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Membrane Systems Planning and Design 365 Table 8.5 Summary of VCF equations for various hydraulic configurations VCF equation Hydraulic configuration Typical membrane process(es) Equation No. Equation No. VCFmax VCFavg (20) (22) (24) h i tf (26) 1 exp t (28) Deposition mode MCF 1 1 MF/UF Small volume crossflow MF/UF tf (19) tf [(tb ?Qb) < Vf] (w/o feed tank) 2t t Large volume crossflow MF/UF tf Qf tf [(tb ?Qb) > Vf] (w/ feed tank) 1 tb Qb 2 t tf " # (21) tf Qf Qf tb Qb tb Qb CSTR w/o NF/RO (small-scale) 1 (23) 1 backwashing MF/UF (w/ bleed) 1 R 1 R CSTR w/ backwashing MF/UF (w/ bleed) 1 t h i tf (25) 1 1 1 exp 1 R tf P t 1 R PFR NF/RO VCFðxÞ QpðxÞ (27) 1 Qp 1 R Qb = backwash flow, gpm. Qf = feed flow, gpm. Qp = filtrate flow, gpd. Qp(X) = filtrate flow at position “X” within the membrane unit, gpd. R = membrane unit recovery, decimal percent. tb = backwash duration, min. tf = filtration cycle duration, min. t = solids retention time, min. VCFavg = average VCF, dimensionless. VCFmax = maximum VCF, dimensionless. VCF(X) = VCF at discrete position “X” within the membrane unit, dimensionless. Vf = volume of feed, gal. X = position in the membrane unit in the direction of tangential flow (i.e., X = 0 at the entrance to the first module), ft.
366 N.K. Shammas and L.K. Wang Table 8.6 Typical range of VCF values for various hydraulic configurations Hydraulic configuration VCF Deposition mode Dead-end 1 Suspension mode PFR 3–20 Crossflow 4–20 CSTR 4–20 5.1. Membrane Flux The flux – the flow per unit of membrane area is one of the most fundamental considerations in the design of a membrane filtration system, since this parameter dictates the amount of membrane area necessary to achieve the desired system capacity and thus the number of membrane modules required. Because the membrane modules represent a substantial component of the capital cost of a membrane filtration system, considerable attention is given to maximizing the membrane flux without inducing excessive reversible fouling, thereby minimizing the number of modules required. Typically, the maximum flux associated with a particular membrane filtration system is determined during pilot testing, mandated by the state, or established via a combination of these two in cases in which the state specifies a maximum operating flux based on the pilot results. Independent of maximum flux, pilot testing is also commonly used to determine a reasonable operating range that balances flux with backwash and chemical cleaning frequencies. Because higher fluxes accelerate fouling, backwashing and chemical cleaning must usually be conducted more frequently at higher fluxes. The upper bound of the range of acceptable operating fluxes (provided this bound does not exceed the state-mandate maximum) is sometimes called the “critical” flux, or the point at which a small increase in flux results in a significant decrease in the run time between chemical cleanings. A membrane filtration system should operate below this critical flux to avoid excessive downtime for cleaning and the consequent wear on the membranes over time due to increased chemical exposure. The flux through a membrane is influenced by a number of factors, including: 1. Pore size (for MF, UF, and MCF membranes) 2. Module type (i.e., cartridge, hollow-fiber, spiral-wound, etc.) 3. Membrane material 4. Water quality However, it is important to note that higher fluxes do not necessarily indicate that one membrane is better than another for a particular application. Factors such as: 1. Estimated membrane life 2. Fouling potential 3. Frequency and effectiveness of chemical cleaning
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Membrane and Desalination Technolog
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Editors Dr. Lawrence K. Wang Zorex
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vi Preface Our treatment of polluti
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Contents Preface . ................
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Contents xi 3.4. Considering Existi
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Contents xiii 7. Membrane Separatio
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Contents xv 6. Design for Large Com
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Contents xvii 13. Desalination of S
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Contributors JIRAPAT ANANPATTARACHA
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CONTENTS 1 Membrane Technology: Pas
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Membrane Technology: Past, Present
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48 J. Ren and R. Wang Key Words Pol
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50 J. Ren and R. Wang Nonporous den
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52 J. Ren and R. Wang pervaporation
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54 J. Ren and R. Wang HO HO OH O OH
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56 J. Ren and R. Wang Fig. 2.7 Chem
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58 J. Ren and R. Wang N O O 3.10. P
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60 J. Ren and R. Wang inversion, th
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62 J. Ren and R. Wang where Dm i an
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64 J. Ren and R. Wang as nucleation
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66 J. Ren and R. Wang and no polyme
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68 J. Ren and R. Wang where b ¼ v1
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70 J. Ren and R. Wang S gelation ti
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72 J. Ren and R. Wang structure wil
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74 J. Ren and R. Wang Viscous finge
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76 J. Ren and R. Wang nonsolvent so
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78 J. Ren and R. Wang Thickness of
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80 J. Ren and R. Wang 5.1.1. Rheolo
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82 J. Ren and R. Wang the spinneret
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84 J. Ren and R. Wang Dynamic visco
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86 J. Ren and R. Wang where A is th
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88 J. Ren and R. Wang In the spinni
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90 J. Ren and R. Wang stress, espec
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92 J. Ren and R. Wang solution at t
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94 J. Ren and R. Wang TIPS ¼ Therm
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96 J. Ren and R. Wang 5. Kesting RE
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98 J. Ren and R. Wang 51. Matsuyama
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100 J. Ren and R. Wang 92. Ren J, C
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102 L. Song and K.Guan Tay Key Word
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104 L. Song and K.Guan Tay Flux A A
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106 L. Song and K.Guan Tay increase
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108 L. Song and K.Guan Tay Table 3.
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110 L. Song and K.Guan Tay • A fe
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112 L. Song and K.Guan Tay Feed wat
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114 L. Song and K.Guan Tay Fouling
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116 L. Song and K.Guan Tay Fouling
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118 L. Song and K.Guan Tay The symb
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120 L. Song and K.Guan Tay Table 3.
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122 L. Song and K.Guan Tay Permeate
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124 L. Song and K.Guan Tay Average
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128 L. Song and K.Guan Tay generati
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132 L. Song and K.Guan Tay flux. Un
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134 L. Song and K.Guan Tay 14. Kaak
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136 N.K. Shammas and L.K. Wang remo
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138 N.K. Shammas and L.K. Wang The
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140 N.K. Shammas and L.K. Wang excu
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142 N.K. Shammas and L.K. Wang dire
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144 N.K. Shammas and L.K. Wang broa
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146 N.K. Shammas and L.K. Wang remo
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150 N.K. Shammas and L.K. Wang 8. S
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152 N.K. Shammas and L.K. Wang 4.5.
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154 N.K. Shammas and L.K. Wang Tabl
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156 N.K. Shammas and L.K. Wang phys
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158 N.K. Shammas and L.K. Wang mono
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160 N.K. Shammas and L.K. Wang 4.8.
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196 N.K. Shammas and L.K. Wang PFR
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198 N.K. Shammas and L.K. Wang 16.
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5 Treatment of Industrial Effluents
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Treatment of Industrial Effluents,
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CONTENTS 6 Treatment of Food Indust
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Treatment of Food Industry Foods an
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272 J. Paul Chen et al. formation a
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278 J. Paul Chen et al. Most UF mem
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300 J. Paul Chen et al. 6.2.3. Tubu
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302 J. Paul Chen et al. Fig. 7.13.
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304 J. Paul Chen et al. a Feed b Me
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306 J. Paul Chen et al. l Product c
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308 J. Paul Chen et al. Feed Permea
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310 J. Paul Chen et al. From Table
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312 J. Paul Chen et al. To calculat
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Adsorption Desalination: A Novel Me
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434 J. Qin and K.A. Kekre 1. INTROD
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436 J. Qin and K.A. Kekre utilized
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438 J. Qin and K.A. Kekre 3.2. Desc
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440 J. Qin and K.A. Kekre Table 10.
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442 J. Qin and K.A. Kekre Fig. 10.4
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462 J. Qin and K.A. Kekre 7.2. Desc
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468 J. Qin and K.A. Kekre and anion
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470 J. Qin and K.A. Kekre become on
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472 J. Qin and K.A. Kekre COD ¼ Ch
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474 J. Qin and K.A. Kekre 25. Parso
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476 J. Qin and K.A. Kekre technique
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478 P. Kajitvichyanukul et al. 1. I
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12 Desalination of Seawater by Ther
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Desalination of Seawater by Thermal
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CONTENTS 13 Desalination of Seawate
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Desalination of Seawater by Reverse
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670 K. Mohanty and R. Ghosh 1. INTR
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680 K. Mohanty and R. Ghosh Cabassu
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684 K. Mohanty and R. Ghosh Membran
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696 K. Mohanty and R. Ghosh 70. Fut
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Acceptance testing, 384-385 ACF. Se
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Index 701 Challenge test solution d
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Index 703 Disinfection by-products
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Index 705 Hemodialysis, 2, 6, 281 H
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Index 707 Membrane bioreactor-rever
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Index 709 Microfiltration-reverse o
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Index 711 Physical cleaning, 322-32
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Index 713 Reynolds number, 676, 679
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Index 715 Thermal concentration, 25
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