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At least 451 records · Page 25
All sourcesNASA NTRSDOE OSTI
NASA NTRS1975

Development of a method for optimal maneuver analysis of complex space missions

A system that allows mission planners to find optimal multiple-burn space trajectories easily is described. Previously developed methods with different gravity assumptions perform the optimization function. The power of these programs is extended by a method of costate estimation. A penalty function method of constraining coast arc times to be positive is included. The capability of the method is demonstrated by finding the optimal control for three different space missions. These include a shuttle abort-once-around mission and two- and three-burn geosynchronous satellite-placement missions.

Mcadoo, S. F., Jr.↗
NASA NTRS1987

Observations of the Jovian UV aurora by Voyager

The observations of the Jovian aurora made by the Voyager UV spectrometer (UVS) during 1979 are analyzed, with special consideration given to the model fitting process. Several different estimates of the function specifying auroral arc geometry were tried, with the Broadfoot et al. (1981) estimate, found by probing with the tip of the UVS slit, giving the best agreement; this agreement is slightly better than the agreement with the Io torus footprint computed by Roederer et al. (1977). The results suggest that the UVS observations are more sensitive to the surface field geometry than are the Voyager flyby in situ observations. The results of a study of intensity maximum positions indicate that the particles exciting the spatially variable portion of the aurora are drifting west, implying either that these particles are electrons or that they are positive ions drifting east more slowly than the corotation lag of the Io torus region carries them to the west. The latter case is most consistent with the high-energy charged particle measurements.

Herbert, Floyd↗
NASA NTRS1989

Numerical optimization in Hilbert space using inexact function and gradient evaluations

Trust region algorithms provide a robust iterative technique for solving non-convex unstrained optimization problems, but in many instances it is prohibitively expensive to compute high accuracy function and gradient values for the method. Of particular interest are inverse and parameter estimation problems, since function and gradient evaluations involve numerically solving large systems of differential equations. A global convergence theory is presented for trust region algorithms in which neither function nor gradient values are known exactly. The theory is formulated in a Hilbert space setting so that it can be applied to variational problems as well as the finite dimensional problems normally seen in trust region literature. The conditions concerning allowable error are remarkably relaxed: relative errors in the gradient error condition is automatically satisfied if the error is orthogonal to the gradient approximation. A technique for estimating gradient error and improving the approximation is also presented.

Carter, Richard G.↗
NASA NTRS2013

Comparative Analysis of Alternative Spectral Bands of CO2 and O2 for the Sensing of CO2 Mixing Ratios

We performed comparative studies to establish favorable spectral regions and measurement wavelength combinations in alternative bands of CO2 and O2, for the sensing of CO2 mixing ratios (XCO2) in missions such as ASCENDS. The analysis employed several simulation approaches including separate layers calculations based on pre-analyzed atmospheric data from the modern-era retrospective analysis for research and applications (MERRA), and the line-byline radiative transfer model (LBLRTM) to obtain achievable accuracy estimates as a function of altitude and for the total path over an annual span of variations in atmospheric parameters. Separate layer error estimates also allowed investigation of the uncertainties in the weighting functions at varying altitudes and atmospheric conditions. The parameters influencing the measurement accuracy were analyzed independently and included temperature sensitivity, water vapor interferences, selection of favorable weighting functions, excitations wavelength stabilities and other factors. The results were used to identify favorable spectral regions and combinations of on / off line wavelengths leading to reductions in interferences and the improved total accuracy.

Pliutau, Denis↗
NASA NTRS2012

Global Air Quality and Health Co-benefits of Mitigating Near-term Climate Change Through Methane and Black Carbon Emission Controls

Tropospheric ozone and black carbon (BC), a component of fine particulate matter (PM < or = 2.5 microns in aerodynamic diameter; PM2.5), are associated with premature mortality and they disrupt global and regional climate. Objectives: We examined the air quality and health benefits of 14 specific emission control measures targeting BC and methane, an ozone precursor, that were selected because of their potential to reduce the rate of climate change over the next 20-40 years. Methods: We simulated the impacts of mitigation measures on outdoor concentrations of PM2.5 and ozone using two composition-climate models, and calculated associated changes in premature PM2.5‑ and ozone-related deaths using epidemiologically derived concentration-response functions. Results: We estimated that, for PM2.5 and ozone, respectively, fully implementing these measures could reduce global population-weighted average surface concentrations by 23-34% and 7-17% and avoid 0.6-4.4 and 0.04-0.52 million annual premature deaths globally in 2030. More than 80% of the health benefits are estimated to occur in Asia. We estimated that BC mitigation measures would achieve approximately 98% of the deaths that would be avoided if all BC and methane mitigation measures were implemented, due to reduced BC and associated reductions of nonmethane ozone precursor and organic carbon emissions as well as stronger mortality relationships for PM2.5 relative to ozone. Although subject to large uncertainty, these estimates and conclusions are not strongly dependent on assumptions for the concentration-response function. Conclusions: In addition to climate benefits, our findings indicate that the methane and BC emission control measures would have substantial co-benefits for air quality and public health worldwide, potentially reversing trends of increasing air pollution concentrations and mortality in Africa and South, West, and Central Asia. These projected benefits are independent of carbon dioxide mitigation measures. Benefits of BC measures are underestimated because we did not account for benefits from reduced indoor exposures and because outdoor exposure estimates were limited by model spatial resolution.

air quality↗
DOE OSTI2022

Towards mapping biodiversity from above: Can fusing lidar and hyperspectral remote sensing predict taxonomic, functional, and phylogenetic tree diversity in temperate forests?

Abstract Aim Rapid global change is impacting the diversity of tree species and essential ecosystem functions and services of forests. It is therefore critical to understand and predict how the diversity of tree species is spatially distributed within and among forest biomes. Satellite remote sensing platforms have been used for decades to map forest structure and function but are limited in their capacity to monitor change by their relatively coarse spatial resolution and the complexity of scales at which different dimensions of biodiversity are observed in the field. Recently, airborne remote sensing platforms making use of passive high spectral resolution (i.e., hyperspectral) and active lidar data have been operationalized, providing an opportunity to disentangle how biodiversity patterns vary across space and time from field observations to larger scales. Most studies to date have focused on single sites and/or one sensor type; here we ask how multiple sensor types from the National Ecological Observatory Network’s Airborne Observation Platform (NEON AOP) perform across multiple sites in a single biome at the NEON field plot scale (i.e., 40 m × 40 m). Location Eastern USA. Time period 2017–2018. Taxa studied Trees. Methods With a fusion of hyperspectral and lidar data from the NEON AOP, we assess the ability of high resolution remotely sensed metrics to measure biodiversity variation across eastern US temperate forests. We examine how taxonomic, functional, and phylogenetic measures of alpha diversity vary spatially and assess to what degree remotely sensed metrics correlate with in situ biodiversity metrics. Results Models using estimates of forest function, canopy structure, and topographic diversity performed better than models containing each category alone. Our results show that canopy structural diversity, and not just spectral reflectance, is critical to predicting biodiversity. Main conclusions We found that an approach that jointly leverages spectral properties related to leaf and canopy functional traits and forest health, lidar derived estimates of forest structure, fine‐resolution topographic diversity, and careful consideration of biogeographical differences within and among biomes is needed to accurately map biodiversity variation from above.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2022

The effect of quasar redshift errors on Lyman-α forest correlation functions

ABSTRACT Using synthetic Lyman-α forests from the Dark Energy Spectroscopic Instrument (DESI) survey, we present a study of the impact of errors in the estimation of quasar redshift on the Lyman-α correlation functions. Estimates of quasar redshift have large uncertainties of a few hundred km s−1 due to the broadness of the emission lines and the intrinsic shifts from other emission lines. We inject Gaussian random redshift errors into the mock quasar catalogues, and measure the auto-correlation and the Lyman-α-quasar cross-correlation functions. We find a smearing of the BAO feature in the radial direction, but changes in the peak position are negligible. However, we see a significant unphysical correlation for small separations transverse to the line of sight which increases with the amplitude of the redshift errors. We interpret this contamination as a result of the broadening of emission lines in the measured mean continuum, caused by quasar redshift errors, combined with the unrealistically strong clustering of the simulated quasars on small scales.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2018

Hydrological niche segregation defines forest structure and drought tolerance strategies in a seasonal Amazon forest

The relationship between rooting depth and above-ground hydraulic traits can potentially define drought resistance strategies that are important in determining species distribution and coexistence in seasonal tropical forests, and understanding this is important for predicting the effects of future climate change in these ecosystems. We assessed the rooting depth of 12 dominant tree species (representing c. 42% of the forest basal area) in a seasonal Amazon forest using the stable isotope ratios (δ 18 O and δ 2 H) of water collected from tree xylem and soils from a range of depths. We took advantage of a major ENSO-related drought in 2015/2016 that caused substantial evaporative isotope enrichment in the soil and revealed water use strategies of each species under extreme conditions. We measured the minimum dry season leaf water potential both in a normal year (2014; Ψ non-ENSO ) and in an extreme drought year (2015; Ψ ENSO ). Furthermore, we measured xylem hydraulic traits that indicate water potential thresholds trees tolerate without risking hydraulic failure (P 50 and P 88 ). We demonstrate that coexisting trees are largely segregated along a single hydrological niche axis defined by root depth differences, access to light and tolerance of low water potential. These differences in rooting depth were strongly related to tree size; diameter at breast height (DBH) explained 72% of the variation in the δ 18 Oxylem. Additionally, δ 18 O xylem explained 49% of the variation in P50 and 70% of P88, with shallow-rooted species more tolerant of low water potentials, while δ 18 O of xylem water explained 47% and 77% of the variation of minimum Ψ non-ENSO and Ψ ENSO . We propose a new formulation to estimate an effective functional rooting depth, i.e. the likely soil depth from which roots can sustain water uptake for physiological functions, using DBH as predictor of root depth at this site. Based on these estimates, we conclude that rooting depth varies systematically across the most abundant families, genera and species at the Tapajós forest, and that understorey species in particular are limited to shallow rooting depths. Our results support the theory of hydrological niche segregation and its underlying trade-off related to drought resistance, which also affect the dominance structure of trees in this seasonal eastern Amazon forest. Synthesis. Our results support the theory of hydrological niche segregation and demonstrate its underlying trade-off related to drought resistance (access to deep water vs. tolerance of very low water potentials). We found that the single hydrological axis defining water use traits was strongly related to tree size, and infer that periodic extreme droughts influence community composition and the dominance structure of trees in this seasonal eastern Amazon forest.

54 ENVIRONMENTAL SCIENCES↗
NASA NTRS1992

Tables Of Gaussian-Type Orbital Basis Functions

NASA technical memorandum contains tables of estimated Hartree-Fock wave functions for atoms lithium through neon and potassium through krypton. Sets contain optimized Gaussian-type orbital exponents and coefficients, and near Hartree-Fock quality. Orbital exponents optimized by minimizing restricted Hartree-Fock energy via scaled Newton-Raphson scheme in which Hessian evaluated numerically by use of analytically determined gradients.

Partridge, Harry↗
NASA NTRSDate not supplied

A Thermodynamic Paradigm for Studying Disease Vector’s Habitats & Life Cycles Using NASA’s NextGen Remote Sensing Instruments

Global public health is entering a new informational age through the use of spatial models of disease vector/host ecologies driven by the use of remotely sensed data to measure environmental and structural factors critical in determining disease vector habitats, distributions, life cycles, and host interactions. The vector habitat microclimates can be quantified in terms of the surface energy budget measured by satellites. The epidemiological equations (processes) can be adapted and modified to explicitly incorporate environmental factors and interfaces required by a specific disease and its vector/host cycle. Remote sensing can be used to measure or evaluate or estimate both environment (state functions) and interface (process functions). Remote sensing can be used to measure or evaluate or estimate both environment (state functions) and interface (process functions) defining vector habitats. The products of remote sensing can be integrated directly into the epidemiological equations to significantly enhance our understanding of disease vector’s life cycles and habitats. The next generation of NASA’s remote sensing instruments recently operational will provide a significant enhancement in our ability to study disease vector’s life cycles and habitats. Three new instruments have become operational on the International Space Station (ISS) In June 2018, ECOSTRESS (The ECOsystem Spaceborne Thermal Radiometer Experiment on Space Station), a five channel, thermal IR instrument with 70 m resolution and approximately 4-5 day repeat cycle of day/night pairs along with DESISa hyperspectral sensor system 235 channels (between 400 and 1000 nanometers), 30 m resolution, and data only being acquired on demand. In November 2018. GEDI (Global Ecosystem Dynamics Investigation). GEDI is a high-resolution laser ranging of Earth’s forests and topography. These instruments set the stage for NASA’s new global designated observables set of remote sensing measurements collecting hyperspectral and multispectral thermal data called SBG (Surface Biology Geology). The SBG is currently in the planning stage. The availability and use of level 1-4 data products generated from these ISS instruments will be discussed.

thermodynamics↗
DOE OSTI2013

THE RICH GLOBULAR CLUSTER SYSTEM OF ABELL 1689 AND THE RADIAL DEPENDENCE OF THE GLOBULAR CLUSTER FORMATION EFFICIENCY

We study the rich globular cluster (GC) system in the center of the massive cluster of galaxies Abell 1689 (z = 0.18), one of the most powerful gravitational lenses known. With 28 Hubble Space Telescope/Advanced Camera for Surveys orbits in the F814W bandpass, we reach a magnitude I{sub 814} = 29 with ∼>90% completeness and sample the brightest ∼5% of the GC system. Assuming the well-known Gaussian form of the GC luminosity function (GCLF), we estimate a total population of N{sup total}{sub GC}= 162,850{sup +75,450}{sub -51,310} GCs within a projected radius of 400 kpc. As many as half of the GCs may comprise an intracluster component. Even with the sizable uncertainties, which mainly result from the uncertain GCLF parameters, this system is by far the largest GC population studied to date. The specific frequency S{sub N} is high, but not uncommon for central galaxies in massive clusters, rising from S{sub N} ≈ 5 near the center to ∼12 at large radii. Passive galaxy fading would increase S{sub N} by ∼20% at z = 0. We construct the radial mass profiles of the GCs, stars, intracluster gas, and lensing-derived total mass, and we compare the mass fractions as a function of radius. The estimated mass in GCs, M{sub GC}{sup total} = 3.9 × 10{sup 10} M{sub ☉}, is comparable to ∼80% of the total stellar mass of the Milky Way. The shape of the GC mass profile appears intermediate between those of the stellar light and total cluster mass. Despite the extreme nature of this system, the ratios of the GC mass to the baryonic and total masses, and thus the GC formation efficiency, are typical of those in other rich clusters when comparing at the same physical radii. The GC formation efficiency is not constant, but varies with radius, in a manner that appears similar for different clusters; we speculate on the reasons for this similarity in profile.

79 ASTRONOMY AND ASTROPHYSICS↗
NASA NTRS1984

The electrical conductivity of the upper mantle as estimated from satellite magnetic field data

The electrical conductivity of the upper mantle is estimated from low-latitude magnetic field variations caused by large fluctuations in the equatorial ring current. The data base is derived from magnetic field magnitude data measured by satellites OGO 2, 4, and 6, which offer better global coverage than land-based observatories. The procedures of analysis consist of: (1) separation of the disturbance field into internal and external parts relative to the surface of the earth, (2) estimation of an electromagnetic response function Q(omega) which relates the internally generated magnetic field variations to the external variations due to the ring current, and (3) interpretation of the estimated response function using theoretical response functions for assumed conductivity profiles. Special consideration is given to possible oceanic and ionospheric effects. Best estimates of the geomagnetic response function Q(omega) for 0.2 to 2.0 cpd indicate an upper mantle conductivity of the order of 0.01 S/m.

Didwall, E. M.↗
DOE OSTI2026

Deep Neural Networks are Adaptive to Function Regularity and Data Distribution in Approximation and Estimation

Deep learning has exhibited remarkable results across diverse areas. To understand its success, substantial research has been directed towards its theoretical foundations. Nev- ertheless, the majority of these studies examine how well deep neural networks can model functions with uniform regularities. In this paper, we explore a different angle: how deep neural networks can adapt to varying degrees of smoothness in functions and nonuni- form data distributions across different locations and scales. More precisely, we focus on a broad class of functions defined by nonlinear tree-based approximation methods. This class encompasses a range of function types, such as functions with uniform regularities and discontinuous functions. We develop nonparametric approximation and estimation theories for this class using deep ReLU networks. Our results show that deep neural networks are adaptive to the nonuniform smoothness of functions and nonuniform data distributions at different locations and scales. We apply our results to several function classes, and derive the corresponding approximation and generalization errors. The validity of our results is demonstrated through numerical experiments.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2014

Discovery of a very large structure at z = 3.78

We report the discovery of a large-scale structure containing multiple protoclusters at z = 3.78 in the Boötes field. The spectroscopic discovery of five galaxies at z = 3.783 ± 0.002 lying within 1 Mpc of one another led us to undertake a deep narrow- and broadband imaging survey of the surrounding field. Within a comoving volume of 72 × 72 × 25 Mpc{sup 3}, we have identified 65 Lyα emitter (LAE) candidates at z = 3.795 ± 0.015, and four additional galaxies at z {sub spec} = 3.730, 3.753, 3.780, 3.835. The galaxy distribution within the field is highly non-uniform, exhibiting three large (≈3-5 ×) overdensities separated by 8-14 Mpc (physical) and possibly connected by filamentary structures traced by LAEs. The observed number of LAEs in the entire field is nearly twice the average expected in field environments based on estimates of the Lyα luminosity function at these redshifts. We estimate that by z = 0 the largest overdensity will grow into a cluster of mass ≈10{sup 15} M {sub ☉}; the two smaller overdensities will grow into clusters of mass (2-6) × 10{sup 14} M {sub ☉}. The highest concentration of galaxies is located at the southern end of the image, suggesting that the current imaging may not map the true extent of the large-scale structure. Finding three large protocluster candidates within a single 0.3 deg{sup 2} field is highly unusual; expectations from theory suggest that such alignments should occur less than 2% of the time. Searching for and characterizing such structures and accurately measuring their volume space density can therefore place constraints on the theory of structure formation. Such regions can also serve as laboratories for the study of galaxy formation in dense environments.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2013

Cone beam breast CT with a high pitch (75 μm), thick (500 μm) scintillator CMOS flat panel detector: Visibility of simulated microcalcifications

Purpose: To measure and investigate the improvement of microcalcification (MC) visibility in cone beam breast CT with a high pitch (75 μm), thick (500 μm) scintillator CMOS/CsI flat panel detector (Dexela 2923, Perkin Elmer).Methods: Aluminum wires and calcium carbonate grains of various sizes were embedded in a paraffin cylinder to simulate imaging of calcifications in a breast. Phantoms were imaged with a benchtop experimental cone beam CT system at various exposure levels. In addition to the Dexela detector, a high pitch (50 μm), thin (150 μm) scintillator CMOS/CsI flat panel detector (C7921CA-09, Hamamatsu Corporation, Hamamatsu City, Japan) and a widely used low pitch (194 μm), thick (600 μm) scintillator aSi/CsI flat panel detector (PaxScan 4030CB, Varian Medical Systems) were also used in scanning for comparison. The images were independently reviewed by six readers (imaging physicists). The MC visibility was quantified as the fraction of visible MCs and measured as a function of the estimated mean glandular dose (MGD) level for various MC sizes and detectors. The modulation transfer functions (MTFs) and detective quantum efficiencies (DQEs) were also measured and compared for the three detectors used.Results: The authors have demonstrated that the use of a high pitch (75 μm) CMOS detector coupled with a thick (500 μm) CsI scintillator helped make the smaller 150–160, 160–180, and 180–200 μm MC groups more visible at MGDs up to 10.8, 9, and 10.8 mGy, respectively. It also made the larger 200–212 and 212–224 μm MC groups more visible at MGDs up to 7.2 mGy. No performance improvement was observed for 224–250 μm or larger size groups. With the higher spatial resolution of the Dexela detector based system, the apparent dimensions and shapes of MCs were more accurately rendered. The results show that with the aforementioned detector, a 73% visibility could be achieved in imaging 160–180 μm MCs as compared to 28% visibility achieved by the low pitch (194 μm) aSi/CsI flat panel detector. The measurements confirm that the Hamamatsu detector has the highest MTF, followed by the Dexel detector, and then the Varian detector. However, the Dexela detector, with its thick (500 μm) CsI scintillator and low noise level, has the highest DQE at all frequencies, followed by the Varian detector, and then the Hamamatsu detector. The findings on the MC visibility correlated well with the differences in MTFs, noise power spectra, and DQEs measured for these three detectors.Conclusions: The authors have demonstrated that the use of the CMOS type Dexela detector with its high pitch (75 μm) and thick (500 μm) CsI scintillator could help improve the MC visibility. However, the improvement depended on the exposure level and the MC size. For imaging larger MCs or scanning at high exposure levels, there was little advantage in using the Dexela detector as compared to the aSi type Varian detector. These findings correlate well with the higher measured DQEs of the Dexela detector, especially at higher frequencies.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
NASA NTRSDate not supplied

Assessment of Sensor Footprint Size and Comparison of Commercial Smallsat Images

Science users of commercial satellite data build their studies on the properties of the satellite data they work with, pixel size being one of the determining factors. However, pixel size and nominal image footprint size can be different, impacting the scale of features discernable in the satellite images. Here, we assess geometric properties such as nominal image footprint size for Planet Labs' SuperDove series, MAXAR's WorldView series, and potentially BlackSky. Additionally, we assess temporal change in nominal footprint size for the SuperDove series. Nominal Image footprint size is assessed over the CalVal sites in Baotou, China; Shadnagar, India; and Big Spring, TX. Edge spread functions are constructed along the black/white transitions, from which the line spread functions are constructed and modulation transfer functions of the scene are estimated. Scene full width half maximum (FWHM), which represents sensor footprint size, is estimated from the line spread function. The average nominal footprint size is 3.3 pixels for SuperDove series, 1.5 pixels for WorldView-2, and 1.3 pixels for WorldView-3. The SuperDove series nominal footprint size improves with time in orbit, from an average of 3.4 pixels soon after launch to an average of 3.2 pixels one or more years after launch.

PlanetScope↗
NASA NTRS1989

On the signal-to-noise ratio in IUE high-dispersion spectra

An observational and data reduction technique for fixed pattern noise (FPN) and random noise (RN) in fully extracted IUE high-dispersion spectra is described in detail, along with actual empirical values of signal-to-noise ratio (S/N) achieved. A co-addition procedure, involving SWP and LWR cameras observations of the same spectrum at different positions in the image format, provides a basis to disentangle FPN from RN, allowing each average amplitude, within a given wavelength interval, to be estimated as a function of average flux number. Empirical curves, derived with the noise algorithm, make it possible to estimate the S/N in individual spectra at the wavelengths investigated. The average S/N at the continuum level in well-exposed stellar spectra varies from 10 to 20, for the orders analyzed, depending on position in the spectral format. The co-addition procedure yields an improvement in S/N by factors ranging from 2.3 to 2.9. Direct measurements of S/N in narrow, line-free wavelength intervals of individual and co-added spectra for weak-lined stars yield comparable, or in some cases somewhat higher, S/N values and improvement factors.

Leckrone, David S.↗