multiphase modeling using edem-cfd coupling for...
TRANSCRIPT
Multiphase Modeling Using
EDEM-CFD Coupling for FLUENT
Nicolas Spogis, Ph.D.
Business Coordinator
E-mail: [email protected]
Presentation Outline
• Overview EDEM-CFD Coupling for FLUENT
• Standard Industrial Applications
– Pneumatic conveying
– Fluidised beds– Fluidised beds
– Kilns
– Particle Drying
• Current Research Activities
– Fluidised bed spray granulation
– Non-spherical particles
– Using EDEM as pre-processor for CFD
Discrete Element Method
• Model the dynamics of each particle
• Lagrangian solution
• Considers:– Mechanical and inertial properties
– Interaction with:• other particles• other particles
• boundary surfaces
• other force fields (surrounding fluid, gravity,
electro-magnetic fields, etc.)
• High spatial resolution of momentum, mass and heat transfer in particulate systems
• Bulk behaviour evolves from the particle scale
EDEM computational cycle
Track each
Detect contact
between elementsCalculate contact forces on each
particle
Calculate body
forces acting on Track each
particle and
boundary element
forces acting on
each particle:
gravity, fluid drag,
electrostatic, 3..
Update particle acceleration
and velocity
Update particle and boundary
element positions
What information can EDEM provide?
SegregationMixing dynamics
Granulation
Bulk
Residence time/
hold-up
Damage/attrition
Bridging
Uniformity of flow
Particle-boundary contact forces
Particle kinematics
Particle-particle contact forces
Particle size/mass/temperature
Particle
Heat transfer
Breakage
Particle-machine
interaction
Fluidization
Mechanical energy
consumption
Pneumatic transport
Surface coating
Agglomeration
Erosion
Particle-boundary contact forces
New particle formation
EDEM results
Particle body forces: gravitational,
fluid, electro-magnetic
Overview of EDEM-CFD Coupling for FLUENT
• Couples with Eulerian multi-
phase models in FLUENT
• Replaces approximation of
solid phase in FLUENT with
explicit calculation of particle explicit calculation of particle
dynamics in EDEM
• Full two-way momentum and
energy coupling
• Various hydrodynamic models
are available, including drag,
lift and fluid-induced torque
• Standard heat transfer
models, such as Ranz &
Marshall are available
EDEM-FLUENT Process Flow
DEM timestep(s)
started at end of fluid
simulation timestep
Fluid iterated
Calls EDEM
Drag forces on particles
calculated using data
extracted from fluid mesh
cells
Forces on fluid from
particles are introduced
into fluid through a series
of momentum sinks
Fluid iterated
to convergence
Particle positions updatedParticle
positions input
into FLUENT
Some processes modelled using EDEM-FLUENT
Entrainment
Agglomeration
Suction
Pneumatic conveying
Entrainment
Drying particles
Pneumatic Conveying
• Pneumatic conveying is employed in various industries,
e.g. pharmaceutical, chemical
• “Plug flow” dense phase transport is widely used, as it is
known to cause less particle attrition, reduced
component wear and lower energy costs
• A paper titled “The simulation of pneumatic transport
within a pipe using a coupled DEM-CFD numerical
model” was presented by our engineer, Stephen Cole at
the 9th ICBMH conference 2007
Plug Flow Simulation
• Particles are packed at the inlet
• It is demonstrated that plug flow is modelled in
this simulation
Fluidised Beds
• Fluidised beds are an important process in various
industries
• They are used in several processes, e.g. fluidised bed
reactors, catalytic cracking, combustion, drying,
coating and etc
• In fluidised beds, due to the forces induced by the
incoming gas flows, the bulk solids exhibit fluid-type
behaviours, for example, free-flow under gravity
Fluidization
Gas Inlet
Fluidised Bed with Embedded Pipe
• A collaboration with the University of
Edinburgh
• Results presented at the International
Conference of Multiphase Flow ’07
Courtesy of Martin Crapper
Fluidised Bed with Immersed Hot Pipe
• The work is extended to
investigating effects of the
bubbles on heat transfer
• A hot pipe is immersed
within the fluidised bedwithin the fluidised bed
Courtesy of Stephen Whitelaw
Kiln Simulation
• Large of number of hot particles entering the kiln
• Temperature rises progressively at the top
Fluidised Bed Spray Granulation
• Fluidised bed granulation is one of the important
processes in powder production
• Improving the granulation efficiency has benefits to the
production line
• The capability of EDEM to model spray coating of • The capability of EDEM to model spray coating of
droplets with solid particles have been demonstrated
• By combining this capability with the coupling module,
we can model fluidised bed spray granulation
• Additional sub-models are needed to model granulation
Spray Coating
• Particles closed to the spray factory that have been sprayed with
droplets have increased mass, hence mass is shown conserved
Conserved Momentum
• Momentum is conserved where the particles hit by the droplets
have reduced velocity
Blocking of a tube with clumps
• Modelling the transportation of
assemblies of flexible bonded
particles in a fluid
Objectives
EDEM-FLUENT co-simulation
Objectives
• Investigation of breakup of bonded
particles relative to bond strength
and fluid flow rates
• Prediction of blockages relative to
size of opening, flow rate and
material properties
Powder Inhaler
• Entrainment of powder particles
from a bed using high speed air
flow
• Investigation of mass flow rate and
particle – geometry impacts
5.0E-06
1.0E-05
1.5E-05
2.0E-05
2.5E-05
3.0E-05
3.5E-05
4.0E-05
Mass Flow Rate (kg/s)
Objectives0.0E+00
0 0.01 0.02 0.03 0.04
Time (s)
Objectives
• Correlate particle impacts with loss of
active ingredient
• Determine effect of
geometry on flow transient
Courtesy of Pfizer, Inc
Particle drying
Particle drying
Packed-bed reactor
Steam-methane reforming
(catalyst + absorbent)
N=4 N=5 N=6 N=7 N=8
N: # particle diameters
0.6
Using EDEM as pre-processor for CFD
(Courtesy: S. Ookawara, Tokyo Institute of Technology, Japan)
0.2
0.3
0.4
0.5
0 0.1 0.2 0.3 0.4
ε (at top)
εmin
Jeshar
Leva & Grummer (clay)
dp / D
t [-]
Effect of catalyst-absorbent packing on heat transfer
Catalyst
Inert
(Courtesy: S. Ookawara, Tokyo Institute of Technology, Japan)