GPS-X Technical Reference

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Sedimentation and Flotation Models 256 The solids flux due to bulk movement of the liquid is a straightforward calculation based on the solids concentration times the liquid bulk velocity, which is up or down depending on its position relative to the feed layer. The solids flux due to sedimentation is specified by a double exponential settling function, applicable to both hindered sedimentation and flocculant sedimentation conditions. The settling function, described by Takács et al. (1991), is given by: Equation 8.1 where: v sj v max rhin rfloc X j o = the settling velocity in layer j (m/d) = the maximum Vesilind settling velocity (m/d) = hindered zone settling parameter (m 3 /gTSS) = flocculant zone settling parameter (m 3 /gTSS) = X j – X min, where X min is the minimum attainable suspended solids concentration, X j is the suspended solids concentration in layer j The minimum attainable solids concentration in a layer, X min, is calculated as a fraction (non-settleable fraction or fns) of the influent solids concentration to the settler: Equation 8.2 It is subject to a maximum value specified by the user; the maximum non-settleable solids or X minmax. The settling velocity is lower bounded to zero, so that if the user specifies parameter values that would result in settling velocities becoming negative, a warning message is printed in the simulation Log window. The settling velocity is also subject to a maximum value specified by the user; the maximum settling velocity or v bnd. GPS-X Technical Reference
257 Sedimentation and Flotation Models The settling function is shown in Figure 8-3. The four regions depicted in this figure are explained as follows: I) the settling velocity equals zero, as the solids attain the minimum attainable concentration; II) the settling velocity is dominated by the flocculating nature of the particles; thus the settling velocity is sensitive to the rfloc parameter; III) settling velocity has become independent of solids concentration (particles have reached their maximum size; and IV) settling velocity is affected by hindering and becomes dependent on the rhin parameter (the model reduces to the Vesilind equation). Simple Models Figure 8-3 – Settling Velocity vs. Concentration In the simple1d sedimentation model, the only numerically integrated variable is the suspended solids concentration. This model can be used when biological reactions in the settler can be ignored. The concentrations of particulate state variables in the influent to the settler (heterotrophic organisms, etc.) are stored as fractions of the total suspended solids concentration entering the settler. Once the model completes the numerical integration of the suspended solids in the settler layers (at the end of each numerical integration time step), the concentrations of particulate state variables in the effluent, underflow (RAS), and pumped flow (WAS) are restored using those fractions. The concentrations of soluble state variables are not changed in the simple1d model. GPS-X Technical Reference
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GPS-X Technical Reference GPS-X Ver
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Table of Contents iii Table of Cont
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v Table of Contents Sedimentation M
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vii Table of Contents Real Time Clo
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ix Table of Contents Figure 6-6 - P
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xi Table of Contents Figure 10-8 -
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xiii Table of Contents Figure 15-6
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xv Table of Contents Table 6-2 - Mo
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17 Modelling Fundamentals Experimen
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19 Modelling Fundamentals The proce
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21 Modelling Fundamentals Overview
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23 Modelling Fundamentals Primary a
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25 Modelling Fundamentals Vesilin
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27 GPS-X Objects CHAPTER 2 GPS-X Ob
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29 GPS- X Objects The mass balance
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31 GPS- X Objects Combining Equatio
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33 GPS-X State Variable Libraries S
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35 GPS-X State Variable Libraries C
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37 GPS-X State Variable Libraries C
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39 GPS-X Composite Variable Librari
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41 GPS-X Composite Variable Calcula
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55 Composite Variable Calculations
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61 Influent Models CHAPTER 5 Influe
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63 Influent Models Figure 5-3 - Inf
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65 Influent Models The three influe
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67 Influent Models Total runoff (Q
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69 Influent Models These inputs are
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71 Influent Models CODFractions COD
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73 Influent Models TSSCOD Figure 5-
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75 Influent Models Figure 5-13 - CN
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77 Influent Models CN and CNIP Libr
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83 Influent Models INFLUENT OBJECTS
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85 Influent Models Figure 5-22 - In
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87 Influent Models Chemical Dosage
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89 Influent Models Figure 5-29 - Ac
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91 Influent Models Figure 5-33 - Se
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93 Influent Models Figure 5-36 - Se
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95 Suspended Growth Models where: V
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97 Suspended Growth Models The baro
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99 Suspended Growth Models Oxygen M
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101 Suspended Growth Models In the
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103 Suspended Growth Models The SOT
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105 Suspended Growth Models Standar
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107 Suspended Growth Models The reg
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109 Suspended Growth Models SUMMARY
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111 Suspended Growth Models Figure
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113 Suspended Growth Models General
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115 Suspended Growth Models Number
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117 Suspended Growth Models Elevati
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121 Suspended Growth Models AERATIO
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123 Suspended Growth Models The ent
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125 Suspended Growth Models The org
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127 Suspended Growth Models Process
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129 Suspended Growth Models It i
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131 Suspended Growth Models Nitroge
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133 Suspended Growth Models Include
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135 Suspended Growth Models
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137 Suspended Growth Models Althoug
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139 Suspended Growth Models Particu
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141 Suspended Growth Models 9. Grow
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143 Suspended Growth Models 21. Sto
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145 Suspended Growth Models 33. Gro
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147 Suspended Growth Models To mode
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149 Suspended Growth Models Algebra
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151 Suspended Growth Models The sto
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153 Suspended Growth Models Decay o
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155 Suspended Growth Models SUGGEST
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157 Suspended Growth Models Special
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159 Suspended Growth Models Table 6
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161 Suspended Growth Models The GPS
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163 Suspended Growth Models where:
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165 Suspended Growth Models The max
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167 Suspended Growth Models If yo
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169 Suspended Growth Models ANAEROB
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171 Suspended Growth Models Simple
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173 Suspended Growth Models With th
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175 Suspended Growth Models Manual
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177 Suspended Growth Models Equatio
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179 Suspended Growth Models The met
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181 Suspended Growth Models Pond Mo
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183 Suspended Growth Models Special
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185 Suspended Growth Models Se
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187 Suspended Growth Models aerated
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193 Suspended Growth Models Calcula
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195 Suspended Growth Models The vap
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197 Suspended Growth Models Oxygen
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199 Suspended Growth Models Estimat
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201 Suspended Growth Models Estimat
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203 Suspended Growth Models Enterin
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Page 219 and 220: 219 Attached-Growth Models Each lay
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Page 251 and 252: 251 Attached-Growth Models Figure 7
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Page 267 and 268: 267 Sand Filtration Models Floatati
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Page 271 and 272: 271 Sand Filtration Models The mass
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Page 275 and 276: 275 Digestion Models Figure 10-1 -
Page 277 and 278: 277 Digestion Models Seven yield co
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Page 297 and 298: 297 Other Models CHAPTER 11 Other M
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307 Others Models The set of above
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309 Others Models There are three p
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311 Others Models DISINFECTION UNIT
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313 Others Models DEWATERING Four m
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315 Others Models The optimal polym
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317 Others Models DISC AND BELT MIC
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319 Others Models Figure 11-12 - Pl
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321 Others Models Physical Setup Fo
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323 Others Models Exponential const
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325 Others Models BLACK BOX The Bla
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327 Tools Object Figure 11-19 - Spe
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329 Tools Object Figure 11-21 - Inp
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331 Tools Object Typical Model Outp
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333 Tools Object The variable speed
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335 Tools Object SLUDGE EFFLUENT BU
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337 Tools Object PH TOOL Take a sam
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339 Tools Object These concentratio
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341 Tools Object LOW-PASS FILTERING
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343 Tools Object Control Variable P
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345 Tools Object The individual mod
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347 Tools Object PID in Position Fo
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349 Tools Object The following para
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351 Tools Object The controller tun
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353 Tools Object When both the proc
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355 Tools Object TIMER CONTROL The
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357 Tools Object Controller - The c
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359 Tools Object (qcon is the crypt
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361 Operating Cost Models CHAPTER 1
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363 Operating Cost Models The energ
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365 Operating Cost Models OPERATING
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367 Operating Cost Models OPERATING
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369 Operating Cost Models CALIBRATI
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371 Operating Cost Models Category
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373 Optimizer If after the reflecti
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375 Optimizer In the objective func
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377 Optimizer Figure 14-2 - Optimiz
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379 Optimizer Figure 14-3 - Example
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381 Optimizer SUMMARY OF THE OPTIMI
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383 Optimizer Use specified standar
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385 Optimizer Level of significance
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387 Optimizer APPENDIX A: MAXIMUM L
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389 Optimizer In GPS-X the log-like
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391 Optimizer Note that the user ca
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393 Optimizer Gradient of the Objec
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395 Optimizer Hessian of the Object
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397 Optimizer For the maximum likel
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399 Optimizer Percentage Variation
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401 Optimizer GPS-X reports the F-v
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403 Optimizer The sum of squares ra
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405 Optimizer To check for violatio
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407 Optimizer If the sample autocor
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409 Optimizer APPENDIX C: NOMENCLAT
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411 Optimizer APPENDIX D: REFERENCE
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413 Miscellaneous CHAPTER 15 Miscel
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415 Miscellaneous As compared to th
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417 Miscellaneous A typical GPS-X o
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419 Miscellaneous RESIDUAL PLOTS Fo
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421 Miscellaneous Figure 15-6 - Res
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423 Miscellaneous REAL TIME CLOCK T
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425 Miscellaneous Figure 15-9 - Ste
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427 Miscellaneous Figure 15-11 - In
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429 Miscellaneous The smoothing fun
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431 Miscellaneous The Gear's Stiff
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Appendix A - Petersen Matrices A-1
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ASM2d in CNPLIB Appendix A - Peters
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15 Lysis of XBP 16 Lysis of XPP 17
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NewGeneral in CNPLIB Appendix A - P
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NewGeneral in CNPLIB Appendix A - P
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Component i Process Rates Appendix
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2 Appendix A - Prefermenter Peterse
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D-2 Appendix D - References Brockwe
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D-4 Appendix D - References Hur, D.
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D-6 Appendix D - References Reilly,
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D-8 Appendix D - References Wuhrman
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