Abstract

Picosecond laser electronic-excitation tagging (PLEET) was demonstrated in a Mach-6 Ludwieg tube at a repetition rate of 100 kHz using a 1064 nm, 100 ps burst-mode laser. The system performance of high-speed velocimetry in unseeded air and nitrogen Mach-6 flows at a static pressure in the range of 5–20 torr were evaluated. Based on time-resolved freestream flow measurements and computational fluid dynamics (CFD) calculations, we concluded that the measurement uncertainty of 100 kHz PLEET measurement for Mach 6 freestream flow condition is ∼1%. The measured velocity profiles with a cone-model agreed well with the CFD computations upstream and downstream of the shockwave; downstream of the shockwave the discrepancy between the CFD and experimental measurement could be attributed to a slight nonzero angle of attack (AoA) or flow unsteadiness. Our results show the potential of utilizing 100 kHz PLEET velocimetry for understanding real-time dynamics of turbulent hypersonic flows and provide the capability of collecting sufficient data across fewer tests in large hypersonic ground test facilities.

© 2020 Optical Society of America under the terms of the OSA Open Access Publishing Agreement

1. Introduction

Hypersonic flights (speeds above Mach 5) provide an unprecedented capability by simultaneously extending traveling range and reducing transit time [1,2]. The design of high-performance hypersonic aircraft requires the careful analysis of external airflows to predict aerodynamics and aeroheating. However, the turbulent, transitional, and unsteady nature of hypersonic flow presents challenges for accurate flowfield computation [14]. Large hypersonic ground test facilities are used extensively for generating forces, moments, heat transfer, and flowfields; they are also used for surface measurements of test articles required to validate computational tools used to extrapolate wind tunnel data for realistic atmospheric flight conditions. Quantitative results in these test environments are essential for the validation of computational fluid dynamics (CFD) models and the development of prediction algorithms. These tools have a direct impact on flight hardware design. Among the host of physical measurable parameters for characterization and modeling of hypersonic aerodynamics, accurate flow velocity field measurement remains a significant but essential challenge in these facilities.

Furthermore, the high flow velocity, high instability, and wide range of frequencies inherent in hypersonic flows require high repetition rate measurements to accurately track the flow dynamics. Jewell and Kimmel reported that the calculated second-mode instability frequency for a sharp cone in a Mach 6 blow-down wind tunnel exceeds 300 kHz for a stagnation pressure of 9.6 MPa (∼1400 psi) [5]. Even higher frequencies (> 1 MHz) may occur in high-enthalpy boundary layers because of their small scales and large boundary layer edge velocity. Additional measurement challenges arise from low static pressure [a few kPa (torr)], which results in a low signal for scattering and fluorescence-based laser diagnostic techniques.

In the last few decades, several laser-based velocimetry techniques have been developed for high-speed flow measurements, including particle imaging velocimetry (PIV) [6,7,8], planar doppler velocimetry (PDV) [10], molecular tagging velocimetry (MTV) [9,11,12], and femtosecond laser electronic excitation tagging (FLEET) [13,14]. However, these techniques have the following limitations:

  • (1) requirement of seeding solid or liquid particles, which can alter the mean flow and introduce unsteady disturbances (PIV),
  • (2) seeding gas molecules which could change test gas properties such as viscosity (MTV,PDV),
  • (3) low measurement speed limited by the laser repetition rate.
A few non-intrusive laser velocimetry techniques, non-seeded (i.e. nitrogen) FLEET [14], Krypton tagging velocimetry (KTV) [4], Iodine tagging velocimetry [12], Acetone tagging velocimetry [11], Nitric Oxide tagging velocimetry [15], and filtered Rayleigh scattering velocimetry [16] have been implemented in supersonic and hypersonic wind tunnels. However, these measurements are constrained by the laser repetition rate (10–1000 Hz). Recently, Jiang et al. [17] demonstrated non-seeded picosecond-laser electronic-excitation tagging (PLEET) velocimetry at a repetition rate of 100 kHz using a picosecond (ps) burst mode laser. This method requires only a focused ps-pulse-laser beam and an intensified camera. An intense 100-ps laser pulse is used to dissociate N2 in a flow and multiple images are acquired from the long-lived fluorescence associated with nitrogen atom recombination back to molecular nitrogen. The strongest emission band lies in the 300–650 nm region of the spectrum, making it readily detectible using an ultraviolet-visible light detector. Similar to the MTV technique, the velocity is calculated from the measured displacement of the tagged emission line captured at specific time intervals using a gated camera. Recently, this technique has been applied to time-resolved velocity measurements in the NASA Langley 0.3-m transonic cryogenic tunnel [18]. Ps-burst-mode laser-based PLEET velocimetry allowed the data acquisition rate for nitrogen-based seedless velocimetry to be increased by more than two orders of magnitude (> 100x faster than FLEET), hence enabling temporally-correlated, spatially-resolved measurements in highly-turbulent hypersonic flows. To date, PLEET has been mostly employed for subsonic and transonic flow diagnostics in large wind tunnel facilities, which operate at a static pressure range of ∼40–400 kPa (300–3000 Torr) [18]. To our knowledge, this technique has not been used for velocimetry in hypersonic flows which are at extremely low-pressure conditions ∼0.13–2.6 kPa (1– 20 Torr). Additionally, all the previous PLEET measurements were performed in pure nitrogen flows and the feasibility of this technique for hypersonic air flows needs to be explored.

In this work, we demonstrated 100 kHz PLEET for flow velocity measurements in the freestream and with a cone-model in a Mach-6 Ludwieg tube using a ps burst-mode laser. The ps-burst-mode-laser-based PLEET system performance for high-speed velocimetry was evaluated for air and nitrogen flows in both the freestream and shock layer of a cone model. The experimentally measured velocities were used to validate the computed (via compressible flow theory) freestream velocity that the hypersonic wind tunnel creates at a given condition, and provide a better understanding of the hypersonic wind tunnel performance.

The organization of this paper is as follows. In section 2, we describe the experimental setup of the 100 kHz PLEET in a Mach 6 Ludwieg tube. In section 3, time-resolved velocity measurements for free-steam and boundary layer cases are discussed. The results and prospects for future work are summarized in section 4.

2. Experimental setup in AFRL hypersonic wind tunnel

(a) AFRL Mach 6 Ludwieg Tube

The Air Force Research Laboratory (AFRL) Mach-6 Ludwieg Tube, shown in Fig. 1, was constructed to generate a Mach-6.14 (±0.03) air flow at various stagnation pressures of 379 kPa–4.14 MPa, resulting in unit freestream Reynolds numbers of 6.56×105/m – 3.28 × 107/m. More details about the Ludwieg tube facility can be obtained from Ref. [19]. The inner surface of the driver tube is heated to ∼505 K, and the driver tube is connected to a gas heater that heats the gas from two compressors up to a temperature around 500 K. This tunnel can be run in different modes: single-diaphragm mode, double-diaphragm mode, and fast plug valve mode. Currently, the tunnel is equipped with a pneumatic-driven fast plug valve with an opening time of ∼18 ms, thereby generating relatively short, frequent runs (200 ms test time in every 20 minutes) with low infrastructure cost. Note that all the images presented in this paper were acquired when the tunnel was operated in a fast plug valve mode. The test chamber has a diameter of approximately 1.27 m and contains three circular hatches, one on the top and one each on the east and west faces of the test chamber. The east hatch is an autoclave door that provides rapid access to the test section. Both the east and west hatches contain 30.5 cm diameter fused silica windows. The top hatch contains a smaller (50 mm diameter) high-graded fused silica window (Corning 7980) with 12.7 mm thickness for the transmission of PLEET laser beams. The PLEET signal was collected from the quartz-side window. A 7-degree half-angle circular cone model made of aluminum was installed for studying velocity profile in the downstream of the shock layer, as shown in Fig. 1(c).

 figure: Fig. 1.

Fig. 1. (a) AFRL Mach-6 Ludwieg Tube Hypersonic Wind Tunnel. (b) A photograph of wind tunnel test section with three optical access ports in an environmental controlled room. (c) A photograph of the 7-degree half-angle circular cone model.

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The AFRL Mach-6 Ludwieg tube has been in operation since 2017 [19]; however, the velocity information available to date has been obtained from a traditional pressure-based pitot tube measurement device. Non-intrusive high-speed velocity measurements are desired for validating the CFD-computed velocity profile in the freestream and boundary-layer conditions. Furthermore, the stagnation temperature, in addition to many other tunnel parameters, can be derived from the measured velocity. Direct velocity measurement, therefore, serves to reduce the substantial uncertainty that exists due to computed flow conditions in hypersonic experiments [20,21].

(b) Experimental Setup for 100 kHz PLEET measurement system

A schematic diagram of the ps-burst-mode-laser-based PLEET system is shown in Fig. 2. The ps burst-mode laser has been discussed in detail in [22], hence only a brief description will be provided here. A fiber-based Mach-Zehnder interferometer generates 100 ps laser pulses which operate with a variable repetition rate (10–1000 kHz) at 1064 nm serves as the master oscillator of the burst-mode laser. The oscillator is coupled through a single-mode fiber and a fiber-coupled acousto-optic modulator (AOM) to increase the contrast ratio between the pulse and background. The pulse sequence is amplified to ∼10 nJ/pulse in a single-mode fiber amplifier. An additional electro-optic modulator (EOM) is applied for further minimizing amplified spontaneous emission (ASE) and also for controlling burst uniformity. The modified burst sequence is then amplified by a chain of Nd: YAG amplifiers. The final laser output could reach approximately 200 mJ/pulse at 1064 nm with 100-kHz rate operation.

 figure: Fig. 2.

Fig. 2. A schematic diagram for the PLEET experimental setup in ARFL Mach-6 Ludwieg Tube.

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The laser beam diameter is expanded to approximately 25 mm by a 3x telescope and then focused onto the probe volume using a spherical plano-convex lens with F = +750 mm. A high-speed camera (Photron, SA-Z) coupled with an external two-stage intensifier (LaVision, HS-IRO) was used to track the long-lived fluorescence from the N2. The emission was collected with a Nikon 85 mm f/1.8 lens. The camera was operated at 200 kHz to track the fluorescence signal displacement for the determination of flow velocities. The distance between the camera lens and the measurement volume is approximately 850 mm. To spatially calibrate the PLEET displacement measurements, a target pattern (dot card) was used. The calibration plane that was determined to have the highest degree of focus (inferred from the size of the individual dots on the target pattern) was selected and used to calibrate the measured displacements. The AFRL Ludwieg tube has three optical doors, thus we are able to keep the optical door of the imaging side close during the entire measurement campaign and hence eliminate the imaging calibration uncertainty issues. The calibration target was placed in the tunnel through the other side of the optical door. The image resolution is approximately 206 µm/pixel.

3. Time-resolved velocity measurements

A proof-of-principle demonstration of velocimetry measurements using 100 kHz PLEET was conducted in a Mach-6.14 wind tunnel with freestream air and nitrogen. Freestream flow velocities are measured upstream of an aerodynamic model. Measurements are also made downstream of the model’s shockwave. In all the cases, the 1064 nm laser pulse energy used for 100 kHz PLEET was ∼200 mJ/pulse (100-ps-duration pulse). Over the entire burst, the average pulse energy is ∼200 mJ/pulse measured at the test section inside the test chamber.

(a) Free-stream velocity measurements:

Figure 3 shows an example of single-shot PLEET velocimetry-images of the Mach 6.14 air and nitrogen freestream flows. The stagnation pressures for air and nitrogen flows are 300 psi and 250 psi, respectively. The corresponding static pressures in Mach 6.14 flow for air and nitrogen are ∼1.3 kPa (10 torr) and ∼1 kPa (8 torr), respectively. For the current experimental setup and laser pulse energies, the PLEET signal can be obtained at an even lower static pressure ∼5 torr for Mach-6.14 nitrogen flows. We did not test PLEET detection capability below the static pressure of 666 Pa (∼5 torr) [stagnation pressure of ∼1.17 MPa (170 psi)]. The Mach-6.14 flow was flowing from left to right. Measurements were conducted at 200 kHz, i.e., 5 µs between two consecutive images, although the laser was operating at 100 kHz. The camera intensifier gate was 500 ns with a ∼50% gain. A shorter gate with a higher gain would provide a narrower PLEET line to achieve higher measurement fidelity. However, because of the 100 ns jitter in the detection system, we used a wider gate time to ensure full signal collection. For the first image, the intensifier gate was 2 µs after the laser excitation, and the second intensifier gate was 7 µs after the laser excitation. The shape of the nitrogen-fluorescence signal shown in Fig. 3 is an approximately 9 mm line rather than a point because of the long focal-length of the lens that was used for this experiment. At the early time delay (t=2 µs), the signal-to-noise ratio (SNR) for air and nitrogen is approximately 60:1 and 58:1, respectively. After 5 µs time delay, SNR for air and nitrogen is approximately 10:1 and 25:1, respectively. It should be noted that the brightness of each image in Fig. 3 is adjusted so that the images are easy to see. By measuring the displacement along the X directions (i.e., freestream flow direction) between two consecutive images, free-steam flow velocity can be calculated. Because PLEET signal lifetime in air is relatively short (approximately 2µs, fluorescence is rapidly quenched by oxygen) as compared to that in pure nitrogen (typically approximately 20 µs), only one displacement for each laser shot was observed in Fig. 3(a) for air. However, a few PLEET signal lines are observed, as shown in Fig. 3(b), when pure nitrogen is used as the flow medium.

 figure: Fig. 3.

Fig. 3. Time-resolved PLEET images with a 100 kHz laser repetition rate and 200 kHz camera imaging rate for Mach-6.14 freestream flow. (a) Airflow freestream case with static pressure of approximately 1.3 kPa (10 torr). (b) Nitrogen flow freestream case with static pressure of approximately 1 kPa (8 torr). The red, green, and orange dashed circles illustrate the PLEET signal movements in time. The brightness of each image was adjusted for easy visibility.

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Analysis of the velocity measurements for the Mach-6.14 air and Mach-6.14 nitrogen flows employing 100 kHz PLEET is shown in Fig. 4, which is based on the PLEET images shown in Fig. 3. For each point, the accurate determination of the center of the PLEET signal in the X-direction was determined by the Gaussian fitting with MATLAB [23]. An example of the determination of horizontal center of plasma emission (along the X axis) via the Gaussian fitting is illustrated in Fig. 6. Then we averaged those values over the entire 9-mm line (along the Y axis) to get the center position of the florescence line. Although the maximum burst duration was 10 ms, most of measurements in the current experiment were performed at maximum output (near the threshold energy) with shorter burst duration 1.5 ms to avoid damaging the laser, optics, and optical window. For both air and nitrogen gases, the flow velocity (from position 1→ 2) is 916 m/s and 903 m/s, respectively. The measurement uncertainty (i.e., detection precision + intrinsic turbulent flow fluctuation) of air and nitrogen flow is approximately 1.7% and 1%, respectively. The measurement uncertainty in the hypersonic flow has resulted from intrinsic uncertainty from detection (e.g., image noise, SNR, laser fluctuation, etc.) and turbulence in hypersonic flows. Since the turbulence level in both cases should be similar, the increased uncertainty is believed to come from the detection system. The observed relative higher uncertainty in the air measurement could result from lower SNR at a longer time delay. The nitrogen PLEET signal is higher than the air PLEET signal due to reduced collisional quenching from the absence of oxygen [13,17,18]. Velocity data are presented for nitrogen flow at position 1 (2 µs after the laser pulse) and position 2 (7 µs after the laser pulse) shown in Fig. 4(b1) and Fig. 4(b2), respectively. The acquired mean velocities from the two locations are nearly the same (< 1% discrepancy). However, the measured velocity varies more at position 2 as compared to position 1. The observed larger uncertainties could result from the relatively lower SNR at later measurement time (SNR drops approximately a factor of 2).

 figure: Fig. 4.

Fig. 4. Measured velocity variation for (a) freestream air flow and (b) freestream nitrogen flow at 100 kHz rate. Velocity at two different positions were measured for nitrogen flow case. The static pressure for air and nitrogen flow case were ∼1.3 kPa (10 torr) and ∼1 kPa (8 torr), respectively. The Mach number for both cases is 6.14.

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Utilizing compressible flow theory, the calculated velocity for the air case is 904 m/s, which is very close to the measured velocity of 916 m/s. The discrepancy is within the measurement uncertainty. By using the experimental measurement, the previously-measured Mach number, and compressible flow theory, the instantaneous stagnation temperature was found to be approximately 460K.

(b) Velocity measurements upstream and downstream of the shock wave:

PLEET velocimetry with a blunt cone model was also performed for Mach-6.14 nitrogen flow, which is shown in Fig. 5. The model is a 7-degree half-angle blunt cone with a hemisphere tip and the radius of the tip is 5 mm. The laser line was set at 1.5 mm upstream of the model tip to avoid damaging the model from the intense ps laser beam. During wind tunnel operation, oftentimes the model position might slightly change due to tunnel vibration, thus this increases the difficulty to place the ps laser beam very close to the model surface. To avoid camera saturation by strong plasma emission, the first image was recorded 2 µs after the laser excitation. The shape of the nitrogen-PLEET signal shown in Fig. 6 is approximately a 9 mm line. The red, green, and orange dashed circles illustrate the PLEET signal line movements with the progression of time. The PLEET signal shows a curved line in the second image which indicates the varying velocity profile. Here, we want to point out that the brightness of each image in Fig. 5 is adjusted for easy-to-see presentation purposes. The PLEET line intensity is reduced by approximately a factor of two 5 µs after the first image (i.e., 0 µs) due to natural fluorescence lifetime and collisional quenching. We also performed PLEET measurements with a blunt cone model for Mach 6.14 air flow. However, we found that the signal quality is poor downstream of the shock wave in the air flow because of higher collisional quenching (fluorescence is rapidly quenched by high density oxygen) as compared to the nitrogen flow case. The resultant low SNR (∼3:1) causes high velocity measurement uncertainty and hence we didn’t present the result in the current paper.

 figure: Fig. 5.

Fig. 5. Time-resolved PLEET images with 100 kHz laser repetition rate and 200 kHz camera imaging rate for Mach-6.14 nitrogen flow with a 7-degree half-angle cylindrical cone model. The stagnation pressure is ∼1.7 MPa (250 psi). The brightness of each image was adjusted for easy visibility.

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Figure 6 shows the quantitative velocity and their fluctuations at three different locations. The velocity was derived from point-to-point (from Gaussian fitting peak in each row) displacement. At 0 µs, Pos#1 the peak PLEET signal is slightly saturated. By employing Gaussian fitting, center position of the peak PLEET signal can be still precisely determined. Velocities at Pos#1 and Pos#2 are approximately the measured freestream velocity as shown in Fig. 3(b1), which indicates that the location is outside the shockwave. A significantly lower velocity was observed at Pos#3, which is located at approximately 3 mm above the model surface. Based on the CFD simulation, as shown in Fig. 7, this location is downstream of the bow shockwave and close to the boundary layer. Downstream of the bow shock, in the vicinity of the area where the PLEET line first intersects the shock, the flow has lower velocity (by 150 m/s), as well as higher gas temperature (by 120 K or about 220%) and density (by 0.12 kg/m3 or about 380%). These conditions lead to higher collisional quenching, leading to lower SNR), resulting in the higher velocity fluctuation in Pos#3. Diffusion also leads to a thicker PLEET signal line and induces lower SNR.

 figure: Fig. 6.

Fig. 6. Measured velocity variation for Mach-6.14 Nitrogen near a 7-degree half-angle blunt cone model. Velocities at three different positions as shown in (a) were measured. (b) Measured velocity fluctuations at 100 kHz rate. The Gaussian fit for determination of line center (along X axis) is illustrated for PLEET signal at Pos #1 and Pos #3.

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(c) Comparison with computational fluid dynamics simulation:

 figure: Fig. 7.

Fig. 7. Comparison of experimental measured PLEET fluorescent line movement and CFD calculation. (a) Representative nitrogen PLEET line displacement for both experiment (single-shot) and theory; (b) experimentally measured velocity profile (single-shot) versus CFD simulation. Contour lines demarcate every 20 m/s in velocity.

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The mean flow over the cone is computed with the reacting, axisymmetric Navier-Stokes equations with a structured grid over a 7-degree half angle cone with a spherical nose bluntness of radius 5.08 mm, using a version of the NASA Data Parallel-Line Relaxation (DPLR) code [24] which has been extensively used to analyze previous experiments performed with the same cone [25]. The inflow conditions for the simulation were matched to the experiment for comparison: pure nitrogen with freestream M = 6.14, temperature, T = 53.96 K, and density ρ = 0.0428 kg/m3. The 360 by 360 cell grid is clustered at the wall and at the nose to capture the gradients at these locations. The nondimensional wall distance y+ for the grid, extracted from the DPLR solution for each case, is everywhere less than unity, where y+ is used as a measure of local grid quality at the wall in the wall-normal direction. The wall boundary condition is isothermal at 297 K.

Quantitative line velocity profiles are also obtained from the PLEET images from Fig. 5 using a MATLAB -based least-squares fitting routine, similar to that used in Ref. [23]. The illustrative results and their comparison with the PLEET fluorescent line movement and velocity profile calculated from CFD calculations are shown in Fig. 7. The CFD-simulated PLEET lines were synthesized by creating a vertical tracer array of 1501 points between y = 6 mm and y = 16 mm. These points are then advanced through the CFD solution using the local computed velocity components Vx and Vy, with a time step of 1 ns. Figure 7(a) records the position of the tracer line every 5000 time steps (i.e. every 5 µs), together with PLEET line movement recorded every 5 µs. The lifetime of nitrogen fluorescence under Mach-6.14 condition [static pressure ∼ 1 kPa (∼8 torr)] is found to be approximately 20 µs; thus, the movement of a single PLEET line at 5 different locations is observed in a single test, as shown in Fig. 7(a). Experimental PLEET velocity is averaged over 4.5 mm distance during 5 µs travel time while the CFD spatial resolution is significantly higher (grid spacing between points in the X-direction ranging from 0.02 mm to 0.5 mm in the region of the PLEET lines in Fig. 7(b), due to clustering near the nose). Here, the PLEET line movement shows the single component of the flow velocity Vx. Although there is significant Vy close to the model tip, the current setup cannot determine the Vy component. The local flow velocity component Vx, which is parallel to the principal flow direction, is shown in Fig. 7(b). As shown in Fig. 7(a), the experimentally measured movement of the PLEET fluorescent line agreed well with the CFD calculation upstream of the shockwave. Behind the bow shock, the discrepancy between the experimental measurement and CFD calculation is larger.

This effect may be attributed to the lower SNR of the fluorescent line behind the bow shock, making the measurement accuracy and uncertainty worse. The PLEET signal was also quenched faster behind the bow shock regime because of higher density. However, most of the experimentally measured velocity profiles are comparable to the contour velocity profiles calculated by CFD as shown in Fig, 7(b), except a few inside the shock layer. We believe that an additional contributing factor is the uncertainty of small cone model attack angle (may result from non-zero angle of attack (AOA)). The cone AoA was measured with a digital protractor, but the results are consistent with a slight nose up orientation, which causes the bow shock to move away from the model surface. Thus, the PLEET lines behind the bow shock may propagate through the slower flow region and hence causes higher bending as compared to the theoretical calculation based on axisymmetric computation. Furthermore, the experimentally derived velocity value is based on the horizontal-only movement of the line, which is not perfectly accurate because the line movement trajectory is not limited to horizontal motion. For example, some portion of the line moves initially in a horizontal direction through the high-density area, and then moves up as the streamlines curve, which results in lower calculated experimental velocity. To reduce this measurement uncertainty, 2D PLEET, tags written into a fluid flow with a laser grid and imaged at discrete times, could be applied. Such measurement was recently demonstrated by Ramsey and Pitz [27] and showed the better measurement accuracy can be achieved by knowing the geometry of laser written tag grids in MTV.

Some systematic error could be created in the PLEET measurement due to the buoyancy force acting on laser-heated gas in the vertical direction. This potential velocity bias is estimated, following the measured gas temperature rise during PLEET measurement from Ref. [17] using isentropic assumptions listed in Eq. (1):

$${V_b} = \frac{{{\rho _a} - {\rho _h}}}{{{\rho _h}}}gt,$$
where ρa is the ambient test flow density, ρh is the laser heated flow density, g is the acceleration due to gravity, and t is time. In the Ref. [17], Jiang et al. used a 8-mm diameter beam with 20 mJ/pulse and focused it with a F=+100 mm lens for plasma generation. In such condition, the laser fluence at the focal point is ∼0.0028J/cm2 and the resultant heated gas temperature is ∼550 K. For the current work, we used a 20-mm diameter beam with ∼200 mJ/pulse and focused it with a F=750 mm lens for plasma generation. The corresponding laser fluence at the focal point is ∼0.0031J/cm2. Thus, the laser fluence for both cases are similar. Therefore, for the present experiment, the local gas temperature after the laser pulse could be estimated to be 550 K. The temperature of the Ludwieg Tube freestream is about 60 K. The induced bias velocity Vb in the vertical direction, for a time interval of 5 µs, is therefore 0.4 mm/s, which is significantly less than the overall wind tunnel velocity (∼0.04% of the freestream velocity). Systematic error in the horizontal direction is also potentially created as the laser-heated gas locally expands and is processed by passing through the oblique shockwave attached to the cone. This is an inherently three-dimensional process which is not amenable to the two-dimensional axisymmetric computations used in the present experiments, but as the effect also relies upon the changing density of the gas due to temperature, it is expected to be on the order of the systematic error due to buoyancy estimated above. Additionally, the laser heating may create a weak shock wave which could potentially affect the hypersonic flow characteristics. However, recent FLEET results in a high-Mach hypersonic wind tunnel [14] found that the laser heating effect is negligible.

4. Summary

In conclusion, PLEET-based velocimetry at repetition rates as high as 100 kHz was successfully demonstrated in a Mach-6 Ludwieg tube, with free stream static pressures of ∼1.3 kPa (10 torr) and ∼1 kPa (8 torr), for air and nitrogen flows, respectively. A ps burst-mode laser system was used to generate the required high-energy 100-ps-duration, 1064 nm laser pulses at a repetition rate of 100 kHz. Proof-of-concept 100 kHz PLEET image sequences were obtained for freestream and boundary-layer conditions. The measured velocities in the freestream were found to be approximately 904 ± 9.8 m/s and 916 ± 16.4 m/s for nitrogen and airflows, respectively. The measured velocity agreed well with the calculated velocity, approximately 904 m/s, for airflows. Similarly, the measured velocity profiles at multiple locations near the boundary-layer with a 7-degree half-angle cone model are also comparable with CFD calculations. Our results show significant promise for the high-repetition-rate PLEET technique to be used for higher Mach number flow measurements. The velocity profiles obtained will be used to reduce the uncertainty in hypersonic wind tunnel testing flow conditions, and this uncertainty reduction will be published elsewhere in a forum focused on aerodynamic ground testing facilities. The ps-burst-mode laser-based PLEET detection enables orders-of-magnitude more rapid acquisition of data over a small time window as compared to recently developed FLEET velocimetry [14] (1 kHz rate) and KTV (at 10 Hz rate) [4] techniques. Although the diminished field of view (due to thick plasma line written by the intense ps laser and long-distance imaging) and single velocity component with a single detector restrict the precision of the PLEET velocimetry. Those problems can be improved by using shorter duration laser pulse (e.g., few ps pulse or sub ps pulse [26]) and using high magnification camera lenses. The Ps-burst-mode-laser-based PLEET velocimetry technique has the potential to provide a measurement speed of 100 kHz or higher, which will allow the tracking of turbulent dynamics in hypersonic flows and the collection of large data sets in a short tunnel operation time.

Funding

Air Force Research Laboratory (FA8650-15-D-2518, FA9101-19-P-0021).

Acknowledgements

Approved for public release, distribution unlimited (# 88ABW-2019-5854l; MSC2019-0450).

Disclosures

The authors declare no conflicts of interest.

References

1. I. A. Leyva, “The relentless pursuit of hypersonic flight,” Phys. Today 70(11), 30–36 (2017). [CrossRef]  

2. P. T. Harsha, L. C. Keel, A. Castrogiovanni, and R. T. Sherrill. “X-43A Vehicle Design and Manufacture,” AIAA 2005-3334. Retrieved: August (2011).

3. D. S. Dolling, “Fluctuating Loads in Shock Wave/Turbulent Boundary Layer Interaction; Tutorial and Update,” AIAA-93-0284 (1993).

4. M. A. Mustafa, N. J. Parziale, M. S. Smith, and E. C. Marineau, “Noninstrusive freestream velocity measurement in large-scale hypersonic wind tunnel,” AIAA J. 55(10), 3611–3616 (2017). [CrossRef]  

5. J. S. Jewell and R. Kimmel, “Boundary layer stability analysis for Stetson’s Mach 6 blunt cone experiments,” J. Spacecr. Rockets 54(1), 258–265 (2017). [CrossRef]  

6. R. J. Andrian, “Twenty years of particle image velocimetry,” Exp. Fluids 39(2), 159–169 (2005). [CrossRef]  

7. P. S. Hsu, S. Roy, N. Jiang, and J. R. Gord, “Large-aperture, tapered fiber–coupled, 10-kHz particle-image velocimetry,” Opt. Express 21(3), 3617 (2013). [CrossRef]  

8. T. Kirmse, J. Agocs, A. Schroder, J. M. Schramm, S. Kari, and K. Hannemann, “Application of particle image velocimetry and the background-oriented schlieren technique in the high enthalpy shock tunnel Gottingen,” Shock Waves 21(3), 233–241 (2011). [CrossRef]  

9. B. F. Bathel, P. M. Danehy, J. A. Inman, and S. B. Jones, “Velocity profile measurements in hypersonic flow using sequentially imaged fluorescence-based molecular tagging,” AIAA J. 49(9), 1883–1896 (2011). [CrossRef]  

10. R. L. McKenzie, “Measurement capabilities of planar Doppler velocimetry using pulsed lasers,” Appl. Opt. 35(6), 948–964 (1996). [CrossRef]  

11. W. R. Lempert, N. Jiang, S. Sethuram, and M. Samimy, “Molecular tagging velocimetry measurements in supersonic microjets,” AIAA J. 40(6), 1065–1070 (2002). [CrossRef]  

12. R. J. Balla, “Iodine Tagging velocimetry in a Mach 10 Wake,” AIAA J. 51(7), 1783–1786 (2013). [CrossRef]  

13. J. B. Michael, M. R. Edwards, A. Dogariu, and R. B. Miles, “Femtosecond laser electronic excitation tagging for quantitative velocity imaging in air,” Appl. Opt. 50(26), 5158–5162 (2011). [CrossRef]  

14. L. E. Dogariu, A. Dogariu, R. B. Miles, M. S. Smith, and E. C. Marineau, “Non-intrusive hypersonic freestream and turbulent boundary-layer velocity measurements in AEDC Tunnel 9 using PLEET,” AIAA 2018-1769, AIAA Aerospace Sciences Meeting 8-12 January (2018).

15. P. D. Danehy, S. O. Byrne, F. P. Houwing, J. S. Fox, and D. R. Smith, “Flow-tagging velocimetry for hypersonic flows using fluorescence of nitric oxide,” AIAA J. 41(2), 263–271 (2003). [CrossRef]  

16. J. N. Forkey, N. D. Finkelstein, W. R. Lempert, and R. B. Miles, “Demonstration and Characterization of Filtered Rayleigh Scattering for Planar Velocity Measurements,” AIAA J. 34(3), 442–448 (1996). [CrossRef]  

17. N. Jiang, J. G. Mance, M. N. Slipchenko, J. J. Felver, H. U. Stauffer, T. Yi, P. M. Danehy, and S. Roy, “Seedless velocimetry at 100 kHz with picosecond-laser electronic-excitation tagging,” Opt. Lett. 42(2), 239–242 (2017). [CrossRef]  

18. R. A. Burns, P. M. Danehy, N. Jiang, M. N. Splichenko, J. Felver, and S. Roy, “Unseeded velocimetry in nitrogen for high-pressure cryogenic wind tunnels: Part II. Picosecond-laser tagging,” Meas. Sci. Technol. 29(11), 115203 (2018). [CrossRef]  

19. R. L. Kimmel, M. Borg, J. S. Jewell, K.-Y. Lam, R. Bowersox, and S. Fuchs, “AFRL Ludwieg Tube Initial Performance,” 55th AIAA Aerospace Sciences Meeting, AIAA 2017-1012 (2017).

20. J. S. Jewell, Boundary-Layer Transition on a Slender Cone in Hypervelocity Flow with Real Gas Effects. Ph.D. Thesis, California Institute of Technology, Pasadena, CA, 2014.

21. J. S. Jewell and J. E. Shepherd, “T5 Conditions Report: Shots 2526–2823,” GALCIT Report FM2014.002, California Institute of Technology, Pasadena, CA, 2014.

22. S. Roy, J. D. Miller, M. N. Slipchenko, P. S. Hsu, J. G. Mance, T. R. Meyer, and J. R. Gord, “100-ps-pulse-duration, 100-J burst-mode laser for kHz–MHz flow diagnostics,” Opt. Lett. 39(22), 6462–6465 (2014). [CrossRef]  

23. N. Jiang, M. Nishihara, and W. R. Lempert, “Quantitative NO2 molecular tagging velocimetry at 500 kHz frame rate,” Appl. Phys. Lett. 97(22), 221103 (2010). [CrossRef]  

24. M. J. Wright, G. V. Candler, and D. Bose, “Data-parallel line relaxation method for the Navier-Stokes equations,” AIAA J. 36(9), 1603–1609 (1998). [CrossRef]  

25. J. S. Jewell, R. E. Kennedy, S.J . Laurence, and R. L. Kimmel, “Transition on a Variable Bluntness 7-Degree Cone at High Reynolds Number,” AIAA SciTech 2018, January 2018, Kissimmee, FL. AIAA 2018-1822.

26. J. M. Fisher, M. E. Smyser, M. N. Slipchenko, S. Roy, and T. R. Meyer, “Burst-mode femtosecond laser electronic excitation ragging for kHz-MHz seedless velocimetry,” Opt. Lett. 45(2), 335–338 (2020). [CrossRef]  

27. M. C. Ramsey and R. W. Pitz, “Template matching for improved accuracy in molecular tagging velocimetry,” Exp. Fluids 51(3), 811–819 (2011). [CrossRef]  

References

  • View by:

  1. I. A. Leyva, “The relentless pursuit of hypersonic flight,” Phys. Today 70(11), 30–36 (2017).
    [Crossref]
  2. P. T. Harsha, L. C. Keel, A. Castrogiovanni, and R. T. Sherrill. “X-43A Vehicle Design and Manufacture,” AIAA 2005-3334. Retrieved: August (2011).
  3. D. S. Dolling, “Fluctuating Loads in Shock Wave/Turbulent Boundary Layer Interaction; Tutorial and Update,” AIAA-93-0284 (1993).
  4. M. A. Mustafa, N. J. Parziale, M. S. Smith, and E. C. Marineau, “Noninstrusive freestream velocity measurement in large-scale hypersonic wind tunnel,” AIAA J. 55(10), 3611–3616 (2017).
    [Crossref]
  5. J. S. Jewell and R. Kimmel, “Boundary layer stability analysis for Stetson’s Mach 6 blunt cone experiments,” J. Spacecr. Rockets 54(1), 258–265 (2017).
    [Crossref]
  6. R. J. Andrian, “Twenty years of particle image velocimetry,” Exp. Fluids 39(2), 159–169 (2005).
    [Crossref]
  7. P. S. Hsu, S. Roy, N. Jiang, and J. R. Gord, “Large-aperture, tapered fiber–coupled, 10-kHz particle-image velocimetry,” Opt. Express 21(3), 3617 (2013).
    [Crossref]
  8. T. Kirmse, J. Agocs, A. Schroder, J. M. Schramm, S. Kari, and K. Hannemann, “Application of particle image velocimetry and the background-oriented schlieren technique in the high enthalpy shock tunnel Gottingen,” Shock Waves 21(3), 233–241 (2011).
    [Crossref]
  9. B. F. Bathel, P. M. Danehy, J. A. Inman, and S. B. Jones, “Velocity profile measurements in hypersonic flow using sequentially imaged fluorescence-based molecular tagging,” AIAA J. 49(9), 1883–1896 (2011).
    [Crossref]
  10. R. L. McKenzie, “Measurement capabilities of planar Doppler velocimetry using pulsed lasers,” Appl. Opt. 35(6), 948–964 (1996).
    [Crossref]
  11. W. R. Lempert, N. Jiang, S. Sethuram, and M. Samimy, “Molecular tagging velocimetry measurements in supersonic microjets,” AIAA J. 40(6), 1065–1070 (2002).
    [Crossref]
  12. R. J. Balla, “Iodine Tagging velocimetry in a Mach 10 Wake,” AIAA J. 51(7), 1783–1786 (2013).
    [Crossref]
  13. J. B. Michael, M. R. Edwards, A. Dogariu, and R. B. Miles, “Femtosecond laser electronic excitation tagging for quantitative velocity imaging in air,” Appl. Opt. 50(26), 5158–5162 (2011).
    [Crossref]
  14. L. E. Dogariu, A. Dogariu, R. B. Miles, M. S. Smith, and E. C. Marineau, “Non-intrusive hypersonic freestream and turbulent boundary-layer velocity measurements in AEDC Tunnel 9 using PLEET,” AIAA 2018-1769, AIAA Aerospace Sciences Meeting 8-12 January (2018).
  15. P. D. Danehy, S. O. Byrne, F. P. Houwing, J. S. Fox, and D. R. Smith, “Flow-tagging velocimetry for hypersonic flows using fluorescence of nitric oxide,” AIAA J. 41(2), 263–271 (2003).
    [Crossref]
  16. J. N. Forkey, N. D. Finkelstein, W. R. Lempert, and R. B. Miles, “Demonstration and Characterization of Filtered Rayleigh Scattering for Planar Velocity Measurements,” AIAA J. 34(3), 442–448 (1996).
    [Crossref]
  17. N. Jiang, J. G. Mance, M. N. Slipchenko, J. J. Felver, H. U. Stauffer, T. Yi, P. M. Danehy, and S. Roy, “Seedless velocimetry at 100 kHz with picosecond-laser electronic-excitation tagging,” Opt. Lett. 42(2), 239–242 (2017).
    [Crossref]
  18. R. A. Burns, P. M. Danehy, N. Jiang, M. N. Splichenko, J. Felver, and S. Roy, “Unseeded velocimetry in nitrogen for high-pressure cryogenic wind tunnels: Part II. Picosecond-laser tagging,” Meas. Sci. Technol. 29(11), 115203 (2018).
    [Crossref]
  19. R. L. Kimmel, M. Borg, J. S. Jewell, K.-Y. Lam, R. Bowersox, and S. Fuchs, “AFRL Ludwieg Tube Initial Performance,” 55th AIAA Aerospace Sciences Meeting, AIAA 2017-1012 (2017).
  20. J. S. Jewell, Boundary-Layer Transition on a Slender Cone in Hypervelocity Flow with Real Gas Effects. Ph.D. Thesis, California Institute of Technology, Pasadena, CA, 2014.
  21. J. S. Jewell and J. E. Shepherd, “T5 Conditions Report: Shots 2526–2823,” GALCIT Report FM2014.002, California Institute of Technology, Pasadena, CA, 2014.
  22. S. Roy, J. D. Miller, M. N. Slipchenko, P. S. Hsu, J. G. Mance, T. R. Meyer, and J. R. Gord, “100-ps-pulse-duration, 100-J burst-mode laser for kHz–MHz flow diagnostics,” Opt. Lett. 39(22), 6462–6465 (2014).
    [Crossref]
  23. N. Jiang, M. Nishihara, and W. R. Lempert, “Quantitative NO2 molecular tagging velocimetry at 500 kHz frame rate,” Appl. Phys. Lett. 97(22), 221103 (2010).
    [Crossref]
  24. M. J. Wright, G. V. Candler, and D. Bose, “Data-parallel line relaxation method for the Navier-Stokes equations,” AIAA J. 36(9), 1603–1609 (1998).
    [Crossref]
  25. J. S. Jewell, R. E. Kennedy, S.J . Laurence, and R. L. Kimmel, “Transition on a Variable Bluntness 7-Degree Cone at High Reynolds Number,” AIAA SciTech 2018, January 2018, Kissimmee, FL. AIAA 2018-1822.
  26. J. M. Fisher, M. E. Smyser, M. N. Slipchenko, S. Roy, and T. R. Meyer, “Burst-mode femtosecond laser electronic excitation ragging for kHz-MHz seedless velocimetry,” Opt. Lett. 45(2), 335–338 (2020).
    [Crossref]
  27. M. C. Ramsey and R. W. Pitz, “Template matching for improved accuracy in molecular tagging velocimetry,” Exp. Fluids 51(3), 811–819 (2011).
    [Crossref]

2020 (1)

2018 (1)

R. A. Burns, P. M. Danehy, N. Jiang, M. N. Splichenko, J. Felver, and S. Roy, “Unseeded velocimetry in nitrogen for high-pressure cryogenic wind tunnels: Part II. Picosecond-laser tagging,” Meas. Sci. Technol. 29(11), 115203 (2018).
[Crossref]

2017 (4)

I. A. Leyva, “The relentless pursuit of hypersonic flight,” Phys. Today 70(11), 30–36 (2017).
[Crossref]

M. A. Mustafa, N. J. Parziale, M. S. Smith, and E. C. Marineau, “Noninstrusive freestream velocity measurement in large-scale hypersonic wind tunnel,” AIAA J. 55(10), 3611–3616 (2017).
[Crossref]

J. S. Jewell and R. Kimmel, “Boundary layer stability analysis for Stetson’s Mach 6 blunt cone experiments,” J. Spacecr. Rockets 54(1), 258–265 (2017).
[Crossref]

N. Jiang, J. G. Mance, M. N. Slipchenko, J. J. Felver, H. U. Stauffer, T. Yi, P. M. Danehy, and S. Roy, “Seedless velocimetry at 100 kHz with picosecond-laser electronic-excitation tagging,” Opt. Lett. 42(2), 239–242 (2017).
[Crossref]

2014 (1)

2013 (2)

2011 (4)

T. Kirmse, J. Agocs, A. Schroder, J. M. Schramm, S. Kari, and K. Hannemann, “Application of particle image velocimetry and the background-oriented schlieren technique in the high enthalpy shock tunnel Gottingen,” Shock Waves 21(3), 233–241 (2011).
[Crossref]

B. F. Bathel, P. M. Danehy, J. A. Inman, and S. B. Jones, “Velocity profile measurements in hypersonic flow using sequentially imaged fluorescence-based molecular tagging,” AIAA J. 49(9), 1883–1896 (2011).
[Crossref]

J. B. Michael, M. R. Edwards, A. Dogariu, and R. B. Miles, “Femtosecond laser electronic excitation tagging for quantitative velocity imaging in air,” Appl. Opt. 50(26), 5158–5162 (2011).
[Crossref]

M. C. Ramsey and R. W. Pitz, “Template matching for improved accuracy in molecular tagging velocimetry,” Exp. Fluids 51(3), 811–819 (2011).
[Crossref]

2010 (1)

N. Jiang, M. Nishihara, and W. R. Lempert, “Quantitative NO2 molecular tagging velocimetry at 500 kHz frame rate,” Appl. Phys. Lett. 97(22), 221103 (2010).
[Crossref]

2005 (1)

R. J. Andrian, “Twenty years of particle image velocimetry,” Exp. Fluids 39(2), 159–169 (2005).
[Crossref]

2003 (1)

P. D. Danehy, S. O. Byrne, F. P. Houwing, J. S. Fox, and D. R. Smith, “Flow-tagging velocimetry for hypersonic flows using fluorescence of nitric oxide,” AIAA J. 41(2), 263–271 (2003).
[Crossref]

2002 (1)

W. R. Lempert, N. Jiang, S. Sethuram, and M. Samimy, “Molecular tagging velocimetry measurements in supersonic microjets,” AIAA J. 40(6), 1065–1070 (2002).
[Crossref]

1998 (1)

M. J. Wright, G. V. Candler, and D. Bose, “Data-parallel line relaxation method for the Navier-Stokes equations,” AIAA J. 36(9), 1603–1609 (1998).
[Crossref]

1996 (2)

J. N. Forkey, N. D. Finkelstein, W. R. Lempert, and R. B. Miles, “Demonstration and Characterization of Filtered Rayleigh Scattering for Planar Velocity Measurements,” AIAA J. 34(3), 442–448 (1996).
[Crossref]

R. L. McKenzie, “Measurement capabilities of planar Doppler velocimetry using pulsed lasers,” Appl. Opt. 35(6), 948–964 (1996).
[Crossref]

Agocs, J.

T. Kirmse, J. Agocs, A. Schroder, J. M. Schramm, S. Kari, and K. Hannemann, “Application of particle image velocimetry and the background-oriented schlieren technique in the high enthalpy shock tunnel Gottingen,” Shock Waves 21(3), 233–241 (2011).
[Crossref]

Andrian, R. J.

R. J. Andrian, “Twenty years of particle image velocimetry,” Exp. Fluids 39(2), 159–169 (2005).
[Crossref]

Balla, R. J.

R. J. Balla, “Iodine Tagging velocimetry in a Mach 10 Wake,” AIAA J. 51(7), 1783–1786 (2013).
[Crossref]

Bathel, B. F.

B. F. Bathel, P. M. Danehy, J. A. Inman, and S. B. Jones, “Velocity profile measurements in hypersonic flow using sequentially imaged fluorescence-based molecular tagging,” AIAA J. 49(9), 1883–1896 (2011).
[Crossref]

Borg, M.

R. L. Kimmel, M. Borg, J. S. Jewell, K.-Y. Lam, R. Bowersox, and S. Fuchs, “AFRL Ludwieg Tube Initial Performance,” 55th AIAA Aerospace Sciences Meeting, AIAA 2017-1012 (2017).

Bose, D.

M. J. Wright, G. V. Candler, and D. Bose, “Data-parallel line relaxation method for the Navier-Stokes equations,” AIAA J. 36(9), 1603–1609 (1998).
[Crossref]

Bowersox, R.

R. L. Kimmel, M. Borg, J. S. Jewell, K.-Y. Lam, R. Bowersox, and S. Fuchs, “AFRL Ludwieg Tube Initial Performance,” 55th AIAA Aerospace Sciences Meeting, AIAA 2017-1012 (2017).

Burns, R. A.

R. A. Burns, P. M. Danehy, N. Jiang, M. N. Splichenko, J. Felver, and S. Roy, “Unseeded velocimetry in nitrogen for high-pressure cryogenic wind tunnels: Part II. Picosecond-laser tagging,” Meas. Sci. Technol. 29(11), 115203 (2018).
[Crossref]

Byrne, S. O.

P. D. Danehy, S. O. Byrne, F. P. Houwing, J. S. Fox, and D. R. Smith, “Flow-tagging velocimetry for hypersonic flows using fluorescence of nitric oxide,” AIAA J. 41(2), 263–271 (2003).
[Crossref]

Candler, G. V.

M. J. Wright, G. V. Candler, and D. Bose, “Data-parallel line relaxation method for the Navier-Stokes equations,” AIAA J. 36(9), 1603–1609 (1998).
[Crossref]

Castrogiovanni, A.

P. T. Harsha, L. C. Keel, A. Castrogiovanni, and R. T. Sherrill. “X-43A Vehicle Design and Manufacture,” AIAA 2005-3334. Retrieved: August (2011).

Danehy, P. D.

P. D. Danehy, S. O. Byrne, F. P. Houwing, J. S. Fox, and D. R. Smith, “Flow-tagging velocimetry for hypersonic flows using fluorescence of nitric oxide,” AIAA J. 41(2), 263–271 (2003).
[Crossref]

Danehy, P. M.

R. A. Burns, P. M. Danehy, N. Jiang, M. N. Splichenko, J. Felver, and S. Roy, “Unseeded velocimetry in nitrogen for high-pressure cryogenic wind tunnels: Part II. Picosecond-laser tagging,” Meas. Sci. Technol. 29(11), 115203 (2018).
[Crossref]

N. Jiang, J. G. Mance, M. N. Slipchenko, J. J. Felver, H. U. Stauffer, T. Yi, P. M. Danehy, and S. Roy, “Seedless velocimetry at 100 kHz with picosecond-laser electronic-excitation tagging,” Opt. Lett. 42(2), 239–242 (2017).
[Crossref]

B. F. Bathel, P. M. Danehy, J. A. Inman, and S. B. Jones, “Velocity profile measurements in hypersonic flow using sequentially imaged fluorescence-based molecular tagging,” AIAA J. 49(9), 1883–1896 (2011).
[Crossref]

Dogariu, A.

J. B. Michael, M. R. Edwards, A. Dogariu, and R. B. Miles, “Femtosecond laser electronic excitation tagging for quantitative velocity imaging in air,” Appl. Opt. 50(26), 5158–5162 (2011).
[Crossref]

L. E. Dogariu, A. Dogariu, R. B. Miles, M. S. Smith, and E. C. Marineau, “Non-intrusive hypersonic freestream and turbulent boundary-layer velocity measurements in AEDC Tunnel 9 using PLEET,” AIAA 2018-1769, AIAA Aerospace Sciences Meeting 8-12 January (2018).

Dogariu, L. E.

L. E. Dogariu, A. Dogariu, R. B. Miles, M. S. Smith, and E. C. Marineau, “Non-intrusive hypersonic freestream and turbulent boundary-layer velocity measurements in AEDC Tunnel 9 using PLEET,” AIAA 2018-1769, AIAA Aerospace Sciences Meeting 8-12 January (2018).

Dolling, D. S.

D. S. Dolling, “Fluctuating Loads in Shock Wave/Turbulent Boundary Layer Interaction; Tutorial and Update,” AIAA-93-0284 (1993).

Edwards, M. R.

Felver, J.

R. A. Burns, P. M. Danehy, N. Jiang, M. N. Splichenko, J. Felver, and S. Roy, “Unseeded velocimetry in nitrogen for high-pressure cryogenic wind tunnels: Part II. Picosecond-laser tagging,” Meas. Sci. Technol. 29(11), 115203 (2018).
[Crossref]

Felver, J. J.

Finkelstein, N. D.

J. N. Forkey, N. D. Finkelstein, W. R. Lempert, and R. B. Miles, “Demonstration and Characterization of Filtered Rayleigh Scattering for Planar Velocity Measurements,” AIAA J. 34(3), 442–448 (1996).
[Crossref]

Fisher, J. M.

Forkey, J. N.

J. N. Forkey, N. D. Finkelstein, W. R. Lempert, and R. B. Miles, “Demonstration and Characterization of Filtered Rayleigh Scattering for Planar Velocity Measurements,” AIAA J. 34(3), 442–448 (1996).
[Crossref]

Fox, J. S.

P. D. Danehy, S. O. Byrne, F. P. Houwing, J. S. Fox, and D. R. Smith, “Flow-tagging velocimetry for hypersonic flows using fluorescence of nitric oxide,” AIAA J. 41(2), 263–271 (2003).
[Crossref]

Fuchs, S.

R. L. Kimmel, M. Borg, J. S. Jewell, K.-Y. Lam, R. Bowersox, and S. Fuchs, “AFRL Ludwieg Tube Initial Performance,” 55th AIAA Aerospace Sciences Meeting, AIAA 2017-1012 (2017).

Gord, J. R.

Hannemann, K.

T. Kirmse, J. Agocs, A. Schroder, J. M. Schramm, S. Kari, and K. Hannemann, “Application of particle image velocimetry and the background-oriented schlieren technique in the high enthalpy shock tunnel Gottingen,” Shock Waves 21(3), 233–241 (2011).
[Crossref]

Harsha, P. T.

P. T. Harsha, L. C. Keel, A. Castrogiovanni, and R. T. Sherrill. “X-43A Vehicle Design and Manufacture,” AIAA 2005-3334. Retrieved: August (2011).

Houwing, F. P.

P. D. Danehy, S. O. Byrne, F. P. Houwing, J. S. Fox, and D. R. Smith, “Flow-tagging velocimetry for hypersonic flows using fluorescence of nitric oxide,” AIAA J. 41(2), 263–271 (2003).
[Crossref]

Hsu, P. S.

Inman, J. A.

B. F. Bathel, P. M. Danehy, J. A. Inman, and S. B. Jones, “Velocity profile measurements in hypersonic flow using sequentially imaged fluorescence-based molecular tagging,” AIAA J. 49(9), 1883–1896 (2011).
[Crossref]

Jewell, J. S.

J. S. Jewell and R. Kimmel, “Boundary layer stability analysis for Stetson’s Mach 6 blunt cone experiments,” J. Spacecr. Rockets 54(1), 258–265 (2017).
[Crossref]

J. S. Jewell, Boundary-Layer Transition on a Slender Cone in Hypervelocity Flow with Real Gas Effects. Ph.D. Thesis, California Institute of Technology, Pasadena, CA, 2014.

J. S. Jewell and J. E. Shepherd, “T5 Conditions Report: Shots 2526–2823,” GALCIT Report FM2014.002, California Institute of Technology, Pasadena, CA, 2014.

R. L. Kimmel, M. Borg, J. S. Jewell, K.-Y. Lam, R. Bowersox, and S. Fuchs, “AFRL Ludwieg Tube Initial Performance,” 55th AIAA Aerospace Sciences Meeting, AIAA 2017-1012 (2017).

J. S. Jewell, R. E. Kennedy, S.J . Laurence, and R. L. Kimmel, “Transition on a Variable Bluntness 7-Degree Cone at High Reynolds Number,” AIAA SciTech 2018, January 2018, Kissimmee, FL. AIAA 2018-1822.

Jiang, N.

R. A. Burns, P. M. Danehy, N. Jiang, M. N. Splichenko, J. Felver, and S. Roy, “Unseeded velocimetry in nitrogen for high-pressure cryogenic wind tunnels: Part II. Picosecond-laser tagging,” Meas. Sci. Technol. 29(11), 115203 (2018).
[Crossref]

N. Jiang, J. G. Mance, M. N. Slipchenko, J. J. Felver, H. U. Stauffer, T. Yi, P. M. Danehy, and S. Roy, “Seedless velocimetry at 100 kHz with picosecond-laser electronic-excitation tagging,” Opt. Lett. 42(2), 239–242 (2017).
[Crossref]

P. S. Hsu, S. Roy, N. Jiang, and J. R. Gord, “Large-aperture, tapered fiber–coupled, 10-kHz particle-image velocimetry,” Opt. Express 21(3), 3617 (2013).
[Crossref]

N. Jiang, M. Nishihara, and W. R. Lempert, “Quantitative NO2 molecular tagging velocimetry at 500 kHz frame rate,” Appl. Phys. Lett. 97(22), 221103 (2010).
[Crossref]

W. R. Lempert, N. Jiang, S. Sethuram, and M. Samimy, “Molecular tagging velocimetry measurements in supersonic microjets,” AIAA J. 40(6), 1065–1070 (2002).
[Crossref]

Jones, S. B.

B. F. Bathel, P. M. Danehy, J. A. Inman, and S. B. Jones, “Velocity profile measurements in hypersonic flow using sequentially imaged fluorescence-based molecular tagging,” AIAA J. 49(9), 1883–1896 (2011).
[Crossref]

Kari, S.

T. Kirmse, J. Agocs, A. Schroder, J. M. Schramm, S. Kari, and K. Hannemann, “Application of particle image velocimetry and the background-oriented schlieren technique in the high enthalpy shock tunnel Gottingen,” Shock Waves 21(3), 233–241 (2011).
[Crossref]

Keel, L. C.

P. T. Harsha, L. C. Keel, A. Castrogiovanni, and R. T. Sherrill. “X-43A Vehicle Design and Manufacture,” AIAA 2005-3334. Retrieved: August (2011).

Kennedy, R. E.

J. S. Jewell, R. E. Kennedy, S.J . Laurence, and R. L. Kimmel, “Transition on a Variable Bluntness 7-Degree Cone at High Reynolds Number,” AIAA SciTech 2018, January 2018, Kissimmee, FL. AIAA 2018-1822.

Kimmel, R.

J. S. Jewell and R. Kimmel, “Boundary layer stability analysis for Stetson’s Mach 6 blunt cone experiments,” J. Spacecr. Rockets 54(1), 258–265 (2017).
[Crossref]

Kimmel, R. L.

R. L. Kimmel, M. Borg, J. S. Jewell, K.-Y. Lam, R. Bowersox, and S. Fuchs, “AFRL Ludwieg Tube Initial Performance,” 55th AIAA Aerospace Sciences Meeting, AIAA 2017-1012 (2017).

J. S. Jewell, R. E. Kennedy, S.J . Laurence, and R. L. Kimmel, “Transition on a Variable Bluntness 7-Degree Cone at High Reynolds Number,” AIAA SciTech 2018, January 2018, Kissimmee, FL. AIAA 2018-1822.

Kirmse, T.

T. Kirmse, J. Agocs, A. Schroder, J. M. Schramm, S. Kari, and K. Hannemann, “Application of particle image velocimetry and the background-oriented schlieren technique in the high enthalpy shock tunnel Gottingen,” Shock Waves 21(3), 233–241 (2011).
[Crossref]

Lam, K.-Y.

R. L. Kimmel, M. Borg, J. S. Jewell, K.-Y. Lam, R. Bowersox, and S. Fuchs, “AFRL Ludwieg Tube Initial Performance,” 55th AIAA Aerospace Sciences Meeting, AIAA 2017-1012 (2017).

Laurence, S.J .

J. S. Jewell, R. E. Kennedy, S.J . Laurence, and R. L. Kimmel, “Transition on a Variable Bluntness 7-Degree Cone at High Reynolds Number,” AIAA SciTech 2018, January 2018, Kissimmee, FL. AIAA 2018-1822.

Lempert, W. R.

N. Jiang, M. Nishihara, and W. R. Lempert, “Quantitative NO2 molecular tagging velocimetry at 500 kHz frame rate,” Appl. Phys. Lett. 97(22), 221103 (2010).
[Crossref]

W. R. Lempert, N. Jiang, S. Sethuram, and M. Samimy, “Molecular tagging velocimetry measurements in supersonic microjets,” AIAA J. 40(6), 1065–1070 (2002).
[Crossref]

J. N. Forkey, N. D. Finkelstein, W. R. Lempert, and R. B. Miles, “Demonstration and Characterization of Filtered Rayleigh Scattering for Planar Velocity Measurements,” AIAA J. 34(3), 442–448 (1996).
[Crossref]

Leyva, I. A.

I. A. Leyva, “The relentless pursuit of hypersonic flight,” Phys. Today 70(11), 30–36 (2017).
[Crossref]

Mance, J. G.

Marineau, E. C.

M. A. Mustafa, N. J. Parziale, M. S. Smith, and E. C. Marineau, “Noninstrusive freestream velocity measurement in large-scale hypersonic wind tunnel,” AIAA J. 55(10), 3611–3616 (2017).
[Crossref]

L. E. Dogariu, A. Dogariu, R. B. Miles, M. S. Smith, and E. C. Marineau, “Non-intrusive hypersonic freestream and turbulent boundary-layer velocity measurements in AEDC Tunnel 9 using PLEET,” AIAA 2018-1769, AIAA Aerospace Sciences Meeting 8-12 January (2018).

McKenzie, R. L.

Meyer, T. R.

Michael, J. B.

Miles, R. B.

J. B. Michael, M. R. Edwards, A. Dogariu, and R. B. Miles, “Femtosecond laser electronic excitation tagging for quantitative velocity imaging in air,” Appl. Opt. 50(26), 5158–5162 (2011).
[Crossref]

J. N. Forkey, N. D. Finkelstein, W. R. Lempert, and R. B. Miles, “Demonstration and Characterization of Filtered Rayleigh Scattering for Planar Velocity Measurements,” AIAA J. 34(3), 442–448 (1996).
[Crossref]

L. E. Dogariu, A. Dogariu, R. B. Miles, M. S. Smith, and E. C. Marineau, “Non-intrusive hypersonic freestream and turbulent boundary-layer velocity measurements in AEDC Tunnel 9 using PLEET,” AIAA 2018-1769, AIAA Aerospace Sciences Meeting 8-12 January (2018).

Miller, J. D.

Mustafa, M. A.

M. A. Mustafa, N. J. Parziale, M. S. Smith, and E. C. Marineau, “Noninstrusive freestream velocity measurement in large-scale hypersonic wind tunnel,” AIAA J. 55(10), 3611–3616 (2017).
[Crossref]

Nishihara, M.

N. Jiang, M. Nishihara, and W. R. Lempert, “Quantitative NO2 molecular tagging velocimetry at 500 kHz frame rate,” Appl. Phys. Lett. 97(22), 221103 (2010).
[Crossref]

Parziale, N. J.

M. A. Mustafa, N. J. Parziale, M. S. Smith, and E. C. Marineau, “Noninstrusive freestream velocity measurement in large-scale hypersonic wind tunnel,” AIAA J. 55(10), 3611–3616 (2017).
[Crossref]

Pitz, R. W.

M. C. Ramsey and R. W. Pitz, “Template matching for improved accuracy in molecular tagging velocimetry,” Exp. Fluids 51(3), 811–819 (2011).
[Crossref]

Ramsey, M. C.

M. C. Ramsey and R. W. Pitz, “Template matching for improved accuracy in molecular tagging velocimetry,” Exp. Fluids 51(3), 811–819 (2011).
[Crossref]

Roy, S.

Samimy, M.

W. R. Lempert, N. Jiang, S. Sethuram, and M. Samimy, “Molecular tagging velocimetry measurements in supersonic microjets,” AIAA J. 40(6), 1065–1070 (2002).
[Crossref]

Schramm, J. M.

T. Kirmse, J. Agocs, A. Schroder, J. M. Schramm, S. Kari, and K. Hannemann, “Application of particle image velocimetry and the background-oriented schlieren technique in the high enthalpy shock tunnel Gottingen,” Shock Waves 21(3), 233–241 (2011).
[Crossref]

Schroder, A.

T. Kirmse, J. Agocs, A. Schroder, J. M. Schramm, S. Kari, and K. Hannemann, “Application of particle image velocimetry and the background-oriented schlieren technique in the high enthalpy shock tunnel Gottingen,” Shock Waves 21(3), 233–241 (2011).
[Crossref]

Sethuram, S.

W. R. Lempert, N. Jiang, S. Sethuram, and M. Samimy, “Molecular tagging velocimetry measurements in supersonic microjets,” AIAA J. 40(6), 1065–1070 (2002).
[Crossref]

Shepherd, J. E.

J. S. Jewell and J. E. Shepherd, “T5 Conditions Report: Shots 2526–2823,” GALCIT Report FM2014.002, California Institute of Technology, Pasadena, CA, 2014.

Sherrill, R. T.

P. T. Harsha, L. C. Keel, A. Castrogiovanni, and R. T. Sherrill. “X-43A Vehicle Design and Manufacture,” AIAA 2005-3334. Retrieved: August (2011).

Slipchenko, M. N.

Smith, D. R.

P. D. Danehy, S. O. Byrne, F. P. Houwing, J. S. Fox, and D. R. Smith, “Flow-tagging velocimetry for hypersonic flows using fluorescence of nitric oxide,” AIAA J. 41(2), 263–271 (2003).
[Crossref]

Smith, M. S.

M. A. Mustafa, N. J. Parziale, M. S. Smith, and E. C. Marineau, “Noninstrusive freestream velocity measurement in large-scale hypersonic wind tunnel,” AIAA J. 55(10), 3611–3616 (2017).
[Crossref]

L. E. Dogariu, A. Dogariu, R. B. Miles, M. S. Smith, and E. C. Marineau, “Non-intrusive hypersonic freestream and turbulent boundary-layer velocity measurements in AEDC Tunnel 9 using PLEET,” AIAA 2018-1769, AIAA Aerospace Sciences Meeting 8-12 January (2018).

Smyser, M. E.

Splichenko, M. N.

R. A. Burns, P. M. Danehy, N. Jiang, M. N. Splichenko, J. Felver, and S. Roy, “Unseeded velocimetry in nitrogen for high-pressure cryogenic wind tunnels: Part II. Picosecond-laser tagging,” Meas. Sci. Technol. 29(11), 115203 (2018).
[Crossref]

Stauffer, H. U.

Wright, M. J.

M. J. Wright, G. V. Candler, and D. Bose, “Data-parallel line relaxation method for the Navier-Stokes equations,” AIAA J. 36(9), 1603–1609 (1998).
[Crossref]

Yi, T.

AIAA J. (7)

M. A. Mustafa, N. J. Parziale, M. S. Smith, and E. C. Marineau, “Noninstrusive freestream velocity measurement in large-scale hypersonic wind tunnel,” AIAA J. 55(10), 3611–3616 (2017).
[Crossref]

B. F. Bathel, P. M. Danehy, J. A. Inman, and S. B. Jones, “Velocity profile measurements in hypersonic flow using sequentially imaged fluorescence-based molecular tagging,” AIAA J. 49(9), 1883–1896 (2011).
[Crossref]

W. R. Lempert, N. Jiang, S. Sethuram, and M. Samimy, “Molecular tagging velocimetry measurements in supersonic microjets,” AIAA J. 40(6), 1065–1070 (2002).
[Crossref]

R. J. Balla, “Iodine Tagging velocimetry in a Mach 10 Wake,” AIAA J. 51(7), 1783–1786 (2013).
[Crossref]

P. D. Danehy, S. O. Byrne, F. P. Houwing, J. S. Fox, and D. R. Smith, “Flow-tagging velocimetry for hypersonic flows using fluorescence of nitric oxide,” AIAA J. 41(2), 263–271 (2003).
[Crossref]

J. N. Forkey, N. D. Finkelstein, W. R. Lempert, and R. B. Miles, “Demonstration and Characterization of Filtered Rayleigh Scattering for Planar Velocity Measurements,” AIAA J. 34(3), 442–448 (1996).
[Crossref]

M. J. Wright, G. V. Candler, and D. Bose, “Data-parallel line relaxation method for the Navier-Stokes equations,” AIAA J. 36(9), 1603–1609 (1998).
[Crossref]

Appl. Opt. (2)

Appl. Phys. Lett. (1)

N. Jiang, M. Nishihara, and W. R. Lempert, “Quantitative NO2 molecular tagging velocimetry at 500 kHz frame rate,” Appl. Phys. Lett. 97(22), 221103 (2010).
[Crossref]

Exp. Fluids (2)

M. C. Ramsey and R. W. Pitz, “Template matching for improved accuracy in molecular tagging velocimetry,” Exp. Fluids 51(3), 811–819 (2011).
[Crossref]

R. J. Andrian, “Twenty years of particle image velocimetry,” Exp. Fluids 39(2), 159–169 (2005).
[Crossref]

J. Spacecr. Rockets (1)

J. S. Jewell and R. Kimmel, “Boundary layer stability analysis for Stetson’s Mach 6 blunt cone experiments,” J. Spacecr. Rockets 54(1), 258–265 (2017).
[Crossref]

Meas. Sci. Technol. (1)

R. A. Burns, P. M. Danehy, N. Jiang, M. N. Splichenko, J. Felver, and S. Roy, “Unseeded velocimetry in nitrogen for high-pressure cryogenic wind tunnels: Part II. Picosecond-laser tagging,” Meas. Sci. Technol. 29(11), 115203 (2018).
[Crossref]

Opt. Express (1)

Opt. Lett. (3)

Phys. Today (1)

I. A. Leyva, “The relentless pursuit of hypersonic flight,” Phys. Today 70(11), 30–36 (2017).
[Crossref]

Shock Waves (1)

T. Kirmse, J. Agocs, A. Schroder, J. M. Schramm, S. Kari, and K. Hannemann, “Application of particle image velocimetry and the background-oriented schlieren technique in the high enthalpy shock tunnel Gottingen,” Shock Waves 21(3), 233–241 (2011).
[Crossref]

Other (7)

P. T. Harsha, L. C. Keel, A. Castrogiovanni, and R. T. Sherrill. “X-43A Vehicle Design and Manufacture,” AIAA 2005-3334. Retrieved: August (2011).

D. S. Dolling, “Fluctuating Loads in Shock Wave/Turbulent Boundary Layer Interaction; Tutorial and Update,” AIAA-93-0284 (1993).

R. L. Kimmel, M. Borg, J. S. Jewell, K.-Y. Lam, R. Bowersox, and S. Fuchs, “AFRL Ludwieg Tube Initial Performance,” 55th AIAA Aerospace Sciences Meeting, AIAA 2017-1012 (2017).

J. S. Jewell, Boundary-Layer Transition on a Slender Cone in Hypervelocity Flow with Real Gas Effects. Ph.D. Thesis, California Institute of Technology, Pasadena, CA, 2014.

J. S. Jewell and J. E. Shepherd, “T5 Conditions Report: Shots 2526–2823,” GALCIT Report FM2014.002, California Institute of Technology, Pasadena, CA, 2014.

L. E. Dogariu, A. Dogariu, R. B. Miles, M. S. Smith, and E. C. Marineau, “Non-intrusive hypersonic freestream and turbulent boundary-layer velocity measurements in AEDC Tunnel 9 using PLEET,” AIAA 2018-1769, AIAA Aerospace Sciences Meeting 8-12 January (2018).

J. S. Jewell, R. E. Kennedy, S.J . Laurence, and R. L. Kimmel, “Transition on a Variable Bluntness 7-Degree Cone at High Reynolds Number,” AIAA SciTech 2018, January 2018, Kissimmee, FL. AIAA 2018-1822.

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Figures (7)

Fig. 1.
Fig. 1. (a) AFRL Mach-6 Ludwieg Tube Hypersonic Wind Tunnel. (b) A photograph of wind tunnel test section with three optical access ports in an environmental controlled room. (c) A photograph of the 7-degree half-angle circular cone model.
Fig. 2.
Fig. 2. A schematic diagram for the PLEET experimental setup in ARFL Mach-6 Ludwieg Tube.
Fig. 3.
Fig. 3. Time-resolved PLEET images with a 100 kHz laser repetition rate and 200 kHz camera imaging rate for Mach-6.14 freestream flow. (a) Airflow freestream case with static pressure of approximately 1.3 kPa (10 torr). (b) Nitrogen flow freestream case with static pressure of approximately 1 kPa (8 torr). The red, green, and orange dashed circles illustrate the PLEET signal movements in time. The brightness of each image was adjusted for easy visibility.
Fig. 4.
Fig. 4. Measured velocity variation for (a) freestream air flow and (b) freestream nitrogen flow at 100 kHz rate. Velocity at two different positions were measured for nitrogen flow case. The static pressure for air and nitrogen flow case were ∼1.3 kPa (10 torr) and ∼1 kPa (8 torr), respectively. The Mach number for both cases is 6.14.
Fig. 5.
Fig. 5. Time-resolved PLEET images with 100 kHz laser repetition rate and 200 kHz camera imaging rate for Mach-6.14 nitrogen flow with a 7-degree half-angle cylindrical cone model. The stagnation pressure is ∼1.7 MPa (250 psi). The brightness of each image was adjusted for easy visibility.
Fig. 6.
Fig. 6. Measured velocity variation for Mach-6.14 Nitrogen near a 7-degree half-angle blunt cone model. Velocities at three different positions as shown in (a) were measured. (b) Measured velocity fluctuations at 100 kHz rate. The Gaussian fit for determination of line center (along X axis) is illustrated for PLEET signal at Pos #1 and Pos #3.
Fig. 7.
Fig. 7. Comparison of experimental measured PLEET fluorescent line movement and CFD calculation. (a) Representative nitrogen PLEET line displacement for both experiment (single-shot) and theory; (b) experimentally measured velocity profile (single-shot) versus CFD simulation. Contour lines demarcate every 20 m/s in velocity.

Equations (1)

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V b = ρ a ρ h ρ h g t ,

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