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Gas-Particle and Granular Flow Systems - 1st Edition - ISBN: 9780128163986, 9780128163993

Gas-Particle and Granular Flow Systems

1st Edition

Coupled Numerical Methods and Applications

Authors: Nan Gui Shengyao Jiang Jiyuan Tu Xingtuan Yang
Paperback ISBN: 9780128163986
eBook ISBN: 9780128163993
Imprint: Elsevier
Published Date: 22nd October 2019
Page Count: 386
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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.

Key Features

  • 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

Table of Contents

Chapter 1
Particle and Pebble Flow-- An Introduction
1.1 Introduction
1.2 Category of particle and pebble flow
1.2.1. By material Bubble-particle system Droplet-particle system Solid-particle system
1.2.2. By concentration Dense flow Dilute flow
1.2.3. By flow behaviour Rapid flow Slow flow Quasi-stationary flow
1.2.4. Pebble flow Extremely slow flow Intermittent flow Consistent flow
1.3 Numerical methods for continuum system
1.3.1 Reynolds Averaged Navier-Stokes simulation
1.3.2 Direct numerical simulation
1.3.3 Large eddy simulation
1.3.4 Mesoscale methods and lattice-Boltzmann Equation
1.3.5 Other particle-based methods
1.4 Numerical methods for particle and pebble system
1.4.1 Deterministic .vs. stochastic model
1.4.2 Molecular dynamics simulation
1.4.3 Discrete Element method
1.4.4 DSMC methods
1.4.5 Other methods
1.5 Summary
1.6 Review Questions
Chapter 2
Discrete Particle Models and Extensions
2.1 Introduction
2.2 Soft-sphere approach
2.2.1. Contact theories
2.2.2. Basic mechanics
2.2.3. Parameter dependence and calibration
2.2.4. Energy dissipation
2.2.5. Computational advantage and limitation
2.3 Hard-sphere approach
2.3.1. Collision dynamics
2.3.2. Restitution coefficient
2.3.3. Friction and non-friction
2.3.4. Collision detection
2.3.5. Energy dissipation
2.3.6. Computational efficiency and shortage
2.4 For non-spherical shapes
2.4.1. Gluing technique
2.4.2. Clumpy effects
2.4.3. Super geometry
2.4.4. Cutting/Overlapping geometry
2.4.5. SIPHPM model
2.4.6. GHPM model
2.4.7. EHPM-DEM model
2.4.8. With wall roughness
2.5 Heat transfer extension
2.5.1. Conduction Particle-scale conduction Effective conduction
2.5.2. Convection
2.5.3. Radiation Correlations Averaged methods Direct simulation Particle-scale radiation Equivalent approach
2.6 Other extensions
2.6.1 Complex forces
2.6.2 Large deformation
2.6.3 Linkage and breakup
2.7 Summary
2.8 Review Questions
Chapter 3
Coupled Methods
3.1 Introduction
3.1.1. Eulerian-Eulerian approach
3.1.2. Eulerian-Lagrangian approach
3.1.3. Inter-phase coupling
3.1.4. Distribution function
3.1.5. Interpolation function
3.1.6. Reversive and conservative
3.2 CFD-DEM coupled approach
3.2.1. Basic strategy
3.2.2. Numerical implementation
3.2.3. Advantages and shortages
3.3 DNS-DEM Coupled Methods
3.3.1. Fully resolved methods
3.3.2. Hydrodynamic forces
3.3.3. Point-force feedback
3.3.4. DNS-Soft-sphere/particle
3.3.5. DNS-Hard-sphere/particle
3.4 LES-DEM Coupled Methods
3.4.1. SGS models
3.4.2. Dense flow modulation
3.4.3. LES-Soft-sphere/particle
3.4.4. LES-Hard-sphere/particle
3.5 LBM-DEM Coupled Methods
3.5.1. Immersed surface/body
3.5.2. Source terms
3.5.3. Inter-phase coupling
3.5.4. Advantages and limitations
3.6 Multiple coupled methods
3.7 Parallel Computing Implementation
3.8 Other approaches
3.9 Summary
3.10 Review Questions
Chapter 4
Physical Characterization and Key Parameters
4.1 Introduction
4.2 Particle flow
4.2.1. Kolmogorov scale
4.2.2. Turbulence characteristic time
4.2.3. Particle response time
4.2.4. Particle Reynolds number
4.2.5. Stokes number
4.2.6. Mass loading
4.2.7. Concentration and voidage
4.2.8. Drag forces and others
4.2.9. Pressure drop
4.2.10. Feedback and modulation
4.3 Pebble Flow
4.3.1. Packing, discharging and recirculating
4.3.2. Discharge pattern
4.3.3. Sphericity and roundness
4.3.4. Mass flow and funnel flow
4.3.5. Stagnant zone
4.3.6. Pebble tracks, stripes, and spindles
4.3.7. Bridging and jamming
4.3.8. Internal collapse
4.3.9. Discharge intermittency
4.3.10. Other phenomena
4.4 Summary
4.5 Review Questions
Chapter 5
Application in Gas-Particle Flows
5.1 Introduction
5.2 Homogeneous dispersions
5.2.1 Turbulence coagulation
5.2.2 Collision clustering
5.2.3 Collision rates and statistics
5.2.4 Inertial and non-inertial effects
5.2.5 Directional and stochastic motion
5.3 Planar jets
5.3.1 Vortex streets
5.3.2 Particle dispersion
5.3.3 Two-way coupling
5.3.4 Turbulence modulation
5.3.5 Convective heat transfer
5.3.6 Prandtl number/Grashof number
5.3.7 Initial momentum thickness effect
5.3.8 In cross flow
5.3.9 Temperature fields and heat transfer
5.4 Swirling jets
5.4.1 Swirl number
5.4.2 Vortex breakdown modes
5.4.3 Tempospatial vortical structure
5.4.4 Particle dispersion
5.4.5 Spectral presentation
5.4.6 Structural modification
5.4.7 Four-way coupling and modulation
5.5 Fluidization
5.5.1 Bubble formation and boundary
5.5.2 Inter-phase forces and pressure drop
5.5.3 Pulsed fluidization and modulated interaction
5.5.4 Particle clustering and fluctuation
5.5.5 Self-mixing and interface
5.5.6 Immersed tubes and erosion
5.5.7 Near wall effects and mesh refinement
5.6 Summary
5.7 Review Questions
Chapter 6
Application in Granular Mixing
6.1 Introduction to drum mixers
6.2 Mixing process, pattern and regime
6.3 Mixing evaluation
6.3.1 Concentration
6.3.2 Radial distribution function
6.3.3 Mixing index and improved MI
6.3.4 Mixing information entropy
6.3.5 Mixing interface and fractal dimension
6.3.6 Local/microscopic mixing
6.3.7 Overall/macroscopic mixing
6.4 Operation and geometry
6.4.1 Rotating speed
6.4.2 Wavy number
6.4.3 Wavy amplitude
6.4.4 Composite parameter
6.4.5 Driving force
6.4.6 Friction resistance
6.4.7 End-wall effect
6.4.8 Non-spherical particles
6.5 With heat transfer
6.5.1 Lagrangian tracks
6.5.2 Mixing and conduction
6.5.3 Interstitial gas and convection
6.5.4 Radiation effect
6.5.5 Finite volume effect
6.6 Summary
6.7 Review Questions
Chapter 7
Application in Pebble Flows
7.1 Introduction
7.2 Pebble bed reactor and HTGR
7.3 Flow regime characterization
7.3.1 Time-energy statistics
7.3.2 SOE–σ criteria
7.3.3 Intermittency index
7.3.4 Fluctuation behaviour
7.4 Pebble mixing
7.4.1 Dispersion
7.4.2 Geometry, behaviour and mechanism
7.4.3 Two-region bed and inter-mixing
7.4.4 Mixing Interface and multifractal
7.4.5 Multiple mixing
7.5 Voidages
7.5.1 Near wall effect
7.5.2 Local voids
7.5.3 Three-dimensional distribution
7.5.4 Interstitial flow and tunnelling effect
7.5.5 Size scaling and dependence
7.5.6 Initial and equilibrium packing
7.6 Discharge rates and flow uniformity
7.6.1 Particle sphericity
7.6.2 Composite size
7.6.3 Bed base geometry
7.6.4 Arcs and cycloids
7.7 Heat transfer for pebbles
7.7.1 Inter- and internal conduction
7.7.2 Convection
7.7.3 Long-distance radiation
7.7.4 Short-distance radiation
7.7.5 Microscopic radiation
7.7.6 Fully coupled CFD-DEM model
7.8 Summary
7.9 Review Questions
A.1 List of Computer Models and Instruction
A.2 List of in-house codes


No. of pages:
© Elsevier 2019
22nd October 2019
Paperback ISBN:
eBook ISBN:

About the Authors

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, China

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, China

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

RMIT University, Australia, University of New South Wales, Australia, Tsinghua University, P.R. China

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, China

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