Optimization and Computational Fluid Dynamics - Department of ...

More documents

Recommendations

Info

Contents xi 8 Multi-objective Optimization for Problems Involving Convective Heat Transfer .................................217 Marco Manzan, Enrico Nobile, Stefano Pieri and Francesco Pinto 8.1 Introduction.......................................... 218 8.2 LiteratureReview..................................... 219 8.3 ProblemStatement.................................... 222 8.3.1 GoverningEquations........................... 223 8.3.2 Fluid Dynamic Boundary Conditions . . . . . . . . . . . . . 224 8.3.3 Temperature Boundary Conditions . . . . . . . . . . . . . . . 225 8.4 NumericalMethods.................................... 228 8.4.1 FluidDynamicIterativeSolution ................ 228 8.4.2 ThermalFieldIterativeSolution................. 229 8.5 GeometryParametrization ............................. 231 8.5.1 WavyChannels................................ 231 8.5.2 CCModule ................................... 234 8.6 OptimizationMethods................................. 235 8.6.1 DesignofExperiment .......................... 238 8.7 OptimizationAlgorithms............................... 239 8.7.1 GeneticAlgorithm ............................. 242 8.7.2 Multi-objectiveApproaches .....................243 8.7.3 Multi-Criteria Decision Making (MCDM) . . . . . . . . . 246 8.7.4 OptimizationProcess...........................247 8.8 ResultsandDiscussion................................. 249 8.8.1 Linear Piecewise Optimization . . . . . . . . . . . . . . . . . . . 249 8.8.2 NURBSOptimization .......................... 250 8.8.3 Linear Piecewise versus NURBS . . . . . . . . . . . . . . . . . 255 8.8.4 Three-dimensionalAnalysis .....................256 8.8.5 CCModule ................................... 258 8.9 ConcludingRemarks................................... 262 References ................................................. 263 9 CFD-based Optimization for a Complete Industrial Process: Papermaking ....................................267 Jari Hämäläinen, Taija Hämäläinen, Elina Madetoja and Henri Ruotsalainen 9.1 Introduction.......................................... 267 9.2 Optimal Shape Design of the Tapered Header . . . . . . . . . . . . . 269 9.3 Optimal Control of the Fiber Orientation in the Slice Channel.............................................. 272 9.3.1 OnModelingFiberOrientation.................. 272 9.3.2 HOCS Fiber – A Trouble Shooting Tool . . . . . . . . . . 273 9.3.3 Depth-averaged Navier-Stokes Equations . . . . . . . . . . 274 9.3.4 Validation of the Depth-averaged Navier-Stokes Equations..................................... 276 9.4 Multi-objectiveOptimizationofPapermaking............. 278
xii Contents 9.4.1 Multi-objectiveOptimization.................... 279 9.4.2 Modeling and Optimizing the Complete PapermakingProcess........................... 281 9.4.3 NumericalExamples ........................... 284 9.5 Towards Decision Support Systems . . . . . . . . . . . . . . . . . . . . . . 286 9.6 Conclusions .......................................... 287 References ................................................. 288 Index ......................................................... 291
Page 1 and 2: Optimization and Computational Flui
Page 3 and 4: Editors: Prof. Dr.-Ing. Dominique T
Page 5 and 6: vi Preface Our first research proje
Page 7 and 8: viii Contents 2.4.1 GoverningEquati
Page 9: x Contents 6.2.3 Parameterization..
Page 13 and 14: xiv List of Contributors Gábor JAN
Page 15: Part I Generalities and methods
Page 18 and 19: 4 Dominique Thévenin 12 10 8 6 4 2
Page 20 and 21: 6 Dominique Thévenin Objective 10
Page 22 and 23: 8 Dominique Thévenin Objective 10
Page 24 and 25: 10 Dominique Thévenin Parameter 2
Page 26 and 27: 12 Dominique Thévenin three-dimens
Page 28 and 29: 14 Dominique Thévenin Let us come
Page 30 and 31: 16 Dominique Thévenin References 1
Page 32 and 33: 18 Gábor Janiga 2.1 Introduction D
Page 34 and 35: 20 Gábor Janiga y Tinlet = 293 K 0
Page 36 and 37: 22 Gábor Janiga y [mm] 25 20 15 10
Page 38 and 39: 24 Gábor Janiga Table 2.1 Number o
Page 40 and 41: 26 Gábor Janiga A dominates the in
Page 42 and 43: 28 Gábor Janiga be shown later, th
Page 44 and 45: 30 Gábor Janiga INPUT FILE Gambit
Page 46 and 47: 32 Gábor Janiga y [mm] 100 50 0 0
Page 48 and 49: 34 Gábor Janiga ∆T ∆P Position
Page 50 and 51: 36 Gábor Janiga ∆P [mPa] 2.2 2.0
Page 52 and 53: 38 Gábor Janiga Table 2.3 Speed-up
Page 54 and 55: 40 Gábor Janiga For all computatio
Page 56 and 57: 42 Gábor Janiga y [mm] 4 2 0 -1 0
Page 58 and 59: 44 Gábor Janiga Air mass flow-rate
Page 60 and 61:
46 Gábor Janiga Temperature variat
Page 62 and 63:
48 Gábor Janiga y [mm] 18 16 14 12
Page 64 and 65:
50 Gábor Janiga The modified k-ω
Page 66 and 67:
52 Gábor Janiga Error for Re∗ =
Page 68 and 69:
54 Gábor Janiga Error for Re∗ 20
Page 70 and 71:
56 Gábor Janiga References 1. Ali,
Page 72 and 73:
58 Gábor Janiga 43. Janiga, G., Th
Page 75 and 76:
Chapter 3 Mathematical Aspects of C
Page 77 and 78:
3 Mathematical Aspects of CFD-based
Page 79 and 80:
Page 81 and 82:
Page 83 and 84:
Page 85 and 86:
Page 87 and 88:
Page 89 and 90:
Page 91 and 92:
Page 93 and 94:
Chapter 4 Adjoint Methods for Shape
Page 95 and 96:
4 Adjoint Methods for Shape Optimiz
Page 97 and 98:
Page 99 and 100:
Page 101 and 102:
Page 103 and 104:
Page 105 and 106:
Page 107 and 108:
Page 109 and 110:
Page 111 and 112:
Page 113 and 114:
Page 115 and 116:
Page 117 and 118:
Page 119 and 120:
Page 121 and 122:
Page 123:
Part II Specific Applications of CF
Page 126 and 127:
112 Nicolas R. Gauger Nomenclature
Page 128 and 129:
114 Nicolas R. Gauger Fig. 5.1 Cost
Page 130 and 131:
116 Nicolas R. Gauger and the four
Page 132 and 133:
118 Nicolas R. Gauger CL := 1 � C
Page 134 and 135:
120 Nicolas R. Gauger the cost func
Page 136 and 137:
122 Nicolas R. Gauger Table 5.1 An
Page 138 and 139:
124 Nicolas R. Gauger The main adva
Page 140 and 141:
126 Nicolas R. Gauger Spalart-Allma
Page 142 and 143:
128 Nicolas R. Gauger (a) (b) Fig.
Page 144 and 145:
Page 146 and 147:
Page 148 and 149:
134 Nicolas R. Gauger Fig. 5.10 Plo
Page 150 and 151:
136 Nicolas R. Gauger drag, lift, s
Page 152 and 153:
138 Nicolas R. Gauger solution of t
Page 154 and 155:
140 Nicolas R. Gauger the presence
Page 156 and 157:
142 Nicolas R. Gauger Fig. 5.16 Con
Page 158 and 159:
144 Nicolas R. Gauger optimization
Page 161 and 162:
Chapter 6 Numerical Optimization fo
Page 163 and 164:
6 Numerical Optimization for Advanc
Page 165 and 166:
Page 167 and 168:
Page 169 and 170:
Page 171 and 172:
Page 173 and 174:
Page 175 and 176:
Page 177 and 178:
Page 179 and 180:
Page 181 and 182:
Page 183 and 184:
Page 185 and 186:
Page 187 and 188:
Page 189 and 190:
Page 191 and 192:
Page 193 and 194:
Page 195 and 196:
Page 197 and 198:
Page 199 and 200:
Page 201 and 202:
Page 203:
Page 206 and 207:
192 Laurent Dumas 7.1 Introducing A
Page 208 and 209:
194 Laurent Dumas C Fig. 7.2 Wake f
Page 210 and 211:
196 Laurent Dumas Table 7.1 Example
Page 212 and 213:
198 Laurent Dumas Fig. 7.5 Numerica
Page 214 and 215:
200 Laurent Dumas 7.3.1.1 Genetic A
Page 216 and 217:
202 Laurent Dumas START Random init
Page 218 and 219:
204 Laurent Dumas • if ˜ J(x ng
Page 220 and 221:
206 Laurent Dumas Table 7.3 Compari
Page 222 and 223:
208 Laurent Dumas Fig. 7.9 General
Page 224 and 225:
210 Laurent Dumas Table 7.4 Four ex
Page 226 and 227:
212 Laurent Dumas Fig. 7.13 Blades
Page 228 and 229:
214 Laurent Dumas Table 7.5 Converg
Page 231 and 232:
Chapter 8 Multi-objective Optimizat
Page 233 and 234:
8 Multi-objective Optimization in C
Page 235 and 236:
Page 237 and 238:
8 Multi-objective Optimizatio Fig.
Page 239 and 240:
Page 241 and 242:
Page 243 and 244:
Page 245 and 246:
Page 247 and 248:
Page 249 and 250:
Page 251 and 252:
Page 253 and 254:
Page 255 and 256:
Page 257 and 258:
Page 259 and 260:
Page 261 and 262:
Page 263 and 264:
Page 265 and 266:
Page 267 and 268:
Page 269 and 270:
Page 271 and 272:
Page 273 and 274:
Page 275 and 276:
Page 277 and 278:
Page 279 and 280:
Page 281 and 282:
Chapter 9 CFD-based Optimization fo
Page 283 and 284:
9 CFD-based optimization for paperm
Page 285 and 286:
Page 287 and 288:
Page 289 and 290:
Page 291 and 292:
Page 293 and 294:
Page 295 and 296:
Page 297 and 298:
Page 299 and 300:
Page 301 and 302:
Page 303:
Page 306 and 307:
292 Index heat exchanger, 222, 224,
show all

Optimization and Computational Fluid Dynamics - Department of ...

Create successful ePaper yourself

Delete template?

Save as template?