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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 1,099 records · Page 61

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NASA NTRS1975

An observation of the high charge cosmic ray nuclei

A double scintillator - double Cerenkov particle telescope, was used to study cosmic ray nuclei with Z greater than 14. This telescope had an exposure of 17,000 sq m-sr-sec and, consequently, the results obtained were of considerable statistical weight. Data are presented on the charge spectrum and on the energy spectrum over the sensitivity range of the Cerenkov detector. The data are compared with data available in the literature, and the implications are discussed.

Scarlett, W. R.↗

NASA NTRS1977

A model of the 1.6 GHz scatterometer

The performance was studied of the 1.6 GHz airborne scatterometer system which is used as one of several Johnson Space Center (JSC) microwave remote sensors to detect moisture content of soil. The system is analyzed with respect to its antenna pattern and coupling, the signal flow in the receiver data channels, and the errors in the signal outputs. The operational principle and the sensitivity of the system, as well as data handling are also described. The finite cross-polarized gains of all four 1.6 GHz scatterometer antennae are found to have profound influence on the cross-polarized backscattered signal returns. If these signals are not analyzed properly, large errors could result in the estimate of the cross-polarized coefficient. It is also found necessary to make corrections to the variations of the aircraft parameters during data reduction in order to minimize the error in the coefficient estimate. Finally, a few recommendations are made to improve the overall performance of the scatterometer system.

Wang, J. R.↗

NASA NTRS1977

A system analysis of the 13.3 GHz scatterometer

The performance of the 13.3 GHz airborne scatterometer system which is used as a microwave remote sensor to detect moisture content of soil is analyzed with respect to its antenna pattern, the signal flow in the receiver data channels, and the errors in the signal outputs. The operational principle and the sensitivity of the system, as well as data handling are also described. The dielectric property of the terrain surface, as far as the scatterometer is concerned, is contained in the assumed forms of the functional dependence of the backscattering coefficient of the incident angle.

Wang, J. R.↗

NASA NTRS1994

Geometrical evidence for dark matter: X-ray constraints on the mass of the elliptical galaxy NGC 720

We describe (1) a new test for dark matter and alternate theories of gravitation based on the relative geometries of the X-ray and optical surface brightness distributions and an assumed form for the potential, of the optical light, (2) a technique to measure the shapes of the total gravitating matter and dark matter of an ellipsoidal system which is insensitive to the precise value of the temperature of the gas and to modest temperature gradients, and (3) a new method to determine the ratio of dark mass to stellar mass that is dependent on the functional forms for the visible star, gas and dark matter distributions, but independent of the distance to the galaxy or the gas temperature. We apply these techniques to X-ray data from the ROSAT Position Sensitive Proportional Counter (PSPC) of the optically flattened elliptical galaxy NGC 720; the optical isophotes have ellipticity epsilon approximately 0.40 extending out to approximately 120 sec. The X-ray isophotes are significantly elongated, epsilon = 0.20-0.30 for semimajor axis a approximately 100 sec. The major axes of the optical and X-ray isophotes are misaligned by approximately 30 deg +/- 15 deg. Spectral analysis of the X-ray data reveals no evidence of temperature gradients or anisotropies and demonstrates that a single-temperature plasma (T approximately 0.6 keV) having subsolar heavy element abundances and a two-temperature model having solar abundances describe the spectrum equally well. Considering only the relative geometries of the X-ray and optical surface brightness distributions and an assumed functional form for the potential of the optical light, we conclude that matter distributed like the optical light cannot produce the observed ellipticities of the X-ray isophotes, independent of the gas pressure, the gas temperature, and the value of the stellar mass; this comparison assumes a state of quasi-hydrostatic equilibrium so that the three-dimensional surfaces of the gas emissivity trace the three-dimensional isopotential surfaces -- we discuss the viability of this assumption for NGC 720. Milgrom's Modification of Newtonian Dynamics (MOND) cannot dispel this manifestation of dark matter. Hence, geometrical considerations require, without mention of pressure or temperature, the presence of an extended, massive dark matter halo in NGC 720. Employing essentially the technique of Buote & Canizares (1992; Buote 1992) we use the shape of the X-ray surface brightness to constrain the shape of the total gravitating matter. The total matter is modeled as either an oblate or prolate spheriod of constant shape and orientation having either a Ferrers (rho approximately r(exp -n)) or Hernquist density. Assuming the X-ray gas is in hydrostatic equilibrium, we construct a model X-ray gas distribution for various temperature profiles. We determine the ellipticity of the total gravitating matter to be epsilon approximately 0.50-0.70. Using the single-temperature model we estimate a total mass approximately (0.41-1.4) x 10(exp 12) h(sub 80) solar mass interior to the ellipsoid of semimajor axis 43.6 h(sub 80) kpc. Ferrers densities as steep as r(exp -3) do not fit the data, but the r(exp -2) and Hernquist models yield excellent fits. We estimate the mass distributions of the stars and the gas and fit the dark matter directly. For a given gas equation of state and functional forms for the visible stars, gas, and dark matter, these models yield a distance-independent and temperature-independent measurement of the ratio of dark mass to stellar mass M(sub DM)/M(sub stars). We estimate a minimum M(sub DM)/M(sub stars) greater than or equal to 4 which corresponds to a total mass slightly greater than that derived from the single-temperature models for distance D = 20h(sub 80) Mpc.

Buote, David A.↗

DOE OSTI2023

Development of a Geothermal Module in reV: Quantifying the Geothermal Potential while Accounting for the Geospatial Intersection of the Grid Infrastructure and Land Use Characteristics

The Renewable Energy Potential (reV) model is a geospatial platform for estimating technical potential and developing renewable energy supply curves, initially developed for wind and solar technologies. The model evaluates deployment constraints, considering land use, environmental, and cultural factors, and estimates the distance to existing grid features to connect future plants (Maclaurin et al., 2021). A pressing deficiency in the reV model, however, is representation of geothermal electricity generation technologies. To address this gap, we developed a novel geothermal generation module for reV that allows for representation and analysis at the same level of detail as other renewable technologies. This paper describes our process for evaluating data sources for the modeling, and presents five preliminary reV geothermal results. More specifically, we present two sets of resource data that represent upper and lower bounds for geothermal potential. We then present several sensitivity runs using the upper bound resource data; the results are encouraging that levelized cost of electricity (LCOE) can be reduced by optimizing the location and estimated capacity of the spatially diverse geothermal resource while considering the distance to existing grid infrastructure. Our preliminary supply curves and levelized cost of electricity (LCOE) results should be considered with care due to the highly uncertainty in geothermal resource potential data. We present median LCOE values for the conterminous U.S. for five scenarios: four hydrothermal (3.5km depth) and one EGS (4.5km depth). The capital and operating costs for each respective technology are modeled. We also compare results using two different resource data sources.

exclusions↗

DOE OSTI2024

Development of a Geothermal Module in reV: Quantifying the Geothermal Potential While Accounting for the Geospatial Intersection of the Grid Infrastructure and Land Use Characteristics: Preprint

exclusions↗

DOE OSTI2025

The DECADE cosmic shear project III: validation of analysis pipeline using spatially inhomogeneous data

We present the pipeline for the cosmic shear analysis of the Dark Energy Camera All Data Everywhere (DECADE) weak lensing dataset: a catalog consisting of 107 million galaxies observed by the Dark Energy Camera (DECam) in the northern Galactic cap. The catalog derives from a large number of disparate observing programs and is therefore more inhomogeneous across the sky compared to existing lensing surveys. First, we use simulated data-vectors to show the sensitivity of our constraints to different analysis choices in our inference pipeline, including sensitivity to residual systematics. Next we use simulations to validate our covariance modeling for inhomogeneous datasets. Finally, we show that our choices in the end-to-end cosmic shear pipeline are robust against inhomogeneities in the survey, by extracting relative shifts in the cosmology constraints across different subsets of the footprint/catalog and showing they are all consistent within 1σ to 2σ. This is done for forty-six subsets of the data and is carried out in a fully consistent manner: for each subset of the data, we re-derive the photometric redshift estimates, shear calibrations, survey transfer functions, the data vector, measurement covariance, and finally, the cosmological constraints. Our results show that existing analysis methods for weak lensing cosmology can be fairly resilient towards inhomogeneous datasets. This also motivates exploring a wider range of image data for pursuing such cosmological constraints.

79 ASTRONOMY AND ASTROPHYSICS↗

NASA NTRS2022

Intrinsic Dimensionality as a Metric for the Impact of Mission Design Parameters

High-resolution space-based spectral imaging of the Earth's surface delivers critical information for monitoring changes in the Earth system as well as resource management and utilization. Orbiting spectrometers are built according to multiple design parameters, including ground sampling distance (GSD), spectral resolution, temporal resolution, and signal-to-noise ratio. Different applications drive divergent instrument designs, so optimization for wide-reaching missions is complex. The Surface Biology and Geology component of NASA's Earth System Observatory addresses science questions and meets applications needs across diverse fields, including terrestrial and aquatic ecosystems, natural disasters, and the cryosphere. The algorithms required to generate the geophysical variables from the observed spectral imagery each have their own inherent dependencies and sensitivities, and weighting these objectively is challenging. Here, we introduce intrinsic dimensionality (ID), a measure of information content, as an applications-agnostic, data-driven metric to quantify performance sensitivity to various design parameters. ID is computed through the analysis of the eigenvalues of the image covariance matrix, and can be thought of as the number of significant principal components. This metric is extremely powerful for quantifying the information content in high-dimensional data, such as spectrally resolved radiances and their changes over space and time. We find that the ID decreases for coarser GSD, decreased spectral resolution and range, less frequent acquisitions, and lower signal-to-noise levels. This decrease in information content has implications for all derived products. ID is simple to compute, providing a single quantitative standard to evaluate combinations of design parameters, irrespective of higher-level algorithms, products, applications, or disciplines.

Intrinsic dimensionality↗

DOE OSTI2023

Understanding the trade-offs of national municipal solid waste estimation methods for circular economy policy

Policies embracing circular economy concepts have taken hold in national legislation around the world. As the number of governments and organizations adopting circular economy policies increases, so does the need for accurate and timely measurement of material resource flows. Since many countries do not have access to centrally reported municipal solid waste (MSW) data, estimation and modeling are critical in evaluating circular economy policy effectiveness. The purpose of this paper is to examine three modeling approaches estimating national MSW data in the United States, including industry-based material flow analysis, waste-extended input-output modeling, and aggregated regional waste reporting. We establish five criteria to guide the analysis through the context of policy monitoring (data quality, flow totality, update frequency, sensitivity to disruption, and product granularity) and use these criteria to analyze and score each model. We then use a literature search to identify five, internationally-implemented options for circular economy policy and determine the data and modeling components that are most helpful in evaluating policy effectiveness. Finally, we provide a crosswalk of the model scores and policy needs to inform the suitability of model selection by policy type. We found that data quality and update frequency are identified as critical components for evaluating circular economy policies within the models evaluated, and can both be fulfilled by aggregated regional waste reporting. Flow totality, sensitivity to disruption, and product granularity requirements vary by both model and policy types. While none of the evaluated models satisfy the combination of requirements for any of the five policies, industry-based material flow analysis offers flow totality for extended producer responsibility, landfill bans, and recycling rate target policies that typically require it. Here, the waste-extended input-output model can provide disruption sensitivity and product granularity as needed for policies like minimum recycled content and market restrictions. Policy developers in areas where strong centralized data collection is not an option should design policy action(s) with modeling tradeoffs in mind, including the potential hybridization of modeling approaches that may provide the most accurate national MSW estimates.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗

NASA NTRS1982

SUMS calibration test report

Calibration was performed on the shuttle upper atmosphere mass spectrometer (SUMS). The results of the calibration and the as run test procedures are presented. The output data is described, and engineering data conversion factors, tables and curves, and calibration on instrument gauges are included. Static calibration results which include: instrument sensitive versus external pressure for N2 and O2, data from each scan of calibration, data plots from N2 and O2, and sensitivity of SUMS at inlet for N2 and O2, and ratios of 14/28 for nitrogen and 16/32 for oxygen are given.

Robertson, G.↗

NASA NTRS1986

Unstalled flutter stability predictions and comparisons to test data for a composite prop-fan model

The aeroelastic stability analyses for three graphite/epoxy composite Prop-Fan designs and post-test stability analysis for one of the designs, the SR-3C-X2 are presented. It was shown that Prop-Fan stability can be effectively analyzed using the F203 modal aeroelastic stability analysis developed at Hamilton Standard and that first mode torsion-bending coupling has a direct effect on blade stability. Positive first mode torsion-bending coupling is a destabilizing factor and the minimization of this parameter will increase Prop-Fan stability. It was also shown that Prop-Fan stability analysis using F203 is sensitive to the blade modal data used as input. Calculated blade modal properties varied significantly with the structural analysis used, and these variations are reflected in the F203 calculations.

Turnberg, J. E.↗

NASA NTRS1989

Use of piezoelectric foil for flow diagnostics

A laboratory investigation was conducted to characterize two piezoelectric-film sensor configurations, a rigidly mounted sensor and a sensor mounted over an air cavity. The sensors are evaluated for sensitivity and frequency response, and methods to optimize data are presented. The cavity-mounted sensor exhibited a superior frequency response and was more sensitive to normal pressure fluctuations and less sensitive to vibrations through the structure. Both configurations were sensitive to large-scale structural vibrations. Flight-test data are shown for cavity-mounted sensors, illustrating practical aspects to consider when designing sensors for application in such harsh environments. The relation of the data to skin friction and maximum shear stress, transition detection, and turbulent viscous layers is derived through analysis of the flight data.

Carraway, Debra L.↗

DOE OSTI2020

Neural Learning Based Blind Source Separation for Detection of Material Defects in Pulsed Thermography Images

In this paper, we introduce a neural learning-based approach to blind source separation for detection of material flaws in pulsed thermography (PT) images. This approach can be used to detect internal defects (pores) in metallic Additively Manufactured (AM) materials. Such defects occur in high-strength alloys produced with direct laser sintering AM method for nuclear energy applications. Pulsed thermal imaging system utilizes a high intensity flash lamp to rapidly heat surface of sample, a high sensitivity infrared camera to capture data of surface temperature variations. The data cube obtained with PT (stack of surface temperature images at different times) can be analyzed with image processing algorithms to detect material defects. Compared with conventional nondestructive evaluation (NDE) methods, such as digital radiography and ultrasonic testing, the PT pulsed infrared thermal detection technique has advantages of one-sided non-contact measurements, fast processing of large sample areas captured in one image. Detection of small material defects requires finding features in thermal images, which have signal contrast levels approaching sensitivity limit of IR camera. In this study, an optimized Neural Learning based Blind Source Separation (NLBSS) algorithm, including Principal Component Analysis (PCA), and Independent Component Analysis (ICA) is demonstrated to automatically extract principal temporal and spatial features of thermography frames to enhance flaw detection. By using the NLBSS algorithm, material internal defects can be automatically detected. Furthermore, this processing approach compensates for experimental thermal imaging artifacts, such as noise and uneven heating. By merging artificial intelligence with the photothermic, the NDE system detects internal calibrated defects of various sizes and depths in AM nuclear-grade metallic alloys.

Zhang, Xin↗

NASA NTRS1990

Cloud cover analysis with Arctic Advanced Very High Resolution Radiometer data. II - Classification with spectral and textural measures

The spectral and textural characteristics of polar clouds and surfaces for a 7-day summer series of AVHRR data in two Arctic locations are examined, and the results used in the development of a cloud classification procedure for polar satellite data. Since spatial coherence and texture sensitivity tests indicate that a joint spectral-textural analysis based on the same cell size is inappropriate, cloud detection with AVHRR data and surface identification with passive microwave data are first done on the pixel level as described by Key and Barry (1989). Next, cloud patterns within 250-sq-km regions are described, then the spectral and local textural characteristics of cloud patterns in the image are determined and each cloud pixel is classified by statistical methods. Results indicate that both spectral and textural features can be utilized in the classification of cloudy pixels, although spectral features are most useful for the discrimination between cloud classes.

Key, J.↗

NASA NTRS2003

Gravity Models from CHAMP and other Satellite Data

CHAMP spacecraft is the first of a series of new spacecraft missions that are revolutionizing our ability to model the Earth's geopotential. We report on the analysis of over 100 days of CHAMP data in 2001 and 2002, merged with tracking data of other satellites such as Jason, Topex, GFO, Starlette, Stella, Spot-2, as well as satellite altimetry. We find that the CHAMP-only component of these solutions is a significant improvement over pre-CHAMP satellite only models with respect to the high degree information expressed by the geopotential model coefficients. For example, the variance of the differences with altimeter-derived anomalies through degree 70 is 2.80 mGal(sup 2) for the CHAMP-only solution based on 87 days of data vs. 10.19 mGal(sup 2) for EGM96S. Nonetheless, in order to model properly the various resonances to which different satellites are sensitive, we must include other satellite data. We evaluate the performance of these new CHAMP derived solutions with EGM96 and the EIGEN series of solutions. We review carefully the performance of these models for altimetric satellites.

Lemoime, Frank G.↗

NASA NTRSDate not supplied

How Well Satellite Remote Sensing Can Inform Surface Level Ozone Production Sensitivity to Precursor Trace Gas Emissions?

Surface-level ozone (O3) pollution mitigation strategies rely on a clear understanding of the atmospheric chemical processes involving O3, NOx (nitric oxide (NO) + nitrogen dioxide (NO2)) and volatile organic compounds (VOCs). A robust spatiotemporal classification of O3 photochemical regimes with relative chemical sensitivity of local O3 formation to emission reductions of NOx (NOx-limited regime) versus VOCs (radical-limited regime) is required to design anthropogenic emission reduction policies in order to improve surface air quality. Numerous studies found that the ratio of satellite-retrieved Vertical Column Densities (VCDs) of formaldehyde (HCHO) to NO2 can diagnose O3 production sensitivity. However, uncertainty still remains about the accuracy of such estimates using satellite-based retrievals. This study conducts an investigation to identify how well satellite data can inform surface-level O3 sensitivity by validating satellite-based estimates against aircraft-based retrievals taken during the Long Island Sound Tropospheric Ozone Study (LISTOS-2018) and Ozone Water-Land Environmental Transition Study (OWLETS-2) field campaigns. For this study, we use HCHO and NO2 retrievals from the Ozone Monitoring Instrument (OMI) onboard the Aura satellite, and high spatiotemporal resolution TROPOspheric Monitoring Instrument (TROPOMI) onboard the Sentinel-5 Precursor (S5P) satellite. The Community Multiscale Air Quality (CMAQ) modelling system is used to provide trace gas vertical profiles to recalculate air mass factor for deriving consistent satellite-based VCDs. To demonstrate the ability of satellites to diagnose O3 production regimes, we validate satellite-derived O3 sensitivity regimes, along with the OMI and TROPOMI products applied, using HCHO and NO2 retrievals from the aircraft-based instruments: Geostationary Trace gas and Aerosol Sensor Optimization (GeoTASO) spectrometer and Geostationary Coastal and Air Pollution Events Airborne Simulator (GCAS) instruments deployed during the LISTOS-2018 and OWLETS-2 campaigns. The results of this work will advance our fundamental knowledge of the spatiotemporal evolution of the complex O3-NOx-VOC chemistry, and will advance our understanding about the quality of remote-sensing, suborbital, and satellite data for accurately observing surface-level O3 production sensitivity.

Satellite↗

DOE OSTI2021

Constrained non-negative matrix factorization enabling real-time insights of in situ and high-throughput experiments

Non-negative matrix factorization (NMF) is an appealing class of methods for performing unsupervised learning on streaming spectral data, particularly in time-sensitive applications such as in situ characterization of materials. These methods seek to decompose a dataset into a small number of components and weights that can compactly represent the underlying signal while effectively reconstructing the observations with minimal error. However, canonical NMF methods have no underlying requirement that the reconstruction uses components or weights that are representative of the true physical processes. In this work, we demonstrate how constraining a subset of the NMF weights or components as rigid priors, provided as known or assumed values, can provide significant improvement in revealing true underlying phenomena. We present a PyTorch-based method for efficiently applying constrained NMF and demonstrate its application to several synthetic examples. Our implementation allows an expert researcher-in-the-loop to provide and dynamically adjust the constraints during a live experiment involving streaming spectral data. Such interactive priors allow researchers to specify known or identified independent components, as well as functional expectations about the mixing or transitions between the components. We further demonstrate the application of this method to measured synchrotron x-ray total scattering data from in situ beamline experiments. In such a context, constrained NMF can result in a more interpretive and scientifically relevant decomposition than canonical NMF or other decomposition techniques. As a result, the details of the method are provided, along with general guidance for employing constrained NMF in the extraction of critical information and insights during time-sensitive experimental applications.

36 MATERIALS SCIENCE↗

NASA NTRS1989

Organic chemistry of cometary dust as derived from PUMA 1 data

Onboard the Halley Fly-By spacecrafts Vega 1, Vega 2, and Giotto were the dust impact mass spectrometers PUMA 1, PUMA 2, and PIA respectively. PUMA 1 was the most sensitive instrument among them. From its data the occurrence of masslines greater than 60 Daltons could be shown to be statistically significant. An analysis of these masslines lead to a scenario, which could explain the masslines as fragment ions from larger molecules which characterize the chemical nature of cometary organic matter as: (1) highly unsaturated hydrocarbons; (2) some of them containing oxygen; (3) less containing nitrogen; and (4) a few containing oxygen and nitrogen as heteroatoms. From the properties of the spectrometer, also some physical parameters of the dust particles could be inferred, such as their density and structure.

Kissel, J.↗