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At least 469 records · Page 26

Micropulsed Plasma Thrusters for Attitude Control of a Low-Earth-Orbiting CubeSat

This study presents a 3-Unit CubeSat design with commercial-off-the-shelf hardware, Teflon-fueled micropulsed plasma thrusters, and an attitude determination and control approach. The micropulsed plasma thruster is sized by the impulse bit and pulse frequency required for continuous compensation of expected maximum disturbance torques at altitudes between 400 and 1000 km, as well as to perform stabilization of up to 20 deg /s and slew maneuvers of up to 180 deg. The study involves realistic power constraints anticipated on the 3-Unit CubeSat. Attitude estimation is implemented using the q method for static attitude determination of the quaternion using pairs of the spacecraft-sun and magnetic-field vectors. The quaternion estimate and the gyroscope measurements are used with an extended Kalman filter to obtain the attitude estimates. Proportional-derivative control algorithms use the static attitude estimates in order to calculate the torque required to compensate for the disturbance torques and to achieve specified stabilization and slewing maneuvers or combinations. The controller includes a thruster-allocation method, which determines the optimal utilization of the available thrusters and introduces redundancy in case of failure. Simulation results are presented for a 3-Unit CubeSat under detumbling, pointing, and pointing and spinning scenarios, as well as comparisons between the thruster-allocation and the paired-firing methods under thruster failure.

Gatsonis, Nikolaos A.↗

Understanding the Role of 𝛼 Particles in Oblique Heliospheric Shock Oscillations

Recent observations by DSCOVR provide high temporal resolution (50 samples per second) magnetic vector field data that allows investigating the details of oblique heliospheric shock oscillations. It was found that some of these shocks exhibit magnetic oscillations, both downstream and upstream of the shock front. The DSCOVR/MAG magnetic field data are supplemented by an extensive database of low Mach number (M < 3) low‐β (<1) shock data observed by Wind albeit with lower temporal resolution. Motivated by the observations, we use the 2.5D hybrid model of the oblique shocks with α particles in addition to kinetic protons and electron fluid. We model the properties of the oblique shocks for a number of typical parameters found in observations and study the effects of the shock parameters and the relative α particle abundances on the properties of the shock magnetic field, density, and velocity oscillations. We find the α particles “surf” on the shock front and produce a wake of density oscillations. We examine the details of the phase space of the ions as well as the ion velocity distribution functions in various parts of the shock and study their nonthermal properties. We determine the effects of the α particle kinetic properties and abundances on the structure and dynamics of the shock downstream oscillations for a range of parameters relevant to low Mach number low‐β heliospheric shocks.

Ofman, L.↗

Update on the Juncture Flow PIV Results and Future Plans

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, 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 captured 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 ional insight gained during this effort will help guide system improvements for the upcoming entry in 2020.

Jenkins, Luther N.↗

Search Enhancements using Natural Language Processing Techniques

NASA Goddard Earth Sciences Data and Information Services Center (GESDISC) is one of the 12 NASA Science Mission Directorate Data Centers. The main goal of GESDISC is to provide earth science data, information, and services to the earth science data community. Consequently, data discovery is at the center of our mission and our search engine is the primary tool for our users to interact, find, and access our data. Existing search approaches are largely focused on hard-matching of keywords in the search query with dataset metadata. Here we propose to expand the search by introducing a complementary natural language processing (NLP) search. At the heart of our proposed NLP search, we trained a joint embedding using scientific text corpus and a curated set of dataset metadata. The embedding learns the association between words in our dataset metadata and those of the scientific text corpus. This enables us to go beyond simple hard-matching of a query and data set metadata and have a notion of “similarity” between the search query and the datasets. We further integrated our NLP search into the Elastic Search (ES) framework leveraging similarity search capabilities offered through the “dense_vector” field type. Our preliminary evaluations show that our proposed NLP search has the potential to be utilized to complement the existing search engine and serve as a base for a dataset recommendation system.

Armin Mehrabian↗

Dense Feature Tracking of Atmospheric Winds with Deep Optical Flow

Atmospheric winds are a key physical phenomenon impacting natural hazards, energy transport, ocean currents, large-scale circulation, and ecosystem fluxes. Observing winds is a complex process and presents a large gap in NASA’s Earth Observation System. Atmospheric motion vectors (AMVs) aim to fill this gap by making numerical estimates of cloud movement between sequences of multi-spectral satellite images, tracking clouds and water vapor. Recent imaging hardware and software advancements have enabled the use of numerical optical flow techniques to produce accurate and dense vector fields outperforming traditional methods. This work presents WindFlow as the first machine learning based system for feature tracking atmospheric motion using optical flow. Due to the lack of large-scale satellite-based observations, we leverage high-resolution numerical simulations from NASA's GEOS-5 Nature Run to perform supervised learning and transfer to satellite images. We demonstrate that our approach using deep learning based optical flow scales to ultra-high-resolution images of size 2881x5760 with less than 1 m/s bias and 2.5 m/s average error. Four network and learning architectures are compared and it is found that recurrent all-pairs field transforms (RAFT) produces the lowest errors on all metrics for wind speed and direction. Results on held out numerical outputs shows RAFT's good performance in each of the spatial, temporal, and physical dimensions. A comparison between WindFlow and an operational AMV product against rawinsonde observations show that RAFT transfers across simulations and thermal infrared satellite observations. This work shows that machine learning based optical flow is an efficient approach to generating robust feature tracking for AMVs consistently over large regions.

Atmospheric winds↗

Identification of Flux Rope Orientation via Neural Networks

Geomagnetic disturbance forecasting is based on the identification of solar wind structures and accurate determination of their magnetic field orientation. For nowcasting activities, this is currently a tedious and manual process. Focusing on the main driver of geomagnetic disturbances, the twisted internal magnetic field of interplanetary coronal mass ejections (ICMEs), we explore a convolutional neural network’s (CNN) ability to predict the embedded magnetic flux rope’s orientation once it has been identified from in situ solar wind observations. Our work uses CNNs trained with magnetic field vectors from analytical flux rope data. The simulated flux ropes span many possible spacecraft trajectories and flux rope orientations. We train CNNs first with full duration flux ropes and then again with partial duration flux ropes. The former provides us with a baseline of how well CNNs can predict flux rope orientation while the latter provides insights into real-time forecasting by exploring how accuracy is affected by percentage of flux rope observed. The process of casting the physics problem as a machine learning problem is discussed as well as the impacts of different factors on prediction accuracy such as flux rope fluctuations and different neural network topologies. Finally, results from evaluating the trained network against observed ICMEs from Wind during 1995–2015 are presented.

Thomas Narock↗

Voyager 1 and 2 Preliminary Observations Within Interplanetary Space of Upstream Suprathermal < 6 KeV Electrons Evidently Connected to Jupiter’s Bow Shock

We present for the first time the Voyager 1 and 2 plasma instrument observations within the interplanetary space of upstream suprathermal E < 6 keV electrons during times when close < 100 RJ from Jupiter’s bow shock. These measurements are a biproduct of our recovery of the Voyager Jupiter flyby measurements of the plasma electrons made by the Plasma Science Experiment (PLS) (Bridge et al., 1977). The initial ion and electron plasma observations were first reported by Bridge et al. (1979a, b). The periods were chosen to follow those reported by Zwickl et al. (1981) using energetic particle data with E ≥ 30 keV from the Low Energy Charged Particle (LECP) instrument (Krimigis et al., 1977). For this study we also use Voyager magnetic field data (Ness et al., 1979a, b) which is critical for this study. Basically, whenever the interplanetary magnetic field is nearly radially aligned relative to the spacecraft sun line, connection to the Jovian bow shock is believed to occur and one would expect those times when the keV suprathermal electron would be observed, but we also see them when the field is not radial but close to Jupiter’s bow shock. Whenever the magnetic field is radial the plasma instrument’s D cup or side sensor, which makes the electron observations (10 eV ≤ E ≤ 6 keV), is viewing ∼ 90 degree pitch angle electrons but evidently its wide field-of-view (FOV) allows one to see the keV electrons assumed to be field aligned. So, we will be looking into FOV alignment issues relative to the local magnetic field vector and any evidence for pitch angle scattering by plasma waves (see Scarf et al., 1981) that might broaden their width in pitch angle and allow their detection.

E C Sittler, Jr↗

Automatic Detection and Classification of Aurora in THEMIS All‐Sky Images

We report a novel machine-learning algorithm for automatically detecting and classifying aurora in all–sky images (ASI) that is largely trained without requiring ground–truth labels. By including a small number of labeled images, we are able to automatically label all of the approximately 700 million images in the Time History of Events and Macroscale Interactions during Substorms (THEMIS) ASI data set from 2008 to 2022. We use a two–stage approach. In the first stage, we adapt the Simple framework for Contrastive Learning of Representations (SimCLR) algorithm to learn latent representations of THEMIS all–sky images. We then finetune a classifier network on the latent representations our model learns of the manually labeled Oslo aurora THEMIS (OATH) data set. We demonstrate that this two–stage approach achieves excellent classification results on data for which there is no current ML classification benchmark. The outcome of this work will facilitate efficient information retrieval for researchers interested in specific categories of aurora and will enable large scale statistical studies and machine learning analyses of THEMIS all–sky images that have not previously been possible. To demonstrate possible ways to utilize this database, we performed a statistical analysis of the occurrence rates of auroral labels with respect to solar wind parameters, interplanetary magnetic field vector, and geomagnetic indices. We further investigate the occurrence rates of auroral phenomena in the annotated data set and their geoeffectiveness by utilizing the co–located THEMIS ground magnetometer data set.

Jeremiah W Johnson↗

Direct observation of 3D topological spin textures and their interactions using soft x-ray vector ptychography

Magnetic topological defects are energetically stable spin configurations characterized by symmetry breaking. Vortices and skyrmions are two well-known examples of 2D spin textures that have been actively studied for both fundamental interest and practical applications. However, experimental evidence of the 3D spin textures has been largely indirect or qualitative to date, due to the difficulty of quantitively characterizing them within nanoscale volumes. Here, we develop soft x-ray vector ptychography to quantitatively image the 3D magnetization vector field in a frustrated superlattice with 10 nm spatial resolution. By applying homotopy theory to the experimental data, we quantify the topological charge of hedgehogs and anti-hedgehogs as emergent magnetic monopoles and probe their interactions inside the frustrated superlattice. We also directly observe virtual hedgehogs and anti-hedgehogs created by magnetically inert voids. We expect that this new quantitative imaging method will open the door to study 3D topological spin textures in a broad class of magnetic materials. Our work also demonstrates that magnetically frustrated superlattices could be used as a new platform to investigate hedgehog interactions and dynamics and to exploit optimized geometries for information storage and transport applications.

Rana, A↗

Lepto-axiogenesis in minimal $\mathrm{SUSY}$ $\mathrm{KSVZ}$ model

We study the lepto-axiogenesis scenario in the minimal supersymmetric KSVZ axion model. Only one Peccei-Quinn (PQ) field and vector-like fields are introduced besides the MSSM with the type-I see-saw mechanism. The PQ field is stabilized by the radiative correction induced by the Yukawa couplings with the vector-like fields introduced in the KSVZ model. We develop a way to follow the dynamics of the PQ field, in particular we found a semi-analytical solution which describes the rotational motion under the log-arithmic potential with including the thermalization effect via the gluon scattering which preserves the PQ symmetry. Based on the solution, we studied the baryon asymmetry, the effective number of neutrino, and the dark matter density composed of the axion and the neutralino. We found that the baryon asymmetry is successfully explained when the mass of PQ field is $\mathcal{O}$(10 6 GeV) ($\mathcal{O}$(10 5 GeV)) with the power of the PQ breaking term being 10 (8).

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

Magnetic field configuration associated with solar gamma ray flares in June, 1991

The vector magnetic field configuration of the solar active region AR 6659 that produced very high levels of flare activity in Jun. 1991 is described. The morphology and evolution of the photospheric fields are described for the period 7-10 Jun., and the flares taking place around these dates and their locations relative to the photospheric fields are indicated. By comparing the observed vector field with the potential field calculated from the observed line-of-sight flux, we identify the nonpotential characteristics of the fields along the magnetic neutral lines where the flares were observed. These results are compared with those from the earlier study of gamma-ray flares.

Hagyard, M. J.↗

On the effects of grid ill-conditioning in three dimensional finite element vector potential magnetostatic field computations

The effects of finite element grid geometries and associated ill-conditioning were studied in single medium and multi-media (air-iron) three dimensional magnetostatic field computation problems. The sensitivities of these 3D field computations to finite element grid geometries were investigated. It was found that in single medium applications the unconstrained magnetic vector potential curl-curl formulation in conjunction with first order finite elements produce global results which are almost totally insensitive to grid geometries. However, it was found that in multi-media (air-iron) applications first order finite element results are sensitive to grid geometries and consequent elemental shape ill-conditioning. These sensitivities were almost totally eliminated by means of the use of second order finite elements in the field computation algorithms. Practical examples are given in this paper to demonstrate these aspects mentioned above.

Wang, R.↗

Data Analysis for the SOLIS Vector Spectromagnetograph

The National Solar Observatory's SOLIS Vector Spectromagnetograph (VSM), which will produce three or more full-disk maps of the Sun's photospheric vector magnetic field every day for at least one solar magnetic cycle, is in the final stages of assembly. Initial observations, including cross-calibration with the current NASA/NSO spectromagnetograph (SPM) will soon be carried out at a test site in Tucson. This paper discusses data analysis techniques for reducing the raw data, calculation of line-of-sight magnetograms and both quick-look and high-precision inference of vector fields from Stokes spectral profiles. Existing SPM algorithms, suitably modified to accomodate the cameras, scanning pattern, and polarization calibration optics for the VSM, will be used to "clean" the raw data and to process line-of-sight, magnetograms. A recent. version of the High Altitude Observatory Milne-Eddington (HAO-ME) inversion code (Skumanich and Lites; 1987, 11)J 322, p. 473) will he used for high-precision vector fields since the algorithm has been extensively tested, is well understood, and is fast enough to complete data analysis within 24 hours of data acquisition. The simplified inversion algorithm of Auer, Heasley. arid House (1977, Sol. Phys. 55, p. 47) forms the initial guess for this version of the HAO-ME code and will be used for quick-look vector analysis of VSM data since its performance on simulated Stokes profiles is better than other candidate methods. Improvements (e.g., principal components analysis or neural networks) are under consideration and will be straightforward to implement. However, current resources are sufficient to store the original Stokes profiles only long enough for high-precision analysis. Retrospective reduction of Stokes data with improved methods will not be possible, and modifications will only be introduced when the advantages of doing so are compelling enough to justify discontinuity in the long-term data stream.

Jones, Harrison P.↗

Spin alignment of vector mesons by glasma fields

We explain how spin alignment of vector mesons can be induced by background fields, such as electromagnetic fields or soft gluon fields. Our study is based on the quantum kinetic theory of spinning quarks and antiquarks and incorporates the relaxation of the dynamically generated spin polarization. The spin density matrix of vector mesons is obtained by quark coalescence via the Wigner function and kinetic equation. Our approach predicts a local spin correlation that is distinct from the nonlocal expressions previously obtained in phenomenological derivations. We estimate the magnitude of such local correlations in the glasma model of the preequilibrium phase of relativistic heavy ion collisions. It is found that the resulting spin alignment could be greatly enhanced and may be comparable to the experimental measurement in order of magnitude. We further propose new phenomenological scenarios to qualitatively explain the transverse-momentum and centrality dependence of spin alignment in a self-consistent framework.

79 ASTRONOMY AND ASTROPHYSICS↗

DC Electric Fields and Associated Plasma Drifts Observed with the C/NOFS Satellite

Initial DC electric field observations and associated plasma drifts are presented from the Vector Electric Field Investigation (VEFI) on the Air Force Communication/Navigation Outage Forecasting System (C/NOFS) satellite. We present statistical averages of the vector fields for the first year of operations that include both the zonal and radial components of the resulting E x B plasma flows at low latitudes. Magnetic field data from the VEFI science magnetometer are used to compute the plasma flows. The DC electric field detector reveals zonal and radial electric fields that undergo strong diurnal variations, typically displaying eastward and outward-directed fields during the day and westward and downward-directed fields at night. There is considerable variation in the large scale DC electric field data, in both the daytime and nighttime cases, with enhanced structures typically observed at night. In general, the measured zonal DC electric field amplitudes include excursions that extend within the 0.4 - 2 m V/m range, corresponding to E x B drifts of the order of 30-150 m/s. The average vertical or radial electric fields may exceed the zonal fields in amplitude by a factor of 1.5 to 2. Although the data compare well, in a general sense, with previous satellite observations and statistical patterns of vertical ion drifts, the E x B drifts we report from C/NOFS rarely show a pronounced pre-reversal enhancement after sunset. We attribute this to a combination of extreme solar minimum conditions and the fact that the C/NOFS orbit of 401 by 867 km carries the probes essentially above the lower altitude regions where the wind-driven dynamo might be expected to create enhanced upwards drifts in the early evening. Evidence for wavenumber 4 tidal effects and other longitudinal signatures have been detected and will be presented. We also discuss off-equatorial electric fields and their relation to the ambient plasma density.

Pfaff, R.↗

DC and Structured Electric Fields Observed on the C/NOFS Satellite and Their Association with Longitude, Plasma Density, and Solar Activity

Observations of DC electric fields and associated E x B plasma drifts gathered by the Vector Electric Field Investigation (VEFI) on the Air Force Communication/Navigation Outage Forecasting System (C/NOFS) satellite are presented. We show statistical averages of the vector fields and resulting E x B plasma flows for the first three years of operations as a function of season, longitude, local time, and Fl 0.7 conditions. Magnetic field data from the VEFI science magnetometer are used to compute the plasma flows. Although typically displaying eastward and outward-directed fields during the day and westward and downward-directed fields at night, the data from DC electric field detector often reveal variations from this pattern that depend on longitude, solar activity, and plasma density. Clear "wave-4" tidal effects in both electric field components have been detected and will be presented. Zonal plasma drifts show a marked variation with solar activity and may be used as a proxy for neutral winds at night. Evidence for pre-reversal enhancements in the meridional drifts that depend on solar activity is present for some longitudes, and are corroborated by clear evidence in the plasma density data that the spacecraft journeyed below the F-peak during evenings when the rise in the ionosphere is most pronounced. In addition to DC electric fields, the data reveal considerable electric field structures at large scales (approx 100's of km) that are usually confined to the nightside. Although such electric field structures are typically associated with plasma density depletions and structures, what is surprising is the number of cases in which large amplitude, structured DC electric fields are observed without a significant plasma density counterpart structure, including their appearance at times when the ambient plasma density appears relatively quiescent. We investigate the mapping of structured electric fields along magnetic field lines from distant locations and consider tropospheric thunderstorm sources to explain some of the observations. The dependence of the structuring on season and solar activity will be reported and discussed.

Pfaff, Robert↗

The Z3 model of Saturns magnetic field and the Pioneer 11 vector helium magnetometer observations

Magnetic field observations obtained by the Pioneer 11 vector helium magnetometer are compared with the Z(sub 3) model magnetic field. These Pioneer 11 observations, obtained at close-in radial distances, constitute an important and independent test of the Z(sub 3) zonal harmonic model, which was derived from Voyager 1 and Voyager 2 fluxgate magnetometer observations. Differences between the Pioneer 11 magnetometer and the Z(sub 3) model field are found to be small (approximately 1%) and quantitatively consistent with the expected instrumental accuracy. A detailed examination of these differences in spacecraft payload coordinates shows that they are uniquely associated with the instrument frame of reference and operation. A much improved fit to the Pioneer 11 observations is obtained by rotation of the instrument coordinate system about the spacecraft spin axis by 1.4 degree. With this adjustment, possibly associated with an instrumental phase lag or roll attitude error, the Pioneer 11 vector helium magnetometer observations are fully consistent with the Voyager Z(sub 3) model.

Connerney, J. E. P.↗