Combustion Modeling Tools in CFD

7/22/2019 Combustion Modeling Tools in CFD

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2011 ANSYS, Inc. October 4, 20111

Combustion Modelling

Tools in CFD Present and Future

Phil Stopford

ANSYS UKPresentation to the DANSISSeminar on Combustion and

Reactive Flows, DONG Energy

Power, Denmark, 5th Oct. 2011


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Contents

Overview of combustion and reacting flow models

Applications illustrating recent trends:

Scale resolving turbulence models

Coupled models of reacting flows

Combustion models in fire simulation

Multiphase reacting flows

Recent developments

ConclusionsQuestions


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Progress since 1980

Computing power increaseHow big a calculation can I run over night?

- In 1980: Steady RANS case with 5k cells on mainframe supercomputer

- In 2011: Transient LES case with 10m cells on 500 parallel nodes

CFD software improvements

- Over-diffusive numerical methods (e.g. SIMPLE, RANS) superseded

- Better resolution of transient phenomena

- Coupled solvers giving better convergence

Physical/Chemical knowledge increase

- Better insights into turbulent flame dynamics, chemical mechanisms

- Laser-based non-intrusive diagnostics


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Fast Chemistry Combustion Models

Eddy dissipation

Uses reduced chemistry reaction mechanisms Overall rate is minimum of turbulent mixing rate and chemical reaction rate Applicable for all types of flame

Non-premixed

Use mixture fraction,f, and assumed PDF for fluctuations off, instead of solving speciestransport equations and reacting rates for equilibrium chemistry

Laminar flamelets for moderate non-equilibrium chemistry

Premixed

Reduce chemistry to reaction progress variable, c c equation model Burning Velocity Model (BVM)

Also called Turbulent Flame speed Closure (TFC) model

Requires a turbulent flame speed correlation, e.g. Zimont, Peters, Glder

Enhanced Coherent Flame Model (ECFM) Solves a transport equation for the flame surface per unit volume

Partially premixed

Combine non-premixed and premixed models

Assumptions in both models apply


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Finite Rate Chemistry Models

Laminar Finite Rate Model Stiff chemistry solvers Applicability of the finite-rate model

Flow regime: Laminar flow

Chemistry: Finite-rate chemistry

Flow configuration : Premixed, non-premixed, partially premixed

Eddy Dissipation Concept (EDC) model

General model of turbulence-chemistry interaction Reactions take place in hot turbulent micro eddies

Compositional Transport PDF

PDF transport equations solved by Monte Carlo method

Mean reaction rate dTdYdYPww Nkk 10

1

0

1

0


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Scale Resolving

Turbulence Models


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Evolution of Turbulence ModelsURANS

Gives unphysical single mode unsteady behavior

LES (Large Eddy Simulation)

Too expensive for most industrial flows due to high resolutionrequirements in boundary layers

DES (Detached Eddy Simulation)

First industrial-strength model for high-Re with LES-content

Increased complexity (grid sensitivity) due to explicit mix of twomodelling concepts

SAS (Scale-Adaptive Simulation)

Extends URANS to many technical flows

Provides LES-content in unsteady regions

Von Karman length scale occurs naturally in formulationWMLES (Wall Modelled LES)

Analytic wall function for viscous sub-layer

Zonal LES

Only apply LES in the critical flow region RANS elsewhere

URANS

SAS-URANS

22 /

/

yU

yULvK



Zonal LES: Model description

Model workflow

(U)RANS solution

User-defined LES zone

kRANS




Model workflow

(U)RANS solution


Source term in k-eqn. inside the LES zone:

C (kLES kRANS)C big factor

Ensures LES eddy

viscosity in LES zone

kRANS kLES




Model workflow

(U)RANS solution




Ensures LES eddy


Momentum sourceat RANS-LES interface

to enforce fluctuationsActivatedsimultaneously

kRANS


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Model workflow

(U)RANS solution




Ensures LES eddy


Momentum sourceat RANS-LES interface

to enforce fluctuations

Low-turbulence part is

cut off automatically:

tsensitive limiter

kRANS


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Near-wall modification: wall modelled LES ( WMLES )

Uses RANS in the inner part of the log layer

Enforces correct (high) turbulent K.E. near the wall

Mesh density at wall independent of Reynolds number

Practical LES method for industrial internal flows


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SAS: Gas-Fired Combustor Validation

Refs. Schildmacher, K.-U., R. Koch, R., ASME-Paper GT2003-38644, 2003, and

Schildmacher, K.-U., Koch, R., Wittig, S., Krebs, W., Hoffmann, S., ASME-Paper 2000-GT-0084, 2000.

Single burner configuration:

Swirl burner of an industrial gas turbine Mounted in rectangular combustion chamber Lean premixed main inlet (methane/air,

preheated)

Axial dilution air (preheated) Atmospheric pressure

Experimental data:

Isothermal: x = 44, 138, 257 mm Reacting: x = 42, 79, 103, 136, 259 mm

Temperature, velocity

Simulation: SAS-SST, EDM, 3.6M cells, 0.1s


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Simulation Results


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Axial Velocity

1.5 mm

2.5 mm

5 mm

7.5 mm


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Temperature

5 mm

10 mm

15 mm

20 mm


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Methane Mass Fraction

5 mm

10 mm

15 mm

20 mm


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Flame Front Dynamics

Iso-surface of premixed flame front coloured

by temperature


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Combustion Instabilities

In gas turbines applications, combustion instabilities can be described as

unsteady flow and pressure fields motion driven by the combustion process.These instabilities are one of the most challenging problem in the development

of gas turbines (especially for land-based fully premixed systems)

The negative effects of combustion instabilities are varied:

Vibration (increased metal fatigue possible structure failure)

Enhanced heat transfer

Reduced operating performance

Deterioration of the pollutant emission performances

Pressure waves impact the:

Turbine

Compressor

Fuel feed


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7th Framework Programme of European CommunityMarie Curie Initial Training Network - LIMOUSINE:

Limit cycles of thermo-acoustic oscillations in gas turbine combustors

Simulation of fluid-structure interaction

Project coordinator, Dr Jim Kok, University of Twente (NL)Keele University (Staffordshire, UK)

Imperial College (London, UK)

CERFACS (Toulouse, France)

Brno University of Technology (CZ)

University of Zaragoza (Spain)

DLR (Stuttgart, Germany)

Ingenieurbro fr Thermo-Akustik (Munich, Germany)

Siemens Power Generation (Mlheim, Germany)

Electrabel/Laborelec (Brussels, Belgium)

ANSYS (UK)

Duration: 4 years from 1st Oct 2008

3 experienced researchers (post doc) and 17 early-stage researchers


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LIMOUSINE Test Burner

Rijke tube test burner at 4 different laboratories

2-D slice of the whole burner

Power ratings: 40 and 60 kW

Air factors, : 1.2, 1.4, 1.6 and 1.8

Structured hexahedral mesh of 37,500 elements SAS-SST and LES scale resolving turbulence

models

Two-step EDM and BVM combustion models

Predictions:

short flame stabilized on the wedge

strong pressure oscillations for < 1.6


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Transient CFD Results

Two peaks at frequencies of

about 240 and 700 Hz

Lower intensity and quenching

for > 1.4


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CFD Results Profiles of resonant modes

Downstream region drives the instability

Weak coupling with upstream wavelength

mode reduces the frequency slightly

Higher resonant frequency consistent with

wavelength mode


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CFD Results v Experiment

power

[kW]

air factor

[-]

pressure oscillation frequencies

[Hz]

simulation simulationendcorrected

experiment 1 experiment 2 analyticaldownstream

analyticalfull

40

1.2 247 234 230 235 258 186

1.4 242 229 217 217 246 183

1.6 238 226 stable stable 241 181

1.8 216 205 stable stable 232 178

60

1.2 280 266 268 268 259 187

1.4 251 238 248 262 249 184

1.6 228 216 stable stable 243 182

1.8 225 213 stable stable 236 179

power

[kW]

air factor

[-]

pressure oscillation amplitude

[Pa]

simulation experiment 2

401.2 1539 743

1.4 1596 862

601.2 2940 3138

1.4 2312 2305

Lowest resonant frequency in

reasonable agreement betweenCFD, experiment and wavelength

mode in downstream section (within

10%)

Amplitude of resonance also of

correct magnitude


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Modal StaticStructural modal frequencies[Hz]

full liner

bending

back-and-forth

117 152

bending

lateral255 331

torsion 531 606

2nd

bending638 -

plate 672 667

2nd plate 734 728

Conclusions:

Symmetric mode fundamental at 670 Hz

Window structure does not influence the plate modes

Structural modelling


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2011 ANSYS, Inc. October 4, 201126 Work

package:2.5

Tufano/ Stopford

Two-way coupling:

1) Fluid to solid force transfer2) Solid to fluid strain transfer

Solid deformation ~ microns does

not affect fluid flow in this case

Results:

Structure response is dominated by

wavelength forcing pressure at 670 Hz

as measured in experiment

Definition of damping is important

Fluid-Structure Interaction


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Double Skin Impingement

Cooled CombustorMain Burner

Pilot Burner

PreChamber

Radial Swirler

DLE Burner and Combustor Technology

Courtesy of Siemens Industrial Turbomachinery Ltd.


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Transient CFD analysis

Combusting cases:

Case 1 without casing

Case 2 with casing

Numerical models:

2-step Eddy Dissipation Model

SAS turbulence model

Compressible solver

without casing

Case 1:

9M tet/prism elements

with casing

Case 2:16M tet/prism elements


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Transient Combusting Simulation

PressureTemperature

Case 2: Aerodynamic and combustion instability in caninduces pressure fluctuations in casing


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Effect of Casing

Casing influence

Without casing With casing


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Precessing Vortex Core (PVC)

A PVC of a double helical structure has been

identified in non-reacting case

The frequency based on Strouhal number is 411

Hz compared to the CFD prediction of 432 Hz

PVC is NOT the most serious source of

instability as it is almost destroyed by

combustionCFD predictions, non-reacting case

Experimental results, non-reacting case

Data from SGT-100 tested at German Airspace Centre DLR


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Comparison with engine test data

Good agreement with theexperimental data.

Major shift in frequency

assumed to be due to

simplifications

Wide frequency peak in

CFD is due to limited

number of running cycles

Ref. G Bulat et al, Paper GT2009-59721, Proc. ASME TURBO Expo 2009: Power for Land,

Sea and Air, June 8-12, 2009, Orlando, FL.


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Coupled Models


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Coupling CFD to a boiler model

Modern 800 MWe coal-fired boilers in South Koreamust manually optimise burner and furnace

settings for each coal blend

CFD model can show how heat flux changes with

burner/furnace settings

1-D boiler model will give plant efficiency as function

of heat fluxes

Therefore models

must be coupled to

simulate the

complete plant

Courtesy of KEPRI and KOSEP


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Coal Furnace/Boiler Interface

Link made between CFX and a steam-side boiler model, PROATES Off-Line fromE.ON

Wall Heat

Flux

Wall

Temperatures

CFX PROATES

Courtesy of E.ON Engineering


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CFX Model

Conventional CFX pulverised coal model Lagrangian particle transport model

One-step devolatilization

Inhomogeneous char oxidation

Discrete transfer radiation

NOx post-processing

Coal sulphur model

Computational time: 24 hours on 2 dual processors (Xeon 5500s)


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Validation Results

Plant data PROATES CFX

Final S/H steam out pr. (bar)

Final S/H steam out temp. ()

Final R/H steam out pr. (bar)

246.2

566

40.46

246.3

566

40.54

Final R/H steam out temp. () 567 579

Evaporator steam out temp. () 411 405

Final R/H spray water flow rate (kg/s) 4.1 7.8

After Secondary Economiser:

Water out temp. () 336 336

Gas exit temp. (

) 380 378 387

Gas exit O2 (molar fraction) 0.0341 0.0356 0.0364

Gas exit CO (molar fraction) 8 10-6 3 10-6

Gas exit SO2 (molar fraction) 1.79 10-4 1.82 10-4

Gas exit NO (molar fraction) 2.19 10-4 2.19 10-4


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Measured and Predicted Heat Absorption

Heat absorption (MW) Plant data PROATES

Final S/H tube bank 137 137

Platen S/H tube bank 139 149

Division S/H tube bank 294 287

Secondary Economiser tube bank 124 125

Final R/H tube bank 158 156

Low temp. R/H tube bank 198 199

Water wall 674 678

Total 1,724 1,731


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CFD Results & Summary

Combined model used fully-coupled, in one-way coupling mode or in standalone mode

as appropriate Software currently used for:

What-if questions

Troubleshooting

Engineer training

Ref. H-Y Park et al., Fuel, Vol. 89, Issue 8, pp 2001-2010, Aug 2010 -


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Fire and Structural Integrity

U.S. Federal Building and Fire Safety Investigation of the World Trade Center Disaster, NIST J. Hill

http://www.nist.gov/public_affairs/ncstmin_dec2-3.htm

MN

MX

-42.11-37.357

-32.603-27.849

-23.095-18.342

-13.588-8.834

-4.081.673211

Vertical displacement contour at 700 C

Comprehensive investigation of the collapse of the

World trade center have revealed the Fire-Induced

Thermal Stress and Structural Failure Analysis.

Fire below steel I-beam and concrete roof as a

two-way fluid-structure interaction

J.Penrose & Y. Sinai, Interflam 2010
http://www.nist.gov/public_affairs/ncstmin_dec2-3.htmhttp://www.nist.gov/public_affairs/ncstmin_dec2-3.htmhttp://www.nist.gov/public_affairs/ncstmin_dec2-3.htmhttp://www.nist.gov/public_affairs/ncstmin_dec2-3.htm


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Coupling of ANSYS to Process SimulationSoftware

APECS: Advanced Process EngineeringCo-Simulator

Funded by US DOE with partners

including NETL, Aspen Technology

and ALSTOM

Two-way data exchange throughstandard CAPE-OPEN interface

Compliant with Aspen Plus, Aspen

HYSYS, ChemCad, COFE, gPROMS,

ProSim Plus, UniSim Design,

INDISS, PRO/II

Reduced order models based of neural

networks and principal

component analysis

Examples of CFD models

linked to Aspen Plus


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Combustion models on

fire simulation


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Droplet trajectories coloured by residence time

Courtesy of Nanomist Systems LLC, US

Large water droplet (150m) mass fraction

Efficiency of fire suppression device is critical

to minimize fire impact as soon as it is detected

Droplet size modeling in possibly complex

geometry are simulated by our users in order to

optimize the location and the effectiveness of

fire suppression equipment

Temperature iso-surfaces and droplet trajectories before

extinction, in a ships machinery spaceBritish Crown Copyright 2007/MOD.

Published with the permission of the Controller of Her Britannic Majesty's Stationery Office

Fire Suppression


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European Commission Firenet project

Combination of modified EDM and detachededdy simulation (DES) turbulence model

Good agreement with experiment

Horvat et al, Comb. Sci. Tech. 2008

AnimationTemperature, fireball

Simulation of Backdraft


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Multiphase Reacting

Flows


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Two stage, up flow, prototype entrained flow gasifier

Models used in the simulation

Discrete Phase: Lagrangian particle transport

Turbulence: Standard k- model

Radiation: Discrete Ordinates model

Reactions: Finite Rate/Eddy Dissipation model

Stochastic tracking: Discrete Random Walk model Operating pressure 2.84 MPa

Boiling point of water 502K

Coal, water and oxygen inlets

Oxygen + Nitrogen 2 x 11.44 kg/s, 440K

Oxygen mass fraction 0.944

Fuel (Combustible Discrete Phase)2 x 10.93 kg/s, 450KWater (Evaporating Discrete Phase)2 x 4.53 kg/s, 450K

Coal, water inlet

Fuel (Combustible Discrete Phase) 6.17 kg/s, 450K

Water (Evaporating Discrete Phase)2.56 kg/s, 450K

Outlet Pressure outlet

Post processing

surface

Entrained Flow Gasifier


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Heterogeneous (particle surface) reactions

Char oxidation

C + O2 CO2 CO

2

gasification

C + CO2 2 CO H2O gasification

C + H2O CO + H2

H2 gasification

C + 2 H2

CH4

Reactions

Homogeneous reactions

CO combustion

CO + 0.5 O2 CO2

Water-gas shift

CO + H2O CO2 + H2

CO2 + H2 CO + H2O

H2 combustion

H2 + 0.5 O2 H2O

CH4 combustion

CH4 + 1.5 O2 CO2 + 2 H2O

CH4 reforming

CH4 + H2O CO + 3 H2

CO + 3 H2 CH4 + H2O

Tar combustion

TAR + CO n CO2

Volatile break-up (Volumetric reaction)

Volatile a CO + b H2S + c CH4 + dH2O + e H2 + f N2 + g TAR


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Test Results

Carbon Monoxide (CO)

Carbon Dioxide (CO2) Water Vapor (H2O)

Static Temperature

Species Mass Fraction

CO 0.614

H2O 0.285

N2 0.028

CH4 0.039

H2 0.005

CO2 0.014

H2S 0.015

Syngas Composition at outlet


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DOE-NETL: Gasification Modeling using Euler-GranularModel

Syamlal and Bissett (1992) have reported gasification modeling withstep-by-step processes

Included drying, devolatilization, tar cracking, steam gasification, CO2gasification, methanation, water-gas shift, char combustion reactions

Gasification UDF for Euler-Granular model

Developed with funding from NETL Based on the work reported by Syamlal and Bissett (1992) and Wen et. al.

(1982)

H2 and CO combustion reactions also included

Used heterogeneous stiff chemistry solver of Fluent12 to take care of thestiffness of these reactions


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Heterogeneous reactions

- Char combustion

2C + O22CO

- CO2 gasification (reversible)C + CO2 2 CO

- H2O gasification (reversible)

C + H2O CO + H2

- H2 gasification (reversible)

C + 2 H2 CH4

Homogeneous reactions

- Water-gas shift (reversible)

CO + H2O CO2 + H2

- CO combustion

CO + 0.5 O2 CO2- CH4 combustion

CH4 + 1.5 O2 CO2 + 2 H2O- H2 combustion

H2 + 0.5 O2 H2O- Tar Combustion

Tar + O2 CO

2+ H

2O

Reactions

Initial stage reactions

- Moisture release

- Devolatilization

- Tar cracking

2322

242

ClNHSHOH

HCHCOCOTARVolatile

2322

242

Cld

NHd

SHd

OHd

Hd

CHd

COd

COdd

322

242

NHSHOHHCHCOCOCTar

322

242

NHc

SHc

OHc

H

c

CH

c

CO

c

CO

cc

O(v)HMoisture 2


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Published Results: Shaoping et. al. (2007)

Transport Gasifier at Power System Development Facility (PSDF),

(a) Flow path lines (b) Solid velocity vectors (c) Carbon combustion rate

(a) (b) (c)

The gas composition at the outlet of PSDF

The mean gas temperature along the PSDF


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Biomass Gasification

Prediction of reacting flow in a static bed with air injection at baseand top feed of solid biomass pellets

Uses Eulerian-Eulerian multiphase model with heterogeneousreactions coded in CFX expression language

Multiphase reactions:

char + CO2 -> 2 CO (char oxidation by CO2)

char + H2O -> CO + H2 (char oxidation by steam) char + 2 H2 -> CH4 (pyrolysis) char + 0.5 O2 -> CO (char oxidation)

Gas phase reactions:

H2 + 0.5 O2 -> H2O (hydrogen combustion)

CH4 + 1.5 O2 -> CO + 2 H2O (methane combustion) CO + 0.5 O2 -> CO2 (CO oxidation) CH4 + H2O -> CO + 3 H2 (methane reforming) CO2 + H2 CO + H2O (gas water shift reaction)

Figure shows cooling effect of adding increasing amounts of watervapour to injected air stream


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Recent Developments


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Improved models that use information from scale resolving

turbulence models: LES, SAS, DES, ...

1) G-Scalar model Norbert Peters

Level set method

Flame-front reconstructionRe-initialisation of G to obtain distance from flame-front

2) Thickened Flame model Thierry PoinsotArtificially broaden flame-front so that is can be resolved

Based on DNS modelling at lower Reynolds number

Premixed Turbulent Combustion


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G-equation model

Progress variable: c-equation in BVM

Mean (RANS) or filtered (LES) reaction progress

Replaced by level set method: G-equation

Mean distance to the flame front

Interface tracking method

Spatially filtered thin flame remains thin Suitable for use with scale resolving turbulence models

c~s)x

c~D(

x)c~u~(

x)c~(

t tuj

t

j

i

j

G~Ds)G~u~(x

)G~

(t ttuij


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G-equation Model

Advantages of G-equation over c-equation Can include the effects of (mean) curvature on the flame speed

(Karlovitz number)

c-equation predicts continually increasing flame brush thickness

Especially bad for LES

Disadvantages of G-equation over c-equation

Must be run in unsteady mode, so computationally expensive

G-equation good model for unsteady flames (LES)

Reference

Norbert Peters, Turbulent Combustion, Cambridge UP,2000


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Hamamoto Test Case Setup

Ref. Hamamoto et al. (1988)

Diameter 125 mm

Height 35 mm

1.0

pini 243 kPa

Tini 325 K

CFD Setup

3D Hex.

Structured

3 sec.

Level Nodes Cells

1 1,536 705

2 6,144 2,945

3 24,576 12,033Turbulence SST Model

sT

Ewalds Closure (2006)

Ignition rT = 3 mm,Vini = 0.2 mm3


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Hamamoto Test Case Results


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Thickened Flame Model

Proposed by Thierry Poinsot et al.Combustion model for scale-resolving turbulence model, e.g. LES, DES or SAS

Laminar flame is too thin to resolve in 3-D

Laminar flame thickness, d ~ 1mm Need about 10 points to resolve internal flame structure

CONCEPT:

Artificially thicken the flame but keep the laminar flame speed constant

Increase flame thickness by the thickening factor, F Multiply laminar mass/heat diffusivities by F Divide laminar reaction rate by F

hi k d l d l


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Thickening factor calculated as: D is the cell length (V1/3 ) Nis the user specified number of grid points in flame (typically 10-15)

d is the user specified laminar flame thickness (usually 0.1 to 0.3 mm)Dynamic TF: Limit diffusivity increase to near flame

Prevent enhanced mixing up or down stream

Dynamic thickening factor, W is calculated as:

so

= spatially filtered absolute reaction rate

is a model constant that controls the transition between thickened andunthickened regions (typically 10)

W )1(1 maxFF

d

DNF

max

hi k d l d l


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Dynamic effective diffusivity calculated as:

Far from flame (W 0 ) , Deff= Dlam + Dturb Near flame (W 1 ), Deff= Dlam E FE is the efficiency factor

Small scale flame wrinkles are suppressed by thickening

Increase the laminar flame speed by E

Multiply both diffusivities and reaction rate by E

Calculated from the turbulentflame speed at the length scales lt= D and lt = FD using e.g. Zimont

correlation

TFM E l Ch (1996) P i d


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TFM Example: Chen (1996) PremixedFlame F3

Instantaneous (filtered) temperature

TFM Laminar

x/d=2.5

x/d=8.5

LES with Re = 24,000


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TFM Example: Chen Flame F3

TFM F, W and E

F

W

E

TFM l Ch fl F3


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TFM example: Chen flame F3

TFM vs LAM vs EXP mean axial velocity

x/d=2.5 x/d=4.5

x/d=6.5 x/d=8.5

l h fl


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TFM example: Chen flame F3

TFM vLAM v EXP mean temperature

x/d=2.5 x/d=4.5

x/d=6.5 x/d=8.5

TFM Ob i


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TFM Observations

Advantage:Generally applicable to all types of turbulent combustion using tabulated or

reduced chemistry schemes

Issues:

1) Thickening destroys influence of small scale turbulence need E factor2) All species must be transported so more computationally expensive than

a progress variable + mixture fraction method

References:Legier, Poinsot and Veynante, Centre for Turbulence Research, Proc Summer

Program 2000, p157

Kuenne, Ketelheun and Janicka, Combustion and Flame 158 (2011) 1750

Ti S l S ti (TSS) M d l


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Time-Scale Separation (TSS) Model

Innovative pollutant model to predict COProblem: How to represent fast formation of CO at flame front and relatively

slow post-flame oxidation?

Time-Scale separation used to represent the two processes:

Data extracted for and from PDF chemistry tables

COTFront

COCO cScsY

Dt

DY

CO formation at flame front CO oxidation to CO2

Front

COY

COS


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F t T d


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Future Trends

Scale-resolving turbulence models used to predict combustion dynamics, e.g.noise and vibration

Trend towards coupled models of CFD with thermal and stress analysis, and also

1-D process models

Increased use of combustion models, rather than inert models, to simulate fires

Growing use of multi-phase reacting flow models, both Eulerian and Lagrangian,

for simulation of coal and biomass gasifiers

Rapid development of unsteady premixed combustion models for use with

scale-resolving turbulence models, e.g. TFM and G-Equation models, but

some work remains to be done

Documents

Combustion Modeling Tools in CFD