Publications

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Here, experiments were performed within Sandia National Labs’ Multiphase Shock Tube to measure and quantify the shock-induced dispersal of a shock/dense particle curtain interaction. Following interaction with a planar travelling shock wave, schlieren imaging at 75 kHz was used to track the upstream and downstream edges of the curtain. Data were obtained for two particle diameter ranges ($d_{p}=106{-}125$,$300{-}355~\unicode[STIX]{x03BC}\text{m}$) across Mach numbers ranging from 1.24 to 2.02. Using these data, along with data compiled from the literature, the dispersion of a dense curtain was studied for multiple Mach numbers (1.2–2.6), particle sizes ($100{-}1000~\unicode[STIX]{x03BC}\text{m}$) and volume fractions (9–32 %). Data were non-dimensionalized according to two different scaling methods found within the literature, with time scales defined based on either particle propagation time or pressure ratio across a reflected shock. The data refelct that spreading of the particle curtain is a function of the volume fraction, with the effectiveness of each time scale based on the proximity of a given curtain’s volume fraction to the dilute mixture regime. It is observed that volume fraction corrections applied to a traditional particle propagation time scale result in the best collapse of the data between the two time scales tested here. In addition, a constant-thickness regime has been identified, which has not been noted within previous literature.

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Time-resolved particle image velocimetry was conducted at 40 kHz using a pulse-burst laser in the supersonic wake of a wall-mounted hemisphere. Velocity fields suggest a recirculation region with two lobes, in which flow moves away from the wall near the centerline and recirculates back toward the hemisphere off the centerline, contrary to transonic configurations. Spatio-temporal cross-correlations and conditional ensemble averages relate the characteristic behavior of the unsteady shock motion to the flapping of the shear layer. At Mach 1.5, oblique shocks develop, associated with vortical structures in the shear layer and convect downstream in tandem; a weak periodicity is observed. Shock motion at Mach 2.0 appears somewhat different, wherein multiple weak disturbances propagate from shear-layer turbulent structures to form an oblique shock that ripples as these vortices pass by. Bifurcated shock feet coalesce and break apart without evident periodicity. Power spectra show a preferred frequency of shear-layer flapping and shock motion for Mach 1.5, but at Mach 2.0, a weak preferred frequency at the same Strouhal number of 0.32 is found only for oblique shock motion and not shear-layer unsteadiness.

Previous efforts determined a set of calibrated model parameters for ReynoldsAveraged Navier Stokes (RANS) simulations of a compressible jet in crossflow (JIC) using a k-ɛ turbulence model. These coefficients were derived from Particle Image Velocimetry (PIV) data of a complementary experiment using a limited set of flow conditions. Here, k-ɛ models using conventional (nominal) and calibrated parameters are rigorously validated against PIV data acquired under a much wider variety of JIC cases, including a flight configuration. The results from the simulations using the calibrated model parameters showed considerable improvements over those using the nominal values, even for cases that were not used in defining the calibrated parameters. This improvement is demonstrated using quality metrics defined specifically to test the spatial alignment of the jet core as well as the magnitudes of flow variables on the PIV planes. These results suggest that the calibrated parameters have applicability well outside the specific flow case used in defining them and that with the right model parameters, RANS results can be improved significantly over the nominal.

Femtosecond Laser Electronic Excitation Tagging (FLEET) is used to measure velocity flowfields in the wake of a sharp 7◦ half-angle cone in nitrogen at Mach 8, over freestream Reynolds numbers from 4.3∗106 /m to 13.8∗106 /m. Flow tagging reveals expected wake features such as the separation shear layer and two-dimensional velocity components. Frequency-tripled FLEET has a longer lifetime and is more energy efficient by tenfold compared to 800 nm FLEET. Additionally, FLEET lines written with 267 nm are three times longer and 25% thinner than that written with 800 nm at a 1 µs delay. Two gated detection systems are compared. While the PIMAX 3 ICCD offers variable gating and fewer imaging artifacts than a LaVision IRO coupled to a Photron SA-Z, its slow readout speed renders it ineffective for capturing hypersonic velocity fluctuations. FLEET can be detected to 25 µs following excitation within 10 mm downstream of the model base, but delays greater than 4 µs have deteriorated signal-to-noise and line fit uncertainties greater than 10%. In a hypersonic nitrogen flow, exposures of just several hundred nanoseconds are long enough to produce saturated signals and/or increase the line thickness, thereby adding to measurement uncertainty. Velocity calculated between the first two delays offer the lowest uncertainty (less than 3% of the mean velocity).

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Fluid-structure interactions were studies on a 7° half-angle cone in the Sandia Hypersonic Wind Tunnel at Mach 5 and 8 and in the Purdue Boeing/AFOSR Mach 6 Quiet Tunnel. A thin composite panel was integrated into the cone and the response to boundary-layer disturbances was characterized by accelerometers on the backside of the panel. Here, under quiet-flow conditions at Mach 6, the cone boundary layer remained laminar. Artificially generated turbulent spots excited a directionally dependent panel response which would last much longer than the spot duration.

A new approach to denoising Time-Resolved Particle Image Velocimetry data is proposed by incorporating measurement uncertainties estimated using the correlation statistics method. The denoising algorithm of Oxlade et al (Experiments in Fluids, 2012) has been modified to add the frequency dependence of PIV noise by obtaining it from the uncertainty estimates, including the correlated term between velocity and uncertainty that is zero only if white noise is assumed. Although the present approach was only partially effective in denoising the 400-kHz “postage-stamp PIV” data, important and novel insights were obtained into the behavior of PIV uncertainty. The belief that PIV noise is white noise has been shown to be inaccurate, though it may serve as a reasonable approximation for measurements with a high dynamic range. Noise spectra take a similar shape to the velocity spectra because increased velocity fluctuations correspond to higher shear and therefore increased uncertainty. Coherence functions show that correlation between velocity fluctuations and uncertainty is strongest at low and mid frequencies, tapering to a much weaker correlation at high frequencies where turbulent scales are small with lower shear magnitudes.

Turbulent viscosities have been calculated from stereoscopic particle image velocimetry (PIV) data for a supersonic jet exhausting into a transonic crossflow. Image interrogation must be optimized to produce useful turbulent viscosity fields. High-accuracy image reconstruction should be used for the final iteration, whereas efficient algorithms produce spatial artifacts in derivative fields. Mean strain rates should be calculated from large windows (128 pixel) with 75% overlap. Turbulent stresses are optimally computed using multiple (more than two) iterations of image interrogation and 75% overlap, both of which increase the signal bandwidth. However, the improvement is modest and may not justify the considerable increase in computational expense. The turbulent viscosity may be expressed in tensor notation to include all three axes of velocity data. In this formulation, a least-squares fit to the multiple equations comprising the tensor generated a scalar turbulent viscosity that eliminated many of the artifacts and noise present in the single-component formulation. The resulting experimental turbulent viscosity fields will be used to develop data-driven turbulence models that can improve the fidelity of predictive computations.

Fluid-structure interactions were studied on a 7◦ half-angle cone in the Sandia Hypersonic Wind Tunnel at Mach 5 and 8 and in the Purdue Boeing/AFOSR Mach 6 Quiet Tunnel. A thin composite panel was integrated into the cone and the response to boundary-layer disturbances was characterized by accelerometers on the backside of the panel. Under quiet-flow conditions at Mach 6, the cone boundary layer remained laminar. Artificially generated turbulent spots excited a directionally dependent panel response which would last much longer than the spot duration. When the spot generation frequency matched a structural natural frequency of the panel, resonance would occur and responses over 200 times greater than under a laminar boundary layer were obtained. At Mach 5 and 8 under noisy flow conditions, natural transition driven by the wind-tunnel acoustic noise dominated the panel response. An elevated vibrational response was observed during transition at frequencies corresponding to the distribution of turbulent spots in the transitional flow. Once turbulent flow developed, the structural response dropped because the intermittent forcing from the spots no longer drove panel vibration.

A new approach to denoising Time-Resolved Particle Image Velocimetry data is proposed by incorporating measurement uncertainties estimated using the correlation statistics method. The denoising algorithm of Oxlade et al (Experiments in Fluids, 2012) has been modified to add the frequency dependence of PIV noise by obtaining it from the uncertainty estimates, including the correlated term between velocity and uncertainty that is zero only if white noise is assumed. Although the present approach was only partially effective in denoising the 400-kHz “postage-stamp PIV” data, important and novel insights were obtained into the behavior of PIV uncertainty. The belief that PIV noise is white noise has been shown to be inaccurate, though it may serve as a reasonable approximation for measurements with a high dynamic range. Noise spectra take a similar shape to the velocity spectra because increased velocity fluctuations correspond to higher shear and therefore increased uncertainty. Coherence functions show that correlation between velocity fluctuations and uncertainty is strongest at low and mid frequencies, tapering to a much weaker correlation at high frequencies where turbulent scales are small with lower shear magnitudes.