Development and assessment of algorithms for DEM-LES simulations of fluidized bed--颗粒学报PARTICUOLOGY

El Hamra, F. E.-Z., & Boukharfane, R. (2023). Development and assessment of algorithms for DEM-LES simulations of fluidized bed. Particuology, 83, 241-257. https://doi.org/10.1016/j.partic.2023.05.009

Development and assessment of algorithms for DEM-LES simulations of fluidized bed

Fatima Ez-Zahra El Hamra, Radouan Boukharfane^*

UM6P College of Computing, Mohammed VI Polytechnic University (UM6P), Benguerir, Morocco

10.1016/j.partic.2023.05.009

Volume 83, December 2023, Pages 241-257

Received 5 February 2023, Revised 13 May 2023, Accepted 26 May 2023, Available online 8 June 2023, Version of Record 3 July 2023.

E-mail: radouan.boukharfane@um6p.ma; radouan.boukharfane@gmail.com

Highlights

• Development of a high fidelity DEM-LES solver for particle scale simulations.

• Consideration of the recent models in both LES and DEM algorithms.

• Use of an efficient parallelization technique.

• Conduct of numerous numerical verification tests of dense flows in fluidized beds.

• Assessment of the performance of SGS turbulence models applied to BFR configuration.

Abstract

The use of high-fidelity Discrete Element Method (DEM) coupled with Computational Fluid Dynamics (CFD) for particle-scale simulations demands extensive simulation times and restricts application to small particulate systems. DEM-CFD simulations require good performance and satisfactory scalability on high-performance computing platforms. A reliable parallel computing strategy must be developed to calculate the collision forces, since collisions can occur between particles that are not on the same processor, or even across processors whose domains are disjoint. The present paper describes a parallelization technique and a numerical verification study based on a number of tests that allow for the assessment of the numerical performance of DEM used in conjunction with Large-Eddy Simulation (LES) to model dense flows in fluidized beds. The fluid phase is computed through solving the volume-averaged four-way coupling Navier-Stokes equations, in which the Smagorinsky sub-grid scale tensor model is used. Furthermore, the performance of Sub-Grid Scale (SGS) turbulence models applied to Fluidized Bed Reactor (FBR) configurations has been assessed and compared. The developed numerical solver represents an interesting combination of techniques that work well for the present purpose of studying particle formation in fluidized beds.

Graphical abstract

Keywords

DEM-LES; Fluidized bed; Computational efficiency; Numerical accuracy

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