Small Scale Rotating Drum#
This example of Lethe-DEM simulates dry granular flow behaviour in a small scale rotating drum. The discrete element method (DEM) is responsible for describing the behaviour of particles. More information regarding the DEM parameters are given in the Lethe-DEM documentation, i.e. DEM parameters.
Features#
Solvers:
lethe-particlesThree-dimensional problem
Rotational boundary
Load-balancing
Files Used in This Example#
Both files mentioned below are located in the example’s folder (examples/dem/3d-small-scale-rotating-drum).
Parameters file for particle insertion:
packing-rotating-drum.prmParameters file for drum rotation:
small-rotating-drum-dem.prm
Description of the Case#
This example simulates a rolling regime in a small scale rotating drum. First, we use Lethe-DEM to fill the bed with 20000 particles. We enable check-pointing in order to write the DEM checkpoint files for the packing which then will be used as the starting point of the DEM simulation of the rotating drum. The solver lethe-particles is used to simulate the behaviour of dry granular flow within the rotating drum.
Parameter File#
Mesh#
In this example, we choose a cylinder grid type to create a cylinder. Grid arguments are the radius of the cylinder (0.056 m) and half-length (0.051 m), respectively. The grid is refined 3 times using the set initial refinement parameters. The expand particle-wall contact search is used in concave geometries to enable extended particle-wall contact search with boundary faces of neighbor cells for particles located in each boundary cell (for more details see Rotating Drum example).
subsection mesh
set type = dealii
set grid type = cylinder
set grid arguments = 0.056:0.051
set initial refinement = 3
end
Packing information#
An insertion box is defined inside the cylindrical domain, inserting 8000 particles every 0.5 seconds while the cylinder is at rest. It is important to note the size of the insertion box to make sure it is completely inside our geometry. Otherwise, particles will be lost during the insertion stage.
subsection insertion info
set insertion method = volume
set inserted number of particles at each time step = 8000
set insertion frequency = 100000
set insertion box points coordinates = -0.05, 0., -0.04 : 0.05, 0.04, 0.04
set insertion distance threshold = 1.1
set insertion maximum offset = 0.05
set insertion prn seed = 19
end
Restart files are written once the packing ends. The restart files are used to start the DEM simulation with the imposed rotating boundary condition.
Lagrangian Physical Properties#
The particles are mono-dispersed with a radius of 0.0015 m and a density of 2500 kg/m3, respectively. All other particles’ physical parameters are taken arbitrary and should be changed based on the physical properties and the experimental values.
subsection lagrangian physical properties
set g = 0.0, -9.81, 0.0
set number of particle types = 1
subsection particle type 0
set size distribution type = uniform
set diameter = 0.003
set number of particles = 20000
set density particles = 2500
set young modulus particles = 100000000
set poisson ratio particles = 0.24
set restitution coefficient particles = 0.97
set friction coefficient particles = 0.3
set rolling friction particles = 0.1
end
set young modulus wall = 100000000
set poisson ratio wall = 0.24
set restitution coefficient wall = 0.85
set friction coefficient wall = 0.35
set rolling friction wall = 0.1
end
Model Parameters#
In this example, we use the dynamic load balancing method. This method checks frequently if load balancing should be applied based on a user inputted frequency. Load balancing is dynamically applied if a certain condition is applied. More details regarding load balancing are explained in the Rotating Drum example.
subsection model parameters
subsection contact detection
set contact detection method = dynamic
set dynamic contact search size coefficient = 0.8
set neighborhood threshold = 1.3
end
subsection load balancing
set load balance method = dynamic
set threshold = 0.5
set dynamic check frequency = 10000
end
set particle particle contact force method = hertz_mindlin_limit_overlap
set particle wall contact force method = nonlinear
set rolling resistance torque method = constant_resistance
set integration method = velocity_verlet
end
DEM Boundary Conditions#
The rotation of the cylinder is applied using a rotational boundary condition with a value of 1 rad/s over the x axis. Based on deal.II boundary colouring, the hull of the cylinder (rotating drum) has an id = 0.
subsection DEM boundary conditions
set number of boundary conditions = 1
subsection boundary condition 0
set boundary id = 0
set type = rotational
set rotational speed = 1
set rotational vector = 1, 0, 0
end
end
Simulation Control#
The packing lethe-particles simulation was run for 2 seconds in real time.
subsection simulation control
set time step = 5e-6
set time end = 2
set log frequency = 2000
set output frequency = 2000
set output path = ./output_dem/
end
The actual rotation of the drum is 3 seconds in real time. We set the time equal to 5 seconds as the simulation is restarted after the packing lethe-particles simulation.
subsection simulation control
set time step = 5e-6
set time end = 5
set log frequency = 2000
set output frequency = 2000
set output path = ./output_dem/
end
Running the Simulation#
The simulation is launched in two steps: the first step packs the particle in the cylinder, while the second step rotates the drum and simulates the movement of the particles.
Note
This example needs a simulation time of approximately 60 minutes on 8 processors using an 12th Gen Intel(R) Core(TM) i9-12900K
Results#
The following movie displays the rolling regime inside the rotating drum obtained with a rotational velocity of 1 rad/s.
Possibilities for Extension#
Use two types of particles with different radius to prove the Brazil-Nut effect.
Perform an unresolved CFD-DEM simulation for wet granular flows to see the impact of the hydrodynamics of the fluid over the particles dynamics.