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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 811 records · Page 45
All sourcesNASA NTRSDOE OSTI
NASA NTRS2010

Thermal Infrared Emission Spectroscopy of Synthetic Allophane and its Potential Formation on Mars

Allophane is a poorly-crystalline, hydrous aluminosilicate with variable Si/Al ratios approx.0.5-1 and a metastable precursor of clay minerals. On Earth, it forms rapidly by aqueous alteration of volcanic glass under neutral to slightly acidic conditions [1]. Based on in situ chemical measurements and the identification of alteration phases [2-4], the Martian surface is interpreted to have been chemically weathered on local to regional scales. Chemical models of altered surfaces detected by the Mars Exploration Rover Spirit in Gusev crater suggest the presence of an allophane-like alteration product [3]. Thermal infrared (TIR) spectroscopy and spectral deconvolution models are primary tools for determining the mineralogy of the Martian surface [5]. Spectral models of data from the Thermal Emission Spectrometer (TES) indicate a global compositional dichotomy, where high latitudes tend to be enriched in a high-silica material [6,7], interpreted as high-silica, K-rich volcanic glass [6,8]. However, later interpretations proposed that the high-silica material may be an alteration product (such as amorphous silica, clay minerals, or allophane) and that high latitude surfaces are chemically weathered [9-11]. A TIR spectral library of pure minerals is available for the public [12], but it does not contain allophane spectra. The identification of allophane on the Martian surface would indicate high water activity at the time of its formation and would help constrain the aqueous alteration environment [13,14]. The addition of allophane to the spectral library is necessary to address the global compositional dichotomy. In this study, we characterize a synthetic allophane by IR spectroscopy, X-ray diffraction (XRD), and transmission electron microscopy (TEM) to create an IR emission spectrum of pure allophane for the Mars science community to use in Martian spectral models.

Rampe, E. B.↗
NASA NTRS2012

Comparison of Observations of Sporadic-E Layers in the Nighttime and Daytime Mid-Latitude Ionosphere

A comparison of numerous rocket experiments to investigate mid-latitude sporadic-E layers is presented. Electric field and plasma density data gathered on sounding rockets launched in the presence of sporadic-E layers and QP radar echoes reveal a complex electrodynamics including both DC parameters and plasma waves detected over a large range of scales. We show both DC and wave electric fields and discuss their relationship to intense sporadic-E layers in both nighttime and daytime conditions. Where available, neutral wind observations provide the complete electrodynamic picture revealing an essential source of free energy that both sets up the layers and drives them unstable. Electric field data from the nighttime experiments reveal the presence of km-scale waves as well as well-defined packets of broadband (10's of meters to meters) irregularities. What is surprising is that in both the nighttime and daytime experiments, neither the large scale nor short scale waves appear to be distinctly organized by the sporadic-E density layer itself. The observations are discussed in the context of current theories regarding sporadic-E layer generation and quasi-periodic echoes.

Pfaff, R.↗
NASA NTRS2017

Lightning Imaging Sensor (LIS) on the International Space Station (ISS): Launch, Installation, Activation and First Results

Mission: Fly a flight-spare LIS (Lightning Imaging Sensor) on ISS to take advantage of unique capabilities provided by the ISS (e.g., high inclination, real time data); Integrate LIS as a hosted payload on the DoD Space Test Program-Houston 5 (STP-H5) mission and launch on a Space X rocket for a minimum 2 year mission. Measurement: NASA and its partners developed and demonstrated effectiveness and value of using space-based lightning observations as a remote sensing tool; LIS measures lightning (amount, rate, radiant energy) with storm scale resolution, millisecond timing, and high detection efficiency, with no land-ocean bias. Benefit: LIS on ISS will extend TRMM (Tropical Rainfall Measuring Mission) time series observations, expand latitudinal coverage, provide real time data to operational users, and enable cross-sensor calibration.

LIS↗
NASA NTRS2016

Time Series Explorer: Bayesian Blocks with Generalized Profiles and in Higher Dimensions

The Time Series Explorer (TSE) is a project aimed at provided new and advanced time series analysis algorithms in two forms: a tool kit and an automated pipeline applying selected tools in machine learning settings. I will present a sketch of TSE with emphasis on time-domain modeling in general and recent improvements of the Bayesian Block (BB) algorithm in particular. This includes generalizing the shape of the elementary blocks from the current constant-rate model to general shapes, such as two-sided exponentials. Related topics will include extension of BB to higher dimensions and a novel way to detect and characterize short time-scale bursts in time-tagged event data. The Fermi Gamma Ray Space Telescope light curve for the Crab Nebula will be used as an example for all of the algorithms discussed. This work is in collaboration with Tom Loredo.

Bayesian Block (BB) algorithm↗
NASA NTRS2021

The RS CVn Type star GT Mus Shows Most Energetic X-ray Flares Throughout the 2010s

We report that the RS CVn-type star GT Mus (HR4492, HD101379+HD101380) was the most active star in the X-ray sky in the last decade in terms of the scale of recurrent energetic flares. We detected eleven flares from GT Mus in eight years of observations with MAXI (Monitor of All-sky X-ray Image)from 2009 August to 2017 August. The detected flare peak luminosities were 1–4×1033erg s−1in the2.0–20.0 keV band for its distance of 109.6 pc. The durations of the flares ranged from 1–4 days. The flare energies are calculated to be 1–8×1038erg, which are at the upper end of the observed stellar flare. We carried out X-ray follow-up observations for one of the eleven flares with NICER (Neutron star Interior Composition Explorer) on 2017 July 18 and found that the flare cooled quasi-statically. On the basis of a quasi-static cooling model, the flare loop length is derived to be 4×1012cm (or60R). The electron density is derived to be1×1010cm−3, which is consistent with the typical value of solar and stellar flares (1010−11cm−3).

Ryo Sasaki↗
NASA NTRS2021

The Role of Fire in Global Forest Loss Dynamics

Fires, among other forms of natural and anthropogenic disturbance, play a central role in regulating the location, composition and biomass of forests. Understanding the role of fire in global forest loss is crucial in constraining land-use change emissions and the global carbon cycle. We analysed the relationship between forest loss and fire at 500 m resolution based on satellite-derived data for the 2003–2018 period. Satellite fire data included burned area and active fire detections, to best account for large and small fires, respectively. We found that, on average, 38 ± 9% (± range) of global forest loss was associated with fire, and this fraction remained relatively stable throughout the study period. However, the fraction of fire-related forest loss varied substantially on a regional basis, and showed statistically significant trends in key tropical forest areas. Decreases in the fraction of fire-related forest loss were found where deforestation peaked early in our study period, including the Amazon and Indonesia while increases were found for tropical forests in Africa. The inclusion of active fire detections accounted for 41%, on average, of the total fire-related forest loss, with larger contributions in small clearings in interior tropical forests and human-dominated landscapes. Comparison to higher-resolution fire data with resolutions of 375 and 20 m indicated that commission errors due to coarse resolution fire data largely balanced out omission errors due to missed small fire detections for regional to continental-scale estimates of fire-related forest loss. Besides an improved understanding of forest dynamics, these findings may help to refine and separate fire-related and non-fire-related land-use change emissions in forested ecosystems.

Dan van Wees↗
NASA NTRSDate not supplied

Capturing Complex Multivariate Time Series Interactions to Detect High-Risk Adverse Events During Flight

The reduction of aviation safety metrics below target thresholds continue to drive down the number of aviation fatalities and accidents. To meet future safety demands, sustained efforts by aviation agencies promoting safety assurance processes and systems have prompted ongoing research on identifying and mitigating in-flight risks. With the projected increase in passenger load factor and rollout of more autonomous systems into the national airspace, the need to detect high-risk events in-time or ahead-of-time is becoming increasingly crucial. New anomaly detection and precursor identification algorithms will need to scale to different airframes, levels of autonomy, and system complexity. While the pervasiveness of deep learning has resulted in the development of performant anomaly detection methods, these sophisticated models currently suffer from low end-user interpretability. Building off our previous work on identifying adverse events in multivariate flight data during descent, we propose a data-driven approach for detecting in-flight adverse events caused by the complex interplay of flight variables. Our approach utilizes ordinal patterns of important aircraft stability variables (e.g., airspeed and descent rate) to capture multivariate flight dynamics that can be used to predict the onset of unstable approaches, a high-risk adverse event that can occur during approach. Through the use of ordinal patterns, we aim to create more interpretable detection models of in-flight adverse events that can be translated to future autonomous systems without difficulty. Our analysis shows the presence of distinct ordinal pattern distributions that can be used to predict unstable approaches 1 minute ahead of time with an accuracy of 0.69 and a recall of 0.73 and 30 seconds ahead with an accuracy of 0.70 and a recall of 0.86.

Risk detection↗
NASA NTRSDate not supplied

Capturing Multivariate Time Series Interactions to Detect High‑Risk Instability During Approach

The reduction of aviation safety metrics below target thresholds continue to drive down the number of aviation fatalities and accidents. To meet future safety demands, sustained efforts by aviation agencies promoting safety assurance processes and systems have prompted ongoing research on identifying and mitigating in-flight risks. With the projected increase in passenger load factor and rollout of more autonomous systems into the national airspace, the need to detect high-risk events in-time or ahead-of-time is becoming increasingly crucial. New anomaly detection and precursor identification algorithms will need to scale to different airframes, levels of autonomy, and system complexity. While the pervasiveness of deep learning has resulted in the development of performant anomaly detection methods, these sophisticated models currently suffer from low end-user interpretability. Building off our previous work on identifying adverse events in multivariate flight data during descent, we propose a data-driven approach for detecting in-flight adverse events caused by the complex interplay of flight variables. Our approach utilizes ordinal patterns of important aircraft stability variables (e.g., airspeed and descent rate) to capture multivariate flight dynamics that can be used to predict the onset of unstable approaches, a high-risk adverse event that can occur during approach. Through the use of ordinal patterns, we aim to create more interpretable detection models of in-flight adverse events that can be translated to future autonomous systems without difficulty. Our analysis shows the presence of distinct ordinal pattern distributions that can be used to predict unstable approaches 1 minute ahead of time with an accuracy of 0.69 and a recall of 0.73 and 30 seconds ahead with an accuracy of 0.70 and a recall of 0.86.

Risk detection↗
DOE OSTI2015

LandScan HD

Research in geographic information science and technology at Oak Ridge National Laboratory is addressing the need for improved human settlement detection and characterization at the world scale.

58 GEOSCIENCES↗
DOE OSTI2017

A Background-Subtracted Search for Annual Modulation in CDMS II

The identification of dark matter is one of the outstanding problems of our time. Cos- mological and astrophysical clues such as structure formation and relic densities, anomalous galaxy rotation curves, and mass density profiles provide ample evidence of an undetected mass component of the universe. Meanwhile, recent advancements in particle physics point toward extensions to the Standard Model, many of which posit candidates for new particles and new physics at the weak scale and beyond. If, as expected, the confluence of the hints of new physics in particle physics, astrophysics, and cosmology at the weak scale is more than coincidence, the detection of dark matter will pave the way for a paradigm shift in our fundamental understanding of the universe.Weakly interacting massive particles (WIMPs), in particular, are a well-motivated class of candidates for particle dark matter. Naturally predicted in supersymmetry (SUSY), WIMPs are stable, weakly-interacting, and produced in sufficient abundance to comprise the quantity of missing mass in a number of simple cases. Over the last two decades of experimentation, significant areas of the parameter space defined by the simplest SUSY theories have been ruled out, but WIMPs and related particles remain compelling candidates for dark matter searches.Several avenues for the detection and identification of dark matter are currently being pursued. The present work is a description of the search for a direct detection of super- symmetric dark matter via scattering from standard model particles. The Cryogenic Dark Matter Search (CDMS) Experiment uses ionization and athermal phonon sensor technolo- gies to achieve event-by-event discrimination of electron and nuclear recoils in cryogenic germanium crystal detectors. At low energies, where the the ability to discriminate individ- ual nuclear recoil events from background is reduced, a periodic variation of the rate and crossover signatures in the energy spectrum can aid the identification of a WIMP signature in the presence of significant backgrounds. In general, the direct detection of dark matter is the first step toward the identification and classification of dark matter in the universe.This work describes a background-subtracted search for annual modulation in the WIMP- search data acquired in the Cryogenic Dark Matter Search II (CDMS II) Experiment, which was the second implementation of the highly successful CDMS technology. We observe no significant modulation in the 2.7 keVnr to 11.9 keVnr (nuclear-recoil-equivalent) energy range selected for this analysis. These results are not compatible with a WIMP dark matter interpretation of the signals reported by the DAMA/LIBRA and CoGeNT experiments, and provide complementary support to earlier CDMS low-threshold germanium analyses.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2026

FATHOMS-RAG: A Framework for the Assessment of Thinking and Observation in Multimodal Systems that use Retrieval Augmented Generation

Retrieval-augmented generation (RAG) has emerged as a promising paradigm for improving factual accuracy in large language models (LLMs). We introduce a benchmark designed to evaluate RAG pipelines as a whole, evaluating a pipelines ability to ingest several modalities of information. We present (1) a curated dataset of 93 questions designed to evaluate a pipeline's ability to ingest textual data, tables, images, multimodal data, and cross-document multimodal data; (2) a phrase-level recall metric for correctness; (3) a nearest-neighbor embedding classifier in an attempt to classify pipeline hallucinations; (4) a comparative evaluation of 2 pipelines built with open-source retrieval mechanisms and 4 closed-source foundational models; and (5) a third-party human evaluation of the alignment of our correctness and hallucination metrics. We find that closed-source pipelines significantly outperform open-source pipelines in both the correctness and halucination metrics, with a wider performance gap in questions relying on multimodal and cross-document information. We also find after a human evaluation of our correctness and hallucination metric compared with our questions and pipeline responses, average agreement was 4.62 for correctness 4.53 for hallucination detection on a 1-5 Likert scale with 5 being strongly agree with our determination.

Hildebrand, Samuel [ORNL] (ORCID:0009000465963104)↗
DOE OSTI2019

Anatomy of a Cooling Flow: The Feedback Response to Pure Cooling in the Core of the Phoenix Cluster

We present new, deep observations of the Phoenix cluster from the Chandra X-ray Observatory, the Hubble Space Telescope, and the Karl Jansky Very Large Array. These data provide an order of magnitude improvement in depth and/or angular resolution at X-ray, optical, and radio wavelengths, yielding an unprecedented view of the core of the Phoenix cluster. We find that the one-dimensional temperature and entropy profiles are consistent with expectations for pure-cooling hydrodynamic simulations and analytic descriptions of homogeneous, steady-state cooling flow models. In the inner ~10 kpc, the cooling time is shorter by an order of magnitude than any other known cluster, while the ratio of the cooling time to freefall time approaches unity, signaling that the ICM is unable to resist multiphase condensation on kpc scales. When we consider the thermodynamic profiles in two dimensions, we find that the cooling is highly asymmetric. The bulk of the cooling in the inner ~20 kpc is confined to a low-entropy filament extending northward from the central galaxy. We detect a substantial reservoir of cool (10^4 K) gas (as traced by the [OII] doublet), which is coincident with the low-entropy filament. The bulk of this cool gas is draped around and behind a pair of X-ray cavities, presumably bubbles that have been inflated by radio jets, which are detected for the first time on kpc scales. These data support a picture in which AGN feedback is promoting the formation of a multiphase medium via a combination of ordered buoyant uplift and locally enhanced turbulence. These processes ought to counteract the tendency for buoyancy to suppress condensation, leading to rapid cooling along the jet axis. The recent mechanical outburst has sufficient energy to offset cooling, and appears to be coupling to the ICM via a cocoon shock, raising the entropy in the direction orthogonal to the radio jets.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2015

bicep2/KECK ARRAY. IV. OPTICAL CHARACTERIZATION AND PERFORMANCE OF THE bicep2 AND KECK ARRAY EXPERIMENTS

bicep2 and the Keck Array are polarization-sensitive microwave telescopes that observe the cosmic microwave background (CMB) from the South Pole at degree angular scales in search of a signature of inflation imprinted as B-mode polarization in the CMB. bicep2 was deployed in late 2009, observed for three years until the end of 2012 at 150 GHz with 512 antenna-coupled transition edge sensor bolometers, and has reported a detection of B-mode polarization on degree angular scales. The Keck Array was first deployed in late 2010 and will observe through 2016 with five receivers at several frequencies (95, 150, and 220 GHz). bicep2 and the Keck Array share a common optical design and employ the field-proven bicep1 strategy of using small-aperture, cold, on-axis refractive optics, providing excellent control of systematics while maintaining a large field of view. This design allows for full characterization of far-field optical performance using microwave sources on the ground. Here we describe the optical design of both instruments and report a full characterization of the optical performance and beams of bicep2 and the Keck Array at 150 GHz.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2018

Biologically inspired approaches for biosurveillance anomaly detection and data fusion

This study developed and tested biologically inspired computational methods to detect anomalous signals in data streams that could indicate a pending outbreak or bio-weapon attack. Current large-scale biosurveillance systems are plagued by two principal deficiencies: (1) timely detection of disease-indicating signals in noisy data and (2) anomaly detection across multiple channels. Anomaly detectors and data fusion components modeled after human immune system processes were tested against a variety of natural and synthetic surveillance datasets. A pilot scale immune-system-based biosurveillance system performed at least as well as traditional statistical anomaly detection data fusion approaches. Machine learning approaches leveraging Deep Learning recurrent neural networks were developed and applied to challenging unstructured and multimodal health surveillance data. Within the limits imposed of data availability, both immune systems and deep learning methods were found to improve anomaly detection and data fusion performance for particularly challenging data subsets.

59 BASIC BIOLOGICAL SCIENCES↗
NASA NTRS2020

Detecting differential ground displacements of civil structures in fast-subsiding metropolises with interferometric SAR and band-pass filtering

Ground displacements due to changes in soil conditions represent a threat to the stability of civil structures in many urban areas, worldwide. In fast-subsiding areas, regional subsidence (wavelength ~ 1,000’s m) can be dominantly high and, consequently, mask other signals at local scales (wavelength ~ 10–100’s m). Still, engineering and construction applications require a comprehensive knowledge of local-scale signals, which can threaten the stability of buildings and infrastructure. Here we present a new technique based on band-pass filters for uncovering local-scale signals hidden by regional subsidence as detected by interferometric SAR measurements. We apply our technique to a velocity field calculated from 21 high-resolution COSMO-SkyMed scenes acquired over Mexico City and obtain components of long (> 478 m), intermediate (42–478 m) and short (< 42 m) spatial wavelengths. Our results reveal that long-wavelength velocities exceed − 400 mm/year, whereas intermediate- and short-wavelength velocities are in the order of ± 15 mm/year. We show that intermediate-wavelength velocities are useful for retrieving signals such as uplift along elevated viaducts of Metro lines 4 and B, as well as differential displacements in Pantitlán station’s pedestrian overpass system and across sharp geotechnical boundaries in the piedmont of Sierra de Santa Catarina—where surface faulting occurs.

Darío Solano-Rojas↗
DOE OSTI2014

Test-particle acceleration in a hierarchical three-dimensional turbulence model

The acceleration of charged particles is relevant to the solar corona over a broad range of scales and energies. High-energy particles are usually detected in concomitance with large energy release events like solar eruptions and flares. Nevertheless, acceleration can occur at smaller scales, characterized by dynamical activity near current sheets. To gain insight into the complex scenario of coronal charged particle acceleration, we investigate the properties of acceleration with a test-particle approach using three-dimensional magnetohydrodynamic (MHD) models. These are obtained from direct solutions of the reduced MHD equations, well suited for a plasma embedded in a strong axial magnetic field, relevant to the inner heliosphere. A multi-box, multiscale technique is used to solve the equations of motion for protons. This method allows us to resolve an extended range of scales present in the system, namely, from the ion inertial scale of the order of a meter up to macroscopic scales of the order of 10 km (1/100th of the outer scale of the system). This new technique is useful to identify the mechanisms that, acting at different scales, are responsible for acceleration to high energies of a small fraction of the particles in the coronal plasma. We report results that describe acceleration at different stages over a broad range of time, length, and energy scales.

79 ASTRONOMY AND ASTROPHYSICS↗
NASA NTRS2011

Dual-Frequency VLBI Study of Centaurus A on Sub-Parsec Scales: The Highest-Resolution View of an Extragalactic Jet

Centaurus A is the closest active galactic nucleus. High resolution imaging using Very Long Baseline Interferometry (VLBI) enables us to study the spectral and kinematic behavior of the radio jet-<:ounterjet system on sub-parsec scales, providing essential information for jet emission and formation models. Aims. Our aim is to study the structure and spectral shape of the emission from the central-parsec region of Cen A. Methods. As a target of the Southern Hemisphere VLBI monitoring program TANAMI (Tracking Active Galactic Nuclei with Millliarcsecond Interferometry), VLBI observations of Cen A are made regularly at 8.4 and 22.3 GHz with the Australian Long Baseline Array (LBA) and associated telescopes in Antarctica, Chile, and South Africa. Results. The first dual-frequency images of this source are presented along with the resulting spectral index map. An angular resolution of 0.4 mas x 0.7 mas is achieved at 8.4 GHz, corresponding to a linear scale of less than 0.013 pc. Hence, we obtain the highest resolution VLBI image of Cen A, comparable to previous space-VLBI observations. By combining with the 22.3 GHz image, we present the corresponding dual-frequency spectral index distribution along the sub-parsec scale jet revealing the putative emission regions for recently detected y-rays from the core region by Fermi/LAT. Conclusions. We resolve the innermost structure of the milliarcsecond scale jet and counter jet system of Cen A into discrete components. The simultaneous observations at two frequencies provide the highest resolved spectral index map of an AGN jet allowing us to identify up to four possible sites as the origin of the high energy emission. Key words. galaxies: active galaxies: individual (Centaurus A, NGC 5128) - galaxies: jets - techniques: high angular resolution

Mueller, C.↗
NASA NTRS2018

On the Ability of Space- Based Passive and Active Remote Sensing Observations of CO2 to Detect Flux Perturbations to the Carbon Cycle

Space-borne observations of CO2 are vital to gaining understanding of the carbon cycle in regions of the world that are difficult to measure directly, such as the tropical terrestrial biosphere, the high northern and southern latitudes, and in developing nations such as China. Measurements from passive instruments such as GOSAT (Greenhouse Gases Observing Satellite) and OCO-2 (Orbiting Carbon Observatory 2), however, are constrained by solar zenith angle limitations as well as sensitivity to the presence of clouds and aerosols. Active measurements such as those in development for the Active Sensing of CO2 Emissions over Nights, Days and Seasons (ASCENDS) mission show strong potential for making measurements in the high-latitude winter and in cloudy regions. In this work we examine the enhanced flux constraint provided by the improved coverage from an active measurement such as ASCENDS. The simulation studies presented here show that with sufficient precision, ASCENDS will detect permafrost thaw and fossil fuel emissions shifts at annual and seasonal time scales, even in the presence of transport errors, representativeness errors, and biogenic flux errors. While OCO-2 can detect some of these perturbations at the annual scale, the seasonal sampling provided by ASCENDS provides the stronger constraint. Plain Language Summary: Active and passive remote sensors show the potential to provide unprecedented information on the carbon cycle. With the all-season sampling, active remote sensors are more capable of constraining high-latitude emissions. The reduced sensitivity to cloud and aerosol also makes active sensors more capable of providing information in cloudy and polluted scenes with sufficient accuracy. These experiments account for errors that are fundamental to the top-down approach for constraining emissions, and even including these sources of error, we show that satellite remote sensors are critical for understanding the carbon cycle.

tropical terrestrial biosphere↗