Multiphase Models in
ANSYS CFD
© 2011 ANSYS, Inc. May 14, 20121
Gilles Eggenspieler
Senior Product Manager
Which Reactor is Better?Depends!
© 2011 ANSYS, Inc. May 14, 20122
When gas dissolution is important
Higher hold up!
Solid catalyst particles
Much better mixing!
ANSYS CFD: A Platform for Modeling Multiphase Flows
© 2011 ANSYS, Inc. May 14, 20123
Multiphase flow involves the simultaneous flow of two or
more immiscible interacting phases
Many industrial processes involve multiphase flow
• Gasoline sprays in automobile combustion engines
• Gasification and coal combustion in power plants
Introduction
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• Gasification and coal combustion in power plants
• Fluid catalytic cracking in refineries
• Aeration in water treatment plants
• Icing on aircrafts
• And several others …
Engineering operations often involve “non-spontaneous”
processes
• Mixing -- Keep a mixture of components that separate
naturally, mixed. Desire to improve contact between the
phases to improve and enhance interfacial transfer processes
• Separation -- Need to separate components that are difficult
Challenges Involving Multiphase Flows
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• Separation -- Need to separate components that are difficult
to separate, such as fine dust from flue gases
Flow dynamics crucial to the efficiency of these processes
Non-linear effect of parameters and geometry on
processes
Lower Dimensional Simulations
Tools like Aspen, HYSYS, gProms
• Quick
• System wide simulation
Need to be supplemented with
detailed engineering analysis
• Engineering anomalies
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• Engineering anomalies
– Flow mal-distribution, hot spots,
stress concentrations
• Insights on off-design performance
• Effect of geometry
The Need for Detailed Simulations
• Include all relevant phenomena
• Effect of inlets, outlets, internals
and other geometric details
captured
• Scale independent
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• Scale independent
• Qualitative and quantitative
information
What is the engineering
problem of interest?
What is the flow regime?
• Length scale of interface in
relation to the domain?
• Regime change?
Appropriate Models for Multiphase Flow
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• Regime change?
Other important physics?
• Impact of flow on size?
• Heterogeneous and
homogeneous reactions
Length scale of equipment - L
Length scale of flow that is resolved (mesh) – l
Interfacial length scale (droplet or bubble size) – d
• l >> d
– Dispersed flow
Modeling Multiphase Flows
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– Dispersed flow
– Droplets, bubbles or particles unresolved!
– Need to model interactions (momentum, heat and mass)
• l << d or d ≈ L
– Separated flow
– Interfacial interactions resolved as part of solution
Separated or Dispersed?
Bubble columns
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Fluidized beds
Separated or Dispersed ?
Sprays
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Separated
flow
Dispersed
flow
Multiphase Models in ANSYS CFD
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VOF MPMEulerian model
Lagrangian models
Multi-fluid VOF Model
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Regime change caused by phase change processes
• Evaporator
• Single phase liquid � Bubble � Slug � Droplet � Single
phase vapor
• Almost all gas-liquid multiphase flow regimes
Different phases have different length scales
Some Flows are Difficult to Classify …
Drops
Drop –
Annular
Annular
Slug –
Annular
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Different phases have different length scales
• Big gas bubble moving through a slurry of fine solids
Include regime transitions
• Change in flow conditions causes change in flow regime
• Bubbles coalesce to form big slugs!
Annular
Slug
Bubble –
Slug
Bubble
Liquid
Adds interfacial sharpening schemes (between selected
phases) in an Eulerian framework
• Includes physics relevant to both sub-grid and super-grid
particles
• With some additional modeling shows potential to model
some regime change processes
Multi-fluid VOF Model
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some regime change processes
Big Bubble Moving Through a Slurry
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Capable of modeling both regimes
Physics in the dispersed region
• Wall lubrication
• Sub-grid scale drag models based on predicted diameter
Physics in the stratified region
Multifluid VOF Model for Regime Transitions
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Physics in the stratified region
• Surface tension
• No-slip at the interface
Demarcation between the two regions identified based
on the a transition air volume fraction
Population balance model
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A Success Story
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Trouble-shooting a Regenerator
Unit not performing to expectations
Increase capacity and ability to lower quality feed
Enriched air with oxygenHeat removal by a flow
through cooler
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Several attempts to improve operations failed.
3000 bpd of lost throughput
http://www.bp.com/genericarticle.do?categoryId=9013612&contentId
=7021456
Spent catalyst from
standpipeCatalyst offtake to
cooler
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Oxygen enriched air Catalyst returning
from cooler
From Asia-Pac. J. Chem. Eng. 2007; 2: 347–354
CFD simulations showed
• Gas by passing
• Regions of low temperature
• Oxygen escaped in the form of bubbles
Cause: Catalyst re-entry to the regenerator.
Results from Simulations
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From Asia-Pac. J. Chem. Eng. 2007; 2: 347–354
Having burnt their finger once …
Simulations done to evaluate proposed modifications
• A different re-entry point
• Gas sparged in a different direction
Designing a Remedy
© 2011 ANSYS, Inc. May 14, 201223From Asia-Pac. J. Chem. Eng. 2007; 2: 347–354
With the Changed Design
© 2011 ANSYS, Inc. May 14, 201224From Asia-Pac. J. Chem. Eng. 2007; 2: 347–354
Volume fraction of bubble
Multiphase Deep Dive
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→ Efficient modeling of poly-disperse
systems
→ DDPM, population balance
→ Enhanced mixed mode (Eulerian and
Lagrangian) models
Today Multiphase Drivers
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→ DDPM, Eulerian wall film model
→ Enhancements to boiling models
→ CHF modeling, user enhancements
→ Numerical enhancements for robust
convergence
→ Various models
Polydisperse System
Modeling
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Framework to track dense
dispersed phases in a Lagrangian
framework
• Fluidized beds, risers, dense cyclones,
bubble columns etc.
Particle-particle interactions
DDPM
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Particle-particle interactions
• Collision breakup model for droplets
• Expression for solid pressure – KTGF
• Explicit particle interaction – DEM –
Valid up to the packing limit
• Other models …
Efficient for poly-disperse particles
KTGF based collision
DEM based collision
NETL bubbling fluidization challenge
Effect of PSD on fluidization quality
• The full PSD is represented with
approximately 0.5 million parcels
• Mean particle diameter 85 and 88
DDPM Examples
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• Mean particle diameter 85 and 88
microns
• With 12% fines, fluidization is uniform
• With 3% fines gas by-passing is observed
and fluidization is not uniform
16 s of flow time on 12 nodes in a day
12% fines 3% fines
Other DDPM-DEM Examples
Transport of proppants in fractures
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Flow of particles with a hopper Mass of particles remaining in the hopper
Brazil Nut Effect
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DQMOM as a full feature
• Predicts segregation of particles in a
poly-disperse mixture
• Can account for growth and breakup
of size classes
Target applications
Population Balance Models
Velocity big bubbles >
velocity small bubbles
All bubbles move with
same velocity
DQMOM QMOMg
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Target applications
• Fluidized beds, gas solid flows, spray
modeling, bubble columns
PB models account for bubble
expansion
Growth and nucleation in
inhomogeneous discrete model
Mixed Mode Modeling
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Engineering problems that include a dynamic and flowing
thin liquid film
• Aircraft icing and runback analysis
• In-cabin condensation
• Wall film on combustor walls
Eulerian Wall Film
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• Wall film on combustor walls
• Annular flow regime in gas-liquid flows
Eulerian Wall Film Model
• Solves for film mass, momentum, heat transfer
• Particle/Phase collection, film formation, transportation, Splashing ,Separation,
Stripping.
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• Eulerian wall film can be coupled with Eulerian-Lagrangian(DPM)
and Eulerian-Eulerian multiphase frame work.
• Available only with 3D solver
Eulerian Wall Film : Modeling Capabilities
1. Coupling with Discrete Phase Model (DPM):
• Solve Film Equation (Mass, momentum & Energy Transfer)
• Particle Collection
– Particles are released from upstream surface
– Particle get collected on the surface & sources to the wall film transport equation will
be added.
Soiling of a Car Body
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• Particle Splashing
Particle Tracks from the
surface upstream
Mass Sources formed due to
particle impingment
Soiling of a Car Body
Eulerian Wall Film : Modeling Capabilities
1. Coupling with DPM:
• Film Separation & re-release of droplets
– The film can separate from an edge if two criteria are met:
1) The angle between faces is sufficiently large
2) The film inertia is above a critical value (defined by the user)
• Film stripping & re-release of droplets
Wef = (Vf2* H
f* ρ
f)/σ
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• Film stripping & re-release of droplets
– Film stripping occurs when high relative
velocities exist between the gas phase and
the liquid film on a wall surface.
– Film can separate if wall shear stress exceeds
film shear Weber number.
• Particle Splashing
• EWF coupling with DPM is automatic :
– for example, particles get released from separation
points with automatic injection
Incoming
Particles Splashed
Particles
IPS Simulation: Car Mirror Simulation
Stripping based on Critical Weber Number criteria
Film Thickness
Stripping Weber Number
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Stripped Particles
Eulerian Wall Film: Modeling capabilities
2. Coupling with Species transport
• Mass transfer (condensation)
• Example:
• Dry air and water vapor flow over the the wall which is at or below the saturation
corresponding to the partial pressure of water vapor at the surface.
• Water vapor get condensed on the wall & form the film
• Air mass fraction, water vapor mass fraction, film height, film temperature etc. can be post
processed
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processed
3. Coupling with bulk flow & solid thermal modeling
• Implicit numerical treatment
• All types of thermal boundary condition:
CHT, Fixed temp, Fixed heat flux…
Liquid
Droplets
Eulerian Wall Film: Modeling Capabilities
4. Coupling with Eulerian Multiphase model:
Application to Running Wet Analysis
• Two Phases are modeled with Eulerian-Eulerian multiphase model
• Air as primary phase & Liquid droplets as secondary phase
• 2nd phase flux normal to the wall boundary removed at the walls where film model is
on & liquid film formed from the removed 2nd phase
• Liquid film modeled with Eulerian wall film
• Liquid film can separate & stripped off & re-release of droplets.
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• Liquid film can separate & stripped off & re-release of droplets.
• To see the separated and stripped particle user need to :
– Unable separation and stripping along
with DPM collection
– Define dummy DPM injection
Liquid Volume Fraction
Boiling Model Enhancements
Critical Heat Flux (CHF) modeling
• Boiling in a vertical pipe with large heat fluxes
• Causes burn out of the liquid film next to the wall
• Flow transitions from bubbly to mist flow
The CHF model
• Accounts for correct heat transfer partitioning at CHF
conditions
Wa
ll T
em
pe
ratu
re
Hoyer’s et. al
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conditions
• Accounts for the variations of drag and interfacial quantities
to move from bubbly to droplet regimeAxial Position (m)
Wa
ll T
em
pe
ratu
re
Inlet mass flux 1495 kg/m2s
Qwall = 797kw/m2
Boiling Model
Enhancements
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Critical heat flux model
– Modeling of departure from nucleate boiling, dry-out
Quenching correction
– Grid independent solutions
Ability to customize boiling sub-models
Advances to the Boiling Model
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Ability to customize boiling sub-models
– UDF hooks for bubble departure frequency, diameter and
nucleation site density
Coupling with the IAC model
Validations for the CHF model
Experimental data from Hoyer
• Area of influence – Kenning
• Bubble departure frequency –
Cole
•Turbulent drift force - Simonin
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Non-uniform wall heat flux
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RPI paper validation case
Vertical pipe
Length: 2 m
Diameter: 15.4 mm
Heat Flux: 570 kW/m2
Mass Flux: 900 kg/m2-s
Operating pressure: 4.5 Mpa
Results from Bartolomei experiments
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Temperature in KVoid fraction
0.0
0.1
0.2
0.3
0.4
0.5
0.0 0.5 1.0 1.5 2.0
Experiments
ANSYS CFD (Fluent)
RPI_paper
Axial distribution of Average void fraction
Continuum Stress Surface Method
• More flexibility in cases involving
variable surface tension
• Surface tension can be a function of
any variable, including temperature
• No explicit modeling of Marangoni
Volume of Fluid Model Enhancements
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• No explicit modeling of Marangoni
effects required
• Expected to be useful in cases where
the Continuum Surface Force
formulation may be difficult to
converge
Images from :Thermally Induced Marangoni Instability of Liquid Microjets
with Application to Continuous Inkjet Printing by Furlani et
al.
Coupled Solver
• Pseudo-transient solver
• Coupled VOF
• Faster & automatic convergence
• Steady state solutions
Numerics Enhancements (Eulerian)
Coupled VOF after 500 iterations
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Coupled P-V, Segregated VOF
after 1400 iterations
DEM model
• Better particle tracking algorithms
• Works with all mesh types
• Fully parallelized (insensitive to partitioning)
DDPM model
Numerical EnhancementsLagrangian Models
Particles where sphere size
changes with diameter and
particle velocity vectors
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DDPM model
• Bug with particle-fluid interaction fixed (correct pressure drop)
• Node based interpolation of source terms
– Helps in all cases, especially in tetrahedral meshes and “big”
particles
Post processing
• Filter how particles are displayed
• Spheres with different sizes
• Associate velocity vectors with particles
Particles filtered by flow velocity
between 10 and 11 m/s