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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 397 records · Page 22
All sourcesNASA NTRSDOE OSTI
NASA NTRS1993

An evaluation of three-dimensional sensors for the extravehicular activity helper/retreiver

The Extravehicular Activity Retriever/Helper (EVAHR) is a robotic device currently under development at the NASA Johnson Space Center that is designed to fetch objects or to assist in retrieving an astronaut who may have become inadvertently de-tethered. The EVAHR will be required to exhibit a high degree of intelligent autonomous operation and will base much of its reasoning upon information obtained from one or more three-dimensional sensors that it will carry and control. At the highest level of visual cognition and reasoning, the EVAHR will be required to detect objects, recognize them, and estimate their spatial orientation and location. The recognition phase and estimation of spatial pose will depend on the ability of the vision system to reliably extract geometric features of the objects such as whether the surface topologies observed are planar or curved and the spatial relationships between the component surfaces. In order to achieve these tasks, accurate sensing of the operational environment and objects in the environment will therefore be critical. The qualitative and quantitative results of empirical studies of three sensors that are capable of providing three-dimensional information to the EVAHR, but using completely different hardware approaches are documented. The first of these devices is a phase shift laser with an effective operating range (ambiguity interval) of approximately 15 meters. The second sensor is a laser triangulation system designed to operate at much closer range and to provide higher resolution images. The third sensor is a dual camera stereo imaging system from which range images can also be obtained. The remainder of the report characterizes the strengths and weaknesses of each of these systems relative to quality of data extracted and how different object characteristics affect sensor operation.

Magee, Michael↗
NASA NTRS1994

Object recognition and pose estimation of planar objects from range data

The Extravehicular Activity Helper/Retriever (EVAHR) is a robotic device currently under development at the NASA Johnson Space Center that is designed to fetch objects or to assist in retrieving an astronaut who may have become inadvertently de-tethered. The EVAHR will be required to exhibit a high degree of intelligent autonomous operation and will base much of its reasoning upon information obtained from one or more three-dimensional sensors that it will carry and control. At the highest level of visual cognition and reasoning, the EVAHR will be required to detect objects, recognize them, and estimate their spatial orientation and location. The recognition phase and estimation of spatial pose will depend on the ability of the vision system to reliably extract geometric features of the objects such as whether the surface topologies observed are planar or curved and the spatial relationships between the component surfaces. In order to achieve these tasks, three-dimensional sensing of the operational environment and objects in the environment will therefore be essential. One of the sensors being considered to provide image data for object recognition and pose estimation is a phase-shift laser scanner. The characteristics of the data provided by this scanner have been studied and algorithms have been developed for segmenting range images into planar surfaces, extracting basic features such as surface area, and recognizing the object based on the characteristics of extracted features. Also, an approach has been developed for estimating the spatial orientation and location of the recognized object based on orientations of extracted planes and their intersection points. This paper presents some of the algorithms that have been developed for the purpose of recognizing and estimating the pose of objects as viewed by the laser scanner, and characterizes the desirability and utility of these algorithms within the context of the scanner itself, considering data quality and noise.

Pendleton, Thomas W.↗
NASA NTRS2016

Contributions of Solar Wind and Micrometeoroids to Molecular Hydrogen in the Lunar Exosphere

We investigate the density and spatial distribution of the H2 exosphere of the Moon assuming various source mechanisms. Owing to its low mass, escape is non-negligible for H2. For high-energy source mechanisms, a high percentage of the released molecules escape lunar gravity. Thus, the H2 spatial distribution for high-energy release processes reflects the spatial distribution of the source. For low energy release mechanisms, the escape rate decreases and the H2 redistributes itself predominantly to reflect a thermally accommodated exosphere. However, a small dependence on the spatial distribution of the source is superimposed on the thermally accommodated distribution in model simulations, where density is locally enhanced near regions of higher source rate. For an exosphere accommodated to the local surface temperature, a source rate of 2.2 g s-1 is required to produce a steady state density at high latitude of 1200 cm-3. Greater source rates are required to produce the same density for more energetic release mechanisms. Physical sputtering by solar wind and direct delivery of H2 through micrometeoroid bombardment can be ruled out as mechanisms for producing and liberating H2 into the lunar exosphere. Chemical sputtering by the solar wind is the most plausible as a source mechanism and would require 10-50 of the solar wind H+ inventory to be converted to H2 to account for the observations.

Impact↗
DOE OSTI2022

Quantifying albedo susceptibility biases in shallow clouds

The evaluation of radiative forcing associated with aerosol–cloud interactions remains a significant source of uncertainty in future climate projections. The problem is confounded by the fact that aerosol particles influence clouds locally and that averaging to larger spatial and/or temporal scales carries biases that depend on the heterogeneity and spatial correlation of the interacting fields and the nonlinearity of the responses. Mimicking commonly applied satellite data analyses for calculation of albedo susceptibility S o , we quantify S o aggregation biases using an ensemble of 127 large eddy simulations of marine stratocumulus. We explore the cloud field properties that control this spatial aggregation bias and quantify the bias for a large range of shallow stratocumulus cloud conditions manifesting a variety of morphologies and ranges of cloud fractions. We show that S o spatial aggregation biases can be on the order of hundreds of percent, depending on the methodology. Key uncertainties emanate from the typically applied adiabatic drop concentration N d retrieval, the correlation between aerosol and cloud fields, and the extent to which averaging reduces the variance in cloud albedo A c and N d . So biases are more often positive than negative and are highly correlated with biases in the liquid water path adjustment. Temporal aggregation biases are shown to offset spatial aggregation biases. Both spatial and temporal biases have significant implications for observationally based assessments of aerosol indirect effects and our inferences of underlying aerosol–cloud–radiation effects.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2020

Imaging Carrier Dynamics and Transport in Hybrid Perovskites with Transient Absorption Microscopy

In this review, the recent progress in using transient absorption microscopy to image charge transport and dynamics in semiconducting hybrid organic–inorganic perovskites is discussed. The basic principles, instrumentation, and resolution of transient absorption microscopy are outlined. With temporal resolution as high as 10 fs, sub-diffraction-limit spatial resolution, and excited-state structural resolution, these experiments have provided crucial details on charge transport mechanisms that have been previously obscured in conventional ultrafast spectroscopy measurements. Morphology-dependent mapping unveils spatial heterogeneity in carrier recombination and cooling dynamics. By spatially separating the pump and probe beams, carrier transport across grain boundaries has been directly visualized. Further, femtosecond temporal resolution allows for the examination of nonequilibrium transport directly, revealing extraordinarily long-range hot carrier migration. The application of transient absorption microscopy is not limited to hybrid perovskites but can also be useful for other polycrystalline materials in which morphology plays an important role in carrier transport.

36 MATERIALS SCIENCE↗
DOE OSTI2020

Tensor factorization for elucidating mechanisms of piezoresponse relaxation via dynamic Piezoresponse Force Spectroscopy

Spatially resolved time and voltage-dependent polarization dynamics in PbTiO 3 thin films is explored using dynamic piezoresponse force microscopy (D-PFM) in conjunction with interferometric displacement sensing. This approach gives rise to 4D data sets containing information on bias-dependent relaxation dynamics at each spatial location without long-range electrostatic artifacts. To interpret these data sets in the absence of defined physical models, we employ a non-negative tensor factorization method which clearly presents the data as a product of simple behaviors allowing for direct physics interpretation. Correspondingly, we perform phase-field modeling finding the existence of ‘hard’ and ‘soft’ domain wall edges. This approach can be extended to other multidimensional spectroscopies for which even exploratory data analysis leads to unsatisfactory results due to many components in the decomposition.

36 MATERIALS SCIENCE↗
NASA NTRS1985

The expected cosmic ray density and stream distributions at the heliolatitudinal asymmetry of solar wind

The results of the spatial distribution of cosmic ray density, gradients, and anisotropy obtained on the basis of the numerical solution of the anisotropic diffusion equation with an account of solar wind velocity change depending on the latitudinal angle theta of the form U=u sub oe sup alpha theta and the diffusion coefficient depending on the spatial coordinates and the particle rigidity are presented. It is shown that the increase of the solar wind velocity and the diffusion coefficient with heliolatitude leads to gradient distributions that are in accord with experimental data observed in space. The results of the energetic spectrum of 11 and 22-year cosmic ray variations obtained with an account of direction of the general magnetic field of the Sun are presented are given.

Alania, M. V.↗
NASA NTRSDate not supplied

Simulation of Radiation-Induced DNA Damage With the Code RITRACKS

INTRODUCTION DNA damage is one of the most physiologically important effects of ionizing radiation. Clustered DNA damage events, like double-strand breaks (DSBs), have the most notable biological consequences. DNA damage types depend on both the track structure of the radiation and the spatial organization of the DNA. High linear energy transfer (LET) charged nuclei, found in galactic cosmic rays (GCR), are known to produce large numbers of complex DNA damage events. The human genome is packaged into chromatin, which can take on locus-dependent and cell type-dependent spatial conformations that correspond to epigenetic states, such as more open, extended structures in transcriptionally active chromatin. These epigenetic differences can affect DNA break patterns in response to ionizing radiation, potentially creating distinct DNA repair and signaling outcomes across the genome in different cells. MATERIAL AND METHODS The code RITRACKS (Relativistic Ion Tracks), which simulates stochastic radiation track structures and radiation chemistry, was used to model damage on isolated and histone-bound DNA by various types of ions and photons. The changes made to the code to perform radiation-induced DNA damage, and simulation results on single nucleosomes are given in our recent paper. In this work, the DNA building capabilities of RITRACKS have been extended to simulate more complex DNA structures build on the coarse-grain simulation framework meso-WLCsim. This code can sample generic chromatin fiber conformation ensembles based on the geometry of nucleosomes and mechanical properties of DNA. Using RITRACKS, we simulated the fragment length distributions (FLD) of irradiated DNA structures built using the chromatin conformations of WLCsim and obtained results representative of those obtained with Radiation-Induced Correlated Cleavage with sequencing (RICC-Seq) experiments [6]. We have also performed Fe ion and photon irradiations of K562, IMR90, BJ and RPE-1 cells at NSRL to experimentally validate results. Sample processing and data analysis are in progress and any available preliminary results will be discussed. DISCUSSION The recent updates in the code RITRACKS allow the calculation of several quantities such as the DNA damage yield and the FLD. This approach can be used to model epigenetic state-specific chromatin structure parameters to leverage the epigenetic state data available for many human cell types to infer relative DNA damage sensitivity among genomic loci.

I Plante↗
DOE OSTI2024

Theory and modeling of molecular modes in the NMR relaxation of fluids

Traditional theories of the nuclear magnetic resonance (NMR) autocorrelation function for intra-molecular dipole pairs assume a single-exponential decay, yet the calculated autocorrelation of realistic systems displays a rich, multi-exponential behavior, resulting in anomalous NMR relaxation dispersion (i.e., frequency dependence). We develop an approach to model and interpret the multi-exponential intra-molecular autocorrelation using simple, physical models within a rigorous statistical mechanical development that encompasses both rotational diffusion and translational diffusion in the same framework. Here, we recast the problem of evaluating the autocorrelation in terms of averaging over a diffusion propagator whose evolution is described by a Fokker–Planck equation. The time-independent part admits an eigenfunction expansion, allowing us to write the propagator as a sum over modes. Each mode has a spatial part that depends on the specified eigenfunction and a temporal part that depends on the corresponding eigenvalue (i.e., correlation time) with a simple, exponential decay. The spatial part is a probability distribution of the dipole pair, analogous to the stationary states of a quantum harmonic oscillator. Drawing inspiration from the idea of inherent structures in liquids, we interpret each of the spatial contributions as a specific molecular mode. These modes can be used to model and predict the NMR dipole–dipole relaxation dispersion of fluids by incorporating phenomena on the molecular level. We validate our statistical mechanical description of the distribution in molecular modes with molecular dynamics simulations interpreted without any relaxation models or adjustable parameters: the most important poles in the Padé–Laplace transform of the simulated autocorrelation agree with the eigenvalues predicted by the theory

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2022

Special Issue: Geostatistics and Machine Learning

Abstract Recent years have seen a steady growth in the number of papers that apply machine learning methods to problems in the earth sciences. Although they have different origins, machine learning and geostatistics share concepts and methods. For example, the kriging formalism can be cast in the machine learning framework of Gaussian process regression. Machine learning, with its focus on algorithms and ability to seek, identify, and exploit hidden structures in big data sets, is providing new tools for exploration and prediction in the earth sciences. Geostatistics, on the other hand, offers interpretable models of spatial (and spatiotemporal) dependence. This special issue on Geostatistics and Machine Learning aims to investigate applications of machine learning methods as well as hybrid approaches combining machine learning and geostatistics which advance our understanding and predictive ability of spatial processes.

58 GEOSCIENCES↗
NASA NTRS1980

Propagation in a shearing plasma. II - Turbulence and the frequency range of pulsar microstructure

Numerical calculations are presented which explore the propagation of radio waves and pulses through a turbulent shearing plasma. A stochastic model is used to describe the turbulent velocity field, in which random fluctuations are superposed on a mean profile. Both Gaussian wave packets and shot-noise pulses polarized in the plane of shearing acquire quasi-periodic intensity modulations above the rest-frame plasma frequency. The frequency range over which these modulations appear is shown to depend on the spatial correlation length of the turbulent fluctuations and on their standard deviation from the mean velocity. The period of the modulations is variable from one realization of the random process to the next, and the average period is frequency dependent. The results of these calculations lend further support to a model for pulsar microstructure in which periodic micropulses are pure temporal modulations of the emitted radiation due to propagation effects in magnetospheric shearing regions. It is shown that turbulence on a scale of approximately 10 cm can produce these quasi-periodic modulations over a frequency range comparable to that of observed microstructure.

Harding, A. K.↗
NASA NTRS1989

Galaxy clustering and the origin of large-scale flows

Peebles's 'cosmic virial theorem' is extended from its original range of validity at small separations, where hydrostatic equilibrium holds, to large separations, in which linear gravitational stability theory applies. The rms pairwise velocity difference at separation r is shown to depend on the spatial galaxy correlation function xi(x) only for x less than r. Gravitational instability theory can therefore be tested by comparing the two up to the maximum separation for which both can reliably be determined, and there is no dependence on the poorly known large-scale density and velocity fields. With the expected improvement in the data over the next few years, however, this method should yield a reliable determination of omega.

Juszkiewicz, R.↗
NASA NTRS1987

Utilizing remote sensing of thematic mapper data to improve our understanding of estuarine processes and their influence on the productivity of estuarine-dependent fisheries

A stochastic spatial computer model addressing coastal resource problems in Lousiana is being refined and validated using thematic mapper (TM) imagery. The TM images of brackish marsh sites were processed and data were tabulated on spatial parameters from TM images of the salt marsh sites. The Fisheries Image Processing Systems (FIPS) was used to analyze the TM scene. Activities were concentrated on improving the structure of the model and developing a structure and methodology for calibrating the model with spatial-pattern data from the TM imagery.

Browder, Joan A.↗
DOE OSTI2024

Large-scale spatially explicit analysis of carbon capture at cellulosic biorefineries

The large-scale production of cellulosic biofuels would involve spatially distributed systems including biomass fields, logistics networks and biorefineries. Better understanding of the interactions between landscape-related decisions and the design of biorefineries with carbon capture and storage (CCS) in a supply chain context is needed to enable efficient systems. Here we analyse the cost and greenhouse gas mitigation potential for cellulosic biofuel supply chains in the US Midwest using realistic spatially explicit land availability and crop productivity data and consider fuel conversion technologies with detailed CCS design for their associated CO 2 streams. Optimization methods identify trade-offs and design strategies leading to systems with attractive environmental and economic performance. Strategic and operational decisions depend on underlying spatial features and are sensitive to biofuel demand and CCS incentives. US CCS incentives neglect to motivate greenhouse gas mitigation from all supply chain emission sources, which leverage spatial interactions between CCS, electricity prices and the biomass landscape.

09 BIOMASS FUELS↗
NASA NTRS1987

Evaluation of several classification schemes for mapping forest cover types in Michigan

Landsat MSS data were evaluated for mapping forest cover types in the northern Lower Peninsula of Michigan. The study examined seasonal variations, interpretation procedures and vegetation composition/distribution and their effect on overall classification accuracy and ability to identify individual pine species. Photographic images were used for visual interpretations while digital analysis was performed using a common (ERDAS) microcomputer image processing system. The classification schemes were evaluated using contingency tables and were ranked using the KAPPA statistic. The various classification schemes were ranked differentially according to study site location. Visual interpretation procedures ranked best, or least accurate, depending on the spatial distribution and complexity of the forest cover. Supervised classification techniques were more accurate than unsupervised clustering over all sites and seasons. Maximum likelihood classification of June data was superior to any digital classification technique of February data. The study indicates that classification accuracy is more dependent on the composition and distribution of forests in the northern lower Peninsula of Michigan than on the selection of a particular classification scheme.

Hudson, W. D.↗
DOE OSTI2023

Stochastic Models, Indices & Optimization Algorithms for Pricing & Hedging Reliability Risks in Modern Power Grids: Data Plan - Princeton

We collected and cleaned the synthetic grid data produced by NREL for the Texas and New York synthetic grids. We developed a high dimensional joint stochastic model for load at the zone level, and solar and wind power productions at the asset level, capturing the spatial and temporal dependencies between all the variables, and demonstrated how such a model could be fitted to historical data. We designed and implemented a simulation engine which can produce Monte Carlo scenarios for the hourly day-ahead values of load, and solar and wind power productions at the spatial and temporal resolutions of the historical data used to fit the model. Finally we developed an open-source Python package which can, from an input grid model, efficiently use forecasts and large numbers of Monte Carlo scenarios to provide unit commitment and economic dispatch for each of these scenarios. The high dimensional stochastic model and the subsequent Monte Carlo simulation engine were implemented in the package PGscen and the corresponding UC and ED optimization programs in the package Vatic.

14 SOLAR ENERGY↗
DOE OSTI2020

Time-dependent Ginzburg-Landau treatment of rf magnetic vortices in superconductors: Vortex semiloops in a spatially nonuniform magnetic field

We apply time-dependent Ginzburg-Landau (TDGL) numerical simulations to study the finite frequency electrodynamics of superconductors subjected to an intense rf magnetic field. Much recent TDGL work has focused on spatially uniform external magnetic fields and largely ignores the Meissner state screening response of the superconductor. In this paper, we solve the TGDL equations for a spatially nonuniform magnetic field created by a point magnetic dipole in the vicinity of a semi-infinite superconductor. A two-domain simulation is performed to accurately capture the effect of the inhomogeneous applied fields and the resulting screening currents. The creation and dynamics of vortex semiloops penetrating deep into the superconductor domain are observed and studied, and the resulting third-harmonic nonlinear response of the sample is calculated. Further, the effect of pointlike defects on vortex semi-loop behavior is also studied. This simulation method will assist our understanding of the limits of superconducting response to intense rf magnetic fields.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
NASA NTRS1993

An Imaging Interferometer for Terrestrial Remote Sensing

A prototype imaging interferometer called DASI (digital array scanned interferometer) is under development at our laboratories. Our objective is to design an instrument for remote sensing of Earth's atmosphere and surface. This paper describes the unusual characteristics of DASIs which make them promising candidates for ground and aircraft-based terrestrial measurements. These characteristics include superior signal-to-noise, design simplicity and compactness, relative to dispersion based imaging spectrometers. Perhaps one of the most notable features of DASIs is their ability to acquire an entire interferogram simultaneously without any moving optical elements. We also describe selected laboratory and ground based field measurements using the prototype DASI. A CCD detector array was placed at the DASI detector plane for wavelength coverage from 0.4 to 1.0 micron. A NICMOS MCT detector was used for coverage from 1.1 to 2.2 micron. The DASI was configured to have a spectral resolution of about 300 1/cm, a spatial field of view of 5 degrees, and a constant number of transverse spatial elements (detector dependent) for each exposure frame. Frame exposure rates were up to 0.6 Hz with the potential to achieve 5 Hz. Image cube measurements of laboratory targets and terrestrial scenes were obtained by multiple frame scanning over the field of view. These data sets reveal the potential science yields from obtaining simultaneous high resolution spatial and spectral information.

Hammer, Philip D.↗