Knowledge-Assisted Visualization of Turbulent Combustion Simulations
Turbulent Combustion: Modelling and Applications
Transcript of Turbulent Combustion: Modelling and Applications
Turbulent Combustion:Modelling and Applications
Princeton Summer School 2021
E. Mastorakos
Engineering Department
University of Cambridge
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Day 3: Modelling for turbulent flames
Non-premixed
Premixed
Stratified
Spray
General comments
2
Turbulent non-premixed combustion: modelling
• No model
• Presumed PDF
• Eddy Break-up, Eddy Dissipation Concepts
• Mixture fraction approaches (flamelet, Conditional Moment Closure)
• Transported PDF
3
No model
Neglect turbulent fluctuations, hence evaluate mean reaction rate at the mean species mass fractions and mean T (“mean”=“ensemble averaged” in the case of RANS, or “resolved” in the case of LES)
4
)~
,...,~
,~
(
~
)()
~~()~
(
21 TYYfw
wx
YDD
xx
Yu
t
Y
i
t
ii
i
=
+
+
=
+
Presumed PDF
5
A. Model P(Y1,Y2,…T) as a series of delta functions evaluated at the mean Y1, Y2, …T. This corresponds to “laminar chemistry”.
B. Presume a shape for the joint PDF, determined by the mean Ys (coming from transport eqtn), possibly also by Y_rms (also coming from modelled governing equation for variance). Shape could be beta-pdf or Gaussian.
Used currently for supersonic combustion, mostly because people pay attention to the CFD, shock waves etc, and not to the turbulence effects on the reaction (Baurle and Girimaji, Comb. Flame, 134 (2003)).
dTdYYdTYYPTYYfw
TYYfw
...)(,...,,(),...,,(
),...,,(
212121...
21
=
=
Eddy break up (EBU)
If chemistry is infinitely fast, then overall reaction rate is determined by the rate of turbulent mixing. Rate of mixing determined by Tturb (=k/e). Given first by Spalding (early 70s):
6
)~
1(~
, 22
fufufufufu YYYk
YAw −−=e
After tuning with
experiment From k-e model Infinitely fast no probability
of intermediate
Developed for premixed, but also used for non-premixed (see next slide)
Eddy dissipation (Magnussen)Magnussen (16th Symp on Combustion) modified
Spalding’s EBU for non-premixed flames:
7
))Prod(1OxFu(, 1
~
,~
,~
min 2
SSS
YBYY
kYAw
prod
oxfufufu +==+
+−=e
After tuning with experiment
From k-e model
Widely used, quick to run, often reasonable results (for furnaces, diesel
engines in diffusion flame phase). Not good for flames close to walls
(similar to EBU). Not good for finite-rate chemistry (no pollution, no
extinction, no autoignition).
Eddy dissipation concept (EDC)
Reaction assumed to occur inside Kolmogorov vortices, each of them treated as a well-stirred reactor. Rate of reaction given by volumetric reaction rate inside vortices and volume fraction of vortices (“reactors”)
8
1
~
,~
,~
min 2
4/1
+
−=
S
YBYY
kY
kCw
prod
oxfufufu
e
e
After calculating volume fraction of
Kolmogorov vortices (Byggstoyl &
Magnussen, 1984)
Many variants. Used in RANS and in LES (Duwig, Chomiak, etc).
Reasonable for some problems, finite-rate chemistry can be included
with some new concepts treating Kolmogorov vortices as well-stirred
reactors.
Infinitely-fast
chemistry
version
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Mixture fraction approaches: the PDF of the mixture fraction P(x)
• Solve equations for mean and variance of mixture fraction
• Presume P(x) (e.g. b-PDF given below).
• Then integrate over P(x).
=1
0
),,(~
),,(),(~
dtxPtxQtxY
Various options!
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10
Mixture fraction approaches: the options for Q
=1
0
),,(~
),,(),(~
dtxPtxQtxY
Infinitely fast chemistry
(“flame sheet” or
“mixed is burnt”)
Finite rate chemistry; Q from pre-calculated
laminar flame (one version of the flamelet model)
Another version of flamelet model: solve for Qa online; function of time
and space (some rough modelling used for the latter)
CMC: solve for Qa online; function of time and space (more rigorous)
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Turbulent diffusion flames: fast and slow chemistry
Q(,x,t) comes from:
(i) flame sheet model (infinitely fast chemistry). Good for big furnaces,
slow flows, flame lengths, first approximation to many problems.
(ii) Equilibrium. For every (mixture fraction), assume thermodynamic
equilibrium. Not very good, gives too much H2 and CO on the rich side.
(iii) Laminar flamelet (either pre-calculation, or on-the-fly)
(iv) Conditional Moment Closure (Q is function of time and space)
=1
0
),,(~
),,(),(~
dtxPtxQtxY
11
12
Turbulent diffusion flames: a result of historical significance and great insight
• Bilger (1976) derived a closed-form result for the mean reaction rate.
• Direct connection between reaction rate and scalar dissipation
demonstrated for the first time. Necessary for understanding flamelet
and CMC models.
• If Yi=f(x), then:
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(from Bilger,1976)
13
Turbulent diffusion flames: flamelet model
Flamelet model variants:
(i) Steady flamelet (i.e. laminar flame solution). Very common; already in FLUENT etc.
(ii) Transient flamelet, “Representative Interactive Flamelet” (Peters 2000)
(iii) Some issues:
- flamelet depends on N; how do we select N from flow field?
- how many flamelet solutions do we use? Over how many N’s?
=1
0
),,(~
),,(),(~
dtxPtxQtxY
13
14
Conditional Moment Closure
x
T
T
xx
xst
T
xst
•Relating the reacting scalar, Q, to
the non-reacting scalar (mixture
fraction).
•What happens if Q is very different
in space or time, as in a lifted flame?
•CMC solves PDE for Q.
=1
0
),,(~
),,(),(~
dtxPtxQtxY
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Final (modelled) CMC equations for sprays:Mortensen & Bilger (2009)
15
+
=
||2
2
wQ
Nt
Q ( )
xx
x
−−−+
+
−
−−
QSQSS
x
QDP
xP
x
Q
xDu
jt
j
jjtj
|)1(||
)(~
)(~1
~~
''
1~2
Transient flamelet model
Terms responsible for flame propagation,
heat losses to walls, stabilization etc.
Droplet interactions. Model
for <S|> needed.
Steady flamelet model
𝑁|𝜂Conditional scalar
dissipation. Model needed.
Scalar dissipation rate (for LES)
CN=42.0
Droplet evaporation and the mixture fraction
=
=
s
sS
x
x
if finite
if 0|
0~S
0=S
r
Yfu,x
Computational cell
Yfu,s , xs
Yfu, , xcell
Yfu,s(Td)
Td
Droplet in
cell
Yfu,s= f(Td) from Clausius-
Clapeyron eqtn
16
Final (modelled) mixture fraction equations:Demoulin & Borghi (2002) + new model for <S|>
)(~
/)(~
ss PSS xx −=
17
18
Turbulent diffusion flames• Large Eddy Simulation – Conditional Moment Closure
Garmory and Mastorakos,
LES-CMC calculations in
Sandia F, PROCI 33, 2010. 18
=1
0
),,(~
),,(),(~
dtxPtxQtxY
Capturing “holes” in flame sheet
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CMC literature
• Klimenko and Bilger, 1999, PECS
• Kronenburg and Mastorakos, 2011, In “Turbulent Combustion
Modelling”, Springer 2011.
• Journal papers by Kronenburg, Mastorakos, Huh, Bilger, Devaud and
others for applications in RANS and LES
• Typically, CMC provides very good results for finite-rate chemistry
effects in turbulent combustion and has been used for very difficult
problems such as ignition and extinction.
• Currently, used a lot for diesel engines, gas turbines, furnaces, fires…
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The pdf method
• Transport equation:
- Conservation of pdf in real and scalar space
- Advection, turbulent diffusion, micro-mixing, chemistry.
- Various additional joint PDF equations can be derived (joint scalar;
joint scalar-velocity; scalar-velocity-frequency)
- Pope, Dopazo, Jones, Roekaerts, etc etc
- Fundamental derivations vs. applications
- Method now present in FLUENT & STAR-CD
- See Haworth, 2010, PECS; Haworth and Pope chapter in Echekki &
Mastorakos 2011.
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The pdf method
(1) Random walk of “virtual particles”, as a solution method of the PDF
equation
(2) Compile statistics over these particles
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The pdf method: Lagrangian approach
• Physical understanding:
- “decompose” fluid into virtual “particles”
- Develop random walks for these “particles” that mimic turbulent
dispersion, molecular mixing.
- Each “particle” carries its own chemistry
- Example:
homogeneous (in the mean),
“Interaction by Exchange with the Mean” mixing model
=
=−
−=pN
n
n
mix
nn
n
YYT
YYw
dt
dY
1
,
Chemistry
Molecular mixing
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The pdf method: Eulerian approach
• Physical understanding:
- “decompose” fluid into virtual “fields”
- Develop random walks for these “fields” that mimic turbulent
dispersion, molecular mixing.
- Each “field” carries its own chemistry, convection, diffusion
- Jones et al. (and others now): for applications in LES for a variety of
flames
- Applications also to urban pollution (Garmory and Mastorakos).
- See original papers for the mathematics and applications (Valino,
Jones etc)
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The pdf method: Eulerian approach
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Modelled PDF
conservation equation
Stochastic PDE for
every field; solve this for
N fields (N: large for
RANS, not too large for
LES).
Careful with solver!
(must be consistent with
stochastic PDE)
Random walk term
(Wiener)
Micromixing (here, modelled by
“Interaction by Exchange with the Mean”
Chemistry
Turb. diffusionConvection
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Premixed flame modelling
• Flamelet
• Flame surface density
• PDF (discussed already)
• CMC (discussed already; some sub-models different)
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Premixed flame modelling
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Flame surface density modelling: turb. flame locally is (almost) like laminar
one; turbulence makes itself known through FSD & I0.
Mean reaction rate
Reactant density
Unstrained
laminar flame
speed
Factor to
account for
strain and
curvature
Flame surface
density (algebraic
model, transport
equation
FSD is active area of research (transport equation, I0, etc). See Cant and
Mastorakos 2007 for an introduction. See Driscoll’s review paper (2008)
for more info on how we measure flame area and how to define flame
speed.
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Premixed flame modelling
• Flamelet model:
• We need Y(c) (and w(c), T(c), etc) and P(c).
• Calculate laminar premixed flame, store results in terms of c (Bradley,
“FGM”, etc): they are all the same model.
• Definition of c varies, could be based on Yfuel or T, 0 in reactants, 1 in
products. Different definition needed if NOx is the target.
• Can be extended for equivalence ratio inhomogeneities.
• Driscoll’s 2008 review paper: how far does flamelet structure go?
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𝜑 = න
𝑐=0
𝑐=1
𝜙 𝑐 𝑃 𝑐 𝑑𝑐
𝑤(𝑐)
𝑌(𝑐), 𝑇(𝑐)
𝜙
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Premixed flame modelling
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How about P(c)?
If flame thin relative to the turbulence scales, Bray-Libby-Moss concept
seems applicable: “Double Delta Function” model for the PDF of c.
BLM go further and close mean reaction rate, turbulent flux etc (see Cant
& Mastorakos, Ch 4)
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Premixed flame modelling
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Mean and variance of c, scalar dissipation of c: (eqtns below are for RANS
or LES, from Farace et al, Comb. Theory and Modelling, 2018):
Progress variable dissipation (new models by Swaminathan, given below
for LES) – unlike passive scalar dissipation, it now depends on chemistry!
Fundamentals of stratified / partially-premixed turbulent
combustion
• Very difficult and topical research area
• “Stratified” : a derivative of premixed flame concepts
• “Edge flames” (e.g. after ignition): a derivative of non-premixed concepts
• “Partially premixed”: this term is vague and should be avoided; better to say “imperfectly premixed”, or “edge”, or “stratified”; described by P(x).
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0.3ms 0.7ms 1.9ms
7.1ms 16.5ms
Turbulent edge flames: definitions
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U: far-field fluid velocity
Ut: fluid velocity at triple point
Vf: absolute flame speed
Vf
Ut
U
SE=Vf-U: edge flame speed relative to the far field
SE=(u/b)1/2SL for laminar flame (Ruetch et al, 1996; analytical result)
S=Vf-Ut : edge flame displacement speed
Turbulent edge flames: DNS & experiments
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Vabs
AVf
Vrθ0.5 ms
0.9 ms
1.8 ms
2.3 ms
3.3 ms
4.2 ms
6.5 ms
9.3 ms
CH4 (Le0.9)
S/SL
P(S
/SL)
<S> = 0.5-0.8 SL,0
<SE>(u/b)1/2SL,0
Must examine
for spraysExp: Heeger et al., 32nd Symp.
DNS: Hesse et al., 32nd Symp.
Fuel
Air
OH-PLIF PIV
Turbulent gaseous edge flames: DNS & experiments
• Absolute, relative edge flame speed, displacement speed
• Dependence on local scalar dissipation, strain etc.
• Findings:
– effects of turbulence NOT the same as in fully-premixed flames
– Counter-gradient transport possible
– Lewis number effects
– Flame speed has large fluctuations
• Chakraborty & Mastorakos Phys. Fluids, 18 (2006), 105103; Proc. Comb. Inst. 32 (2009) 1399–1407; Flow Turbul. Comb. (2009) to appear.
• Richardson et al., Proc. Comb. Inst. 31 (2007) 1683–1690
• Heeger et al. Proc. Comb. Inst. 32 (2009) 2957–2964;
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DN
S
Ex
p.
Turbulent spray flames
• Models usually as for non-premixed flames
• Turbulent Combustion of Sprays Workshop
• To first-order, evaporation is uncoupled from the combustion model (evaporation creates the fuel)
– BUT: mixture fraction and variance (in RANS or LES) have terms including spray effects
– Scalar dissipation modelling needs improvement when sprays are present
– If premixed flame are used for flamelet modelling, spray flames should in principle be used for tabulations: laminar flame in spray very different than in gases!
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Laminar “premixed” spray flame
Neophytou and Mastorakos, CNF, 200935
Laminar “premixed” spray flame
Neophytou and Mastorakos, CNF, 2009
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Post-flame pyrolysis
Evaporation The flame creates its fuel.
Very complex structures; not used in
turbulent combustion modelling so
far.
Laminar “premixed” spray flame
Neophytou and Mastorakos, CNF, 2009 37
Flame speed depends on SMD,
overall f, gaseous f.
Turbulent “premixed” spray flame
Chakraborty’s group, 201738
Model validation
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Velocity, mixture fraction: needed as “background”; good agreement does not provide validation for the combustion model.
Mean T and major species: if good, we begin to pay attention…
RMS of major species: extra level of validation.
Mean and rms of radicals (e.g. OH): agreement provides good evidence that model works
NO & soot: difficult to predict (chemistry + experiment problematic…)
Validation must be done across a range of conditions (e.g. low velocity, high velocity etc), otherwise it means little.
Industry also needs validation at high pressure and very high Reynolds number.
DNS can be used for sub-model validation, typically based on small-scale quantities (large scale phenomena typically not converged statistically).
Target flames for model validationNon-premixed:
Sandia D-E-F: piloted CH4/air jet flames, still diffusion flame, strong local extinctionSydney swirl CH4: stabilisation by recirculation zone; local extinction
“Partially premixed”:DLR: nominally non-premixed, local liftoff causes some premixing, quick mixing
Premixed:Piloted Bunsen flame: overall shape, relatively low KaPiloted jet flames (Sydney, Michigan, Lund, USC etc): very high Ka – combustion sustained by the
hot co-flowing productsTurbulent flame speed experiments
Sprays:Sydney piloted jet (carrier air+vapour+droplets): various fuels, range of conditionsCambridge swirl spray flames: range of fuels and conditions, focus on local and global extinctionRouen, Delft, Heidelberg: spray in low co-flow (low Re)
http://swirl-flame.eng.cam.ac.uk/
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Target flames for model validation
Autoignition:“Cabra” flame (fuel in vitiated air), Cambridge (fuel in hot air), diesel-like (Sandia, ETH)
Spark ignition:Cambridge (series of flames); Ecole Centrale (annular)
Soot:Laminar diffusion flame (Santoro), Adelaide jet flames, DLR swirl flames (1-3bar)
Pick the flame experiment whose research focus was the focus of your modelling effort.
No flame is good for everything!
No model is good for everything!
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Combustion CFDStep 1: Decide what you want to predict well, and what is OK to be less accurate. What phenomenon are you looking to simulate well? What is the focus of your research?
Step 2: Make sure aerodynamics is OK (grid should be sufficient, validate code against simple problems, then code+grid against cold flow in complex geometry).
Step 3: Estimate how many CPU hours you have. Should they be spent on better statistical convergence? On more chemistry? On more grid nodes? On running more conditions?
Step 4: Perform the simulations, compile averages (if LES), compare against experiment.
Step 5: Draw conclusions on the suitability of your code/model for the particular phenomenon you set out to simulate.
Many papers, from well-known groups, in high-quality journals, make over-claims about their models without the appropriate validation. Examples or erroneous claims:
“Model works for blow-off” although validated for stable flame far from blow-off…“Model OK for heat loss” although not validated against radiative heat transfer data…“Model works for autoignition at 50bar” although chemistry validated at 10bar…Often, people confuse conclusions on chemistry / CFD / turbulent combustion model.
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Conclusions – Day 3
Old models (EBU etc) use infinitely-fast chemistry. OK for flame length for easy problems.
Useful for initial condition of more complex simulation.
Flamelet models:
If flame does not have local extinction, flamelet model (for prem or non-prem) is OK.
Premixed flames seem more resilient to stretch effects than non-premixed, and hence
flamelet models for premixed have wider applicability.
If significant finite-rate kinetic effects, solve chemistry together with flow:
(i) CMC
(ii) PDF (Lagrangian or Eulerian)
(iii) flamelet with c-x formulation
(iv) Linear Eddy Model
(v) Thickened Flame Model
(vi) “Eddy Dissipation” versions
Must see validation for difficult lab-scale problems involving local extinction (e.g. Sandia F;
Cambridge bluff-body premixed, Cambridge swirl non-premixed and spray, Sydney, DLR
etc), before trusting results. Same for soot.
Sprays: usually derivative from non-premixed; spray flame intricacies not included yet.43
Turbulent Combustion:Modelling and Applications
Princeton Summer School 2021
E. Mastorakos
Engineering Department
University of Cambridge
1
Day 4 & 5: Applications to diesel engines and gas turbines
RANS of diesel-like “bomb” experiments
RANS of diesel engines
Pollutants
Gas turbine combustion
LES/CMC of swirl flame – focus on local and global extinction
LES/CMC of g.t. flame – focus on soot emission
LES/TFM of interacting burners – focus on LBO
2
Diesel engine modelling
• Some preliminary considerations:
– Is initial condition (P,T) OK?
– Is grid sufficient for good spray penetration prediction?
– Which chemistry should I use?
– Soot and NOx schemes at my conditions?
– RANS or LES?
– Models for heat losses to walls?
– How many cycles? Exhaust gas recirculation?
3
Diesel engine modelling
ETH experiment - heptane injection in constant volume chamber. Data exist for:
Autoignition time
Autoignition location
Pressure rise vs. time
Modelling: RANS with Lagrangian spray description, CMC for turbulent reaction model , reduced heptane scheme
Target of simulation: autoignition time, overall pressure rise
Wright et al., Flow Turbulence and Combustion, 2010
4
ETH diesel-like experiment
5
ETH diesel-like experiment
6
ETH diesel-like experiment
7
ETH diesel-like experiment
8
Mie scattering (spray core)
Schlieren (spray)
ETH diesel-like experiment
9
Separate autoignition visualisations at same time from injection:
- Each time, autoignition occurs at different locations, but at the same time approximately
ETH diesel-like experiment
10
No spray terms in mixture fraction variance; no spray correction in c model; no spray correction in CMC equation.
ETH diesel-like experiment
11
ETH diesel-like experiment
12
Atomisation model affects spray development; but perhaps only in the beginning (for this experiment!)
ETH diesel-like experiment
13
Natural outcome of CMC and flamelet models is Q vs. mixture fraction.In CMC, these are functions of space (not only time).
Transient flamelet calcs, constant scaldis.
Choice of chemical scheme affects ignition time.
A general comment about non-premixed autoignition
14
Autoignition time depends on scalar dissipation rate (different dependencies for each P,T condition, chemical scheme, fuel)
If engine operates in this regime,no delaying effect due to strain, hence simpler models OK
But operation at high N means strong effect of strain, hence need good turbulent combustion model.
ETH diesel-like experiment
15
Large sensitivity to chemical mechanism!Uncertainty of initial condition!
What can we really conclude about the CMC turbulent combustion model?
ETH diesel-like experiment
16
Everything in real devices has uncertainties.Significant sensitivities to CFD (injection model, initial temperature, initial turbulence in chamber), solver settings, chemical model.
Very important: be careful with comparison done against ONE set of conditions only!
Sandia diesel-like experiment
17
“Engine Combustion Network”
Sandia experiment with heptane
RANS-CMC, focus on spray models in combustion model
Borghesi et al., Comb. Theory and Modelling, 2011
Focus of simulation: see whether spray terms in CMC equation make a difference
Sandia diesel-like experiment
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<x> xrms <OH> <T>
Sandia diesel-like experiment
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What do we conclude?
- We capture flame location vs. time. This is a success of the CMC model (spatial diffusion and convection terms responsible). Analysis in paper consolidates this conclusion.
- We capture autoignition time trends with exhaust gas recirculation (more important than capturing the exact autoignition time, which is a strong function of the chemical scheme).
- Good validation case for the turbulent combustion model for a diesel-engine like configuration.
Sandia diesel-like experiment: focus on soot
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Now focus on sooting tendency of fuels, conditions (EGR), and relative performance of two models:
- “Laminar chemistry”- Multidimensional Conditional Moment Closure
Why? Because recently people have ignored 40 years of combustion research and run CFD codes for engines with no combustion model…BUT: often the results look good! How is this possible?
Wright et al., “Influence of turbulence–chemistry interaction for n-heptane spray combustion under diesel engine conditions with emphasis on soot formation and oxidation”, Comb. Theory Modelling, 2014
Sandia diesel-like experiment: focus on soot
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Two-equation model for soot (mass fraction, number density), including model for differential diffusion of soot particles (due to Kronenburg and Bilger), basic model due to Leung and Lindstedt. See paper for details.
Sandia diesel-like experiment
22DI: “Direct Integration” (no combustion model, “laminar chemistry”)
Sandia diesel-like experiment
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For conventional diesel combustion, not big difference of overall observable (if system is kinetics controlled). This is why people did it!But for cases with significant mixing and oxidation, CMC much better than DI. Including proper turbulent combustion model gives generality.
Heavy-duty diesel engine
24
“0D-CMC”: Integrate N over whole engine volume; give this N to the CMC code (i.e. CMC reduces to transient flamelet)
“2D-CMC”: Two-dimensional CMC equation in space
Good agreement for overall pressure trace and heat release rate.
In this engine, N is relatively low relative to the N_critical ; hence local differences in N do not result in significant differences in Qa.
Wright et al, IJER, 2009
Heavy-duty diesel engine
25
75%
load100%
load
Heavy-duty diesel engine
26
NOx : getting absolute value is just luck; but trends imply good overall success of the model.
In this configuration, most of the NOx is due to the thermal (Zel’dovich) mechanism; hence success to capture trend means success to capture temperature OK.
For systems with lower NOx (and those with prompt NOx being the dominant route), turbulent combustion models and chemical schemes have not been fully validated yet.
Gas turbine combustors
27
Primary & secondary
atomization, dispersion
Chemical mechanism,
turbulence-chemistry
interactions
Heat loss,
radiationNOx, CO, soot,
Temperature
profile, velocity,
vorticity
Flame location Aerodynamics
Thermo-acoustics
(coupling with combustor
acoustics)RED: Usual targets
BLUE: Models
Heat transfer
Gas turbine combustors
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General comments:
- Spray initial conditions: very important for success of overall simulation
- Combustion model: important for Lean-Premixed Prevapourisedconcepts and others with quick mixing
- Chemistry: very important for soot, NOx, local and global extinction- Do we have good enough schemes for kerosene chemistry?
- Aerodynamics: due to strong swirl, curved streamlines, dilution jets, cooling flows, simple RANS does not work too well. Migration to LES has taken place in academia and is taking place in industry.
- Radiation: could become important, as accuracy improves
Gas turbine combustors
29
Next few slides:
- Some comments on extinction of flames with swirl
- Results from CH4 jet diffusion flames (Sandia F), CH4 swirl flames (Sydney & Cambridge): validation of LES/CMC for local and global extinction
- Results from Cambridge swirl spray flame: validation of combustion model for spray local extinction
- Demonstration of calculation of realistic gas turbine combustor including soot.
30
Capturing extinction is one of the “Holy Grails” of turbulent combustion theory.
Can we predict blow-off curve with CFD? There is evidence we are making good
progress. Used here as an example of finite-rate kinetic effects to demonstrate
how modelling helps.
0
50
100
150
200
250
0 5 10 15 20 25
Air velocity, m/sA
FR
Lean extinction
Rich extinction
Lean ignition
Rich ignition
Ahmed & Mastorakos, CNF, 2007
The practical ignition/blow-off loop: must run lean so that NOx, CO, soot are low
31
Basic considerations
Extinction is due to competition between fluid mechanics & chemistry.
Manifested in critical strain rate in laminar counterflow flames, well-
stirred reactor critical points, S-shaped curve etc. Laminar flame
extinction is reasonably well understood.
Turbulent flames - local:
- Premixed: Karlovitz number
- Non-premixed: scalar dissipation (Sandia D-F; Sydney series)
- Spray: Not studied much
Turbulent flames – global:
- how do localised extinctions lead to global extinction?
- is it “extinction” or “destabilisation”?
32
Blow-off in gas turbine afterburners: perhaps the first flame stabilisation problem studied
Bluff-body stabilized lean premixed
CH4-air flame close to blow-off, Ub
= 31.4 m/s, Φ = 0.66 (Kariuki PhD)
From Glassman, 4th ed.
(1) Knowledge from afterburner-type geometry must be extended to
non-premixed & spray flames and to short flames.
(2) More detailed research needed.
33
Bluff-body stabilised premixed flames (Dawson et al, Proc Comb Inst 33:1559-1566, 2011)
f same, U increases
OPEN
ENCLOSED<OH*>
Prior to BO
Bluff-body stabilised premixed flames (Dawson et al, Proc CombInst 33:1559-1566, 2011)
34
Flames increasingly closer to blow-off condition(Kariuki et al, Comb Flame, 2012)
Local data from PIV & OH-PLIF:
high u’ gives Ka~12 at location of
extinction. This is much higher than
the limit for igniting a turbulent
premixed flame (Ka~2 ; from
Bradley et al.).
s
Increasing UHigh f Low f
s
35
Blow-off event: OH* and planar Mie (aerosol in reactants)
Reactants penetrate from
downstream end of RZ, not
from the sides. Anchoring point
fails less than downstream.
Blow-off event lasts ~20 ms
(many d/U)
OH*: orange
Mie: grey
36
Approach to extinction: simultaneous CH2O & OH PLIF to image reaction rate (PROCI 35th, 2014)
Reaction inside RZ & fragmentation; flame-flame touching.
Surprising large amounts of CH2O in RZ and thickening of preheat zone.
f=0.75
f=0.68
OH-PLIF CH2O-PLIF CH2O x OH
37
Locally high Ka?
Our knowledge on critical Ka for premixed flames is mostly based on ignition
experiments (e.g. spark a mixture; let kernel grow a little; see if flame
propagates). Some decisions needed what constitutes “good” from “failed” flame
(Bradley, Shy, and many others).
Presence of hot products behind flame affects extinction drastically, allowing very
high Ka locally:
Opposed jet flames (e.g. recent work from Gomez)
Premixed jet in hot co-flow (Dunn et al. experiment from Sydney; modelling)
Related to MILD combustion (lack of clearly-defined ignition/extinction)
Lack of hot products in RZ (fresh reactants, partially-burnt fluid), caused by local
extinction at downstream regions of high Ka, seems to be the main route for
global blow-off of recirculating premixed flames. This is not “destabilisation” in
the sense of flow velocity / turbulent flame speed inbalance.
38
Premixed Non-premixed Spray
All dimensions in mm.
Swirling recirculating flames: 3 types of flame in same burner (Cavaliere et al., FTaC, 2013)
Swirling recirculating flames: 3 types of flame in same burner (Cavaliere et al., FTaC, 2013)
Blow-off of spray flames
Blow-off is not instantaneous, when viewed with kHz diagnostics(Cavaliere, Kariuki, Mastorakos, FTaC, 2013)
39
SPRAY OH*, 5 kHzSPRAY, 30 Hz
40
Ub=19.6 m/s, Φ=0.51 Ub=19.9 m/s, Φ=0.31 Ub=18.3m/s, Φ=0.13,
PREMIXED NON-PREMIXED SPRAY
Blow-off event: OH* & OH-PLIF (5kHz)
OH*
OH-PLIF
Blow-off event: OH* & OH-PLIF (5kHz)
41
Various liquid fuels: Images far from blow-off
Ethanol Decane DodecaneHeptane
OH
PLIF
<OH* >
(Ruoyang Yuan, PhD, 2015;
In. J Spray Comb Dyn 2018)
Various liquid fuels: Images far from blow-off
42
Images close to blow-off
OH
PLIF
<OH* >
Ethanol Decane DodecaneHeptane
Approach to extinction ➔ very fragmented reaction sheet
Images close to blow-off
Large Eddy Simulation: can blow-off be predicted?
43
Combustion sub-grid model critical: balance of strain & reaction must be included
somehow.
LES with CMC (Garmory & Mastorakos, PROCI 33) has been shown to predict
well the Sandia Flame “F”.
So, can we predict global blow-off dynamics and condition in recirculating
flames?
44
LES-CMC: CMC Equation has all the needed ingredients to capture extinction
Conditionally filtered reacting scalar
Chemical source term – 1st order closure, i.e. f(Qa) only
Conditionally filtered velocity – responsible for propagation
Conditionally filtered scalar dissipation rate – responsible
for local extinction
Sub-grid conditional
flux – propagation
45
LES/CMC captures localized extinction (Garmory &
Mastorakos, PROCI, 33rd, 1673-1680, 2011)
Overall very good agreement for Sandia D & F
xst - OH OH <YOH|h>
LES/CMC captures localized extinction (Garmory & Mastorakos, PROCI, 33rd, 1673-1680, 2011)
46
LES/CMC of the CH4 non-premixed TECLFAM flame (Ayache & Mastorakos, FTaC, 2013)
Stoichiometric contour, coloured by OH
Localised extinction and flame liftoff captured.
OH*, experiment
47
LES/CMC of the CH4 non-premixed Sydney flame (Zhang & Mastorakos, PROCI 36, 2017)
Localised extinction captured correctly. Validation against
unconditionally- and conditionally-averaged quantities
48
Capturing global blow-off (Tylizczak et al, FTaC, 2014; Zhang et al, PROCI 35, FTaC 2016)
Conventional LES with mixture fraction (passive scalar), low-Ma,
Smagorinski; estimate sub-grid variance of mixture fraction & sub-grid
scalar dissipation; Lagrangian spray, Abramzon-Sirignano single droplet
evaporation. All models used as “validated” for simple flames.
1-step chemistry for C7H16, 19-species reduced for CH4
LES gives mixing and velocity field to CMC code
CMC code gives density to LES code
LES code: PRECISE-UNS from Rolls-Royce plc
CMC code: new unstructured version (UCAM)
Approach: simulate flame at low U; increase to the determined blow-off
U; what does the LES predict?
49
10
12
14
16
18
20
22
24
26
28
30
0 0.05 0.1 0.15 0.2 0.25 0.3 0.35 0.4
Air
velo
cit
y [
m/s
]
Fuel Flow rate [g/s]
Decane
heptane
Blow-off of swirling heptane spray flame: the target experiment (Cavaliere et al., FTaC, 2014)
OH-PLIF of SWH1
Blow-off condition
SWH1: stable
SWH3: blow-off
CFD path
50
Flame structure
OH-PLIF (exp)
Localized extinction
& re-ignition
Reaction rate LES
51
T=0.0550s
T=0.0600s T=0.0650s T=0.0700s
T=0.0750s T=0.0800s T=0.0850s T=0.0900s
Results: Increasing velocity from SWH1 to SWH3
(stoichiometric isosurface, coloured by T) => global
extinction
Simulation at blow-off U predicts fully extinguished flame & no re-ignition!
Results: Increasing velocity from SWH1 to SWH3 (stoichiometric
isosurface, coloured by T) => global extinction
52
Duration of blow-off event
Blow-off lasts ~20ms, not far from experiment
53
Images close to blow-off: heptane spray flame (Yuan
et al, PROCI 35, 2014; Giusti et al, in preparation)
Flame close to blow-off is fragmented, similar to experiment. LES/CMC captures this violent extinction event. Extinction and re-ignition captured (not possible with flamelet models, unless specifically developed for extinction)
LES/CMC of ethanol spray flame close to blow-off (Giusti et al,
PROCI 36, 2017)
54
Images close to blow-off: heptane spray flame (Yuan
et al, PROCI 35, 2014; Giusti et al, in preparation)
Statistics of local extinction at bluff-body edge captured OK.
LES/CMC of ethanol spray flame close to blow-off (Giusti et al,
PROCI 36, 2017)
55
Complete blow-off curve: Non-premixed CH4 flame (Zhang &
Mastorakos, FTaC 2016)
Full blow-off curve predicted to within 25%
Kerosene swirl flame with LES-CMC
56
Domain
Bluff-body (Φ25)
Swirled air inlet annulus (60°) (Φ37)
Hollow 60°spray
Cambridge bluff body non-premixed swirl-stabilized burnerHollow cone kerosene spray was injected from centre of bluff body at 60° with SMD of ~60 μm based on experiments
Kerosene Fuels:❖ A2: conventional Jet A, C11H22
❖ C1: alcohol-to-jet-fuel, C13H28
❖ C5: synthetic fuel, C10H19
Foale, Giusti & Mastorakos, 2020, AIAA SciTech
Stable swirl kerosene flame with LES-CMC
57
LBO condition – kerosene spray flame with CFD
58
CFD blowoff velocity within 15% of experimental value
Sensitive to numerical set-up (choice of chemistry, spray etc)
Doubly-Conditioned Moment Closure for sprays (Sitte & Mastorakos, CNF 2019)
59
EXP by Rouen
Lift-off OK
c=0.1c=0.6
60
A recap and a conclusion on CMC – as an example of the approach of validating a turb combustion model
CMC model was first derived and some closures validated against DNS
(late 90s-early 00s)
RANS/CMC across a range of flames with simple geometries and some
finite-rate kinetics: further validation
LES/CMC of jet flames, swirl flames: degree of local extinction OK
LES/CMC of full blow-off curve: for gaseous flames OK
LES/CMC of local extinction in ethanol swirl spray flame: OK.
Next steps: more complex fuels; full blow-off curve, soot, Nox.... Then,
move on to real combustors…
We have made progress. Hierarchical approach absolutely necessary.
• …from the experiment
Unsteady behaviour - thermoacoustics
61 Experiment by A.-M. Kypraiou, PhD 2016, CST 2018, ETFS 2018
The amplitude of the HRR fluctuations increases with the amplitude of the velocity fluctuations.
• Some observations:
a) The flame seems to pulsate in the axial direction
b) Regions with high OH* chemiluminescence signal appear at mid-height and close to the walls
c) The opening of the flame brushes on the two sides of the bluff-body changes in time
Phase-locked OH* chemiluminescencesignal
➢ F = 160 Hz➢ A = 0.3➢ Ub = 15 m/s➢ Global eq. ratio = 0.55
• Can we predict the heat release rate fluctuations?
˗ Good prediction of the phase lag
˗ Good prediction of the HRR fluctuations
Unsteady behavior of the flame
62
EXP
CFD
85 deg
90 deg
Line: EXPStar: CFD
Experiment by A.-M. Kypraiou
• What is the mechanism leading to heat release rate fluctuations?
Unsteady behavior of the flame
63
Stoichiometric mixture fraction isosurface coloured with temperature
a) Axial fluctuation of the flame location
b) Fluctuation of the area of the stoichiometric iso-surface
c) This leads to fluctuations of the heat release rate
The key mechanism leading to the fluctuations of the heat release rate seems related to the fluctuation of the flame surface.
• During the forced cycle the stoichiometricmixture fraction isoline moves in the axialdirection.
Forced non-premixed flame
64
white line = the stoichiometric mixture fractionblack line = zero axial velocity
HRRAxial
velocity
Experiments by A.-M. Kypraiou (CST, 2018, ETFS 2018)
• Instantaneous screenshot of the flame
Instantaneous flame structure
65
▪ The outer surface of the flame is not burning (red arrow)
▪ Rich pockets of mixture impinge the wall (green arrow)
˗ There the flame is close to a fully burning state
˗ Wall effects might need to be included in the computation
white line = the stoichiometric mixture fraction
mixture fraction OH mass fraction CH2O mass fraction HRR Temperature (K)
66
LES/CMC of realistic Rolls-Royce combustor (Giusti et al., ASME J Engng Gas Turb Power 2018)
Working with industry…
67
LES/CMC of realistic Rolls-Royce combustor (Giusti et al., ASME J Engng Gas Turb Power 2018)
68
LES/CMC of realistic Rolls-Royce combustor (Giusti et al., ASME J Engng Gas Turb Power 2018)
First validation of real combustor CFD against in-situ soot measurements.
Soot location captured OK.
69
LES/CMC soot with sectional model (Gkantonas et al, Fuel, 2020)
Coupling of a soot sectional model from Uni of Napoli (A. D’Anna’sgroup) with LES/CMC. Validation in laminar flame first:
70
LES/CMC soot with sectional model (Gkantonas et al, Fuel, 2020)
Cambridge RQL burner
Mean axial velocity for two flow split ratios
71
LES/CMC soot with sectional model (Gkantonas et al, Fuel, 2020)
Flame location captured OK
72
LES/CMC soot with sectional model (Gkantonas et al, Fuel, 2020)
Sooty locations captured OK.
Trends with flow split captured OK.
Careful: direct comparison not easy!
LBO CFD for premixed
73
CFD code: CCM+ v. 2021.1, thickened flame model, det CH4 chem
LES
Chase LBO condition & flame structure close to LBO
Simulations of Cambridge experimentby Sandeep Jella (Siemens Energy)
LBO CFD for premixed
74
16 m/s
30 m/s
Sandeep Jella (Siemens Energy)
LBO CFD for premixed
75
Very broad distributions of CH2O – CFD consistent with experiment
Sandeep Jella (Siemens Energy)
CH2OOH*
OH
CH2O
T
Conclusions – Day 4
Autoignition: kinetically-driven phenomenon. Is strain rate in engines high enough to delay
autoignition?
Structure of flame: mixture fraction-based (flamelet, CMC) and PDF methods work very
well. LEM, EDC demonstrate good results too (check literature).
Extinction: for jet & swirl flames, advanced flamelet, CMC, PDF methods work OK. Full
blow-off curve prediction validated with LES/CMC so far. TFM works well for many gt
combustion problems.
Soot: very sensitive to chemical model; need more experiments; validation for swirl flames
very little.
NOx: very little validation so far (“Delft piloted jet flame”); need similar focused efforts for
swirl flames.
Hierarchical approach: validate across many simpler flames first; across range of
conditions; then you can begin to trust your model and code.
Do not over-claim and over-generalise: turbulent flames can burn you…
76