air diffusion flames

air diffusion flames

Hydroxyl Time-Series Measurements in Laminar and Moderately Turbulent Methane/Air Diffusion Flames M. W. RENFRO,* S. D. PACK, G. B. KING, and N. M. LA...

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Hydroxyl Time-Series Measurements in Laminar and Moderately Turbulent Methane/Air Diffusion Flames M. W. RENFRO,* S. D. PACK, G. B. KING, and N. M. LAURENDEAU Flame Diagnostics Laboratory, School of Mechanical Engineering, Purdue University, West Lafayette, Indiana 47907-1288, USA

Picosecond time-resolved laser-induced fluorescence (PITLIF) is a developing technique used to probe minor-species concentrations in flames at rates sufficient for the study of turbulent fluctuations. This method has previously been applied to the measurement of CH signals in laminar and low-Reynolds number turbulent diffusion flames. In the present work, Laser-induced Fluorescence (LIF) measurements of OH are obtained in the same flames. The peak concentrations of the hydroxyl radical provide a signal-to-noise ratio sufficient to extend the measurements to a variety of axial and radial locations relative to the flame front. The time-series measured are used to compute power spectral densities (PSDs) which provide frequency information not available from more typical probability density functions. The PSDs are compared to those from the previous CH work and to expectations for scalars in moderately turbulent flames from the literature. These measurements provide the first known PSDs of the hydroxyl radical in a low-Reynolds number turbulent nonpremixed flame. © 1998 by The Combustion Institute

INTRODUCTION Modeling of turbulent diffusion flames via the probability density function (PDF) of mixture fraction has received much attention in the literature and significant progress has been made in developing state relationships for major species as a function of mixture fraction [1] and in building plausible mixture fraction PDFs [2]. However, this procedure often relies on the collapse of scalars to a one-dimensional coordinate and is usually not very effective for flame intermediates [3, 4]. In general, another independent variable, such as the scalar dissipation rate, is required to describe the behavior of such species. A joint PDF can be used to incorporate both variables but even then the use of a PDF to describe turbulent fluctuations will not provide information on the frequencies of the fluctuations in the flow. This frequency information, provided by the power spectral density (PSD), has been studied extensively for nonreacting turbulent flows for which the velocity PSD is expected to display a 25/3 power law region at high Reynolds number [5]. However, in a flame, the local Reynolds number will be much lower than that typically defined from the cold fuel flow rate. Mydlarski and Warhaft [6] measured velocity PSDs via *Corresponding author. COMBUSTION AND FLAME 115:443– 455 (1998) © 1998 by The Combustion Institute Published by Elsevier Science Inc.

hotwire anemometry in a turbulent air jet and showed that even for nonreacting flows, the 25/3 slope is only approached asymptotically for very high Taylor-microscale Reynolds numbers (Re l . 400). Measured values of the PSD slope were observed to be in the range 21.1 to 21.3 at their smallest air flow rates (Re l 5 50). The implication for turbulent combustion is that even if the cold fuel flow rate is high, the increase in kinematic viscosity at flame temperatures could cause the velocity PSD slope to be less steep than 25/3 at high frequencies. Go ¨kalp et al. [7] studied the slopes of velocity PSD measurements in premixed turbulent ethylene/air flames and observed significant departures from the 25/3 limit. The measured PSDs became steeper from the reactant to the product side of the flame front, with slopes both larger and smaller than 25/3. A velocity PSD reported for the same flow conditions but without reaction showed an inertial subrange with a 25/3 slope. However, the effect of combustion on the velocity PSD cannot be described by only a decrease in the local Reynolds number. The authors suggest that the velocity PSDs are complicated by fluctuations in the products and by the intermittent passage of the flame front. They also suggest that scalar PSDs would be required for proper interpretation. Some measurements of scalar PSDs in turbulent nonpremixed flames are available from the literature 0010-2180/98/$19.00 PII S0010-2180(98)00015-7

444 and are introduced when interpreting our results; however, prior to our work with picosecond time-resolved laser-induced fluorescence (PITLIF) such information was not available for minor species. In this paper, we report the first known measurements of OH time-series in a lowReynolds number turbulent diffusion flame. From these time-series, the PSD is computed at frequencies up to 2 kHz. Previous measurements of CH time-series and PSDs in the same flames have been reported [8] and are alluded to subsequently for comparative purposes. However, the signal-to-noise ratio (SNR) in the prior work was insufficient for adequate analysis of the PSD shape. In contrast, the hydroxyl radical is present at much higher concentrations and, despite some spectroscopic disadvantages, the resulting SNR is sufficient for measuring time-series at many locations in an axisymmetric diffusion flame. We report such measurements in both a laminar and a low-Reynolds number turbulent methane/air diffusion flame and compare PSD and PDF shapes as functions of axial height and radial location to similar measurements of scalars from the literature and to our previous CH measurements. We also discuss possible implications of the reported PSD shapes.

EXPERIMENTAL CONSIDERATIONS PITLIF has been used for the hydroxyl timeseries measurements. This developing technique seeks to combine LIF measurements with the capability for on-the-fly electronic quenching corrections, yielding a time-series of quantitative concentration measurements. At this time, it is not possible to correct multiple points of a time-series owing to insufficient electronics for handling the high data acquisition rate and to the large data files necessary for measuring the fluorescence lifetimes (;2 ns). The correction has, however, been demonstrated for single points at times approaching the Kolmogorov scale [9] and the laser system has been upgraded to increase power and decrease noise since this previous study. Future improvements to the electronics should eventually permit the collec-

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Fig. 1. Hydroxyl fluorescence lifetime versus mixture fraction. The bottom graph details the range of mixture fractions for which OH concentrations are at least 10% of the peak value.

tion of a time-series which is independent of collisional quenching. Variations in the quenching rate coefficient for OH in a laminar methane/air diffusion flame have been estimated previously at 620% [10]. We have duplicated this numerical study by using more recent estimates of major species concentrations across the flame front [1] and the respective quenching cross-sections for OH as a function of temperature [11]. The analysis is presented in detail elsewhere [12]. The results, summarized in terms of calculated fluorescence lifetimes in Fig. 1, indicate that quenching variations should be no more than 615% over the range of mixture fractions at which OH is experimentally found to exist (defined by [OH] $ 0.1 [OH]max based on the data of Barlow and Carter [4] and Smooke et al. [13]). The effect of this variation on the PSD is complicated as the quenching fluctuations will produce their own spectral shape derived from fluctuations in the major species concentrations and temperature. Hence, the measured fluorescence PSDs represent contributions from fluctuations in both the hydroxyl concentration and

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Fig. 2. Experimental setup used for the time-series measurements of OH. P, polarization rotator; C, chopper; M, 0.25-m monochromator; R, radiometer.

the quenching rate coefficient. It is, of course, desirable to remove the quenching dependence completely through on-the-fly corrections and this is currently being pursued; however, our estimates of variations in the quenching rate coefficient indicate that this potential error should be relatively small, especially when compared to the measured fluctuations in fluorescence signal. In particular, for our turbulent flame, the relative standard deviation (68% confidence interval) of the measured fluorescence signal is found to be greater than 60% for most measurement locations. The estimated relative standard deviation of the instrumentation noise (including shot noise) is less than 15% [12]; thus, most of the fluctuations present in the measured time-series result from concentration fluctuations. The laser and detection system are shown in Fig. 2. A large frame, multimode, 20-W argon– ion laser was used to pump a Spectra Physics Tsunami, regeneratively mode-locked, 80-MHz, Ti:Sapphire laser. The output of this laser was frequency-tripled using a CSK SuperTripler, modulated by an optical chopper, and focused over the burner assembly. The temporal width of the laser beam was 18 ps, resulting in a spectral width of ;1 cm21 for the transformlimited, sech2 pulse-shape characteristic of the Ti:Sapphire laser system. The wavelength was tuned to excite the relatively temperature-insensitive Q1(8) line in the (0,0) band of the A 2 –X 2 system of OH at 309.33 nm. The beam diameter at the focus was measured to be ;100 mm FWHM, which resulted in an average laser irradiance of 1.0 3 105 mW/cm2 in the probe volume. Fluorescence was collected perpendicular to the laser beam with a 7.6-cm focal-length lens and focused into a 0.25-m monochromator via a

15.2-cm focal-length lens. The entrance slit of the monochromator (1 mm) was used along with the beam diameter to define the probe volume (100 mm 3 100 mm 3 500 mm). At our low Reynolds numbers, these dimensions are probably sufficient for resolving the smallest scales of the flow; however, the current probe volume dimensions may not be sufficient for future studies in fully turbulent flames for which the Kolmogorov scales are smaller. Fortunately, the electronics that are being investigated as replacements to the current system should not only allow for on-the-fly quenching corrections, but should also increase the SNR by an order of magnitude. Tighter probe volumes could be utilized at this point. The exit slit of the monochromator (6.5 mm) was set to allow a detection bandwidth of 26 nm centered at 309 nm in the (0,0) band, thus blocking spontaneous flame emission outside of this range. A PMT (Hamamatsu HS5321) with a risetime of 700 ps and a transit time-spread of 160 ps was used to detect the fluorescence. The PMT current was boosted by a low-noise preamplifier and then demodulated by a lock-in amplifier which utilizes phase-sensitive amplification tied to an optical chopper to increase the SNR. Typical lock-in amplifiers have a bandwidth of no more than 200 Hz. We have bypassed the 6 dB internal filters of our lock-in system and have used an external 8-pole, 6-zero, constant-delay low-pass filter to provide analog signals with a bandwidth of over 10 kHz. This technique necessarily increases the noise but is required to resolve the higher frequency fluctuations in a turbulent flame. For the present measurements, the low-pass filter was set to provide a 2-kHz bandwidth owing to the 4-kHz operation limit for the optical chopper. A data acquisition board then sampled this signal at 4

446 kHz. An electro-optical modulator could be used to increase the modulation rate and thus increase the sampling rate, but this also causes a decrease in the SNR as the effective averaging time for each point of the time-series diminishes. For the measurements reported here, the 4-kHz limit does not appear to significantly affect the results as the PSD decays into the noise floor prior to the upper frequency limit at all measurement locations. For fully turbulent flames this may not be the case. The SNR enhancement expected from the improved electronic system should allow for time-series measurements with larger bandwidths. Means, PDFs, and PSDs (0 –2 kHz) were all computed from the sampled time-series. These calculations comprise the results presented in this paper. A concentric tube burner identical to that used for the previous CH measurements [8] was used to create the diffusion flames. Methane was supplied through the central tube (5.5 mm inner diameter) and air was supplied through an outer annulus for the laminar flame to dampen the effects of room air fluctuations. The Reynolds number based on the cold methane flow rate was 70 and 2800 for the laminar and turbulent flames, respectively. The relatively low turbulent Reynolds number was required to keep the flame attached to the burner.

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Fig. 3. Mean OH radial fluorescence profiles in the laminar diffusion flame.

ferences. Up to a height of x 5 30 mm, virtually all of the signal is from OH fluorescence. At x 5 40 mm and x 5 50 mm, significant interference occurs on the fuel side of the OH peak. The location and width of these interference peaks are very similar to those noted for previous CH measurements [12] and are likely caused by scattering from soot particles formed in the diffusion flame. Laminar Flame Time-Series and PSDs

RESULTS AND DISCUSSION Laminar Flame Radial Profiles Mean OH radial profiles were measured in the laminar flame at several heights above the burner as shown in Fig. 3. The OH peak signal level does not change significantly with increasing height above the burner. The width of the OH peak, however, doubles from x 5 3 mm to x 5 30 mm and the location of the peaks moves further out with increasing height because of flame widening. The width of the peak for OH is about twice that for CH owing to the existence of OH over a larger range of mixture fractions and temperatures [13]. Fluorescence detection spectra were obtained at several locations and radial profiles were repeated after tuning the laser off the OH transition to check for potential inter-

Time-series were obtained at peak radial locations in the laminar flame for several heights above the burner. This diffusion flame has a strong buoyancy-driven flicker at low frequency, and the amplitude of the oscillation is expected to increase with height above the burner [14]. For CH, SNR issues required that the timeseries measurement only be made low in the flame [8]. Here, measurements can be made at many heights and at radial locations away from the peak concentration. The fluorescence signal was sampled at 800 Hz for these measurements, thus resolving frequencies up to 400 Hz. Timeseries measured at the peak radial concentration at heights of x 5 3, 10, and 30 mm are shown in Fig. 4. Consistent with expectation, the low-frequency flicker is visually more apparent high in the flame. The PSDs computed from these time-series are shown in Fig. 5. The

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Fig. 4. Time-series of OH fluorescence signal in the flickering laminar diffusion flame at three heights. The preamplifier gain was doubled for the x 5 3 mm measurement.

low-frequency oscillation is apparent at each height, although the strength of the oscillation grows with increasing height above the burner. In addition to this ;15 Hz frequency, components are present at 133 Hz owing to the chopper wheel rotation rate, 60 Hz owing to line noise, and 30 Hz for the measurement at x 5 30 mm. The latter component is likely a second harmonic of the buoyancy-induced flicker that is apparent as the amplitude becomes sufficiently large [14]. PSDs determined from measurements of OH in a laminar premixed burner show only the 133-Hz and 60-Hz noise components. Other potential noise sources (laser fluctuations, electronics, etc.) are below the shotnoise floor and do not contribute to the reported spectra. Compared to the time-series previously measured for CH, the SNR (mean/standard deviation) for OH is about 10 times larger. The noise in the time-series is largely caused by shot noise and by the ineffectiveness of the lock-in amplifier in measuring signals consisting of low average photon levels [12]. The decrease in relative noise for OH results directly from an increase in the number of fluorescence photons reaching the photomultiplier tube (PMT). An important consequence of this reduction in relative noise is a reduction in the PSD background. Ironi-

Fig. 5. PSDs of OH fluorescence signal in the flickering laminar diffusion flame. Fifty PSDs calculated from timeseries like those shown in Fig. 4 are averaged to obtain cleaner PSDs.

cally, this decrease in the noise floor causes the hydroxyl PSD to appear noisier than that for CH [8] since noise sources (e.g., line noise) with small contributions to the PSD can now be resolved. If the noise floor from a typical CH time-series were present for these OH measurements, even the buoyancy-induced frequency would not be apparent at the lowest measured height in Fig. 5. A comparison between the CH and OH PSDs in this flame sheds light on another difference not caused by SNR issues. Comparing the amplitude of the buoyancy-induced fluctuation at 15 Hz, the CH PSD [8] is observed to be two orders of magnitude greater than the OH PSD. The buoyancy forces cause a low-frequency oscillation of flame velocities [14]. The effect of this oscillation on the fluorescence time-series arises from a convolution of these velocity fluctuations with the distribution in minor-species concentration. For OH, the concentration peaks are wider than those for CH in the radial direction and the changes in peak concentration

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are smaller than those for CH from one height to the next. The result is that a small amplitude velocity fluctuation for OH will cause a small change in its fluorescence signal, whereas this change is apparently much larger for CH. This can be understood from the species conservation equation [15],

r

­Y i Y i! 1 w i Y i2¹ Y z ~ r Y iV 5 2r vY z ¹Y ­t

(1)

where Y i is the species mass fraction, w i the Y i the diffusion species production rate, and V velocity for the ith species. Using the continuity equation and the definition of mass fraction, Eq. 1 can be converted into a form useful for species concentration measurements, i.e., ­C i w Y i! 1 i Y z ~C ivY ! 2 ¹ Y z ~C iV 5 2¹ ­t Mi

(2)

where C i is the concentration (moles/cm3) and M i is the molecular weight of the ith species. The relationship between velocity and concentration fluctuations can subsequently be derived under the following assumptions: (1) Concentration variations from diffusion and chemical production/destruction are negligible compared Y i 5 0). (2) to those from convection (w i 5 0; V Velocity fluctuations occur at a single frequency, v. (3) The amplitude of the velocity fluctuation, A (m/s), is not a strong function of position or time. (4) The concentration gradient is approximately constant. Under these assumptions, vY s 5 A sin ( v t) and the change in measured local concentration with respect to time becomes ­C i ­C i 5 2A sin ~ v t! . ­t ­s

(3)

The amplitude of the concentration fluctuation, and hence the strength in the PSD, is directly proportional to the species concentration gradient. These assumptions may or may not be reasonable for fluctuations in the laminar flame, but Eq. 3 certainly serves to illustrate one way by which the radial profile can affect the timeseries measurement. Although not necessary for the present study, this analysis could be further generalized to allow velocity fluctuations over a range of frequencies by taking a Fourier series summation of Eq. 3 over all such frequencies.

Fig. 6. Time-series of OH fluorescence signal in the flickering laminar diffusion flame at the radial peak location (x 5 5 mm and x 5 20 mm) and 0.5 mm toward the fuel stream (x 5 5 mm).

The postulated behavior with respect to the concentration gradient as described in the previous paragraph can be pursued further by comparing time-series and PSDs measured away from the radial peak. Figure 6 shows time-series of OH measured at the radial peak for x 5 5 mm and x 5 20 mm, and also 0.5 mm toward the fuel stream for x 5 5 mm. The buoyancy-induced oscillations are visually apparent in the off-peak time-series measurement similar to the on-peak measurement higher in the flame, whereas the peak measurement at x 5 5 mm just appears noisy. Figure 7 shows the corresponding PSDs for these three time-series. Note the stronger coupling between the velocity fluctuation and the measured fluorescence fluctuation at the location where the concentration gradient is largest for x 5 5 mm. The energy of the fluctuation is even larger for the off-peak case lower in the flame than for the on-peak case much higher in the flame, which underscores the importance of a greater concentration gradient, as indicated in Eq. 3. The noise floor for the off-peak measurement is also higher owing to the lower fluorescence signal. Thus, the PSD appears cleaner when in reality the spectral noise sources are just buried beneath a larger spectrally uniform noise floor

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Fig. 8. Radial profiles of mean OH fluorescence signal in the low-Reynolds number turbulent diffusion flame.

Fig. 7. PSDs computed for the time-series of Fig. 6, comparing radial peak and fuel-side location measurements.

(shot-noise). This off-peak PSD is almost identical to that obtained at the peak radial concentration (x 5 3 mm) in the same flame for CH [8].

different from the x 5 5 mm case. Consequently, a comparison is presented for only the x 5 5 and x 5 30 mm cases. Turbulent Flame Probability Density Functions Figure 9 shows the PDFs computed at x 5 30

Turbulent Flame Radial Profiles Radial fluorescence profiles measured in the turbulent flame are shown in Fig. 8. As before, fluorescence detection spectra and off-resonance profiles were obtained to test for fluorescence interferences. No interferences were found below x 5 60 mm in this flame. The SNRs achievable here permit a detailed examination of PSD and PDF shapes at different locations. PDFs are available with low repetition rate lasers and as such are not unique to the PITLIF instrument; however, PDF and PSD shapes can now be compared for further analysis of such flames. Time-series measurements were made at many radial locations at heights of x 5 5, 30, and 60 mm. The PDFs and PSDs for the x 5 30 mm and x 5 60 mm cases were found to be nearly identical to each other but considerably

Fig. 9. PDFs measured at x 5 30 mm in the turbulent diffusion flame for various radial locations (y). Negative values of y are on the fuel side of the peak (0 mm).

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Fig. 10. Time-series measured at the peak radial fluorescence signal for x 5 30 mm in the turbulent diffusion flame.

mm for several radial locations. Far off the peak on either the air or fuel side (uyu . 2 mm), the PDF is centered near zero (no measured signal). At these locations, there is still some deviation from the zero mean as a result of flame emission. At the radial peak, where the concentration is larger, the bulk of the PDF exists significantly above zero. However, even at the peak, fluctuations are large enough to cause a zero signal some of the time. The result is a bimodal structure in the PDF. This type of PDF is found frequently in this flame, and in each case the time-series from which it is computed is visually meaningful. A time-series measured at the radial peak for x 5 30 mm is shown in Fig. 10. The bimodal nature of the signal is apparent. Although the frequencies at which these fluctuations occur cannot be observed from this plot, it is apparent that the signal is more likely to occur at the peak or at zero than anywhere in between. Figure 11 shows PDFs for x 5 5 mm at various radial locations. On the air side of the peak (y 5 0.5 mm), the PDF shows a nearly symmetric distribution toward higher and lower signals. At the peak, the PDF is again nearly symmetric. However, in this case, a long tail toward lower signals exists but the probability is monotonically decreasing and not bimodal. A mirror image of the peak PDF occurs on the air

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Fig. 11. PDFs measured at x 5 5 mm in the turbulent diffusion flame as a function of radial position (y). Negative values of y are on the fuel-side of the radial peak (0 mm).

side at y 5 1.0 mm. On the fuel side, the distribution is nonsymmetric, skewed in one direction or the other depending on the mean value. The shapes of these PDFs are not apparent from the time-series as with the previous bimodal case. For the symmetric PDFs, the signal does not always contain zero values (e.g. the air-side PDF at y 5 0.5 mm in Fig. 11), particularly for the larger mean signal locations, whereas for the skewed (bimodal) PDFs, the probability of obtaining no signal is always greater than zero and often represents a significant portion of the overall time-series. Comparing the two heights, the PDF shape for x 5 30 mm does not significantly change from the air side to the fuel side. The distribution is sometimes less bimodal than at the peak (y 5 0 mm) but it is always nonsymmetric and all differences are likely a result of only the changing mean concentration. In contrast, the PDF shape at x 5 5 mm is nonsymmetric on the fuel side (similar to all PDFs at x 5 30 mm) and symmetric on the air side. This difference cannot be described by just a change in the mean concentration. Since the flame is attached to the burner, the scalar fluctuations are attenuated at lower elevations (x 5 5 mm) and grow downstream [14]. This could impact both the PDFs and PSDs. Moreover, at the lower heights, the

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Fig. 12. PSDs measured at x 5 30 mm in the turbulent diffusion flame. The darkest line is 1.0 mm to the air side of the peak, the medium line is at the peak, and the lightest line is 1.5 mm to the fuel side of the peak.

flame front is outside the shear layer [16]; thus, the impact of fuel-stream turbulence on species concentration could be more important for fuelside measurements than for air-side measurements, which may be dominated by the buoyant outer flow [14]. Higher in the flame, where both the shear layer and the scalar fluctuations are greater, the differences from the air side to the fuel side should be less pronounced, as found in our experimental measurements. Turbulent Flame Power Spectral Densities PSDs were also computed at each of the points corresponding to the previous PDFs. Figure 12 shows the PSDs at x 5 30 mm. Each PSD appears to have a two-slope structure with a linear region (log-log scale) from DC to ;100 Hz and a second linear region above ;200 Hz. The second slope decays into the noise floor, which is a function of the SNR. Consistent with the PDFs (Fig. 9), no substantial difference is observed from the fuel to the air side. The fuel side PSD has a slightly higher knee frequency (intersection of first and second slopes) and the transition from one slope to the next is sharper but these differences are small. From linear fits to these two slopes, the decay coefficient for the first slope varies from about 20.5 to 21.0 from

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Fig. 13. PSDs measured at x 5 5 mm in the turbulent diffusion flame. The darkest line is 0.5 mm to the air side of the peak, the medium line is at the peak, and the lightest line is 0.5 mm to the fuel side of the peak.

the fuel to the air side, respectively. The second (high-frequency) slope does not vary significantly from the fuel to the air side, having an average value of about 22.4. The uncertainty in this slope is about 15% for the measurements from one side to the other. Some of this difference arises from the need to vary the fit range as the knee frequency changes and as the noise floor rises and begins to corrupt the higher frequency regions. A repeatability analysis reveals an uncertainty (2s) of less than 5% in this slope for measurements repeated at the same location, for which the knee frequency and noise floor remain constant. Figure 13 shows a similar comparison of PSDs for a height of x 5 5 mm. At this height, significant differences are found from the fuel to the air side, similar to the PDFs (Fig. 11). The fuel-side PSD has a two-slope structure with a sharp transition between the first and second linear slope. As at x 5 30 mm, the knee frequency decreases from the fuel side to the air side of the flame front. For the air-side PSD, the two slopes are so close in magnitude that the PSD visually looks like a single-slope decay. The low-frequency slope varies again from about 20.5 to 21.0 from the fuel side to the air side, respectively. The high-frequency slope is ap-

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M. W. RENFRO ET AL. be adequately characterized. Despite this, the PSDs measured very near the burner surface (x 5 1 mm) were found to be identical from the fuel side to the air side, each having a singleslope structure with a slope of about 21.2 above around 10 Hz. Moreover, the PDFs at these locations were found to be symmetric at all radial measurement locations. Interpretation of Turbulent Flame Results

Fig. 14. PSDs of OH and CH at x 5 5 mm. The data have been smoothed by a five-point moving average for clarity in the high-frequency region.

proximately 22.2 for the fuel-side PSD, and drops to about 21.2 for the air-side PSD. A typical air-side PSD at x 5 5 mm is plotted, along with a similar measurement for CH, in Fig. 14. The CH PSD was previously found to display a slope of 21.2 for both fuel- and air-side measurements [12]. This is nearly identical to the slope for the OH measurement on the air side at the same height, despite the significantly narrower radial distribution of CH. However, the OH fluctuations are much higher in amplitude at lower frequencies, a difference that will be examined in future work. Since the measurements are not made at the same radial location, this similarity could be coincidental. Moreover, at this low height, the overall standard deviation of the hydroxyl time-series measurement is not significantly greater than the maximum possible fluctuation from electronic quenching (615%). Thus the effects of quenching could be problematic to measurements in this region of the flame. In particular, some of the disparity between the OH and CH PSDs could be a result of differences in quenching fluctuations. Some OH measurements were also made below x 5 5 mm. As the probe volume approaches the burner surface, vignetting becomes problematic and the radial profile cannot

The possible significance of a PSD slope steeper than 22.0 can be addressed by examining the relationship between velocity fluctuations and the fluorescence signal via the radial shape of the hydroxyl profile. Momentarily neglecting other sources of potential fluorescence fluctuations (quenching variations, diffusion, OH creation and depletion) and assuming that all variations result from velocity fluctuations which merely move the OH radial profile back and forth across the probe volume, a relationship can be found between the velocity and fluorescence PSDs. In this case, the instantaneous fluorescence signal can only be a function of the instantaneous position of the radial OH profile. Consequently, the fluorescence timeseries must be proportional to the integral of the velocity time-series. This can be understood more clearly by reexamining Eqs. 2 and 3 which show that for these assumptions (negligible nonconvective terms) the temporal change in the fluorescence signal is proportional to the instantaneous velocity. The fluorescence signal must then be proportional to the integral of these velocity fluctuations. The relationship between the spectrum of a function (position, x) as compared to its derivative (velocity, v) is well known [5, 17], i.e., S v( v ) 5 v 2S x( v )

(4)

This means that the OH fluorescence spectrum will have an additional 22.0 slope imposed upon that for the velocity spectrum but will otherwise maintain the same shape. If the above effect, namely convection of the radial OH profile without a change in its basic shape, is to be the dominant or only source of fluctuations, the slope of the PSD must be steeper than 22.0 at high frequencies as the velocity PSD in

HYDROXYL TIME-SERIES MEASUREMENTS turbulent flames is most likely itself decaying at a significant slope. Fluorescence PSDs with slopes steeper than 22 are very possibly dominated at high frequencies by this velocity effect, although many other physical processes are occurring such as electronic quenching, diffusion, and reaction. A possibility for future work in this area is to compare fluorescence and velocity PSDs obtained at the same point in the flame. The present analysis implicitly assumes that the fluorescence time-series accurately mimics the time-series for flame location. This assumption is most accurate for small-scale fluctuations (high frequencies) which do not encompass a large portion of the OH spatial distribution. For large-scale fluctuations, we must obviously consider the convolution of the actual radial profile with the greater fluctuations in flame-front location. For many PSDs measured in the turbulent diffusion flame (x $ 5 mm), the high-frequency slopes are near 22.4. If the above convective effect were responsible, this would indicate a velocity decay with a slope of only 20.4. This is far below the Kolmogorov limited 25/3, but the Reynolds number for our flame is also very low and a strong dependence of the high-frequency slope on Reynolds number has been observed in previous velocity measurements [6]. For the case of a fixed scalar profile moving across the measurement location, the PDF can be estimated from an assumed Gaussian velocity PDF [2] and can result in a bimodal shape [18]. The bimodal or skewed PDFs measured here match the types of PDFs computed by Effelsberg and Peters [2]. Furthermore, the bimodal PDFs in the current investigation coincide with PSD slopes steeper than 22.0 in all cases. Additional sources for these fluctuations should be examined in future work, but both the PDFs and PSDs measured high in the turbulent diffusion flame are consistent with fluctuations associated only with convection. To arrive at this simplification, the diffusion and reaction rate terms in the species conservation equation have been neglected. Neglecting w i is equivalent to assuming that the species concentration, Y i , is only a function of a conserved scalar; that is, both Y i and the mixture fraction are governed by the same conservation equation.

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For locations where the PDF appears Gaussian, the high-frequency slope of the PSD is around 21.2 in most cases. This slope is insufficiently steep to be described solely by convection. The relevant regions are low in the diffusion flame where the flame is attached to the burner. In these regions the scalar dissipation rate is much higher [19] and neglecting source terms when evaluating fluctuating species likely becomes invalid. As noted previously, minorspecies concentrations are not generally well described by just the mixture fraction [3] so this behavior is not unexpected. The PSDs for other species and temperature (as required to calculate w i ) may need to be considered to describe the hydroxyl PSDs in these regions. Velocity time-series measured at the same point in the flame could be used with composition and temperature profiles and simplified chemistry to attempt a calculation of OH and CH PSDs. For now, without these measurements, hydroxyl PSDs can only be compared to other timeresolved scalar measurements in similar flames. McQuay and Cannon [20] recently measured temperature PSDs in an elliptic diffusion flame (Re 5 6000). Although much of their work was focused on the differences occurring on the major and minor axes of these flames, the PSDs are some of the most detailed found in the literature. The temperature PSDs are characterized by slopes similar to those measured for OH. In particular, the fuel-side temperature PSDs are flat at low frequencies, show a sharp knee frequency at several hundred Hertz, and display a power-law decay at higher frequencies with slopes steeper than 22.0. Moving toward the air side, the knee frequency decreases and the transition between the flat low-frequency and decaying high-frequency regions becomes less clear. Finally, far on the air side, the PSDs are characterized by one slope over nearly all relevant frequencies. High in the flame, the temperature PSDs are more similar from the air to the fuel side. The associated PDFs are also largely nonsymmetric although never bimodal. The existence of enhanced small-scale fluctuations in the fuel stream for both temperature and OH is consistent with the numerical predictions of Katta and Roquemore [16]. However, unlike the present OH measurements, the highfrequency slopes of McQuay and Cannon [20]

454 are always steeper than 22.0. This slope is consistent with convection-dominated fluctuations for temperature. Low in the flame, where the hydroxyl PSDs appear to indicate that nonconvective terms are important, the temperature PSDs still exceed 22.0.

SUMMARY In conclusion, OH fluorescence time-series have been presented in both laminar and lowReynolds number turbulent diffusion flames for the first time. Unfortunately, the current state of the electronics used with the PITLIF instrument does not allow real-time quenching corrections to the measured time-series. This is recognized as a potential limitation to the current measurements and present work is involved in upgrading the electronics to allow on-the-fly quenching corrections. However, estimates for the variation in the OH quenching rate coefficient in a diffusion flame show that the associated error should be less than 615%. Thus, the time-series reported still represent species concentration fluctuations up to this limit. Moreover, the PDFs and PSDs computed from the PITLIF measurements have sufficient SNRs to provide detailed information at a variety of locations in both laminar and moderately turbulent flames. The application of PITLIF to hydrogen flames at higher Reynolds numbers will allow future work to focus on fully turbulent conditions. The significant results of the present study can be summarized as follows: 1. The laminar flame is observed to have a strong ;15 Hz buoyancy-induced OH oscillation consistent with previous measurements of CH in the same flame. 2. The strength of this oscillation in the PSD depends on the local concentration gradient as predicted by the species conservation equation. 3. PSDs measured high in the turbulent diffusion flame are found to have high-frequency slopes steeper than 22.0, possibly a result of convective fluctuations. 4. Low in the turbulent diffusion flame, the PSDs display slopes very close to 21.2, which

M. W. RENFRO ET AL. is not steep enough to be described by pure convective fluctuations. 5. PSDs measured on the fuel side of the turbulent flame front are characterized by more intense small-scale (high-frequency) fluctuations than those on the air side. This behavior is consistent with other scalar (temperature) measurements in similar flames [20] and with numerical predictions [16]. 6. PDFs at all locations where the PSD slope is steeper than 22.0 are nonsymmetric and usually bimodal. This behavior can be predicted from turbulent PDF analysis [18] and is consistent with previous scalar measurements of temperature [21] and density [22]. Both the steep PSD slope and the bimodal PDF shape can be derived from the species conservation equation if all fluorescence fluctuations are assumed to arise from convection. In general, the PSDs measured are very repeatable and display interesting similarities and differences when compared with other scalar measurements. Clearly more work is needed to establish the mechanism for the reported hydroxyl fluctuations, but the present analysis suggests that regions high in low-Reynolds number diffusion flames may be sufficiently dominated by species convection that chemical reaction rates might not be needed to describe relevant OH fluctuations. This would be equivalent to treating [OH] as solely a function of the local mixture fraction. However, regions low in the flame, where primary oxidation of the fuel is occurring, apparently cannot be simplified in this way. This work is supported by the U.S. Air Force Office of Scientific Research, with Dr. Julian Tishkoff as technical monitor. We are grateful for discussions with Dr. Michael Klassen (Hughes Associates, Inc.) concerning the quenching rate coefficient calculations and with Professor Jay Gore (Purdue University) concerning data analysis and interpretation.

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Received 11 July 1997; revised 26 January, 1998