Multiphysics Modelling of Fluid-Particulate Systems provides an explanation of how to model fluid-particulate systems using Eulerian and Lagrangian methods. The computational cost and relative merits of the different methods are compared, with recommendations on where and how to apply them provided. The science underlying the fluid‐particulate phenomena involves computational fluid dynamics (for liquids and gases), computational particle dynamics (solids), and mass and heat transfer. In order to simulate these systems, it is essential to model the interactions between phases and the fluids and particles themselves. This book details instructions for several numerical methods of dealing with this complex problem.
This book is essential reading for researchers from all backgrounds interested in multiphase flows or fluid-solid modeling, as well as engineers working on related problems in chemical engineering, food science, process engineering, geophysics or metallurgical processing.
1. Introduction - p. xi 2. Part I: Computational Fluid Dynamics: Discrete Element Modeling of Fluidized Beds - p. xvi 3. 1: Introduction: discrete element modeling-computational fluid dynamics of fluidized beds - p. xvi 4. 2: Methodology: computational fluid dynamics-discrete element modeling of fluidized beds - p. 22 5. 3: Validation case study: bubbling in the fluidized bed - p. 49 6. 4: Validation case study: sound waves in a fluidized medium - p. 74 7. Part II: Large (non-)spherical particle modelling in the context of fluid filtration applications (resolved eulerian-lagrangian) - p. 105 8. 5: Introduction: Large, (non-)spherical particle modeling in the context of fluid filtration applications - p. 105 9. 6: Methodology: large (non)spherical particle modeling in the context of fluid filtration applications - p. 113 10. Abstract - p. 113 11. 6.1. Fundamentals and modeling task - p. 115 12. 6.2. Basic concepts of the large Lagrangian dirt particle and deposition model - p. 124 13. 6.3. The (non)spherical dirt particle deposition solvers - p. 127 14. 6.4. Adaptive time-stepping for explicit Euler temporal discretization of spherical and nonspherical particle speed-up - p. 200 15. 6.5. Extension modules: electrostatic module and bacteria module - p. 229 16. 6.6. Workflow, C++ program structure, and how to use the solver - p. 232 17. 7: Validation: experimental and semianalytical - p. 247 18. 8: Application and results: filter fiber engineering - p. 272 19. 9: Conclusion and vision - p. 279 20. Part III: Modeling Shocks through Multiphase Media with Smoothed Particle Hydrodynamics - p. 282 21. 10: Introduction: smoothed particle hydrodynamics modeling of shocks - p. 282 22. 11: Methodology: smoothed particle hydrodynamics modeling of shocks - p. 292 23. 12: Validation: smoothed particle hydrodynamics modeling of shocks - p. 315 24. 13: Conclusion: smoothed particle hydrodynamics modeling of shocks - p. 353 25. Index - p. 356
Multiphysics Modelling of Fluid-Particulate Systems provides an explanation of how to model fluid-particulate systems using Eulerian and Lagrangian methods. The computational cost and relative merits of the different methods are compared, with recommendations on where and how to apply them provided. The science underlying the fluid‐particulate phenomena involves computational fluid dynamics (for liquids and gases), computational particle dynamics (solids), and mass and heat transfer. In order to simulate these systems, it is essential to model the interactions between phases and the fluids and particles themselves. This book details instructions for several numerical methods of dealing with this complex problem.
This book is essential reading for researchers from all backgrounds interested in multiphase flows or fluid-solid modeling, as well as engineers working on related problems in chemical engineering, food science, process engineering, geophysics or metallurgical processing.
1. Introduction - p. xi 2. Part I: Computational Fluid Dynamics: Discrete Element Modeling of Fluidized Beds - p. xvi 3. 1: Introduction: discrete element modeling-computational fluid dynamics of fluidized beds - p. xvi 4. 2: Methodology: computational fluid dynamics-discrete element modeling of fluidized beds - p. 22 5. 3: Validation case study: bubbling in the fluidized bed - p. 49 6. 4: Validation case study: sound waves in a fluidized medium - p. 74 7. Part II: Large (non-)spherical particle modelling in the context of fluid filtration applications (resolved eulerian-lagrangian) - p. 105 8. 5: Introduction: Large, (non-)spherical particle modeling in the context of fluid filtration applications - p. 105 9. 6: Methodology: large (non)spherical particle modeling in the context of fluid filtration applications - p. 113 10. Abstract - p. 113 11. 6.1. Fundamentals and modeling task - p. 115 12. 6.2. Basic concepts of the large Lagrangian dirt particle and deposition model - p. 124 13. 6.3. The (non)spherical dirt particle deposition solvers - p. 127 14. 6.4. Adaptive time-stepping for explicit Euler temporal discretization of spherical and nonspherical particle speed-up - p. 200 15. 6.5. Extension modules: electrostatic module and bacteria module - p. 229 16. 6.6. Workflow, C++ program structure, and how to use the solver - p. 232 17. 7: Validation: experimental and semianalytical - p. 247 18. 8: Application and results: filter fiber engineering - p. 272 19. 9: Conclusion and vision - p. 279 20. Part III: Modeling Shocks through Multiphase Media with Smoothed Particle Hydrodynamics - p. 282 21. 10: Introduction: smoothed particle hydrodynamics modeling of shocks - p. 282 22. 11: Methodology: smoothed particle hydrodynamics modeling of shocks - p. 292 23. 12: Validation: smoothed particle hydrodynamics modeling of shocks - p. 315 24. 13: Conclusion: smoothed particle hydrodynamics modeling of shocks - p. 353 25. Index - p. 356
