FLUENT 6.2Product Presentation

Multiphase and Chemical Processes

Mikael Stallgård, FLUENT SE

mas@fluent.se

Multiphase Modeling Capability- Overview -

Current Multiphase Models in FLUENTDispersed Phase Model

Steady and Unsteady particle trackingStochastic and Particle cloud model for turbulent dispersion Ability to include particle size distribution and include various forces and physics for particles (reaction), many UDF’s and post processing capabilities

Volume of Fluid ModelSolves for the interface between g/l and l/lAdvanced front tracking to resolve interfaceEffective for modeling the motion of large ( much bigger than grid) bubbles

Current Multiphase Models in FLUENTMixture model

A multi fluid model: Time dependent and 3D extension of drift flux modelCan effectively replace Eulerian Fluid/Fluid model where phases reach equilibrium fast.

Eulerian-Eulerian/Eulerian-Granular Multiphase ModelSolves momentum, enthalpy, and continuity equations for N phasesTurbulence models for dilute and dense phase regimes.

DEM3rd party integration (EDEM) for Lagrarian particle tracking withparticle-particle integration, may now be coupled with Fluent6.2

Multiphase – New features in 6.2

FLUENT 6.2

Multiphase Flows/Major Enhancement

Multiphase species transport and chemical reactionsSupport for all multiphase models Allows mass transfer between species in different phasesHeterogeneous reaction rates specified with UDF

Ozone Decomposition in a Fluidized Bed

Particles in a fluidized catalytic bed are used to convert ozone (O3) to oxygen (O2)FLUENT is used to study fluidization and reaction in a single simulationThe Eulerian granular multiphase (EGM) model is used with reactions in the gas phase

Ozone Decomposition in a Fluidized Bed

Rising bubbles of gas are predicted by the transient EGM calculationBubbles pass through bed surface and enter the gas space above

Ozone Decomposition in a Fluidized Bed

Gas phase reaction takes place in bed region onlyCout/Cin of ozone (1 –conversion) (pink) vs. gas velocity compares well with data (blue)

Saturation in gas holdup occurs when bed can no longer hold more gas, even at higher velocitiesFLUENT captures complex physics in a single simulation for this important industrial application

FLUENT 6.2

Multiphase Flows

Multiphase species transport and chemical reactionsSupport for all multiphase models Allows mass transfer between species in different phasesHeterogeneous reaction rates specified with UDF

Reynolds stress (RSM) turbulence model for dilute Eulerian multiphase flows

FLUENT 6.2

Multiphase Flows

Multiphase species transport and chemical reactionsSupport for all multiphase modelsAllows mass transfer between species in different phasesHeterogeneous reaction rates specified with UDF

Reynolds stress (RSM) turbulence model for dilute Eulerian multiphase flows

Extensions for the granular modelFull PDE for granular temperature Johnson and Jackson boundary conditionAdditional new options for granular property specificationSupport for granular model with mixture model

Multiphase/Mixture Model …

Mixture modelSecondary phase can now be granular

Applicable for solid-fluid simulationsSecondary phase cannot be “packed bed”

Granular physics added as followsAdd total granular pressure to momentum equationSolids viscosity available for dispersed solid phasePacking limit for solids Only algebraic granular temperature is availableApplicability is mainly for liquid-solids multiphase systems. Density difference should be small.

Slip velocity now contains dispersion due to turbulence.

Return

FLUENT 6.2

Multiphase/VOFVolume-of-fluid (VOF) model enhancements

Species transport and chemical reactions

More efficient front tracking, HRICHigh Resolution Interface Capturing (HRIC) schemeAllows larger time steps than geo-recon scheme

More diffuse than geo-reconProvides sharper interface than QUICKAvailable for structured and unstructured meshesApplication

Prediction of standing free surface waves in steady state

New open channel boundary condition

Support for inviscid flows

Improved surface tension robustness

Multiphase/VOF …

New HRIC scheme example of swirling fuel injector

First Order Implicit HRIC Implicit

Second Order Implicit

Interface Capture Using Implicit VOFVelocity Vectors Colored by Volume Fraction

Multiphase/VOF …

Experimental PhotographCourtesy of IIHR, U. of Iowa

Contours of Z Coordinate on Free Surface

Front tracking/open channel BC: Hydrofoil

FLUENT 6.2

Multiphase Flows

Discrete phase model (DPM) enhancementsNew wall film model

Particles impinge on a surface, splash and/or form a thin film

FLUENT 6.2

Wall Film Model: IC Engine

Wall Film Height (mm)Spray Colored by Particle Velocity

DPM …

Wall film modelParticles impinge on a surface and form a thin film

ImpingingFuel Droplet

Splashing

Fuel Film

Wall Conduction

ConvectiveHeat Transfer

Evaporation Shear Force Film Thickness

Flow separationand

Sheet Breakup

Ref. StantonInt. J. of Heat &

Mass Transfer (1998)

FLUENT 6.2

Multiphase Flows

Discrete phase model (DPM) enhancementsNew wall film model

Particles impinge on a surface, splash and/or form a thin film

Two-way particle-turbulence coupling

More accurate and efficient particle trackingNew tracking schemesError-controlled adaption of integration time-stepAutomated tracking scheme selection

FLUENT 6.2

Multiphase Flows

Target applications include:Bubble Column ReactorsFluidized Bed ReactorsAutomotive In-Cylinder FlowsSpray Nozzles and AtomizersShip HydrodynamicsFuel Injector Pumps

HydrocycloneSeparation of Solids

from Water

(Courtesy of M Slack

Fluent Europe)

Hydrocyclone Application

The experimental cyclone study carried out by Mondron et. al (1990) is used as a case study to validate the simulation approach

75mm diameter cycloneLimestone and water slurry with 10.47 % by weight solids with a size distributionOpen to atmosphere Air is drawn into the underflow and exits through the overflow via a stable air core.

Best Practice Modelling specific to Cyclones

The modelling challenges3 dimensional flow patternsAnisotropic turbulenceDispersed secondary phase

Both high and low volume loadingsSize distributionsParticle to Particle interactions

Low pressure central coreMay result in a backflow of gas (air core) in hydrocycloneUnstable flow structures may develop

Mesh Numerical sensitivityRadial Pressure distribution on over and underflow boundaries

Anisotropic Turbulence

+ k-epsilon, � RNG, –— RSM, ∆ experiment [LDA]

Tangential velocity Axial velocity

LES Cyclone Animations

Velocity magnitude Axial vorticity Velocity vectors

Transient flow structures

Multiphase Models

Air Core and Particle trajectories shown.

Multi-Phase Modelling (1) Lagrangian particle tracking

Effective method for quantifying separation performance.Can be carried out as a coupled calculation or as a post processing exercise.Must use sufficient particles to ensure insensitive result.Release position/distribution at inlet will is reflected in the predicted separation performance. In a steady flow field particles which may have only spent a fraction of a second in a toriodal re-circulation are held there indefinitely.Stochastic random kicks can be delivered to represent the effect of turbulent flow structuresDoes not account for the volume occupied by dispersed materialNo particle to particle interaction

Multi-Phase Modelling (2)

Algebraic Slip Mixture modelSolves a single set of momentum equations for both continuous and dispersed phases, (same velocity).Accounts for the occupied volume Can not simulate phases travelling in different directionsDispersed phase must achieve terminal velocity quickly

Computationally cheap Can be used to solve for air core but does not account for any interface effects, fluffy interface – cheap robust.Adequate when phases remain suspendedStruggles to resolve high dispersed phase concentrations at walls

Multi-Phase Modelling (3)

Eulerian-Eulerian-Granular modelThe most definitive multiphase model which solves a separate set of momentum equations for each phase.Accounts for high volume loadingsParticle to Particle interactionAccurate predictions of air core development

High CPU cost when combined with RSM turbulence equations.

RSM and Eulerian simulation results Cokljat et. al. 2003

Mondron cyclone simulated using RSM and Eulerian-Eulerianapproach, 5 phases simulated on 70,000 cells took 4 days to solve on 6 parallel CPU.

Validation (Test Case)

Tangential velocity at 2 locations measured using LDA compared to CFD predictions.

DPM particles (limestone) predicted separation efficiency curve compared to measured cyclone performance

Flow split

CFD 9%

Experiment 8.48

Templates

What are Templates?

Templates = process automation toolsEasy-to-use, customized interfacesRun GAMBIT and FLUENT in the backgroundAddress specific applications, customized and fine-tuned for your specific processesFacilitate the CFD process for both CFD engineers and non-CFD engineers

Templates do not replace the role of the expert analyst in defining the process, exploring the limits and fixing any problems.

Why Templates?

To increase productivity To enable broader use of CFDTo standardize processes

Increased Productivity

Automate & streamline any repetitive portion of the CFD analysis processSave time of CFD experts for more advanced CFD analysis projectsReduce turnaround time, to enable many more CFD calculationsMake parametric calculations possible, for studying design modifications

Broader Use of CFD

Use CFD in the design processUse CFD with optimization

Objective functions can be implemented in a template to perform optimization tasks

Enable any degreed engineer to use CFDNo knowledge or training of the supporting packages (GAMBIT,FLUENT,TGrid) is requiredA few analysts can support or supervise the work of many design engineers or process engineers

Standardize Processes

Capture engineering / process knowledgeExpert knowledge is embedded in the templateBest practices are built in, to ensure a better solution and faster convergenceOptimum mesh topologies are hardwired

Ensure process consistencyA standardized CFD process produces results independent of the userGet comparable results from every regional office

Example: Cyclone template

Which methodology do you want ?Physics vs. computational cost, complexity & stabilityFor design

Appropriate geometry description (circular inlet for demonstration only) RSMConstant slurry density with ASMM air core predictionDPM post processing used to calculate the separation performance.The tool automates the set up running and reporting of the results

Variety of cyclone geometries easily created using scripts

Maintenance & Evolution

Initial template version is based on current ‘best practices’ for given objectivesTemplates will need to evolve over time

‘Best practices’ may improve because of added knowledge from using the templateObjectives may changeGAMBIT and FLUENT will change too

Template maintenance is part of the service provided by Fluent Consulting

Future Modelling Developments

Future Activities

New solver technologiesInvestigation on different matrices - coupling

AccuracyHigher order schemes for time dependents problemNeed to reproduce convection without excessive numerical smearingNeed to account for time limitation in higher order spatial discretization.

Future Activities

Investigation on time dependent algorithm Need to reduce dramatically the computational time for large industrial cases.

Fractional steps methodMixed Implicit-Explicit SchemesPISO

Future Activities (DPM)

Improve robustness of current DPMExtend to dense multiphase flows

Interpolate particle properties to the gridInclude volume fraction in the continuous phase

Include particle normal stressImprove coupling with the continuous phase for a robust solution

Intelligent ParticlesHandle Polydispersed granular flows

Single Fluid Approach

Mixture, VOF and Cavitation Model will benefit from the transient Non Iterative Algorithm (NITA) Continuous improvement on physical modelling, accuracy and boundary conditions

Granular Flow Regimes

Kinetic theorySolid mechanicsElasticity

Stress is strain dependent

Stress is strain independent

Stress is strain dependent

Rapid flowSlow flowStagnant

ViscousPlasticElastic

Future Activities

Currently the granular model is applicable to the viscous regimeExtend validity of the model for frictional and elastic regime

Frictional ViscositySolids pressure and volume fraction relationshipHypoplasticity models

Binary models for viscous regimePolydispersed models for viscous regime

Turbulence in Multiphase

Models available in FLUENTMixture model, solves two equation turbulence model based on the mixture of all phasesDispersed Model, solves two equation turbulence model for primary phase and assumes turbulence quantities for dispersed phaseFull Κ−ε model for each individual phaseMixture Reynolds stress model Dispersed Reynolds stress model

Developments in Turbulence

Most model are just a simple extension of single phase modelsStarting from fundamental equation for the Reynolds stresses in multiphase develop Explicit Algebraic Stress Models capable of capturing the connection between the phases in the eddy viscosity formulation.Improvement on the modelling of dispersionImprovement in the RSMLES for multiphase

Population Balance

This is a critical component in modeling particulate systemsDispersed phase systems play an important role in many industrial production processesThree models are available for one dispersed phase

Discretization MethodStandard Method of MomentQMOM

Improvements on the kernels for aggregation, breakage and growthExtend to n phase

Data Structure for Multiphase ModelsData Structure in multiphase models involve multiple domains:

Super Domain: This is the top-level domain contains all phase-independent and mixture data: geometry, connectivity, propertySub-Domains: Each phase has a sub-domain that inherits the mixture-specific data and maintains the phase-specific dataInteraction Domain: To activate the phase interaction mechanisms

Sub-Domains

Threads

InletFluid-2

Fluid-1

Solid-1

OutletPorousMedium

Solid-2Wall

Threads

InletFluid-2

Fluid-1

Solid-1

OutletPorousMedium

Solid-2Wall

Threads

InletFluid-2

Fluid-1

Solid-1

OutletPorousMedium

Solid-2Wall

Interaction Domain

InletFluid-2

Fluid-1

Solid-1

OutletPorousMedium

Solid-2Wall

SuperDomain

Threads

Primary PhaseDomain

Secondary PhaseDomains

Sub-Threads

Coming Soon: FLUENT 6.3

FLUENT 6.3: Current Status

New feature versionImportant new core numerics functionality Enhanced physical modeling capabilitiesCustomer-requested enhancements

Development is currently underwayRelease is estimated for late 2005

Let’s preview the new core numerics functionality that we are working on in FLUENT 6.3…

FLUENT 6.3

New Core Numerics Functionality

Support for polyhedral meshesAutomatic cell agglomeration in the solverReduces original tetrahedral mesh by 3-5x

Results in faster convergence

Original tet/hybrid mesh: 51,467 cellsNew polyhedral mesh: 16,908 cells

FLUENT 6.3

Polyhedral Mesh: Simplified Sedan

Static PressureMesh

FLUENT 6.3

New Core Numerics Functionality

Support for polyhedral meshesAutomatic cell agglomeration in the solverReduces original tetrahedral mesh by 3-5x

Results in faster convergence

Pressure-based coupled solverImproved convergence and robustness for skewed/stretched meshes and “stiff” problemsConvergence rates not sensitive to mesh sizeLittle need to change relaxation factorsAbility to switch on-the-fly to fully segregated solver

FLUENT 6.3

Pressure-Based Coupled Solver: Propeller

2482101300Segregated (FLUENT 6.2)

4141360P-V Coupled (FLUENT 6.3)

Memory (MB)CPU (min)Iterations

Static Pressure

Solver Performance ComparisonMesh size: 172,000 Cells