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At least 1,621 records · Page 90
All sourcesNASA NTRSDOE OSTI
NASA NTRS2018

Estimation of Seasonal Snow Water Equivalent Using Landsat Observations

This work presents a methodology for estimating seasonal snow water equivalent (SWE) from the use of remotely sensed Visible and Near Infrared observations from the Landsat mission. The method is comprised of two main components: (1) a coupled land surface model and snow depletion curve model, which is used to generate an ensemble of predictions of SWE and snow cover area for a given set of (uncertain) inputs, and (2) a reanalysis step, which updates estimation variables to be consistent with the satellite observed depletion of the fractional snow cover time series. This method was applied over the Sierra Nevada (USA) based on the assimilation of remotely sensed fractional snow covered area data over the Landsat 5-8 record (1985-2016). The verified dataset (based on a comparison with over 9000 station years of in situ data) exhibited mean and root-mean-square errors less than 3 and 13 cm, respectively, and correlations with in situ SWE observations of greater than 0.95. The method (fully Bayesian), resolution (daily, 90-meter), temporal extent (32 years), and accuracy provide a unique dataset for investigating snow processes. In particular, this presentation illustrates how the reanalysis dataset was used to provide climatology of the seasonal snowfall accumulation rates, distributions, and variability over the last three decades.

SWE↗
DOE OSTI2014

Improving the precision of astrometry for space debris

The data reduction method for optical space debris observations has many similarities with the one adopted for surveying near-Earth objects; however, due to several specific issues, the image degradation is particularly critical, which makes it difficult to obtain precise astrometry. An automatic image reconstruction method was developed to improve the astrometry precision for space debris, based on the mathematical morphology operator. Variable structural elements along multiple directions are adopted for image transformation, and then all the resultant images are stacked to obtain a final result. To investigate its efficiency, trial observations are made with Global Positioning System satellites and the astrometry accuracy improvement is obtained by comparison with the reference positions. The results of our experiments indicate that the influence of degradation in astrometric CCD images is reduced, and the position accuracy of both objects and stellar stars is improved distinctly. Our technique will contribute significantly to optical data reduction and high-order precision astrometry for space debris.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2016

Understanding the optical properties of ambient sub- and supermicron particulate matter: results from the CARES 2010 field study in northern California

Abstract. Measurements of the optical properties (absorption, scattering and extinction) of PM1, PM2.5 and PM10 made at two sites around Sacramento, CA, during the June 2010 Carbonaceous Aerosols and Radiative Effects Study (CARES) are reported. These observations are used to establish relationships between various intensive optical properties and to derive information about the dependence of the optical properties on photochemical aging and sources. Supermicron particles contributed substantially to the total light scattering at both sites, about 50 % on average. A strong, linear relationship is observed between the scattering Ångström exponent for PM10 and the fraction of the scattering that is contributed by submicron particles (fsca, PM1) at both sites and with similar slopes and intercepts (for a given pair of wavelengths), suggesting that the derived relationship may be generally applicable for understanding variations in particle size distributions from remote sensing measurements. At the more urban T0 site, the fsca, PM1 increased with photochemical age, whereas at the downwind, more rural T1 site the fsca, PM1 decreased slightly with photochemical age. This difference in behavior reflects differences in transport, local production and local emission of supermicron particles between the sites. Light absorption is dominated by submicron particles, but there is some absorption by supermicron particles ( ∼ 15 % of the total). The supermicron absorption derives from a combination of black carbon that has penetrated into the supermicron mode and from dust, and there is a clear increase in the mass absorption coefficient of just the supermicron particles with increasing average particle size. The mass scattering coefficient (MSC) for the supermicron particles was directly observed to vary inversely with the average particle size, demonstrating that MSC cannot always be treated as a constant in estimating mass concentrations from scattering measurements, or vice versa. The total particle backscatter fraction exhibited some dependence upon the relative abundance of sub- versus supermicron particles; however this was modulated by variations in the median size of particles within a given size range; variations in the submicron size distribution had a particularly large influence on the observed backscatter efficiency and an approximate method to account for this variability is introduced. The relationship between the absorption and scattering Ångström exponents is examined and used to update a previously suggested particle classification scheme. Differences in composition led to differences in the sensitivity of PM2.5 to heating in a thermodenuder to the average particle size, with more extensive evaporation (observed as a larger decrease in the PM2.5 extinction coefficient) corresponding to smaller particles; i.e., submicron particles were generally more susceptible to heating than the supermicron particles. The influence of heating on the particle hygroscopicity varied with the effective particle size, with larger changes observed when the PM2.5 distribution was dominated by smaller particles.

54 ENVIRONMENTAL SCIENCES↗
NASA NTRS2018

TPSAS-NF1676L-32014-DND

The Cloud-Aerosol Lidar with Orthogonal Polarization (CALIOP), on-board the Cloud-Aerosol Lidar and Infrared Pathfinder Satellite Observations (CALIPSO) is a satellite-borne polarization sensitive lidar. It has been providing the vertical distributions of clouds and aerosols along with their microphysical and optical properties since 2006. One of its important Level 2 products, feature classification, has been determined using the lidar information from 532 nm parallel and perpendicular channels, and 1064 nm channel measurements of layer integrated backscatter. Deep machine learning methods which combine both the channel and texture information to recognize feature patterns is uniquely beneficial when applied to this data. In this study, we will use Convolutional Neural Network (CNN), a deep machine learning method, to classify lidar aerosol subtypes by using the lidar profile observations. This method uses additional information from the vertical texture of the feature instead of using only the layer information. Note that in the integrated layer properties, the texture information has been masked due to averaging. Our results will show how the texture information plays a role in the classification. This preliminary work explores the benefits and potential of deep machine learning methods for lidar retrievals and focuses on the aerosol subtype classification. The broader application extends to the classification of other feature types. Future applications include the developing deep machine learning methods with neural networks to retrieve properties of the features, and studies of indirect effect of cloud-aerosol interaction from lidar measurements.

Shan Zeng Kowalski↗
DOE OSTI2016

Phase equilibria in the U-Si system from first-principles calculations

Density functional theory calculations have been used with spin-orbit coupling and on-site Coulomb correction (GGA + U) methods to investigate the U-Si system. Structural prediction methods were employed to identify alternate stable structures. Convex hulls of the U-Si system were constructed for each of the methods to highlight the competing energetics of various phases. For GGA calculations, new structures are predicted to be dynamically stable, but these have not been experimentally observed. When the GGA + U (U eff > 1.3 eV) method is considered, the experimentally observed structures are predicted to be energetically preferred. Phonon calculations were used to investigate the energy predictions and showed that the use of the GGA + U method removes the significant imaginary frequencies observed for U 3 Si 2 when the correction is not considered. In conclusion, total and partial electron density of states calculations were also performed to understand the role of GGA + U methods and orbitals on the bonding and stability of U-Si compounds.

36 MATERIALS SCIENCE↗
DOE OSTI2023

Correlated insulator of excitons in WSe 2 /WS 2 moiré superlattices

A panoply of unconventional electronic states has been observed in moiré superlattices. Engineering similar bosonic phases remains, however, largely unexplored. We report the observation of a bosonic correlated insulator in tungsten diselenide/tungsten disulfide (WSe 2 /WS 2 ) moiré superlattices composed of excitons, that is, tightly bound electron-hole pairs. We develop a pump probe spectroscopy method that we use to observe an exciton incompressible state at exciton filling ν ex = 1 and charge neutrality, indicating a correlated insulator of excitons. With varying charge density, the bosonic correlated insulator continuously transitions into an electron correlated insulator at charge filling ν e = 1, suggesting a mixed correlated insulating state between the two limits. Our studies establish semiconducting moiré superlattices as an intriguing platform for engineering bosonic phases.

Science & Technology - Other Topics↗
DOE OSTI2016

SUN-TO-EARTH CHARACTERISTICS OF THE 2012 JULY 12 CORONAL MASS EJECTION AND ASSOCIATED GEO-EFFECTIVENESS

We analyze multi-spacecraft observations associated with the 2012 July 12 coronal mass ejection (CME), covering the source region on the Sun from the Solar Dynamics Observatory , stereoscopic imaging observations from the Solar Terrestrial Relations Observatory ( STEREO ), magnetic field characteristics from Mercury Surface, Space Environment, Geochemistry, and Ranging ( MESSENGER ), and type II radio burst and in situ measurements from Wind . A triangulation method based on STEREO stereoscopic observations is employed to determine the kinematics of the CME, and the outcome is compared with the results derived from the type II radio burst using a solar wind electron density model. A Grad–Shafranov technique is applied to Wind in situ data to reconstruct the flux-rope structure and compare it with the observations of the solar source region, which helps in understanding the geo-effectiveness associated with the CME structure. Our conclusions are as follows: (1) the CME undergoes an impulsive acceleration, a rapid deceleration before reaching MESSENGER , and then a gradual deceleration out to 1 au, which should be considered in CME kinematics models; (2) the type II radio burst was probably produced from a high-density interaction region between the CME-driven shock and a nearby streamer or from the shock flank with lower heights, which implies uncertainties in the determination of CME kinematics using solely type II radio bursts; (3) the flux-rope orientation and chirality deduced from in situ reconstructions at Wind agree with those obtained from solar source observations; (4) the prolonged southward magnetic field near the Earth is mainly from the axial component of the largely southward inclined flux rope, which indicates the importance of predicting both the flux-rope orientation and magnetic field components in geomagnetic activity forecasting.

79 ASTRONOMY AND ASTROPHYSICS↗
NASA NTRS1991

Spectroscopic investigations of microwave generated plasmas

The study deals with the plasma behavior as applied to spacecraft propulsion from the perspective of obtaining better design and modeling capabilities. The general theory of spectroscopy is reviewed, and existing methods for converting emission-line intensities into such quantities as temperatures and densities are outlined. Attention is focused on the single-atomic-line and two-line radiance ratio methods, atomic Boltzmann plot, and species concentration. Electronic temperatures for a helium plasma are determined as a function of pressure and a gas-flow rate using these methods, and the concentrations of ions and electrons are predicted from the Saha-Eggert equations using the sets of temperatures obtained as a function of the gas-flow rate. It is observed that the atomic Boltzmann method produces more reliable results for the electronic temperature, while the results obtained from the single-line method reflect the electron temperatures accurately.

Hawley, Martin C.↗
DOE OSTI2013

Investigation of statistical iterative reconstruction for dedicated breast CT

Purpose: Dedicated breast CT has great potential for improving the detection and diagnosis of breast cancer. Statistical iterative reconstruction (SIR) in dedicated breast CT is a promising alternative to traditional filtered backprojection (FBP). One of the difficulties in using SIR is the presence of free parameters in the algorithm that control the appearance of the resulting image. These parameters require tuning in order to achieve high quality reconstructions. In this study, the authors investigated the penalized maximum likelihood (PML) method with two commonly used types of roughness penalty functions: hyperbolic potential and anisotropic total variation (TV) norm. Reconstructed images were compared with images obtained using standard FBP. Optimal parameters for PML with the hyperbolic prior are reported for the task of detecting microcalcifications embedded in breast tissue.Methods: Computer simulations were used to acquire projections in a half-cone beam geometry. The modeled setup describes a realistic breast CT benchtop system, with an x-ray spectra produced by a point source and an a-Si, CsI:Tl flat-panel detector. A voxelized anthropomorphic breast phantom with 280 μm microcalcification spheres embedded in it was used to model attenuation properties of the uncompressed woman's breast in a pendant position. The reconstruction of 3D images was performed using the separable paraboloidal surrogates algorithm with ordered subsets. Task performance was assessed with the ideal observer detectability index to determine optimal PML parameters.Results: The authors' findings suggest that there is a preferred range of values of the roughness penalty weight and the edge preservation threshold in the penalized objective function with the hyperbolic potential, which resulted in low noise images with high contrast microcalcifications preserved. In terms of numerical observer detectability index, the PML method with optimal parameters yielded substantially improved performance (by a factor of greater than 10) compared to FBP. The hyperbolic prior was also observed to be superior to the TV norm. A few of the best-performing parameter pairs for the PML method also demonstrated superior performance for various radiation doses. In fact, using PML with certain parameter values results in better images, acquired using 2 mGy dose, than FBP-reconstructed images acquired using 6 mGy dose.Conclusions: A range of optimal free parameters for the PML algorithm with hyperbolic and TV norm-based potentials is presented for the microcalcification detection task, in dedicated breast CT. The reported values can be used as starting values of the free parameters, when SIR techniques are used for image reconstruction. Significant improvement in image quality can be achieved by using PML with optimal combination of parameters, as compared to FBP. Importantly, these results suggest improved detection of microcalcifications can be obtained by using PML with lower radiation dose to the patient, than using FBP with higher dose.

62 RADIOLOGY AND NUCLEAR MEDICINE↗
NASA NTRS1985

Limits on the Doppler factor in relativistic jets by means of gamma-ray observations

A new, simple and potentially useful method for constraining the kinematical parameters of relativistic jets based on gamma ray spectral measurements of Active Galaxies is presented. The application of this method to the Quasar 3C273 leads to a value of the Doppler factor of 3 to 4. This corresponds to jet parameters of mu 2 and theta 15 deg in good agreement with the values estimated independently from radio observations of superluminal motion. For the particular case of 3C273, the results are also compared to those given by a similar technique based on the comparison of the X-ray observational data with the synchrotron self Compton prediction from radio measurements. The application of the proposed technique to a significant sample of active galaxies as a result of future gamma ray surveys of the sky is briefly discussed, particularly with respect to possible ways to constrain the cosmological constants H sub o and q sub o.

Dean, A. J.↗
NASA NTRS2010

Robust Mosaicking of Stereo Digital Elevation Models from the Ames Stereo Pipeline

Robust estimation method is proposed to combine multiple observations and create consistent, accurate, dense Digital Elevation Models (DEMs) from lunar orbital imagery. The NASA Ames Intelligent Robotics Group (IRG) aims to produce higher-quality terrain reconstructions of the Moon from Apollo Metric Camera (AMC) data than is currently possible. In particular, IRG makes use of a stereo vision process, the Ames Stereo Pipeline (ASP), to automatically generate DEMs from consecutive AMC image pairs. However, the DEMs currently produced by the ASP often contain errors and inconsistencies due to image noise, shadows, etc. The proposed method addresses this problem by making use of multiple observations and by considering their goodness of fit to improve both the accuracy and robustness of the estimate. The stepwise regression method is applied to estimate the relaxed weight of each observation.

Kim, Tae Min↗
DOE OSTI2013

ULTRAVIOLET EMISSION-LINE CORRELATIONS IN HST/COS SPECTRA OF ACTIVE GALACTIC NUCLEI: SINGLE-EPOCH BLACK HOLE MASSES

Effective methods of measuring supermassive black hole masses in active galactic nuclei (AGNs) are of critical importance to studies of galaxy evolution. While there has been much success in obtaining masses through reverberation mapping, the extensive observing time required by this method has limited the practicality of applying it to large samples at a variety of redshifts. This limitation highlights the need to estimate these masses using single-epoch spectroscopy of ultraviolet (UV) emission lines. We use UV spectra of 44 AGNs from HST/COS, the International Ultraviolet Explorer, and the Far Ultraviolet Spectroscopic Explorer of the C IV {lambda}1549, O VI {lambda}1035, O III] {lambda}1664, He II {lambda}1640, C II {lambda}1335, and Mg II {lambda}2800 emission lines and explore their potential as tracers of the broad-line region and supermassive black hole mass. The higher signal-to-noise ratio and better spectral resolution of the Cosmic Origins Spectrograph (COS) on the Hubble Space Telescope (HST) resolve AGN intrinsic absorption and produce more accurate line widths. From these, we test the viability of mass-scaling relationships based on line widths and luminosities and carry out a principal component analysis based on line luminosities, widths, skewness, and kurtosis. At L{sub 1450} {<=} 10{sup 45} erg s{sup -1}, the UV line luminosities correlate well with H{beta}, as does the 1450 A continuum luminosity. We find that C IV, O VI, and Mg II can be used as reasonably accurate estimators of AGN black hole masses, while He II and C II are uncorrelated.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2016

SU-D-207A-07: The Effects of Inter-Cycle Respiratory Motion Variation On Dose Accumulation in Single Fraction MR-Guided SBRT Treatment of Renal Cell Carcinoma

Purpose: To assess the dose deposition in simulated single-fraction MR-Linac treatments of renal cell carcinoma, when inter-cycle respiratory motion variation is taken into account using online MRI. Methods: Three motion characterization methods, with increasing complexity, were compared to evaluate the effect of inter-cycle motion variation and drifts on the accumulated dose for an SBRT kidney MR-Linac treatment: 1) STATIC, in which static anatomy was assumed, 2) AVG-RESP, in which 4D-MRI phase-volumes were time-weighted, based on the respiratory phase and 3) PCA, in which 3D volumes were generated using a PCA-model, enabling the detection of inter-cycle variations and drifts. An experimental ITV-based kidney treatment was simulated in a 1.5T magnetic field on three volunteer datasets. For each volunteer a retrospectively sorted 4D-MRI (ten respiratory phases) and fast 2D cine-MR images (temporal resolution = 476ms) were acquired to simulate MR-imaging during radiation. For each method, the high spatio-temporal resolution 3D volumes were non-rigidly registered to obtain deformation vector fields (DVFs). Using the DVFs, pseudo-CTs (generated from the 4D-MRI) were deformed and the dose was accumulated for the entire treatment. The accuracies of all methods were independently determined using an additional, orthogonal 2D-MRI slice. Results: Motion was most accurately estimated using the PCA method, which correctly estimated drifts and inter-cycle variations (RMSE=3.2, 2.2, 1.1mm on average for STATIC, AVG-RESP and PCA, compared to the 2DMRI slice). Dose-volume parameters on the ITV showed moderate changes (D99=35.2, 32.5, 33.8Gy for STATIC, AVG-RESP and PCA). AVG-RESP showed distinct hot/cold spots outside the ITV margin, which were more distributed for the PCA scenario, since inter-cycle variations were not modeled by the AVG-RESP method. Conclusion: Dose differences were observed when inter-cycle variations were taken into account. The increased inter-cycle randomness in motion as captured by the PCA model mitigates the local (erroneous) hotspots estimated by the AVG-RESP method.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2023

Mathematical solutions in internal dose assessment: A comparison of Python-based differential equation solvers in biokinetic modeling

Abstract In biokinetic modeling systems employed for radiation protection, biological retention and excretion have been modeled as a series of discretized compartments representing the organs and tissues of the human body. Fractional retention and excretion in these organ and tissue systems have been mathematically governed by a series of coupled first-order ordinary differential equations (ODEs). The coupled ODE systems comprising the biokinetic models are usually stiff due to the severe difference between rapid and slow transfers between compartments. In this study, the capabilities of solving a complex coupled system of ODEs for biokinetic modeling were evaluated by comparing different Python programming language solvers and solving methods with the motivation of establishing a framework that enables multi-level analysis. The stability of the solvers was analyzed to select the best performers for solving the biokinetic problems. A Python-based linear algebraic method was also explored to examine how the numerical methods deviated from an analytical or semi-analytical method. Results demonstrated that customized implicit methods resulted in an enhanced stable solution for the inhaled 60 Co (Type M) and 131 I (Type F) exposure scenarios for the inhalation pathway of the International Commission on Radiological Protection (ICRP) Publication 130 Human Respiratory Tract Model (HRTM). The customized implementation of the Python-based implicit solvers resulted in approximately consistent solutions with the Python-based matrix exponential method ( expm ). The differences generally observed between the implicit solvers and expm are attributable to numerical precision and the order of numerical approximation of the numerical solvers. This study provides the first analysis of a list of Python ODE solvers and methods by comparing their usage for solving biokinetic models using the ICRP Publication 130 HRTM and provides a framework for the selection of the most appropriate ODE solvers and methods in Python language to implement for modeling the distribution of internal radioactivity.

61 RADIATION PROTECTION AND DOSIMETRY↗
NASA NTRS1974

UCLA International Conference on Radiation and Remote Probing of the Atmosphere, University of California, Los Angeles, Calif., August 28-30, 1973, Proceedings

Approaches for solving multiple scattering problems in planetary atmospheres are considered along with the solution of the radiative transfer theory problems by the Monte Carlo method, the radiative transfer of visible radiation in turbid atmospheres, aspects of scattering and absorption from poly-dispersed aerosols, and multiple scattering in cloud layers. Other subjects discussed include particulate sizes from polarization measurements, lidar observations of atmospheric particulate content, methods of calculating infrared transfer, molecular absorption parameters in atmospheric modelling, and infrared remote sounding. The influence of the atmosphere on spectral radiance and contrasts of natural formations measured from space is investigated and analytical results for radiative transfer in thick atmospheres are presented. Individual items are announced in this issue.

Kuriyan, J. G.↗
NASA NTRS2005

A Stochastic Cratering Model for Asteroid Surfaces

The observed cratering records on asteroid surfaces (four so far: Gaspra, Ida, Mathilde, and Eros [1-4]) provide us with important clues to their past bombardment histories. Previous efforts toward interpreting these records have led to two basic modeling styles for reproducing the statistics of the observed crater populations. The first, and most direct, method is to use Monte Carlo techniques [5] to stochastically populate a matrix-model test surface with craters as a function of time [6,7]. The second method is to use a more general, parameterized approach to duplicate the statistics of the observed crater population [8,9]. In both methods, several factors must be included beyond the simple superposing of circular features: (1) crater erosion by subsequent impacts, (2) infilling of craters by impact ejecta, and (3) crater degradation and era- sure due to the seismic effects of subsequent impacts. Here we present an updated Monte Carlo (stochastic) modeling approach, designed specifically with small- to medium-sized asteroids in mind.

Richardson, J. E.↗
DOE OSTI2021

Causal Evaluations for Identifying Differences between Observations and Earth System Models

We use a nascent data-driven causal discovery method to find and compare causal relationships in observed data and climate model output. We consider ten different features in the Arctic climate collected from public databases on observational and Energy Exascale Earth System Model (E3SM) data. In identifying and analyzing the resulting causal networks, we make meaningful comparisons between observed and climate model interdependencies. This work demonstrates our ability to apply the PCMCI causal discovery algorithm to Arctic climate data, that there are noticeable similarities between observed and simulated Arctic climate dynamics, and that further work is needed to identify specific areas for improvement to better align models with natural observations.

54 ENVIRONMENTAL SCIENCES↗