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For its experimental validation, digital image velocimetry is applied to determine the instantaneous velocity field of objects rotating around an axis with a constant angular velocity.
A novel, embedded, 2D Particle Image Velocimetry system has been developed and implemented to obtain off-body velocity measurements in the junction of an 8% wing-body configuration in the NASA Langley Research Center 14- by 22-Foot Subsonic Tunnel. Although the initial purpose for implementing the system during this test was to evaluate system performance and identify potential risks, the system worked remarkably well and a considerable amount of data were obtained in the wing-fuselage junction near the trailing edge at a Reynolds Number of 2.4 Million and angle of attack of 5 degrees. In addition to providing notable efficiencies with regard to image acquisition and test operations, the PIV system proved to be quite capable of capturing unique details of the flow separation to complement the extensive suite of measurement techniques applied during the test. Instantaneous PIV vector fields reveal that the flow separation is not stationary but rather highly dynamic. Mean flow statistics calculated from the PIV measurements highlight where reverse flow and Reynolds stresses are concentrated in the separated region and agree well with results from the embedded Laser Doppler Velocimeter system and Computational Fluid Dynamics. The comparisons and additional insight gained during this effort will help guide system improvements for follow-on tests.
Report describes experiment to test digital image velocimetry developed to measure velocities of flows seeded with light-reflecting particles.
The development and testing of a holographic technique capable of measuring the three velocity components in selected regions of the flow field are described. Several techniques, including laser Doppler velocimetry, hot wire and particle image velocimetry (PIV) are commonly used to measure a flow field. The advantage of the PIV technique is that it provides instantaneous measurements in a selected plane of the flow field. The aim is to extend the conventional two dimensional PIV technique to simultaneously record several planes by means of the holographic technique. In the holographic technique, parallel laser sheets are used to increase the intensity of the light in specific planes of the flow field. Particles as small as 5 microns can be recorded.
Polystyrene latex sphere particles are widely used to seed flows for velocimetry techniques such as Particle Image Velocimetry (PIV) and Laser Doppler Velocimetry (LDV). These particles may be doped with fluorescent dyes such that signals spectrally shifted from the incident laser wavelength may be detected via Laser Induced Fluorescence (LIF). An attractive application of the LIF signal is achieving velocimetry in the presence of strong interference from laser scatter, opening up new research possibilities very near solid surfaces or at liquid/gas interfaces. Additionally, LIF signals can be used to tag different fluid streams to study mixing. While fluorescence-based PIV has been performed by many researchers for particles dispersed in water flows, the current work is among the first in applying the technique to micron-scale particles dispersed in a gas. A key requirement for such an application is addressing potential health hazards from fluorescent dyes; successful doping of Kiton Red 620 (KR620) has enabled the use of this relatively safe dye for fluorescence PIV for the first time. In this paper, basic applications proving the concept of PIV using the LIF signal from KR620-doped particles are exhibited for a free jet and a twophase flow apparatus. Results indicate that while the fluorescence PIV techniques are roughly 2 orders of magnitude weaker than Mie scattering, they provide a viable method for obtaining data in flow regions previously inaccessible via standard PIV. These techniques have the potential to also complement Mie scattering signals, for example in multi-stream and/or multi-phase experiments.
The instantaneous velocity fields of time-dependent flows, or of a collection of objects moving with spatially varying velocities, can be measured by means of digital image velocimetry (DIV). DIV overcomes several shortcomings of such existing techniques as laser-speckle or particle-image velocimetry. Attention is presently given to numerically generated images representing objects in uniform motion which are then used for the experimental validation of DIV.
An important phase of any Stereo Imaging Velocimetry experiment is particle tracking. Particle tracking seeks to identify and characterize the motion of individual particles entrained in a fluid or air experiment. We analyze a cylindrical chamber filled with water and seeded with density-matched particles. In every four-frame sequence, we identify a particle track by assigning a unique track label for each camera image. The conventional approach to particle tracking is to use an exhaustive tree-search method utilizing greedy algorithms to reduce search times. However, these types of algorithms are not optimal due to a cascade effect of incorrect decisions upon adjacent tracks. We examine the use of a guided evolutionary neural net with simulated annealing to arrive at a globally optimal assignment of tracks. The net is guided both by the minimization of the search space through the use of prior limiting assumptions about valid tracks and by a strategy which seeks to avoid high-energy intermediate states which can trap the net in a local minimum. A stochastic search algorithm is used in place of back-propagation of error to further reduce the chance of being trapped in an energy well. Global optimization is achieved by minimizing an objective function, which includes both track smoothness and particle-image utilization parameters. In this paper we describe our model and present our experimental results. We compare our results with a nonoptimizing, predictive tracker and obtain an average increase in valid track yield of 27 percent
Particle Imaging Velocimetry (PIV) is an optical technique whereby a pulsed laser sheet is used to illuminate particles entrained in a fluid across an extended planar cross section of a flow field. Electronic recording of the particle positions at two closely timed laser pulses permits the computation of the flow velocity. PIV captures the instantaneous flow field, permitting the study of unsteady flow phenomena. Mean flow statistics can be computed by acquiring several hundred images and averaging the results. The first-ever successful application of PIV to acquire measurements in a high-speed rotating turbomachinery blade row was completed in NASA Lewis Research Center's W-8 Single Stage Axial Compressor Facility. Measurements were acquired in a 20-in.-diameter transonic compressor rotor operating at 17,188 rpm. A custom-designed light-sheet generating probe was used to insert the high-energy, pulsed light-sheet illumination required for recording the unblurred images of particles entrained in the fluid. Measurements of the shock wave formed within the rotor blade passage and of unsteady structures within the blade wakes were acquired. These measurements provide insight into unsteady spatial structures in the flow field which cannot be measured with the more conventional laser anemometry technique. The PIV technique provides both instantaneous and average velocity data in a transonic compressor in an order of magnitude less time than required for other conventional optical diagnostic techniques.
This paper presents new trends in Particle Image Velocimetry and practical aspects relevant to the application of the technique to large scale wind tunnel testing. The various problems and their solutions to the operation of PIV in large scale wind tunnels are discussed. Application of the technique in mapping complex flows are also presented.
This report provides turbulent flow statistics made using particle image velocimetry (PIV) for several internally mixed exhaust systems with external plugs (Plug20 designs). The tests were conducted at the NASA Glenn Research Center’s Aero-Acoustic Propulsion Laboratory (AAPL) in May and June 2022. The corresponding acoustic data for the configurations and flows presented in this report can be found in an earlier Technical Memorandum, NASA/TM-20210010291, “Plug20 Test Report.” The Plug20 nozzle family was designed to represent commercial supersonic vehicles in the 2025 to 2035 timeframe with a bypass ratio around 4, having an internal mixer, with and without an external plug to improve nacelle boattail drag and shock. The flow conditions measured represent engine cycles for commercial supersonic aircraft at takeoff, having pressure ratios of 2.0 and heated fan and core streams, measured both with and without a flight stream surrounding the plume. A few unheated flow conditions were also tested to tie results to other baseline test results. The PIV measurements in both streamwise and cross-stream planes are described, along with brief analysis to visually catalog the contents and confirm their validity. In this analysis, the streamwise PIV is found to match benchmark datasets within its experimental error. However, the cross-stream turbulent quantities measured by two systems do not match each other or the streamwise measurements in amplitude—caution is required when using the cross-stream data. Data acquired and included in this report are (1) velocity statistics of the plumes in both a streamwise and several cross-stream planes, and (2) the hot nozzle geometry. Tabular forms of the data and computer-aided design (CAD) files of the hot geometry are presented as supplemental files described in Appendix A (TM-20230006779SUPPL1.zip) and Appendix B (TM-20230006779SUPPL2.zip).
Global velocimetry measurements were taken using Particle Image Velocimetry (PIV) in the subsonic flow exiting a 1 inch circular nozzle in an attempt to better understand the turbulence characteristics of its shear layer region. This report presents the results of the PIV analysis and data reduction portions of the test and details the processing that was done. Custom data analysis and data validation algorithms were developed and applied to a data ensemble consisting of over 750 PIV 70 mm photographs taken in the 0.85 mach flow facility. Results are presented detailing spatial characteristics of the flow including ensemble mean and standard deviation, turbulence intensities and Reynold's stress levels, and 2-point spatial correlations.
Using a new technique, three-dimensional Particle Imaging Velocimetry, trajectories of individual ejecta particles during experimental impacts can be captured in flight. Initial results of this system for oblique impacts are discussed.
Particle image velocimetry (PIV) is an effective tool in experimental fluid mechanics for extracting flow fields from images. Recently, convolutional neural networks (CNNs) have been used to perform PIV analysis with accuracy on par with classical methods. Here we extend the use of CNNs to analyze PIV data while providing simultaneous uncertainty quantification on the inferred flow field. The method we apply in this paper is a Bayesian convolutional neural network (BCNN) which learns distributions of the CNN weights through variational Bayes. In order to demonstrate the utility of BCNNs for the PIV task, we compare the performance of three distinct BCNN models with simple architectures. The first network estimates flow velocity from image interrogation regions only. Our second model learns to infer velocity from both the image interrogation regions and interrogation region cross-correlation maps. Finally, our best performing network infers velocities from interrogation region cross-correlation maps only. We find that BCNNs using interrogation region cross-correlation maps as inputs perform better than those using interrogation windows only as inputs and discuss reasons why this may be the case. Additionally, we test the best performing BCNN on a full synthetic test image pair and a real image pair from the 1st International PIV Challenge. We show that ~98% of true particle displacements from the full synthetic image pair can be captured within the BCNN's 95% confidence intervals, and that the BCNN's performance on the real image pair is quantitatively similar to that of algorithms tested in the 1st International PIV Challenge. Finally, we show that BCNNs can be generalized to be used with multi-pass PIV algorithms with a moderate loss in accuracy, which may be overcome by future work on finetuning and training schemes. So to our knowledge, this is the first use of Bayesian neural networks to perform PIV.
A planar optical velocity measurement technique known as Particle Image Velocimetry (PIV) is being used to study transient events in compressors. In PIV, a pulsed laser light sheet is used to record the positions of particles entrained in a fluid at two instances in time across a planar region of the flow. Determining the recorded particle displacement between exposures yields an instantaneous velocity vector map across the illuminated plane. Detailed flow mappings obtained using PIV in high-speed rotating turbomachinery components are used to improve the accuracy of computational fluid dynamics (CFD) simulations, which in turn, are used to guide advances in state-of-the-art aircraft engine hardware designs.
Mixing of two fluids generated by steady and particularly g-jitter acceleration is fundamental towards the understanding of transport phenomena in a microgravity environment. We propose to carry out flight and ground-based experiments to quantify flow fields due to g-jitter type of accelerations using Stereo Imaging Velocimetry (SIV), and measure the concentration field using laser fluorescence. The understanding of the effects of g-jitter on transport phenomena is of great practical interest to the microgravity community and impacts the design of experiments for the Space Shuttle as well as the International Space Station. The aim of our proposed research is to provide quantitative data to the community on the effects of g-jitter on flow fields due to mixing induced by buoyancy forces. The fundamental phenomenon of mixing occurs in a broad range of materials processing encompassing the growth of opto-electronic materials and semiconductors, (by directional freezing and physical vapor transport), to solution and protein crystal growth. In materials processing of these systems, crystal homogeneity, which is affected by the solutal field distribution, is one of the major issues. The understanding of fluid mixing driven by buoyancy forces, besides its importance as a topic in fundamental science, can contribute towards the understanding of how solutal fields behave under various body forces. The body forces of interest are steady acceleration and g-jitter acceleration as in a Space Shuttle environment or the International Space Station. Since control of the body force is important, the flight experiment will be carried out on a tunable microgravity vibration isolation mount, which will permit us to precisely input the desired forcing function to simulate a range of body forces. To that end, we propose to design a flight experiment that can only be carried out under microgravity conditions to fully exploit the effects of various body forces on fluid mixing. Recent flight experiments, by the P.I. through collaboration with the Canadian Space Agency (STS-85, August 1997), aimed at determining the stability of the interface between two miscible liquids inside an enclosure show that a long liquid column (5 cm) under microgravity isolation conditions can be stable, i.e. the interface remains sharp and vertical over a short time scale; thus transport occurs by molecular mass diffusion. On the other hand, when the two liquids were excited from a controlled vibration source (Microgravity Vibration Isolation Mount) two to four mode large amplitude quasi-stationary waves were observed. The data was limited to CCD recording of the dynamics of the interface between the two fluids. We propose to carry out flight experiments to quantify the dynamics of the flow field using Stereo Imaging Velocimetry and measure the concentration field using laser fluorescence. The results will serve as a basis to understand effects of g-jitter on transport phenomena, in this case mass diffusion. As the measurement of the kinematics of the flow field will shed light on the instability mechanism. The research will allow measurement of the flow field in microgravity environment to prove two hypotheses: (1) Maxwell's hypothesis: finite convection always exists in diffusing systems, and (2) Quasi-stationary waves inside a bounded enclosure in a microgravity environment is generated by Kelvin-Helmholtz instability; resonance of the interface which produces incipient mixing is due to Rayleigh-Taylor instability. The first hypothesis can be used as a benchmark experiment to illustrate diffusive mixing. The second hypothesis will lead to the understanding of g-jitter effects on buoyancy driven flow fields which occur in many situations involving materials processing, and other basic fluid physics phenomena. In addition, the second hypothesis will also provide insight in how Rayleigh-Taylor and Kelvin-Helmholtz instabilities propagate concentration fronts during mixing. Measurement of the flow field using SIV is important because it is the flow field which causes instability at the interface between the two fluids. Mixing driven by buoyancy induced flow fields will be addressed both experimentally and computationally. The experimental effort will address the kinematics of mixing: stretching, transport and chaos. Quantification of the mechanisms of mixing will consists of measuring the flow field using the SIV system at Glenn and capturing the dynamics of the interface, to measure mass transport, using a CCD camera. These experiments will be carried out within the framework of Earth's gravity and g-jitter microgravity acceleration as in a Space Shuttle environment or the International Space Station. The g-jitter will be induced and controlled using a tunable vibration isolation platform to isolate against vibration as well as input periodic and random vibration to the system. The parametric range of the microgravity experiment will be extended from the experiments on STS-85 to investigate higher mode quasi-stationary waves (8 to 12), as well as resonance regions which leads to chaos and turbulence. Ground-based experiments will focus on effects of vibration on stably stratified fluid layers in order to scale for possible scenarios in a microgravity environment. These vibrations will be subjected perpendicular to the concentration field on the ground since the parallel case can only be carried out in a microgravity environment. The concept of dynamical similarity will be applied to tune the experiments as closely as possible to a Space Shuttle environment or the International Space Station. The computational effort will take advantage of the Computational Laboratory at Glenn to corroborate the experimental findings with predictions of the dynamics of the flow field using the codes FLUENT (finite difference based) and FIDAP (finite element based). We will investigate two important cases, single-fluid model to address dilute systems with negligible jump in viscosity and the more general two-fluid model which accounts for finite jump in viscosity. Apart from its microgravity relevance, this experiment is well suited to study dynamics in nonlinear systems.
An optical measurement technique known as Three-Dimensional Digital Particle Image Velocimetry (3-D DPIV) was used to characterize the tip clearance flow in NASA Glenn Research Center's low-speed axial compressor. 3-D DPIV is a technique in which a stereoscopic imaging system consisting of two cross-correlation cameras is used to record particles entrained in a flow as a laser light sheet is pulsed at two instances in time. Although 3-D DPIV has been used elsewhere, this is the first time it has been used to measure compressor tip clearance flows. In-house modifications of the DPIV system include the use of effective seeding technology and a novel system to perform a priori calibrations at all five measurement planes, greatly reducing facility run time. Computational fluid dynamics predictions, which are used to guide design changes toward improving the efficiency and operating range of turbomachinery, can be verified and improved by comparison with 3-D DPIV measurements of the actual tip clearance flow. This measurement campaign dealt with the characterization of the tip clearance vortex in the first stage of a four-stage axial compressor. The tip clearance vortex is formed in compressors operating with a clearance gap between the moving rotor blade tips and the stationary casing when a leakage flow, forced from the pressure side of the blade over the blade tip, forms a vortical structure on the suction side of the blade. 3-D DPIV is ideally suited to measure the clearance vortex for two reasons: (1) this technique captures the entire blade passage flow at one instant in time, so that wandering of the vortex during the measurement does not smear out velocity gradients in the flow field, and (2) the spanwise component of velocity changes sign across the vortex core, providing a more accurate measurement of the vortex location than was available with previous two-dimensional measurement approaches. These two attributes of the data will enable computational fluid dynamics researchers to validate their predictions to a level of accuracy not previously attainable. In an effort to understand the effects of this flow phenomenon on the operation of the low speed axial compressor, data were acquired at two mass flow coefficients: 0.395 (design operating point) and 0.35 (operating point just above stall). In order to identify the spatial extent, location, and magnitude of the tip clearance vortex for each mass flow condition, data were acquired at five equally spaced spanwise locations, from 90- to 100-percent span. The data presented shows a cross section of the tip clearance vortex at 94-percent span and a mass flow coefficient of 0.395, where the color contours represent the radial velocity component. The blue (flow towards the hub) and red (flow towards the casing) regions illustrate the extent of the tip clearance vortex. The interface between the blue and red regions delineates the location of the vortex core.
Acoustic velocity measurements were taken using Particle Image Velocimetry (PIV) in a Normal Incidence Tube configuration at various frequency, phase, and amplitude levels. This report presents the results of the PIV analysis and data reduction portions of the test and details the processing that was done. Estimates of lower measurement sensitivity levels were determined based on PIV image quality, correlation, and noise level parameters used in the test. Comparison of measurements with linear acoustic theory are presented. The onset of nonlinear, harmonic frequency acoustic levels were also studied for various decibel and frequency levels ranging from 90 to 132 dB and 500 to 3000 Hz, respectively.
Particle image velocimetry (PIV) measurements were conducted in the Arc-Heated Combustion Tunnel (ACT-II) on a high-enthalpy Mach 4.5 nozzle flow. The primary motivation for the current work is to establish the feasibility of PIV as a high-quality flow diagnostic technique in hypersonic arc-heated flows and produce a high-resolution hypersonic nozzle flow characterization, including nozzle free jet shear layer velocity profiles. Due to the uncertain nature of the gas composition in the flowfield of interest, PIV measurements of a supersonic wedge flow were used to couple the flow velocities to the oblique shock relations. This enabled a PIV-derived total temperature calculation that does not require a priori assumptions of the exact gas composition. A PIV expansion module was developed for this study, and proper seed sizing and material were selected for the present flow. An analysis of the seed particle response from the PIV measurements provided an initial validation of the seed performance while revealing potential issues with consistent seed sizing. These measurements and derived conditions represent a means of acquiring high-resolution velocimetry and temperature datasets that consider uncertainties in the experimental generation of hypersonic high-enthalpy flows.