scholarly journals A coupled lattice Boltzmann method and discrete element method for discrete particle simulations of particulate flows

2018 ◽  
Vol 172 ◽  
pp. 706-719 ◽  
Author(s):  
C. Rettinger ◽  
U. Rüde
Keyword(s):  
Discrete Element Method ◽  
Lattice Boltzmann Method ◽  
Lattice Boltzmann ◽  
Discrete Element ◽  
Particulate Flows ◽  
Discrete Particle ◽  
Particle Simulations ◽  
Boltzmann Method ◽  
Element Method

Multiscale Simulation with a Two-Way Coupled Lattice Boltzmann Method and Discrete Element Method

2017 ◽  
Vol 40 (9) ◽  
pp. 1591-1598 ◽  
Author(s):  
Marie-Luise Maier ◽  
Thomas Henn ◽  
Gudrun Thaeter ◽  
Hermann Nirschl ◽  
Mathias J. Krause
Keyword(s):  
Discrete Element Method ◽  
Lattice Boltzmann Method ◽  
Lattice Boltzmann ◽  
Discrete Element ◽  
Multiscale Simulation ◽  
Boltzmann Method ◽  
Element Method

scholarly journals Modelling Complex Particle–Fluid Flow with a Discrete Element Method Coupled with Lattice Boltzmann Methods (DEM-LBM)

2020 ◽  
Vol 4 (4) ◽  
pp. 55
Author(s):  
Wenwei Liu ◽  
Chuan-Yu Wu
Keyword(s):  
Discrete Element Method ◽  
Lattice Boltzmann Method ◽  
Lattice Boltzmann ◽  
Fluid Flows ◽  
Discrete Element ◽  
Dense Particle ◽  
Inertial Migration ◽  
Complex Particle ◽  
Boltzmann Method ◽  
Element Method

Particle–fluid flows are ubiquitous in nature and industry. Understanding the dynamic behaviour of these complex flows becomes a rapidly developing interdisciplinary research focus. In this work, a numerical modelling approach for complex particle–fluid flows using the discrete element method coupled with the lattice Boltzmann method (DEM-LBM) is presented. The discrete element method and the lattice Boltzmann method, as well as the coupling techniques, are discussed in detail. The DEM-LBM is thoroughly validated for typical benchmark cases: the single-phase Poiseuille flow, the gravitational settling and the drag force on a fixed particle. In order to demonstrate the potential and applicability of DEM-LBM, three case studies are performed, which include the inertial migration of dense particle suspensions, the agglomeration of adhesive particle flows in channel flow and the sedimentation of particles in cavity flow. It is shown that DEM-LBM is a robust numerical approach for analysing complex particle–fluid flows.

Numerical study of sheared mobile polydisperse sediment beds with a coupled lattice Boltzmann - discrete element method

2021 ◽  
Author(s):  
Christoph Rettinger ◽  
Sebastian Eibl ◽  
Ulrich Rüde ◽  
Bernhard Vowinckel
Keyword(s):  
Discrete Element Method ◽  
Lattice Boltzmann ◽  
Numerical Study ◽  
Experimental Studies ◽  
Discrete Element ◽  
Parallel Execution ◽  
Coupling Mechanism ◽  
Size Segregation ◽  
Minimum Diameter ◽  
Element Method

<p>With the increasing computational power of today's supercomputers, geometrically fully resolved simulations of particle-laden flows are becoming a viable alternative to laboratory experiments. Such simulations enable detailed investigations of transport phenomena in various multiphysics scenarios, such as the coupled interaction of sediment beds with a shearing fluid flow. There, the majority of available simulations as well as experimental studies focuses on setups of monodisperse particles. In reality, however, polydisperse configurations are much more common and feature unique effects like vertical size segregation.</p><p>In this talk, we will present numerical studies of mobile polydisperse sediment beds in a laminar shear flow, with a ratio of maximum to minimum diameter up to 10. The lattice Boltzmann method is applied to represent the fluid dynamics through and above the sediment bed efficiently. We model particle interactions by a discrete element method and explicitly account for lubrication forces. The fluid-particle coupling mechanism is based on the geometrically fully resolved momentum transfer between the fluid and the particulate phase. We will highlight algorithmic aspects and communication schemes essential for massively parallel execution.</p><p>Utilizing these capabilities allows us to achieve large-scale simulations with more than 26.000 densely-packed polydisperse particles interacting with the fluid. With this, we are able to reproduce effects like size segregation and to study the rheological behavior of such systems in great detail. We will evaluate and discuss the influence of polydispersity on these processes. These insights will be used to improve and extend existing macroscopic models.</p>

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