Supplemental Information: Particle Emission Characteristics of a Gas Turbine with a Double
Annular Combustor
Adam M. Boies, Marc E. J. Stettler, Jacob J. Swanson, Tyler J. Johnson, Jason S. Olfert,
Mark Johnson, Max L. Eggersdorfer, Theo Rindlisbacher, Jing Wang, Kevin Thomson, Greg
Smallwood, Yura Sevcenco, David Walters, Paul Williams, Joel Corbin, Amewu A. Mensah,
Ramin Dastanpour and Steven N. Rogak
Emission Indices
Black carbon emission indices, EI(BC), were compared for three different laser induced
incandescence (LII) instruments on three different lines. The results of measurements on the
FOCA, Annex and SAMPLE III lines are shown in Figure S1, and demonstrate that the
differences in measured EI(BC) among instruments and sample lines is less than the different
EI(BC) at each given thrust setting. For each thrust setting the variability of the CFM56-5B42P EI(BC), indicated by the grey error bars, as measured by each LII overlaps demonstrating
that no distinction can be made by the measurements from individual instruments or lines at a
given thrust. These results establish that reported EI(BC) values using one LII on one line are
not statistically different than using other LII results on other lines.
Figure S1: Black carbon emission index, EI(BC), for CFM56-5B4-2P at various thrust
settings as measured by LII on three separate lines shown in Figure 1 for 28th April. The inset
is a rescaled version of EI(BC) for DAC operation.
The variability for particle number based emission indices (EIn) was low and was omitted
from the main article to allow for better view of symbols. SI Figure 2 below is a reproduction
1
of Figure 4 within the main article with the addition of 5 and 95% variability. The variability
within the system was the greatest source of uncertainty within the system.
Figure S2: Black carbon number emission index, EIn, for CFM56-5B4-2P as measured by
CPCs with D50 cut points of 10 nm (open symbols) and 23 nm (cross and plus sign) on two
separate lines (FOCA and SAMPLE III) for various thrust settings. Error bars represent the
90% variability interval within a given thrust setting.
Air-to-Fuel Ratio
Global air-to-fuel ratio was as determined from undiluted CO2 measurements according to the
method defined by the Office of Aviation Research (2006). The air-to-fuel ratios relative to
the stoichiometric air to fuel ratio (SAFR = 22.72) are shown in Figure S2 for varying thrust
settings. Single pilot combustion occurred during low thrust settings (< ~25% full thrust) and
resulted in a global lean combustion. However, the local stoichiometry within the pilot
combustor is rich (not measured) and only mixes with excess air downstream of the pilot
combustion zone. The rich combustion ensures stability of the flame. During dual annular
combustion the global air-to-fuel ratio drops, and the second combustor operates in a locally
lean-burn condition. Local stoichiometry data was not measured for either pilot combustor or
DAC thrust settings.
2
Figure S3: Global air-to-Fuel (AFR) ratio for varying thrust settings over the range of thrust
settings.
3
Effective Density
The particle effective density was determined as a function of particle mobility in the manner
described by Johnson et al. (In Press 2014) where 𝑘 = 11.92 and 𝐷fm = 2.76. The effective
density of the mean mobility diameter is plotted in Figure S3 as a function of thrust setting.
The effective density is seen to decrease from ~900 kg/m3 to ~720 kg/m3 with increased
thrust setting during pilot combustion mode. When comparing these results to Figure 5 where
it is shown that particle mobility diameter increases over the same thrust range, it is apparent
that the effective density of particles decreases as the particle diameter increases. The change
in effective density is also known to impact the signal decay from LII measurements,
resulting in longer decay times for particles of greater effective densities. For DAC thrust
settings (> ~25% full thrust) more than 90% of the effective densities are determined to be
between 800 to 900 kg/m. In almost all cases the effective densities, as determined by using
mobility measurements from the DMS500 (FOCA, SAMPLE and Gantry) are greater than
the effective densities determined by using the nanoSMPS (SAMPLE) and longSMPS
(SAMPLE/FOCA).
Figure S4: Number mean aggregate effective density versus thrust as determined by massmobility relations at a range of engine thrusts. The effective density is derived from Eq. 2 and
the mobility measurements shown in Figure 5 from DMS500 (FOCA – asterisk, SAMPLE –
triangle, Gantry - Circle), nanoSMPS (SAMPLE – diamond), longSMPS (SAMPLE/FOCA –
square).
Aggregate Mobility Diameter and Mass
The mean aggregate mobility diameter was measured for multiple CPMA-selected aggregate
masses at different thrust settings (circle – 9%, triangle – 17%, square – 21%, star – 24% and
4
diamond – 31%). The results are shown in Figure S4 for both undenduded (white fill) or
denuded (black fill), where there is a similar power-law relationship observed for all samples.
These results are equivalent to those shown in Johnson et al. (In Press 2014).
Figure S5: Measured mean aggregate mobility for a CPMA-selected aggregate mass. Thrust
settings are represented by symbols (circle – 9%, triangle – 17%, square – 21%, star – 24%
and diamond – 31%), face color indicates whether the samples were undenduded (white) or
denuded (black) and line type indicates whether the samples were collected from the FOCA
(solid) or Annex III line (dashed).
5
Primary Particle Diameter
The volume area equivalent primary particle diameter was determined as described in §2.2,
Eq. 4, which relates the volume area equivalent primary particle diameter within an aggregate
to the measured aggregate mass and mobility. As described in the text accompanying Figure
6, volume area equivalent primary particle diameter increases with aggregate mobility,
0.8
whereby a power-law relationship of 𝑑va = 0.79 𝑑m
± 25% encapsulates all but one of the
measured data points. Individual power-law fits are shown in Figure S5, which demonstrate
that higher R2 values (R2 > 0.96 for all but one thrust setting) can be achieved when fitting
individual thrust settings. The resulting 𝐷va values vary from 0.65 to 0.98 for the individual
fits with 𝑘va values that vary from 1.39 to 0.44, where larger 𝐷va correspond to smaller 𝑘va
values.
Figure S6: Volume area equivalent primary particle diameter as a function of aggregate
mobility diameter as measured by mass and mobility analysis. Primary particle size is
determined according to Eq. 4. The blue lines correspond to the empirical fit with the power
law form of Eq. 5 for each thrust setting.
6
Mass-Mobility Exponent
The mass-mobility exponent, 𝐷fm , was compared for a method by which it was determined
by effective density data to Eq. 2, and from a method of fitting the data to the volume area
equivalent primary particle data. The ordinate represents the mass mobility exponent, 𝐷fm ,
determined by taking the best fit to effective density data as conducted by Johnson et al. (In
Press 2014). The abscissa represents the mass mobility exponent as determined by finding
𝐷va from a least-squares fit to primary particle data as shown in Figure 6 and solving the
relation, 𝐷fm = 2𝐷α − 𝐷va (2𝐷α − 3) (Eq. 5 in main article) with a 𝐷𝛼 =1.069. The difference
in the Dfm is small and arises from the differences of conducting a least squares fit to the
same data weighted in different manners. These results confirm that using the Eggersdorfer
constant, 𝐷α =1.069, allows for conversion between 𝐷fm and 𝐷va .
Figure S7: Mass-mobility exponent, 𝐷fm , determined by taking the best fit to effective
density versus mass-mobility exponent as determined by a fit to primary particle data shown
in Figure S5 for 𝐷va and calculated using Eq. 5.
Dynamic Shape Factor
Dynamic shape factor may be determined by comparing the measured mobility and
aerodynamic diameters. AMS-measured vacuum aerodynamic diameter was measured in
parallel to mobility measurements, see Figure 1. The mean mobility diameter and mean
vacuum aerodynamic diameter were plotted and compared to lines of constant dynamic shape
factor, 𝜒, as defined by DeCarlo et al. (2004). The dynamic shape factors of the measured
aggregates are equal to or less than 1, which is a non-physical result. It was concluded that
7
insensitivity of the AMS to vacuum aerodynamic diameters less than 50 nm biased the
measurements, resulting in mean measured vacuum aerodynamic diameters that were skewed
to larger diameters. Further work is needed to improve the sensitivity of AMS for aggregates
with diameters less than 50 nm in order to make definitive measurements of dynamic shape
factors for gas turbine BC particles.
Figure S8: Vacuum aerodynamic diameter and mobility diameter of aggregates measured at
seven different thrust settings (black diamonds). Lines of constant dynamic shape factor, χ, as
defined by DeCarlo et al. (2004), are shown along with general relations for 𝜒 for aggregates
of less than and greater than 60 primary particles.
TEM Image Processing
A semi-automatic image processing program developed in MATLAB was used for the
analysis of the TEM micrographs (Dastanpour et al., 2014). Grayscale TEM image (Fig. 8-a)
are binarized by setting threshold level for the brightness of the image (Fig. 8-b). Aggregate
projected area, maximum length and width, 2-D gyration radius, and projected area
equivalent diameter of the aggregates are measured from the binary image. Primary particles
are sized manually. To enhance the accuracy, large aggregates are cropped into several
sections. Since primary particles are not perfect spheres, the reported diameter is determined
by the mean of the diameter measured in two different directions (Fig. 8-c).
8
Figure S9: TEM image processing steps: a) Original TEM image; b) Binarized TEM image;
c) Manual primary particle sizing
Although manual measurement of the primary particle size is time-intensive, unlike
automatic methods (Bescond et al., 2014; Grishin et al., 2012), it does not require prior
information on the size distribution of the monomers in aggregates. Grishin’s method is also
sensitive to model parameters and has to be calibrated for different TEM images frequently.
Line Loss Correction Factor
As shown in Figure S9, the ratio of line loss corrected to measured particle number and
particle mass concentrations were determined for each thrust setting. The particle number line
loss correction factors (𝐶𝐹PN ) varied from 4.4 to 1.7 with the highest correction factor at low
thrust setting, and the lowest at the highest thrust setting of pilot combustion mode. Similarly,
the particle mass correction factors (𝐶𝐹PM ) were highest (2.2) at the lowest thrust setting and
lowest (1.5) at the highest thrust setting of the pilot combustion mode. The line loss
correction factors for mass (mean of 1.9) were less than the particle number (mean of 2.9)
correction because of the inherent weighting of mass mobility distributions to larger particle
sizes, thus lessening the impact of small particle losses. The 𝐶𝐹PN and 𝐶𝐹PM were determined
using the downstream measured geometric mean and a fixed geometric mean (𝜎𝑔 =1.7). The
results indicate that over the range of distributions measured, the impact of varying geometric
mean had little effect (<10% relative error) on the overall line loss correction factors.
9
Figure S10: UTRC line loss penetration of 25 m line length and line temperature of 160°C.
The line loss correction factors were determined for the particle number (PN) and particle
mass (PM) for each thrust setting, shown in Figure S11. The line loss correction routine was
applied to the measured size distributions, which were in general well characterized by
single-mode log-normal distributions with geometric standard deviations 𝜎g = 1.73 (90% CI
[1.65 1.80]). Correction factors are greatest for thrust settings with smaller particle diameters.
In all cases, particle number correction factors were larger than particle mass correction
factors, as particle number distributions are dominated by small particles whereas particle
mass is proportional to the third moment of the particle size distribution. As shown there is
little difference between correction factors determined by using the measured geometric
standard deviation as opposed to a constant geometric standard deviation 𝜎g = 1.7.
10
Figure S11: Line loss correction factors for particle number and particle mass at various
thrust settings. Line loss correction factors indicated by solid symbols were determined using
the respective measured geometric standard deviation, while the open symbols represent
correction factors that were determined with a constant geometric standard deviation (𝜎g =
1.7).
As shown in Figure S10, the corrected geometric mean mobility diameter is less than the
measured geometric mobility diameter for all distributions due to the greater propensity for
smaller particles to be preferentially lost during transport. The relationship between line loss
corrected and measured geometric mean mobility diameter is well described by a linear
relationship, 𝑑pc = 1.165 𝑑𝑝 − 8.8249 nm, where the norm of the residuals is 1.36 for the
corrected versus measured geometric mobility diameter. The linear relationship is used to
correct the reported geometric mobility diameter within the results section of the article.
11
Figure S12: Line loss corrected particle mobility diameter shown versus measured particle
mobility diameter.
12
Engine Conditions
Figure S13: Measured combustor inlet temperature (T3) and engine speed for CFM56-5B42P at various thrust settings.
As shown in Figure S14 the individually measured datapoints for EI(BC), EIn, and geometric
mean mobility diameter demonstrate the repeatability of the measured metrics at a set thrust
point (~17%). In general measurements that were taken on the 28th and 30th April, 2015
agreed well, with deviations within an individual run that were less than the deviation
between measurements taken on different days. Measurements that were taken on the 29th
April, 2015 tended to be more highly variable due to deviations in the dilution system,
affecting the concentration of CO2 measured and calculated dilution factor. During all
measurements, despite the variability in thrust setpoint, the measured quantity remained
relatively steady. The geometric mean particle diameter was relatively insensitive to thrust
setting, but does appear to be affected by the line in which the measurement was taken on. In
particular the SAMPLE system appeared to have higher small particle loss (<20 nm) which
had the effect of increasing the geometric mean mobility diameter of particles measured on
this line.
13
Variability of Particle Measurements
Figure S14: (a) Black carbon mass emission index, EI(BC), (b) number emission index, EIn,
and (c) geometric mean diameter as measured by LII, CPCs and DMS/SMPS systems,
respectively. Data represents individual measurements (~1 Hz) from each system in order to
demonstrate the repeatability of the measurements.
14
Three representative particle size distributions are shown in Figure S15 for representative
thrust settings. Two settings were during pilot combustion (6% and 17%) and one during
double annular combustion (31%). The measured size distributions are all well characterized
by single-mode log-normal distributions, where the individual scans do not deviate greatly
from the mean measured distribution over the entire setpoint duration. The particle size
distributions corrected for line loss are a factor of 1.6 - 2.1 greater in total concentration than
the measured distributions, and the geometric mean particle size is 9-18% smaller for
corrected versus measured geometric mean particle diameter.
Figure S15: Particle mobility distribution as measured by nano-SMPS on the SAMPLE line
for (a) 6%, (b) 17% and (c) 31% thrust settings for 30th April. Colored lines represent
individual scans, solid black line represents average of individual scans and the dashed line
represents the line-loss corrected particle size distribution.
15
Measurement Uncertainty
The measurement uncertainties for the various instruments are given in SI Table 1 below. A
further discussion of the nature of the uncertainty and verification method is given thereafter.
SI Table 1: Measurement uncertainties for various instruments and physical parameters in
this study. Derived uncertainty determined in accordance with Abernethy et al. (1985).
1
Correspondence with NRC Canada, as determined in APRIDE-4 and APRIDE-5 campaigns.
(Symonds, 2010)
3
(Johnson et al., 2013)
4
(Johnson et al., 2013)
5
As shown in SI Table 3 below.
6
TSI and Grimm CPC product manual.
7
ISO 15900:2009
8
(Eggersdorfer et al., 2012)
9
References given in main text.
2
16
Condensation Particle Counter
Measurement of particle size and concentration by differential mobility analysis (DMA) and
condensation particle counting (CPC), respectively, are well-established, NIST-traceable
methods. SI Table 1 shows the counting accuracy for CPCs in single counting and
photometric modes for the model CPCs used in this study. Both manufacturer’s (TSI and
Grimm) estimate accuracy is better than 10% when used in the single-counting mode, as was
always the condition in this work.
SI Table 2: Counting accuracy for CPCs in single-counting and photometric modes. The
concentration range (in cm-3) provided by the manufacturer for single-counting mode is
shown in parenthesis.
3775
3772
3010
5435 (5430?)
single – count photometric
10% (0 - 50,000)
20%
10% (0 - 10,000)
n/a
10% (0 - 10,000)
n/a
10% (0 - 23,000)
n/a
Detailed studies of CPC calibration and accuracy have revealed that CPCs can be calibrated
to levels much more precise than manufacturer’s estimates (Fletcher et al., 2009; Giechaskiel
et al., 2010; Owen et al., 2012). For example, Owen et al. (2012) reported the relative
expanded uncertainty of a CPC (coverage factor of k = 2) is 2.8% over the range of about 1
particle·cm−3 to 104 particles·cm−3. However, because CPC counting accuracy during our test
campaign was conducted on a “spot-check” basis and no instrument-specific calibration
curve was used, a more conservative standard uncertainty of 10% is most appropriate to
apply to the concentration data herein.
Differential Mobility Analyzer
Standard sizing accuracy of the DMAs used was not explicitly provided by the manufacturer,
although the 3081 and 3085 DMAs are ISO 15900:2009 compliant and it is stated that
“rigorous peer reviewed uncertainty analyses have been performed indicating TSI’s DMA
has a sizing uncertainty of approximately <2% (TSI, 2015)”. Vasiliou (2005) found that
particle sizing of 3085 and 3081 DMAs was within the NIST-stated uncertainty range of the
measured PSL particles. Mulholland et al. (2006) conducted a detailed uncertainty analysis
for 100 nm and 60 nm standard reference PSL particles. They found relative expanded
uncertainty of a 3081 DMA (coverage factor of k = 2) for a particle diameter of 101.8 nm to
be 1.1 nm and 0.63 nm for a 63.9 nm particles. For smaller particles like the gas turbine soot
aggregates measured here, the uncertainty will be slightly higher due to the effects of
Brownian motion on the DMA transfer function. Kim et al. (2005) estimated the uncertainty
for a 20 nm particle in a 3085 DMA to be ~ 0.7%. As the case with the CPCs, the
manufacturer’s estimate of uncertainty (i.e. ~2%) appears to best represent the uncertainty of
the particle sizes measured for this work.
Laser Induced Incandescence
As determined by the LII mass calibration method, the uncertainty of the measurement ties to
the uncertainty of the calibration and then any uncertainties associated with differences
between the particulate measured during calibration and that measured in engine tests. This
latter uncertainty is an ongoing topic in the SAE-E31 community (VARIANT and MANTRA
17
campaigns, where instrument response differences with source have been observed). The
uncertainty of the calibration is principally defined by the uncertainty of the NIOSH method
which is suggested to be 16.7% from the NIOSH 5040 standard document. NPL suggests a
higher value – 25% (95% confidence limit). From engine test comparisons (A-PRIDE4, APRIDE5), differences less than +/- 25% have been observed, which is the uncertainty level
assumed in this study.
Centrifugal Particle Mass Analyzer
The uncertainty in the CPMA measurements were explored in detail by Symonds et al.
(2013) and they determined a 2.8% uncertainty in the CPMA mass-to-charge setpoint at a
95% confidence interval (CI). The uncertainty in the standard DMS500 measurements were
determined by Symonds (2010) to be 10% in mobility size at a 95% CI.
Differential Mobility Spectrometer
The DMS500 used in the CPMA-DMS system was modified and therefore the standard
DMS500 uncertainties do not apply. The uncertainty of the modified DMS was determined
by comparing it against a DMA and knowing the uncertainty in the DMA measurements
(Mulholland et al., 1999). The results of this comparison was indicated that the mDMS has a
mobility diameter sizing uncertainty of 3.04%-3.35% (at a 95% CI) depending on the particle
mobility size. Further details regarding this comparison and the uncertainty of the mDMS are
shown in the supplemental information of Johnson et al. (2013). Johnson et al. (2013) also
found the uncertainty in the effective particle density measured using the CPMA-mDMS
system was 9.5%-10.4% (at a 95% CI) depending on the particle mobility size.
Transmission Electron Microscopy
Average standard error for TEM primary particle diameter (either dp or dva) is ~2 nm (1.6
nm). Measured standard deviations and standard errors are reported in SI Table 3. Imaging
magnification varied from 100k to 300k for the whole range of test points, which typically
corresponds to ~1 to 0.6 nm/pixel resolution. The image processing procedure takes into
account the exact magnification. Although these changes in resolution may influence the
results slightly, almost all images taken from ONE test point (RPM/load) are at the same
magnification.
18
SI Table 3: Standard deviations and standard errors for TEM measured primary particle
diameters.
RPM
1000
1600
1845
2600
2630
2810
3025
3400
3700
3950
4500
STD
6.1
8.08
16.93
6.13
9.76
4.68
12.4
5.45
5.79
4.35
5.99
d p [nm]
STE
0.95
1.2
4.52
2.5
1.45
0.71
2.77
0.82
1.14
0.87
1.11
AVG
7.79
1.64
d va [nm]
STD
STE
6.05
0.95
8.34
1.24
15.19
4.06
6.05
2.47
9.86
1.47
4.74
0.72
12.64
2.83
5.34
0.8
5.97
1.17
5.83
1.17
6.11
1.13
7.83
1.64
19
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