Behavior of particle swarms at low and moderate Reynolds numbers using computational fluid dynamics—Discrete element model

2020 ◽  
Vol 32 (7) ◽  
pp. 073304
Author(s):  
Oladapo Ayeni ◽  
Shashank S. Tiwari ◽  
Chunliang Wu ◽  
Jyeshtharaj B. Joshi ◽  
Krishnaswamy Nandakumar
Keyword(s):  
Fluid Dynamics ◽  
Computational Fluid Dynamics ◽  
Element Model ◽  
Reynolds Numbers ◽  
Discrete Element ◽  
Discrete Element Model ◽  
Particle Swarms

scholarly journals MFIX-Exa: A path toward exascale CFD-DEM simulations

2021 ◽  
pp. 109434202110092
Author(s):  
Jordan Musser ◽  
Ann S Almgren ◽  
William D Fullmer ◽  
Oscar Antepara ◽  
John B Bell ◽  
...  
Keyword(s):  
Fluid Dynamics ◽  
Computational Fluid Dynamics ◽  
Element Model ◽  
Discrete Element Model ◽  
Software Framework ◽  
Chemical Reactors ◽  
Software Infrastructure ◽  
Fundamental Physics ◽  
Dem Simulations ◽  
Algorithmic Approaches

MFIX-Exa is a computational fluid dynamics–discrete element model (CFD-DEM) code designed to run efficiently on current and next-generation supercomputing architectures. MFIX-Exa combines the CFD-DEM expertise embodied in the MFIX code—which was developed at NETL and is used widely in academia and industry—with the modern software framework, AMReX, developed at LBNL. The fundamental physics models follow those of the original MFIX, but the combination of new algorithmic approaches and a new software infrastructure will enable MFIX-Exa to leverage future exascale machines to optimize the modeling and design of multiphase chemical reactors.

Discrete element method–computational fluid dynamics analyses of flexible fibre fluidization

2021 ◽  
Vol 910 ◽  
Author(s):  
Yiyang Jiang ◽  
Yu Guo ◽  
Zhaosheng Yu ◽  
Xia Hua ◽  
Jianzhong Lin ◽  
...  
Keyword(s):  
Fluid Dynamics ◽  
Computational Fluid Dynamics ◽  
Discrete Element Method ◽  
Discrete Element ◽  
Dynamics Analyses ◽  
Element Method

Abstract

scholarly journals Discrete element model for general polyhedra

2021 ◽  
Author(s):  
Alfredo Gay Neto ◽  
Peter Wriggers
Keyword(s):  
Frictional Contact ◽  
Virtual Work ◽  
Particle Surface ◽  
Element Model ◽  
Discrete Element ◽  
Discrete Element Model ◽  
Principle Of Virtual Work ◽  
Dynamics Model ◽  
Railway Ballast ◽  
Multibody Dynamics Model

AbstractWe present a version of the Discrete Element Method considering the particles as rigid polyhedra. The Principle of Virtual Work is employed as basis for a multibody dynamics model. Each particle surface is split into sub-regions, which are tracked for contact with other sub-regions of neighboring particles. Contact interactions are modeled pointwise, considering vertex-face, edge-edge, vertex-edge and vertex-vertex interactions. General polyhedra with triangular faces are considered as particles, permitting multiple pointwise interactions which are automatically detected along the model evolution. We propose a combined interface law composed of a penalty and a barrier approach, to fulfill the contact constraints. Numerical examples demonstrate that the model can handle normal and frictional contact effects in a robust manner. These include simulations of convex and non-convex particles, showing the potential of applicability to materials with complex shaped particles such as sand and railway ballast.

scholarly journals Thermoelectric Generation with Impinging Nano-Jets

Energies ◽  
2021 ◽  
Vol 14 (2) ◽  
pp. 492
Author(s):  
Fatih Selimefendigil ◽  
Hakan F. Oztop ◽  
Mikhail A. Sheremet
Keyword(s):  
Fluid Dynamics ◽  
Power Generation ◽  
Computational Fluid Dynamics ◽  
Reynolds Number ◽  
Conversion Efficiency ◽  
Reynolds Numbers ◽  
Thermoelectric Generation ◽  
Volume Fractions ◽  
Water Jets ◽  
Conversion Efficiencies

In this study, thermoelectric generation with impinging hot and cold nanofluid jets is considered with computational fluid dynamics by using the finite element method. Highly conductive CNT particles are used in the water jets. Impacts of the Reynolds number of nanojet stream combinations (between (Re1, Re2) = (250, 250) to (1000, 1000)), horizontal distance of the jet inlet from the thermoelectric device (between (r1, r2) = (−0.25, −0.25) to (1.5, 1.5)), impinging jet inlet to target surfaces (between w2 and 4w2) and solid nanoparticle volume fraction (between 0 and 2%) on the interface temperature variations, thermoelectric output power generation and conversion efficiencies are numerically assessed. Higher powers and efficiencies are achieved when the jet stream Reynolds numbers and nanoparticle volume fractions are increased. Generated power and efficiency enhancements 81.5% and 23.8% when lowest and highest Reynolds number combinations are compared. However, the power enhancement with nanojets using highly conductive CNT particles is 14% at the highest solid volume fractions as compared to pure water jet. Impacts of horizontal location of jet inlets affect the power generation and conversion efficiency and 43% variation in the generated power is achieved. Lower values of distances between the jet inlets to the target surface resulted in higher power generation while an optimum value for the highest efficiency is obtained at location zh = 2.5ws. There is 18% enhancement in the conversion efficiency when distances at zh = ws and zh = 2.5ws are compared. Finally, polynomial type regression models are obtained for estimation of generated power and conversion efficiencies for water-jets and nanojets considering various values of jet Reynolds numbers. Accurate predictions are obtained with this modeling approach and it is helpful in assisting the high fidelity computational fluid dynamics simulations results.

Modeling a Fluidized Bed Dryer through Computational Fluid Dynamics and Discrete Element Method

2021 ◽  
Author(s):  
Sebastian Alexander Pérez Cortés ◽  
Yerko Rafael Aguilera Carvajal ◽  
Juan Pablo Vargas Norambuena ◽  
Javier Antonio Norambuena Vásquez ◽  
Juan Andrés Jarufe Troncoso ◽  
...  
Keyword(s):  
Fluid Dynamics ◽  
Computational Fluid Dynamics ◽  
Discrete Element Method ◽  
Fluidized Bed ◽  
Discrete Element ◽  
Fluidized Bed Dryer ◽  
Element Method
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