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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 1,351 records · Page 75
All sourcesNASA NTRSDOE OSTI
DOE OSTI2021

Joint impedance and facies inversion of time-lapse seismic data for improving monitoring of CO 2 incidentally stored from CO 2 EOR

Time-lapse seismic monitoring is an effective and proven technology for mapping the distribution of CO 2 in a subsurface reservoir. When injected CO 2 displaces other reservoir fluids, porous-medium properties are changed and thus the seismic impedance changes, causing time-lapse seismic amplitude differences in the injection zones. The analysis and interpretation of images created from these amplitude differences can provide information about reservoir architecture and the CO 2 migration within the reservoir. Incorporating seismic inversion and rock physics into the interpretation of time-lapse seismic data can considerably improve the modeling and monitoring to detect and assess the location of CO 2 over time. The joint inversion method presented in this paper has an integral representation of the geology in the inversion algorithm using elastic facies, which provides information about the spatial distribution of the geologic heterogeneities controlling the movement of fluids in the reservoir. The method was successfully applied to time-lapse seismic data from a mature oil field undergoing CO 2 enhanced oil recovery. The estimated seismic acoustic impedances and facies reflect the characteristics of individual geologic facies and fluid conditions of the reservoir subject to CO 2 injection. Finally, the probabilities estimated by the joint impedance and facies inversion for the reservoir's litho-fluid facies can be used for forecasting CO 2 saturation and pressure changes within the target reservoir.

4D seismic↗
DOE OSTI2017

In situ frustum indentation of nanoporous copper thin films

Mechanical properties of thin films are often obtained solely from nanoindentation. At the same time, such measurements are characterized by a substantial amount of uncertainty, especially when mean pressure or hardness are used to infer uniaxial yield stress. In this paper we demonstrate that indentation with a pyramidal flat tip (frustum) indenter near the free edge of a sample can provide a significantly better estimate of the uniaxial yield strength compared to frequently used Berkovich indenter. This is first demonstrated using a numerical model for a material with an isotropic pressure sensitive yield criterion. Numerical simulations confirm that the indenter geometry provides a clear distinction of the mean pressure at which a material transitions to inelastic behavior. The mean critical pressure is highly dependent on the plastic Poisson ratio ν p so that at the 1% offset of normalized indent depth, the critical pressure p m c normalized to the uniaxial yield strength σ 0 is 1 < p m c /σ 0 < 1.3 for materials with 0 < ν p < 0.5. Choice of a frustum over Berkovich indenter reduces uncertainty in hardness by a factor of 3. These results are used to interpret frustum indentation experiments on nanoporous (NP) Copper with struts of typical diameter of 45 nm. An estimate of the yield strength of NP Copper is obtained 230 MPa < σ 0 < 300 MPa. Edge indentation further allows one to obtain in-plane strain maps near the critical pressure. Finally, comparison of the experimentally obtained in-plane strain maps of NP Cu during deformation and the strain field for different plastic Poisson ratios suggest that this material has a plastic Poisson ratio of the order of 0.2–0.3. However, existing constitutive models may not adequately capture post-yield behavior of NP metals.

36 MATERIALS SCIENCE↗
NASA NTRS1973

Ice development on Lake Champlain

The author has identified the following significant results. Only one usable ERTS-1 scene was available for lake ice survey of Lake Champlain. The January 8, 1973, coverage (image no. 1169-11521) revealed the presence of various ice tones, patterns, and arrangements as well as open water. MSS band 5 imagery provided the most useful data. While it was not possible to differentiate open water from one - two day old ice, which only occurred over a small portion of the lake area, it was possible to interpret the tonal signatures of the frozen portion in terms of freezing history or age. The dark gray-tones of new, smooth ice contrasts with the medium gray-tones of older ice, and the rough texture of wind-jammed bay ice. Mapping of these patterns seems quite feasible with moderate enlargement of the scene (2 to 3X).

Lind, A. O.↗
NASA NTRS1977

Investigation of the effects of construction and stage filling of reservoirs on the environment and ecology: Preproject baseline

The author has identified the following significant results: (1) LANDSAT imagery can be used effectively as a baseline for detection of environmental change, resulting from construction of a major inland reservoir. (2) Forest cover can be observed adequately on two-band composite enlargements at a scale of 1:130,000. (3) Forest cover delineated on LANDSAT enlargements compares accurately with ground truth at a scale of 1:250,000. (4) A dual image mapping technique superimposing winter, summer, and spring scenes using the zoom transfer scope facilitates the determination. (5) The same technique can be used to detect changes in the project area, resulting from construction activities. (6) High altitude aircraft imagery can also be used to interpret changes in land use and forest type. (7) Construction operations can be more clearly detailed on the air photos than on LANDSAT imagery.

Riggins, R. E.↗
NASA NTRS1978

A manual for inexpensive methods of analyzing and utilizing remote sensor data

Instructions are provided for inexpensive methods of using remote sensor data to assist in the completion of the need to observe the earth's surface. When possible, relative costs were included. Equipment need for analysis of remote sensor data is described, and methods of use of these equipment items are included, as well as advantages and disadvantages of the use of individual items. Interpretation and analysis of stereo photos and the interpretation of typical patterns such as tone and texture, landcover, drainage, and erosional form are described. Similar treatment is given to monoscopic image interpretation, including LANDSAT MSS data. Enhancement techniques are detailed with respect to their application and simple techniques of creating an enhanced data item. Techniques described include additive and subtractive (Diazo processes) color techniques and enlargement of photos or images. Applications of these processes, including mappings of land resources, engineering soils, geology, water resources, environmental conditions, and crops and/or vegetation, are outlined.

Elifrits, C. D.↗
NASA NTRS1981

Elevation of a cane-growing area of the state of Sao Paulo using LANDSAT data

Images at a scale of 1:250.000 were visually interpreted for identification and area estimates of sugar cane plantations in Sao Paulo. The basic criteria for crop identification were the spectral characteristics of channels 5 and 7 and their temporal variations observed from different LANDSAT passes. Using this technique, it was possible to map the sugar cane areas as well as the sugar cane already harvested. An area of 801,950 hectares was estimated within the study area. The confidence interval of correct classification ranged from 87.11% to 94.71%.

Dejesusparada, N.↗
NASA NTRS1984

Passive microwave remote sensing for sea ice research

Techniques for gathering data by remote sensors on satellites utilized for sea ice research are summarized. Measurement of brightness temperatures by a passive microwave imager converted to maps of total sea ice concentration and to the areal fractions covered by first year and multiyear ice are described. Several ancillary observations, especially by means of automatic data buoys and submarines equipped with upward looking sonars, are needed to improve the validation and interpretation of satellite data. The design and performance characteristics of the Navy's Special Sensor Microwave Imager, expected to be in orbit in late 1985, are described. It is recommended that data from that instrument be processed to a form suitable for research applications and archived in a readily accessible form. The sea ice data products required for research purposes are described and recommendations for their archival and distribution to the scientific community are presented.

Source record↗
NASA NTRS1992

Mapping the spectral variability in photosynthetic and non-photosynthetic vegetation, soils, and shade using AVIRIS

The primary objective of this research was to map as many spectrally distinct types of green vegetation (GV), non-photosynthetic vegetation (NPV), shade, and soil (endmembers) in an Airborne Visible/Infrared Imaging Spectrometer (AVIRIS) scene as is warranted by the spectral variability of the data. Once determined, a secondary objective was to interpret these endmembers and their abundances spatially and spectrally in an ecological context.

Roberts, Dar A.↗
DOE OSTI2025

Signal-preserving CMB component separation with machine learning

Analysis of microwave sky signals, such as the cosmic microwave background, often requires component separation using multifrequency methods, whereby different signals are isolated according to their different frequency behaviors. Many so-called blind methods, such as the internal linear combination (ILC), make minimal assumptions about the spatial distribution of the signal or contaminants, and only assume knowledge of the frequency dependence of the signal. The ILC produces a minimum-variance linear combination of the measured frequency maps. In the case of Gaussian, statistically isotropic fields, this is the optimal linear combination, as the variance is the only statistic of interest. However, in many cases the signal we wish to isolate, or the foregrounds we wish to remove, are non-Gaussian and/or statistically anisotropic (in particular for the case of Galactic foregrounds). In such cases, it is possible that machine learning (ML) techniques can be used to exploit the non-Gaussian features of the foregrounds and thereby improve component separation. However, many ML techniques require the use of complex, difficult-to-interpret operations on the data. We propose a hybrid method whereby we train an ML model using only combinations of the data that , and combine the resulting ML-predicted foreground estimate with the ILC solution to reduce the error from the ILC. We demonstrate our methods on simulations of extragalactic temperature and Galactic polarization foregrounds and show that our ML model can exploit non-Gaussian features, such as point sources and spatially varying spectral indices, to produce lower-variance maps than ILC—e.g., reducing the variance of the B-mode residual by factors of up to 5—while preserving the signal of interest in an unbiased manner. Moreover, we often find improved performance even when applying our ML technique to foreground models on which it was not trained. Published by the American Physical Society 2025

McCarthy, Fiona (ORCID:0000000253893565)↗
DOE OSTI2023

$\text{GPLaSDI}$: Gaussian Process-based interpretable Latent Space Dynamics Identification through deep autoencoder

Numerically solving partial differential equations (PDEs) can be challenging and computationally expensive. This has led to the development of reduced-order models (ROMs) that are accurate but faster than full order models (FOMs). Recently, machine learning advances have enabled the creation of non-linear projection methods, such as Latent Space Dynamics Identification (LaSDI). LaSDI maps full-order PDE solutions to a latent space using autoencoders and learns the system of ODEs governing the latent space dynamics. By interpolating and solving the ODE system in the reduced latent space, fast and accurate ROM predictions can be made by feeding the predicted latent space dynamics into the decoder. In this paper, we introduce GPLaSDI, a novel LaSDI-based framework that relies on Gaussian process (GP) for latent space ODE interpolations. Using GPs offers two significant advantages. First, it enables the quantification of uncertainty over the ROM predictions. Second, leveraging this prediction uncertainty allows for efficient adaptive training through a greedy selection of additional training data points. This approach does not require prior knowledge of the underlying PDEs. Consequently, GPLaSDI is inherently non-intrusive and can be applied to problems without a known PDE or its residual. Here we demonstrate the effectiveness of our approach on the Burgers equation, Vlasov equation for plasma physics, and a rising thermal bubble problem. Our proposed method achieves between 200 and 100,000 times speed-up, with up to 7% relative error.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2025

Unveiling X-ray absorption signatures of boron nitride via first-principles simulation and machine learning

Boron nitride (BN) allotropes hold great promise in many advanced applications ranging from optical and photonic devices to energy storage and battery systems to tribological components. The diverse functionalities of this material stem from BN’s highly tunable structural and electronic properties, which are governed by the versatile boron–nitrogen bonding configurations. Exploring the structural landscape of BN can unveil novel structures possessing unique properties suited for specific applications, therefore accelerating the design of next-generation advanced functional materials. In this work, we leverage boron K-edge X-ray absorption spectroscopy (XAS) as an effective probe for local structural features and chemical environments. A total of 210 BN crystal structures are generated via analogies to the extensive array of carbon allotropes, and XAS is simulated for each unique local motif within the resulting collection of structures. A mapping between structural features and spectral signatures was established by synergizing first-principle simulations with data-driven based post-analysis approaches. Specifically, we developed a neural network model that can satisfactorily predict spectra line shapes from local structural descriptors. Toward automatic spectroscopic interpretation of any new BN structures, supervised machine learning models, trained on this structure–spectrum dataset, can accurately infer local coordination environments from simulated XAS, highlighting the strength of this unique approach of combining high-fidelity first-principles simulation and machine-learning to accelerate target design of novel BN materials via rational understanding of local structure-spectrum correlations.

36 MATERIALS SCIENCE↗
DOE OSTI2023

AlphaFold predictions are valuable hypotheses and accelerate but do not replace experimental structure determination

Abstract Artificial intelligence-based protein structure prediction methods such as AlphaFold have revolutionized structural biology. The accuracies of these predictions vary, however, and they do not take into account ligands, covalent modifications or other environmental factors. Here, we evaluate how well AlphaFold predictions can be expected to describe the structure of a protein by comparing predictions directly with experimental crystallographic maps. In many cases, AlphaFold predictions matched experimental maps remarkably closely. In other cases, even very high-confidence predictions differed from experimental maps on a global scale through distortion and domain orientation, and on a local scale in backbone and side-chain conformation. We suggest considering AlphaFold predictions as exceptionally useful hypotheses. We further suggest that it is important to consider the confidence in prediction when interpreting AlphaFold predictions and to carry out experimental structure determination to verify structural details, particularly those that involve interactions not included in the prediction.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2013

INTERFEROMETRIC OBSERVATIONS OF NITROGEN-BEARING MOLECULAR SPECIES IN THE STAR-FORMING CORE AHEAD OF HH 80N

We present Very Large Array NH{sub 3} and Plateau de Bure Interferometer NH{sub 2}D and HN{sup 13}C observations of the star-forming core ahead of HH 80N, the optically obscured northern counterpart of the Herbig-Haro objects HH 80/81. The main goal is to determine the kinematical information of the high density regions of the core (n ∼> 10{sup 5} cm{sup –3}) missed in previous works due to the depletion of the species observed (e.g., CS). The obtained maps show different kinematical signatures between the eastern and western parts of the core, suggesting a possible dynamical interaction of the core with the HH 80/81/80N outflow. The analysis of the position-velocity (P-V) plots of these species rules out a previous interpretation of having a molecular ring-like structure with a radius of 6 × 10{sup 4} AU traced by CS infalling onto a central protostar found in the core (IRS1). A high degree of NH{sub 3} deuteration, with respect to the central part of the core harboring IRS1, is derived in the eastern part, where a dust condensation (SE) is located. This deuteration trend of NH{sub 3} suggests that SE is in a pre-stellar evolutionary stage, earlier than that of IRS1. Since SE is the closest condensation to the HH 80N/81/80N outflow, in a case of outflow-core dynamical interaction, it should be perturbed first and be the most evolved condensation in the core. Therefore, the derived evolutionary sequence for SE and IRS1 makes outflow triggered star formation on IRS1 unlikely.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2025

Position-Dependent Neutron Time-of-Flight Deviation at VULCAN Diffractometer

In neutron diffraction, it is critical to precisely measure the lattice spacing, as it is an indicator of a material’s physical characteristics, such as lattice strain, thermal expansion, and phase structures. In time-of-flight (TOF) measurements, the lattice spacing is determined by the recorded TOF from a well-calibrated instrument. However, changes in neutron time-of-flight are sensitive to many factors, such as the alignment of instrument optics, temperature, sample positions, sample dimensions, internal strains, and chemical or physical heterogeneities at the grain level. At VULCAN (SNS, ORNL), which is a high-flux engineering neutron diffractometer, we used a 1-mm-diameter diamond powder sample to scan for changes in TOF by measuring d-spacing values at different sample positions under several configurations. The 2D map of the TOF deviation or d-spacing deviation, in terms of lattice shift/lattice strain, is reported. The change in TOF is dependent on the scanned location in the beam as well as on detector locations. The results are informative for experimental planning, data interpretation, and future instrument design.

36 MATERIALS SCIENCE↗
NASA NTRS1970

Recent advances in radar applications to agriculture

A series of remote radar sensing studies are summarized. These efforts comprise geoscience interpretations of such complex phenomena as those manifested in agricultural patterns. Considered are basic remote sensing needs in agriculture and the design and implementation of radar keys in the active microwave region as well as fine resolution radar imagery techniques for agriculture determinations and soil mapping.

Morain, S. A.↗
NASA NTRS1972

An interdisciplinary analysis of ERTS data for Colorado mountain environments using ADP techniques. An early analysis of ERTS-1 data

There are no author-identified significant results in this report. The principal problem encountered has been the lack of good quality, small scale baseline photography for the test areas. Analysis of the ERTS-1 data for the San Juan Site will emphasize development of a preliminary spectral classification defining grass cover categories, and then selection of subframes for intensive investigation of the forestry, geologic, and hydrologic properties of the area. Primary work has been devoted to the selection and digitization of areas for topographic modeling, and compilation of ground based data maps necessary for computer analysis. Study effort has emphasized: geomorphic features; macro-vegetation; micro-vegetation; snow-hydrology; insect/disease damage; and blow-down. Analysis of a frame of the Lake Texoma area indicates a great deal of potential in the analysis and interpretation of ERTS imagery. Preliminary results of investigations of geologic, forest, range, cropland, and water resources of the area are summarized.

Hoffer, R. M.↗
NASA NTRS1977

A comparison of photointerpretive and digital production methods for four key remote sensing-based information products

This paper evaluates the costs of producing four remote sensing-based information products: timber volume estimate tables, Level II land use/land cover maps, soil maps, and vegetative cover maps. Two production methods for each product are evaluated, one is based on digital processing of satellite data, and the other on conventional photointerpretation of aircraft data. For each product, a comparison is conducted of the two strategies' production costs (including data acquisition, 'ground truthing', interpretation, compilation, and printing charges) and their performance (as measured by accuracy and timeliness). Each of the production methods reviewed has been demonstrated - either operationally or experimentally - and the costs, timeliness and other performance estimates presented are based on observations made in practice. The results show that for these products, satellite-based production results in significant cost and timeliness improvements at the cost of a loss in accuracy.

Eastwood, L. F., Jr.↗
NASA NTRS1979

Evidence for a variable far-infrared source in NGC 6334

NGC 6334 has been mapped with a 40-250 micron photometer with 1 arcmin resolution. Six sources of far-infrared radiation have been detected. The second-strongest source was not detected in an earlier (2.7 years) 40-350 micron survey of the same region. This source is interpreted as a variable far-infrared source. The new source, located at the position of OH and H2O maser sources, is extended (0.7 arcmin FWHM) and has a bolometric luminosity of 190,000 solar luminosities and may represent a hitherto unobserved transient stage of protostellar collapse.

Mcbreen, B.↗