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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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All sourcesNASA NTRSDOE OSTI
NASA NTRS2011

Complete Hard X-Ray Surveys, AGN Luminosity Functions and the X-Ray Background

AGN are believed to make up most of the Cosmic X-Ray Background (CXB) above a few keV, but this background cannot be fully resolved at energies less than 10 keV due to absorption. The Swift/BAT and INTEGRAL missions are performing the first complete hard x-ray surveys with minimal bias due to absorption. The most recent results for both missions will be presented. Although the fraction of the CXB resolved by these surveys is small, it is possible to derive unbiased number counts and luminosity functions for AGN in the local universe. The survey energy range from 15-150 keV contains the important reflection and cutoff spectral features dominate the shape of the AGN contribution to the CXB. Average spectral characteristics of survey detected AGN will be presented and compared with model distributions. The numbers of hard x-ray blazars detected in these surveys are finally sufficient to estimate this important component's contribution the cosmic background. Constraints on CXB models and their significance will be discussed.

Tueller, Jack↗
DOE OSTI2024

Physics-Based Machine Learning Methods for U-235 Forensics Signatures

Signatures of low-intensity U-235 sources have been recently studied by utilizing a variety of machine learning (ML) classifiers using features derived from gamma spectral measurements collectedunder structured campaigns. Several ML classifiers, such as ensemble of tress and classification trees, revealed misleadingly-optimistic training error due to over-fitting, and furthermore,their performance is not directly relatable to the physical properties due to their data-driven, opaque designs. We present a regression-based ML method that first estimates the inverse distanceto the source and then utilizes a threshold to infer its presence, by representing the background as a source located at an infinite distance. For the inverse distance estimation, we study the ensembleof trees and Gaussian process regression methods, and a hyper parameter auto-tuning and selection method that employs five regression estimators. These methods avoid the over-fittingobserved in several ML classifiers, while providing the classification error nearly comparable to them based on independent test data. Their error is directly related to estimates of the inversephysical distance to source, and the precision of error determines the seperability property that determines the false alarm and missed detection rates. The property of monotonic decrease of thesource strength with increasing detector distance combined with Poisson distribution of measurements is utilized to analytically validate these methods by deriving the generalization equations ofunderlying regression methods.

Rao, Nageswara↗
NASA NTRS2010

Non-Targeted Effects and the Dose Response for Heavy Ion Tumorigenesis

BACKGROUND: There is no human epidemiology data available to estimate the heavy ion cancer risks experienced by astronauts in space. Studies of tumor induction in mice are a necessary step to estimate risks to astronauts. Previous experimental data can be better utilized to model dose response for heavy ion tumorigenesis and plan future low dose studies. DOSE RESPONSE MODELS: The Harderian Gland data of Alpen et al.[1-3] was re-analyzed [4] using non-linear least square regression. The data set measured the induction of Harderian gland tumors in mice by high-energy protons, helium, neon, iron, niobium and lanthanum with LET s ranging from 0.4 to 950 keV/micron. We were able to strengthen the individual ion models by combining data for all ions into a model that relates both radiation dose and LET for the ion to tumor prevalence. We compared models based on Targeted Effects (TE) to one motivated by Non-targeted Effects (NTE) that included a bystander term that increased tumor induction at low doses non-linearly. When comparing fitted models to the experimental data, we considered the adjusted R2, the Akaike Information Criteria (AIC), and the Bayesian Information Criteria (BIC) to test for Goodness of fit.In the adjusted R2test, the model with the highest R2values provides a better fit to the available data. In the AIC and BIC tests, the model with the smaller values of the summary value provides the better fit. The non-linear NTE models fit the combined data better than the TE models that are linear at low doses. We evaluated the differences in the relative biological effectiveness (RBE) and found the NTE model provides a higher RBE at low dose compared to the TE model. POWER ANALYSIS: The final NTE model estimates were used to simulate example data to consider the design of new experiments to detect NTE at low dose for validation. Power and sample sizes were calculated for a variety of radiation qualities including some not considered in the Harderian Gland data set and with different background tumor incidences. We considered different experimental designs with varying number of doses and varying low doses dependant on the LET of the radiation. The optimal design to detect a NTE for an individual ion had 4 doses equally spaced below a maximal dose where bending due to cell sterilization was < 2%. For example at 100 keV/micron we would irradiate at 0.03 Gy, 0.065 Gy, 0.13 Gy, and 0.26 Gy and require 850 mice including a control dose for a sensitivity to detect NTE with 80% power. Sample sizes could be improved by combining ions similar to the methods used with the Harderian Gland data.

Chappelli, Lori J.↗
NASA NTRS2015

An Initial Assessment of the Surface Reference Technique Applied to Data from the Dual-Frequency Precipitation Radar (DPR) on the GPM Satellite

It has long been recognized that path-integrated attenuation (PIA) can be used to improve precipitation estimates from high-frequency weather radar data. One approach that provides an estimate of this quantity from airborne or spaceborne radar data is the surface reference technique (SRT), which uses measurements of the surface cross section in the presence and absence of precipitation. Measurements from the dual-frequency precipitation radar (DPR) on the Global Precipitation Measurement (GPM) satellite afford the first opportunity to test the method for spaceborne radar data at Ka band as well as for the Ku-band-Ka-band combination. The study begins by reviewing the basis of the single- and dual-frequency SRT. As the performance of the method is closely tied to the behavior of the normalized radar cross section (NRCS or sigma(0)) of the surface, the statistics of sigma(0) derived from DPR measurements are given as a function of incidence angle and frequency for ocean and land backgrounds over a 1-month period. Several independent estimates of the PIA, formed by means of different surface reference datasets, can be used to test the consistency of the method since, in the absence of error, the estimates should be identical. Along with theoretical considerations, the comparisons provide an initial assessment of the performance of the single- and dual-frequency SRT for the DPR. The study finds that the dual-frequency SRT can provide improvement in the accuracy of path attenuation estimates relative to the single-frequency method, particularly at Ku band.

space-borne weather radars↗
NASA NTRS2015

Airborne Lidar-Based Estimates of Tropical Forest Structure in Complex Terrain: Opportunities and Trade-Offs for REDD+

Background: Carbon stocks and fluxes in tropical forests remain large sources of uncertainty in the global carbon budget. Airborne lidar remote sensing is a powerful tool for estimating aboveground biomass, provided that lidar measurements penetrate dense forest vegetation to generate accurate estimates of surface topography and canopy heights. Tropical forest areas with complex topography present a challenge for lidar remote sensing. Results: We compared digital terrain models (DTM) derived from airborne lidar data from a mountainous region of the Atlantic Forest in Brazil to 35 ground control points measured with survey grade GNSS receivers. The terrain model generated from full-density (approx. 20 returns/sq m) data was highly accurate (mean signed error of 0.19 +/-0.97 m), while those derived from reduced-density datasets (8/sq m, 4/sq m, 2/sq m and 1/sq m) were increasingly less accurate. Canopy heights calculated from reduced-density lidar data declined as data density decreased due to the inability to accurately model the terrain surface. For lidar return densities below 4/sq m, the bias in height estimates translated into errors of 80-125 Mg/ha in predicted aboveground biomass. Conclusions: Given the growing emphasis on the use of airborne lidar for forest management, carbon monitoring, and conservation efforts, the results of this study highlight the importance of careful survey planning and consistent sampling for accurate quantification of aboveground biomass stocks and dynamics. Approaches that rely primarily on canopy height to estimate aboveground biomass are sensitive to DTM errors from variability in lidar sampling density.

Airborne lidar↗
NASA NTRSDate not supplied

The Relationship Between Two Methods for Estimating Uncertainties in Data Assimilation

This note examines the relationship between two apparently unrelated methods for estimating error statistics or uncertainties of relevance to data assimilation. The first method is due to (Desroziers et al., 2005, Q. J. R. Meteorol. Soc., 131, 3385–3396; referred to as DBCP hereafter) and relies on residual statistics readily available from data assimilation applications. The second method, the three- cornered hat (3CH) developed by Gray and Allan (1974, IEEE 28th Annual Symp. Freq. Control, 243–246), only recently applied to atmospheric sciences, uses three data sets and can derive estimates of relevant error uncertainties as well. The usefulness of both methods lies in them not requiring knowledge of the true value of the quantities at play. DBCP derives its results by relying explicitly on the constraints as- sociated with the data assimilation minimization problem; 3CH is general and its estimates hold as long as errors in the three data sets of choice are uncorrelated. Establishing the relationship between the methods requires applying the 3CH approach to the same observation, background, and analysis data sets used by DBCP. In this case, the same assumptions of DBCP on residual errors allow for cancellation of error cross–covariance terms in 3CH such that two of its corners derive identical estimates for observation and background error covariances as those of DBCP. The error cross–covariance terms associated with the third corner are shown to add up to twice the analysis error covariance so that the 3CH estimate for the third corner recovers the negative of the analysis error covariance. Illustrations of these findings are provided by deriving uncertainties for radio occultation bending angles.

Ricardo Todling↗
NASA NTRS2004

Rain, Snow, Hurricanes, and Blizzards: Remote Sensing of Cloud Particles

Hurricanes, blizzards and other weather events are important to understand not only for disaster preparation, but also to track the global energy balance and to improve weather and climate forecasts. For several decades, passive radiometers and active radars on aircraft and satellites have been employed to remotely sense rain rates and the properties of liquid particles. In the past few years the relationships between frozen particles and millimeter-wave observations have become understood well enough to estimate the properties of ice in clouds. This colloquium will start with a broad background of the use of remote sensing of precipitation and then focus on recent research in the estimation of frozen cloud properties, both for ice that will eventually melt into rain and for solid precipitation falling in northern climates. The electromagnetic absorption and scattering properties of liquid rain and frozen particles will be explained. Retrieved cloud particle contents and size distributions for Hurricane Erin (2001 ) and the March 5-6, 2001 New England regional blizzard will be discussed. Future directions and challenges of this work will also be presented.

Gail Skofronick-Jackson↗
NASA NTRS1999

Carrier Estimation Using Classic Spectral Estimation Techniques for the Proposed Demand Assignment Multiple Access Service

In any satellite communication, the Doppler shift associated with the satellite's position and velocity must be calculated in order to determine the carrier frequency. If the satellite state vector is unknown then some estimate must be formed of the Doppler-shifted carrier frequency. One elementary technique is to examine the signal spectrum and base the estimate on the dominant spectral component. If, however, the carrier is spread (as in most satellite communications) this technique may fail unless the chip rate-to-data rate ratio (processing gain) associated with the carrier is small. In this case, there may be enough spectral energy to allow peak detection against a noise background. In this thesis, we present a method to estimate the frequency (without knowledge of the Doppler shift) of a spread-spectrum carrier assuming a small processing gain and binary-phase shift keying (BPSK) modulation. Our method relies on an averaged discrete Fourier transform along with peak detection on spectral match filtered data. We provide theory and simulation results indicating the accuracy of this method. In addition, we will describe an all-digital hardware design based around a Motorola DSP56303 and high-speed A/D which implements this technique in real-time. The hardware design is to be used in NMSU's implementation of NASA's demand assignment, multiple access (DAMA) service.

Scaife, Bradley James↗
DOE OSTI2024

Physics-Based Machine Learning Methods for U-235 Forensics Signatures

Signatures of low-intensity U-235 sources have been recently studied by utilizing a variety of machine learning (ML) classifiers using features derived from gamma spectral measurements collected under structured campaigns. Several ML classifiers, such as ensemble of tress and classification trees, revealed misleadingly-optimistic training error due to over-fitting, and furthermore, their performance is not directly relatable to the physical properties due to their data-driven, opaque designs. We present a regression-based ML method that first estimates the inverse distance to the source and then utilizes a threshold to infer its presence, by representing the background as a source located at an infinite distance. For the inverse distance estimation, we study the ensemble of trees and Gaussian process regression methods, and a hyper parameter auto-tuning and selection method that employs five regression estimators. These methods avoid the over-fitting observed in several ML classifiers, while providing the classification error nearly comparable to them based on independent test data. Their error is directly related to estimates of the inverse physical distance to source, and the precision of error determines the seperability property that determines the false alarm and missed detection rates. The property of monotonic decrease of the source strength with increasing detector distance combined with Poisson distribution of measurements is utilized to analytically validate these methods by deriving the generalization equations of underlying regression methods.

Rao, Nageswara↗
NASA NTRS1994

The Use of High Spectral Resolution Bands for Estimating Absorbed Photosynthetically Active Radiation (A Par)

Most remote sensing estimations of vegetation variables such as Leaf Area Index (LAI), Absorbed Photosynthetically Active Radiation (APAR), and phytomass are made using broad band sensors with a bandwidth of approximately 100 nm. However, high resolution spectrometers are available and have not been fully exploited for the purpose of improving estimates of vegetation variables. A study directed to investigate the use of high spectral resolution spectroscopy for remote sensing estimates of APAR in vegetation canopies in the presence of nonphotosynthetic background materials such as soil and leaf litter is presented. A high spectral resolution method defined as the Chlorophyll Absorption Ratio Index (CARI) was developed for minimizing the effects of nonphotosynthetic materials in the remote estimates of APAR. CARI utilizes three bands at 550, 670, and 700 nm with bandwidth of 10 nm. Simulated canopy reflectance of a range of LAI were generated with the SAIL model using measurements of 42 different soil types as canopy background. CARI obtained from the simulated canopy reflectance was compared with the broad band vegetation indices (Normalized Difference Vegetation Index (NDVI), Soil Adjusted Vegetation Index (SAVI), and Simple Ratio (SR)). CARI reduced the effect of nonphotosynthetic background materials in the assessment of vegetation canopy APAR more effectively than broad band vegetation indices.

Kim, Moon S.↗
NASA NTRS1972

Electron microprobe analysis program for biological specimens: BIOMAP

BIOMAP is a Univac 1108 compatible program which facilitates the electron probe microanalysis of biological specimens. Input data are X-ray intensity data from biological samples, the X-ray intensity and composition data from a standard sample and the electron probe operating parameters. Outputs are estimates of the weight percentages of the analyzed elements, the distribution of these estimates for sets of red blood cells and the probabilities for correlation between elemental concentrations. An optional feature statistically estimates the X-ray intensity and residual background of a principal standard relative to a series of standards.

Edwards, B. F.↗
NASA NTRS1983

Estimating time and time-lag in time-of-flight velocimetry

Estimating time and time-lag in time-of-flight velocimeters is investigated. Statistics of a filtered Poisson point process is given. A Maximum Likelihood Estimator is compared with suboptimum estimators in terms of robustness. For a dominating background combined spatial and temporal processing can improve the robustness compared with purely temporal processing. Schemes for the spatial filters are given.

Lading, L.↗
NASA NTRS1988

Internal erosion rates of a 10-kW xenon ion thruster

A 30 cm diameter divergent magnetic field ion thruster, developed for mercury operation at 2.7 kW, was modified and operated with xenon propellant at a power level of 10 kW for 567 h to evaluate thruster performance and lifetime. The major differences between this thruster and its baseline configuration were elimination of the three mercury vaporizers, use of a main discharge cathode with a larger orifice, reduction in discharge baffle diameter, and use of an ion accelerating system with larger acceleration grid holes. Grid thickness measurement uncertainties, combined with estimates of the effects of reactive residual facility background gases gave a minimum screen grid lifetime of 7000 h. Discharge cathode orifice erosion rates were measured with three different cathodes with different initial orifice diameters. Three potential problems were identified during the wear test: the upstream side of the discharge baffle eroded at an unacceptable rate; two of the main cathode tubes experienced oxidation, deformation, and failure; and the accelerator grid impingement current was more than an order of magnitude higher than that of the baseline mercury thruster. The charge exchange ion erosion was not quantified in this test. There were no measurable changes in the accelerator grid thickness or the accelerator grid hole diameters.

Rawlin, Vincent K.↗
NASA NTRS1988

Internal erosion rates of a 10-kW xenon ion thruster

A 30 cm diameter divergent magnetic field ion thruster, developed for mercury operation at 2.7 kW, was modified and operated with xenon propellant at a power level of 10 kW for 567 h to evaluate thruster performance and lifetime. The major differences between this thruster and its baseline configuration were elimination of the three mercury vaporizers, use of a main discharge cathode with a larger orifice, reduction in discharge baffle diameter, and use of an ion accelerating system with larger acceleration grid holes. Grid thickness measurement uncertainties, combined with estimates of the effects of reactive residual facility background gases gave a minimum screen grid lifetime of 7000 h. Discharge cathode orifice erosion rates were measured with three different cathodes with different initial orifice diameters. Three potential problems were identified during the wear test: the upstream side of the discharge baffle eroded at an unacceptable rate; two of the main cathode tubes experienced oxidation, deformation, and failure; and the accelerator grid impingement current was more than an order of magnitude higher than that of the baseline mercury thruster. The charge exchange ion eroison was not quantified in this test. There were no measurable changes in the accelerator grid thickness or the accelerator grid hole diameters.

Rawlin, Vincent K.↗
NASA NTRS2010

Ten-Year Climatology of Summertime Diurnal Rainfall Rate Over the Conterminous U.S.

Diurnal cycles of summertime rainfall rates are examined over the conterminous United States, using radar-gauge assimilated hourly rainfall data. As in earlier studies, rainfall diurnal composites show a well-defined region of rainfall propagation over the Great Plains and an afternoon maximum area over the south and eastern portion of the United States. Zonal phase speeds of rainfall in three different small domains are estimated, and rainfall propagation speeds are compared with background zonal wind speeds. Unique rainfall propagation speeds in three different regions can be explained by the evolution of latent-heat theory linked to the convective available potential energy, than by gust-front induced or gravity wave propagation mechanisms.

Matsui, Toshihisa↗
NASA NTRS2011

Measurement of Separate Cosmic-Ray Electron and Positron Spectra with the Fermi Large Area Telescope

We measured separate cosmic-ray electron and positron spectra with the Fermi Large Area Telescope. Because the instrument does not have an onboard magnet, we distinguish the two species by exploiting the Earth's shadow, which is offset in opposite directions for opposite charges due to the Earth's magnetic field. We estimate and subtract the cosmic-ray proton background using two different methods that produce consistent results. We report the electron-only spectrum, the positron-only spectrum, and the positron fraction between 20 GeV and 200 GeV, We confirm that the fraction rises with energy in the 20-100 GeV range and determine for the first time that it continues to rise between 100 and 200 GeV,

Ackermann, M.↗
NASA NTRS2012

Measurement of Separate Cosmic-Ray Electron and Positron Spectra with the Fermi Large Area Telescope

We measured separate cosmic-ray electron and positron spectra with the Fermi Large Area Telescope. Because the instrument does not have an onboard magnet, we distinguish the two species by exploiting Earth's shadow, which, is offset in opposite directions for opposite charges due to Earth's magnetic field. We estimate and subtract the cosmic-ray proton background using two different methods that produce consistent results. We report the electron-only spectrum, the positron-only spectrum, and the positron fraction between 20 and 200 Ge V. We confirm that the fraction rises with energy in the 20-100 Ge V range. The three new spectral points between 100 and 200 GeV are consistent with a fraction that is continuing to rise with energy.

Ferrara, E. C.↗
NASA NTRS2021

Applications of Dynamic Land Surface Information for Passive Microwave Precipitation Retrieval

Accurate, physically based precipitation retrieval over global land surfaces is an important goal of the NASA/JAXA Global Precipitation Measurement Mission (GPM). This is a difficult problem for the passive microwave constellation, as the signal over radiometrically warm land surfaces in the microwave frequencies means that the measurements used are indirect and typically require inferring some type of relationship between an observed scattering signal and precipitation at the surface. GPM, with collocated radiometer and dual-frequency radar, is an excellent tool for tackling this problem and improving global retrievals. In the years following the launch of the GPM Core Observatory satellite, physically based passive microwave retrieval of precipitation over land continues to be challenging. Validation efforts suggest that the operational GPM passive microwave algorithm, the Goddard profiling algorithm (GPROF), tends to overestimate precipitation at the low (<5 mm h−1) end of the distribution over land. In this work, retrieval sensitivities to dynamic surface conditions are explored through enhancement of the algorithm with dynamic, retrieved information from a GPM-derived optimal estimation scheme. The retrieved parameters describing surface and background characteristics replace current static or ancillary GPROF information including emissivity, water vapor, and snow cover. Results show that adding this information decreases probability of false detection by 50% and, most importantly, the enhancements with retrieved parameters move the retrieval away from dependence on ancillary datasets and lead to improved physical consistency.

Sarah Ringerud↗