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

Abstract

In the present study, the sedimentation of a swarm of mono-sized particles is investigated using the Computational Fluid Dynamics–Discrete Element Model (CFD-DEM) approach. The computational approach employed was able to accurately predict the breakup pattern of the swarm of particles into secondary clusters. The rate of leakage of the particles from the cluster (in the creeping flow regime) was found to linearly increase with an increase in the initial number of particles present in the sedimenting cluster. The breakup pattern of the cluster of particles was found to be highly sensitive to the shape of the outer domain. At Rec = 5, the sedimentation of the cluster in a cylindrical outer domain was observed to break up into six secondary blobs (k = 6), whereas for a square and a rectangular outer domain, the breakup resulted in four (k = 4) and two (k = 2) secondary blobs, respectively. Besides, the CFD-DEM approach was found to be in excellent agreement with the experimental data as opposed to the Oseenlet point particle approach, which could not accurately predict the settling velocities for a sedimenting cluster at a finite Rec and high solid fraction (Rec = 14, ϕs ≈ 0.5).

Segregation and intermixing in polydisperse liquid–solid fluidized beds: A multifluid model validation study

“…In this direction, we have already started taking the results from the present study ahead and combining them with our in‐house immersed boundary method (IBM) solver, 39 CFD–DEM solver, 9 and anisotropic Gaussian E–E solver 40 …”

“…The limitations posed by the MFM can be overcome by using a more rational approach such as (i) the computational fluid dynamics-discrete element method (CFD-DEM) approach, which solves the equation of motion tracking the trajectory of each particle, thereby considering them as discrete entities. 9,10 (ii) Direct numerical simulations (DNS)-solving the fundamental governing equations for the continuous and the dispersed phases without averaging or filtering approaches. Although both CFD-DEM and DNS provide a much rational solution, they are computationally intensive and expensive for simulating polydisperse LSFB.…”

“…Most of the commonly used interfacial interaction models used to provide closures are based on empirical or semiempirical models, which makes their use restricted under specific flow conditions. The limitations posed by the MFM can be overcome by using a more rational approach such as (i) the computational fluid dynamics–discrete element method (CFD–DEM) approach, which solves the equation of motion tracking the trajectory of each particle, thereby considering them as discrete entities 9,10 . (ii) Direct numerical simulations (DNS)—solving the fundamental governing equations for the continuous and the dispersed phases without averaging or filtering approaches.…”

Numerical Analysis of Single-Particle Motion Using CFD-DEM in Varying-Curvature Elbows

“…Due to the advantages of the DEM method with respect to solid particle calculation, many researchers use this method for coupling with a continuous phase [11][12][13]. Zhao [14] simulated the gas-solid flow in a two-dimensional downer using the CFD-DEM method.…”

Computational fluid dynamic simulations of regular bubble patterns in pulsed fluidized beds using a two‐fluid model

“…[24,25] Recent CFD model development for fluid-solid systems can be categorized into two main approaches: (i) the continuum approach (Eulerian view), commonly referred to as the two-fluid model (TFM) and (ii) the discrete approach (Lagrangian perspective), formally known as the discrete element model (DEM). [26][27][28][29] The TFM treats the fluid and solid phases as an interpenetrating continuum and solves two sets of mass, momentum, and energy equations for each of the two phases. The constitutive equations in the TFM are based on the ensemble averaging approach and thus face the closure problem.…”