OSA's Digital Library

Optics Letters

Optics Letters

| RAPID, SHORT PUBLICATIONS ON THE LATEST IN OPTICAL DISCOVERIES

  • Editor: Xi-Cheng Zhang
  • Vol. 39, Iss. 8 — Apr. 15, 2014
  • pp: 2350–2353
« Show journal navigation

Imaging Fourier-transform spectrometer measurements of a turbulent nonpremixed jet flame

Jacob L. Harley, Brent A. Rankin, David L. Blunck, Jay P. Gore, and Kevin C. Gross  »View Author Affiliations


Optics Letters, Vol. 39, Issue 8, pp. 2350-2353 (2014)
http://dx.doi.org/10.1364/OL.39.002350


View Full Text Article

Acrobat PDF (925 KB)





Browse Journals / Lookup Meetings

Browse by Journal and Year


   


Lookup Conference Papers

Close Browse Journals / Lookup Meetings

Article Tools

Share
Citations

Abstract

This work presents recent measurements of a CH4/H2/N2 turbulent nonpremixed jet flame using an imaging Fourier-transform spectrometer (IFTS). Spatially resolved (128×192 pixels, 0.72mm/pixel) mean radiance spectra were collected between 1800cm1ν˜4500cm1 (2.22μmλ5.55μm) at moderate spectral resolution (δν˜=16cm1, δλ¯=20nm) spanning the visible flame. Higher spectral-resolution measurements (δν˜=0.25cm1, δλ¯=0.3nm) were also captured on a smaller window (8×192) at 20, 40, and 60 diameters above the jet exit and reveal the rotational fine structure associated with various vibrational transitions in CH4, CO2, CO, and H2O. These new imaging measurements compare favorably with existing spectra acquired at select flame locations, demonstrating the capability of IFTS for turbulent combustion studies.

© 2014 Optical Society of America

Combustion diagnostics is a field of long standing interest with many resources continually dedicated to its study. Turbulence has significant effects on combustion processes such as turbulence-chemistry interactions, turbulence-radiation interactions, scalar dissipation, transport, and mixing. Nonintrusive optical diagnostic methods have been used to study combustion and all must consider the effects of turbulence. Laser-based methods are highly effective and widely used due to their high spectral and temporal resolution [1

1. K. Kohse-Höinghaus and J. B. Jeffries, Applied Combustion Diagnostics (Taylor & Francis, 2002).

]. Dispersive instruments [2

2. Y. Zheng, R. S. Barlow, and J. P. Gore, J. Heat Transfer 125, 678 (2003). [CrossRef]

,3

3. Y. Zheng, R. S. Barlow, and J. P. Gore, J. Heat Transfer 125, 1065 (2003). [CrossRef]

] and Fourier-transform spectrometers [4

4. P. R. Solomon, P. E. Best, R. M. Carangelo, J. R. Markham, P.-L. Chien, R. J. Santoro, and H. G. Semerjian, Symp. Int. Combust. Proc. 21, 1763 (1988).

] have been used with optical scanners to tomographically deconvolve temperature and species concentrations. High-speed infrared cameras with various bandpass filters have been used to map spatial variations in radiant intensity and relate these to various measures of turbulence (e.g., integral length and time scales) [5

5. B. A. Rankin, D. A. Blunck, and J. P. Gore, J. Heat Transfer 135, 021201 (2013). [CrossRef]

] as well as the spatial distribution of scalar values (e.g., temperature and mole fraction) [6

6. D. Blunck, S. Basu, Y. Zheng, V. Katta, and J. Gore, Proc. Comb. Inst. 32, 2527 (2009).

].

An imaging Fourier-transform spectrometer (IFTS) is a hyperspectral imager that combines a Michelson interferometer with a staring infrared focal-plane array (FPA). There are several potential advantages of this instrumentation for combustion diagnostics. High spectral resolution across a wide bandpass enables identification of multiple species. Proper interpretation of the spectrum can permit simultaneous determination of temperature and species concentrations [7

7. K. C. Gross, K. C. Bradley, and G. P. Perram, Environ. Sci. Technol. 44, 9390 (2010). [CrossRef]

]. High spectral resolution is also beneficial to tomographic reconstruction techniques [8

8. L. Ma, W. Cai, A. W. Caswell, T. Kraetschmer, S. T. Sanders, S. Roy, and J. R. Gord, Opt. Express 17, 8602 (2009). [CrossRef]

]. High-speed broadband infrared imagery is collected during each interferometric scan. This captures turbulence information and enables similar types of analysis already performed using infrared cameras. IFTS provides a useful passive and nonintrusive technique for studying combustion and is particularly useful when (1) both high-speed imagery and spatially resolved spectra are required, (2) characterization of high-pressure systems is required and collisional broadening effects become important, (3) more than one optical port is not available, limiting the types of laser-based methods available for interrogation. The present work presents the first IFTS measurements of a canonical turbulent jet flame. The scope of this work includes a qualitative discussion of the spectral imagery and a quantitative comparison with existing spectral measurements acquired at select locations in a similar flame. The impact of turbulent intensity fluctuations on interferogram formation is also described. Quantitative interpretation of flame spectra is the ultimate goal of this effort. However, it requires scalar-field fluctuation statistics, and this important topic will be considered in future work.

The experiment consisted of the Telops Hyper-Cam IFTS, two calibration blackbodies, and the flame. The flame tube is 480 mm long with an 8 mm exit diameter (D), mounted vertically, and moveable via unislide to allow combined imaging of the entire visible flame length without camera tilt. The flame replicates Flame DLR_A from the International Workshop on Measurement and Computation of Turbulent Nonpremixed Flames (TNF Workshop) with a jet exit Reynolds number of 15,200 and exit velocity of 42.2m/s. Mass flow rates were 313, 59, 1105mg/s for CH4, H2, and N2, respectively. Flow rates were calibrated using a dry turbine meter and controlled by setting the pressure upstream of three choked orifice plates [5

5. B. A. Rankin, D. A. Blunck, and J. P. Gore, J. Heat Transfer 135, 021201 (2013). [CrossRef]

].

The TNF Workshop flames are well characterized and designed for collaborative comparisons of measurements and models. A library of local velocities and scalar values (temperature, species mole fractions) measured simultaneously using laser Doppler velocimetry, Raman, Rayleigh, and LIF techniques is available for download [9,10

10. W. Meier, R. S. Barlow, Y.-L. Chen, and J.-Y. Chen, Combust. Flame 123, 326 (2000). [CrossRef]

].

The IFTS is based on a traditional Michelson interferometer coupled to a high-speed 320×256 indium antimonide staring FPA via f/#=2.5 imaging optics [7

7. K. C. Gross, K. C. Bradley, and G. P. Perram, Environ. Sci. Technol. 44, 9390 (2010). [CrossRef]

,11

11. V. Farley, A. Vallières, M. Chamberland, A. Villemaire, and J.-F. Legault, Proc. SPIE 6398, 63980T (2006). [CrossRef]

]. The spectral range covers 1800–6667cm1, and the spectral resolution can be selected between 0.25 and 150cm1. An interferometric “datacube” is a collection of snapshot images taken at equally spaced optical path differences (OPDs), and Fourier-transformation along this dimension produces a spectrum at each pixel.

An external 0.25× telescope expanded the field-of-view and reduced the minimum working distance to the flame. A 45% transmission neutral density filter, used to prevent saturation, limited the short-wavelength response to 2.22 μm (4500cm1). The IFTS was located (47.5±1.0)cm from the flame. The imaging system has an effective focal length of 19.7 mm at this working distance. The 30 μm pixel pitch of the FPA yields an instantaneous field-of-view (IFOV) of 1.52 mrad which translates to (0.72±0.02)mm at the flame and is constant across the array. The mean RMS spot size radius is 13.7 μm, and increases from 11.2 to 21.1 μm moving from center to corner of a 128×192 window. Mapping the Rayleigh λ/4 wavefront error depth-of-focus criterion, δf=±2λ(f/#)2, to object space produces a conservative estimate of the depth-of-field of ±2cm when computed at 2.5 μm, the shortest wavelength with appreciable energy arriving at the FPA. Throughout much of the flame, the spectral imagery can thus be interpreted as integrated along the line-of-sight (LOS). However, the widest part of the flame is 15cm, indicating some blurring will occur along the LOS. A detailed Zemax [12] optical model of our system indicates that more than 75% of the energy (relative to the diffraction-limited case, 86.4%) comes from the LOS for a pixel viewing the center of the widest (±7.5cm) flame region.

The IFTS was mounted to a gimbal with preset locations for intermittent calibration measurements. A standard two-point calibration using the wide-area blackbodies set to 595°C and 200°C was performed pixel-wise to determine the system response [gain, Gi(ν˜)] and instrument self-emission [offset, LiI(ν˜)]. The higher blackbody temperature produced a peak signal at 90% of the detector’s dynamic range and slightly exceeding that from the brightest part of the flame. At 595°C, the Planckian distribution monotonically decreases with frequency across the detector bandpass. This resulted in a nominal signal-to-noise ratio (SNR) in G(ν˜), which decreased nearly linearly from 15 to 1 between 3000 and 5000cm1. Since the system response is known to vary smoothly and slowly with ν˜, a spline was fit to each pixel’s gain curve to mitigate the impact of low-gain SNR on the calibrated spectrum.

Two sets of flame measurements were made. The first set was collected with high spectral resolution (0.25cm1) in a small window (8×192) traversing the flame at 20, 40, and 60D above the burner to facilitate identification of various chemical species. Interferometric datacubes consisted of 52,742 images and were collected at a rate of 0.55 Hz, and 512 cubes were averaged to produce a mean, calibrated image of the flame radiance. The second set increased the FPA window height (128×192) to facilitate measurement of the entire flame and decreased spectral resolution (16cm1) to simplify data reduction. Datacubes consisted of 1186 images and the acquisition rate increased to 4.2 Hz. Seven separate regions of the flame were imaged to produce a composite image of the entire flame. In each set the camera’s integration time was 20 μs, and imaging frame rates exceeded 5 kHz. Ambient temperature, pressure, and humidity were monitored with a Kestrel 4500 Weather Meter with averages of 25°C, 989 hPa, and 44% respectively.

Fig. 1. Panel A: schematic illustrating the FPA capturing infrared images at fixed OPDs as the Michelson sweeps, generating an interferometric datacube. Panel B: single interferogram (green, upper curve) and corresponding raw spectrum (red, lower curve) at flame center 20D above exit. Panel C: Time-averaged interferogram (green, upper curve) and corresponding mean flame spectrum (red, lower curve).

For a turbulent jet the scene radiance is stochastically fluctuating on a timescale much shorter than the interferometer’s acquisition rate. Thus, the “DC” term is now time-dependent and the AC term has no simple interpretation as it is the cosine transformation of a stochastically varying signal. This is illustrated in Panel B of Fig. 1 showing a single interferogram and corresponding raw magnitude spectrum. The fluctuations in integrated intensity dominate the signal and obscure the zero-path difference (ZPD) where all wavelengths constructively interfere. The corresponding spectrum is dominated by the frequencies associated with turbulent radiation fluctuation, although a feature near 2300cm1 resembling emission from the asymmetric stretching mode (ν3) of CO2 is recognizable. Large intensities below the detector cut-off (ν˜1800cm1) are due to turbulent fluctuations.

For an ergodic system, an ensemble of measurements will produce a mean interferogram corresponding to the mean spectral radiance since Eq. (1) is a linear transformation. Panel C presents the same pixel’s mean interferogram from 512 measurements, demonstrating that the turbulent fluctuations are suppressed. The resulting spectrum is now recognizable with rotational fine structure associated with vibrational transitions in H2O, CH4, CO, and CO2.

Figure 2 presents uncalibrated broadband imagery in Panels A and B, dividing the flame along the axis of symmetry into single-snapshot and time-averaged quantities. Each segment is temporally independent from the others. In Panels A and B the images were acquired at a common OPD near x=370μm. Away from ZPD the imagery is similar to what an infrared camera would measure (Ii(x)IiDC) since the broadband nature of radiation ensures |IiAC(x)|IiDC. At the burner tip, the distance traveled by the jet during the FPA’s integration time is 0.84 mm, exceeding the IFOV by approximately 12%, a conservative estimate of blurring due to the rapid deceleration of the jet. Moreover, the turbulence integral length scales for this flame between 20 and 60D are within 9.1–24 mm [5

5. B. A. Rankin, D. A. Blunck, and J. P. Gore, J. Heat Transfer 135, 021201 (2013). [CrossRef]

]. Thus, the turbulent structures exceed the spatial resolution by an order of magnitude. The time between repeated observations at a particular OPD is 240 ms, greatly exceeding the turbulence integral time scales (2.3–5 ms between 20 and 60D). Repeated observations at each OPD are statistically independent.

Fig. 2. Panel A: single broadband images from the lower spectral resolution (16cm1) datasets with 128×192 FPA window. Panel B: corresponding time-averaged broadband images. Panel C: Time-averaged radiance spectrally averaged over a prominent CO2 band. Panel D: Time-averaged radiance spectrally averaged over a prominent CH4 band. (Last spatial region limited due to unislide range.)

Fig. 3. Panel A: diametric, high-resolution (δν˜=0.25cm1) apparent flame spectrum at 20D with spectroscopic transitions annotated. Panel B: apparent (—) and atmospheric-corrected (⋯) low-resolution diametric flame spectra (δν˜=16cm1) at 20, 40, and 60D (black, red, blue) compared with previous measurements (○). Radiance uncertainty (95% confidence interval) presented as a translucent band around each apparent spectrum. The CO2 and CH4 bands used in Fig. 2 are identified.

References

1.

K. Kohse-Höinghaus and J. B. Jeffries, Applied Combustion Diagnostics (Taylor & Francis, 2002).

2.

Y. Zheng, R. S. Barlow, and J. P. Gore, J. Heat Transfer 125, 678 (2003). [CrossRef]

3.

Y. Zheng, R. S. Barlow, and J. P. Gore, J. Heat Transfer 125, 1065 (2003). [CrossRef]

4.

P. R. Solomon, P. E. Best, R. M. Carangelo, J. R. Markham, P.-L. Chien, R. J. Santoro, and H. G. Semerjian, Symp. Int. Combust. Proc. 21, 1763 (1988).

5.

B. A. Rankin, D. A. Blunck, and J. P. Gore, J. Heat Transfer 135, 021201 (2013). [CrossRef]

6.

D. Blunck, S. Basu, Y. Zheng, V. Katta, and J. Gore, Proc. Comb. Inst. 32, 2527 (2009).

7.

K. C. Gross, K. C. Bradley, and G. P. Perram, Environ. Sci. Technol. 44, 9390 (2010). [CrossRef]

8.

L. Ma, W. Cai, A. W. Caswell, T. Kraetschmer, S. T. Sanders, S. Roy, and J. R. Gord, Opt. Express 17, 8602 (2009). [CrossRef]

9.

http://www.sandia.gov/TNF/abstract.html.

10.

W. Meier, R. S. Barlow, Y.-L. Chen, and J.-Y. Chen, Combust. Flame 123, 326 (2000). [CrossRef]

11.

V. Farley, A. Vallières, M. Chamberland, A. Villemaire, and J.-F. Legault, Proc. SPIE 6398, 63980T (2006). [CrossRef]

12.

http://radiantzemax.com.

13.

J. M. Hollas, High Resolution Spectroscopy, 2nd ed. (Wiley, 1998).

OCIS Codes
(110.3080) Imaging systems : Infrared imaging
(120.1740) Instrumentation, measurement, and metrology : Combustion diagnostics
(300.2140) Spectroscopy : Emission
(300.6300) Spectroscopy : Spectroscopy, Fourier transforms
(110.4234) Imaging systems : Multispectral and hyperspectral imaging

ToC Category:
Spectroscopy

History
Original Manuscript: February 17, 2014
Revised Manuscript: March 14, 2014
Manuscript Accepted: March 14, 2014
Published: April 9, 2014

Citation
Jacob L. Harley, Brent A. Rankin, David L. Blunck, Jay P. Gore, and Kevin C. Gross, "Imaging Fourier-transform spectrometer measurements of a turbulent nonpremixed jet flame," Opt. Lett. 39, 2350-2353 (2014)
http://www.opticsinfobase.org/ol/abstract.cfm?URI=ol-39-8-2350


Sort:  Author  |  Year  |  Journal  |  Reset  

References

  1. K. Kohse-Höinghaus and J. B. Jeffries, Applied Combustion Diagnostics (Taylor & Francis, 2002).
  2. Y. Zheng, R. S. Barlow, and J. P. Gore, J. Heat Transfer 125, 678 (2003). [CrossRef]
  3. Y. Zheng, R. S. Barlow, and J. P. Gore, J. Heat Transfer 125, 1065 (2003). [CrossRef]
  4. P. R. Solomon, P. E. Best, R. M. Carangelo, J. R. Markham, P.-L. Chien, R. J. Santoro, and H. G. Semerjian, Symp. Int. Combust. Proc. 21, 1763 (1988).
  5. B. A. Rankin, D. A. Blunck, and J. P. Gore, J. Heat Transfer 135, 021201 (2013). [CrossRef]
  6. D. Blunck, S. Basu, Y. Zheng, V. Katta, and J. Gore, Proc. Comb. Inst. 32, 2527 (2009).
  7. K. C. Gross, K. C. Bradley, and G. P. Perram, Environ. Sci. Technol. 44, 9390 (2010). [CrossRef]
  8. L. Ma, W. Cai, A. W. Caswell, T. Kraetschmer, S. T. Sanders, S. Roy, and J. R. Gord, Opt. Express 17, 8602 (2009). [CrossRef]
  9. http://www.sandia.gov/TNF/abstract.html .
  10. W. Meier, R. S. Barlow, Y.-L. Chen, and J.-Y. Chen, Combust. Flame 123, 326 (2000). [CrossRef]
  11. V. Farley, A. Vallières, M. Chamberland, A. Villemaire, and J.-F. Legault, Proc. SPIE 6398, 63980T (2006). [CrossRef]
  12. http://radiantzemax.com .
  13. J. M. Hollas, High Resolution Spectroscopy, 2nd ed. (Wiley, 1998).

Cited By

Alert me when this paper is cited

OSA is able to provide readers links to articles that cite this paper by participating in CrossRef's Cited-By Linking service. CrossRef includes content from more than 3000 publishers and societies. In addition to listing OSA journal articles that cite this paper, citing articles from other participating publishers will also be listed.

Figures

Fig. 1. Fig. 2. Fig. 3.
 

« Previous Article  |  Next Article »

OSA is a member of CrossRef.

CrossCheck Deposited