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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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All sourcesNASA NTRSDOE OSTI
DOE OSTI2024

Vegetation Warming Experiment: Environmental Conditions, Utqiagvik (Barrow), Alaska, 2017

Environmental conditions measured in five warming chambers and paired ambient control plots located on the Barrow Environmental Observatory (BEO), Utqiagvik, Alaska from 22 June - 17 September, 2017. These data were recorded in support of the Zero Power Warming (ZPW) vegetation warming experiment, a series of single season vegetation warming treatments conducted over four years from 2017-2021 (no experiment in 2020). Air temperature and humidity, infrared surface (canopy) temperature, soil temperature, soil moisture, NDVI (normalized difference vegetation index), PRI (photochemical reflectance index), solar radiation and chamber venting were recorded in each chamber at 1 minute intervals. Ambient air temperature, humidity, solar radiation and uplooking PRI and NDVI were measured at a centrally located meteorology station. Vapor pressure deficit (VPD) was calculated and included in the final processed data products. Data has undergone full QA/QC and is presented as 1 minute data, and hourly and daily aggregate data products. This data package includes unprocessed raw data (*.dat files), processed data (*.csv) and metadata including a full description of sensors, calculations and processing (*.csv, *.pdf). See related NGEE-Arctic Vegetation Warming Experiment data packages for leaf-level gas exchange and other leaf trait data; chamber, plot and landscape phenocamera images; thaw depth, and GPS locations of chambers and ambient plots. The Next-Generation Ecosystem Experiments: Arctic (NGEE Arctic), was 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

Vegetation Warming Experiment: Environmental conditions, Utqiagvik (Barrow), Alaska, 2021

Environmental conditions measured in five warming chambers and paired ambient control plots located on the Barrow Environmental Observatory (BEO), Utqiagvik, Alaska from 19 June - 17 September, 2021. These data were recorded in support of the Zero Power Warming (ZPW) vegetation warming experiment, a series of single season vegetation warming treatments conducted over four years from 2017-2021 (no experiment in 2020). Air temperature and humidity, infrared surface (canopy) temperature, soil temperature, soil moisture, NDVI (normalized difference vegetation index), PRI (photochemical reflectance index), solar radiation and chamber venting were recorded in each chamber at 1 minute intervals. Ambient air temperature, humidity, solar radiation and uplooking PRI and NDVI were measured at a centrally located meteorology station. Vapor pressure deficit (VPD) was calculated and included in the final processed data products. Data has undergone full QA/QC and is presented as 1 minute data, and hourly and daily aggregate data products. This data package includes unprocessed raw data (*.dat files), processed data (*.csv) and metadata including a full description of sensors, calculations and processing (*.csv, *.pdf). See related NGEE-Arctic "Vegetation Warming Experiment" data packages for leaf-level gas exchange and other leaf trait data; chamber, plot and landscape phenocamera images; thaw depth, and GPS locations of chambers and ambient plots. The Next-Generation Ecosystem Experiments: Arctic (NGEE Arctic), was 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↗
NASA NTRS1992

SIMS studies of oxide growth on beta-NiAl

This paper reports on a study of the growth of aluminum oxide on beta-NiAl at temperatures up to 1200 C. The scales have been formed in two-stage experiments using O2-16 and O2-18 gases, and the various isotopic species have been located by direct imaging using SIMS. Supplementary information on oxide morphologies and structures has been obtained by SEM. SIMS images and depth profiles indicate where oxidation has taken place predominantly by cation or anion diffusion at different stages of the growth process. The way in which the presence of small amounts of reactive elements can affect scale growth is also considered. These results help to provide an improved understanding of the mechanism of alumina scale formation, which is of benefit in the development of oxidation-resistant alloys and intermetallics for service at high temperatures.

Mitchell, D. F.↗
NASA NTRS2003

Automated Serial Sectioning for 3D Reconstruction

Some aspects of an apparatus and method for automated serial sectioning of a specimen of a solder, aluminum, or other relatively soft opaque material are discussed. The apparatus includes a small milling machine (micromiller) that takes precise, shallow cuts (increments of depth as small as 1 micron) to expose successive sections. A microscope equipped with an electronic camera, mounted in a fixed position on the micromiller, takes pictures of the newly exposed specimen surface at each increment of depth. The images are digitized, and the resulting data are subsequently processed to reconstruct three-dimensional (3D) features of the specimen.

Alkemper, Jen↗
NASA NTRS2022

Radiation Tolerance and Mitigation for Neuromorphic Processors

Neuromorphic processors are designed to execute Deep Neural Networks (DNNs) at very high speed using only a fraction of the electrical power needed to run a DNN on a traditional CPU or GPU. This unique capability makes Neuromorphic processors a prime candidate for space systems, where advanced computational tasks like image analysis, depth map reconstruction, or rover control need to be executed in a power-starved environment. In contrast to the growing number of applications of Neuromorphic processors in smart phones, the automotive and robotics domain, the space environment is unforgiving because of extreme temperatures and high levels of radiation. Any space system, operating beyond LEO requires computing hardware that is resilient against radiation effects. However, Neuromorphic processors have not yet been designed or tested for their radiation tolerance. In this report, we consider traditional methods of detection of radiation events and mitigation via redundancy and gauge their effectiveness on DNNs. In contrast to traditional flight software, however, neural networks represent a statistical algorithm, which might affect its resilience against radiation events. We will focus on the analysis of the tolerance of DNNs with respect to radiation events and discuss techniques to detect radiation hits using on-chip triple modular redundancy (TMR) on an Intel Loihi neuromorphic processor and to mitigate radiation damage. We describe an architecture for on-chip TMR for the Intel Loihi and present results of initial experiments.

Neural Networks↗
NASA NTRS1983

Sharp-Focus Composite Microscope Imaging by Computer

Enhanced depth of focus aids medical analysis. Computer image-processing system synthesizes sharply-focused composite picture from series of photomicrographs of same object taken at different depths. Computer rejects blured parts of each photomicrograph. Remaining in focus portions form focused composite. System used to study alveolar lung tissue and has applications in medicine and physical sciences.

Wall, R. J.↗
NASA NTRS1986

Shuttle Imaging Radar - Physical controls on signal penetration and subsurface scattering in the Eastern Sahara

Interpretation of Shuttle Imaging Radar-A (SIR-A) images by McCauley et al. (1982) dramatically changed previous concepts of the role that fluvial processes have played over the past 10,000 to 30 million years in shaping this now extremely flat, featureless, and hyperarid landscape. In the present paper, the near-surface stratigraphy, the electrical properties of materials, and the types of radar interfaces found to be responsible for different classes of SIR-A tonal response are summarized. The dominant factors related to efficient microwave signal penetration into the sediment blanket include (1) favorable distribution of particle sizes, (2) extremely low moisture content and (3) reduced geometric scattering at the SIR-A frequency (1.3 GHz). The depth of signal penetration that results in a recorded backscatter, here called 'radar imaging depth', was documented in the field to be a maximum of 1.5 m, or 0.25 of the calculated 'skin depth', for the sediment blanket. Radar imaging depth is estimated to be between 2 and 3 m for active sand dune materials. Diverse permittivity interfaces and volume scatterers within the shallow subsurface are responsible for most of the observed backscatter not directly attributable to grazing outcrops. Calcium carbonate nodules and rhizoliths concentrated in sandy alluvium of Pleistocene age south of Safsaf oasis in south Egypt provide effective contrast in premittivity and thus act as volume scatterers that enhance SIR-A portrayal of younger inset stream channels.

Schaber, G. G.↗
NASA NTRS1995

Binocular Convergence and Errors in Judged Distance While Using Head-mounted See-through Displays

Previous observations have shown that optical superposition of a physical backdrops at the judged depth of a stereoscopic virtual image moves the judged depth closer to the observer. This effect was more pronounced for slowly moving physical backdrops and was not enhanced when the virtual image was rendered as a flat shaded solid object rather than a open wire-frame. Since this change in rendering making the virtual image more completely occlude the backdrop did not effect its judged depth and since the motion of the backdrop which would have attracted visual attention and binocular convergence did Increase its perceptual displacement, it was concluded that the change In Judged depth was not due to the perceived occlusion. Rather it was concluded to be due to an increase in binocular convergence. An experimental test of this hypothesis using a unobtrusive nonius technique to detect absolute and relative convergence has confirmed the presence of convergence correlated with the magnitude of the change in judged position of this virtual Image. The practical implications of this cause are demonstrated by a second study using monocular, biocular and stereoscopic viewing conditions and the consequences for the design of head-mounted see-through displays for near work are discussed.

Ellis, Stephen R.↗
NASA NTRS1988

Static stereo vision depth distortions in teleoperation

A major problem in high-precision teleoperation is the high-resolution presentation of depth information. Stereo television has so far proved to be only a partial solution, due to an inherent trade-off among depth resolution, depth distortion and the alignment of the stereo image pair. Converged cameras can guarantee image alignment but suffer significant depth distortion when configured for high depth resolution. Moving the stereo camera rig to scan the work space further distorts depth. The 'dynamic' (camera-motion induced) depth distortion problem was solved by Diner and Von Sydow (1987), who have quantified the 'static' (camera-configuration induced) depth distortion. In this paper, a stereo image presentation technique which yields aligned images, high depth resolution and low depth distortion is demonstrated, thus solving the trade-off problem.

Diner, D. B.↗
DOE OSTI2017

Secondary ion mass spectrometry: The application in the analysis of atmospheric particulate matter

Currently, considerable attention has been paid to atmospheric particulate matter (PM) investigation due to its importance in human health and global climate change. Surface characterization of PM is important since the chemical heterogeneity between the surface and bulk may vary its impact on the environment and human being. Secondary ion mass spectrometry (SIMS) is a surface technique with high surface sensitivity, capable of high spatial chemical imaging and depth profiling. Recent research shows that SIMS holds great potential in analyzing both surface and bulk chemical information of PM. In this review, we presented the working principal of SIMS in PM characterization, summarized recent applications in PM analysis from different sources, discussed its advantages and limitations, and proposed the future development of this technique with a perspective in environmental sciences.

aerosol↗
NASA NTRS2023

Spectral and Spatial Dependencies in the Validation of Satellite-Based Aerosol Optical Depth from the Geostationary Ocean Color Imager Using the Aerosol Robotic Network

The regional and global scale of aerosols in the atmosphere can be quantified using the aerosol optical depth (AOD) retrieved from satellite observations. To obtain reliable satellite AODs, conducting consistent validations and refining retrieval algorithms are crucial. AODs and Ångström exponents (AEs) measured with the aerosol robotic network (AERONET) are considered as the ground truth for satellite validations. AERONET AEs are used to collocate the wavelength of the AERONET AODs to those of the satellite AODs when there is a discordancy in their wavelengths. However, numerous validation studies have proposed different strategies by applying the AERONET AODs and AEs, and spatiotemporal collocation criteria. This study examined the impact of the wavelength and spatial collocation radius variations by comparing AODs at 550 nm derived from the geostationary ocean color imager (GOCI) with those obtained from the AERONET for the year 2016. The estimated AERONET AODs at 550 nm varied from 5.18% to 11.73% depending on the selection of AOD and AE, and the spatial collocation radii from 0 to 40 km, respectively. The longer the collocation radius and the higher the AODs, the greater the variability observed in the validation results. Overall, the selection of the spatial collocation radius had a stronger impact on the variability in the validation results obtained compared to the selection of the wavelength. The variability was also found in seasonal analysis. Therefore, it is recommended to carefully select the data wavelength and spatial collocation radius, consider seasonal effects, and provide this information when validating satellite AODs using AERONET.

GOCI↗
DOE OSTI2014

Spatially resolved chemical imaging of individual atmospheric particles using nanoscale imaging mass spectrometry: Insighs into particle origin and chemistry

Knowledge of the spatially-resolved composition of atmospheric particles is essential for differentiating between their surface versus bulk chemistry, understanding particle reactivity and the potential environmental impact. We demonstrate the application of nanometer-scale secondary ion mass spectrometry (Cameca NanoSIMS 50 ion probe) for 3D chemical imaging of individual atmospheric particles without any sample pre-treatment, such as the sectioning of particles. Use of NanoSIMS depth profile analysis enables elemental mapping of particles with nanometer spatial resolution over a broad of range of particle sizes. We have used this technique to probe spatially resolved composition of ambient particles collected during a field campaign in Mexico City. Particles collected during this campaign have been extensively characterized in the past using other particle analysis techniques and hence offer a unique opportunity for exploring the utility of depth resolved chemical imaging in ambient particle research. 1 Particles examined in this study include those collected during a pollution episode related to urban waste incineration as well as background particles from the same location prior to the episode. Particles from the pollution episode show substantial intra-particle compositional variability typical of particles resulting from multiple emission sources. In contrast, the background particles have relatively homogeneous compositions with enhanced presence of nitrogen, oxygen and chlorine at the particle surface. The observed surface enhancement of nitrogen and oxygen species is consistent with the presence of surface nitrates resulting from gas-particle heterogeneous interactions and is indicative of atmospheric ageing of the particles. The results presented here illustrate 3D characterization of ambient particles for insights into their chemical history.

Environmental Molecular Sciences Laboratory↗
NASA NTRS1973

Water penetration study

Nine film-filter combinations have been tested for effectiveness in recording water subsurface detail when exposed from an aerial platform over a typical water body. An experimental 2-layer positive color film, a 2-layer (minus blue layer) film, a normal 3-layer color film, a panchromatic black-and-white film, and an infrared film with selected filters were tested. Results have been tabulated to show the relative capability of each film-filter combination for: (1) image contrast in shallow water (0 to 5 feet); (2) image contrast at medium depth (5 to 10 feet); (3) image contrast in deep water (10 feet plus); (4) water penetration; maximum depth where detail was discriminated; (5) image color (the spectral range of the image); (6) vegetation visible above a water background; (7) specular reflections visible from the water surface; and (8) visual compatibility; ease of discriminating image detail. Recommendations for future recording over water bodies are included.

Lockwood, H. E.↗
NASA NTRS2014

Application of Spectral Analysis Techniques in the Intercomparison of Aerosol Data. Part II: Using Maximum Covariance Analysis to Effectively Compare Spatiotemporal Variability of Satellite and AERONET Measured Aerosol Optical Depth

Moderate Resolution Imaging SpectroRadiometer (MODIS) and Multi-angle Imaging Spectroradiomater (MISR) provide regular aerosol observations with global coverage. It is essential to examine the coherency between space- and ground-measured aerosol parameters in representing aerosol spatial and temporal variability, especially in the climate forcing and model validation context. In this paper, we introduce Maximum Covariance Analysis (MCA), also known as Singular Value Decomposition analysis as an effective way to compare correlated aerosol spatial and temporal patterns between satellite measurements and AERONET data. This technique not only successfully extracts the variability of major aerosol regimes but also allows the simultaneous examination of the aerosol variability both spatially and temporally. More importantly, it well accommodates the sparsely distributed AERONET data, for which other spectral decomposition methods, such as Principal Component Analysis, do not yield satisfactory results. The comparison shows overall good agreement between MODIS/MISR and AERONET AOD variability. The correlations between the first three modes of MCA results for both MODIS/AERONET and MISR/ AERONET are above 0.8 for the full data set and above 0.75 for the AOD anomaly data. The correlations between MODIS and MISR modes are also quite high (greater than 0.9). We also examine the extent of spatial agreement between satellite and AERONET AOD data at the selected stations. Some sites with disagreements in the MCA results, such as Kanpur, also have low spatial coherency. This should be associated partly with high AOD spatial variability and partly with uncertainties in satellite retrievals due to the seasonally varying aerosol types and surface properties.

aerosols↗
NASA NTRS1988

Shifting Of Image Fields For Better Stereoscopic TV Images

Concept for shifting horizontal positions of TV image fields of stereoscopic TV display reduces stereoscopic depth distorting while increasing stereoscopic depth resolution of images. Applicable to form of stereoscopic TV in which two views of scene presented by two video cameras to different fields of one monitor. According to concept, view of left camera shifts to left, and right camera, to right. Images made to overlap, so observed comfortably. Shifting done by inexpensive electronic circuitry.

Diner, Daniel B.↗
DOE OSTI2025

Nondestructive Evaluation of Concrete: Elastic Property Imaging Through Full Waveform Inversion

Concrete is a major construction material worldwide and plays a crucial role in the nuclear industry. The elastic properties of concrete are prone to change and degrade while in service, as it is often subjected to extreme operational and environmental conditions. An accurate evaluation of concrete's elastic properties is thus essential to ensure structural integrity and safety. This is especially true for concrete in nuclear power plants, where irradiation effects significantly impact concrete mechanical properties. There are various methods to assess these properties, with ultrasound-based techniques showing high potential due to their nondestructive nature, cost-effectiveness, and safety. While several nondestructive evaluation methods exist, most rely on idealizations such as assuming homogeneous material and plane wavefronts. In this work, we address these issues by introducing an ultrasound-based nondestructive method aimed at reconstructing spatially varying images of concrete mechanical properties. By accurately modeling wave physics, including scattering and reflection, we overcome several of the aforementioned idealizations and aim to utilize the full waveform for imaging material properties through depth, resulting in more reliable images. Full waveform inversion (FWI) was first introduced by geophysicists to reconstruct subsurface elastic property images. The goal is to minimize the difference between simulated and recorded wavefield signals, often through gradient-based optimization algorithms. While FWI is primarily conducted using the acoustic approximation of the wave equation, few works focus on elastic FWI, where the goal is to reconstruct images of not only the pressure wave speed but also the shear wave speed and density (or their equivalents). This work explores the potential of using elastic FWI to predict concrete mechanical properties as an initial effort for a more accurate monitoring of concrete conditions in service. Reconstructing images of different elastic parameters enables more specificity and accurate condition diagnosis. This paper will detail this approach and provide examples demonstrating the effectiveness of elastic FWI in reconstructing comprehensive maps of concrete mechanical properties.

42 - ENGINEERING↗