Multiphase Modeling Using

EDEM-CFD Coupling for FLUENT

Nicolas Spogis, Ph.D.

Business Coordinator

E-mail: nicolas@esss.com.br

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)