| Introduction | p. 1 |
| Computational Fluid Dynamics | p. 1 |
| Levels of Approximation: General | p. 2 |
| Statement of the Scale Separation Problem | p. 3 |
| Usual Levels of Approximation | p. 4 |
| Large-Eddy Simulation | p. 8 |
| Formal Introduction to Scale Separation: Band-Pass Filtering | p. 11 |
| Definition and Properties of the Filter in the Homogeneous Case | p. 11 |
| Definition | p. 11 |
| Fundamental Properties | p. 13 |
| Characterization of Different Approximations | p. 14 |
| Differential Filters | p. 16 |
| Three Classical Filters for Large-Eddy Simulation | p. 17 |
| Differential Interpretation of the Filters | p. 22 |
| Spatial Filtering: Extension to the Inhomogeneous Case | p. 27 |
| General | p. 27 |
| Non-uniform Filtering Over an Arbitrary Domain | p. 28 |
| Time Filtering: A Few Properties | p. 38 |
| Application to Navier-Stokes Equations | p. 39 |
| Navier-Stokes Equations | p. 40 |
| Formulation in Physical Space | p. 40 |
| Formulation in General Coordinates | p. 40 |
| Formulation in Spectral Space | p. 41 |
| Filtered Navier-Stokes Equations in Cartesian Coordinates (Homogeneous Case) | p. 42 |
| Formulation in Physical Space | p. 42 |
| Formulation in Spectral Space | p. 43 |
| Decomposition of the Non-linear Term. Associated Equations for the Conventional Approach | p. 43 |
| Leonard's Decomposition | p. 43 |
| Germano Consistent Decomposition | p. 54 |
| Germano Identity | p. 56 |
| Invariance Properties | p. 59 |
| Realizability Conditions | p. 64 |
| Extension to the Inhomogeneous Case for the Conventional Approach | p. 66 |
| Second-Order Commuting Filter | p. 67 |
| High-Order Commuting Filters | p. 68 |
| Filtered Navier-Stokes Equations in General Coordinates | p. 69 |
| Basic Form of the Filtered Equations | p. 69 |
| Simplified Form of the Equations - Non-linear Terms Decomposition | p. 69 |
| Closure Problem | p. 70 |
| Statement of the Problem | p. 70 |
| Postulates | p. 71 |
| Functional and Structural Modeling | p. 72 |
| Functional Modeling (Isotropic Case) | p. 75 |
| Phenomenology of Inter-Scale Interactions | p. 75 |
| Local Isotropy Assumption: Consequences | p. 76 |
| Interactions Between Resolved and Subgrid Scales | p. 77 |
| A View in Physical Space | p. 86 |
| Summary | p. 88 |
| Basic Functional Modeling Hypothesis | p. 88 |
| Modeling of the Forward Energy Cascade Process | p. 89 |
| Spectral Models | p. 89 |
| Physical Space Models | p. 93 |
| Improvement of Models in the Physical Space | p. 115 |
| Implicit Diffusion: The MILES Concept | p. 140 |
| Modeling the Backward Energy Cascade Process | p. 147 |
| Preliminary Remarks | p. 147 |
| Deterministic Statistical Models | p. 148 |
| Stochastic Models | p. 153 |
| Functional Modeling: Extension to Anisotropic Cases | p. 163 |
| Statement of the Problem | p. 163 |
| Application of Anisotropic Filter to Isotropic Flow | p. 163 |
| Scalar Models | p. 164 |
| Tensorial Models | p. 167 |
| Application of an Isotropic Filter to an Anisotropic Flow | p. 168 |
| Phenomenology of Inter-Scale Interactions | p. 169 |
| Anisotropic Models | p. 174 |
| Structural Modeling | p. 183 |
| Introduction and Motivations | p. 183 |
| Formal Series Expansions | p. 184 |
| Models Based on Approximate Deconvolution | p. 184 |
| Nonlinear Models | p. 194 |
| Homogenization Technique: Perrier and Pironneau Models | p. 199 |
| Scale Similarity Hypotheses and Models Using Them | p. 201 |
| Scale Similarity Hypotheses | p. 201 |
| Scale Similarity Models | p. 203 |
| A Bridge Between Scale Similarity and Approximate Deconvolution Models. Generalized Similarity Models | p. 206 |
| Mixed Modeling | p. 207 |
| Motivations | p. 207 |
| Examples of Mixed Models | p. 209 |
| Differential Subgrid Stress Models | p. 213 |
| Deardorff Model | p. 213 |
| Link with the Subgrid Viscosity Models | p. 214 |
| Deterministic Models of the Subgrid Structures | p. 215 |
| General | p. 215 |
| S3/S2 Alignment Model | p. 216 |
| S3/¿ Alignment Model | p. 216 |
| Kinematic Model | p. 216 |
| Explicit Evaluation of Subgrid Scales | p. 217 |
| Fractal Interpolation Procedure | p. 219 |
| Chaotic Map Model | p. 220 |
| Kinematic-Simulation-Based Reconstruction | p. 223 |
| Subgrid Scale Estimation Procedure | p. 224 |
| Multilevel Simulations | p. 225 |
| Direct Identification of Subgrid Terms | p. 233 |
| Linear-Stochastic-Estimation-Based Model | p. 234 |
| Neural-Network-Based Model | p. 235 |
| Implicit Structural Models | p. 236 |
| Local Average Method | p. 237 |
| Scale Residual Model | p. 238 |
| Numerical Solution: Interpretation and Problems | p. 241 |
| Dynamic Interpretation of the Large-Eddy Simulation | p. 241 |
| Static and Dynamic Interpretations: Effective Filter | p. 241 |
| Theoretical Analysis of the Turbulence Generated by Large-Eddy Simulation | p. 243 |
| Ties Between the Filter and Computational Grid. Pre-filtering | p. 248 |
| Numerical Errors and Subgrid Terms | p. 250 |
| Ghosal's General Analysis | p. 250 |
| Remarks on the Use of Artificial Dissipations | p. 255 |
| Remarks Concerning the Time Integration Method | p. 258 |
| Analysis and Validation of Large-Eddy Simulation Data | p. 261 |
| Statement of the Problem | p. 261 |
| Type of Information Contained in a Large-Eddy Simulation | p. 261 |
| Validation Methods | p. 262 |
| Statistical Equivalency Classes of Realizations | p. 263 |
| Ideal LES and Optimal LES | p. 266 |
| Correction Techniques | p. 267 |
| Filtering the Reference Data | p. 268 |
| Evaluation of Subgrid Scale Contribution | p. 268 |
| Practical Experience | p. 269 |
| Boundary Conditions | p. 271 |
| General Problem | p. 271 |
| Mathematical Aspects | p. 271 |
| Physical Aspects | p. 272 |
| Solid Walls | p. 274 |
| Statement of the Problem | p. 274 |
| A Few Wall Models | p. 281 |
| Case of the Inflow Conditions | p. 297 |
| Required Conditions | p. 297 |
| Inflow Condition Generation Techniques | p. 298 |
| Coupling Large-Eddy Simulation with Multiresolution/Multidomain Techniques | p. 309 |
| Statement of the Problem | p. 309 |
| Methods with Full Overlap | p. 311 |
| One-Way Coupling Algorithm | p. 312 |
| Two-Way Coupling Algorithm | p. 312 |
| FAS-like Multilevel Method | p. 313 |
| Kravchenko et al. Method | p. 316 |
| Methods Without Full Overlap | p. 316 |
| Hybrid RANS/LES Approaches | p. 319 |
| Motivations and Presentation | p. 319 |
| Zonal Decomposition | p. 320 |
| Statement of the Problem | p. 320 |
| Sharp Transition | p. 321 |
| Smooth Transition | p. 323 |
| Zonal RANS/LES Approach as Wall Model | p. 324 |
| Nonlinear Disturbance Equations | p. 325 |
| Universal Modeling | p. 327 |
| Germano's Hybrid Model | p. 327 |
| Speziale's Rescaling Method and Simplifications | p. 328 |
| Arunajatesan's Modified Two-Equation Model | p. 329 |
| Bush-Mani Limiters | p. 330 |
| Implementation | p. 331 |
| Filter Identification. Computing the Cutoff Length | p. 331 |
| Explicit Discrete Filters | p. 334 |
| Uniform One-Dimensional Grid Case | p. 334 |
| Extension to the Multidimensional Case | p. 337 |
| Extension to the General Case. Convolution Filters | p. 337 |
| High-Order Elliptic Filters | p. 338 |
| Implementation of the Structure Function Model | p. 338 |
| Examples of Applications | p. 341 |
| Homogeneous Turbulence | p. 341 |
| Isotropic Homogeneous Turbulence | p. 341 |
| Anisotropic Homogeneous Turbulence | p. 342 |
| Flows Possessing a Direction of Inhomogeneity | p. 344 |
| Time-Evolving Plane Channel | p. 344 |
| Other Flows | p. 348 |
| Flows Having at Most One Direction of Homogeneity | p. 348 |
| Round Jet | p. 349 |
| Backward Facing Step | p. 356 |
| Square-Section Cylinder | p. 360 |
| Other Examples | p. 361 |
| Industrial Applications | p. 362 |
| Large-Eddy Simulation for Nuclear Power Plants | p. 362 |
| Flow in a Mixed-Flow Pump | p. 362 |
| Flow Around a Landing Gear Configuration | p. 367 |
| Flow Around a Full Scale Car | p. 368 |
| Lessons | p. 370 |
| General Lessons | p. 370 |
| Subgrid Model Efficiency | p. 371 |
| Wall Model Efficiency | p. 374 |
| Mesh Generation for "Building Blocks" Flows | p. 375 |
| Statistical and Spectral Analysis of Turbulence | p. 379 |
| Turbulence Properties | p. 379 |
| Foundations of the Statistical Analysis of Turbulence | p. 379 |
| Motivations | p. 379 |
| Statistical Average: Definition and Properties | p. 380 |
| Ergodicity Principle | p. 380 |
| Decomposition of a Turbulent Field | p. 382 |
| Isotropic Homogeneous Turbulence | p. 383 |
| Introduction to Spectral Analysis of the Isotropic Turbulent Fields | p. 383 |
| Definitions | p. 383 |
| Modal Interactions | p. 385 |
| Spectral Equations | p. 386 |
| Characteristic Scales of Turbulence | p. 388 |
| Spectral Dynamics of Isotropic Homogeneous Turbulence | p. 389 |
| Energy Cascade and Local Isotropy | p. 389 |
| Equilibrium Spectrum | p. 389 |
| EDQNM Modeling | p. 391 |
| Isotropic EDQNM Model | p. 391 |
| Cambon's Anisotropic EDQNM Model | p. 393 |
| Bibliography | p. 397 |
| Index | p. 423 |
| Table of Contents provided by Publisher. All Rights Reserved. |