Theory and Application of Discrete Element Method to Simulation of Multiphase Flows

The book provides an in-depth exploration of the theory, implementation, and vast applications of the Discrete Element Method (DEM) and its coupling with Computational Fluid Dynamics (CFD) for simulating complex multiphase flows. Beginning with the core theoretical framework of DEM covering particle kinematics, contact detection algorithms, and contact force models the book systematically progresses to advanced topics. It provides detailed coverage of critical particle-fluid interaction mechanisms, robust CFD-DEM coupling schemes, and the integration of heat and mass transfer phenomena. The strategies for enabling large-scale simulations, including parallel computing, GPU acceleration, and coarse-graining techniques, are also included. The book stands apart through its unparalleled breadth of application-centric chapters. Readers will find dedicated sections on:
   Conventional and Advanced Reactors: Bubbling, spouted, and circulating fluidized beds, as well as magnetized and electrostatic systems.
   Dense Granular Systems: Particle packing, shear flow, silo/hopper discharge, and moving bed applications in chemical looping, pyrolysis, heat exchanger, and blast furnaces.
   Industrial Process Engineering: Pneumatic and screw conveyors, pump wear and flow dynamics, and mining operations in crushers, mills, screens, and chutes.
   Advanced Manufacturing: Pharmaceutical processes like milling, blending, granulation, tableting, and coating, as well as battery electrode calendering and recycling.
   Emerging Trends: The integration of machine learning and optimization strategies for complex multiphase flow systems.
Bridging fundamental theory with cutting-edge practical advancements, Theory and Application of Discrete Element Method to Simulation of Multiphase Flows is an essential guide for students, engineers, and researchers seeking to model systems where particle dynamics are paramount.

Inhaltsverzeichnis

Nomenclature.- Introduction.- Theoretical Framework.- Contact Mechanics.- Particle Shapes and Contact Parameters.- Computational Fluid Dynamics (CFD).- Fluid-Particle Coupling Schemes (CFD-DEM).- Application of DEM to Fluidized Bed.- Application of DEM to Dense Granular System.- Application of DEM to Aerodynamic Particle Separation of Mixture Particles.- Application of DEM to Powder Transport System.- Application of DEM to Battery Technology.- Machine Learning and Optimization.- Strategies for Large-Scale CFD-DEM Simulations.- Challenges and Future Research.

Über den Autor / die Autorin

Ramesh K. Agarwal, Ph.D., is the William Palm Professor of Engineering in the Department of Mechanical Engineering and Materials Science at Washington University in St. Louis. From 1994 to 2001, he was the Sam Bloomfield Distinguished Professor and Executive Director of the National Institute for Aviation Research at Wichita State University. From 1978 to 1994, he was the Program Director and McDonnell Douglas Fellow at McDonnell Douglas Research Laboratories in St. Louis. He received his Ph.D. in Aeronautical Sciences from Stanford University in 1975, an M.S. in Aeronautical Engineering from the University of Minnesota in 1969, and B.S. in Mechanical Engineering from the Indian Institute of Technology, Kharagpur, in 1968. Over a period of 50 years, Professor Agarwal has worked in various areas of computational science and engineering, including computational fluid dynamics (CFD), computational acoustics, magneto-hydrodynamics and electromagnetics, computational materials science and manufacturing, computational control theory and robotics, and multidisciplinary design and optimization. The range of applications in CFD includes subsonic, transonic and hypersonic flows, rarefied and micro-flows, active flow control, turbulence modeling, bio-fluid dynamics, turbomachinery and pumps, wind energy, energy efficiency of buildings, carbon capture and sequestration and chemical looping combustion.  He is the author and co-author of over 600 publications and serves on the editorial board of more than 20 journals. He has given many plenaries, keynotes, and invited lectures at various national and international conferences in over 60 countries worldwide. Professor Agarwal continues to serve on many professional, government, and industrial advisory committees. He is a Fellow of 32 professional societies including the AIAA, ASME, IEEE, SAE, AAAS, APS, and IOP. Professor Agarwal has received many prestigious honors and national/international awards from various professional societies and organizations for his research contributions, including the AIAA Reeds Aeronautics Award, SAE Medal of Honor, ASME Honorary Membership, and an Honorary Fellowship from the Royal Aeronautical Society. 
Yali Shao, Ph.D., is currently an associate professor in the School of Energy and Mechanical Engineering at Nanjing Normal University in Nanjing. She received her Ph.D. in 2020 from the Key Laboratory of Energy Thermal Conversion and Control of the Ministry of Education, School of Energy and Environment at Southeast University, Nanjing, under the guidance of Prof. Baosheng Jin. Dr. Shao has worked in the areas of numerical simulation of multiphase flow, chemical looping carbon capture technology and ammonia-hydrogen zero-carbon fuel utilization technology. She is the author and co-author of over 30 publications. Dr. Shao has collaborated extensively with Professor Ramesh K. Agarwal in the area of DEM and CFD simulations in the past seven years, which is continuing. She has also co-authored many publications with Professor Agarwal in international journals.

Zusammenfassung

The book provides an in-depth exploration of the theory, implementation, and vast applications of the Discrete Element Method (DEM) and its coupling with Computational Fluid Dynamics (CFD) for simulating complex multiphase flows. Beginning with the core theoretical framework of DEM—covering particle kinematics, contact detection algorithms, and contact force models—the book systematically progresses to advanced topics. It provides detailed coverage of critical particle-fluid interaction mechanisms, robust CFD-DEM coupling schemes, and the integration of heat and mass transfer phenomena. The strategies for enabling large-scale simulations, including parallel computing, GPU acceleration, and coarse-graining techniques, are also included. The book stands apart through its unparalleled breadth of application-centric chapters. Readers will find dedicated sections on:
•    Conventional and Advanced Reactors: Bubbling, spouted, and circulating fluidized beds, as well as magnetized and electrostatic systems.
•    Dense Granular Systems: Particle packing, shear flow, silo/hopper discharge, and moving bed applications in chemical looping, pyrolysis, heat exchanger, and blast furnaces.
•    Industrial Process Engineering: Pneumatic and screw conveyors, pump wear and flow dynamics, and mining operations in crushers, mills, screens, and chutes.
•    Advanced Manufacturing: Pharmaceutical processes like milling, blending, granulation, tableting, and coating, as well as battery electrode calendering and recycling.
•    Emerging Trends: The integration of machine learning and optimization strategies for complex multiphase flow systems.
Bridging fundamental theory with cutting-edge practical advancements, Theory and Application of Discrete Element Method to Simulation of Multiphase Flows is an essential guide for students, engineers, and researchers seeking to model systems where particle dynamics are paramount.

Produktdetails

• Autoren: Ramesh K Agarwal, Ramesh K. Agarwal, Yali Shao
• Verlag: Springer, Berlin
• Sprache: Englisch
• Produktform: Fester Einband
• Erscheint: 28.03.2026
• EAN: 9783032111562
• ISBN: 978-3-0-3211156-2
• Illustration: Approx. 300 p. 250 illus., 150 illus. in color.
• Themen: Naturwissenschaften, Medizin, Informatik, Technik > Informatik, EDV > Allgemeines, Lexika; Maschinenbau: Strömungsmechanik, Industrielle Chemie und Chemietechnologie, Verfahrenstechnik und -technologie, Chemical Engineering, Engineering Fluid Dynamics, Computational Science and Engineering, Chemical Process Engineering, multiphase flow, Battery Modeling, Bayesian optimization, Combustion and Gasification, Fluidized Bed, Multi-Particle Systems, Dense Granular System, CFD-DEM, Fluid Catalytic Cracking, Powder Transport System, Pyrolysis and Methanation