 231 (2004) 81–90 0.5 wall shear rate 0.4 0.3 0.2 0.1 0 -0.1 0 1 2 3 4 5 6 4 5 6 x (a) 0.5 0.4 wall shear rate around the cylinder are separated, thus resulting in the formation of two symmetric standing eddies behind the cylinder. As the Reynolds number increases, the standing eddies increase in length and the boundary layer separation points move towards the cylinder front stagnation point. Looked from the point of view of vorticity transport, as presented in Fig. 2(c) and (d), the wake of the cylinder consists of two layers of vorticity, shed in a similar fashion as in the case of a cylinder in unbounded flow. An additional important feature here is the presence of two additional vorticity layers bound on the channel walls. Another characteristic of the flow is the two high-velocity jets formed at the two flow constriction sections above and below the cylinder. These jets merge after the recirculation zone, leading to a velocity profile with an inflection point at the channel symmetry plane. As the Reynolds number is increased beyond the critical value of 60, the flow is destabilized, apparently through a Hopf bifurcation, and becomes periodic. As may be seen in Fig. 3, the recirculation eddies cease to be symmetric, they oscillate and are periodically detached. In parallel, there is an oscillation in the strength of the two high-velocity jets, as well as in the free vorticity layers shed from the cylinder. The above features suggest that the mechanism of the first instability of this flow is the same as that for a cylinder in unbounded flow. Indeed, if the mean flow is subtracted, the streamfunction of the oscillating part, as shown in Fig. 4, is very similar to the center- or cylinder-modes observed by Karniadakis et al. [3] and Chen et al. [5] (see their Figs. 9(c) and 8, respectively). In addition, the critical Reynolds number found by Chen et al. [5] for the case of a single cylinder in a channel is 83, which is not very different from 60 obtained in this study. Progressively, as the Reynolds number is increased, the flow instability is intensified. The waveforms of the fluctuating velocities, shown in Fig. 5, are enriched in harmonics, become more complex and tend to a chaotic state. Another characteristic observed is that the basic frequency of the oscillations changes rapidly over a narrow range of Reynolds numbers from 70 to 90. In Fig. 6 instantaneous streamfunctions are shown during an oscillation cycle at Re = 170. As may be observed, a characteristic of the flow is that the two high-velocity jets periodically increase in strength, collide and break through each other. Another distinct characteristic of the flow at higher Reynolds numbers is the periodic appearance of recirculation eddies at the channel walls. These eddies form near the point where the recirculation zone ends behind the cylinder, move along the channel walls, and disappear as they approach the constrictions close to the next cylinder. Similar wall eddies were observed in the study of Karniadakis et al. [3] when the small-diameter cylinders were placed close to one of the channel walls. The critical Reynolds number above which wall eddies first appear, was found to be close to 78. This was determined 85 0.3 0.2 0.1 0 -0.1 0 (b) 1 2 3 x Fig. 7. Dimensionless instantaneous shear rate as a function of position along the lower wall for various time intervals during an eddy turnover period, at Reynolds numbers 77 (a) and 78 (b). At Re = 78 negative shear rates appear. by calculating instantaneous shear rate profiles along one of the walls. As may be seen from Fig. 7, at Re = 77 shear rates are positive throughout an oscillation cycle, whereas at Re = 78 instantaneous negative shear rates appear. It is instructive to observe flow vorticity contours, as shown in Fig. 8. As the Reynolds number is increased, the free vorticity layers oscillate and gain strength locally to form separate vortices. These vortices interact with the layers of wall-bound vorticity forcing it to move away from the walls. As a result of this interaction the free vortices move away from the walls, as well. This behavior bears resemblance with the one presented in the numerical study of the interaction of a free vortex with a flat plate boundary layer by Luton et al. [13]. Thus, a distinct characteristic of the flow around cylinders in a channel is that, in addition to the vortices shed from the cylinders, conjugate vortices appear, originating from the wall-bound vorticity. Additionally, as 86 C.P. Koutsou et al. / Journal of Membrane Science 231 (2004) 81–90 Fig. 8. Instantaneous vorticity contours at Reynolds numbers of 70 (a), 90 (b), 110 (c), and 170 (d). At the higher Reynolds numbers vortices originating from the walls appear. pointed out by Zovatto and Pedrizzetti [6], in contrast to the case of a cylinder in unbounded flow, counterclockwise vortices shed from the lower side of the cylinder move upward and vice versa. Finally, another characteristic feature of the flow is the frequency of oscillations. By taking velocity traces at various locations in the channel and applying FFT transforms the frequency spectrum of the oscillations can be calculated. As shown in Fig. 9, over a narrow range of Reynolds numbers from 70 to 90 the dominant dimensionless frequency, which is equal to the Strouhal number (St = ΩD/U0 ), shifts from 0.295 to 0.495. This is the same Reynolds number range where wall eddies appear. Further increase of the Reynolds number results in enrichment of the frequency spectrum with harmonics and subharmonics, but without significant change in the dominant frequency. It may be mentioned here that a Strouhal number of 0.369 at the onset of instability was obtained by Chen et al. [5] for an analogous case of a single cylinder in a channel, whereas for a cylinder in unbounded flow the corresponding number is 0.138. 3.2. Statistical flow characteristics Fig. 9. Dimensionless frequency spectra of the fluctuations of the normal velocity for various Reynolds numbers, at a position midway between two consecutive cylinders on the symmetry plane. In Fig. 10 time-averaged flow velocity and Reynolds stress contours are shown. The velocity contours, apart from their obvious symmetry characteristics (i.e. u is symmetric and v is anti-symmetric with respect to the channel centerline), reveal that at relatively low Reynolds numbers the two high-velocity jets retain their identity, whereas as the Reynolds number increases the intense oscillations result in a smooth mean profile approaching plug flow. From the Reynolds stress contours, it may be observed that intense fluctuations move closer to the cylinder as the Reynolds number is increased and progressively occupy a larger extent of the flow domain on both sides of the cylinder. Apart from flow mixing, a characteristic of spacers and turbulence promoters in channels is the increase of wall-shear rates, which is directly related to the increase of mass transfer coefficients in high Schmidt number transport processes, such as salt transport in membrane desalination. As mentioned already, optimization of mass transfer C.P. Koutsou et al. / Journal of Membrane Science 231 (2004) 81–90 87 Fig. 10. Contours of time-averaged velocity components and Reynolds stresses for various Reynolds numbers. Red and purple points correspond to the minimum and maximum values, respectively. (Please refer to colour version on Science Direct). mean wall-shear rate 40 Re=70 Re=90 Re=110 Re=145 Re=170 30 20 10 0 0 1 2 (a) 3 4 5 6 x characteristics is beyond the scope of this paper, since this would require a more realistic representation of the membrane spacer geometry and a three-dimensional simulation. However, it is interesting to observe some relevant characteristics of the flow studied. In Fig. 11 time-averaged wall-shear rates and their fluctuations (r.m.s. values) are shown. Given D and U0 , as length and velocity scales, the shear rates are normalized by U0 /D. As expected, for all Reynolds numbers the maximum mean shear rate occurs near the constrictions above and below the cylinder. This maximum is significantly larger than that in a plane-channel, where the corresponding dimensionless shear rate for laminar flow is uniform and equal to 3. Fluctuations in shear rate appear to be significant as well. In all cases a local maximum occurs right before the cylinder where velocity fluctuations are more intense. Above a Reynolds number of 90, secondary local maxima appear downstream of the cylinder, which are related to wall boundary layer separation and the appearance of wall eddies. Finally, in Fig. 12 the dimensionless pressure drop, which is proportional to a friction coefficient, is shown 1 Re=70 Re=90 Re=110 Re=145 Re=170 6 Steady flow Unsteady flow Plane-channel -dP/dx wall shear rate fluctuations 8 4 0.1 2 0 0 (b) 1 2 3 4 5 6 x 0.01 50 60 70 80 90 100 200 Re Fig. 11. Dimensionless time-averaged shear rate (a) and r.m.s. values of the fluctuations (b) for various Reynolds numbers, as a function of position along the lower wall. Fig. 12. Dimensionless mean pressure gradient as a function of Reynolds number. Plane-channel laminar flow correlation: −dP/dx = 3Re−1 . C.P. Koutsou et al. / Journal of Membrane Science 231 (2004) 81–90 as a function of Reynolds number. This is also an important parameter in spacer optimization, since it is related to the additional energy costs incurred to achieve improved mass transfer benefits. The correlation found for the present geometry in the unstable flow regime is −dP/dx = 3.1Re−0.47 . As expected, the presence of the cylinders leads to a significant increase in pressure drop compared with that in a plane-channel, where for laminar flow −dP/dx = 3Re−1 . 0.25 N=5400 N=10000 N=21600 0.2 Amplitude 88 0.15 0.1 3.3. Validation of the results 0.05 To test the validity of the simulation results, tests with grids containing approximately twice and four times the original number of nodes were performed. In Fig. 13 timeaveraged wall-shear rates and r.m.s. values of their fluctuations are shown. In Fig. 14 the frequency spectra of the N=5400 N=10000 N=21600 mean shear rate 1 1.5 2 Frequency velocity fluctuations at a certain position in the channel are shown. Inspection of Figs. 13 and 14 suggests that not only statistical quantities but the transient flow behavior is also adequately resolved, for the range of Reynolds numbers covered in this study. 30 20 3.4. Effect of periodic conditions 10 0 0 1 2 (a) 3 4 5 6 x 8 wall shear rate fluctuations 0.5 Fig. 14. Dimensionless frequency spectra of the fluctuations of the normal velocity for three different grids comprised of 5400, 10 000 and 21 600 nodes, at Re = 170, at a position midway between two consecutive cylinders on the channel symmetry plane. 40 N=5400 N=10000 N=21600 6 4 2 0 0 (b) 0 1 2 3 4 5 6 x Fig. 13. Dimensionless time-averaged shear rate (a) and r.m.s. values of the fluctuations (b), as a function of position along the lower wall, for three different grids comprised of 5400, 10 000 and 21 600 nodes, at Re = 170. As mentioned in the previous section, periodic boundary conditions are usually employed in turbulent flow numerical simulations. The presence of the periodic array of cylinders imposes a strong constraint on the flow to acquire spatially periodic characteristics. However, the periodicity of geometry does not necessarily coincide with that of the flow, especially in the unstable flow regime. Ideally, a large number of cells, each containing one cylinder, should be considered. It is assumed in this study that considering only a single periodic cell adequately captures the dominant flow features and the main statistical quantities. To test this assumption, the flow in a periodic cell of twice the original length, containing two cylinders was simulated. The same spatial resolution was kept resulting in a grid containing twice the number of nodes. As may be seen from Fig. 15 a qualitative difference exists in that the oscillations in two neighboring cells are now exactly out of phase, whereas the single-cell simulations constrain neighboring cells to oscillate in phase. It may thus be hypothesized that in a simulation containing more cells, phase differences would exist between neighboring cells. However, as may be observed, the dominant flow features remain the same as in the single-cell simulations. In Fig. 16 time-averaged wall-shear rates and r.m.s. values are shown. It is evident that there is qualitative similarity of the flow features, and that the statistical quantities retain the basic periodicity of the geometry. Moreover, there is C.P. Koutsou et al. / Journal of Membrane Science 231 (2004) 81–90 89 satisfactory quantitative agreement between the single and the double-cell results. On the basis of these test results, it is suggested that simulations considering a flow periodicity coinciding with that of the geometry are capable of adequately capturing the dominant flow features and may also be used to obtain statistical quantities of interest, such as pressure drop, wall-shear rates and mass transfer coefficients. 4. Concluding remarks Fig. 15. Streamfunction (a) and vorticity contours (b) at Re = 170, obtained from a simulation where the flow periodicity interval is taken to be twice that of the geometry. mean wall shear rate 40 30 20 10 0 0 2 4 (a) 6 8 10 12 8 10 12 x 10 mean wall shear rate 8 6 4 2 0 (b) The flow in a model two-dimensional geometry, consisting of a plane-channel in which an array of cylinders is located, has been studied in order to obtain a better understanding of the behavior, the dominant features and structures, as well as the statistical characteristics. Above a critical Reynolds number of 60 the flow becomes unstable due to mechanisms similar to those operating in the case of a cylinder in unbounded flow. Above a Reynolds number of 78 wall eddies appear, conjugate to those shed by the cylinder. This distinct characteristic of the flow in the channel wall is due to the interaction of the vorticity shed by the cylinders with the vorticity layers created on the channel walls. Three-dimensional effects (i.e. along the cylinder axis) have not been considered in this study. It is known, for example, that above a Reynolds number close to 180 three-dimensional instabilities appear in the case of a cylinder in unbounded flow. However, the dominant flow features remain unaltered [5]. By employing periodic boundary conditions in the streamwise direction, significant savings in computational costs may be made since the computational domain can be restricted to just one cell containing one cylinder. The approach adopted, which is usual practice in turbulent flow numerical simulations, may be also applied to tackle the mass transfer problem in order to obtain local mass transfer coefficients. The interested reader may consult Karniadakis et al. [3] for a similar study of heat transfer. Although the flow periodicity does not coincide with that of the geometry, its statistical characteristics do so. Thus reliable information on features important for membrane spacer optimization studies can be obtained in this way. The understanding obtained in this study is expected to facilitate optimization studies of membrane spacer configuration, where three-dimensional simulations and more realistic geometries need to be considered. 0 2 4 6 x Fig. 16. Time-averaged shear rate (a) and r.m.s. values of the fluctuations (b), as a function of position along the lower wall, for Re = 170. The continuous and dotted lines correspond to simulations where the flow periodicity interval is the same and twice that of the geometry, respectively. Nomenclature dP/dx D H L pressure gradient (Pa/m) diameter of cylinders (m) channel height (m) cylinder spacing (m) 90 N P P̂ Re St t T u u u′ u′ U0 v v v′ v′ x y C.P. Koutsou et al. / Journal of Membrane Science 231 (2004) 81–90 number of nodes pressure (Pa) periodic part of pressure (Pa) Reynolds number Strouhal number time turnover period (s) u-velocity mean u-velocity Reynolds stress (or r.m.s. u-velocity) average velocity (m/s) v-velocity mean v-velocity Reynolds stress (or r.m.s. v-velocity) x-coordinate y-coornidate Greek letters v kinematic viscosity (m2 /s) Ω shedding frequency (Hz) References [1] G. Shock, A. Miquel, Mass transfer and pressure loss in spiral wound modules, Desalination 64 (1987) 339–352. [2] C.C. Zimmerer, V. Kottke, Effects of spacer geometry on pressure drop, mass transfer, mixing behavior, and residence time, distribution, Desalination 104 (1996) 129–134. [3] G.E. Karniadakis, B.B. Mikic, A.T. Patera, Minimum-dissipation transport enhancement by flow destabilization: Reynolds’ analogy revisited, J. Fluid Mech. 192 (1988) 365–391. [4] P.G. Drazin, W.H. 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