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Optics Express

Optics Express

  • Editor: Andrew M. Weiner
  • Vol. 21, Iss. 1 — Jan. 14, 2013
  • pp: 1152–1162
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50-kHz-rate 2D imaging of temperature and H2O concentration at the exhaust plane of a J85 engine using hyperspectral tomography

Lin Ma, Xuesong Li, Scott T. Sanders, Andrew W. Caswell, Sukesh Roy, David H. Plemmons, and James R. Gord  »View Author Affiliations


Optics Express, Vol. 21, Issue 1, pp. 1152-1162 (2013)
http://dx.doi.org/10.1364/OE.21.001152


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Abstract

This paper describes a novel laser diagnostic and its demonstration in a practical aero-propulsion engine (General Electric J85). The diagnostic technique, named hyperspectral tomography (HT), enables simultaneous 2-dimensional (2D) imaging of temperature and water-vapor concentration at 225 spatial grid points with a temporal response up to 50 kHz. To our knowledge, this is the first time that such sensing capabilities have been reported. This paper introduces the principles of the HT techniques, reports its operation and application in a J85 engine, and discusses its perspective for the study of high-speed reactive flows.

© 2013 OSA

1. Introduction

The study of reactive flows continues to challenge diagnosticians with the need for non-intrusive techniques that can provide quantitative measurements with adequate temporal and spatial resolution [1

1. R. K. Hanson, “Applications of quantitative laser sensors to kinetics, propulsion and practical energy systems,” Proc. Combust. Inst. 33(1), 1–40 (2011). [CrossRef]

]. Such measurements have been repeatedly shown to be invaluable for the validation of existing models and also for the inspiration of new models. These techniques are furthermore desired to be robust and suitable for in situ monitoring and control purposes in practical combustion and propulsion systems to improve their efficiency and performance [2

2. K. Kohse-Hoinghaus, R. S. Barlow, M. Alden, and E. Wolfrum, “Combustion at the focus: laser diagnostics and control,” Proc. Combust. Inst. 30(1), 89–123 (2005). [CrossRef]

].

Among the properties important for reactive flows, temperature and concentration of chemical species are two most important ones; and the corresponding developments of diagnostic techniques have attracted a tremendous amount of research efforts. This paper reports a new laser diagnostic that can measure 2-dimensional (2D) distribution of temperature and concentration of water vapor (H2O) simultaneously with a temporal resolution of 50 kHz and a spatial resolution of 225 (15 × 15) grid points. The HT technique utilizes multiple line-of-sight-averaged measurements of the absorption spectra of H2O vapor to infer the distribution of temperature and H2O concentration. To our knowledge, this is the first time that such measurement capabilities have been reported. The technique has been demonstrated in the exhaust plane of a practical aero-propulsion engine (General Electric J85).

For 2D measurement of the concentration of chemical species, the well-established technique is planar laser-induced fluorescence (PLIF) [4

4. A. C. Eckbreth, Laser Diagnostics for Combustion Temperature and Species (Gordon and Breach Publishers, 1996).

]. The temporal resolution of PLIF is largely driven by the availability of high-speed lasers, cameras, and intensifiers. With such hardware becoming commercially available recently, multi-kHz PLIF systems have gradually become at more and more researchers’ disposal [6

6. I. Boxx, M. Stohr, C. Carter, and W. Meier, “Sustained multi-kHz flamefront and 3-component velocity-field measurements for the study of turbulent flames,” Appl. Phys. B. 95(1), 23–29 (2009). [CrossRef]

8

8. B. H. Cheung and R. K. Hanson, “CW laser-induced fluorescence of toluene for time-resolved imaging of gaseous flows,” Appl. Phys. B. 98(2-3), 581–591 (2010). [CrossRef]

]. Customer-built laser systems can further extend PLIF measurements to tens of kHz [9

9. K. N. Gabet, R. A. Patton, N. Jiang, W. R. Lempert, and J. A. Sutton, “High-speed CH2O PLIF imaging in turbulent flames using a pulse-burst laser system,” Appl. Phys. B. 106(3), 569–575 (2012). [CrossRef]

, 10

10. N. Jiang, M. Webster, W. R. Lempert, J. D. Miller, T. R. Meyer, C. B. Ivey, and P. M. Danehy, “MHz-rate nitric oxide planar laser-induced fluorescence imaging in a Mach 10 hypersonic wind tunnel,” Appl. Opt. 50(4), A20–A28 (2011). [CrossRef] [PubMed]

], comparable to that of the HT technique reported here. The spatial resolution of PLIF is typically well below a millimeter, significantly superior to the HT technique demonstrated in this current work (38.3 mm, or 1.5 inches). Note however that 1) the spatial resolution of the HT technique is fundamentally limited by the size of the laser beam and can be dramatically improved beyond 38.3 mm, and 2) our current implementation of the HT technique essentially trades spatial resolution for the field-of-view (FOV). The current HT implementation monitored a 57 × 57 cm (22.5 × 22.5 inches) region. The spatial resolution can be improved by decreasing the size of the FOV, a trade-off that PLIF faces too.

For 2D measurement of temperature, Rayleigh scattering represents a well-established technique [4

4. A. C. Eckbreth, Laser Diagnostics for Combustion Temperature and Species (Gordon and Breach Publishers, 1996).

]. The comparison between Rayleigh scattering and the HT technique is similar to that between PLIF and HT. The temporal resolution of Rayleigh scattering is again largely driven by the availability of hardware, and can reach comparable level as reported here. The spatial resolution of typical Rayleigh scattering is superior to that of the HT technique reported here, and trade-off between spatial resolution and the size of the FOV applies to Rayleigh scattering too.

Comparison of HT to PLIF and Rayleigh scattering in other aspects (besides temporal and spatial resolution and the FOV) provides further motivation for the HT technique. For example, quantitative interpretation of PLIF measurements requires independent information of temperature and local quenching rates, which can be difficult or even impossible to obtain in practical reactive flows. The Rayleigh signal depends on local gas composition, which can make the signal indecipherable in reactive flows. Furthermore, Rayleigh signal is relatively weak because of its non-resonant and elastic nature. As a result, conventional Rayleigh scattering is susceptible to interference due to particulate/droplet scattering and surface reflection, restricting its practical applications, and laser diagnosticians have been investigating techniques such as filtered Rayleigh scattering [11

11. D. Hoffman, K. U. Münch, and A. Leipertz, “Two-dimensional temperature determination in sooting flames by filtered Rayleigh scattering,” Opt. Lett. 21(7), 525–527 (1996). [CrossRef] [PubMed]

] to overcome these issues. Lastly, the laser equipments involved in PLIF and Rayleigh scattering are typically not fiber coupled, requiring their implementation to be in close proximity to the target test rig. Such requirements often pose significant challenges in practice because of the harsh environment created by combustion and propulsion systems, and these challenges are further compounded by the relatively bulky size of the laser equipment involved with PLIF and Rayleigh techniques.

2. Background of hyperspectral tomography

Figure 1
Fig. 1 The mathematical formulation of the hyperspectral tomography problem.
depicts the HT problem. A hyperspectral laser beam is directed along the line of sight, denoted by l, to probe the domain of interest as shown in the left panel. Absorption by the target species will attenuate the probe laser beam, and the absorbance at a certain wavelength (e.g., λi) generally contains contributions from multiple transitions centered at various wavelengths (including that centered at λi itself), as schematically shown in the right panel. Here, we use p(Lj, λi), termed a projection, to denote the absorbance at a projection location Lj and a wavelength λi. The projection, p(Lj, λi), is expressed by the following integral:
p(Lj,λi)=abkS(λk,T())X()Φ(λkλi)Pd
(1)
where a and b are the integration limits determined by the line of sight and the geometry of the domain of interest, S(λk, T(l)) is the line strength of the contributing transition centered at a wavelength λk and depends nonlinearly on temperature (T); T(l) and X (l) are the temperature and mole-fraction profile of the absorbing species along the line of sight, respectively; Φ is the Voigt lineshape function; and P is the pressure, assumed to be uniform. The summation runs over all the transitions with non-negligible contributions. In this work, the domain of interest is discretized by superimposing a square mesh in the Cartesian coordinate, as shown in the left panel of Fig. 1; and the integration in Eq. (1) is also discretized accordingly.

The HT problem seeks to determine the distributions of T and X over the discretized domain with a finite set of projections as described in Eq. (1). We developed a method to cast the inversion problem into a nonlinear optimization problem, where the T and X distributions are retrieved by minimizing the following function:
D(Trec,Xrec)=j=1Ji=1I[pm(Lj,λi)pc(Lj,λi)]2pm(Lj,λi)2
(2)
where pm(Lj, λi) denotes the measured projection at a location Lj and a wavelength λi; pc(Lj, λi) the computed projection based on a reconstructed T and X profile (denoted by Trec and Xrec, respectively); and J and I the total number of wavelengths and projection locations used in the tomography scheme, respectively. This function, D, provides a quantitative measure of the closeness between the reconstructed and the actual temperature and concentration profiles. The contribution from each wavelength to D is normalized by the projection at this wavelength itself, such that projections measured at all wavelengths are weighted equally in the inversion. In an ideal case where the measurements are noise free, D reaches its global minimum (zero) when Trec and Xrec match the actual profiles.

The formulation in Eq. (2) allows the flexible incorporation of available a priori information via regulation. For instance, in practice, the T and X distribution sought are non-negative, bounded, and smooth to a certain degree because of thermal and mass diffusion. All such information is included in minimizing Eq. (2) [19

19. L. Ma and W. Cai, “Determination of the optimal regularization parameters in hyperspectral tomography,” Appl. Opt. 47(23), 4186–4192 (2008). [CrossRef] [PubMed]

, 20

20. L. Ma and W. Cai, “Numerical investigation of hyperspectral tomography for simultaneous temperature and concentration imaging,” Appl. Opt. 47(21), 3751–3759 (2008). [CrossRef] [PubMed]

]. More specifically, the non-negativity and boundedness regularizations are incorporated in the minimization algorithm (the simulated annealing algorithm), and the smoothness regularization is implemented by modifying the target function D into:
F(Trec,Xrec)=D(Trec,Xrec)+γTRT(Trec)+γXRX(Xrec)
(3)
where RT and RX are the regularization factors for temperature and concentration, respectively; γT and γX are positive constants (regularization parameters) to scale the magnitude of RT and RX properly. More details of the use of regularization factors, the determination of the optimal regularization parameters, and the simulated annealing algorithm can be found in [18

18. W. Cai, D. J. Ewing, and L. Ma, “Application of simulated annealing for multispectral tomography,” Comput. Phys. Commun. 179(4), 250–255 (2008). [CrossRef]

20

20. L. Ma and W. Cai, “Numerical investigation of hyperspectral tomography for simultaneous temperature and concentration imaging,” Appl. Opt. 47(21), 3751–3759 (2008). [CrossRef] [PubMed]

]. Finally, the solution of the minimization problem described in Eq. (3) provides the tomographic reconstruction of the T and X distributions.

3. Experimental arrangement

A measurement campaign was conducted to apply the HT technique to the exhaust stream of the augmentor-equipped J85-GE-5 gas turbine engine located at the University of Tennessee Space Institute (UTSI). This engine is operated by personnel affiliated with the Air Force Arnold Engineering and Development Center (AEDC) and has been developed and used as a test bed for evaluation of advanced diagnostic techniques [23

23. K. P. Savage, G. R. Beitel, R. S. Hiers, and R. J. Schulz, “Test capabilities in the AEDC/UTSI J85 turbojet test stand,” in 2007 U. S. Air Force T&E Days (AIAA, 2007)

].

An overview of the experimental arrangement is shown in Fig. 2
Fig. 2 Overview of the experimental setup with a 30-beam HT sensor applied at the exhaust stream of a J85 engine. The laser system (labeled as TDM 3-FDML) was operated from the facility control room and 60-m-long optical fibers were used to transmit the laser signals to the engine location. A 4 × 32 multiplexer located near the engine was used to combine and split the three laser signals into 32 independent outputs. A customer-built tomography frame was mounted at the measurement location (the exit plane of the exhaust nozzle), holding the probe laser beams in position to create the 15 × 15 grid pattern for the tomographic reconstruction.
. The UTSI test facility consists of a high-bay room which contains the J85 engine and a control room located in an adjacent building. The HT sensor was installed on a tomography frame, which held the sensor at the exhaust plane of the engine as shown. The HT sensor utilized 32 laser beams, generated by a laser system consisting of three independent Fourier-domain mode-locked (FDML) lasers [24

24. L. A. Kranendonk, X. An, A. W. Caswell, R. E. Herold, S. T. Sanders, R. Huber, J. G. Fujimoto, Y. Okura, and Y. Urata, “High speed engine gas thermometry by Fourier-domain mode-locked laser absorption spectroscopy,” Opt. Express 15(23), 15115–15128 (2007). [CrossRef] [PubMed]

]. These lasers were placed in the control room, and their operation was synchronized and controlled by a master clock and three function generators (FG). The laser beams generated were then delivered to the measurement location by single-mode fibers (SMF), with length of ~60 m. A 4 × 32 multiplexer was used to combine and distribute the laser beams over the required 32 channels needed for the experiment. The multiplexer was placed near the engine to minimize the length needed for the test-section delivery fibers. A total of 30 laser beams coming out of the multiplexer were used for the actual measurements: 15 of them installed to probe the measurement plane horizontally and 15 vertically (more details shown in Fig. 3
Fig. 3 Schematic representation of the optical test section hardware. A 15 x 15 crossing beam grid pattern with a 36.3-mm beam spacing was used for the tomographic reconstruction. Light from the laser was delivered to the test section via single-mode fibers (SMF) and was collimated and transmitted across the engine exhaust flow. 1-in collection lenses were used on the receiving side and focused the laser light onto photodiodes. Panel (a): configuration of the probe beams. Panel (b): a photograph of the frame and the optical components overlaid by a sample reconstruction to illustrate the location of the flowfield. Panel(c): schematic of the location of the measurements plane in the exhaust and a sample measurement of the 2D distribution of the temperature measured at this location.
), forming a square mesh of 225 grid points over which the tomography reconstruction was performed according to the method described in Section 2. The remaining two laser beams coming out of the multiplexer were used for laser referencing: one of them was sent to a photodiode to record the laser intensity and the other directed to a Mach-Zehnder interferometer to monitor the wavelength scan. The data-acquisition system was placed near the engine (~15 m away from the engine) to minimize the required length of coaxial cable. Cost was the primary motivation for minimizing the length of the fiber and cable.

Figure 3 provides a more detailed illustration of the HT sensor and its installation. The 30 probe beams were installed on a customer-built aluminum frame, which was designed both to hold the probe beams at the measurement plane and also to protect the electro-optic components from the high-temperature and -velocity combustion flow. Panel (a) shows the configuration of the probe beams: 15 installed horizontally and 15 vertically, with a spacing of 38.3 mm (1.5 inches) between probe beams. Panel (b) shows a photograph of the frame and the optical components (with a measured temperature distribution superimposed in the middle). The frame consisted of a square base plate with an opening sized to match the diameter of the exit shroud of the J85 engine 45.72 cm (18 inches). On each of the four sides of the frame, two sets of rails were fabricated and used to mount the fiber collimators and detectors. Each of the 30 probe beams consisted of a laser delivery fiber (Corning SMF-28), a collimating lens, free-space path across the test section, a collection lens, and a photodetector. The collimating lens used was a 1.25-mm-diameter plano/convex fused silica rod-shape lens with a designed working distance of 92 mm at a wavelength of 1310 nm. The plano side of the collimating lens was fused directly to the end of the SMF, and the entire collimating assembly was held in a kinematic stage for beam-alignment purposes. A plano-convex lens with a diameter of 25.4 mm was used to collect and focus light onto the photodetector (Thorlabs PDA10CF, with an active area with 0.5-mm diameter). Panel (c) depicts the location of the measurements plane in the exhaust and a sample measurement of the 2D distribution of the temperature measured at this location. The analog voltage signal from the detector was transferred via coaxial cable to a National Instruments PXI-5105 data-acquisition board for digitization and subsequent data storage on a personal computer.

4. Hyperspectral laser source

A key component in the HT sensor is the hyperspectral laser source, which enabled the measurement of a large number of absorption transitions across a wide spectral range at high repetition rate. The laser source chosen for this work was a time-division-multiplexed (TDM) combination of three FDML lasers, hereafter referred to as the TDM 3-FDML system. This system operates near 1350 nm to monitor H2O vapor absorption features. TDM has been used in H2O vapor absorption spectroscopy for years [25

25. S. I. Chou, D. S. Baer, R. K. Hanson, W. Z. Collison, and T. Q. Ni, “HBr concentration and temperature measurements in a plasma etch reactor using diode laser absorption spectroscopy,” J. Vac. Sci. Technol. A 19(2), 477–484 (2001). [CrossRef]

]. Recently developed TDM lasers for H2O absorption spectroscopy offer enhanced capabilities. For example, a recent TDM laser concept enabled rapid monitoring of numerous (10s to 100s) discrete spectral channels [26

26. T. Kraetschmer, D. Dagel, and S. T. Sanders, “Simple multiwavelength time-division multiplexed light source for sensing applications,” Opt. Lett. 33(7), 738–740 (2008). [CrossRef] [PubMed]

] and was successfully used to monitor gas temperature and H2O and CH4 concentrations in a high-pressure gas turbine combustor rig operated at the Air Force Research Laboratory (AFRL) [27

27. A. W. Caswell, T. Kraetschmer, K. Rein, S. T. Sanders, S. Roy, D. T. Shouse, and J. R. Gord, “Application of time-division-multiplexed lasers for measurements of gas temperature and CH4 and H2O concentrations at 30 kHz in a high-pressure combustor,” Appl. Opt. 49(26), 4963–4972 (2010). [CrossRef] [PubMed]

].

Structurally, the three FDML lasers used in this work were virtually identical. Each was configured to output a high-repetition-rate (~50-kHz) wavelength sweep over a unique ~10 cm−1 spectral range. In our earlier work where one FDML laser was used for H2O absorption spectroscopy for the first time [24

24. L. A. Kranendonk, X. An, A. W. Caswell, R. E. Herold, S. T. Sanders, R. Huber, J. G. Fujimoto, Y. Okura, and Y. Urata, “High speed engine gas thermometry by Fourier-domain mode-locked laser absorption spectroscopy,” Opt. Express 15(23), 15115–15128 (2007). [CrossRef] [PubMed]

], a single FDML was configured to sweep a much broader range (~150 cm−1). By multiplexing 3 FDMLs in this work, we focused on three spectral regions of the H2O spectrum with the highest temperature sensitivity to reduce the data-acquisition load relative to our initial work. Because the center wavelength and sweep range of each of the 3 FDMLs can be independently adjusted [28

28. C. Jirauschek, B. Biedermann, and R. Huber, “A theoretical description of Fourier domain mode locked lasers,” Opt. Express 17(26), 24013–24019 (2009). [CrossRef] [PubMed]

], the TDM 3-FDML source can be optimized for each test article of interest. For example, when the gas pressure within the test environment is high (e.g., 30 bar) the sweep range of each FDML is generally increased to allow more complete monitoring of the shapes of spectral features. When the gas temperatures within the test environment are confined to some limited range, the center wavelengths of the 3 FDMLs can be chosen to offer maximum temperature sensitivity within that range. In this work, the test gas was near atmospheric pressure, so we chose relatively narrow wavelength sweeps (~10 cm−1 each); the temperatures were expected to span 300–2300 K, so we chose features that maximized the overall temperature sensitivity over this wide range of temperatures, following an approach similar to that described in reference [29

29. X. An, A. W. Caswell, J. J. Lipor, and S. T. Sanders, “Determining the optimum wavelength pairs to use for molecular absorption thermometry based on the continuous-spectral lower-state energy,” J. Quant. Spectrosc. Radiat. Transf. 112(14), 2355–2362 (2011). [CrossRef]

].

Because each FDML sweeps a ~10 cm−1 range, absorption baselines can be accurately determined along with in situ feature lineshapes. The latter capability reduces the need to rely on auxiliary measurements of gas pressure and offers the potential for gas pressure measurements in addition to the usual targets (gas temperature and H2O mole fraction).

The TDM 3-FDML laser was designed for multi-beam tomographic measurements based on H2O absorption spectroscopy. The three FDML cavity lengths were matched to within 3 cm (cavity lengths: ~3020 m) in order to operate the fiber Fabry-Perot tunable filters (FFP-TFs) at the same frequency: 50.24337 kHz (the overall repetition rate of the TDM 3-FMDL system). Because of the high number of output beams, each of the three FDML output signals was amplified with an external-cavity semiconductor optical amplifier (SOA) to compensate for the multiplexing loss (−15 dB for 32 fiber-coupled outputs, neglecting excess loss). Pulsing each of these SOAs at ~33% duty cycle facilitated time-division multiplexing of the 3 FDMLs and allowed selection of the middle of the blue-to-red sweep of each laser. The injection current to each external-cavity SOA was provided by an off-the-shelf diode laser controller (Wavelength Electronics, LDTC 2/2 E, 2-MHz modulation bandwidth). The gate signals to the diode-laser controllers were provided by a pulse generator (Berkeley Nucleonics Corporation, BNC555) that was locked with the three FFP-TF drive signal generators (FG, Agilent 33220A) to a synthesized clock generator (Stanford Research Systems, SRS CG635). The entire laser system was housed in a transportable 19-inch rack enclosure.

5. Results and discussions

Measurements were performed on the J85 engine under different conditions including ground-idle, full-military, and full-afterburner operation. Figure 4
Fig. 4 Absorption spectra measured during a single scan of the TDM 3-FDML laser operating at 50.24337 kHz (~20 microseconds). Each panel shows the spectra measured by one of the three FDML lasers.
shows a sample set of the spectra measured by the TDM 3-FDML laser during one single scan under full-afterburner operation. Each panel shows the spectra measured by one FDML laser during that scan at two beam locations (illustrated by the red and blue arrows in the right panel). These two beams locations were chosen to represent a “hot beam” and a “cold beam, beams 4 and 22 illustrated by the red and blue arrow in the right panel, respectively. The hot beam (beam 4) passes through the center of the engine exhaust, along which the temperature distribution varies significantly more than that along the cold beam, which passes through the edge of the exhaust stream. As a result of such different temperature distributions, the spectra measured at the hot and cold beam locations also differ as shown in Fig. 4. Such difference forms the basis for the tomographic reconstruction discussed in Section 2.

A smaller set of absorption transitions can be selected out of those monitored by the three FDML lasers, as shown in Fig. 4, for two considerations. First, not all the transitions shown in Fig. 4 are equally valuable for the tomographic reconstruction [30

30. L. Ma, X. Li, W. Cai, S. Roy, J. R. Gord, and S. T. Sanders, “Selection of multiple optimal absorption transitions for nonuniform temperature sensing,” Appl. Spectrosc. 64(11), 1274–1282 (2010). [CrossRef] [PubMed]

]. Second, consideration of computational cost also motivates the use of a smaller set of transitions [21

21. L. Ma, W. Cai, A. W. Caswell, T. Kraetschmer, S. T. Sanders, S. Roy, and J. R. Gord, “Tomographic imaging of temperature and chemical species based on hyperspectral absorption spectroscopy,” Opt. Express 17(10), 8602–8613 (2009). [CrossRef] [PubMed]

], because the computational cost is approximately proportional to the number of transitions used in the tomographic reconstruction. In this work, we selected a total of 12 transitions out of those shown in Fig. 4 according to the method described in [30

30. L. Ma, X. Li, W. Cai, S. Roy, J. R. Gord, and S. T. Sanders, “Selection of multiple optimal absorption transitions for nonuniform temperature sensing,” Appl. Spectrosc. 64(11), 1274–1282 (2010). [CrossRef] [PubMed]

] for the tomographic reconstruction. Absorption measured at these 12 selected wavelengths was then used as inputs to Eq. (3) to perform the tomographic inversion.

The reconstructions shown in Fig. 5 were obtained based on a square domain of measurement, even though the flowfield was circular. This work defined a square domain of measurement by the tips of the collimating lenses and the tips of the collection lenses, as shown in Panels (a) and (b) of Fig. 3. This square region was then discretized into grids of size 36.3 × 36.3 mm as shown in Panel (a) of Fig. 3 for the tomographic reconstruction.

6. Summary

This paper reports a new laser diagnostic that can measure 2D distribution of temperature and H2O concentration simultaneously with a temporal resolution of 50 kHz at 225 spatial grid points. To our knowledge, it is the first time that such measurement capabilities have been reported. The diagnostic technique leverages recent developments in hyperspectral laser sources and fiber technologies, so that 1) a large number of absorption transitions can be measured over a relatively wide spectral range with a rapid repetition rate, and 2) the probe laser can be split and delivered to perform measurements at multiple spatial locations. A mathematical formulation and a corresponding algorithm have been developed to exploit the multi-spectral and multi-spatial information, yielding 2D tomography imaging of the temperature and H2O concentration distribution.

The HT technique has been demonstrated in the exhaust plane of a practical aero-propulsion engine (General Electric J85). Simultaneous imaging measurement of the distribution of temperature and H2O concentration were obtained at a rate of 50 kHz under different engine operation conditions. The application in a practical aero-propulsion engine demonstrated several unique advantages of the HT technique, including its robustness and ease of implementation in practical systems, and its ability to perform measurements across a relatively large FOV. These advantages are expected to contribute to some critical issues in aero-propulsion systems, such as combustion instability and thermal-acoustic coupling.

Acknowledgments

Funding for this research was provided by the Air Force Research Laboratory under Phase II SBIR Contract No. FA8650-09-C-2946. The authors also acknowledge support from the Air Force Office of Scientific Research (Dr. Chiping Li, Program Manager). Some components used in the construction of the fiber Fabry-Perot tunable filter laser (FFP-TFL) were provided by the NSF/DARPA-sponsored Photonics Technology Access Program (PTAP) program, monitored by Marko Slusarczuk.

References and links

1.

R. K. Hanson, “Applications of quantitative laser sensors to kinetics, propulsion and practical energy systems,” Proc. Combust. Inst. 33(1), 1–40 (2011). [CrossRef]

2.

K. Kohse-Hoinghaus, R. S. Barlow, M. Alden, and E. Wolfrum, “Combustion at the focus: laser diagnostics and control,” Proc. Combust. Inst. 30(1), 89–123 (2005). [CrossRef]

3.

F. Mayinger and O. Feldmann, Optical Measurements: Techniques and Applications (Springer, 2001).

4.

A. C. Eckbreth, Laser Diagnostics for Combustion Temperature and Species (Gordon and Breach Publishers, 1996).

5.

R. S. Barlow, “Laser diagnostics and their interplay with computations to understand turbulent combustion,” Proc. Combust. Inst. 31(1), 49–75 (2007). [CrossRef]

6.

I. Boxx, M. Stohr, C. Carter, and W. Meier, “Sustained multi-kHz flamefront and 3-component velocity-field measurements for the study of turbulent flames,” Appl. Phys. B. 95(1), 23–29 (2009). [CrossRef]

7.

M. Stoehr, I. Boxx, C. Carter, and W. Meier, “Dynamics of lean blowout of a swirl-stabilized flame in a gas turbine model combustor,” Proc. Combust. Inst. 33(2), 2953–2960 (2011). [CrossRef]

8.

B. H. Cheung and R. K. Hanson, “CW laser-induced fluorescence of toluene for time-resolved imaging of gaseous flows,” Appl. Phys. B. 98(2-3), 581–591 (2010). [CrossRef]

9.

K. N. Gabet, R. A. Patton, N. Jiang, W. R. Lempert, and J. A. Sutton, “High-speed CH2O PLIF imaging in turbulent flames using a pulse-burst laser system,” Appl. Phys. B. 106(3), 569–575 (2012). [CrossRef]

10.

N. Jiang, M. Webster, W. R. Lempert, J. D. Miller, T. R. Meyer, C. B. Ivey, and P. M. Danehy, “MHz-rate nitric oxide planar laser-induced fluorescence imaging in a Mach 10 hypersonic wind tunnel,” Appl. Opt. 50(4), A20–A28 (2011). [CrossRef] [PubMed]

11.

D. Hoffman, K. U. Münch, and A. Leipertz, “Two-dimensional temperature determination in sooting flames by filtered Rayleigh scattering,” Opt. Lett. 21(7), 525–527 (1996). [CrossRef] [PubMed]

12.

P. J. Emmerman, R. Goulard, R. J. Santoro, and H. G. Semerjian, “Multi-angular absorption diagnostics of a turbulent argon-methane jet,” J. Energy 4(2), 70–77 (1980). [CrossRef]

13.

P. Paci, Y. Zvinevich, S. Tanimura, B. E. Wyslouzil, M. Zahniser, J. Shorter, D. Nelson, and B. McManus, “Spatially resolved gas phase composition measurements in supersonic flows using tunable diode laser absorption spectroscopy,” J. Chem. Phys. 121(20), 9964–9970 (2004). [CrossRef] [PubMed]

14.

A. M. Chojnacki, G. J. Wolga, and F. C. Gauldin, “Infrared color center laser system for tomographic determination of temperature and species concentration distributions in combusting systems,” Combust. Sci. Technol. 134(1-6), 165–181 (1998). [CrossRef]

15.

R. Villarreal and P. L. Varghese, “Frequency-resolved absorption tomography with tunable diode lasers,” Appl. Opt. 44(31), 6786–6795 (2005). [CrossRef] [PubMed]

16.

P. Wright, C. A. Garcia-Stewart, S. J. Carey, F. P. Hindle, S. H. Pegrum, S. M. Colbourne, P. J. Turner, W. J. Hurr, T. J. Litt, S. C. Murray, S. D. Crossley, K. B. Ozanyan, and H. McCann, “Toward in-cylinder absorption tomography in a production engine,” Appl. Opt. 44(31), 6578–6592 (2005). [CrossRef] [PubMed]

17.

C. T. Herman, “Image reconstruction from projections - the fundamentals of computerized tomography,” in Computer Science and Applied Mathematics (Academic Press, 1980).

18.

W. Cai, D. J. Ewing, and L. Ma, “Application of simulated annealing for multispectral tomography,” Comput. Phys. Commun. 179(4), 250–255 (2008). [CrossRef]

19.

L. Ma and W. Cai, “Determination of the optimal regularization parameters in hyperspectral tomography,” Appl. Opt. 47(23), 4186–4192 (2008). [CrossRef] [PubMed]

20.

L. Ma and W. Cai, “Numerical investigation of hyperspectral tomography for simultaneous temperature and concentration imaging,” Appl. Opt. 47(21), 3751–3759 (2008). [CrossRef] [PubMed]

21.

L. Ma, W. Cai, A. W. Caswell, T. Kraetschmer, S. T. Sanders, S. Roy, and J. R. Gord, “Tomographic imaging of temperature and chemical species based on hyperspectral absorption spectroscopy,” Opt. Express 17(10), 8602–8613 (2009). [CrossRef] [PubMed]

22.

X. An, T. Kraetschmer, K. Takami, S. T. Sanders, L. Ma, W. Cai, X. Li, S. Roy, and J. R. Gord, “Validation of temperature imaging by H2O absorption spectroscopy using hyperspectral tomography in controlled experiments,” Appl. Opt. 50(4), A29–A37 (2011). [CrossRef] [PubMed]

23.

K. P. Savage, G. R. Beitel, R. S. Hiers, and R. J. Schulz, “Test capabilities in the AEDC/UTSI J85 turbojet test stand,” in 2007 U. S. Air Force T&E Days (AIAA, 2007)

24.

L. A. Kranendonk, X. An, A. W. Caswell, R. E. Herold, S. T. Sanders, R. Huber, J. G. Fujimoto, Y. Okura, and Y. Urata, “High speed engine gas thermometry by Fourier-domain mode-locked laser absorption spectroscopy,” Opt. Express 15(23), 15115–15128 (2007). [CrossRef] [PubMed]

25.

S. I. Chou, D. S. Baer, R. K. Hanson, W. Z. Collison, and T. Q. Ni, “HBr concentration and temperature measurements in a plasma etch reactor using diode laser absorption spectroscopy,” J. Vac. Sci. Technol. A 19(2), 477–484 (2001). [CrossRef]

26.

T. Kraetschmer, D. Dagel, and S. T. Sanders, “Simple multiwavelength time-division multiplexed light source for sensing applications,” Opt. Lett. 33(7), 738–740 (2008). [CrossRef] [PubMed]

27.

A. W. Caswell, T. Kraetschmer, K. Rein, S. T. Sanders, S. Roy, D. T. Shouse, and J. R. Gord, “Application of time-division-multiplexed lasers for measurements of gas temperature and CH4 and H2O concentrations at 30 kHz in a high-pressure combustor,” Appl. Opt. 49(26), 4963–4972 (2010). [CrossRef] [PubMed]

28.

C. Jirauschek, B. Biedermann, and R. Huber, “A theoretical description of Fourier domain mode locked lasers,” Opt. Express 17(26), 24013–24019 (2009). [CrossRef] [PubMed]

29.

X. An, A. W. Caswell, J. J. Lipor, and S. T. Sanders, “Determining the optimum wavelength pairs to use for molecular absorption thermometry based on the continuous-spectral lower-state energy,” J. Quant. Spectrosc. Radiat. Transf. 112(14), 2355–2362 (2011). [CrossRef]

30.

L. Ma, X. Li, W. Cai, S. Roy, J. R. Gord, and S. T. Sanders, “Selection of multiple optimal absorption transitions for nonuniform temperature sensing,” Appl. Spectrosc. 64(11), 1274–1282 (2010). [CrossRef] [PubMed]

OCIS Codes
(100.6950) Image processing : Tomographic image processing
(280.1740) Remote sensing and sensors : Combustion diagnostics

ToC Category:
Image Processing

History
Original Manuscript: September 27, 2012
Revised Manuscript: November 8, 2012
Manuscript Accepted: November 9, 2012
Published: January 10, 2013

Citation
Lin Ma, Xuesong Li, Scott T. Sanders, Andrew W. Caswell, Sukesh Roy, David H. Plemmons, and James R. Gord, "50-kHz-rate 2D imaging of temperature and H2O concentration at the exhaust plane of a J85 engine using hyperspectral tomography," Opt. Express 21, 1152-1162 (2013)
http://www.opticsinfobase.org/oe/abstract.cfm?URI=oe-21-1-1152


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References

  1. R. K. Hanson, “Applications of quantitative laser sensors to kinetics, propulsion and practical energy systems,” Proc. Combust. Inst.33(1), 1–40 (2011). [CrossRef]
  2. K. Kohse-Hoinghaus, R. S. Barlow, M. Alden, and E. Wolfrum, “Combustion at the focus: laser diagnostics and control,” Proc. Combust. Inst.30(1), 89–123 (2005). [CrossRef]
  3. F. Mayinger and O. Feldmann, Optical Measurements: Techniques and Applications (Springer, 2001).
  4. A. C. Eckbreth, Laser Diagnostics for Combustion Temperature and Species (Gordon and Breach Publishers, 1996).
  5. R. S. Barlow, “Laser diagnostics and their interplay with computations to understand turbulent combustion,” Proc. Combust. Inst.31(1), 49–75 (2007). [CrossRef]
  6. I. Boxx, M. Stohr, C. Carter, and W. Meier, “Sustained multi-kHz flamefront and 3-component velocity-field measurements for the study of turbulent flames,” Appl. Phys. B.95(1), 23–29 (2009). [CrossRef]
  7. M. Stoehr, I. Boxx, C. Carter, and W. Meier, “Dynamics of lean blowout of a swirl-stabilized flame in a gas turbine model combustor,” Proc. Combust. Inst.33(2), 2953–2960 (2011). [CrossRef]
  8. B. H. Cheung and R. K. Hanson, “CW laser-induced fluorescence of toluene for time-resolved imaging of gaseous flows,” Appl. Phys. B.98(2-3), 581–591 (2010). [CrossRef]
  9. K. N. Gabet, R. A. Patton, N. Jiang, W. R. Lempert, and J. A. Sutton, “High-speed CH2O PLIF imaging in turbulent flames using a pulse-burst laser system,” Appl. Phys. B.106(3), 569–575 (2012). [CrossRef]
  10. N. Jiang, M. Webster, W. R. Lempert, J. D. Miller, T. R. Meyer, C. B. Ivey, and P. M. Danehy, “MHz-rate nitric oxide planar laser-induced fluorescence imaging in a Mach 10 hypersonic wind tunnel,” Appl. Opt.50(4), A20–A28 (2011). [CrossRef] [PubMed]
  11. D. Hoffman, K. U. Münch, and A. Leipertz, “Two-dimensional temperature determination in sooting flames by filtered Rayleigh scattering,” Opt. Lett.21(7), 525–527 (1996). [CrossRef] [PubMed]
  12. P. J. Emmerman, R. Goulard, R. J. Santoro, and H. G. Semerjian, “Multi-angular absorption diagnostics of a turbulent argon-methane jet,” J. Energy4(2), 70–77 (1980). [CrossRef]
  13. P. Paci, Y. Zvinevich, S. Tanimura, B. E. Wyslouzil, M. Zahniser, J. Shorter, D. Nelson, and B. McManus, “Spatially resolved gas phase composition measurements in supersonic flows using tunable diode laser absorption spectroscopy,” J. Chem. Phys.121(20), 9964–9970 (2004). [CrossRef] [PubMed]
  14. A. M. Chojnacki, G. J. Wolga, and F. C. Gauldin, “Infrared color center laser system for tomographic determination of temperature and species concentration distributions in combusting systems,” Combust. Sci. Technol.134(1-6), 165–181 (1998). [CrossRef]
  15. R. Villarreal and P. L. Varghese, “Frequency-resolved absorption tomography with tunable diode lasers,” Appl. Opt.44(31), 6786–6795 (2005). [CrossRef] [PubMed]
  16. P. Wright, C. A. Garcia-Stewart, S. J. Carey, F. P. Hindle, S. H. Pegrum, S. M. Colbourne, P. J. Turner, W. J. Hurr, T. J. Litt, S. C. Murray, S. D. Crossley, K. B. Ozanyan, and H. McCann, “Toward in-cylinder absorption tomography in a production engine,” Appl. Opt.44(31), 6578–6592 (2005). [CrossRef] [PubMed]
  17. C. T. Herman, “Image reconstruction from projections - the fundamentals of computerized tomography,” in Computer Science and Applied Mathematics (Academic Press, 1980).
  18. W. Cai, D. J. Ewing, and L. Ma, “Application of simulated annealing for multispectral tomography,” Comput. Phys. Commun.179(4), 250–255 (2008). [CrossRef]
  19. L. Ma and W. Cai, “Determination of the optimal regularization parameters in hyperspectral tomography,” Appl. Opt.47(23), 4186–4192 (2008). [CrossRef] [PubMed]
  20. L. Ma and W. Cai, “Numerical investigation of hyperspectral tomography for simultaneous temperature and concentration imaging,” Appl. Opt.47(21), 3751–3759 (2008). [CrossRef] [PubMed]
  21. L. Ma, W. Cai, A. W. Caswell, T. Kraetschmer, S. T. Sanders, S. Roy, and J. R. Gord, “Tomographic imaging of temperature and chemical species based on hyperspectral absorption spectroscopy,” Opt. Express17(10), 8602–8613 (2009). [CrossRef] [PubMed]
  22. X. An, T. Kraetschmer, K. Takami, S. T. Sanders, L. Ma, W. Cai, X. Li, S. Roy, and J. R. Gord, “Validation of temperature imaging by H2O absorption spectroscopy using hyperspectral tomography in controlled experiments,” Appl. Opt.50(4), A29–A37 (2011). [CrossRef] [PubMed]
  23. K. P. Savage, G. R. Beitel, R. S. Hiers, and R. J. Schulz, “Test capabilities in the AEDC/UTSI J85 turbojet test stand,” in 2007 U. S. Air Force T&E Days (AIAA, 2007)
  24. L. A. Kranendonk, X. An, A. W. Caswell, R. E. Herold, S. T. Sanders, R. Huber, J. G. Fujimoto, Y. Okura, and Y. Urata, “High speed engine gas thermometry by Fourier-domain mode-locked laser absorption spectroscopy,” Opt. Express15(23), 15115–15128 (2007). [CrossRef] [PubMed]
  25. S. I. Chou, D. S. Baer, R. K. Hanson, W. Z. Collison, and T. Q. Ni, “HBr concentration and temperature measurements in a plasma etch reactor using diode laser absorption spectroscopy,” J. Vac. Sci. Technol. A19(2), 477–484 (2001). [CrossRef]
  26. T. Kraetschmer, D. Dagel, and S. T. Sanders, “Simple multiwavelength time-division multiplexed light source for sensing applications,” Opt. Lett.33(7), 738–740 (2008). [CrossRef] [PubMed]
  27. A. W. Caswell, T. Kraetschmer, K. Rein, S. T. Sanders, S. Roy, D. T. Shouse, and J. R. Gord, “Application of time-division-multiplexed lasers for measurements of gas temperature and CH4 and H2O concentrations at 30 kHz in a high-pressure combustor,” Appl. Opt.49(26), 4963–4972 (2010). [CrossRef] [PubMed]
  28. C. Jirauschek, B. Biedermann, and R. Huber, “A theoretical description of Fourier domain mode locked lasers,” Opt. Express17(26), 24013–24019 (2009). [CrossRef] [PubMed]
  29. X. An, A. W. Caswell, J. J. Lipor, and S. T. Sanders, “Determining the optimum wavelength pairs to use for molecular absorption thermometry based on the continuous-spectral lower-state energy,” J. Quant. Spectrosc. Radiat. Transf.112(14), 2355–2362 (2011). [CrossRef]
  30. L. Ma, X. Li, W. Cai, S. Roy, J. R. Gord, and S. T. Sanders, “Selection of multiple optimal absorption transitions for nonuniform temperature sensing,” Appl. Spectrosc.64(11), 1274–1282 (2010). [CrossRef] [PubMed]

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