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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 1,711 records · Page 95
All sourcesNASA NTRSDOE OSTI
NASA NTRS2012

Stereo and IMU-Assisted Visual Odometry for Small Robots

This software performs two functions: (1) taking stereo image pairs as input, it computes stereo disparity maps from them by cross-correlation to achieve 3D (three-dimensional) perception; (2) taking a sequence of stereo image pairs as input, it tracks features in the image sequence to estimate the motion of the cameras between successive image pairs. A real-time stereo vision system with IMU (inertial measurement unit)-assisted visual odometry was implemented on a single 750 MHz/520 MHz OMAP3530 SoC (system on chip) from TI (Texas Instruments). Frame rates of 46 fps (frames per second) were achieved at QVGA (Quarter Video Graphics Array i.e. 320 240), or 8 fps at VGA (Video Graphics Array 640 480) resolutions, while simultaneously tracking up to 200 features, taking full advantage of the OMAP3530's integer DSP (digital signal processor) and floating point ARM processors. This is a substantial advancement over previous work as the stereo implementation produces 146 Mde/s (millions of disparities evaluated per second) in 2.5W, yielding a stereo energy efficiency of 58.8 Mde/J, which is 3.75 better than prior DSP stereo while providing more functionality.

Source record↗
NASA NTRS2013

Constraints on the Compositions of Phobos and Deimos from Mineral Absorptions

The compositions of Phobos and Deimos have remained controversial despite multiple Earth- and space-based observations acquired during the last 40 years. Phobos is composed of at least two spectral units that are both dark yet distinct at visible to near infrared wavelenghts; a spectrally red-sloped "red" unit covers most of the moon and a less red-sloped "blue" unit is present in the ejecta of the approximately 9-km diameter impact crater Stickney [1,2]. Deimos is similar spectrally to Phobos' "red" unit [2]. Here we report results from mapping mineral absorptions on Phobos and Deimos using visible/near infrared observations from the Compact Reconnaissance Imaging Spectrometer for Mars (CRISM). We find evidence for an absorption feature at 0.65 m in the Phobos red unit and Deimos that is reproducible in observations from other instruments. The phase responsible is uncertain but may be a Fe-bearing phyllosilicate and/or graphite, consistent with the notion that Phobos and Deimos have compositions similar to CM carbonaceous chondrites [3].

Fraeman, A. A.↗
NASA NTRS2019

Heading for 20 Years of Quasi-Global Precipitation with the New Version 06 IMERG

The U.S. Global Precipitation Measurement mission (GPM) science team is developing a long-term dataset based on intercalibrated estimates from the international constellation of precipitation-relevant satellites and other data. The Integrated Multi-satellitE Retrievals for GPM (IMERG) merged precipitation product (IMERG) is computed at the half hour, 0.1° x 0.1° resolution globally in three "Runs"—Early, Late, and Final (4 hours, 14 hours, and 3.5 months after observation time, respectively). GPM is well into computing the new Version 06, which will be the first time IMERG covers the last two decades and routinely provides morphed estimates in polar regions where the surface is snow- and ice-free.A few salient features of the IMERG algorithm will be summarized, then representative examples of IMERG products will be shown. This starts with basic results, such as animations of maps, then extends to preliminary analyses of dataset characteristics. For example, the diurnal cycle demonstrates improvements over V05.

Huffman, George J.↗
NASA NTRSDate not supplied

MEDPRAT Treatment Clusters: Improving Representation of Mission Medical Risk

INTRODUCTION The Medical Extensible Dynamic Probabilistic Risk Assessment Tool (MEDPRAT) implements a computational model that aims to quantify spaceflight medical risk by utilizing probabilistic techniques to simulate critical event incidence and outcomes over thousands of simulated mission trials. The goal of MEDPRAT is to characterize mission medical risk and provide insight into medical resource utilization. In order to analyze the medical resource space, treatment must be mapped from each simulated condition, and resources consumed as a result of this treatment must be tracked throughout the course of the mission. A new MEDPRAT feature, ‘treatment clusters’, provide a more sophisticated method of defining the structure and interaction between resources, more closely mimicking the way treatment is carried out clinically. METHODS Treatment clusters expand on the two existing treatment groupings (combination and alternate) adding a new grouping: bundled treatment. Treatment clusters may be combined to any depth, giving users the ability to specify complex treatment trees whose behavior is governed by several user-specified parameters. This approach emphasizes reusability, as treatment clusters, once defined, can be used to create more complex treatment trees or applied to many conditions. By configuring parameters for contribution, efficacy, necessity, primacy, and equivalence, resource relationships and dependencies can be more accurately represented, thereby allowing users to build capabilities with desired treatment properties, for example an intravenous capability for conditions such as anaphylaxis, acute radiation syndrome, etc. MEDPRAT v1.0 remains backward compatible with existing treatment structures, giving users the ability to define new treatment clusters as evidence becomes available, without having to recode their existing treatment databases. In addition to facilitating the representation of more complex treatment options, by pairing treatment clusters with the internal optimization routine, the MEDPRAT set selector, medical resources can be identified as organized in bundles, where appropriate, so that optimized resource sets include groups of highly-dependent resources only when all resources of the group are together. For example, it would be wasteful to include ultrasound gel but not an ultrasound machine, since the gel provides no benefit as a treatment without the ultrasound machine. With treatment clusters, the user may require that both resources are available to provide any benefit as treatment, so that if one resource is optimized out of the set, the other resource will be optimized out as well. RESULTS AND CONCLUSIONS We will report on MEDPRAT treatment clusters used in a bundling study under the IMPACT project of the ExMC element. We will discuss an example of a complex treatment tree. Through the implementation of this feature MEDPRAT enables treatment to be defined and applied in a way that is more representative of the real world, providing more accurate insight into mission medical risk and the medical resource space.

Lawrence Leinweber↗
NASA NTRS1990

The Magellan Venus explorer's guide

The Magellan radar-mapping mission to the planet Venus is described. Scientific highlights include the history of U.S. and Soviet missions, as well as ground-based radar observations, that have provided the current knowledge about the surface of Venus. Descriptions of the major Venusian surface features include controversial theories about the origin of some of the features. The organization of the Magellan science investigators into discipline-related task groups for data-analysis purposes is presented. The design of the Magellan spacecraft and the ability of its radar sensor to conduct radar imaging, altimetry, and radiometry measurements are discussed. Other topics report on the May 1989 launch, the interplanetary cruise, the Venus orbit-insertion maneuver, and the in-orbit mapping strategy. The objectives of a possible extended mission emphasize the gravity experiment and explain why high-resolution gravity data cannot be acquired during the primary mission. A focus on the people of Magellan reveals how they fly the spacecraft and prepare for major mission events. Special items of interest associated with the Magellan mission are contained in windows interspersed throughout the text. Finally, short summaries describe the major objectives and schedules for several exciting space missions planned to take us into the 21st century.

Young, Carolynn↗
NASA NTRS2011

Image Segmentation, Registration, Compression, and Matching

A novel computational framework was developed of a 2D affine invariant matching exploiting a parameter space. Named as affine invariant parameter space (AIPS), the technique can be applied to many image-processing and computer-vision problems, including image registration, template matching, and object tracking from image sequence. The AIPS is formed by the parameters in an affine combination of a set of feature points in the image plane. In cases where the entire image can be assumed to have undergone a single affine transformation, the new AIPS match metric and matching framework becomes very effective (compared with the state-of-the-art methods at the time of this reporting). No knowledge about scaling or any other transformation parameters need to be known a priori to apply the AIPS framework. An automated suite of software tools has been created to provide accurate image segmentation (for data cleaning) and high-quality 2D image and 3D surface registration (for fusing multi-resolution terrain, image, and map data). These tools are capable of supporting existing GIS toolkits already in the marketplace, and will also be usable in a stand-alone fashion. The toolkit applies novel algorithmic approaches for image segmentation, feature extraction, and registration of 2D imagery and 3D surface data, which supports first-pass, batched, fully automatic feature extraction (for segmentation), and registration. A hierarchical and adaptive approach is taken for achieving automatic feature extraction, segmentation, and registration. Surface registration is the process of aligning two (or more) data sets to a common coordinate system, during which the transformation between their different coordinate systems is determined. Also developed here are a novel, volumetric surface modeling and compression technique that provide both quality-guaranteed mesh surface approximations and compaction of the model sizes by efficiently coding the geometry and connectivity/topology components of the generated models. The highly efficient triangular mesh compression compacts the connectivity information at the rate of 1.5-4 bits per vertex (on average for triangle meshes), while reducing the 3D geometry by 40-50 percent. Finally, taking into consideration the characteristics of 3D terrain data, and using the innovative, regularized binary decomposition mesh modeling, a multistage, pattern-drive modeling, and compression technique has been developed to provide an effective framework for compressing digital elevation model (DEM) surfaces, high-resolution aerial imagery, and other types of NASA data.

Yadegar, Jacob↗
NASA NTRS2003

Developmental gene regulatory network architecture across 500 million years of echinoderm evolution

Evolutionary change in morphological features must depend on architectural reorganization of developmental gene regulatory networks (GRNs), just as true conservation of morphological features must imply retention of ancestral developmental GRN features. Key elements of the provisional GRN for embryonic endomesoderm development in the sea urchin are here compared with those operating in embryos of a distantly related echinoderm, a starfish. These animals diverged from their common ancestor 520-480 million years ago. Their endomesodermal fate maps are similar, except that sea urchins generate a skeletogenic cell lineage that produces a prominent skeleton lacking entirely in starfish larvae. A relevant set of regulatory genes was isolated from the starfish Asterina miniata, their expression patterns determined, and effects on the other genes of perturbing the expression of each were demonstrated. A three-gene feedback loop that is a fundamental feature of the sea urchin GRN for endoderm specification is found in almost identical form in the starfish: a detailed element of GRN architecture has been retained since the Cambrian Period in both echinoderm lineages. The significance of this retention is highlighted by the observation of numerous specific differences in the GRN connections as well. A regulatory gene used to drive skeletogenesis in the sea urchin is used entirely differently in the starfish, where it responds to endomesodermal inputs that do not affect it in the sea urchin embryo. Evolutionary changes in the GRNs since divergence are limited sharply to certain cis-regulatory elements, whereas others have persisted unaltered.

NASA Program Fundamental Space Biology↗
DOE OSTI2024

Snow distribution patterns revisited: A physics-based and machine learning hybrid approach to snow distribution mapping in the sub-Arctic Supporting Data

Snow in the Arctic and sub-Arctic is highly variable at fine scales, with deep drifts and shallow scoured areas creating a complex pattern of snow on the landscape. This fine-scale variation in snow is driven primarily by landscape and vegetation properties. Some landscape features, such as river beds, will rapidly fill in with snow during the wintertime due to high winds, while shrubs will trap blowing snow, resulting in drifts. Meanwhile, snow will blow off of exposed areas, resulting in abnormally shallow snow. These complex interactions between wind, vegetation, and terrain are difficult to represent well with physically-based models, but machine learning techniques have shown promise in the past. Here, we propose a hybrid modeling approach, where we use machine learning derived snow pattern maps to inform SnowModel, a physically-based snow process model. We develop and test this technique at the Teller 27 Seward Peninsula NGEE-Arctic study site. This dataset includes 5 *.nc files of model inputs and outputs plus one user guide (*.pdf). We present the data we use to drive SnowModel (vegetation type, digital elevation model), the snow pattern maps used to inform SnowModel (Standardized Depth Values maps, Machine Learning Snow Distribution Pattern), and our machine learning, SnowModel, and Hybrid snow depth and snow water equivalent results. The Next-Generation Ecosystem Experiments: Arctic (NGEE Arctic), a research effort to reduce uncertainty in Earth System Models by developing a predictive understanding of carbon-rich Arctic ecosystems and feedbacks to climate. NGEE Arctic was supported by the Department of Energy's Office of Biological and Environmental Research. The NGEE Arctic project had two field research sites: 1) located within the Arctic polygonal tundra coastal region on the Barrow Environmental Observatory (BEO) and the North Slope near Utqiagvik (Barrow), Alaska and 2) multiple areas on the discontinuous permafrost region of the Seward Peninsula north of Nome, Alaska. Through observations, experiments, and synthesis with existing datasets, NGEE Arctic provided an enhanced knowledge base for multi-scale modeling and contributed to improved process representation at global pan-Arctic scales within the Department of Energy's Earth system Model (the Energy Exascale Earth System Model, or E3SM), and specifically within the E3SM Land Model component (ELM).

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2024

Monitoring water quality in the lower Kansas River using remote sensing

Abstract We demonstrate how to combine remote sensing data from satellite imagery (Sentinel‐2) with in situ water quality gauging (USGS Super Gages and the Gybe hyperspectral radiometer) to create spatially dense maps of water quality parameters (chlorophyll‐a concentration, turbidity, and nitrate plus nitrite concentration) along the lower Kansas River. The water quality maps are created using locally tuned models of the target water quality parameters, and this study describes the steps used to design, calibrate, and validate the empirical correlations. Water quality parameters such as chlorophyll‐a concentration are correlated with well‐studied absorption and scattering features in the visible spectrum (roughly 400–700 nm). Nutrients (such as nitrate plus nitrite concentration) lack strong absorption features in the visible spectrum, and in those cases we describe a novel surrogate data modeling approach that identifies overlapping water parcels between the in situ gauging and the remote sensing imagery. Measurements from the overlapping water parcels yield excellent correlations () for the target water quality parameters for limited windows of time (or limited sections of river reaches). Examples are provided illustrating how the water quality maps can be used to track river inputs from ungauged sources (such as creeks), or reveal the mixing patterns at the confluences.

Tufillaro, Nicholas↗
NASA NTRS2004

First Global Maps of Stratospheric and Tropospheric NO2 from OMI

The Ozone Monitoring Instrument (OMI) was launched successfully in July 2004, as one of four instruments on the EOS Aura satellite. OMI makes hyperspectral measurements that are used to retrieve column densities of critical trace gases, including formaldehyde, BrO, SO2 and NO2 . We present the first results from the OM1 operational NO2 algorithm and demonstrate its ability to retrieve the tropospheric and stratospheric components of NO2. The DOAS method is used to determine slant column densities, and initial air mass factors (AMFs) are used. to give initial estimates of the vertical column densities (VCDs). VCDs from up to 15 consecutive orbits are collected, and a spatial filtering technique is applied to extract the synoptic-scale features characteristic of the stratospheric, field. features to be evidence of tropospheric excess NO2 , and apply an AMF appropriate to polluted conditions, to obtain an improved retrieval of the NO2 total VCD. We describe the assumptions underlying the algorithm in detail, and show global maps of NO2 VCDs, based on the first operational data from OMI.

Bucsela, Eric J.↗
NASA NTRS1979

Multisensor analysis of hydrologic features in the Wind River Range, Wyoming with emphasis on the SEASAT SAR

The author has identified the following significant results. Analysis of imagery obtained over west-central Wyoming indicates that Seasat SAR has capability for hydrologic mapping. Both the L-Band (Seasat) and the X-Band (aircraft) SAR imagery were useful for observing drainage detail. Streams have bright signatures on the SAR imagery because the riparian vegetation produces a rough surface and thus high radar returns. Lakes appear relatively bright on the Seasat image presumably in response to surface ripples and waves induced by wind action. SAR imagery did not reveal snow at either the 23.5 cm (L-Band) or 2.8 cm (X-Band) wavelengths. Comparing Seasat and X-Band aircraft SAR imagery to LANDSAT RBV imagery, U-2 photography, and topographic maps of the Wind River Range, it appears that the SAR data do not seem to provide as much hydrologic information as do the other sensors in the visible and near infrared portions of the spectrum.

Foster, J. L.↗
NASA NTRS1973

Evaluation of the potentials of the ERTS techniques for geological mapping purposes

The author has identified the following significant results. Preliminary analysis of the full frame images shows the following: (1) The techniques employed were found suitable for study purposes. (2) The positional accuracy of the system corrected bulk processed MSS images is about 100-400 m. (3) Drainage is well depicted and morphotectonic features could be recognized. (4) Water bodies are clearly shown in MSS band 7. (5) Major roads, railway lines, and large towns are more or less detectable on bands 6 and 7. (6) Vegetation and agricultural areas are recognizable at many places. (7) Major rock formation boundaries, in general, are more or less clear. (8) Some of the structural trends including folded and linear structural elements are clear. (9) MSS bands 5 and 7 appear to be most useful for visual analysis. (10) Quick look analysis suggests that regional geological mapping on ERTS-1 imagery of the study area will be probably quite feasible. However, detailed analysis, visual and quantitative, on subframes, which is under progress may render more significant results.

Mohr, H. E. C. V.↗
DOE OSTI2022

Modeling the distribution of the endangered Jemez Mountains salamander (Plethodon neomexicanus) in relation to geology, topography, and climate

The Jemez Mountains salamander (Plethodon neomexicanus; hereafter JMS) is an endangered salamander restricted to the Jemez Mountains in north-central New Mexico, United States. This strictly terrestrial and lungless species requires moist surface conditions for activities such as mating and foraging. Threats to its current habitat include fire suppression and ensuing severe fires, changes in forest composition, habitat fragmentation, and climate change. Forest composition changes resulting from reduced fire frequency and increased tree density suggest that its current aboveground habitat does not mirror its historically successful habitat regime. However, because of its limited habitat area and underground behavior, we hypothesized that geology and topography might play a significant role in the current distribution of the salamander. We modeled the distribution of the JMS using a machine learning algorithm to assess how geology, topography, and climate variables influence its distribution. The best habitat suitability model indicates that geology type and maximum winter temperature (November to March) were most important in predicting the distribution of the salamander (23.5% and 50.3% permutation importance, respectively). Minimum winter temperature was also an important variable (21.4%), suggesting this also plays a role in salamander habitat. Our habitat suitability map reveals low uncertainty in model predictions, and we found slight discrepancies between the designated critical habitat and the most suitable areas for the JMS. Because geological features are important to its distribution, we recommend that geological and topographical data are considered, both during survey design and in the description of localities of JMS records once detected.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2025

Exotic phases in finite-density ℤ 3 theories

Lattice ℤ 3 theories with complex actions share many key features with finite- density QCD including a sign problem and $\mathcal{CK}$ symmetry. Complex ℤ 3 spin and gauge models exhibit a generalized Kramers-Wannier duality mapping them onto chiral ℤ 3 spin and gauge models, which are simulatable with standard lattice methods in large regions of parameter space. The Migdal-Kadanoff real-space renormalization group (RG) preserves this duality, and we use it to compute the approximate phase diagram of both spin and gauge ℤ 3 models in dimensions one through four. Chiral ℤ 3 spin models are known to exhibit a Devil’s Flower phase structure, with inhomogeneous phases that can be thought of as ℤ 3 analogues of chiral spirals. Out of the large class of models we study, we find that only chiral spin models and their duals have a Devil’s Flower structure with an infinite set of inhomogeneous phases, a result we attribute to Elitzur’s theorem. We also find that different forms of the Migdal-Kadanoff RG produce different numbers of phases, a violation of the expectation for universal behavior from a real-space RG. We discuss extensions of our work to ℤ N models, SU(N) models and nonzero temperature.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2023

Analysis of X-ray images and spectra (aXis2000): A toolkit for the analysis of X-ray spectromicroscopy data

Spectromicroscopy refers to analytical methods that combine imaging and spectroscopy to provide detailed, spatially resolved analytical information about a sample, such as the type and quantitative spatial distributions of chemical components, geometric or magnetic alignment information, crystal structure, etc. The analysis of X-ray images and spectra (aXis2000) software described in this work provides a set of routines within a single, integrated, graphical-oriented package to read, display, manipulate and analyze spectromicroscopy data, with particular focus on soft X-ray spectromicroscopy methods such as scanning transmission X-ray microscopy (STXM), X-ray photoemission electron microscopy (XPEEM), scanning photoelectron X-ray microscopy (SPEM) and transmission X-ray microscopy (TXM). Here, this free software is described and compared to other software that can provide similar or complementary capabilities. Examples of spectromicroscopic analyses using advanced features of aXis2000 are provided.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2021

Phase diagram of CeSb 2 from magnetostriction and magnetization measurements: Evidence for ferrimagnetic and antiferromagnetic states

Cerium diantimonide (CeSb 2 ) is one of a family of rare-earth-based magnetic materials that exhibit metamagnetism, enabling control of the magnetic ground state through an applied magnetic field. At low temperatures, CeSb 2 hosts a rich phase diagram with multiple magnetically ordered phases for many of which the order parameter is only poorly understood. In this work, we report a study of its metamagnetic properties by scanning tunneling microscopy (STM) and magnetization measurements. We use STM measurements to characterize the sample magnetostriction with subpicometer resolution from magnetic field and temperature sweeps. This allows us to directly assess the bulk phase diagram as a function of field and temperature and relate spectroscopic features from tunneling spectroscopy to bulk phases. Our magnetostriction and magnetization measurements indicate that the low-temperature ground state at zero field is ferrimagnetic. Quasiparticle interference mapping shows evidence for a reconstruction of the electronic structure close to the Fermi energy upon entering the magnetically ordered phase.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
DOE OSTI2022

Identifying Majorana vortex modes via nonlocal transport

The combination of two-dimensional Dirac surface states with s-wave superconductivity is expected to generate localized topological Majorana zero modes in vortex cores. Putative experimental signatures of these modes have been reported for heterostructures of proximitized topological insulators, iron-based superconductors or certain transition metal dichalcogenides. Despite these efforts, the Majorana nature of the observed excitation is still under debate. In this work, we propose to identify the presence of Majorana vortex modes using a nonlocal transport measurement protocol originally employed for one-dimensional settings. In the case of an isolated subgap state, the protocol provides a spatial map of the ratio of local charge- and probability-density which offers a clear distinction between Majorana and ordinary fermionic modes. We show that these distinctive features survive in the experimentally relevant case of hybridizing vortex core modes.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
DOE OSTI2026

Improving Detector Systematic Uncertainties Through Data-Driven Machine Learning

Detector simulation in liquid argon time projection chambers (LArTPCs) is a constant challenge. In particular the modeling of electrons response on wires is highly nontrivial. However, new machine learning techniques exist which can be leveraged to ameliorate these concerns. We present a novel methodology to attempt to learn from cosmic muon data in the ICARUS detector how reconstructed wire signals are influenced by features of the hits such as location, particle direction, angle relative to the wire plane, etc. A model can then be generated which can apply the learned mapping to Monte Carlo events to create a more data-like simulation sample. By creating such a sample we expect to reduce the systematic uncertainties at ICARUS due to our detector modeling.

Hausner, Harry [Fermilab] (ORCID:0000000188932280)↗