Theory and Application of Discrete Element Method to Simulation of Multiphase Flows
-
12% KEDVEZMÉNY?
- Kiadói listaár EUR 181.89
-
75 438 Ft (71 846 Ft + 5% áfa)
Az ár azért becsült, mert a rendelés pillanatában nem lehet pontosan tudni, hogy a beérkezéskor milyen lesz a forint árfolyama az adott termék eredeti devizájához képest. Ha a forint romlana, kissé többet, ha javulna, kissé kevesebbet kell majd fizetnie.
- Kedvezmény(ek) 12% (cc. 9 053 Ft off)
- Kedvezményes ár 66 386 Ft (63 224 Ft + 5% áfa)
66 386 Ft
Beszerezhetőség
Még nem jelent meg, de rendelhető. A megjelenéstől számított néhány héten belül megérkezik.
Why don't you give exact delivery time?
A beszerzés időigényét az eddigi tapasztalatokra alapozva adjuk meg. Azért becsült, mert a terméket külföldről hozzuk be, így a kiadó kiszolgálásának pillanatnyi gyorsaságától is függ. A megadottnál gyorsabb és lassabb szállítás is elképzelhető, de mindent megteszünk, hogy Ön a lehető leghamarabb jusson hozzá a termékhez.
A termék adatai:
- Kiadó Springer Nature Switzerland
- Megjelenés dátuma 2026. április 7.
- ISBN 9783032111562
- Kötéstípus Keménykötés
- Terjedelem245 oldal
- Méret 235x155 mm
- Nyelv angol
- Illusztrációk XII, 245 p. 123 illus., 93 illus. in color. 700
Kategóriák
Hosszú leírás:
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.
Theory and Application of Discrete Element Method to Simulation of Multiphase Flows bridges fundamental theory with cutting-edge practical advancements, serving as an essential guide for students, engineers, and researchers seeking to model systems where particle dynamics are paramount.
- Provides a complete roadmap from core theory to high-performance applications for complex multiphase flow simulations;
- Delivers insights on a range of sectors, featuring dedicated applications in energy, manufacturing and heavy industry;
- Future-proofs computational modeling skills by offering practical guidance on bridging simulation with AI.
Tartalomjegyzék:
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.
Több