Engineering Papers⌕ Search

SEARCH · Engineering Papers

Results for “velocity map imaging”

Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

Quote a phrase for an exact phrase match. Source license links do not imply unrestricted reuse.

At least 217 records · Page 12

Overview of Terrain Relative Navigation Approaches for Precise Lunar Landing

The driving precision landing requirement for the Autonomous Landing and Hazard Avoidance Technology project is to autonomously land within 100m of a predetermined location on the lunar surface. Traditional lunar landing approaches based on inertial sensing do not have the navigational precision to meet this requirement. The purpose of Terrain Relative Navigation (TRN) is to augment inertial navigation by providing position or bearing measurements relative to known surface landmarks. From these measurements, the navigational precision can be reduced to a level that meets the 100m requirement. There are three different TRN functions: global position estimation, local position estimation and velocity estimation. These functions can be achieved with active range sensing or passive imaging. This paper gives a survey of many TRN approaches and then presents some high fidelity simulation results for contour matching and area correlation approaches to TRN using active sensors. Since TRN requires an a-priori reference map, the paper concludes by describing past and future lunar imaging and digital elevation map data sets available for this purpose.

Terrain Relative Navigation (TRN)↗

Overview of terrain relative navigation approaches for Precise Lunar Landing

The driving precision landing requirement for the Autonomous Landing and Hazard Avoidance Technology project is to autonomously land within 100m of a predetermined location on the lunar surface. Traditional lunar landing approaches based on inertial sensing do not have the navigational precision to meet this requirement. The purpose of Terrain Relative Navigation (TRN) is to augment inertial navigation by providing position or bearing measurements relative to known surface landmarks. From these measurements, the navigational precision can be reduced to a level that meets the 100m requirement. There are three different TRN functions: global position estimation, local position estimation and velocity estimation. These functions can be achieved with active range sensing or passive imaging. This paper gives a survey of many TRN approaches and then presents some high fidelity simulation results for contour matching and area correlation approaches to TRN using active sensors. Since TRN requires an a-priori reference map, the paper concludes by describing past and future lunar imaging and digital elevation map data sets available for this purpose.

Montgomery, James F.↗

Physics-informed neural networks for identification of material properties using standing waves

A metallic structure in its initial stage of failure involves plastic deformation or environmental degradation that changes the elastic modulus and density. This work presents the detection of change in wave velocity (a function of elastic modulus and density) as a system identification problem. A physics-informed neural network (PINN) is proposed to solve the system identification problem. The PINN takes the spatial coordinates of scanning locations and time as inputs and provides the displacement and wave velocity as outputs. The governing partial differential equation of standing waves in a rod is incorporated into the neural network as physics in the form of a loss function. The wave velocity vector is randomly initiated. During the training of the network, physics is used to determine and update the wave velocity target vector from the network’s displacement predictions. The measured data, comprising sparse displacement response on the rod structure, are used to train the PINN. The wave velocity at the sparse locations on the rod is learned from the predicted displacements during the training. Using the predictions of the trained network, the response of free vibration or material property variation can be reconstructed at unscanned locations on the structure to obtain high-resolution maps for full-field imaging to detect and localize the changes caused by plastic deformation. The PINN’s sparse scanning and simultaneous prediction capability during training can lead to high scanning and data-processing speeds. This capability yields a nondestructive evaluation system that can predict the presence of degraded material locations as the structural vibrations are scanned and processed in real time.

Rathod, Vivek↗

Seismic monitoring of a small CO 2 injection using a multi-well DAS array: Operations and initial results of Stage 3 of the CO 2 CRC Otway project

Active time-lapse seismic is widely employed for monitoring CO 2 geosequestration due to its ability to track the distribution of fluids in space and time. However, standard 4D seismic monitoring suffers from several challenges, including high cost, disruption to other land uses, and, consequently, relatively large intervals between monitor surveys. Some of these challenges can be mitigated using permanently installed sources and receivers. Such an approach was tested at the CO 2 CRC Otway site by continuous offset VSP monitoring of 15,000 t of supercritical CO 2 injected into an aquifer 1,500 m deep with nine permanent seismic sources (surface orbital vibrators or SOVs) and five downhole fibre-optic receivers. This continuous monitoring is complemented by multi-well 4D VSP using a mobile vibroseis source and the same DAS receivers, which included one baseline and two monitor surveys after injection of 4,000 and 12,000 t of CO 2 . The continuous DAS-SOV monitoring detected an abrupt increase of travel times below the injection interval on the second day of injection (after injection of 300 t of CO 2 ) and tracked the growth of the areal CO 2 plume by mapping changes of reflection amplitudes. The plume is also detected by time-lapse changes of reflection amplitudes in multi-well 4D VSPs. The plume images obtained from continuous offset VSP and 4D VSP are broadly consistent with each other but with some differences due to differences in illumination, lateral variations of velocities and seismic anisotropy. Furthermore, these differences also serve as a measure of uncertainty of 4D VSP images.

4D VSP↗

Multi-line FLEET by imaging periodic masks

A simple linear configuration for multi-line FLEET velocimetry is used for the first time to image an overexpanded unsteady supersonic jet. The FLEET lines are spaced 0.5-1.0 mm apart and up to six lines can simultaneously be used to visualize the flowfield. These lines are created using periodic masks, despite the mask blocking 25 — 30% of the 10 mJ incident beam. Maps of mean single-component velocity in the direction along the principal flow axis, and turbulence intensity in that same direction, are created using multi-line FLEET, and computed velocities agree well with that obtained from single-line (traditional) FLEET. Compared to traditional FLEET, multi-line FLEET offers increased simultaneous spatial coverage and the ability to produce spatial correlations in the streamwise direction. This FLEET permutation is especially well-suited for short-duration test facilities

42 ENGINEERING↗

Autonomous Navigation Results from the Mars Exploration Rover (MER) Mission

In January, 2004, the Mars Exploration Rover (MER) mission landed two rovers, Spirit and Opportunity, on the surface of Mars. Several autonomous navigation capabilities were employed in space for the first time in this mission. ]n the Entry, Descent, and Landing (EDL) phase, both landers used a vision system called the, Descent Image Motion Estimation System (DIMES) to estimate horizontal velocity during the last 2000 meters (m) of descent, by tracking features on the ground with a downlooking camera, in order to control retro-rocket firing to reduce horizontal velocity before impact. During surface operations, the rovers navigate autonomously using stereo vision for local terrain mapping and a local, reactive planning algorithm called Grid-based Estimation of Surface Traversability Applied to Local Terrain (GESTALT) for obstacle avoidance. ]n areas of high slip, stereo vision-based visual odometry has been used to estimate rover motion, As of mid-June, Spirit had traversed 3405 m, of which 1253 m were done autonomously; Opportunity had traversed 1264 m, of which 224 m were autonomous. These results have contributed substantially to the success of the mission and paved the way for increased levels of autonomy in future missions.

autonomous↗

A TOPAS model for lens-based proton radiography

Abstract Objective. Proton Radiography can be used in conjunction with proton therapy for patient positioning, real-time estimates of stopping power, and adaptive therapy in regions with motion. The modeling capability shown here can be used to evaluate lens-based radiography as an instantaneous proton-based radiographic technique. The utilization of user-friendly Monte Carlo program TOPAS enables collaborators and other users to easily conduct medical- and therapy- based simulations of the Los Alamos Neutron Science Center (LANSCE). The resulting transport model is an open-source Monte Carlo package for simulations of proton and heavy ion therapy treatments and concurrent particle imaging. Approach. The four-quadrupole, magnetic lens system of the 800-MeV proton beamline at LANSCE is modeled in TOPAS. Several imaging and contrast objects were modelled to assess transmission at energies from 230–930 MeV and different levels of particle collimation. At different proton energies, the strength of the magnetic field was scaled according to βγ, the inverse product of particle relativistic velocity and particle momentum. Main results. Materials with high atomic number, Z, (gold, gallium, bone-equivalent) generated more contrast than materials with low-Z (water, lung-equivalent, adipose-equivalent). A 5-mrad collimator was beneficial for tissue-to-contrast agent contrast, while a 10-mrad collimator was best to distinguish between different high-Z materials. Assessment with a step-wedge phantom showed water-equivalent path length did not scale directly according to predicted values but could be mapped more accurately with calibration. Poor image quality was observed at low energies (230 MeV), but improved as proton energy increased, with sub-mm resolution at 630 MeV. Significance. Proton radiography becomes viable for shallow bone structures at 330 MeV, and for deeper structures at 630 MeV. Visibility improves with use of high-Z contrast agents. This modality may be particularly viable at carbon therapy centers with accelerators capable of delivering high energy protons and could be performed with carbon therapy.

60 APPLIED LIFE SCIENCES↗

Flow pattern and void fraction characterization in nitrogen/water flows through a diamond-type triply periodic minimal surface lattice

Here, this study presents, to the authors knowledge, the first experimental investigation on the void fraction and flow patterns in two-phase flows through a diamond-type Triply Periodic Minimal Surface (TPMS) lattice. An additively manufactured TPMS structure was tested under upward co-current flow of a water/nitrogen mixture. Superficial velocities varied for a total of 42 test conditions (gas: 0.01–2.4 m/s; liquid: 0.01–2.4 m/s; mass flux: 20–2370 kg/m 2 ·s). High-speed video and X-ray imaging enabled time-averaged void fraction measurements and identified six distinct flow regimes which were used to develop a flow pattern map. Comparison of the void fraction data with correlations from literature demonstrated the Rouhani and Axelsson (1970) [49] correlation modified by Steiner (1993) [52] provided the best agreement, which was improved with empirically fit coefficients. This approach predicted the void fraction with errors < ±20% for 64% of the data, with a mean absolute percent deviation (MAPD) of 23%. The measured frictional pressure drop was compared to correlations from literature which captured the observed trends but did not provide good accuracy. The best agreement was found after optimizing the empirical coefficients of the Muller-Steinhagen & Heck (1986) [56] correlation; this approach captured 33% of the data within ±20% with a MAPD of 46% over the full range and captured 71% of the data within ±20% a MAPD of 13.3% at mass fluxes >1100 kg/m 2 -s. These results provide foundational insight into TPMS two-phase flow behavior and inform modeling and design of advanced heat exchange components incorporating TPMS geometries.

42 - ENGINEERING↗

A physics-informed and hierarchically regularized data-driven model for predicting fluid flow through porous media

This paper presents a new deep learning data-driven model for predicting structure dependent pore-fluid velocity fields in rock. The model is based on a Convolutional Auto-Encoder (CAE) artificial neural network capable of learning from image data generated by direct numerical simulations of fluid flow through pore-structures, such as by Lattice Boltzmann or molecular dynamics methods. The main novelty of the model in comparison to previous CAE-based data-driven approaches consists of three parts. The first is a methodology for decomposing the full-domain of the porous media into sub-regions, or “sub-domains”, in order to reduce the overall size of the CAE, batch process the sub-domains in parallel, and enable the CAE to learn local and generalizable nonlinear mappings of pore-fluid velocities. The second consists of embedding the finite difference solutions of the incompressible Navier-Stokes and continuity equations into convolutional layers prior to the CAE in order to provide the CAE with knowledge of fluid dynamics physics (PhyFlow). The third main novelty is that the training of the CAE is regularized with a hierarchical loss function that encourages the learning of fluid flow patterns (in a way similar to ranked modes in principal component analysis), ranking from most to least important. This is shown to increase the stability in learning, reduce over-fitting, and promote interpretability of the CAE neural network layers (HierCAE). The comprehensive new data-driven model, which we call the PhyFlow-HierCAE model, is shown to exhibit improved accuracy and generalizability of flow field predictions over conventional CAE models, attributable to the embedded physical knowledge and the hierarchical regularization, as well as realize orders of magnitude speed-ups in computation times as a surrogate for the direct numerical simulations. Examples of training and forward predictions on unseen pore-structures are provided and evaluated for data from Lattice Boltzmann and molecular dynamics simulations of pore-fluid flow. The model is shown to be a fast and accurate emulator (or “surrogate”) for predicting effective permeability of unseen pore-structures based on learning from relatively small direct numerical simulation datasets.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

Surge Flow in a Centrifugal Compressor Measured by Digital Particle Image Velocimetry

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.

Wernet, Mark P.↗

Electronic interactions in Dirac fluids visualized by nano-terahertz spacetime interference of electron-photon quasiparticles

Ultraclean graphene at charge neutrality hosts a quantum critical Dirac fluid of interacting electrons and holes. Interactions profoundly affect the charge dynamics of graphene, which is encoded in the properties of its electron-photon collective modes: surface plasmon polaritons (SPPs). Here, we show that polaritonic interference patterns are particularly well suited to unveil the interactions in Dirac fluids by tracking polaritonic interference in time at temporal scales commensurate with the electronic scattering. Spacetime SPP interference patterns recorded in terahertz (THz) frequency range provided unobstructed readouts of the group velocity and lifetime of polariton that can be directly mapped onto the electronic spectral weight and the relaxation rate. Our data uncovered prominent departures of the electron dynamics from the predictions of the conventional Fermi-liquid theory. The deviations are particularly strong when the densities of electrons and holes are approximately equal. The proposed spacetime imaging methodology can be broadly applied to probe the electrodynamics of quantum materials.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗

Axisymmetric Flow Properties for Magnetic Elements of Differing Strength

Aspects of the structure and dynamics of the flows in the Sun's surface shear layer remain uncertain and yet are critically important for understanding the observed magnetic behavior. In our previous studies of the axisymmetric transport of magnetic elements we found systematic changes in both the differential rotation and the meridional flow over the course of Solar Cycle 23. Here we examine how those flows depend upon the strength (and presumably anchoring depth) of the magnetic elements. Line of sight magnetograms obtained by the HMI instrument aboard SDO over the course of Carrington Rotation 2097 were mapped to heliographic coordinates and averaged over 12 minutes to remove the 5-min oscillations. Data masks were constructed based on the field strength of each mapped pixel to isolate magnetic elements of differing field strength. We used Local Correlation Tracking of the unmasked data (separated in time by 1- to 8-hours) to determine the longitudinal and latitudinal motions of the magnetic elements. We then calculated average flow velocities as functions of latitude and longitude from the central meridian for approx 600 image pairs over the 27-day rotation. Variations with longitude indicate and characterize systematic errors in the flow measurements associated with changes in the signal from disk center to limb. Removing these systematic errors reveals changes in the axisymmetric flow properties that reflect changes in flow properties with depth in the surface shear layer.

Rightmire-Upton, Lisa↗

Trajectory Reconstruction of the ST-9 Sounding Rocket Experiment Using IMU and Landmark Data

This paper presents trajectory reconstruction of the ST-9 sounding rocket experiment using the onboard IMU data and descent imagery. The raw IMU accelerometer measurements are first converted into inertial acceleration and then used in trajectory integration. The descent images are pre-processed using a map-matching algorithm and unique landmarks for each image are created. Using the converted IMU data and descent images, the result from dead-reckoning and the kinematic-fix approaches are first compared with the GPS measurements. Then, both the IMU data and landmarks are processed together using a batch least-squares filter and the position, velocity, stochastic acceleration, and camera orientation of each image are estimated. The reconstructed trajectory is compared with the GPS data and the corresponding formal uncertainties are presented. The result shows that IMU data and descent images processed with a batch filter algorithm provide the trajectory accuracy required for pin-point landing.

Park, Ryan S.↗

Characterization of Subsurface Flow Dynamics for Forecasting of Solar Activity

Evolution of large-scale magnetic field structures in the solar photosphere and corona is controlled by motions beneath the visible surface of the Sun. Subsurface plasma flows play a critical role in formation and evolution of active regions and their activity. We analyze subsurface flow maps provided by the local helioseismology pipeline from the Helioseismic and Magnetic Imager (HMI) data on board the Solar Dynamics Observatory, and investigate links between flow characteristics and magnetic activity. The primary goal is to determine flow descriptors, which can improve solar activity forecasts. In particular, by employing machine learning classifiers, we test how the flow helicity and velocity shear descriptors can improve the prediction of initiation of flares and CME eruptions.

Kosovichev, Alexander↗

Mapping of Glacial Motion and Surface Topography of Hielo Patagonico Norte, Chile, Using Satellite SAR L-band Interferometry Data

The first topographic and ice-motion maps of the northwestern flank of Hielo Patagonico Norte (HPN, northern Patagonia Icefield), in Chile, were produced using satellite synthetic-aperture interferometric radar data acquired by NASA's Spaceborne Imaging Radar C instrument in October 1994. The topographic map has a IO m vertical precision with a 30 m horizontal spacing, which should be sufficient to serve as a reference for monitoring future mass changes of the icefield. The ice-motion map is accurate to within 4 mm/ d (or 1/ ma). The radar-derived surface topography and ice velocity are used to estimate the ice discharge from the accumulation area of four outlet glaciers, and the calving flux and mass balance of Glaciar San Rafael. The results demonstrate the use of SAR interferometry for monitoring glaciological parameters on a spatial and temporal scale unattainable by any other means.

Rignot, Eric↗

Asymmetric Stokes-V Profiles at the Penumbral Boundary of a Sunspot

We present the spectropolarimetric measurements of a sunspot in the active region NOAA 6958 (15S03W), situated near the central meridian disk passage. The follower polarity sunspot was somewhat symmetrically round shaped with an elongated penumbra. There were several opposite polarity magnetic elements at, and beyond the penumbral boundary. The H-alpha images of the sunspot show the bright emission regions near the penumbral boundary towards the sun-center, which was of opposite polarity with respect to the main spot. The net-circular polarization (NCP) map shows that NCP is negative in the inner part of the spot and positive at the penumbral boundary and near the H-alpha plage. The Doppler velocities were determined by measuring the center-of-gravity (COG) of the Stokes-I profile and zero-crossing (ZC) wavelength of the Stokes-V profiles. The COG velocity map in general agrees with the Evershed flow. In addition, it shows the up flow in the penumbral region. The ZC velocities show the strong down flow at the penumbral boundary. Double-lobed Stokes-V profiles are observed at the locations, where the penumbral fibrils terminate coinciding the H-alpha plage. The Double lobed profiles had an unshifted component similar to the Stokes-V profiles of the sunspot penumbra and a shifted component with a velocity of about 5 km/s. The amplitude of the second component increases along the penumbral fibril as a function of the distance from the center of the sunspot. In this paper we discuss the role of emerging flux in generating the observed double lobed profiles. Based on our present observations, we propose to observe with the Solar-B Spectropolarimeter for understanding the nature of emerging flux near the sunspots.

Choudhary, Debi Prasad↗

New Space Domain Processing Technique for Pulsed Laser Velocimetry

A new and fast data processing technique for pulsed-laser-velocimetry data is described. A simplified cross correlation algorithm was developed which uses the time history information of the recorded particle images. It is shown that, the use of the particle time history information (which can be obtained using an electronic camera to record the particle exposures) facilitates high speed processing and unambiguous velocity vector information. It was found that a complex convection vortex flow can be recorded and completely processed in less than 2 min on a personal computer, producing a two-dimensional map of the flow field containing over 300 velocity vectors.

Wernet, Mark P.↗

Dynamic behavior of the Bering Glacier-Bagley icefield system during a surge, and other measurements of Alaskan glaciers with ERS SAR imagery

ERS-1 synthetic aperture radar (SAR) imagery was employed for the measurement of the dynamics of the Bagley icefield during a major surge in 1993-1994, the measurement of ice velocities on the Malaspina piedmont glacier during a quiescent phase between surges, and for mapping the snow lines and the position of the terminus of Nabesna glacier on Mount Wrangell (a 4317 m andesitic shield volcano) in the heavily glacierized Saint Elias and Wrangell Mountains of Alaska. An overview and summary of results is given. The methods used include interferometry, cross-correlation of sequential images, and digitization of boundaries using terrain-corrected SAR imagery.

Lingle, Craig S.↗