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At least 19 records
All sourcesNASA NTRSDOE OSTI
DOE OSTI2024

PDV Inspection and Analysis Demonstration: 2024 PDV Workshop

This document walks a user through a demonstration of working with PDV digitizer data using python. This demonstration and included suggested exercises will be used at the 2024 PDV workshop hands-on session as an example and skill-development training session. The tutorial allows the user to generate synthetic but realistic PDV waveform data and visualize/inspect the results using spectrograms and waveform viewing tools.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2021

Time-lens photon Doppler velocimetry (TL-PDV)

Here, we describe a time lens (TL) to expand the dynamic range of photon Doppler velocimetry (PDV) systems. The principle and preliminary design of a TL-PDV system are explained and shown to be feasible through simulations. In a PDV system, an interferometer is used for measuring frequency shifts due to the Doppler effect from the target motion. However, the sampling rate of the electronics could limit the velocity range of a PDV system. A four-wave-mixing (FWM) TL applies a quadratic temporal phase to an optical signal within a nonlinear FWM medium (such as an integrated photonic waveguide or a highly nonlinear optical fiber). By spectrally isolating the mixing product, termed the idler, and with appropriate lengths of dispersion prior to and after this FWM TL, a temporally magnified version of the input signal is generated. Therefore, the frequency shifts of PDV can be “slowed down” with the magnification factor M of the TL. M = 1 corresponds to a regular PDV system without a TL. M = 10 has been shown to be feasible for a TL-PDV system. The use of this effect for PDV can expand the velocity measurement range and allow for the use of lower bandwidth electronics. TL-PDV will open up new avenues for various dynamic material experiments.

47 OTHER INSTRUMENTATION↗
NASA NTRS1999

Investigation of Point Doppler Velocimetry (PDV) for Transition Detection in Boundary Layers

A two-component Point Doppler Velocimeter (PDV) system has been improved through the use of vapor-limited iodine cells that have responses that are insensitive to temperature variations. Two-component PDV velocity measurements have been obtained for a 1 inch diameter uniform circular jet flow at a nominal exit velocity of 60 m/sec, corresponding to a Reynolds number of 100,000. Similar data have also been obtained for an annular jet and a swirling jet, These PDV data runs have been duplicated to judge the repeatability of these measurements, and also have been compared with hot wire anemometer data for the same flow conditions. PDV mean velocity results are repeatable to within approximately 1-2 meters per second; the PDV RMS velocity results are also quite repeatable. Exit profiles of PDV mean axial velocity data generally agree with hot wire anemometer results to within about 2 meters per second as well. However, the PDV RMS velocity results are consistently lower than the hot wire results everywhere but at the exit of the standard jet, where they are too high relative to the hot wire data. This is believed to at least be partially due to the method used to compute the RMS (Root Mean Square).

Kuhlman, John↗
NASA NTRS1999

Investigation of Point Doppler Velocimetry (PDV) for Transition Detection in Boundary Layers

A two component Point Doppler Velocimetry (PDV) system has been developed and tested. Improvements were made to an earlier PDV system, in terms of experimental techniques, as well as the data acquisition and reduction software. Measurements of the streamwise and spanwise mean and fluctuating velocities for flows from a rectangular channel and over an NACA 0012 airfoil were made, and the data were compared against hot wire data. The closest to the airfoil surface that PDV measurements could be made was on the order of 0.005 m(0.2", z/c = 0.0169). When the PDV and hot wire data were compared, the time traces for each appeared similar. The mean velocities agreed to within plus or minus 2 m/sec, while the RMS velocities agreed to plus or minus 0.4 m/sec. While the PDV time autocorrelations agreed with those of the hot wire data, the PDV power spectral densities were noisier above 750 Hz. A major source of error in these experiments was determined to be the drifting of the iodine cell stem temperatures. While the stem temperatures were controlled to within plus or minus 0.1 C, this could lead to a frequency shift of as much as 6 MHz, which translates into an error of 1.6 m/sec for the back scatter channel, and up to 6.9 m/sec for the forward scatter channel. These error estimates are consistent with the observed error magnitudes.

Kuhlman, John M.↗
DOE OSTI2024

Enhanced PDV waveform search and analysis method using parallel circular-convolution / cross-correlation for improved dynamic surface velocity extraction [Poster]

Previous work on exhaustive search methodologies for extracting best-match parameters pertaining to dynamic surface quantities from PDV was done by cross-correlating synthetically generated PDV waveforms with observed counterparts using the circular-convolution theorem. This work was further developed into an open-source PDV analysis toolkit called CCPDVANALYSIS which expands upon and enhances the previously tested methods by parallelizing serial algorithmic components and incorporating a comprehensive script library for different flavors of instantaneous frequency functions utilized in generating synthetic PDV waveforms. Results of these enhancements have been shown to markedly decrease execution times of exhaustive search and extraction algorithms and produce improved velocity recoveries for low-velocity and dynamically varying velocity signals. The CCPDVANALYSIS script library demonstrates an advanced method for extracting velocities from low-velocity and non-constant velocity signals further extending and improving the methods beyond capabilities of traditional frequency domain tools.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2024

Technology and times scales in Photonic Doppler Velocimetry (PDV)

Photonic Doppler Velocimetry (PDV) is a fiber-based measurement amenable to a wide range of experimental conditions. Interference between two optical signals—one Doppler shifted and the other not—is the essential principle in these measurements. A confluence of commercial technologies, largely driven by the telecommunication industry, makes PDV particularly convenient at near-infrared wavelengths. This discussion considers how measurement time scales of interest relate to the design, operation, and analysis of a PDV measurement, starting from the steady state through nanosecond resolution. Benefits and outstanding challenges of PDV are summarized, with comparisons to related diagnostics.

47 OTHER INSTRUMENTATION↗
DOE OSTI2020

Extreme measurements with Photonic Doppler Velocimetry (PDV)

Photonic Doppler Velocimetry (PDV) is a fiber-based diagnostic for the extreme conditions created by high-speed impact, explosive detonation, electrical pulsed power, and intense laser ablation. PDV is a conceptually simple application of the optical Doppler effect, but measurements above 1 km/s only became practical at the beginning of the twenty-first century. In this work, I discuss the evolution of PDV, its operational details, practical analysis, and outstanding challenges.

47 OTHER INSTRUMENTATION↗
DOE OSTI2020

Stastically determined experimental uncertainties in photon Doppler velocimetry (PDV) measurements

Shock-ramp experiments place high demands on the precision, accuracy, and temporal resolution of transformed velocimetry signals. To minimize uncertainty after total propagation of a shockramp experiment, ideally multiple PDV traces are used. However, each trace has some uncertainty that is a function of the PDV system and analysis of the velocimetry data. In order to determine a reasonable experimental estimate of minimum uncertainty, we calculate observed uncertainties in as-fielded PDV systems using multiple channels to sample the velocity on each shot. We also calculate the uncertainty’s sensitivity to choice of analysis methods.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2022

Small Windowed PDV Slab Shot Verification

Windowed PDV probes are used as a time of arrival diagnostic where conventional PDV measurements cannot be made with accuracy i.e., measurements where the surface measured is bare HE or the surface measured does not provide quality optical return for PDV directly. Often hydro experiments require that these diagnostics be minimally invasive, so their installation does not negatively impact the device performance or the overall experiments goals. In this report we build 3 mm diameter windowed probes and show that they give an error that is still within the error of piezo pins.

13 HYDRO ENERGY↗
NASA NTRS1997

Accuracy Study of a 2-Component Point Doppler Velocimeter (PDV)

A two-component Point Doppler Velocimeter (PDV) which has recently been developed is described, and a series of velocity measurements which have been obtained to quantify the accuracy of the PDV system are summarized. This PDV system uses molecular iodine vapor cells as frequency discriminating filters to determine the Doppler shift of laser light which is scattered off of seed particles in a flow. The majority of results which have been obtained to date are for the mean velocity of a rotating wheel, although preliminary data are described for fully-developed turbulent pipe flow. Accuracy of the present wheel velocity data is approximately +/- 1 % of full scale, while linearity of a single channel is on the order of +/- 0.5 % (i.e., +/- 0.6 m/sec and +/- 0.3 m/sec, out of 57 m/sec, respectively). The observed linearity of these results is on the order of the accuracy to which the speed of the rotating wheel has been set for individual data readings. The absolute accuracy of the rotating wheel data is shown to be consistent with the level of repeatability of the cell calibrations. The preliminary turbulent pipe flow data show consistent turbulence intensity values, and mean axial velocity profiles generally agree with pitot probe data. However, there is at present an offset error in the radial velocity which is on the order of 5-10 % of the mean axial velocity.

Kuhlman, John↗
DOE OSTI2023

Brief History and Summary of the PDV [Slides]

The early development of the PDV was not a straightforward process. There were many fortuitous events that occurred over several years to make it happen. The drive toward more PDV channels per digitizer was initially driven by the high cost of the digitizer. The optical pin dome diagnostic for the national labs was the driver for very large channel count.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
NASA NTRS1992

Simultaneous mapping of the unsteady flow fields by Particle Displacement Velocimetry (PDV)

Current experimental and computational techniques must be improved in order to advance the prediction capability of the longitudinal vortical flows shed by underwater vehicles. The generation, development, and breakdown mechanisms of the shed vortices at high Reynolds numbers are not fully understood. The ability to measure hull separated vortices associated with vehicle maneuvering does not exist at present. The existing point-by-point measurement techniques can only capture approximately the large 'mean' eddies but fail to meet the dynamics of small vortices during the initial stage of generation. A new technique, which offers a previously unavailable capability to measure the unsteady cross-flow distribution in the plane of the laser light sheet, is called Particle Displacement Velocimetry (PDV). PDV consists of illuminating a thin section of the flowfield with a pulsed laser. The water is seeded with microscopic, neutrally buoyant particles containing imbedded fluorescing dye which responds with intense spontaneous fluorescence with the illuminated section. The seeded particles in the vortical flow structure shed by the underwater vehicle are illuminated by the pulse laser and the corresponding particle traces are recorded in a single photographic frame. Two distinct approaches were utilized for determining the velocity distribution from the particle traces. The first method is based on matching the traces of the same particle and measuring the distance between them. The direction of the flow can be identified by keeping one of the pulses longer than the other. The second method is based on selecting a small window within the image and finding the mean shift of all the particles within that region. The computation of the auto-correlation of the intensity distribution within the selected sample window is used to determine the mean displacement of particles. The direction of the flow is identified by varying the intensity of the laser light between pulses. Considerable computational resources are required to compute the auto-correction of the intensity distribution. Parallel processing will be employed to speed up the data reduction. A few examples of measured unsteady vortical flow structures shed by the underwater vehicles will be presented.

Huang, Thomas T.↗
DOE OSTI2024

PDV Sensitivity [Slides]

The concept of PDV sensitive is not new. But we tend not to discuss sensitivity in a rigorous, quantified way. That should change. Indeed there is a natural definition, which is just the energy of light from the target within the analysis window that gives a SNR of 10 in the frequency domain. Systems designers, diagnostic engineers, and operators should use the language of sensitivity: (1) Absolute sensitivity: nW * ns; (2) Launch power: mW or dBm; (3) Relative surface return: dB; (4) Relative sensitivity: dB * ns. This will help us design better systems, choose the correct system for the job, maintain our systems, and tune our systems.

47 OTHER INSTRUMENTATION↗
DOE OSTI2021

Godiva IER268 PDV Measurements

PowerPoint slides providing a quick-look of photon Doppler velocimetry (PDV) data taken during a series bursts using the Godiva machine located at the NNSS Device Assembly Facility. Vibrations, or ringing, of approximately 7.2 to 7.8 kHz were observed.

47 OTHER INSTRUMENTATION↗
DOE OSTI2025

Modeling and Design of a Sub-Nyquist PDV Digitization System

Photon-Doppler Velocimetry (PDV) uses interferometry of a transmitted optical signal reflected from a fast-moving device under test (DUT) to generate a product signal at a doppler shifted frequency which is proportional to the velocity of the object being measured. The technique has applications in shock physics, where it is used to measure fast-moving objects over a short lifespan of travel, such as a bullet, shrapnel, or other shock accelerated object.

42 ENGINEERING↗
DOE OSTI2025

PDV Methods and Analysis for Surveillance of Explosive Components

The Weapons Evaluation Test Laboratory (WETL) at Sandia is collaborating with Lawrence Livermore National Laboratory (LLNL) to enhance explosive surveillance testing by integrating Photon Doppler Velocimetry (PDV) data. This project has streamlined the testing environment, reducing hardware costs and training needs while improving data collection efficiency and usability for lab technicians.

Kress, Matthew Kip [Sandia National Laboratories (↗