Proceedings of ASME Turbo Expo 2018
Turbomachinery Technical Conference and Exposition
GT2018
June 11-15, 2018, Oslo, Norway
GT2018-76434
LES OF HYDROGEN ENRICHED METHANE/AIR COMBUSTION IN THE SGT-800
BURNER AT REAL ENGINE CONDITIONS
Daniel Moëll
Daniel Lörstad
Siemens Industrial Turbomachinery AB
SE-612 83 Finspång, Sweden
Xue-Song Bai
Dept. of Energy Sciences, Lund University
PO Box 118, SE-221 00 Lund, Sweden
ABSTRACT
DLE (Dry Low Emission) techniques are widely used today to
reduce the harmful NOx emissions associated with high combustion temperatures. In many DLE systems the fuel and air are premixed which effectively keep the flame temperature as low as possible, ideally equal to the turbine inlet temperature. By using premixing stability issues such as flash back and combustion driven
dynamics may occur. Operating the engine with hydrogen diluted
natural gas will decrease the flash back limits of the system due
to the high diffusivity and highly reactive nature of hydrogen. In
this study the stability effects of hydrogen diluted into methane
in the Siemens SGT-800 combustor is studied. The SGT-800
combustor is an annular combustor where the flame is stabilized
using a swirl burner combined with a sudden expansion combustor. The expansion gives rise to a vortex break down where
the flame stabilizes in the local low speed zones. Here a single
burner sector is studied using the flow solver Siemens PLM software STAR-CCM+. The turbulence is simulated through the use
of LES (Large Eddy Simulation) where the largest energy carrying flow scales are resolved and only the smaller scales are
modelled. The chemistry is coupled to the turbulent flow simulation by the use of FGM (Flamelet Generated Manifolds) which
are integrated using presumed probability density functions. The
FGM approach assumes that the local flame structure is laminar and that all species across a flame can be related to a set
of control variables. The control variables in this case are the
heat loss, the mixture fraction and its variance and a reaction
progress variable. In this paper two effects are studied, first the
transition from an atmospheric flame to a pressurized flame and
second the effect of hydrogen enrichment. The flame shape and
position are mainly affected by the transition from atmospheric
to high pressure, where the power density increases by almost
a factor of 20. The flame is moving further upstream closer to
the burner in all pressurized cases. The hydrogen enrichment
plays a strong role in how the combustion driven dynamics is
coupling with the acoustics of the rig. The high pressure pure
methane case show a strong pressure peak whereas the hydrogen
enriched case dampens that peak and distributes the energy to
other frequencies. This work shows that high fidelity CFD is capable of capturing complex flow and flame interactions such as
thermoacoustic instabilities in industrial scale systems.
NOMENCLATURE
A
Model constant
CS
Model constant
D
Mixing tube diameter
Dc
Diffusion coefficient
DZ
Diffusion coefficient
Si j
Strain rate tensor
Yk
Mass fraction of species k
Yc
Un-normalized reaction progress variable
Z
Mixture fraction
T
Temperature
cµ
Turbulence model constant
c
Reaction progress variable
h
Enthalpy
k
Turbulent kinetic energy
p
Pressure
r
Radial position along mixing tube radius
t
Time
ui
Velocity component along xi direction
x
Axial distance from burner exit nozzle plane
xi
Cartesian coordinate vector
∆
Mesh cell size
α
Diffusion of heat
1
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αk
δi j
νt
ν
ρ
τi j
τ
Species k weight coefficient
Kronecker delta
Sub-grid viscosity
Kinematic viscosity
Density
Stress tensor
Normalized simulation time
INTRODUCTION
During the last few decades large efforts have been spent to reduce the NOx (Nitric Oxides) emissions from industrial gas turbines. The technology developed has been based on the concept
of operating under lean pre-mixed conditions and thereby keeping the flame temperature low without the use of water or steam
injection; this technique is called DLE (Dry Low Emissions).
One of the key success factors when operating at DLE conditions
is sufficient mixing between fuel and air.
The Siemens SGT-800 is a 57 MW single-shaft gas turbine [1], utilizing an annular combustor with 30 Siemens 3rd
generation DLE burners, Figure 1, and a capability of operating
below 20 ppm NOx at 50-100% load using standard natural gas.
The combustor is equipped with a serial cooling system making
virtually all combustion air pass through the burners, keeping
the flame temperature similar to the turbine inlet temperature.
The SGT-800 burner consists of three critical components; swirl
generator, transition piece and a mixing tube. The swirl generator (swirler) adds swirl to the combustion air making sure that
the desired ratio between axial and tangential velocity needed to
maintain a stable combustion process is generated. The majority
of the fuel (main fuel) is also injected at the swirler inlet through
discrete injection points in the swirler wings, making sure that
the intended mixture between air and fuel is achieved. The transition piece transforms the air passage from an asymmetric shape
to a cylindrical shape while maintaining the ratio between axial
and tangential flow components as well as the desired mixture
profile. The mixing tube allows the air and fuel to further mix
until the desired fuel and air mixture required to maintain the stable, low NOx , combustion featured by the SGT-800 gas turbine
is accomplished.
In industry today there are typically demands on both
the accuracy and cost in combustion simulations. Traditionally RANS (Reynolds Averaged Navier Stokes) simulations have
been a very common approach for flow simulations. For simulations with reacting flows, RANS along with flamelets [2] or finite rate chemistry with global one step chemistry has been commonly used. In the RANS approach the turbulence modelling is
often based on eddy viscosity closures, for example the k − ε [3],
the k − ω [4] and the k − ω SST [5, 6]. There are also models where the Reynolds stresses are solved directly, for example
RSM-SSG [7] and RSM-LRR [8]. Another way of treating the
turbulence is the use of Large Eddy Simulations (LES) where
the larger energy carrying flow scales are directly resolved and
FIGURE 1: Siemens 3rd generation DLE burner.
only the smaller scales needs to be modelled. As for RANS eddy
viscosity based closures are commonly used in LES where for
example the Smagoringsky model and the dynamic Smagorinsky model are commonly used models [9,10]. Instead of directly
modelling the eddy viscosity the sub grid turbulent kinetic energy may be modelled instead [11]. When performing reacting
flow simulations the sub-grid closure is often very similar to the
RANS closures, but will play a less significant role since some
of the turbulence is resolved. When using finite rate chemistry
the closures range from rather simple models like the thickened
flame model [12] and the partially stirred reactor model [13]
which are typically not to computationally expensive to more
complex models like the linear eddy model [14] and the transported PDF (Probability Density Function) model [15] which are
very computationally expensive. For the flamelet type models the
filtered reaction rate is often related to the flame surface density
which is often modelled using an algebraic closure [16]. Another
type of flamelet combustion modelling is the FGM (Flamelet
Generated Manifold) approach [17, 18] where tables are used
to correlate species concentrations and laminar reaction rates as
function of certain key parameters, which may also be integrated
across presumed PDFs to account for turbulence. LES is starting to become feasible for complex industrial geometries at high
Reynolds numbers [19, 20] but the coupling to real gas turbine
geometries at relevant flow conditions is to a large extent missing [21].
Previous studies of the SGT-800 burner using URANS
and SAS (Scale Adaptive Similarities) combined with steady
flamelets [22], show good agreement on the large scale physics
but some model constant adjustments were required. A recent
mixing study of the SGT-800 burner [23], shows that LES is superior to URANS and SAS models in terms of fuel air mixing
predictions. The present study aims to explore the usage of LES
combined with a flamelet model to study the SGT-800 burner
fitted to an atmospheric combustion rig. The baseline case is the
atmospheric flow case with pure methane as fuel, air pre-heat and
flame temperature similar to engine conditions. In addition, two
pressurized cases, one with pure methane as fuel and one with
2
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surfaces within the combustion chamber. The total number of
cells is 28 million and most of the cells are distributed in the
swirler, mixing and reaction regions. The cell size in the flame
region and most of the mixing region is less than one millimetre
and the local cell size distributions are shown in Figure 3. Three
inlets are present with the mass flow, temperature, mixture fraction and reaction progress variable specified at each inlet. The
first inlet is for the combustion air, situated upstream the swirl
generator of the burner, cf. blue arrow in Figure 3. The second
inlet is for the main fuel supply, situated close to the swirl generator, cf. red arrow in Figure 3. The third inlet is for the pilot fuel
supply, situated in the burner tip close to the combustion chamber, as indicated by the red circle in Figure 3. In this case 97% of
the total fuel flow is through the main fuel inlet and 3% is through
the pilot fuel inlet. The outlet, situated downstream the combustion chamber in the exhaust system, is a zero gradient pressure
outlet. All walls are treated as no-slip and adiabatic. The initial
conditions are based on steady RANS simulations. To reduce the
influence of the acoustic impedance of the inlet and outlet boundaries, a large part of the inlet plenum and exhaust system of the
rig has been included in the computational model. The grid sensitivity of this burner is investigated in [22, 23] where the present
grid is sufficiently resolved. In the atmospheric case, Popes criterion for LES [26], M =< ksgs > /(< ksgs > + < kres >) < 0.2
is calculated and depicted in Figure 3c. Here it is shown that the
criterion is satisfied in all regions with exceptions in the film air
holes and pilot cavity.
FIGURE 2: Atmospheric combustion rig set-up.
methane enriched by 30% hydrogen, with 20 bar pressure are
simulated using the same geometry as in the atmospheric case.
The study explores the differences and similarities between the
three cases which is an important step in the transition from simulating atmospheric lab scale flame towards using high fidelity
methods for real gas turbine geometries.
COMPUTATIONAL CASE
In this case the burner is fitted to an atmospheric combustion
test rig, Figure 2. The test rig offers optical access to most of
the flame region and OH-PLIF measurements have been carried
out [24]. Besides the OH-PLIF data there is also dynamics pressure measurement available. Concentration measurements from
water rig measurements of the same burner is also available for
comparison of the mixing characteristics of the burner. Three
different cases are simulated using the same geometry. The first
case is an atmospheric case where the boundary conditions used
in the simulations are based on flow conditions from the experimental rig described in [24]. The air is pre-heated to 693K
whereas the fuel is kept at ambient conditions, similar to real engine conditions. The global equivalence ratio in the experiments
and simulations is scaled to represent the engine flame temperature. Natural gas with approximately 90% methane and 10%
higher hydrocarbons are used as fuel in the experiments whereas
pure methane is used in the simulation, where the fuel flow is
corrected to obtain the same flame temperature. The second case
is a high pressure case with 20 bar pressure. The air and fuel
flows are scaled accordingly compared to the atmospheric case,
similar to the work done in [25]. The third case is also a 20 bar
case but with 30% (by volume) hydrogen mixed into the natural
gas. The air flow is the same as in the second case whereas the
fuel flow is scaled so that the global flame temperature is kept
constant among all cases. The Reynolds number of the atmospheric case is in the order of 100, 000 based on the mass flow
through the burner and the burner diameter and in the order of
2, 000, 000 in the high pressure cases.
The mesh is a polyhedral one with prism layers on all wall
NUMERICAL METHOD
In this work the flow solver Siemens PLM software STARCCM+ v12.02 [27], is used. The turbulence is treated using
LES and the chemical reactions are treated using the FGM approach [17, 18]. The pre-computed FGM table is based on the
chemical kinetics mechanism GRI mech 3.0 [28] combined with
a 0-D reactor model. In FGM the inner structure of a laminar
flame is assumed. Tables are used to tabulate the inner flame
structure based on some key parameters. The key parameters in
this particular case are mixture fraction, mixture fraction variance, reaction progress variable and heat loss. This methodology
has recently been applied to a gas turbine model combustor [29]
with reasonable agreement with experimental data. The reaction progress variable is monotonically decreasing or increasing
across the flame and is normally defined based on temperature or
some major species. All other species of the laminar flame may
be related to the reaction progress variable. The un-normalized
reaction progress variable may be defined as weighted linear
combinations of species mass fractions:
N
Yc =
∑ αkYk
(1)
k=1
where αk is a weight function and Yk is the k0 th species mass
fraction. Many different combinations of species and weight fac-
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αCO2
1
αH20
0.52
αC2H2
0.16
αH
-0.38
αCO
0.91
αH2
1
αOH
-0.66
αO
0.4
TABLE 1: Progress variable weight function
To represent the fuel and air mixing as well as the combustion,
three transport equations, one for mixture fraction, one for mixture fraction variance and one for the reaction progress variable,
are solved in addition to transport equations for velocity, continuity and specific enthalpy:
(a)
∂ ρ̄ ∂ ρ̄ ũi
+
=0
∂t
∂ xi
(3)
∂ ρ̄τirj ∂ p̄ ∂ τ̄i j
∂ ρ̄ u˜j ∂ ρ̄ ũi u˜j
+
=−
−
+
(4)
∂t
∂ xi
∂ xi
∂xj
∂ xi
fi − ρ̄ h̃ũi
∂ ρ̄ hu
∂
∂ h̃
D p̄
∂ ρ̄ h̃ ∂ ρ̄ ũi h̃
+
=−
+
ρ̄α
+
∂t
∂ xi
∂ xi
∂ xi
∂ xi
Dt
(5)
(b)
+ τi j
∂uj
∂ xi
∂ ρ̄ ∂ ρ̄ ũi c̃
∂
∂
+
=−
(ρ̄ uf
i c − ρ̄ ũi c̃)+
∂t
∂ xi
∂ xi
∂ xi
∂c
ρDc
+ ω̇¯ c (6)
∂ xi
∂ ρ̄ ∂ ρ̄ ũi Z̃
∂
∂ f
+
=−
ρ̄ ui Z − ρ̄ ũi Z̃ +
∂t
∂ xi
∂ xi
∂ xi
∂Z
ρDZ
(7)
∂ xi
Here the mixture fraction is formed based on a unity Lewis number assumption.
(c)
Sub-grid closure for LES
In this case, the residual stress tensor, τirj , in the filtered velocity
equations is closed using the Smagorinsky sub-grid turbulence
model [9], where the sub-grid viscous stress tensor is directly related to the strain rate tensor through the sub-grid eddy viscosity:
FIGURE 3: Overview of computational grid with air and fuel
inlets specified with blue and red arrows respectively (a and b)
and Popes criterion for LES quality [26] (c).
tors have been proposed [17, 30–32]. Recently an optimized reaction progress variable for methane/hydrogen/air mixtures has
been presented [33], where eight species are used to define the
progress variable where the weight factors are summarized in
Table 1.
This approach is adopted is this study. The normalized
progress variable is defined based on the weighted species mass
fractions as:
Yc −Yc0 (Z)
c = eq
(2)
Yc (Z) −Yc0 (Z)
τirj −
1
τi j δi j = −νt S̃i j = −νt
3
∂ ũi ∂ u˜j
+
∂ x j ∂ xi
and the sub-grid eddy viscosity is modelled as:
q
2
νt = (CS ∆) |S̃|, |S̃| = S̃i j S̃i j
(8)
(9)
where the Smagorinsky constant, CS , is assigned a value of 0.1.
Wall damping is applied through the use of van Driest wall damping function [34] with a model constant, A, value of 25. All scalar
flux terms (first term on RHS of Eq. 5-7) are closed using a gradient diffusion assumption. No radiation is treated in these sim-
4
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2
1
<u>/u
R
, <u'>/u
R
[-]
3
0
-1
-3
-2
-1
0
1
2
1
2
Center line location x/D [-]
1
, <T'>/T
R
[-]
(a)
FIGURE 4: Reaction progress variable compared to PDF of OH-
<T>/T
R
gradient from PLIF data [24].
0.8
100%CH4 , 0%H2 , atm
0.6
70%CH4 , 30%H 2 , 20bar
0.4
0.2
0
-3
ulations so the radiation term has been removed from Eq. 5. The
remaining term that needs closure is the filtered reaction rate in
the progress variable equation, which is closed based on the FGM
tabulated reaction rates. To account for the effect of turbulence
the final reaction rate is integrated across two presumed PDFs,
one for the mixture fraction and one for the reaction progress
variable.
100%CH4 , 0%H2 , 20bar
-2
-1
0
Center line location x/D [-]
(b)
FIGURE 5: Axial velocity and temperature along the burner cen-
tre line where solid lines are mean values and dashed lines are
fluctuations.
RESULTS AND DISCUSSION
Method validation
The time average of the reaction progress variable for the atmospheric case is depicted in Figure 4. To verify that the flame
position and shape are well predicted, OH-PLIF (Planar Laser
Induced Florescence) data from [24] is used. The operational
conditions are identical between the experiments and the simulations with the exception of the pilot flames, which are not active
in the OH-PLIF experiments. In [24] gradient tracking has been
used to track the OH gradient from the fresh reactant side towards
the burnt side. This OH gradient is often very sharp and is often
used as a flame front tracker. The data used here for comparison
is the PDF of the OH-PLIF gradient which gives an overview of
where the flame is most likely stabilized and how much the flame
is moving. The PDF of the OH gradient is pasted on top of the
time averaged reaction progress from the CFD in the right half
of Figure 4. The comparison between the CFD predictions and
the PLIF data shows that the cone angle of the inner part of the
flame as well as the average position of the flame are very well
predicted by the CFD code. The outer part of the flame is in reasonable agreement but there is a lack of OH gradient PDF in the
PLIF data which is most likely due to the fact that there is no
pilot flames present in the OH PLIF data.
lines denote mean values and dashed lines fluctuations. The values are normalized using the burner exit velocity based on the
mass flow and the global adiabatic flame temperature. An qualitative overview of the three different flow cases is presented in
Figure 6. Here the time average of axial velocity and temperature
(upper half of figures) along with their time averaged fluctuations
(lower part of figures) are shown in the burner centre plane. The
Iso-line of zero time averaged axial velocity and time averaged
progress variable of 0.5 is shown in the upper and lower row respectively. The flow is being accelerated and swirled through
the swirl generator, where the majority of the fuel is also added.
A forward stagnation point followed by a central re-circulation
zone is located close to the burner exit in all three flow cases.
The forward stagnation point and central re-circulation zone are
caused by a vortex break down, which occurs when the rotating
flow is geometrically expanded at the burner exit into the combustion chamber [35]. All three flow cases show a high axial
velocity close to the burner centre line with the highest value
just upstream the mixing tube close to x/D = −2.4 followed by
a slow decay until x/D ≈ −0.5 where the forward stagnation
point is located on a time averaged basis. The decay in axial
velocity along the centre line is due to radial pressure gradient
present in the swirling flow. The axial velocity upstream the
stagnation zone is decreasing with the increasing pressure for
both high pressure cases with the largest decrease in the pure
methane case. The increase in flow velocity for the hydrogen enriched case relative to the high pressure methane case is due to
Effects of pressure and hydrogen enrichment
Time averaged axial velocity and temperature are presented
quantitatively along the burner centre line in Figure 5 where solid
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(a) <ũ> and <ũ0 >, 100% CH4 /0% H2 , Atm
(b) <ũ> and <ũ0 >, 100% CH4 /0% H2 , 20bar
(c) <ũ> and <ũ0 >, 70% CH4 /30% H2 , 20bar
(d) <T̃ > and <T̃ 0 >, 100% CH4 /0% H2 , Atm
(e) <T̃ > and <T̃ 0 >, 100% CH4 /0% H2 , 20bar
(f) <T̃ > and <T̃ 0 >, 70% CH4 /30% H2 , 20bar
FIGURE 6: Time average (upper half of figures) and RMS of fluctuation (lower half of figures) of axial velocity (upper row) and
temperature (bottom row) for all flow cases. Iso-line shows zero time averaged axial velocity (upper row) and time averaged progress
variable of 0.5 (bottom row)
is M-shaped in all three cases, with an upstream stabilization
point close to x/D = −0.3 in all three cases. The atmospheric
case show a flame with a high volume whereas the two pressurized cases show more compact flames. The outer shear layer of
the M-shaped flame is stabilized by the pilot flames, which provides heat to the outer re-circulation zone outside of the flame.
In the hydrogen case, the pilot produces higher temperatures than
the methane cases, even though the pilot fuel ratio is kept constant. This is a local effect of fuel air mixing in the pilot flame
region where a part of the combustion air is injected to mix with
the pilot fuel. One major difference between the atmospheric
case and the pressurized cases is the time averaged shape of the
pilot flame. From the iso-line of < c̃ >= 0.5 it is revealed that
in the atmospheric case the pilot flame is shaped like a sphere
and in the high pressure cases it is M-shaped. This change in
pilot flame shape will play an important role in the pilot flame
stabilization and its interaction with the main flow, which will
be discussed later. Studying the temperature field close to the
swirler walls there are clear traces of the discrete fuel injection
points in the swirler where the cold fuel is injected into the preheated air stream. The RMS fluctuations of temperature show
non-zero values close to the fuel injection region and close to the
flame region. The non-zero values in the fuel injection region is
the increased volumetric fuel flow rate. All three cases also show
a clear re-circulation zone featured by a negative axial velocity
downstream of the burner exit at x/D = 0. The appearance of
the re-circulation zone differs between the pure methane cases
and the hydrogen diluted case. Both methane cases show a local
minimum in axial velocity, located approximately x/D ≈ 0.75
apart from each other, which is not seen in the hydrogen enriched
case where the axial velocity is steadily decreasing from the start
of the forward stagnation point at x/D = 0.5 and two burner diameters into the combustion chamber. The axial velocity RMS
fluctuations are also similar between the three flow cases. The
RMS fluctuations are generally low close to the swirler walls
and rather even throughout the entire mixing tube with a ground
level of < u0 > /uR = 0.25 which is due to turbulent fluctuations. The highest RMS fluctuations are found close to the burner
exit region, where the highest axial velocity gradients are found,
with peak values of < u0 > /uR = 1.0. The level of fluctuations
are on the same order as the axial velocity close to the burner
exit and stems from both turbulence and spatial movements of
the forward stagnation point. The width of the fluctuation peak
shows how much the forward stagnation point is spatially distorted throughout the simulations.
The time averaged temperature reveals that the main flame
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due to the unsteady nature of the jet in cross-flow fuel injection
arrangement [36, 37]. The non-zero values in the flame region
is due to the movements of the unsteady flame. The RMS of
temperature fluctuations show that the flames are spatially stabilizing between −0.4 < x/D < 0.75 in the pressurized cases and
between −0.3 < x/D < 1.5 in the atmospheric case. The shape
of the RMS temperature in the flame region is very similar between the two high pressure cases but the peak value is higher in
the hydrogen enriched case. The local flame stabilization point is
dependent on the local flow speed and the local turbulent burning
velocity. The laminar flame speed is decreasing with an increasing pressure at the same conditions but the turbulent flame speed
is increasing with an increasing pressure [38], which, combined
with a higher power density in the high pressure cases, makes the
high pressure flames stabilize further upstream the atmospheric
flame. In the hydrogen enriched case the flame stabilization point
will be affected by both the increased flow velocity and velocity
fluctuations upstream the flame as well as the increase in laminar
flame speed associated with hydrogen enrichment. The laminar
flame speed properties of the different mixtures will be discussed
next.
100%CH 4 , 0%H2 , atm
1.25
100%CH 4 , 0%H2 , 20bar
70%CH 4 , 30%H 2 , atm
1
S L [m/s]
70%CH 4 , 30%H 2 , 20bar
0.75
0.5
0.25
0
1300
1400
1500
1600
1700
1800
1900
2000
2100
2200
T a [K]
FIGURE 7: Laminar flame speed as function of adiabatic flame
temperature with a pre-heat of 693 K.
laminar flame speed is seen in Figure 5 where the forward stagnation point is moving more downstream than the flame location
with the hydrogen enrichment, indicating a higher burning velocity. Effects of un-even Lewis numbers are not accounted for in
the transitions between laminar and turbulent flame speed which
could have an impact on the global flame location in the hydrogen enriched case.
Laminar premixed flame properties
Laminar flames were simulated using both methane and
methane enriched by 30% hydrogen under the same operating
conditions as the three flow cases in this study. The flames are
studied using Cantera, [39], combined with GRI Mech 3.0 [28],
which is also used as a basis for the FGM tabulation in the CFD
predictions. The results are shown in Figure 7 where the laminar
flame speed is plotted against the adiabatic flame temperature
for the different fuel lean cases . A fourth case, 70% methane
and 30% hydrogen under atmospheric conditions, is added for
comparison. Here the effect of the hydrogen under atmospheric
pressure is clearly seen as a distinct increase in laminar flame
speed given a certain adiabatic flame temperature. However this
effect has almost vanished for the high pressure flames where the
adiabatic flame temperature is lower than 1900 K, which is the
case for the present simulations. At the present flame temperature the relative increase in laminar flame speed is 25% in the
atmospheric case but only 12% in the pressurized case. This is
due to the competition of branching and termination for the H +
O2 reaction, which plays an important role for the laminar flame
speed. The increase in laminar flame speed with hydrogen enrichment at atmospheric conditions is due to the larger amount
of radicals available for consumption, [40]. At atmospheric pressure the chain branching reaction H + O2
OH + O dominates
whereas at high pressure the terminating reaction H + O2 +M
HO2 + M dominates, [41], which reduces the amount of H radicals available, thereby reducing the effect of hydrogen addition
to the laminar flame speed. Since the FGM library is computed
based on laminar kinetics, these results will have a direct impact
on the turbulent flame calculations as well. The small increase in
Fuel and air mixing
The fuel and air mixing characteristics upstream the flame at
x/D = −1.2 are depicted in Figure 8. Here the mixture fraction and the RMS fluctuation of mixture fraction from three flow
cases are compared to concentration measurements obtained in
a water rig, [23]. The magnitude of the concentration maximum
and minimum agrees well between the experimental data and the
atmospheric flow case, but both locations are shifted approximately r/D ≈ 0.05 towards a higher radius. The trend of the
RMS fluctuations in the atmospheric flow case is captured well
but the magnitude is higher than the experimental data, which is
most likely due to an under-prediction of the concentration fluctuations in the water rig experiments due to insufficient shutter
speed in the camera, [23]. In the high pressure pure methane
case the mixture fraction peak value is predicted at a higher radius and with a higher value than the atmospheric case. The mixture fraction minimum is predicted at the same radius but with a
lower value. This indicates that the mixing rate is slower in the
pressurized case as compared to both the water rig case and the
atmospheric reacting case. This observation is in-line with the
observations in [23] where LES data of a non-reacting 20 bar
case is compared to water rig LES data and experiments. The
mean value of the hydrogen enriched case is lower than the pure
methane cases due to the lower fuel mass fraction as a result of
the constant flame temperature. Besides the shift in mean mixture fraction the hydrogen enriched profile is very similar to the
profile from the atmospheric flow case. The local mixing will
7
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0.5
in simulation length is accounted for by the use of zero padding.
The experimental data in this case does include the pilot flames
with the same fuel split as in the CFD case. Comparing the two
pressure traces from the atmospheric flow cases it is observed
that the two raw signals have very similar appearance. This is
confirmed by comparing the FFT where the two first regions of
pressure density, located at St ≈ 0.19 and St ≈ 0.67 are in excellent agreement, both in terms of Strouhal numbers and in terms
of power amplitude. The third dominant pressure power peak is
found close to St = 1.5. Here the CFD is predicting a slight shift
in frequency towards higher values but the power is still very
well predicted. This shows that the unsteady pressure fluctuations in a highly turbulent flame are well captured by the CFD
model. The unsteady pressure fluctuations consist of both acoustic pressure fluctuations which will depend on the combustion rig
geometry and flame/flow interactions where unsteady flow phenomenons such as the presence of vortex break down [35] and
precessing vortex core (PVC) [42] structures will play a key role.
In the pressure trace of the pressurized cases it is observed that
the pressure peak values are in the order of 25-30 times higher
than the atmospheric pressure peaks which is due to the factor of
20 increase of pressure and thermal power. The pressure peaks
are found at the same dominant Strouhal numbers as in the atmospheric case. For the pure methane case the peak at St = 0.67 is
the most dominant one with a peak value 150 times higher than
the maximum peak value from the atmospheric case.
A standing acoustic wave will have a frequency/geometry
relation such as f = c/2L where c is the local speed of sound
and L is a length between the end surfaces. Inside the combustion chamber the speed of sound of the fully reacted gas
is c ≈ 10ure f , the combustion chamber length starting from
the burner dump plane ending at the contraction downstream
is Lcomb ≈ 8D and the width of the combustor at the square
window section is Wcomb ≈ 3.2D. The two lowest eigenfrequencies inside the combustor, presented in terms of Strouhal
numbers, are Stcc1 = c/(2 ∗ Lcomb ) = 10/(2 ∗ 8) = 0.625 and
Stcc2 = c/(2 ∗Wcomb ) = 10/(2 ∗ 3.2) = 1.5625 which are in very
good agreement with the second and third dominant peaks in Figure 9. Based on this geometrical analysis, the only way the first
dominant pressure peak at St = 0.19 will fit inside the rig is if it
is an axial pressure mode ranging from the plenum upstream the
burner down to the exhaust part of the rig. From detailed analysis of the flame movements close to the burner centre axis it is
concluded that the flame is oscillating with St ∼ 0.1 − 0.2 which
is how energy is feed into the first dominant pressure mode.
The second mode close to St = 0.67 is investigated further in
Figure 10. In Figure 10 the centre plane pressure is presented
through one pressure cycle at St = 0.67 along with the burner tip
surface, where the pilot flames are situated, and isovolumes of
T /Tre f > 1.16. Here the pressure mode shape inside the combustion chamber is clearly seen. It is also discovered that the pilot flames are strongly interacting with the pressure wave. When
0.45
r/D [-]
0.4
0.35
100%CH4 , 0%H2 , atm
100%CH4 , 0%H2 , 20bar
0.3
70%CH4 , 30%H 2 , 20bar
Water rig experiments
0.25
0.2
0.15
0.1
0.05
0
0.7
0.8
0.9
1
1.1
1.2
0.2
0.25
Normalized mixture fraction [-]
0.5
0.45
0.4
0.35
r/D [-]
0.3
0.25
0.2
0.15
0.1
0.05
0
0
0.05
0.1
0.15
Normalized variance of mixture fraction [-]
FIGURE 8: Fuel air mixing statistics at x/D = −1.2 upstream the
burner exit.
play an important role in the flame stabilization process. If for
example rich pockets of fuel are present upstream the flame front,
the local flame stabilization point will move upstream towards
the un-burned mixture and vice versa.
Thermoacoustic analysis
The fluctuating pressure has been measured during the atmospheric experiments at the location of the pressure transducer as
indicated in Figure 2. The pressure in all three flow cases is sampled at the same location throughout the entire simulation time.
The fluctuating pressures are presented in Figure 9 as a function of the normalized simulation time τ, where τ is normalized
based on the burner reference velocity and diameter such that
τ = t ∗ uR /D. The Fast Fourier Transform (FFT) of the pressure
traces are presented as well where the frequencies are presented
in terms of Strouhal numbers. The Strouhal number is calculated based on the frequency spectra from the FFT, the burner
diameter and the burner reference velocity, uR . The fluctuating
pressure is normalized by a reference pressure and the difference
8
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100
75
1
Normalized pressure [-]
Normalized pressure [-]
1.5
0.5
0
-0.5
-1
-1.5
50
25
0
-25
-50
-75
-100
0
10
20
30
40
50
0
10
20
Samplingtime, τ [-]
0.3
40
50
20
4
/0%H 2 , atm
Power amplitude [-]
Experimental data, 100%CH
CFD, 100%CH 4 /0%H 2 , atm
0.25
Power amplitude [-]
30
Samplingtime, τ [-]
0.2
0.15
0.1
0.05
0
CFD, 100%CH 4 /0%H 2 , 20 bar
CFD, 70%CH4 /30%H 2 , 20 bar
15
10
5
0
0
1
2
3
4
0
Strouhal number [-]
1
2
3
4
Strouhal number [-]
FIGURE 9: Pressure sampled in the CFD simulations at the location of the pressure transducer in the experiments (top) with the
corresponding FFT (bottom).
the peak is located close to the burner some of the pilot flames
produces large zones of temperatures above 1.16 and when the
peak is located close to the combustion chamber exit no traces of
temperatures above 1.16 are seen. This will create a strong interaction between the heat release and the acoustic field which may
explain why the amplitude of the 20 bar pressure traces in Figure 9 is increasing with time. This might be due to the fact that
the pilot flames are premixed. The amount of air and fuel feed
to the flames will be dependent of the local pressure from over
both the fuel nozzles and the air passages. If instantaneous pressure is high in front of the pilot flames air will go through other
passages, such as the swirler, whereas the fuel has no other way
to go due to the separate pilot fuel feed. How strong this interaction will be is likely linked to the shape of the pilot flames. The
pilot flame shape is changing with the pressure which may cause
the strong interaction between the pilot flames and the eigenfrequency of the combustion chamber.
spheric and high pressure (20 bar) conditions. Pure methane
is used in the atmospheric case whereas both pure methane and
methane enriched by 30 % hydrogen are used in the high pressure
cases.
The CFD predictions in the atmospheric case are in good
agreement with available measurement data in the form of OHPLIF data, pressure transducer data as well as concentration measurement data. The flame shape and position are predicted well
and the interactions between flow and flame are also reasonably
well predicted.
The pressurized cases shows a more compact flame which
is due to the increased thermal density of the flame. The flame
position is moving towards the burner exit when going from atmospheric to pressurized conditions. The difference in flame
shape and position with and without hydrogen enrichment is not
very strong, which is supported by the laminar flame data provided. The difference in the fluctuating pressure between the two
different fuels is much more severe, since the flow/flame dynamics is interacting more with the acoustic field of the rig in the case
of pure methane. This shows that even though the time averaged
CONCLUDING REMARKS
In this study LES based on the FGM combustion model is
adopted to study the Siemens SGT-800 burner at both atmo-
9
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Norm. Pressure
50
0
-50
42
42.5
43
43.5
44
43.5
44
43.5
44
43.5
44
43.5
44
43.5
44
43.5
44
Norm. Pressure
τ
50
0
-50
42
42.5
43
Norm. Pressure
τ
50
0
-50
42
42.5
43
Norm. Pressure
τ
50
0
-50
42
42.5
43
Norm. Pressure
τ
50
0
-50
42
42.5
43
Norm. Pressure
τ
50
0
-50
42
42.5
43
Norm. Pressure
τ
50
0
-50
42
42.5
43
τ
FIGURE 10: Time series of the St = 0.67 pressure mode in the pure methane 20 bar case with centre plane pressure normalized by
a reference value (left column), burner tip surface combined with isovolume of T /Tre f > 1.16 (middle column), and instance of time
combined with location on pressure trace at the location of the pressure transducer (right column).
10
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statistics are similar between different fuels, second order effects
such as thermoacoustic fluctuations may play a large role in the
performance of a fuel if it is interacting with the acoustic eigenfrequencies of the system. Understanding this coupling between
the fuel and transient flow effects such as thermoacoustics and
flashback is of key importance for gas turbine developers. Scale
and time resolved CFD seems to be a very promising method to
provide such information.
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ACKNOWLEDGEMENT
This work was financed by Siemens Industrial Turbomachinery
AB and the Swedish research council, VR.
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the content of this paper, in whole or in part, for any purpose must
be addressed to Siemens Industrial Turbomachinery AB directly.
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