GPS-X Technical Reference

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Attached Growth Models 240 Operational Parameters The operational parameters menu contains settings for the aeration and backwashing of the filter. The solids capture fraction is used to determine the mass of solids captured on the filter. These solids are then removed via the The backwash flow rate and backwash duration per 24-hr period are used (along with the calculated captured solids) to calculate a mass flow of backwashed solids. The backwashed flow is converted from an intermittent event to a continuous flow of equivalent mass solids. This allows for the model to be solved using the steady-state solver. Details of the aeration setup can be found in the More... button under in the Aeration Setup section. (Figure 7-16) Figure 7-16 - Simple BAF Model Operational Parameters Menu (More...) The remaining menus are equivalent to those found in the Trickling Filter Model. GPS-X Technical Reference
241 Attached-Growth Models ADVANCED BIOLOGICAL AERATED FILTER (BAF) MODEL The advanced biological aerated filter (BAF model is a robust, mechanistically-based model. It uses the same biological reactions found in the suspended-growth models discussed in Chapter 6. Conceptual Model The advanced BAF model consists of four major components: Hydraulics and Filter Operation, Filtration, Biological Reactions, and a Biofilm. They are described in the following sections. Hydraulics and Filter Operation The model needs to be able to describe the complex operation of the bio filter stages each consisting of one or more units in different operating modes. In the simplest implementation (number of units is 1); the model simulates the behavior of a single BAF unit. This unit can be in filtration, standby, backwash, or flush mode. In filtration, standby and flush mode, the filter is represented hydraulically as a tank consisting of a certain number of horizontal sections (6 in the default case). The actual filtration bed is preceded by a mixed tank without filter material to describe the dilution effects of the volume of water under the filter bed. A similar mixed tank is added to account for the liquid on top of the filter media. In backwash mode the horizontal sections of the filter are combined and converted to one mixed tank. The model assumes that during backwash the filter media is ideally mixed. The influent loading to the filter determines if the filter is in filtration, standby, backwash, or flush mode. In filtration and flushed modes, flow is entering the filter through the input stream and coming out through the output stream. In standby mode, there is no flow through the filter. In backwash mode, flow is entering the filter through the backwash input stream and coming out through the backwash output stream. A complex bio filter plant could be represented by the proper number of individual filter units placed on the drawing board to describe the changing conditions in the plant and forecast effluent quality. Due to the level of complexity within one filter unit and the typical number of units in the plant this approach is not feasible even with substantial computing capacity. Since the difference between individual units operating in the same mode is not drastic, a simplified operation mode provides a good approximation of operating and effluent conditions with substantially less overhead. 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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119 Suspended Growth Models Figure
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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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Page 275 and 276: 275 Digestion Models Figure 10-1 -
Page 277 and 278: 277 Digestion Models Seven yield co
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291 Digestion Models ADM1 State Var
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293 Digestion Models AEROBIC DIGEST
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295 Digestion Models Figure 10-15 -
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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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