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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.

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At least 91 records · Page 5

Quantifiable Assessment of SWNT Dispersion in Polymer Composites

NASA LaRC has established a new protocol for visualizing the nanomaterials in structural polymer matrix resins. Using this new technique and reconstructing the 3D distribution of the nanomaterials allows us to compare this distribution against a theoretically perfect distribution. Additional tertiary structural information can now be obtained and quantified with the electron tomography studies. These tools will be necessary to establish the structural-functional relationships between the nano and the bulk. This will also help define the critical length scales needed for functional properties. Field ready tool development and calibration can begin by using these same samples and comparing the response. i.e. gold standards of good and bad dispersion.

Park, Cheol↗

Coronal Polarization of Pseudostreamers and the Solar Polar Field Reversal

The reversal of the solar polar magnetic field is notoriously hard to pin down due to the extreme viewing angle of the pole. In Cycle 24, the southern polar field reversal can be pinpointed with high accuracy due to a large-scale pseudostreamer that formed over the pole and persisted for approximately a year. We tracked the size and shape of this structure with multiple observations and analysis techniques including PROBA2/SWAP EUV images, AIA EUV images, CoMP polarization data, and 3D tomographic reconstructions. We find that the heliospheric field reversed polarity in February 2014, whereas in the photosphere, the last vestiges of the previous polar field polarity remained until March 2015. We present here the evolution of the structure and describe its identification in the Fe XII 1074nm coronal emission line, sensitive to the Hanle effect in the corona.

magnetic field↗

PERISCOPE: PERIapsis Subsurface Cave OPtical Explorer

In this NIAC report we present a new technique enabling a practical option for mapping these structures at a relatively low cost: Photon Time-of-Flight (PTOF) imaging. Consider a scene with a surface that is in a camera's line of sight, with unknown geometry beyond the line of sight. PTOF works by directing laser pulses onto the visible surface and detecting the returned light after it reflects off the visible surface, onto the hidden surfaces, and back to the detector. An algorithm then reconstructs a 3d model of the hidden surface. The information gained has a wide variety of applications across NASA, the scientific community, the burgeoning commercial space industry, and in commercial and industrial use here on Earth.

Exploration↗

Macro-Scale Findings of the DebriSat Debris Field Obtained from X-Rays of the Catch Panels

The DebriSat project analyzes the debris from a hypervelocity impact test conducted on a 56 kg-simulated satellite target in 2014. Its purpose is to generate a comprehensive database of the size, mass, material, shape, and the radar and optical properties of fragments generated from orbital collisions of modern-built spacecraft. Three hundred ninety-one foam catch panels from the DebriSat test have been X-rayed to locate the particles within them for subsequent extraction and assessment. The data from the tens of thousands of extracted particles has heretofore been the focus of the debris assessment. The work presented here connects the X-ray sample location images to reconstruct the 3D distribution of the entire fragment cloud. Although some errors are inherent to the process, this 3D database is valuable for qualitative studies of size and energy distributions. Further, the 3D database can indicate the extent of bending or breaking of the fragments as they decelerated to full capture. By virtue of its full sphere perspective, the 3D database allows graphical insight to the physics of the collision and breakup. This 3D representation has been developed as a “point and click” graphical interface to retrieve the full data set on individual recovered and assessed fragments within the growing database. Overall, this macro-level screening technique has added enormous insight to the experiment in unexpected ways.

Allen, Anthony↗

Expanding NeMO-Net Machine Learning Capabilities for Citizen Science

NASA NeMO-Net, the neural multi-modal observation and training network for global coral reef assessment, is an open-source deep convolutional neural network and interactive active learning training software aiming to accurately assess the present and past dynamics of coral reef ecosystems through determination of percent living cover and morphology as well as mapping of spatial distribution. We present an interactive citizen science video game, released this April, for desktop and iOS devices where users interactively label morphology classifications over mm-scale 3D coral reef imagery captured using diver photomosaic imagery, the UAV enabled NASA FluidCam instrument, and satellite datasets. To date, the application has had over 40,000 downloads and over 60,000 unique coral reef classifications, each filtered through a user-based rating and expert evaluation system. We also present results from NeMO-Net’s convolutional neural network (CNN) models used to semantically segment 2D satellite imagery as well as projections of 3D coral reconstructions using user input data as training datasets. Fusing datasets using machine learning from multiple remote sensing platforms presents novel methodologies for assessing the health of coral ecosystems, which are critically endangered by a changing climate. In partnering with Mission Blue, the National Oceanic and Atmospheric Administration (NOAA), and the Living Oceans Foundation (LOF), NeMO-Net leverages an international consortium of subject matter experts to provide both proper training for citizen scientists and the generation of a labeled datasets to ingest into machine learning algorithms for global coral reef identification.

NeMO-Net↗

Expanding NeMO-Net Machine Learning Capabilities for Citizen Science

NASA NeMO-Net, the neural multi-modal observation and training network for global coral reef assessment, is an open-source deep convolutional neural network and interactive active learning training software aiming to accurately assess the present and past dynamics of coral reef ecosystems through determination of percent living cover and morphology as well as mapping of spatial distribution. We present an interactive citizen science video game, released this April, for desktop and iOS devices where users interactively label morphology classifications over mm-scale 3D coral reef imagery captured using diver photomosaic imagery, the UAV enabled NASA FluidCam instrument, and satellite datasets. To date, the application has had over 40,000 downloads and over60,000 unique coral reef classifications, each filtered through a user-based rating and expert evaluation system. We also present results from NeMO-Net’s convolutional neural network (CNN) models used to semantically segment 2D satellite imagery as well as projections of 3D coral reconstructions using user input data as training datasets. Fusing datasets using machine learning from multiple remote sensing platforms presents novel methodologies for assessing the health of coral ecosystems, which are critically endangered by a changing climate. In partnering with Mission Blue, the National Oceanic and Atmospheric Administration (NOAA), and the Living Oceans Foundation (LOF), NeMO-Net leverages an international consortium of subject matter experts to provide both proper training for citizen scientists and the generation of a labeled datasets to ingest into machine learning algorithms for global coral reef identification.

NeMO-Net↗

Optical Navigation for Autonomous Approach of Small Unknown Bodies

State of the practice in navigation around small celestial bodies heavily relies on ground sup- port and human skill, in particular, for perception-based operations such as optical navigation and mapping. This leads to longer duration and more complex mission operations and sub- sequently higher cost. Furthermore, it imposes limitations for certain missions such as fast fly-bys or multi-agent operations. In this work, we present an autonomous navigation strat- egy suitable for approaching small unexplored bodies. During the approach, we estimate the body’s physical properties as well as the spacecraft’s relative trajectory and associated un- certainties. The autonomous navigation strategy, which is solely based on optical measure- ments, begins as soon as the body becomes resolved in the navigation camera and terminates at the start of proximity operations, when the spacecraft makes its first trajectory correction to stay in the vicinity of the body. Our strategy uses multiple image-processing algorithms: light-curve analysis for estimating the target body’s rotation rate, Shape-from-Silhouette for reconstructing the 3D shape and estimating its rotation pole, and feature tracking tailored to Small-Body images for estimating relative navigation parameters. We used the Mission Analysis, Operations, and Navigation Toolkit Environment (MONTE) developed by the Jet Propulsion Laboratory to evaluate the feasibility of this multi-phase navigation strategy using simulated images of an approach trajectory. We used the Rosetta mission data to generate photorealistic images to characterise the performance of this approach. This work is based on the assumptions that the spacecraft attitude is known, the body is a principal-axis rotator, a-priori estimates of ephemerides and scale are available, and the body is observed from a zero sun phase only during initial approach. Preliminary results show orbit determination performance that is on par with the human navigation from the Rosetta mission; albeit with a 1% bias in spacecraft-target radial distance estimate. The bias error is likely due to the robustness and accuracy of the visual tracking under dynamic lighting conditions and per- spective changes, which decrease accuracy.

Villa, Jacopo↗

Unveiling the Journey of A Highly Inclined CME: Insights from the March 13, 2012, Event With 110° Longitudinal Separation

Context. A fast (∼2000 km s -1 ) and wide (>110°) coronal mass ejection (CME) erupted from the Sun on March 13, 2012. Its interplanetary counterpart was detected in situ two days later by STEREO-A and near-Earth spacecraft, such as ACE, Wind, and Cluster. We suggest that at 1 au the CME extended at least 110° in longitude, with Earth crossing its east flank and STEREO-A crossing its- west flank. Despite their separation, measurements from both positions showed very similar in situ CME signatures. The solar source region where the CME erupted was surrounded by three coronal holes (CHs). Their locations with respect to the CME launch site were east (negative polarity), southwest (positive polarity) and west (positive polarity). The solar magnetic field polarity of the area covered by each CH matches that observed at 1 au in situ. Suprathermal electrons at each location showed mixed signatures with only some intervals presenting clear counter streaming flows as the CME transits both locations. The strahl population coming from the shortest magnetic connection of the structure to the Sun showed more intensity. Aims. The aim of this work is to understand the propagation and evolution of the CME and its interaction with the surrounding CHs, to explain the similarities and differences between the observations at each spacecraft, and report what one of the most longitudinal expanded CME structures measured in situ would be. Methods. Known properties of the large-scale structures from a variety of catalogues and previous studies were used to have a better overview of this particular event. In addition, multipoint observations were used to reconstruct the 3D geometry of the CME and determine the context of the solar and heliospheric conditions before the CME eruption and during its propagation. The graduated cylindrical shell model (GCS) was used to reproduce the orientation, size and speed of the structure with a simple geometry. Also, the Drag-Based Model (DBM) was utilised to understand the conditions of the interplanetary medium better in terms of the drag undergone by the structure while propagating in different directions. Finally, a comparative analysis of the different regions of the structure through the different observatories was carried out in order to directly compare the in situ plasma and magnetic field properties at each location. Results. The study presents important findings regarding the in situ measured CME on March 15, 2012, detected at a longitudinal separation of 110° in the ecliptic plane despite its initial inclination being around 45° when erupted (March 13). This suggests that the CME may have deformed and/or rotated, allowing it to be observed near its legs with spacecraft at a separation angle greater than 100°. The CME structure interacted with high-speed streams generated by the surrounding CHs. The piled-up plasma in the sheath region exhibited an unexpected correlation in magnetic field strength despite the large separation in longitude. In situ observations reveal that at both locations there was a flank encounter – where the spacecraft crossed the first part of the CME – then encountered ambient solar wind, and finally passed near the legs of the structure. Conclusions. A scenario covering all evidence is proposed for both locations with a general view of the whole structure and solar wind conditions. Also, the study shows the necessity of having multipoint observations of large-scale structures in the heliosphere.

methods: data analysis↗

The Ionospheric Three-Dimensional Electron Density Variations Induced by the 21 August 2017 Total Solar Eclipse by Using Global Ionospheric Specification

Global Ionospheric Specification (GIS) is based on the Gauss–Markov Kalman filter to assimilate the slant total electron content (TEC) observed from ground-based GPS receivers and space-based radio occultation instrumentations in order to reconstruct three-dimensional (3D) ionospheric electron density structure, and it can remotely sense and monitor the weather condition in space. In this study, five minutes of high temporal resolution GIS is implemented in order to reconstruct the 3D electron density structure on the 21 August 2017 total solar eclipse and analyze the variations induced by the moon’s shadow. To obtain more information of the ionosphere, from the extend 2200 GPS stations on the continental United States, are added for assimilation. The results show the ionosphere peak height (hmF2) uplift was 30–50 km altitude in latitude 25–40°N, and that the electron density depletion at higher altitudes (400 km) has a more noticeable time delay than at low altitudes (200 km), especially in low-latitude regions.

Ionosphere↗

Average Cross-Sectional Area of DebriSat Fragments Using Volumetrically Constructed 3D Representations

Debris fragments from the hypervelocity impact testing of DebriSat are being collected and characterized for use in updating existing satellite breakup models. One of the key parameters utilized in these models is the ballistic coefficient of the fragment which is directly related to its area‐to‐mass ratio. However, since the attitude of fragments varies during their orbital lifetime, it is customary to use the average cross‐sectional area in the calculation of the area‐to‐mass ratio. The average cross‐sectional area is defined as the average of the projected surface areas perpendicular to the direction of motion and has been shown to be equal to one‐fourth of the total surface area of a convex object. Unfortunately, numerous fragments obtained from the DebriSat experiment show significant concavity (i.e., shadowing) and thus we have explored alternate methods for computing the average cross‐sectional area of the fragments. An imaging system based on the volumetric reconstruction of a 3D object from multiple 2D photographs of the object was developed for use in determining the size characteristic (i.e., characteristics length) of the DebriSat fragments. For each fragment, the imaging system generates N number of images from varied azimuth and elevation angles and processes them using a space‐carving algorithm to construct a 3D point cloud of the fragment. This paper describes two approaches for calculating the average cross‐sectional area of debris fragments based on the 3D imager. Approach A utilizes the constructed 3D object to generate equally distributed cross‐sectional area projections and then averages them to determine the average cross‐sectional area. Approach B utilizes a weighted average of the area of the 2D photographs to directly compute the average cross‐sectional area. A comparison of the accuracy and computational needs of each approach is described as well as preliminary results of an analysis to determine the "optimal" number of images needed for the 3D imager to accurately measure the average cross sectional area of objects with known dimensions.

Scruggs, T.↗

Magnetic resonance imaging as a tool for extravehicular activity analysis

The purpose of this research is to examine the value of magnetic resonance imaging (MRI) as a means of conducting kinematic studies of the hand for the purpose of EVA capability enhancement. After imaging the subject hand using a magnetic resonance scanner, the resulting 2D slices were reconstructed into a 3D model of the proximal phalanx of the left hand. Using the coordinates of several landmark positions, one is then able to decompose the motion of the rigid body. MRI offers highly accurate measurements due to its tomographic nature without the problems associated with other imaging modalities for in vivo studies.

Dickenson, R.↗

Limited Angle Reconstruction Method for Reconstructing Terrestrial Plasmaspheric Densities from EUV Images

A new method for reconstructing the global 3D distribution of plasma densities in the plasmasphere from a limited number of 2D views is presented. The method is aimed at using data from the Extreme Ultra Violet (EUV) sensor on NASA s Imager for Magnetopause-to-Aurora Global Exploration (IMAGE) satellite. Physical properties of the plasmasphere are exploited by the method to reduce the level of inaccuracy imposed by the limited number of views. The utility of the method is demonstrated on synthetic data.

Newman, Timothy↗

X-Band Radar for Studies of Tropical Storms from High Altitude UAV Platform

The increased role of unmanned aerial vehicles (UAV) in NASA's suborbital program has created a strong interest in the development of instruments with new capabilities, more compact sizes and reduced weights than the instruments currently operated on manned aircrafts. There is a strong demand and tremendous potential for using high altitude UAV (HUAV) to carry weather radars for measurements of reflectivity and wind fields from tropical storms. Tropical storm genesis frequently occurs in ocean regions that are inaccessible to piloted aircraft due to the long off shore range and the required periods of time to gather significant data. Important factors of interest for the study of hurricane genesis include surface winds, profiled winds, sea surface temperatures, precipitation, and boundary layer conditions. Current satellite precipitation and surface wind sensors have resolutions that are too large and revisit times that are too infrequent to study this problem. Furthermore, none of the spaceborne sensors measure winds within the storm itself. A dual beam X-band Doppler radar, UAV Radar (URAD), is under development at the NASA Goddard Space Flight Center for the study of tropical storms from HUAV platforms, such as a Global Hawk. X-band is the most desirable frequency for airborne weather radars since these can be built in a relatively compact size using off-the-shelf components which cost significantly less than other higher frequency radars. Furthermore, X-band radars provide good sensitivity with tolerable attenuation in storms. The low-cost and light-weight URAD will provide new capabilities for studying hurricane genesis by analyzing the vertical structure of tropical cyclones as well as 3D reflectivity and wind fields in clouds. It will enable us to measure both the 3D precipitation structure and surface winds by using two antenna beams: fixed nadir and conical scanning each produced by its associated subsystem. The nadir subsystem is a magnetron based radar modified from a marine radar transceiver. It is capable of measuring vertical reflectivity and velocity profile while being a lower-cost, smaller size, and lighter weight version of the NASA ER-2 Doppler Radar (EDOP), which has flown during many NASA field campaigns and has provided valuable scientific information on hurricanes and weather phenomena. Unfortunately, EDOP is too large and heavy for most UAV platforms, but the experience gained with this instrument provided us with the heritage to build a new low-cost, light-weight, smaller system that will be capable of flying on UAVs. The scanning subsystem uses a TWT transmitter and provides measurements of 3D reflectivity/wind fields in-clouds. Conical scanning of the radar beam at a 35 deg. incidence angle will also provide information of surface wind speed and direction derived from the surface return over a single 360 deg. sweep. URAD data system will be Linux based with the capability of autonomous operation. It will utilize cutting edge digital receiver and FPGA technologies to carry out the data acquisition and processing tasks. High speed navigation data from the aircraft will also be captured and saved along with radar data for 3D measurement field reconstruction and aircraft motion correction. There is a tremendous potential for UAVs to carry down-looking weather radars for measurements of reflectivity, horizontal and vertical winds from tropical storms. With operation from HUAV platforms, the dual beam X-band radar under development promises to provide greatly needed information for tropical storm research.

Rodriquez, Shannon↗

Modeling the Quiet Time Outflow Solution in the Polar Cap

We use the Polar Wind Outflow Model (PWOM) to study the geomagnetically quiet conditions in the polar cap during solar maximum, The PWOM solves the gyrotropic transport equations for O(+), H(+), and He(+) along several magnetic field lines in the polar region in order to reconstruct the full 3D solution. We directly compare our simulation results to the data based empirical model of Kitamura et al. [2011] of electron density, which is based on 63 months of Akebono satellite observations. The modeled ion and electron temperatures are also compared with a statistical compilation of quiet time data obtained by the EISCAT Svalbard Radar (ESR) and Intercosmos Satellites (Kitamura et al. [2011]). The data and model agree reasonably well. This study shows that photoelectrons play an important role in explaining the differences between sunlit and dark results, ion composition, as well as ion and electron temperatures of the quiet time polar wind solution. Moreover, these results provide validation of the PWOM's ability to model the quiet time ((background" solution.

Glocer, Alex↗

Modeling Solar Zenith Angle Effects on the Polar Wind

We use the Polar Wind Outflow Model (PWOM) to study the geomagnetically quiet conditions in the polar cap during solar maximum. The PWOM solves the gyrotropic transport equations for O+, H+, and He+ along several magnetic field lines in the polar region in order to reconstruct the full 3D solution. We directly compare our simulation results to the data based empirical model of Kitamura et al. (2011) of electron density which is based on 63 months of Akebono satellite observations. The modeled ion and electron temperatures are also compared with a statistical compilation of quiet time data obtained by the EISCAT Svalbard Radar (ESR) and Intercosmos Satellites. The data and model agree reasonably well, albeit with some differences. This study shows that photoelectrons play an important role in explaining the differences between sunlit and dark results of electron density, ion composition, as well as ion and electron temperatures of the quiet time polar wind solution. Moreover, these results provide an initial validation of the PWOM s ability to model the quiet time "background" solution.

Glocer, A↗

Tracking Nonradial Outflows in Extreme Ultraviolet and White Light Solar Images

Understanding the solar corona requires knowledge of its dynamics through its various layers and subsequent connectivity to the heliosphere. This requires understanding the nature of the outflows and the physical transitions through the middle corona (∼1.5–6.0 Rs). While this region is still inaccessible to in situ measurements, remote sensing observations are available, but their interpretation can be controversial due to line-of-sight effects and the nonradial motion of outflowing structures close to the Sun (≤3.0 Rs). In this work, we describe a method to mitigate these challenges by generating nonradial height–time profiles of outflows by using advanced image processing techniques. The northern and southern boundaries of a large equatorial streamer during the 2008 solar minimum were identified in STEREO/SECCHI solar images, using two different methodologies based on thresholds of brightness and piecewise polynomial function fitting. To address line-of-sight issues, we used tomographic reconstruction of the 3D distribution of the coronal electron density based on SECCHI/COR2 images. Spectral analysis of the time series of the position angle of the streamer boundary revealed its oscillatory nature at some heights at 36–48 and 10.5–14.6 hr. Dividing the distance between the northern and southern streamer boundaries in equal parts at each height, we obtained nonradial height–time paths from which we generated nonradial profiles of corona/solar wind plasma outflow. We tracked outflows as they moved uninterruptedly from the Sun in EUVI, through COR1 and into COR2. Finally, we discuss the preliminary results of nonradial plane-of-sky velocities for a coronal mass ejection and two small-scale features.

Nathalia Alzate↗