Gas-Particle and Granular Flow Systems
Coupled Numerical Methods and Applications
- 1st Edition - October 23, 2019
- Latest edition
- Authors: Nan Gui, Shengyao Jiang, Jiyuan Tu, Xingtuan Yang
- Language: English
- Paperback ISBN:9 7 8 - 0 - 1 2 - 8 1 6 3 9 8 - 6
- eBook ISBN:9 7 8 - 0 - 1 2 - 8 1 6 3 9 9 - 3
Gas-Particle and Granular Flow Systems: Coupled Numerical Methods and Applications breaks down complexities, details numerical methods (including basic theory, modeling and techn… Read more
Gas-Particle and Granular Flow Systems: Coupled Numerical Methods and Applications breaks down complexities, details numerical methods (including basic theory, modeling and techniques in programming), and provides researchers with an introduction and starting point to each of the disciplines involved. As the modeling of gas-particle and granular flow systems is an emerging interdisciplinary field of study involving mathematics, numerical methods, computational science, and mechanical, chemical and nuclear engineering, this book provides an ideal resource for new researchers who are often intimidated by the complexities of fluid-particle, particle-particle, and particle-wall interactions in many disciplines.
- Presents the most recent advances in modeling of gas-particle and granular flow systems
- Features detailed and multidisciplinary case studies at the conclusion of each chapter to underscore key concepts
- Discusses coupled methods of particle and granular flow systems theory and includes advanced modeling tools and numerical techniques
Chemical Engineers, Materials Scientists, and Chemists in research and industry comprise the primary audience. Secondary audience includes instructors and students taking related coursework at the graduate level
Chapter 1Particle and Pebble Flow-- An Introduction1.1 Introduction1.2 Category of particle and pebble flow1.2.1. By material1.2.1.1. Bubble-particle system1.2.1.2. Droplet-particle system1.2.1.3. Solid-particle system1.2.2. By concentration1.2.2.1. Dense flow1.2.2.2. Dilute flow1.2.3. By flow behaviour1.2.3.1. Rapid flow 1.2.3.2. Slow flow1.2.3.3. Quasi-stationary flow1.2.4. Pebble flow1.2.4.1. Extremely slow flow 1.2.4.2. Intermittent flow1.2.4.3. Consistent flow1.3 Numerical methods for continuum system1.3.1 Reynolds Averaged Navier-Stokes simulation1.3.2 Direct numerical simulation1.3.3 Large eddy simulation1.3.4 Mesoscale methods and lattice-Boltzmann Equation1.3.5 Other particle-based methods1.4 Numerical methods for particle and pebble system1.4.1 Deterministic .vs. stochastic model 1.4.2 Molecular dynamics simulation1.4.3 Discrete Element method1.4.4 DSMC methods1.4.5 Other methods1.5 Summary1.6 Review QuestionsChapter 2Discrete Particle Models and Extensions2.1 Introduction2.2 Soft-sphere approach2.2.1. Contact theories2.2.2. Basic mechanics2.2.3. Parameter dependence and calibration2.2.4. Energy dissipation2.2.5. Computational advantage and limitation2.3 Hard-sphere approach2.3.1. Collision dynamics2.3.2. Restitution coefficient2.3.3. Friction and non-friction2.3.4. Collision detection2.3.5. Energy dissipation2.3.6. Computational efficiency and shortage2.4 For non-spherical shapes2.4.1. Gluing technique2.4.2. Clumpy effects 2.4.3. Super geometry2.4.4. Cutting/Overlapping geometry2.4.5. SIPHPM model2.4.6. GHPM model2.4.7. EHPM-DEM model2.4.8. With wall roughness2.5 Heat transfer extension2.5.1. Conduction2.5.1.1 Particle-scale conduction2.5.1.2 Effective conduction2.5.2. Convection2.5.3. Radiation2.5.3.1 Correlations2.5.3.2 Averaged methods2.5.3.3 Direct simulation2.5.3.4 Particle-scale radiation2.5.3.5 Equivalent approach2.6 Other extensions2.6.1 Complex forces2.6.2 Large deformation2.6.3 Linkage and breakup2.7 Summary2.8 Review QuestionsChapter 3Coupled Methods3.1 Introduction3.1.1. Eulerian-Eulerian approach3.1.2. Eulerian-Lagrangian approach3.1.3. Inter-phase coupling3.1.4. Distribution function3.1.5. Interpolation function3.1.6. Reversive and conservative3.2 CFD-DEM coupled approach3.2.1. Basic strategy3.2.2. Numerical implementation3.2.3. Advantages and shortages3.3 DNS-DEM Coupled Methods3.3.1. Fully resolved methods3.3.2. Hydrodynamic forces3.3.3. Point-force feedback3.3.4. DNS-Soft-sphere/particle3.3.5. DNS-Hard-sphere/particle3.4 LES-DEM Coupled Methods3.4.1. SGS models3.4.2. Dense flow modulation3.4.3. LES-Soft-sphere/particle3.4.4. LES-Hard-sphere/particle3.5 LBM-DEM Coupled Methods3.5.1. Immersed surface/body3.5.2. Source terms3.5.3. Inter-phase coupling3.5.4. Advantages and limitations3.6 Multiple coupled methods3.7 Parallel Computing Implementation3.8 Other approaches3.9 Summary3.10 Review QuestionsChapter 4Physical Characterization and Key Parameters4.1 Introduction4.2 Particle flow4.2.1. Kolmogorov scale4.2.2. Turbulence characteristic time4.2.3. Particle response time 4.2.4. Particle Reynolds number 4.2.5. Stokes number4.2.6. Mass loading4.2.7. Concentration and voidage4.2.8. Drag forces and others4.2.9. Pressure drop4.2.10. Feedback and modulation4.3 Pebble Flow4.3.1. Packing, discharging and recirculating4.3.2. Discharge pattern4.3.3. Sphericity and roundness4.3.4. Mass flow and funnel flow 4.3.5. Stagnant zone4.3.6. Pebble tracks, stripes, and spindles4.3.7. Bridging and jamming4.3.8. Internal collapse4.3.9. Discharge intermittency4.3.10. Other phenomena4.4 Summary4.5 Review QuestionsChapter 5Application in Gas-Particle Flows5.1 Introduction5.2 Homogeneous dispersions5.2.1 Turbulence coagulation5.2.2 Collision clustering5.2.3 Collision rates and statistics5.2.4 Inertial and non-inertial effects5.2.5 Directional and stochastic motion5.3 Planar jets5.3.1 Vortex streets5.3.2 Particle dispersion5.3.3 Two-way coupling5.3.4 Turbulence modulation5.3.5 Convective heat transfer5.3.6 Prandtl number/Grashof number5.3.7 Initial momentum thickness effect5.3.8 In cross flow5.3.9 Temperature fields and heat transfer5.4 Swirling jets5.4.1 Swirl number5.4.2 Vortex breakdown modes5.4.3 Tempospatial vortical structure5.4.4 Particle dispersion5.4.5 Spectral presentation5.4.6 Structural modification5.4.7 Four-way coupling and modulation5.5 Fluidization5.5.1 Bubble formation and boundary5.5.2 Inter-phase forces and pressure drop5.5.3 Pulsed fluidization and modulated interaction 5.5.4 Particle clustering and fluctuation5.5.5 Self-mixing and interface5.5.6 Immersed tubes and erosion5.5.7 Near wall effects and mesh refinement5.6 Summary5.7 Review QuestionsChapter 6Application in Granular Mixing6.1 Introduction to drum mixers6.2 Mixing process, pattern and regime6.3 Mixing evaluation6.3.1 Concentration6.3.2 Radial distribution function6.3.3 Mixing index and improved MI6.3.4 Mixing information entropy6.3.5 Mixing interface and fractal dimension6.3.6 Local/microscopic mixing6.3.7 Overall/macroscopic mixing6.4 Operation and geometry6.4.1 Rotating speed 6.4.2 Wavy number6.4.3 Wavy amplitude6.4.4 Composite parameter6.4.5 Driving force6.4.6 Friction resistance6.4.7 End-wall effect6.4.8 Non-spherical particles6.5 With heat transfer6.5.1 Lagrangian tracks6.5.2 Mixing and conduction 6.5.3 Interstitial gas and convection 6.5.4 Radiation effect6.5.5 Finite volume effect6.6 Summary6.7 Review QuestionsChapter 7Application in Pebble Flows 7.1 Introduction7.2 Pebble bed reactor and HTGR7.3 Flow regime characterization7.3.1 Time-energy statistics7.3.2 SOE–σ criteria7.3.3 Intermittency index7.3.4 Fluctuation behaviour7.4 Pebble mixing7.4.1 Dispersion7.4.2 Geometry, behaviour and mechanism 7.4.3 Two-region bed and inter-mixing7.4.4 Mixing Interface and multifractal7.4.5 Multiple mixing7.5 Voidages7.5.1 Near wall effect7.5.2 Local voids7.5.3 Three-dimensional distribution7.5.4 Interstitial flow and tunnelling effect7.5.5 Size scaling and dependence7.5.6 Initial and equilibrium packing7.6 Discharge rates and flow uniformity7.6.1 Particle sphericity7.6.2 Composite size7.6.3 Bed base geometry7.6.4 Arcs and cycloids7.7 Heat transfer for pebbles7.7.1 Inter- and internal conduction7.7.2 Convection7.7.3 Long-distance radiation7.7.4 Short-distance radiation7.7.5 Microscopic radiation7.7.6 Fully coupled CFD-DEM model7.8 Summary7.9 Review QuestionsAppendixA.1 List of Computer Models and InstructionA.2 List of in-house codes
- Edition: 1
- Latest edition
- Published: October 23, 2019
- Language: English
NG
Nan Gui
Nan Gui, PhD, is Associate Professor of Chemical Engineering at the Institute of Nuclear and New Energy Technology at Tsinghua University in Beijing, China. Dr. Gui’s career in research and instruction spans more than 20 years. He has a multi-disciplinary research focus across physics, chemistry, materials science, mathematics, numerical methods, computational science, and a number of engineering disciplines including mechanical, chemical, and nuclear. He has authored more than 70 articles across a range of peer-reviewed journals.
Affiliations and expertise
Chemical Engineering, Institute of Nuclear and New Energy Technology, Tsinghua University in Beijing, ChinaSJ
Shengyao Jiang
Shengyao Jiang is a researcher in the Laboratory of Advanced Reactor Engineering and Safety at Tsinghua University.
Affiliations and expertise
Institute of Nuclear and New Energy Technology, Tsinghua University, Beijing, ChinaJT
Jiyuan Tu
Jiyuan Tu is Professor and Deputy Head, Research and Innovation, Department of Aerospace, Mechanical and Manufacturing Engineering, at Royal Melbourne Institute of Technology (RMIT) University, Australia. Professor Tu’s research interests are in the areas of computational fluid dynamics (CFD) and numerical heat transfer (NHT), computational and experimental modelling of multiphase flows, fluid-structure interaction, optimal design of drug delivery devices, and simulation of blood flow in arteries.
Affiliations and expertise
Professor and Deputy Head, Research and Innovation, Department of Aerospace, Mechanical and Manufacturing Engineering, at Royal Melbourne Institute of Technology (RMIT) University, Australia.XY
Xingtuan Yang
Xingtuan Yang is a researcher in the Laboratory of Advanced Reactor Engineering and Safety at Tsinghua University.
Affiliations and expertise
Institute of Nuclear and New Energy Technology, Tsinghua University, Beijing, ChinaRead Gas-Particle and Granular Flow Systems on ScienceDirect