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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 307 records · Page 17
All sourcesNASA NTRSDOE OSTI
DOE OSTI2023

Magnetic Misalignment of Interstellar Dust Filaments

We present evidence for scale-independent misalignment of interstellar dust filaments and magnetic fields. We estimate the misalignment by comparing millimeter-wave dust-polarization measurements from Planck with filamentary structures identified in neutral-hydrogen (H I ) measurements from H I 4PI. We find that the misalignment angle displays a scale independence (harmonic coherence) for features larger than the H I 4PI beamwidth (16$\acute{.}$2). We additionally find a spatial coherence on angular scales of ${ \mathcal O }(1^\circ )$. We present several misalignment estimators formed from the auto- and cross-spectra of dust-polarization and H I -based maps, and we also introduce a map-space estimator. Applied to large regions of the high-Galactic-latitude sky, we find a global misalignment angle of ~2°, which is robust to a variety of masking choices. By dividing the sky into small regions, we show that the misalignment angle correlates with the parity-violating TB cross-spectrum measured in the Planck dust maps. The misalignment paradigm also predicts a dust EB signal, which is of relevance in the search for cosmic birefringence but as yet undetected; the measurements of EB are noisier than those of TB, and our correlations of EB with misalignment angle are found to be weaker and less robust to masking choices. We also introduce an H I -based dust-polarization template constructed from the Hessian matrix of the H I intensity, which is found to correlate more strongly than previous templates with Planck dust B modes.

79 ASTRONOMY AND ASTROPHYSICS↗
NASA NTRS1973

An analytical analysis of the dispersion predictions for effluents from the Saturn 5 and Scout-Algol 3 rocket exhausts

Predictions of the spatial concentration mapping of the potentially toxic constituents of the exhaust effluents from a launch of a Saturn 5 and of a Scout-Algol 3 vehicle utilizing the NASA/MSFC Multilayer Diffusion Program are provided. In the case of the Saturn 5, special attention was given to the concentration fields of carbon monoxide with a correlation of carbon dioxide concentrations. The Scout-Algol 3 provided an example of the centerline concentrations of hydrogen chloride, carbon monoxide, and alumina under typical meteorological conditions. While these results define the specific environmental impact of these two launches under the meteorological conditions existing during launches, they also provide a basis for the empirical monitoring of the constituents of the exhaust effluents of these vehicles.

Stephens, J. B.↗
NASA NTRS1978

An initial state perturbation experiment with the GISS model

Monthly mean global forecasts for January 1975 have been computed with the Goddard Institute for Space Studies model from four slightly different sets of initial conditions - a 'control' state and three random perturbations thereof - to simulate the effects of initial state uncertainty on forecast quality. Differences among the forecasts are examined in terms of energetics, synoptic patterns and forecast statistics. The 'noise level' of the model predictions is depicted on global maps of standard deviations of sea level pressures, 500 mb heights and 850 mb temperatures for the set of four forecasts. Initial small-scale random errors do not appear to result in any major degradation of the large-scale monthly mean forecast beyond that generated by the model itself, nor do they appear to represent the major source of large-scale forecast error.

Spar, J.↗
NASA NTRS1980

The contribution of space observations to water resources management; Proceedings of the Symposium, Bangalore, India, May 29-June 9, 1979

The symposium focused on hydrology, soil moisture estimation and ground water exploration, wetlands monitoring and water quality estimation, hydrometeorology, snow and ice monitoring, and evapotranspiration estimation. Other problems discussed include surface water and flood mapping, watershed runoff estimation and prediction, and new space systems contributing to water resources management.

Salomonson, V. V.↗
NASA NTRS1985

A comparison of observed and forecast energetics over North America

The observed kinetic energy balance is calculated over North America and compared with that computed from forecast fields for the 13-15 January 1979 cyclone. The FGGE upper-air rawinsonde network serves as the observational database while the forecast energetics are derived from a numerical integration with the GLAS fourth-order general circulation model initialized at 00 GMT 13 January. Maps of the observed and predicted kinetic energy and eddy conversion are in good qualitative agreement, although the model eddy conversion tends to be 2 to 3 times stronger than the observed values. Both the forecast and observations exhibit the lower and upper tropospheric maxima in vertical profiles of kinetic energy generation and dissipation typically found in cyclonic disturbances. An interesting time lag is noted in the observational analysis with the maximum observed kinetic energy occurring 12 h later than the maximum eddy conversion over the same region.

Baker, W. E.↗
NASA NTRS1987

Stress history of the Tharsis Region, Mars

The Tharsis topographic rise of Mars is roughly 5000 km wide and 10 km high and is believed to have originated more than 3.5 BY ago. Within its boundaries lie the four largest volcanoes on the planet. It is also the locus of a series of fracture traces which extend over approximately a hemisphere. The events leading to the formation of the Tharsis region continue to generate debate. Three geophysical models of the formation of Tharsis are now in general contention and each of these models has been used to predict a characteristic stress-field. These models are: the volcanic construct model, the isostatic compensation model, and the lithospheric uplift model. Each has been used by its proponents to predict some of the features observed in the Tharsis region but none accurately accounts for all of the fracture features observed. This is due, in part, to the use of fractures too young to be directly related to the origin of Tharsis. To constrain the origin of Tharsis, as opposed to its later history, one should look for the oldest fractures related to Tharsis and compare these to the predictions made by the models. Mapping of old terrains in and around the Tharsis rise has revealed 175 hitherto unknown old fracture features.

Francis, Robert A.↗
NASA NTRS1990

A numerical algorithm to propagate navigation error covariance matrices associated with generalized strapdown inertial measurement units

The design and operation of a Strapdown Navigation Analysis Program (SNAP) developed to perform covariance analysis on spacecraft inertial-measurement-unit (IMU) navigation errors are described and demonstrated. Consideration is given to the IMU modeling subroutine (with user-specified sensor characteristics), the data input procedures, state updates and the simulation of instrument failures, the determination of the nominal trajectory, the mapping-matrix and Monte Carlo covariance-matrix propagation methods, and aided-navigation simulation. Numerical results are presented in tables for sample applications involving (1) the Galileo/IUS spacecraft from its deployment from the Space Shuttle to a point 10 to the 8th ft from the center of the earth and (2) the TDRS-C/IUS spacecraft from Space Shuttle liftoff to a point about 2 h before IUS deployment. SNAP is shown to give reliable results for both cases, with good general agreement between the mapping-matrix and Monte Carlo predictions.

Weir, Kent A.↗
NASA NTRS1990

Magellan radar to reveal secrets of enshrouded Venus

Imaging Venus with a synthetic aperture radar (SAR) with 70 percent global coverage at 1-km optical line-pair resolution to provide a detailed global characterization of the volcanic land-forms on Venus by an integration of image data with altimetry is discussed. The Magellan radar system uses navigation predictions to preset the radar data collection parameters. The data are collected in such a way as to preserve the Doppler signature of surface elements and later they are transmitted to the earth for processing into high-resolution radar images. To maintain high accuracy, a complex on-board filter algorithm allows the altitude control logic to respond only to a narrow range of expected photon intensity levels and only to signals that occur within a small predicted interval of time. Each mapping pass images a swath of the planet that varies in width from 20 to 25 km. Since the orbital plane of the spacecraft remains fixed in the inertial space, the slow rotation of Venus continually brings new areas into view of the spacecraft.

Saunders, R. Stephen↗
NASA NTRS2012

Aquarius: The Instrument and Initial Results

Aquarius was launched on June 10, 2011 aboard the Aquarius/SAC-D observatory and the instrument has been operating continuously since the initial turned-on was completed on August 25. The initial observed antenna temperatures were close to predicted and the first salinity map was released in September. In order to map the ocean salinity field, Aquarius includes several special features such as the inclusion of a scatterometer to provide a roughness correction, measurement of the third Stokes parameter to correct for Faraday rotation, and fast sampling to mitigate the effects of RFI. This paper provides an overview of the instrument and an example of initial results. Details are covered in subsequent papers in the session on Aquarius

Ocean salinity↗
NASA NTRS2016

OSIRIS-REx Orbit Determination Covariance Studies at Bennu

The Origins Spectral Interpretation Resource Identification Security Regolith Explorer (OSIRIS-REx) mission is a NASA New Frontiers mission launching in 2016 to rendezvous with the small, Earth-crossing asteroid (101955) Bennu in late 2018, and ultimately return a sample of regolith to Earth. Approximately 3 months before the encounter with Bennu, the asteroid finally becomes detectable in the narrow field PolyCam imager. The spacecraft's rendezvous with Bennu begins with a series of four Asteroid Approach Maneuvers, which slow the spacecraft's speed relative to Bennu beginning two and a half months prior to closest approach, ultimately delivering the spacecraft to a point 18 km from Bennu on Nov 18, 2018. An extensive campaign of proximity operations activities to characterize the properties of Bennu and select a suitable sample site will follow. This paper will discuss the challenges of navigating near a small 500-m diameter asteroid. The navigation at close proximity is dependent on the accurate mathematical model or digital terrain map of the asteroids shape. Predictions of the spacecraft state are very sensitive to spacecraft small forces, solar radiation pressure, and mis-modeling of Bennu's gravity field. Uncertainties in the physical parameters of the central body Bennu create additional challenges. The navigation errors are discussed and their impact on science planning will be presented.

Covariance↗
NASA NTRS2009

The First Prediction of a Rift Valley Fever Outbreak

El Nino/Southern Oscillation (ENSO) related anomalies were analyzed using a combination of satellite measurements of elevated sea surface temperatures, and subsequent elevated rainfall and satellite derived normalized difference vegetation index data. A Rift Valley fever risk mapping model using these climate data predicted areas where outbreaks of Rift Valley fever in humans and animals were expected and occurred in the Horn of Africa from December 2006 to May 2007. The predictions were subsequently confirmed by entomological and epidemiological field investigations of virus activity in the areas identified as at risk. Accurate spatial and temporal predictions of disease activity, as it occurred first in southern Somalia and then through much of Kenya before affecting northern Tanzania, provided a 2 to 6 week period of warning for the Horn of Africa that facilitated disease outbreak response and mitigation activities. This is the first prospective prediction of a Rift Valley fever outbreak.

Anyamba, Assaf↗
DOE OSTI2022

Modeling the distribution of the endangered Jemez Mountains salamander (Plethodon neomexicanus) in relation to geology, topography, and climate

The Jemez Mountains salamander (Plethodon neomexicanus; hereafter JMS) is an endangered salamander restricted to the Jemez Mountains in north-central New Mexico, United States. This strictly terrestrial and lungless species requires moist surface conditions for activities such as mating and foraging. Threats to its current habitat include fire suppression and ensuing severe fires, changes in forest composition, habitat fragmentation, and climate change. Forest composition changes resulting from reduced fire frequency and increased tree density suggest that its current aboveground habitat does not mirror its historically successful habitat regime. However, because of its limited habitat area and underground behavior, we hypothesized that geology and topography might play a significant role in the current distribution of the salamander. We modeled the distribution of the JMS using a machine learning algorithm to assess how geology, topography, and climate variables influence its distribution. The best habitat suitability model indicates that geology type and maximum winter temperature (November to March) were most important in predicting the distribution of the salamander (23.5% and 50.3% permutation importance, respectively). Minimum winter temperature was also an important variable (21.4%), suggesting this also plays a role in salamander habitat. Our habitat suitability map reveals low uncertainty in model predictions, and we found slight discrepancies between the designated critical habitat and the most suitable areas for the JMS. Because geological features are important to its distribution, we recommend that geological and topographical data are considered, both during survey design and in the description of localities of JMS records once detected.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2024

Deep learning models map rapid plant species changes from citizen science and remote sensing data

Anthropogenic habitat destruction and climate change are reshaping the geographic distribution of plants worldwide. However, we are still unable to map species shifts at high spatial, temporal, and taxonomic resolution. Here, we develop a deep learning model trained using remote sensing images from California paired with half a million citizen science observations that can map the distribution of over 2,000 plant species. Our model— Deepbiosphere— not only outperforms many common species distribution modeling approaches (AUC 0.95 vs. 0.88) but can map species at up to a few meters resolution and finely delineate plant communities with high accuracy, including the pristine and clear-cut forests of Redwood National Park. These fine-scale predictions can further be used to map the intensity of habitat fragmentation and sharp ecosystem transitions across human-altered landscapes. In addition, from frequent collections of remote sensing data, Deepbiosphere can detect the rapid effects of severe wildfire on plant community composition across a 2-y time period. These findings demonstrate that integrating public earth observations and citizen science with deep learning can pave the way toward automated systems for monitoring biodiversity change in real-time worldwide.

Gillespie, Lauren E.↗
NASA NTRSDate not supplied

Transonic Limit Cycle Oscillations of the Benchmark Supercritical Wing

This paper considers transonic flutter mechanisms of the Benchmark Supercritical Wing, a model under study in the Aeroelastic Prediction Workshop series. Flutter boundaries are mapped out across an angle of attack sweep at Mach 0.8, utilizing both time-domain and linearized frequency-domain solvers, manual meshes and adapted meshes, and various governing equations. With increased angle of attack, linearized and finite amplitude flutter predictions exhibit differences above 3◦ as the flow begins to separate; the latter predictions are found to be driven by subcritical limit cycle oscillations whose strength increases with angle of attack. Moderate perturbation values provide a stability boundary at 5◦ which matches the experimental data, but it is not clear how the experimental perturbation, from one test condition to the next, can be reasonably characterized.

Bret Stanford↗
DOE OSTI2022

Improved AlphaFold modeling with implicit experimental information

Machine-learning prediction algorithms such as AlphaFold and RoseTTAFold can create remarkably accurate protein models, but these models usually have some regions that are predicted with low confidence or poor accuracy. We hypothesized that by implicitly including new experimental information such as a density map, a greater portion of a model could be predicted accurately, and that this might synergistically improve parts of the model that were not fully addressed by either machine learning or experiment alone. An iterative procedure was developed in which AlphaFold models are automatically rebuilt on the basis of experimental density maps and the rebuilt models are used as templates in new AlphaFold predictions. We show that including experimental information improves prediction beyond the improvement obtained with simple rebuilding guided by the experimental data. This procedure for AlphaFold modeling with density has been incorporated into an automated procedure for interpretation of crystallographic and electron cryo-microscopy maps.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2024

Performance evaluation of the USGS velocity model for the San Francisco Bay Area

In this study, we evaluated the performance of the United States Geological Survey velocity model developed for the San Francisco Bay Area (SFBA), version 21.1. The evaluation was performed through high-resolution three-dimensional physics-based ground motion simulations of seven small-magnitude earthquakes (ranging from magnitude 3.8 to 4.4) that occurred on the eastern side of the San Francisco Bay. The simulations were performed in the frequency range from 0 to 5 Hz with a minimum shear-wave velocity of 250 m/s, which allowed the capture of wave propagation effects of the near-surface soft materials that characterize local basins. Based on the direct comparison of Fourier amplitude spectra between recorded and simulated ground motions for more than 250 stations, we found that the velocity model generally performs well in the frequency range of 0.2–5 Hz. The median value of the Fourier amplitude residuals was found to be near zero for all seven earthquakes. The slight over-prediction of 0.2 log-natural units at frequencies above 3 Hz in our simulations was attributed to the potentially inaccurate representation of the source radiation pattern by a double-couple point source model, and simple representation of shallow small-scale underground structural complexity in the velocity model. Maps of spectral amplitude differences between the simulated and recorded data were used to identify areas responsible for systematic ground motion over-predictions or under-predictions. For example, while some sub-domains over soft sediments show over-prediction patterns, the block east of the Hayward fault is prone to exhibit patterns of under-prediction. These maps can be used to guide future refinements of the SFBA velocity model. Since our simulation methodology allows for the decoupling of the source and wave propagation effects, the ground motion data generated by our simulations can also be used to quantify the epistemic uncertainty due to the velocity model, in empirically based ground motion estimates for the SFBA.

58 GEOSCIENCES↗
DOE OSTI2021

Localized Defect Detection from Spatially Mapped, In-Situ Process Data With Machine Learning

In powder bed fusion additive manufacturing, machines are often equipped with in-situ sensors to monitor the build environment as well as machine actuators and subsystems. The data from these sensors offer rich information about the consistency of the fabrication process within a build and across builds. This information may be used for process monitoring and defect detection; however, little has been done to leverage this data from the machines for more than just coarse-grained process monitoring. In this work we demonstrate how these inherently temporal data may be mapped spatially by leveraging scan path information. We then train a XGBoost machine learning model to predict localized defects—specifically soot–using only the mapped process data of builds from a laser powder bed fusion process as input features. The XGBoost model offers a feature importance metric that will help to elucidate possible relationships between the process data and observed defects. Finally, we analyze the model performance spatially and rationalize areas of greater and lesser performance.

3D printing↗
NASA NTRS1984

Analysis of the quality of image data acquired by the LANDSAT-4 Thematic Mapper and Multispectral Scanners

The geometric quality of TM film and digital products is evaluated by making selective photomeasurements and by measuring the coordinates of known features on both the TM products and map products. These paired observations are related using a standard linear least squares regression approach. Using regression equations and coefficients developed from 225 (TM film product) and 20 (TM digital product) control points, map coordinates of test points are predicted. The residual error vectors and analysis of variance (ANOVA) were performed on the east and north residual using nine image segments (blocks) as treatments. Based on the root mean square error of the 223 (TM film product) and 22 (TM digital product) test points, users of TM data expect the planimetric accuracy of mapped points to be within 91 meters and within 117 meters for the film products, and to be within 12 meters and within 14 meters for the digital products.

Colwell, R. N.↗