You are previewing Applied Computational Fluid Dynamics Techniques: An Introduction Based on Finite Element Methods, 2nd Edition.
O'Reilly logo
Applied Computational Fluid Dynamics Techniques: An Introduction Based on Finite Element Methods, 2nd Edition

Book Description

Computational fluid dynamics (CFD) is concerned with the efficient numerical solution of the partial differential equations that describe fluid dynamics. CFD techniques are commonly used in the many areas of engineering where fluid behavior is an important factor. Traditional fields of application include aerospace and automotive design, and more recently, bioengineering and consumer and medical electronics. With Applied Computational Fluid Dynamics Techniques, 2nd edition, Rainald Löhner introduces the reader to the techniques required to achieve efficient CFD solvers, forming a bridge between basic theoretical and algorithmic aspects of the finite element method and its use in an industrial context where methods have to be both as simple but also as robust as possible.

This heavily revised second edition takes a practice-oriented approach with a strong emphasis on efficiency, and offers important new and updated material on;

  • Overlapping and embedded grid methods

  • Treatment of free surfaces

  • Grid generation

  • Optimal use of supercomputing hardware

  • Optimal shape and process design

Applied Computational Fluid Dynamics Techniques, 2nd edition is a vital resource for engineers, researchers and designers working on CFD, aero and hydrodynamics simulations and bioengineering. Its unique practical approach will also appeal to graduate students of fluid mechanics and aero and hydrodynamics as well as biofluidics.

Table of Contents

  1. Cover Page
  2. Title Page
  3. Copyright
  4. Contents
  5. Foreword
  6. ACKNOWLEDGEMENTS
  7. 1 INTRODUCTION AND GENERAL CONSIDERATIONS
    1. 1.1. The CFD code
    2. 1.2. Porting research codes to an industrial context
    3. 1.3. Scope of the book
  8. 2 DATA STRUCTURES AND ALGORITHMS
    1. 2.1. Representation of a grid
    2. 2.2. Derived data structures for static data
    3. 2.3. Derived data structures for dynamic data
    4. 2.4. Sorting and searching
    5. 2.5. Proximity in space
    6. 2.6. Nearest-neighbours and graphs
    7. 2.7. Distance to surface
  9. 3 GRID GENERATION
    1. 3.1. Description of the domain to be gridded
    2. 3.2. Variation of element size and shape
    3. 3.3. Element type
    4. 3.4. Automatic grid generation methods
    5. 3.5. Other grid generation methods
    6. 3.6. The advancing front technique
    7. 3.7. Delaunay triangulation
    8. 3.8. Grid improvement
    9. 3.9. Optimal space-filling tetrahedra
    10. 3.10. Grids with uniform cores
    11. 3.11. Volume-to-surface meshing
    12. 3.12. Navier–Stokes gridding techniques
    13. 3.13. Filling space with points/arbitrary objects
    14. 3.14. Applications
  10. 4 APPROXIMATION THEORY
    1. 4.1. The basic problem
    2. 4.2. Choice of trial functions
    3. 4.3. General properties of shape functions
    4. 4.4. Weighted residual methods with local functions
    5. 4.5. Accuracy and effort
    6. 4.6. Grid estimates
  11. 5 APPROXIMATION OF OPERATORS
    1. 5.1. Taxonomy of methods
    2. 5.2. The Poisson operator
    3. 5.3. Recovery of derivatives
  12. 6 DISCRETIZATION IN TIME
    1. 6.1. Explicit schemes
    2. 6.2. Implicit schemes
    3. 6.3. A word of caution
  13. 7 SOLUTION OF LARGE SYSTEMS OF EQUATIONS
    1. 7.1. Direct solvers
    2. 7.2. Iterative solvers
    3. 7.3. Multigrid methods
  14. 8 SIMPLE EULER/NAVIER–STOKES SOLVERS
    1. 8.1. Galerkin approximation
    2. 8.2. Lax–Wendroff (Taylor–Galerkin)
    3. 8.3. Solving for the consistent mass matrix
    4. 8.4. Artificial viscosities
    5. 8.5. Boundary conditions
    6. 8.6. Viscous fluxes
  15. 9 FLUX-CORRECTED TRANSPORT SCHEMES
    1. 9.1. Algorithmic implementation
    2. 9.2. Steepening
    3. 9.3. FCT for Taylor–Galerkin schemes
    4. 9.4. Iterative limiting
    5. 9.5. Limiting for systems of equations
    6. 9.6. Examples
    7. 9.7. Summary
  16. 10 EDGE-BASED COMPRESSIBLE FLOW SOLVERS
    1. 10.1. The Laplacian operator
    2. 10.2. First derivatives: first form
    3. 10.3. First derivatives: second form
    4. 10.4. Edge-based schemes for advection-dominated PDEs
  17. 11 INCOMPRESSIBLE FLOW SOLVERS
    1. 11.1. The advection operator
    2. 11.2. The divergence operator
    3. 11.3. Artificial compressibility
    4. 11.4. Temporal discretization: projection schemes
    5. 11.5. Temporal discretization: implicit schemes
    6. 11.6. Temporal discretization of higher order
    7. 11.7. Acceleration to the steady state
    8. 11.8. Projective prediction of pressure increments
    9. 11.9. Examples
  18. 12 MESH MOVEMENT
    1. 12.1. The ALE frame of reference
    2. 12.2. Geometric conservation law
    3. 12.3. Mesh movement algorithms
    4. 12.4. Region of moving elements
    5. 12.5. PDE-based distance functions
    6. 12.6. Penalization of deformed elements
    7. 12.7. Special movement techniques for RANS grids
    8. 12.8. Rotating parts/domains
    9. 12.9. Applications
  19. 13 INTERPOLATION
    1. 13.1. Basic interpolation algorithm
    2. 13.2. Fastest 1-time algorithm: brute force
    3. 13.3. Fastest N -time algorithm: octree search
    4. 13.4. Fastest known vicinity algorithm: neighbour-to-neighbour
    5. 13.5. Fastest grid-to-grid algorithm: advancing-front vicinity
    6. 13.6. Conservative interpolation
    7. 13.7. Surface-grid-to-surface-grid interpolation
    8. 13.8. Particle–grid interpolation
  20. 14 ADAPTIVE MESH REFINEMENT
    1. 14.1. Optimal-mesh criteria
    2. 14.2. Error indicators/estimators
    3. 14.3. Refinement strategies
    4. 14.4. Tutorial: h-refinement with tetrahedra
    5. 14.5. Examples
  21. 15 EFFICIENT USE OF COMPUTER HARDWARE
    1. 15.1. Reduction of cache-misses
    2. 15.2. Vector machines
    3. 15.3. Parallel machines: general considerations
    4. 15.4. Shared-memory parallel machines
    5. 15.5. SIMD machines
    6. 15.6. MIMD machines
    7. 15.7. The effect of Moore's law on parallel computing
  22. 16 SPACE-MARCHING AND DEACTIVATION
    1. 16.1. Space-marching
    2. 16.2. Deactivation
  23. 17 OVERLAPPING GRIDS
    1. 17.1. Interpolation criteria
    2. 17.2. External boundaries and domains
    3. 17.3. Interpolation: initialization
    4. 17.4. Treatment of domains that are partially outside
    5. 17.5. Removal of inactive regions
    6. 17.6. Incremental interpolation
    7. 17.7. Changes to the flow solver
    8. 17.8. Examples
  24. 18 EMBEDDED AND IMMERSED GRID TECHNIQUES
    1. 18.1. Kinetic treatment of embedded or immersed objects
    2. 18.2. Kinematic treatment of embedded surfaces
    3. 18.3. Deactivation of interior regions
    4. 18.4. Extrapolation of the solution
    5. 18.5. Adaptive mesh refinement
    6. 18.6. Load/flux transfer
    7. 18.7. Treatment of gaps or cracks
    8. 18.8. Direct link to particles
    9. 18.9. Examples
  25. 19 TREATMENT OF FREE SURFACES
    1. 19.1. Interface fitting methods
    2. 19.2. Interface capturing methods
  26. 20 OPTIMAL SHAPE AND PROCESS DESIGN
    1. 20.1. The general optimization problem
    2. 20.2. Optimization techniques
    3. 20.3. Adjoint solvers
    4. 20.4. Geometric constraints
    5. 20.5. Approximate gradients
    6. 20.6. Multipoint optimization
    7. 20.7. Representation of surface changes
    8. 20.8. Hierarchical design procedures
    9. 20.9. Topological optimization via porosities
    10. 20.10. Examples
  27. REFERENCES
  28. INDEX