GPS-X Technical Reference

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Other Models 308 The shape of the curve represented by the above equation is shown in Figure 11-5: Figure 11-5 – Curve Showing Relationship between the Soluble Components Concentration, and Require Metal Dose for Unit Soluble Component Removal The integration of curve in Figure 11-5 between the limits of Sin (concentration of soluble component in influent) and So (concentration of soluble component in effluent) results in the following expression. For a given metal dose and inlet concentration, the equation is solved to estimate the So, concentration of soluble component in effluent. Equation 11.7 Equation 11.8 where: P me = metal dose, gMe/m 3 S in = concentration of soluble component in influent, g/m 3 S o = concentration of soluble component in effluent, g/m 3 GPS-X Technical Reference
309 Others Models There are three parameters F max, F min and k a used in the model. The parameter F max may be interpreted as the amount of metal required to remove the said component at very low concentrations. It is general observation that the amount of metal required at lower concentration of soluble component is much higher than the metal amount required when the concentration of soluble component is higher. The parameter of F min, can be interpreted as the amount of metal required to remove the said component at high concentrations. The parameter of k a signifies the transition between the F min and F max. Higher values of k a will result in a very steep transition between the F min and F max, essentially improving the removal efficiencies. Conversely, lower values of k a will result in a mild transition and thus decreasing the removal efficiencies. It is important to highlight here regarding the fate of the removed soluble components. As, the flocculation process does not cause any mass loss, the removed soluble compounds are just converted into their particulate state. The si, scol and snd are just transformed to xi, xs and xns states respectively. It should be noted that the value of these parameters depends on the environmental conditions temperature, pH, mixing, and wastewater characteristics. Therefore, it is recommended that adequate calibration is performed to find the appropriate values for specific cases. GRIT CHAMBER The model associated with this object is a simple empirical model where grit production is directly proportional to the flow coming in the grit chamber. The amount of grit produced (in grams per m 3 of influent) is user specified. STRUVITE PRECIPITATION MODEL The struvite precipitation reactor model represents an up-flow granular bed reactor with recycle. The model uses a bed fluidization model to estimate the granular bed height and the solid concentration in the effluent stream. An internal recycle is provided to achieve bed fluidization velocity required by the user. A typical layout showing the application of struvite reactor is as shown in Figure 11-6. Some typical outputs from the struvite precipitation model are as shown in Figure 11-7and Figure 11-8. 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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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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255 Sedimentation and Flotation Mod
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Page 267 and 268: 267 Sand Filtration Models Floatati
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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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Page 313 and 314: 313 Others Models DEWATERING Four m
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Page 317 and 318: 317 Others Models DISC AND BELT MIC
Page 319 and 320: 319 Others Models Figure 11-12 - Pl
Page 321 and 322: 321 Others Models Physical Setup Fo
Page 323 and 324: 323 Others Models Exponential const
Page 325 and 326: 325 Others Models BLACK BOX The Bla
Page 327 and 328: 327 Tools Object Figure 11-19 - Spe
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Page 331 and 332: 331 Tools Object Typical Model Outp
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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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