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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 433 records · Page 24
All sourcesNASA NTRSDOE OSTI
DOE OSTI2024

X-ray scattering based scanning tomography for imaging and structural characterization of cellulose in plants

X-ray and neutron scattering have long been used for structural characterization of cellulose in plants. Due to averaging over the illuminated sample volume, these measurements traditionally overlooked the compositional and morphological heterogeneity within the sample. Here, a scanning tomographic imaging method is described, using contrast derived from the X-ray scattering intensity, for virtually sectioning the sample to reveal its internal structure at a resolution of a few micrometres. This method provides a means for retrieving the local scattering signal that corresponds to any voxel within the virtual section, enabling characterization of the local structure using traditional data-analysis methods. This is accomplished through tomographic reconstruction of the spatial distribution of a handful of mathematical components identified by non-negative matrix factorization from the large dataset of X-ray scattering intensity. Joint analysis of multiple datasets, to find similarity between voxels by clustering of the decomposed data, could help elucidate systematic differences between samples, such as those expected from genetic modifications, chemical treatments or fungal decay. The spatial distribution of the microfibril angle can also be analyzed, based on the tomographically reconstructed scattering intensity as a function of the azimuthal angle.

36 MATERIALS SCIENCE↗
DOE OSTI2024

Theoretical Studies in Hadronic Physics and Fundamental Symmetries

The nucleons (protons and neutrons) are at the center of every atom, the fundamental building blocks of matter in our Universe. Their structure and properties have been actively studied at DOE’s Thomas Jefferson Lab as well as the future US electron-ion collider at Brookhaven National Lab, and are believed to be described by a mathematical theory known as quantum chromodynamics (QCD). In this project, the PI and collaborators invented a theoretical approach called “Generalized parton distributions through Universal Moment Parametrization” (GUMP) to construct the 3D structure of the nucleon from experimental data on Deeply virtual compton scattering and Deep-Exclusive meson production, and semi-inclusive jet or meson productions. The PI and collaborators have also explored the full power of a theory called the large- momentum effective theory (LaMET) to calculate the 3D structure of the nucleon from the first principles known as lattice QCD. In particular, the work paved the way for unprecedented precision calculations which are coming in next decade.

3D Structure↗
NASA NTRS1973

The application of laser Doppler velocimetry to trailing vortex definition and alleviation

A laser Doppler velocimeter whose focal volume can be rapidly traversed through a flowfield has been used to overcome the problem introduced by excursions of the central vortex filament within a wind tunnel test section. The basic concepts of operation of the instrument are reviewed and data are presented which accurately define the trailing vortex from a square-tipped rectangular wing. Measured axial and tangential velocity distributions are given, both with and without a vortex dissipator panel installed at the wing tip. From the experimental data, circulation and vorticity distributions are obtained and the effect of turbulence injection into the vortex structure is discussed.

Orloff, K. L.↗
NASA NTRS1976

Software techniques for a distributed real-time processing system

The paper describes software techniques developed for the Unified Data System (UDS), a distributed processor network for control and data handling onboard a planetary spacecraft. These techniques include a structured language for specifying the programs contained in each module, and a small executive program in each module which performs scheduling and implements the module task.

Lesh, F.↗
NASA NTRS1980

Galilean satellite eclipse studies. II - Jovian stratospheric and tropospheric aerosol content

Aerosol profiles of the Jovian stratosphere and troposphere are presented using the Galilean satellite eclipse technique. The aerosol content is tenuous and varies with altitude, increasing rapidly with downward passage through the tropopause. The data indicate the presence of some aerosols of undetermined structure above the tropopause. An extended haze distribution is proposed, but the possibility that the stratospheric aerosol resides in a thin layer is not excluded.

Smith, D. W.↗
NASA NTRS1996

The Three-Dimensional Spatial Structure of Cirrus Clouds Determined from Lidar Satellite Observations

Simultaneous imagery from the University of Wisconsin Volume Imaging Lidar (VIL) and meteorological satellites were used to quantify the spatial structure of cirrus clouds with 60 m resolution. This data was used to determine the spatial distributions of cloud base altitude, cloud top altitude, and mid-cloud altitude. Two dimensional auto-correlation functions describing the mean shape of cirrus clouds were computed. Because cirrus clouds seldom have distinct edges, these correlation functions are derived as a function of a threshold value which defines the cloud edge.

Eloranta, E. W.↗
NASA NTRS2002

Detection by Transit Photometry

A periodic sequence of planetary transits provides a valid detection of an orbiting planet and provides the relative size of the planet and its orbital period. Ancillary measurements of the stellar spectrum and the variations of the star's radial velocity or position combined with stellar models allow the absolute size of the planet and its mass to be obtained. The results of this approach have already shown that the planet orbiting HD209458 has only 70% of the mass of Jupiter, but is nearly 50% larger in radius. Based on models of planetary structure, these results imply that the planet must have spent most of its lifetime so close to the star that it has not been able to cool and contract as have the giant planets in our Solar System. Thus its density is much less than Jupiter and Saturn and is actually less than that of water; i.e., about 0.4 gr/cu cm. If more sensitive measurements of the light curve of stars with closely orbiting planets can be made that provide the varying amplitude of the light reflected by the planet at various phases in its orbit, then characteristics of the planetary atmosphere can be obtained. Potentially, these data can identify major molecular species present in the atmosphere and tell us if clouds are present and yield the phase function of the aerosols. Although such detail cannot be obtained for Earth-size planets because their signal amplitudes are too small, it is possible to get data critical to the determination of the structure of extrasolar planetary systems. In particular, the size distributions and their orbital distributions can be measured by the transit photometry missions now in development. The COROT mission should be able to find large terrestrial planets in short-period orbits while the more ambitious Kepler and Eddington missions should be able to detect planets even smaller than the Earth and at orbital distances that place them in the habitable zone of their stars.

Borucki, William J.↗
DOE OSTI2026

Poisson Log-Normal Process for Count Data Prediction

Modeling count data is important in physics and other scientific disciplines, where measurements often involve discrete, non-negative quantities such as photon or neutrino detection events. Traditional parametric approaches can be trained to generate integer-count predictions but may struggle with capturing complex, non-linear dependencies often observed in the data. Gaussian process (GP) regression provides a robust non-parametric alternative to modeling continuous data; however, it cannot generate integer outputs. We propose the Poisson Log-Normal (PoLoN) process, a framework that employs GP to model Poisson log-rates. As in GP regression, our approach relies on the correlations between data points captured via GP kernel structure rather than explicit functional parameterizations. We demonstrate that the PoLoN predictive distribution is Poisson-LogNormal and provide an algorithm for optimizing kernel hyperparameters. Furthermore, we adapt the PoLoN approach to the problem of detecting weak localized signals superimposed on a smoothly varying background - a task of considerable interest in many areas of science and engineering. Our framework allows us to predict the strength, location and width of the detected signals. We evaluate PoLoN's performance using both synthetic and real-world datasets, including the open dataset from CERN which was used to detect the Higgs boson at the Large Hadron Collider. Our results indicate that the PoLoN process can be used as a non-parametric alternative for analyzing, predicting, and extracting signals from integer-valued data.

Saha, Anushka [Rutgers U., Piscataway]↗
DOE OSTI2025

Modeling the Behavior of Complex Aqueous Electrolytes Using Machine Learning Interatomic Potentials: The Case of Sodium Sulfate

Understanding the structure and thermodynamics of solvated ions is essential for advancing applications in electrochemistry, water treatment, and energy storage. While ab initio molecular dynamics methods are highly accurate, they are limited by short accessible time and length scales whereas classical force fields struggle with accuracy. Herein, we explore the structure and thermodynamics of complex monovalent-divalent ion pairs using Na 2 SO 4 (aq) as a case study by applying a machine learning interatomic potential (MLIP) trained on density functional theory (DFT) data. Our MLIP-based approach reproduces key bulk properties such as density and radial distribution functions of water. We provide the hydration structure of the sodium and sulfate ions in the 0.1–2 M concentration range and the one-dimensional and two-dimensional potentials of mean force for the sodium–sulfate ion pairing at the low concentration limit (0.1 M), which are inaccessible to DFT. At low concentrations, the sulfate ion is strongly solvated, leading to the stabilization of solvent-separated ion pairs over contact ion pairs. Minimum energy pathway analysis revealed that coordinating two sodium ions with a sulfate ion is a multistep process whereby the sodium ions coordinate to the sulfate ion sequentially. Finally, we demonstrate that MLIPs allow the study of solvated ions beyond simple monovalent pairs with DFT-level accuracy in their low concentration limit (0.1 M) via statistically converged properties from ns-long simulations.

anions↗
NASA NTRS2001

Tropical Ocean Evaporation/SST Sensitivity and It's Link to Water and Energy Budget Variations During ENSO

The continuing debate over feedback mechanisms governing tropical sea surface temperatures (SSTs) and tropical climate in general has highlighted the diversity of potential checks and balances within the climate system. Competing feedbacks due to changes in surface evaporation, water vapor, and cloud long- and shortwave radiative properties each may serve critical roles in stabilizing or destabilizing the climate system. It is also intriguing that even those climate variations having origins internal to the climate system - changes in ocean heat transport for example, apparently require complementary equilibrating effects by changes in atmospheric energy fluxes. Perhaps the best observational evidence of this is the relatively invariant nature of tropically averaged net radiation exiting the top-of-atmosphere (TOA) as measured by broadband satellite sensors over the past two decades. Thus, analyzing how these feedback mechanisms are operating within the context of current interannual variability may offer considerable insight for anticipating future climate change. In this paper we focus primarily on interannual variations of ocean evaporative fluxes and their significance for coupled water and energy cycles within the tropical climate system. In particular, we use both the da Silva estimates of surface fluxes (based on the Comprehensive Ocean Atmosphere Data Set, COADS) and numerical simulations from several global climate models to examine evaporation sensitivity to perturbations in SST associated with warm and cold ENSO events. The specific questions we address are as follows: (1) What recurring patterns of surface wind and humidity anomalies are present during ENSO and how do they combine to yield systematic evaporation anomalies?, (2) What is the resulting tropical ocean mean evaporation-SST sensitivity associated with this climate perturbation?, and (3) What role does this evaporation play in tropical heat and water balance over tropical oceanic regions? We use the da Silva ocean flux data to identify composite structure of departures of latent heat flux from climatology. We also show how these patterns arise out of associated wind and humidity anomaly distributions. Our preliminary work shows that evaporation sensitivity estimates from the da Silva / COADS data, computed for the tropical oceans (30 degrees N/S) are in the neighborhood of 5 to 6 W/square m K. Model estimates are also quite close to this figure. This rate is only slightly less than a rate corresponding to constant relative humidity; however, substantial regional departures from constant relative humidity are present. These patterns are robust and we relate the associated wind and humidity fluctuations noted in previous investigations to the derived evaporation anomalies. Finally, these results are interpreted with other data from the Earth radiation Budget Experiment (ERBE), Global Precipitation Climatology Project (GPCP) and NASA's Surface Radiation Budget (SRB) data set to characterize the tropical energetics of ENSO-related climate variability.

Robertson, Franklin R.↗
DOE OSTI2020

Distribution Development for the RDX Regional Model at Los Alamos National Laboratory - 20385

Representing uncertainty in model inputs often means finding a balance between uncertainty and physical reality. Developing wide distributions may seem conservative in principle, but this approach may lead to unrealistic model results. Characterizing the current state of knowledge of stochastic inputs presents many challenges, especially if the data available are limited or have limited relevance to the site. Relationships among these inputs may also be important to represent but are typically complex or difficult to define. Often special adjustments must be made to account for reduced credibility in particular data. If parameters are strongly related to one another, a correlation structure may be developed for input to the model. Other techniques such as regression models may be used to incorporate relationships between the information available and the desired parameters. The process of developing distributions must consider details of the model in terms of what the distribution is meant to represent. This paper uses the example of a probabilistic fate and transport model for hexahydro-1,3,5-trinitro-1,3,5-triazine (RDX) in the regional aquifer at Los Alamos National Laboratory (LANL). For many parameters, a single draw is applied to all space and time over which the model is run, for a single iteration. This simplification is often made for many reasons, and can often be beneficial, but also adds additional complexity in the distribution development process. Defining the distributional goals as they relate to the modeling process is an important step, which should take place prior to evaluation of the data. Usually, the distributions developed are meant to characterize the average value of the parameter over the spatial and temporal domain of the model. Distribution development requires consideration of many sources of information on the parameter where available, ideally from multiple references. Examples of different sources include data from different references but also from different conditions, measurement methods, or experimental types. Depending on these conditions and the reliability or relevance of particular references, different sources of data may each contribute valuable information but have varying relevance to the site. In these cases, weighting data unequally is a useful way to incorporate this information. As an example, aqueous dispersivity data are available for a variety of rock types. Only a few values are available for the desired rock type, and this is not enough to develop a distribution. Therefore, dispersivity values from other rock types are included in distribution development but are down-weighted such that the best data have the most influence on the distribution developed. In another case, K{sub d} distributions in the model are meant to represent a known composition of multiple soil types. Data from these materials are weighted accordingly to develop a distribution for the weighted average K{sub d} across soil types. Other cases include varying reliability of different sources, and weighting data according to the confidence in these sources. In some cases, input parameters are correlated with one another. An example is advective porosity, which is positively correlated with total porosity and must be less than total porosity. Paired data with both parameters must exist to discern the relationship between the two parameters and if it is necessary to build a correlation structure into the model. In general, correlated parameters may be represented in the model by a multivariate distribution, or perhaps more desirably, capturing the correlation within the developed distributions which may be treated as independent from one another. In the example of porosity, this can be done by transforming advective porosity into a proportion of total porosity which may be drawn independently from the distribution of total porosity. This paper explores how complex data and correlations can be incorporated to meet the distributional goals of the model, using the RDX regional model as a detailed example. (authors)

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗
DOE OSTI2022

The Latent Dirichlet Allocation model applied to airborne LiDAR data: A case study on mapping forest degradation associated with fragmentation and fire in the Amazon region

1. LiDAR data are being increasingly used to provide a detailed characterization of the vertical profile of forests. This characterization enables the generation of new insights on the influence of environmental drivers and anthropogenic disturbances on forest structure as well as on how forest structure influences important ecosystem functions and services. Unfortunately, extracting information from LiDAR data in a way that enables the spatial visualization of forest structure, as well as its temporal changes, is challenging due to the high dimensionality of these data. 2. In this study, we show how the Latent Dirichlet Allocation model applied to LiDAR data (LidarLDA) can be used to identify forest structural types and how the relative abundance of these forest types changes throughout the landscape. The code to fit this model is made available through the open-source r package LidarLDA in github. We illustrate the use of LidarLDA both with simulated data and data from a large-scale fire experiment in the Brazilian Amazon region. 3. Using simulated data, we demonstrate that LidarLDA accurately identifies the number of forest types as well as their spatial distribution and absorptance probabilities. For the empirical data, we found that LidarLDA detects both landscape-level patterns in forest structure as well as the strong interacting effect of fire and forest fragmentation on forest structure based on the experimental fire plots. More specifically, LidarLDA reveals that proximity to forest edge exacerbates the impact of fires, and that burned forests remain structurally different from unburned areas for at least 7 years, even when burned only once. Importantly, LidarLDA generates insights on the 3D structure of forest that cannot be obtained using more standard approaches that just focus on top-of-the-canopy information (e.g. canopy height models based on LiDAR data). 4. By enabling the mapping of forest structure and its temporal changes, we believe that LidarLDA will be of broad utility to the ecological research community.

54 ENVIRONMENTAL SCIENCES↗
NASA NTRS1989

Gravity wave structure between 60 and 90 km inferred from Space Shuttle reentry data

Density fluctuations obtained along seven Space Shuttle reentry tracks are used to examine the horizontal structure and the vertical distribution of density variance in the mesosphere and lower thermosphere. The tracks lie primarily over open ocean at middle and low latitudes and represent the only measurements of horizontal atmospheric structure at these heights available to date. The density fluctuations are interpreted in terms of gravity-wave motions and reveal significant density (and velocity) variance at horizontal scales ranging from about 10 to 1000 km. Fluctuation amplitudes are used to infer corresponding velocity perturbations and characteristic vertical scales and frequencies of the wave spectrum. Results suggest that the mean velocity variance is smaller over the Pacific ocean than over major land masses, and that the variance increases with height in a manner consistent with that expected in the present of wave saturation processes.

Fritts, David C.↗
NASA NTRS1984

Suprathermal ions upstream from interplanetary shocks

Low energy (10 eV-30 keV) observations of suprathermal ions ahead of outward propagating interplanetary shock waves (ISQ) are reported. The data were taken with the fast plasma experiment on ISEE 1 and 2 during 17 events. Structure was more evident in the suprathermal ion distribution in the earth bow shock region than in the upstream region. Isotropic distributions were only observed ahead of ISW, although field alignment, kidney-bean distributions, ion shells in velocity space and bunches of gyrating ions were not. The data suggest that the solar wind ions are accelerated to suprathermal energies in the vicinity of the shocks, which feature low and subcritical Mach numbers at 1 AU.

Gosling, J. T.↗
NASA NTRS1990

A redshift survey toward a proposed void of galaxies suggested by the distribution of Abell clusters

A program of redshift measurements was carried out in a region of the sky in which a relative under-density of Abell clusters had been used to infer the presence of a large (diameter about 40/h Mpc) void in the general galaxy distribution. The purpose of this study was to investigate whether the large-scale distribution of galaxies is traced by the distribution of rich clusters. Redshifts are presented for 308 galaxies in the Zwicky Catalog in a 234 square degree region centered on R.A. about 2h, Decl. about 12 deg of which 229 have been newly measured. These data reveal a pattern of filamentary structure alternating with voids of characteristic diameter about 25-30/h Mpc, throughout the volume sampled. While the redshift data reveal an underdensity in the distribution of galaxies in the general region suggested by the Abell cluster distribution, they do not support the existence there of a 40/h Mpc diameter void.

Willick, Jeffrey A.↗
NASA NTRS2011

Maturation of Structural Health Management Systems for Solid Rocket Motors

Concepts of an autonomous and automated space-compliant diagnostic system were developed for conditioned-based maintenance (CBM) of rocket motors for space exploration vehicles. The diagnostic system will provide real-time information on the integrity of critical structures on launch vehicles, improve their performance, and greatly increase crew safety while decreasing inspection costs. Using the SMART Layer technology as a basis, detailed procedures and calibration techniques for implementation of the diagnostic system were developed. The diagnostic system is a distributed system, which consists of a sensor network, local data loggers, and a host central processor. The system detects external impact to the structure. The major functions of the system include an estimate of impact location, estimate of impact force at impacted location, and estimate of the structure damage at impacted location. This system consists of a large-area sensor network, dedicated multiple local data loggers with signal processing and data analysis software to allow for real-time, in situ monitoring, and longterm tracking of structural integrity of solid rocket motors. Specifically, the system could provide easy installation of large sensor networks, onboard operation under harsh environments and loading, inspection of inaccessible areas without disassembly, detection of impact events and impact damage in real-time, and monitoring of a large area with local data processing to reduce wiring.

Quing, Xinlin↗
DOE OSTI2022

Study of the deformed halo nucleus 31 Ne with Glauber model based on microscopic self-consistent structures

In this work, the exotic deformed nucleus 31 Ne is studied with an approach that combines self-consistent structure and reaction theories. The deformed relativistic Hartree-Bogoliubov theory in continuum (DRHBc) is utilized to demonstrate that deformation and pairing correlations give rise to a halo structure with a large-amplitude p-wave configuration in 31 Ne. Then the valence nucleon wave functions and angle-averaged density distributions of 30 Ne from this theory are used as input for the Glauber reaction model to study the observables of neutron-rich neon isotopes to search halo signatures. With NL1 effective interaction, our predictions of the reaction cross sections for these exotic neon isotopes on a carbon target can better reproduce the experimental data than those from the relativistic mean field model for a spherical shape with resonances and pairing correlation contributions, and are roughly 3.3% (~ 50 mb) larger than those with Gaussian function-fitted densities of the core nuclei. The calculated one-neutron removal cross section at 240 MeV/nucleon, and the inclusive longitudinal momentum distribution of the 30 Ne residues from the 31Ne breakup reaction are largely improved over previous theoretical predictions and agree well with data. These reaction evaluations indicate a dilute density distribution in coordinate space and are a canonical signature of a halo structure. Moreover, our predictions with the NL3 and PK1 effective interactions give slightly better descriptions of reaction observables for exotic neon isotopes.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗