Paper # 070LT-0209
Topic: Laminar & Turbulent Flames
8th U. S. National Combustion Meeting
Organized by the Western States Section of the Combustion Institute
and hosted by the University of Utah
May 19-22, 2013
Quantitative Imaging of Radiation Intensity
from a Turbulent Sooting Flame
Robert K. Kapaku1, Brent A. Rankin2, Jay P. Gore1
1
School of Mechanical Engineering, Purdue University, West Lafayette, IN 47907, USA
2
Innovative Scientific Solutions, Inc., Dayton, OH 45440, USA
Motivated by the detrimental effects of pollutant emissions from combustion devices on health and environment, a turbulent
sooting ethylene diffusion flame is studied in this work. Large radiation heat loss from these flames is also of interest in applications
involving manufacturing and heating furnaces and fire safety. Quantitative imaging of infrared radiation intensity is a method of
comparing measurements and results of large eddy simulations rendered in the form of images. The current study reports quantitative
experimental images of the infrared radiation intensity from a turbulent ethylene flame that matches the Reynolds number of a nonsooting flame from the International Workshop on Measurement and Computation of Turbulent Non-premixed Flames. A high-speed
infrared camera with three band-pass filters was used to acquire the images of radiation intensity. Measurements using a fast infrared
array spectrometer were obtained for comparison. The luminous flame measurements show thin radiating structures corresponding to
soot layers and significantly higher mean and fluctuating radiation intensities. The results of this work have applications to validation
of models of soot formation, oxidation, and emission.
1.
Introduction
Turbulent sooting flames are important in many combustion applications such as industrial furnaces, gas turbine
engines, and fire safety. Radiation heat transfer can affect soot formation, oxidation, and emission. The incorporation of
radiation effects to computational models of sooting flames is important in order to estimate flame temperature, which in
turn controls soot formation and oxidation rates [1]. Wang et. Al [1] suggest that Large Eddy Simulations (LES) with
suitably reduced chemical kinetics with fuel-rich chemistry and a suitable radiation model can predict soot formation in
an ethylene nonpremixed jet flame. The study concluded that experimental radiation intensity measurements were
important for validation of LES and subgrid scale models of soot formation and oxidation processes.
Gore and Faeth [2] investigated the structure and spectral radiation characteristics of turbulent ethylene/air diffusion
flames. Their work concluded that the effects of turbulence/radiation interactions were more significant for continuum
radiation from soot than for 4.3µm gas band radiation from carbon dioxide. Zheng and Gore [3] measured spectral
radiation intensities and applied deconvolution and inverse radiation techniques to estimate radial profiles of temperature
and soot volume fractions. At 40 diameters (D = 8 mm) downstream, a peak mean temperature of 1500K and peak soot
volume fraction of .4 ppm were reported at a radius of 2.4 diameters. The work emphasized the need for acquiring
benchmark experimental data of luminous flames similar to the International Workshop on Measurement and
Computation of Turbulent Non-premixed Flames (TNF Workshop) [4].
More recently, soot volume fractions in turbulent luminous flames have been measured with laser-induced
incandescence (LII) [5-9]. Xin and Gore [5] used LII measurements to characterize the statistical distribution of soot in
turbulent buoyant flames. Ensemble averaged soot volume fractions were found to increase with downstream distance
from the burner exit before peaking and decreasing toward the flame tips. The intermittency reduced the mean peak
value by an order of magnitude compared to the instantaneous peak value. Qamar et al. [6] measured soot volume
fractions in a turbulent natural gas flame using LII. Their results showed that soot layers were formed near strained
flame sheets and were convected and distorted by the flow. The axial and radial distributions of soot were utilized to
support analytical models of soot. Köhler et al. [7] presented the first simultaneous, instantaneous particle image
velocimetry (PIV) and LII measurements in a heavily sooting flame. The study emphasized the need for time dependent
simulations of spatial and temporal dynamics of soot events throughout the flame. Lee et al. [8] utilized LII and planar
laser-induced fluorescence (PLIF) to measure soot, hydroxyl radical (OH), and polycyclic aromatic hydrocarbon (PAH)
concentrations in a turbulent nonpremixed ethylene/air flame. Distinct soot, OH, and PAH formation/oxidation regions
were characterized. Turbulence levels influenced the amount of soot produced but did not affect the characteristic shape
of the soot profiles. Soot field structures were found to be highly intermittent, anisotropic, thin in the direction along the
flame axis, and isolated. Buxton et al. [9] built upon these concepts to perform simultaneous PLIF, LII, and PIV
measurements in a sooting jet flame. Soot structures were observed in regions with low magnitude Reynolds stresses. A
strong correlation was also found between the LII and PLIF signals in the region of peak mean soot volume fraction.
These studies have advanced the understanding of complex soot generation and interaction in luminous turbulent flames.
The establishment of representative sooting flames with well-defined operating conditions that emerged as part of the
International Sooting Flame Workshop [10] highlights the need for data capable of guiding advanced computational
models of resolved scale and subgrid scale soot processes.
Quantitative imaging of radiation intensity can provide new insights and data for comparison with computational
models. Mehta et al. [11] applied gas-phase chemistry and soot models validated for laminar flames to turbulent flames
and found good agreement with experimental temperature and soot volume fractions. They compared radiative heat flux
from the model to experiment data, reaching good agreement. Mueller et al. [12] developed an integrated LES model for
sooting turbulent nonpremixed flames. An important parameter in this model was heat loss due to radiation. Chatterjee
et al. [13] developed a new approach for modeling soot radiation in buoyant diffusion flames, validated for laminar
smoke point flames and adapted for application in LES of turbulent sooty flames. Peak radiant emission values were
found to closely match experimental data, with more work needed to match locations of peak emission.
Images of radiation intensity have been demonstrated as a comparison tool for validating LES models. By utilizing
LES scalar values combined with a narrowband radiation model (RADCAL) [14], Rankin [15] rendered images of
radiation intensity. Computational image generation allowed spectral radiation intensity results to be displayed in a way
that mimicked experimental observations [15]. Rankin et al. [16] also utilized infrared imaging for detailed statistical
analysis of both temporal and spatial correlations of radiation intensity from a non-luminous flame.
Motivated by this, the objectives of the present work are as follows:
1. Acquire quantitative time-dependent infrared images of the radiation intensity from soot, water vapor, and carbon
dioxide in a representative turbulent nonpremixed sooting flame.
2. Compare the images of the radiation intensity from the sooting flame to those of a non-sooting flame with an
identical Reynolds number primarily defining the jet exit velocity.
3. Discuss the value of quantitative comparisons of measured and computed images of the infrared radiation
intensity for prompting improvements in radiation and soot models.
2.
Methods
2.1 Flame and Coordinate System
The nonpremixed turbulent ethylene flame was established on a 480mm long tube with a nominal inner diameter (D)
of 8mm. An ethylene flow rate of 993 mg/s was selected to match the Reynolds number (15,200) of a representative
nonluminous turbulent flame (flame A) from the TNF Workshop [4]. The Reynolds number was calculated based on
cold gas properties, the exit velocity, and exit diameter. The mass flow rate was calibrated using a dry test turbine meter
and controlled by setting the pressure upstream of a choked orifice plate. Given the identical burner tube diameter and
the closeness of gas phase kinematic viscosities at room temperature as well as the hydrocarbon stoichiometry, the
identical Reynolds number represents similarity of residence times for the mixing, reaction, and radiation processes.
Figure 1 illustrates the experimental arrangement for the flame and radiation intensity measurements. The flame
coordinate system (x, r, ) was defined with an origin located at the center of the burner exit. The camera coordinate
system (X,R,Y) was defined with an origin located at (x, r, ) = (0, d, 0) where d is the distance between the camera lens
and the flame axis. The burner was mounted to a traverse mechanism allowing for multiple flame heights to be
observed.
2.2 Radiation Intensity Measurements
Time-dependent images of the infrared radiation intensity emitted from the turbulent ethylene flame were measured
using a high speed infrared camera (FLIR Phoenix). The camera was located approximately 50 cm from the flame
centerline. The spatial resolution was approximately .53 mm 2 for each pixel at the center of the flame. Three bandpass
filters were used to measure radiation from soot and H2O (2.58 ± 0.03 μm); soot, H2O, and CO2(2.77 ± 0.1 μm); and soot
and CO2 (4.34 ± 0.12 μm). The camera measured spectrally integrated radiation intensity along approximate lines of
2
sight through the flame as shown in Fig. 1 and described by the solution to the radiative transfer equation for absorbingemitting media [16],
)
( )
( ) (
,
(1)
∫
∫ ∫
where
is the blackbody spectral intensity and
and
are the spectral limits of the filter. The spectral
absorption coefficient ( ) accounts for transmission losses through the filter and lens and the spectral response of the
camera focal plane array, first demonstrated by Rankin et al. [15-16]. The optical thickness ( ) is defined as [16]
,
(2)
∫
where κλ is the linear absorption coefficient and s is the path length.
The camera was calibrated using a blackbody radiation source positioned at the same distance as the camera from
the plume centerline to account for the effect of atmospheric absorption. Transmission losses through the lens and filter
and response of the detector were included in the calibration process.
The infrared camera exposure time (6-100 µs) was varied in order to optimize the detector sensitivity. Sampling
rates were between 270 and 345 Hz, depending on the camera exposure time. At each location, 6400 infrared images
were collected. Time-dependent mean and RMS were determined from these data. The uncertainty in the mean
radiation intensity measurements was previously established to be 15% (95% confidence) based on intensity
measurements using the same camera and associated optics [15].
3.
Results and Discussion
Time-dependent images of the radiation intensity from the turbulent sooting flame for the 2.58 ± 0.03 μm, 2.77 ± 0.1
μm, and 4.34 ± 0.12 μm bands are shown in Figure 2, Figure 3, and Figure 4 respectively. Three consecutive timedependent images separated by approximately 2.9 – 3.7 ms are shown from left to right in these figures. The images are
spatially related from top to bottom; however, there is no direct temporal relationship in the vertical direction. A low
intensity region is observed near the burner exit (0 ≤ x/D ≤ 40). This is consistent with past measurements of radiation
intensity from turbulent jet flames. Regions of high and low intensity appear throughout the flame both on and off the
image centerline. The time-dependent images show thin regions of high radiation intensity in the lower wavelengths
centered at 2.58 µm and 2.77 µm where broadband radiation from soot is dominant. This is consistent with published
LII measurements of sooting turbulent flames [5-9] where thin, intermittent soot regions were reported. The thin, high
radiation intensity regions are not observed in the longer wavelengths centered at 4.34 µm. Instead, the images of the
infrared radiation intensity from the turbulent sooting flame qualitatively are consistent with images of the nonluminous
turbulent flame for the longer wavelengths [15-16]. These observations agree with past spectral measurements of the
turbulent ethylene flame demonstrating that the radiation intensity from soot is most significant at wavelengths below 4
µm [2].
Beyond the peak intensity (85 ≤ x/D ≤ 160) the mean radiation intensity decreases steadily in the plume region. The
radiation intensity fluctuations vary significantly in this region. Ambient air entrained into the flow cools and dilutes the
combustion products and reduces radiation intensity.
Mean radiation intensity at a wavelength filter range of 2.77 ± 0.1 μm is shown in Figure 5. The mean and
normalized RMS radiation intensities along the centerline are shown in Figure 6. Radiation intensity measurements from
the non-luminous turbulent flame are shown in Figure 6 for comparison. The peak radiation intensity is observed near
x/D = 90 for the lower wavelengths and at x/D = 70 for the higher wavelengths. The difference in the locations of the
peak radiation intensity are based on the facts that soot decrements due to oxidation and cools by radiation at heights
lower than those at which the radiative cooling of CO2 occurs. Peak centerline radiation intensity is greater in the
luminous flame by a factor of 3 at the 2.58 ± 0.03 μm and 2.77 ± 0.1 μm wavelength bands and a factor of 1.3 at the 4.34
± 0.12 μm wavelength band. The luminous flame radiation intensity has a steeper slope around the peak value at the
2.58 ± 0.03 μm and 2.77 ± 0.1 μm wavelength bands. Both the sooting and non-sooting flames exhibit an axially
symmetric radiation intensity rise and fall around the peak centerline value.
Normalized RMS increases from 0 near the burner, remains approximately constant for 20 ≤ x/D ≤ 90 and exhibits
nonlinear increase in the plume region beyond the peak intensity. The shape and the magnitude of the normalized RMS
is similar for the sooting and the non-sooting flames.
The quantitative images of the radiation intensity from the turbulent sooting flame reported in this work provide
benchmark data for comparison with computational results. Rankin demonstrated that LES results could be utilized
along with a narrowband radiation model, the radiative transfer equation, and in image rendering algorithm to simulate
images of radiation intensity [15]. The simulated images are compared quantitatively with infrared camera
measurements to provide new insights and potential improvements in combustion and radiation models. The application
3
of similar methods to the sooting flame studied in this work is expected to provide new insights and improvements in
soot and radiation models.
4.
Conclusions
Quantitative time-dependent infrared radiation images of a representative turbulent nonpremixed sooting flame are
presented in this study. The primary results and conclusions are as follows:
1. Quantitative imaging of infrared radiation intensity is a useful nonintrusive technique for sooting flames. The
images provide benchmark radiation intensity data for future LES and subgrid scale models of luminous flames.
2. Species that radiate in the wavelengths not dominated by soot are also detectable, adding to the functionality of
infrared imaging as a diagnostic tool for luminous flames where in situ laser diagnostics may not be able to easily
penetrate.
3. Radiation intensity images show thin, high radiation intensity regions corresponding to soot radiation. These
regions are evident for wavelength bands of 2.58 ± 0.03 μm and 2.77 ± 0.1 μm, but not for the 4.34 ± 0.12 μm band.
4. Radiation intensity images in the turbulent sooting flame show peak centerline radiation intensities of magnitudes
greater than a factor of 3 at the lower wavelength bands (2.58 ± 0.03 μm and 2.77 ± 0.1 μm) and greater than a factor of
1.3 at the upper wavelength band (4.34 ± 0.12 μm). Normalized RMS is of similar magnitudes in the non-sooting and
sooting turbulent flames.
Acknowledgements
The authors would like to acknowledge Jiange Xiao for his assistance with operating the flame.
References
[1] Wang, H., Kook, S., Doom, J., Oefelein, J.C., Zhang, J., Shaddix, C.R., Schefer, R.W., and Pickett, L.M.
“Understanding and predicting soot generation in turbulent non-premixed jet flames.,” Sandia National Laboraties
Report. Oct. 2010.
[2] Gore, J.P. and Faeth, G.M., “Structure and spectral radiation properties of turbulent ethylene/ air diffusion flames,”
Symposium (International) on Combustion, Volume 21, Issue 1, 1988, Pages 1521-1531.
[3] Zheng, Y., and Gore, J., “Measurements and inverse calculations of spectral radiation intensities of a turbulent
ethylene/air jet flame,” Proceedings of the Combustion Institute, Volume 30, Issue 1, January 2005, Pages 727-734.
[4] International Workshop on Measurement and Computation of Turbulent Non-premixed Flames, Sandia
National Laboratories, 2001, available at <http://www.sandia.gov/TNF/>.
[5] Xin, Y. and Gore, J.P. “Two-dimensional soot distributions in buoyant turbulent fires,” Proceedings of the
Combustion Institute, Volume 30, Issue 1, January 2005, Pages 719-726.
[6] Qamar, N.H., Alwahabi, Z.T., Chan, Q.N., Nathan, G.J., Roekaerts, D., and King, K.D. “Soot volume fraction in a
piloted turbulent jet non-premixed flame of natural gas,” Combustion and Flame, Volume 156, Issue 7, July 2009, Pages
1339-1347.
[7] Köhler, M., K. Geigle, W. Meier, B. Crosland, K. Thomson, and G. Smallwood. 2011. "Sooting turbulent jet flame:
characterization and quantitative soot measurements," Applied Physics B: Lasers & Optics, Volume 104, no. 2, August
2011, Pages 409-425.
[8] Lee, S-Y., Turns, S.R., Santoro, R.J. “Measurements of soot, OH, and PAH concentrations in turbulent ethylene/air
jet flames,” Combustion and Flame, Volume 156, Issue 12, December 2009, Pages 2264-2275
[9] Buxton, O.R.H., Burns, R.A., Clemens, N.T., “Simultaneous Krypton PLIF, LII and PIV Measurements in a Sooting
Jet Flame,” 51st AIAA Aerospace Sciences Meeting Including the New Horizons Forum and Aerospace Exposition,
Grapevine, Texas, 07-10 January, 2013.
[10] International Sooting Flame Workshop, The University of Adelaide, 2012, available at <
http://www.adelaide.edu.au/cet/isfworkshop/data-sets/>
[11] Mehta, R.S., Haworth, D.C., and Modest, M.F. “Composition PDF/photon Monte Carlo modeling of moderately
sooting turbulent jet flames,” Combustion and Flame, Volume 157, Issue 5, May 2010, Pages 982-994
[12] Mueller, M.E. and Pitsch, H. “LES model for sooting turbulent nonpremixed flames,” Combustion and Flame,
Volume 159, Issue 6, June 2012, Pages 2166-2180.
[13] Chatterjee, P., de Ris, J.L., Wang, Y., and Dorofeev, S.B. “A model for soot radiation in buoyant diffusion flames,”
Proceedings of the Combustion Institute, Volume 33, Issue 2, 2011, Pages 2665-2671.
[14] Grosshandler, W., “RADCAL: A Narrow-Band Model for Radiation Calculations in a Combustion Environment,”
NIST Technical Note 1402, U.S. Government Printing Office, Washington D.C., 1993.
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[15] Rankin, B.A., “Quantitative Experimental and Model-Based Imaging of Infrared Radiation Intensity from Turbulent
Reacting Flows,” PhD Dissertation, Purdue University, West Lafayette, IN, 2012.
[16] Rankin, B.A., Blunck, D.L., and Gore, J.P. “Infrared Imaging and Spatiotemporal Radiation Properties of a
Turbulent Nonpremixed Jet Flame and Plume,” Journal of Heat Transfer, Volume 135, Issue 2.
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Figure 1. Experimental arrangement for acquiring images of the radiation intensity from the turbulent sooting
flame.
6
Radiation Intensity
𝑾
( 𝟐 )
𝒔𝒓
x/D
𝒎
r/D
Figure 2: Time-dependent images of infrared radiation intensity from the turbulent sooting flame. The images
are acquired using a band-pass filter (2.58±.03 µm) that transmits radiation from soot and water vapor.
7
Radiation Intensity
𝑾
( 𝟐 )
𝒔𝒓
x/D
𝒎
r/D
Figure 3: Time-dependent images of infrared radiation intensity from the turbulent sooting flame. The images
are acquired using a band-pass filter (2.77±.1 µm) that transmits radiation from soot, water vapor, and carbon
dioxide.
8
Radiation Intensity
𝑾
( 𝟐 )
𝒔𝒓
x/D
𝒎
r/D
Figure 4: Time-dependent images of infrared radiation intensity from the turbulent sooting flame. The images
are acquired using a band-pass filter (4.34±.12 µm) that transmits radiation from soot, and carbon dioxide.
9
Radiation
Intensity
𝑾
( 𝟐 )
𝒔𝒓
x/D
𝒎
r/D
Figure 5. Time-averaged image of infrared radiation intensity (2.77±.1 µm) from the turbulent sooting flame.
10
2.0
Sooting Non-Sooting 2.58 +/- 0.03 m
Imean
2
Imean (W/m -sr)
240
1.6
Irms / Imean
200
1.2
160
120
0.8
Irms / Imean
280
80
0.4
40
00
1280
0.0
Sooting Non-Sooting 2.77 +/- 0.12 m
Imean
1.2
Irms / Imean
960
800
0.8
640
480
Irms / Imean
2
Imean (W/m -sr)
1120
0.4
320
160
0
0.0
Sooting Non-Sooting 4.34 +/- 0.10 m
Imean
1.2
Irms / Imean
1200
0.8
800
Irms / Imean
2
Imean (W/m -sr)
1600
0.4
400
0
0.0
0
20
40
60
80
100
120
140
x/D
Figure 6. Mean and normalized RMS radiation intensity from the turbulent sooting flame and turbulent nonsooting flame (flame A) [14].
11