Simulation of granular flow in a rotating frame of reference using the discrete element method

Delacroix, Bastien; Bouarab, Anya F.; Fradette, Louis; Bertrand, François; Blais, Bruno

doi:10.1016/j.powtec.2020.05.006

Cited by 9 publications

(6 citation statements)

References 20 publications

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“…33 To integrate Newton's equation of motion, we implement the Velocity Verlet scheme. 47 CFD-DEM Coupling. CFD and DEM are mainly coupled through the void fraction calculation and the fluid−particle interactions.…”

Section: Strategy In Cfd-demmentioning

confidence: 99%

Toward High-Order CFD-DEM: Development and Validation

Geitani

Golshan

Blais

2023

Ind. Eng. Chem. Res.

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CFD-DEM is used to simulate solid−fluid systems. DEM models the motion of discrete particles while CFD models the dynamics of the fluid phase. Coupling both necessitates the calculation of the void fraction and the solid−fluid forces resulting in a computationally expensive method. Additionally, evaluating volume-averaged quantities locally restricts particle to cell size ratios limiting the accuracy of the CFD. To mitigate these limitations, we develop a unified finite element CFD-DEM solver which integrates the CFD and DEM solvers into a single software resulting in faster and cheaper coupling between the solvers. It supports dynamically load-balanced parallelization. This allows for more efficient simulations as load balancing ensures the even distribution of workloads among processors; thus, exploiting available resources efficiently. Our solver supports high order schemes; thus, allowing the use of larger elements enhancing the validity and stability of the void fraction schemes while achieving better accuracy. We verify and validate our CFD-DEM solver with a large array of test cases: particle sedimentation, a fluidized bed, the Rayleigh Taylor instability, and a spouted bed.

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Section: Strategy In Cfd-demmentioning

confidence: 99%

Toward High-Order CFD-DEM: Development and Validation

Geitani

Golshan

Blais

2023

Ind. Eng. Chem. Res.

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“…When the force only depends on the position, the Velocity Verlet scheme is second-order accurate for position and velocity. In this context, the Velocity Verlet scheme is symplectic (see [32] for a full demonstration). When the force depends on the velocity, as is the case when the coefficient of restitution is not one, the scheme is first-order accurate for both position and velocity [32].…”

Section: Velocity Verletmentioning

confidence: 99%

“…In this context, the Velocity Verlet scheme is symplectic (see [32] for a full demonstration). When the force depends on the velocity, as is the case when the coefficient of restitution is not one, the scheme is first-order accurate for both position and velocity [32]. In practice, however, it is still significantly more accurate than an explicit Euler scheme.…”

Section: Velocity Verletmentioning

confidence: 99%

Lethe-DEM : An open-source parallel discrete element solver with load balancing

Golshan¹,

Münch²,

Gassmöller³

et al. 2021

Preprint

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Approximately 75% of the raw material and 50% of the products in the chemical industry are granular materials. The Discrete Element Method (DEM) provides detailed insights of phenomena at particle scale and it is therefore often used for modeling granular materials. However, because DEM tracks the motion and contact of individual particles separately, its computational cost increases nonlinearly O(n p log(n p )) -O(n 2 p ) depending on the algorithm) with the number of particles (n p ). In this article, we introduce a new open-source parallel DEM software with load balancing: Lethe-DEM. Lethe-DEM, a module of Lethe, consists of solvers for two-dimensional and three-dimensional DEM simulations. Loadbalancing allows Lethe-DEM to significantly increase the parallel efficiency by ≈ 25 − 70% depending on the granular simulation. We explain the fundamental modules of Lethe-DEM, its software architecture, and the governing equations. Furthermore, we verify Lethe-DEM with several tests including analytical solutions and comparison with other software. Comparisons with experiments in a flat-bottomed silo, wedge-shaped silo, and rotating drum validate Lethe-DEM. We investigate the strong and weak scaling of Lethe-DEM with 1 ≤ n c ≤ 192 and 32 ≤ n c ≤ 320 processes, respectively, with and without load-balancing. The strong-scaling analysis is performed on the wedge-shaped silo and rotating drum simulations, while for the weak-scaling analysis, we use a dam break simulation. The best scalability of Lethe-DEM is obtained in the range of 5000 ≤ n p /n c ≤ 15 000. Finally, we demonstrate that large scale simulations can be carried out with Lethe-DEM using the simulation of a three-dimensional

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“…We used a previously developed unresolved CFD‐DEM model in a rotating frame of references Delacroix et al 45,46 The model is based on the CFDEM platform, 47 which combines two open‐source software packages, that is, LIGGGHTS 48 for granular dynamics using the discrete element method (DEM) and OpenFOAM 49 for the CFD. The CFD part is based on a cell‐centered finite volume approach.…”

Section: Model Descriptionmentioning

confidence: 99%

“…Based on Newton's second law of motion, the governing equations for the translational ( u p , i ) and rotational ( ω p , i ) motions of particle i in a noninertial frame of reference can be written as 48,51–53 :

m_{i} \frac{d u_{normalp, i}}{dt} = \sum_{j} f_{normalc, italicij} + \sum_{k} f_{lr, italicik} + f_{pf, i} + f_{normalg, i} - \underset{{bold-italicF}_{Coriolis}}{\underset{true︸}{2 m_{i} Ω \times {bold-italicu}_{p, i}}} - \underset{{bold-italicF}_{Centrifugal}}{\underset{true︸}{m_{i} Ω \times (Ω \times {bold-italicq}_{p, i})}}

I_{i} \frac{d ω_{normalp, i}}{dt} = \sum_{j} ((), M_{normalt, italicij} + M_{normalr, italicij}) - \underset{{bold-italicT}_{Coriolis}}{\underset{true︸}{I (Ω \times {bold-italicω}_{p, i})}}

where m i is the mass of particle i , Ω is the rotation vector of the frame of reference, q p, i and u p, i are the position (from the projection point on the axis of rotation: q p, i · Ω = 0) and velocity vectors of a particle i , I i is the moment of inertia of particle i , ω p, i is the angular velocity of particle i , f c, ij is the contact forces between particles i and j , f lr, ik is the noncontact (long‐range) forces between particles i and k , f pf, i is the particle‐fluid interaction forces, f g, i is the gravitational force ( f g, i = m i g ), and M t, ij and M r, ij are the tangential and rolling friction torques acting on particle i due to its contact with particle j . In the present work, non‐contact forces such as electrostatic or Van Der Waals forces in Equation () and Coriolis torque in Equation () were not taken into account due to the size and nature of the particles …”

Section: Model Descriptionmentioning

confidence: 99%

Which impeller should be chosen for efficient solid–liquid mixing in the laminar and transitional regime?

et al. 2021

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The vast majority of solid–liquid mixing studies have focused on high Reynolds number applications with configurations and impeller geometries adapted to this type of regime. However, the mixing of particles in a viscous fluid is an essential element of many contemporary industries. We used the computational fluid dynamics‐discrete element method model previously developed in our group to investigate solid–liquid mixing with close‐clearance impellers in the laminar regime of operation. We compared different geometries, that is, the double helical ribbon, anchor, Paravisc™, and Maxblend™ impellers. We investigated the impact of fluid viscosity and compared the results with those obtained with the pitched blade turbine, a more commonly used impeller, based on power consumption for equivalent mixing states. This study highlights that the higher the viscosity of the fluid, the more interesting it is to use close‐clearance impellers for their ability to generate a strong shear stress and a strong bulk flow in the entire vessel.

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Simulation of granular flow in a rotating frame of reference using the discrete element method

Cited by 9 publications

References 20 publications

Toward High-Order CFD-DEM: Development and Validation

Toward High-Order CFD-DEM: Development and Validation

Lethe-DEM : An open-source parallel discrete element solver with load balancing

Which impeller should be chosen for efficient solid–liquid mixing in the laminar and transitional regime?

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