GPS-X Technical Reference

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Influent Models 76 If the individual flow type is selected, there will be an intermittent (or batch) influent. Under the Flow sub-menu item individual, the user can specify the starting and ending time of the batch influent, and the volume of each truck (1 truck per day by default - the number of trucks per day is specified in the Influent Composition sub-menu). The total volume specified will be fed at an average rate over the total dumping time specified, that is there will be one influent flow spike. If the individual load type is selected, the loading is determined by the amount specified in the Individual Loads sub-menu. The stoichiometry is specified in the Influent Characterization menu and the number of trucks per day is specified in the Composition sub-menu (see Figure 5-15). INFLUENT APPENDICES Figure 5-15 - Batch Input Menu - Flow Data Model Inputs Model-Dependent State and Composite Variables When setting up your influent model, it is important that you realize what state variables are used in each biological model. The following sections outline the state variables used in the models in the different libraries. Of similar importance is an understanding of how the composite variables are calculated from the state variables. This is important because many of the influent models go backwards (i.e. from the composite variables to the state variables); hence, an understanding of these relationships will help if debugging is necessary. Influent Advisor has been developed specifically to help navigate the more complicated influent models. The following figures were developed to help with this understanding. The composite variable figures are copies of the figures presented in the composite variables chapter of this Reference; however, they are repeated here because of their importance to the influent model calculations. GPS-X Technical Reference
77 Influent Models CN and CNIP Libraries This section contains one table and two figures which are to help the user understand how GPS-X has calculated the CNLIB state variables, and what state variables should be calculated depending on which biological model you are using. Table 5-2 - State Variables Used in Each Biological Model Included in CNLIB and CNIPLIB State Variable Mantis ASM1 ASM3 si ss xi xs xu xsto xbh xba so snh snd xnd sno snn salk xii 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
Page 25 and 26: 25 Modelling Fundamentals Vesilin
Page 27 and 28: 27 GPS-X Objects CHAPTER 2 GPS-X Ob
Page 29 and 30: 29 GPS- X Objects The mass balance
Page 31 and 32: 31 GPS- X Objects Combining Equatio
Page 33 and 34: 33 GPS-X State Variable Libraries S
Page 35 and 36: 35 GPS-X State Variable Libraries C
Page 37 and 38: 37 GPS-X State Variable Libraries C
Page 39 and 40: 39 GPS-X Composite Variable Librari
Page 41 and 42: 41 GPS-X Composite Variable Calcula
Page 55 and 56: 55 Composite Variable Calculations
Page 61 and 62: 61 Influent Models CHAPTER 5 Influe
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Page 65 and 66: 65 Influent Models The three influe
Page 67 and 68: 67 Influent Models Total runoff (Q
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Page 71 and 72: 71 Influent Models CODFractions COD
Page 73 and 74: 73 Influent Models TSSCOD Figure 5-
Page 75: 75 Influent Models Figure 5-13 - CN
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Page 81 and 82: 81 Influent Models Figure 5-18 - CN
Page 83 and 84: 83 Influent Models INFLUENT OBJECTS
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Page 95 and 96: 95 Suspended Growth Models where: V
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Page 109 and 110: 109 Suspended Growth Models SUMMARY
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Page 113 and 114: 113 Suspended Growth Models General
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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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189 Suspended Growth Models Figure
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191 Suspended Growth Models Figure
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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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203 Suspended Growth Models Enterin
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209 Suspended Growth Models MODELLI
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211 Suspended Growth Models TEMPERA
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213 Suspended Growth Models Table 6
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215 Suspended Growth Models The PAC
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217 Suspended Growth Models CHAPTER
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219 Attached-Growth Models Each lay
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221 Attached-Growth Models Equation
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223 Attached-Growth Models The mode
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225 Attached-Growth Models The phys
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227 Attached-Growth Models Liquid F
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229 Attached-Growth Models This con
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231 Attached-Growth Models The next
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233 Attached-Growth Models The SBC
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235 Attached-Growth Models Based on
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237 Attached-Growth Models Operatio
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239 Attached-Growth Models Hydrauli
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241 Attached-Growth Models ADVANCED
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243 Attached-Growth Models Filtrati
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245 Attached-Growth Models Operatio
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247 Attached-Growth Models This for
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249 Attached-Growth Models HYBRID S
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251 Attached-Growth Models Figure 7
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253 Sedimentation and Flotation Mod
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267 Sand Filtration Models Floatati
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269 Sand Filtration Models The back
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271 Sand Filtration Models The mass
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273 Sand Filtration Models Figure 9
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275 Digestion Models Figure 10-1 -
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277 Digestion Models Seven yield co
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279 Digestion Models Based on the a
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281 Digestion Models Combining the
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283 Digestion Models The Operationa
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285 Digestion Models Kinetic and St
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287 Digestion Models The rest of th
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291 Digestion Models ADM1 State Var
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293 Digestion Models AEROBIC DIGEST
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297 Other Models CHAPTER 11 Other M
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299 Others Models High volume for p
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301 Others Models The sludge pretre
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303 Others Models With a large over
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305 Others Models Dosage Controller
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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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