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At least 1,477 records · Page 82
All sourcesNASA NTRSDOE OSTI
DOE OSTI2024

LYNM PE1 Pre-Experiment A Site Characterization Report

Underground chemical explosive experiments such as LYNM PE1 generate large multiphenomenological datasets, require complex site preparation and build out, and utilize cutting edge models and analysis techniques to analyze and simulate the explosion-induced signals. This wide range of outcomes makes it a necessity to thoroughly characterize the testbed in advance of experiments in a way that complements the wide suite of data being generated. Here, we present a broad overview of the site characterization work and data collection that was conducted before Experiment A, which is the first in a series of three PE1 experiments. This work includes, but is not limited to, geologic mapping, physical sample collection, analysis of material properties, geophysical borehole logging, and in-situ measurements. This information was collected by a large, dedicated team and was used to inform site construction, finalize instrumentation placement, generate Geologic Framework Models, feed pre-experiment predictions, and facilitate post-experiment data analysis

58 GEOSCIENCES↗
DOE OSTI2024

LYNM PE1 Pre-Experiment A Site Characterization Report

Underground chemical explosive experiments such as LYNM PE1 generate large multi-phenomenological datasets, require complex site preparation and build out, and utilize cutting edge models and analysis techniques to analyze and simulate the explosion-induced signals. This wide range of outcomes makes it a necessity to thoroughly characterize the testbed in advance of experiments in a way that complements the wide suite of data being generated. Here, we present a broad overview of the site characterization work and data collection that was conducted before Experiment A, which is the first in a series of three PE1 experiments. This work includes, but is not limited to, geologic mapping, physical sample collection, analysis of material properties, geophysical borehole logging, and in-situ measurements. This information was collected by a large, dedicated team and was used to inform site construction, finalize instrumentation placement, generate Geologic Framework Models, feed pre-experiment predictions, and facilitate post-experiment data analysis.

45 MILITARY TECHNOLOGY, WEAPONRY, AND NATIONAL DEF↗
DOE OSTI2026

Interpretable Deep Learning for Advancing Field-Enhanced Catalysis

This DOE Early Career project developed a physics-informed, interpretable AI-and-modeling framework to understand and exploit electric-field effects in heterogeneous catalysis, with ammonia cracking and synthesis as a representative pathway. The team built and validated methods to map local electric fields on metal surfaces and nanoparticles, showing that low-coordination features (tips/edges/corners) can concentrate fields by several-fold relative to flat facets. Using DFT-generated datasets, the project created physics-guided machine learning models that rapidly predict local electric fields and field-dependent adsorption energetics with near-DFT accuracy while reducing computational cost by orders of magnitude. These predictions were integrated with microkinetic modeling to quantify how field-dipole interactions reshape reaction energetics and mechanisms, enabling large increases in predicted catalytic rates and substantial reductions in operating temperature under favorable field conditions. To accelerate discovery of earth-abundant catalysts, the project combined interpretable ML screening (with electronic-structure descriptors identified as key drivers) with a generative inverse-design workflow based on diffusion models and physics constraints. The resulting closed-loop approach, linking simulation, mechanistic modeling, and AI, provides reusable tools and datasets for designing catalysts and operating conditions in field-enhanced catalysis, with broad relevance to electrostatic catalysis, plasma catalysis, electrocatalysis, and other energy-related chemical transformations.

30 DIRECT ENERGY CONVERSION↗
DOE OSTI2023

National Center for Airborne Laser Mapping (NCALM) LiDAR, Imagery, and DEM data from five NGEE Arctic Sites, Seward Peninsula, Alaska, August 2021

From August 8 through August 16 of 2021, airborne remote sensing data was collected by the National Center for Airborne Laser Mapping (NCALM) in collaboration with NGEE Arctic scientists. Data was collected around five NGEE Arctic study sites on the Seward Peninsula of Alaska: Teller mm 27, Teller mm 47, Kougarok mm 64, Kougarok mm 86, and Council mm 71. A Robinson R44 II helicopter with a RIEGL VQ-580 II airborne laser scanner was used to collect the LiDAR point cloud data for each study site. A Phase One iXM-RS100F camera was integrated with the Riegl sensor to collect RGB imagery. This data package contains LiDAR point clouds (.las), RGB imagery (tif), 1 m or 50 cm Digital Elevation Models (.tif) generated from the LiDAR data, and shapefiles of the .las tiling system for each site (.shp). Two supplemental documents are also included in the package: 1) a report describing data collection details, GNSS corrections, and processing steps and 2) a document describing the LiDAR Classification used (.pdf). This survey was conducted towards the end of the summer on the Seward Peninsula, and can be paired with data collected in April of 2022 during the snow-on campaign "National Center for Airborne Laser Mapping (NCALM) LiDAR and DEM data from two NGEE Arctic Sites, Seward Peninsula, Alaska, Winter 2022" (Singhania et.al, 2023) (NGA314). 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 NTRS1975

Seasonal streamflow estimation employing satellite snowcover observations

Low resolution meteorological satellite and high resolution earth resources satellite data have been used to map snow covered area over the upper Indus River and the Wind River Mountains of Wyoming, respectively. For the Indus River early spring snow covered area was extracted and related to April through June stream flow from 1967-1971 using a regression equation. Prediction of the April-June 1972 stream flow from the satellite data was within three percent of the actual total. Composited results from two years of data over seven Wind River Mountain watersheds indicated that LANDSAT-1 snow cover observations, separated on the basis of watershed elevation, could also be related to runoff in significant regression equations.

Rango, A.↗
NASA NTRS1986

A simple tectonic model for crustal accretion in the Slave Province: A 2.7-2.5 Ga granite greenstone terrane

A prograding (direction unspecified) trench-arc system is favored as a simple yet comprehensive model for crustal generation in a 250,000 sq km granite-greenstone terrain. The model accounts for the evolutionary sequence of volcanism, sedimentation, deformation, metamorphism and plutonism, observed througout the Slave province. Both unconformable (trench inner slope) and subconformable (trench outer slope) relations between the volcanics and overlying turbidities; and the existence of relatively minor amounts of pre-greenstone basement (microcontinents) and syn-greenstone plutons (accreted arc roots) are explained. Predictions include: a varaiable gap between greenstone volcanism and trench turbidite sedimentation (accompanied by minor volcanism) and systematic regional variations in age span of volcanism and plutonism. Implications of the model will be illustrated with reference to a 1:1 million scale geological map of the Slave Province (and its bounding 1.0 Ga orogens).

Hoffman, P. F.↗
NASA NTRS1989

Predictions for the total solar eclipse of 1991

A total eclipse of the sun will be widely visible from the Western Hemisphere on July 11, 1991. Detailed predictions for this event are presented which include tables of geographic coordinates for the northern limit, southern limit and center line of the path of totality, local circumstances on the center line and for 95 cities within the partial and total eclipse paths, maps depicting the path of totality, the sky during totality and the lunar limb profile. The author discusses the general characteristics of the eclipse including local circumstances from various points along the central path, the Saros series history and effects caused by the lunar limb profile.

Espenak, Fred↗
NASA NTRS1999

SiC and Si3N4 Recession Due to SiO2 Scale Volatility Under Combustor Conditions

Silicon carbide (SiC) and Si3N4 materials were tested in various turbine engine combustion environments chosen to represent either conventional fuel-lean or fuel-rich mixtures proposed for high-speed aircraft. Representative chemical vapor-deposited (CVD), sintered, and composite materials were evaluated by furnace and high-pressure burner rig exposures. Although protective SiO2 scales formed in all cases, the evidence presented supports a model based on paralinear growth kinetics (i.e., parabolic growth moderated simultaneously by linear volatilization). The volatility rate is dependent on temperature, moisture content, system pressure, and gas velocity. The burner tests were thus used to map SiO2 volatility (and SiC recession) over a range of temperatures, pressures, and velocities. The functional dependency of material recession (volatility) that emerged followed the form A[exp(-Q / RT)](P(sup x)v(sup y). These empirical relations were compared with rates predicted from the thermodynamics of volatile SiO and SiOxHy reaction products and a kinetic model of diffusion through a moving boundary layer. For typical combustion conditions, recession of 0.2 to 2 micrometers/hr is predicted at 1200 to 1400 C, far in excess of acceptable long-term limits.

Smialek, James L.↗
NASA NTRS2000

Sampling Errors of SSM/I and TRMM Rainfall Averages: Comparison with Error Estimates from Surface Data and a Sample Model

Quantitative use of satellite-derived maps of monthly rainfall requires some measure of the accuracy of the satellite estimates. The rainfall estimate for a given map grid box is subject to both remote-sensing error and, in the case of low-orbiting satellites, sampling error due to the limited number of observations of the grid box provided by the satellite. A simple model of rain behavior predicts that Root-mean-square (RMS) random error in grid-box averages should depend in a simple way on the local average rain rate, and the predicted behavior has been seen in simulations using surface rain-gauge and radar data. This relationship was examined using satellite SSM/I data obtained over the western equatorial Pacific during TOGA COARE. RMS error inferred directly from SSM/I rainfall estimates was found to be larger than predicted from surface data, and to depend less on local rain rate than was predicted. Preliminary examination of TRMM microwave estimates shows better agreement with surface data. A simple method of estimating rms error in satellite rainfall estimates is suggested, based on quantities that can be directly computed from the satellite data.

Bell, Thomas L.↗
NASA NTRS2002

Mountain-Top-to-Mountain-Top Optical Link Demonstration

A mountain-top-to-mountain-top optical link was demonstrated between JPL's Table Mountain Facility (TMF), Wrightwood, California, and Strawberry Peak (SP), Lake Arrowhead, California, during the months of June, August, and September of 2000. The bidirectional laser link was nearly horizontal at an altitude of 2 km and spanned a range of 46.8 km. The 780-nm beacon laser transmitted from TMF comprised eight co-propagating mutually incoherent laser beams. The normalized variance or scintillation index (SI) of the individual beacon lasers measured by recording the signal received through 8.50-cm-diameter spotting telescopes on three different nights (June 28-30, 2000) was 1.05 +/- 0.2, 1.76 +/- 0.6, and 0.96 +/- 0.24, respectively. These measurements agreed with values predicted by a heuristic model. The SI of the signal received at SP was found to decrease progressively with an increasing number of beams, and a factor of 3 to 3.5 reduction was achieved for all eight beams. The beam divergence determined by mapping out the point spread function of a few of the individual laser footprints received at SP was 85 to 150 microrad, compared to a design goal of 120 microrad. The 852-nm communications laser beam received at TMF through a 60-cm-diameter telescope on the nights of August 4 and September 14 and 15, 2000, yielded SI values of 0.23 +/- 0.04, 0.32 +/- 0.01, and 0.49 +/- 0.18, respectively, where the reduction was attributed to aperture averaging. The probability distribution functions of the received signal at either end, mitigated by multi-beam averaging in one direction and by aperture averaging in the other direction, displayed lognormal behavior. Consequently, the measured fade statistics showed good agreement with a lognormal model.

Biswas, A.↗
NASA NTRS2021

Southern Bhutan Ecological Forecasting III: Utilizing NASA Earth Observations to Model Land Cover Change and Elephant Wildlife Corridors in Southern Bhutan

Habitat loss of the endangered Asian elephants (Elephas maximus) accompanied by rapid urbanization has contributed to the rising human-elephant conflict (HEC) crisis in southern Bhutan. This poses a serious threat to the survival of Asian elephants, a keystone wildlife species essential for maintaining Bhutan’s forest ecosystems and rich biodiversity. With expanding urban areas, HECs present challenges to conservation efforts in the region. The team partnered with the Bhutan Foundation, the Bhutan Tiger Center, and Bhutan Ecological Society to help mitigate this issue using remote sensing technology and NASA Earth observations. The team refined Land Use and Land Cover (LULC) maps for 2010–2019 generated in previous terms and elephant corridor maps to include information on human settlements using Landsat 5 Thematic Mapper (TM) and Landsat 8 Operational Land Imager (OLI) data. We generated LULC change maps and forecasted the LULC to 2030 using TerrSet Land Change Modeler, providing insights into future elephant habitat suitability in southern Bhutan. The results indicated that built-up areas increased approximately 688.9% from 2010 to 2019 and the forecasted 2030 LULC also predicted an increase in built-up areas compared to 2019. Suitable corridors in Gelephu intersect cultivated and built-up areas, indicating close proximity of elephants to humans and a need to research alternative corridor strategies. The end products from this project will aid partner organizations in decision-making processes in urban planning and future conservation strategies that include the refined placement of biological corridors to aid elephant movement and reduce the risk of HECs.

Thinley Yidzin Wangden↗
NASA NTRS2023

Sidelobe Modeling and Mitigation for A Three Mirror Anastigmat Cosmic Microwave Background Telescope

Telescopes measuring cosmic microwave background (CMB) polarization on large angular scales require exquisite control of systematic errors to ensure the fidelity of the cosmological results. In particular, far-sidelobe contamination from wide angle scattering is a potentially prominent source of systematic error for large aperture microwave telescopes. Here we describe and demonstrate a ray-tracing-based modeling technique to predict far sidelobes for a three mirror anastigmat telescope designed to observe the CMB from the South Pole. Those sidelobes are produced by light scattered in the receiver optics subsequently interacting with the walls of the surrounding telescope enclosure. After comparing simulated sidelobe maps and angular power spectra for different enclosure wall treatments, we propose a highly scattering surface that would provide more than an order of magnitude reduction in the degree-scale far-sidelobe contrast compared to a typical reflective surface. We conclude by discussing the fabrication of a prototype scattering wall panel and presenting measurements of its angular scattering profile.

Ian Gullett↗
NASA NTRS1991

InSb linear multiplexed FPAs for the CRAF/Cassini visible and infrared mapping spectrometer

This paper provides a review of a custom multiplexer circuit designed for use with a 256 element InSb linear array in the CRAF/Cassini VIMS instruments. The requirements, operation noise model and test results from a prototype 1 x 64 array are discussed. The infrared focal plane array (FPA) preliminary design and the impact of the new multiplexer on the instruments' predicted performance will be discussed. Emphasis will be placed on the multiplexer that was designed for the CRAF/Cassini missions. The FPA assembly combines electronic and optical components into a single hermetically sealed hybrid package. The detector configuration is that of a linear dual-multiplexed indium antimonide array with 256 elements, each 103 x 200 on 123-micron centers.

Niblack, Curtiss↗
NASA NTRS2005

Mapping Galactic 60Fe Synthesis in Cen CIR Region

This included a 1 year no cost time extension. The grant was for research into the origin of radioactive 60Fe, whose detection was a mission goal for INTEGRAL and RHESSI. During the grant period, both missions ultimately discovered gamma-line emission from this long lived radioactivity at precisely the value that had been predicted years before by Timmes and Woosley (ApJ, 449,204 (1995)). Unfortunately, using "revised" stellar models and cross sections Rauscher et a1 (ApJ, 576, 323 (2002)), had meanwhile predicted a much larger value. During the grant period, Dieter Hartmann (PI on the complementary grant at Clemson) and Woosley corresponded on this discrepancy and Hartmann visited Santa Cruz (November 20 - 28,2004). All of the grant funds in NAG513659 paid for the expenses of that visit. Subsequently, partly motivated by conversations with Hartmann and Diehl, Woosley re-investigated the production of 60Fe and 26A1 in massive stars from 12 - 120 solar masses, with an eye towards determining the relevant, uncertain physics. The chief changes in Rauscher et a1 were "new" Hauser Feshbach cross sections for 59,60Fe(ng) and 26Al(np)26Mg. The latter has an experimental evaluation which was actually better represented in the study of Timmes and Woosley. The iron (ng) cross sections are from theory and the Timmes and Woosley values were just as reliable as those from Rauscher. Experiments need to be done to resolve who is right. In addition uncertainties in stellar winds, opacities and the IMF were explored. The bottom line is that the value predicted by Timmes and Woosley could well be the correct one, but the experimental error bar is larger than was realized. At least half of the uncertainty is nuclear cross sections that can, and should be measured in the laboratory.

Woosley, Stanford↗
DOE OSTI2021

Laboratory earthquake forecasting: A machine learning competition

Earthquake prediction, the long-sought holy grail of earthquake science, continues to confound Earth scientists. Could we make advances by crowdsourcing, drawing from the vast knowledge and creativity of the machine learning (ML) community? We used Google’s ML competition platform, Kaggle, to engage the worldwide ML community with a competition to develop and improve data analysis approaches on a forecasting problem that uses laboratory earthquake data. The competitors were tasked with predicting the time remaining before the next earthquake of successive laboratory quake events, based on only a small portion of the laboratory seismic data. The more than 4,500 participating teams created and shared more than 400 computer programs in openly accessible notebooks. Complementing the now well-known features of seismic data that map to fault criticality in the laboratory, the winning teams employed unexpected strategies based on rescaling failure times as a fraction of the seismic cycle and comparing input distribution of training and testing data. In addition to yielding scientific insights into fault processes in the laboratory and their relation with the evolution of the statistical properties of the associated seismic data, the competition serves as a pedagogical tool for teaching ML in geophysics. The approach may provide a model for other competitions in geosciences or other domains of study to help engage the ML community on problems of significance.

58 GEOSCIENCES↗
NASA NTRSDate not supplied

Influence of Thermophysical Property Variability on Thermal Predictions of Ti-6Al-4V

The additive manufacturing (AM) industry has experienced rapid growth in recent decades as industrial interest in the process has grown. Because of this, there are many groups interested in simulations of the AM process. However, the influence of thermophysical property variability on the melt pool geometry during processing of various AM alloys is unclear. The goal of my work at NASA Langley Research Center (LaRC) was to characterize this influence on Ti-6Al-4V during AM processing alongside developing a tool to enable equivalent studies on other AM materials. To facilitate this process, a database tool was developed to contain and organize thermophysical data previously reported by primary sources. The specific thermophysical properties of interest for this study were density, specific heat capacity, and conductivity. Thermal diffusivity was calculated using the other three properties. This data was then fit with a Gaussian distribution and then randomly sampled from using Monte Carlo random value sampling. Using the Rosenthal equation, this sample data was used to simulate the temperature field during additive manufacturing and extract the melt pool geometry. Specifically, the melt pool’s length, width, and depth. This process was repeated an arbitrary number of times, with the default being 1000. Once this information was obtained, histograms were made showing the distributions of the sizes of the melt pool’s length, width, and depth. Representative statistical metrics of the distributions were calculated (mean, standard deviation, and coefficient of variance). This work found that at the simulated processing values, the melt pool’s width and depth had a 5.7% variation while the length had a 3.2% variation. Additionally, a tool was constructed to graph a thermal color map representation of the melt pool for specific, arbitrary values of density, specific heat, and conductivity. This tool allowed for more efficient plotting of individual queries of the thermophysical properties. The results that were observed in the research were that values reported in literature vary and this variance can have a significant impact on the simulation. Predictions of the melt pool’s dimensions show that length has a standard deviation of approximately 6 μm, width has a standard deviation of approximately 5 μm, and depth can vary by approximately 3 μm. Considering the mean sizes of length, width, and depth are 185 μm, 88 μm, and 44 μm respectively, such a deviation is significant. This shows that depth, for example, could be more than 10% larger or smaller than expected. This demonstrates that variability in the reported thermophysical properties are not negligible and should be expected to have an influence on the results of the laser powder bed fusion additive manufacturing process. When simulating this process in the future, measures should be taken to account for this discrepancy and the uncertainty involved

Justin Martin↗
NASA NTRS1994

Thermal and albedo mapping of the polar regions of Mars using Viking thermal mapper observations: 2. South polar region

We present the first maps of the apparent thermal inertia and albedo of the south polar region of Mars. The observations used to create these maps were acquired by the infrared thermal mapper (IRTM) instruments on the two Viking Orbiters over a 30-day period in 1977 during the Martian late southern summer season. The maps cover the region from 60 deg S to the south pole at a spatial resolution of 1 deg of latitude, thus completing the initial thermal mapping of the entire planet. The analysis and interpretation of these maps is aided by the results of a one-dimensional radiative convective model, which is used to calculate diurnal variations in surface and atmospheric temperatures, and brightness temperatures at the top of the atmosphere for a range of assumptions concerning dust optical properties and dust optical depths. The maps show that apparent thermal inertias of bare ground regions decrease systematically from 60 deg S to the south pole. In unfrosted regions close to the south pole, apparent thermal inertias are among the lowest observed anywhere on the planet. On the south residual cap, apparent thermal inertias are very high due to the presence of CO2 frost. In most other regions of Mars, best fit apparent albedos based on thermal emission measurements are generally in good agreement with actual surface albedos based on broadband solar reflectance measurements. The one-dimensional atmospheric model calculations also predict anomalously cold brightness temperatures close to the pole during late summer, and after considering a number of alternatives, it is concluded that the net surface cooling due to atmospheric dust is the best explanation for this phenomenon. The region of lowest apparent thermal inertia close to the pole, which includes the south polar layered deposits, is interpreted to be mantled by a continuous layer of aeolian material that must be at least a few millimeters thick. The low thermal inertias mapped in the south polar region imply an absence of surface water ice deposits, which is consistent with Viking Mars atmospheric water detector (MAWD) measurements which show low atmospheric water vapor abundances throughout the summer season.

Paige, David A.↗
DOE OSTI2025

In situ Detection of Plasma Induced Surface Interaction based on Deep Learning based Visual Diagnostics (Technical Report)

It is characteristic for many plasma devices to undergo plasma-material interaction leading to surface erosion. These processes, often not easily detectable, lead to changes in device performance and lifespan. State-of-the-art lifetime tests and wear experiments require over 1000s hours. A self-consistent model for accurately predicting the erosion's effects is not available. In situ detection of these processes is not a trivial task since the surface variations at the early stages have a micron scale. Such limitations not only restrict testing and prediction capabilities but also slow the development of new thrusters and limit mission duration. To address these challenges, an in-situ diagnostic for real-time erosion assessment has been developed, aiming to expedite lifetime testing and broaden experimental campaigns. Several works were dedicated to real-time and in situ monitoring of material erosion during plasma exposure using laser holography, microscopy, and with telemicroscopes. However, the applicability of these approaches is limited due to complexity, cost and less flexibility as they often require placing diagnostic equipment inside the vacuum chamber. In collaboration with Princeton Collaborative Research Facility (PCRF), Princeton Plasma Physics Laboratory (PPPL), a new diagnostic approach is developed, where geometry modifications to the ceramic channel walls were introduced that would result in accelerated channel erosion. We employed Long-distance microscope (LDM) imagery, combined with Deep-Learning based Shape from focus or depth from focus (DFF or SFF) approach, that provides an accessible and cost-effective solution. LDM employs focus variation techniques to continuously capture multiple images of the target object at distinct focal planes. DFF, an optical focus variation method, generates a 3D topographical surface depth map from a sequence of variably focused images. Combined with the developed diagnostic, this approach offers a controllable means to study erosion under accelerated conditions. In this work, we develop Neural Network-based DFF algorithm applicable for LDM data to quantitatively evaluate plasma induced surface modification from LDM data. Next, we develop Deep Learning-based super-resolution depth map image reconstruction technique to increase the resolution of depth maps obtained from DFF algorithm to improve the accuracy of erosion measurements. Thirdly, we develop several image processing techniques to remove noise and improve the quality of depth map image. Here we report the results of initial tests for this approach. An experimental setup designed and built in PPPL was employed that consists of a 3-cm gridded ion source that produces a neutralized argon beam with energies up to 600 eV. A hexagonal boron nitride (h-BN) ceramic target, designed based on computational predictions, was used. Tests were conducted to reconstruct the complex geometry of the target under the lighting conditions of the operated ion source.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗