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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 1,459 records · Page 81
All sourcesNASA NTRSDOE OSTI
DOE OSTI2026

Analysis of Tank 38H (HTF-38-26-16, -17), Tank 43H (HTF 43-26-18, -19) and Tank 22 (HTF-22-26-20, -21) Samples for Support of the Enrichment Control and Corrosion Control Programs

Savannah River National Laboratory (SRNL) analyzed samples from Tank 38H, Tank 43H and Tank 22H to support the Enrichment Control Program (ECP) and Corrosion Control Program (CCP). The results indicate the concentrations of most soluble species in the Tank 38H surface sample are ~ 76% of the concentrations in the previous Tank 38H surface sample. The current Tank 38H subsurface sample is a clear solution with soluble species that are ~ 70% of the concentrations in the previous Tank 38H subsurface. Significant differences in the concentrations of major components between the current Tank 38H surface and subsurface samples indicate stratification of solution species between these two locations within Tank 38H.

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗
DOE OSTI2017

Progressive CPU Volume Rendering with Sample Accumulation

Here, we present a new method for progressive volume rendering by accumulating object-space samples over successively rendered frames. Existing methods for progressive refinement either use image space methods or average pixels over frames, which can blur features or integrate incorrectly with respect to depth. Our approach stores samples along each ray, accumulates new samples each frame into a buffer, and progressively interleaves and integrates these samples. Though this process requires additional memory, it ensures interactivity and is well suited for CPU architectures with large memory and cache. This approach also extends well to distributed rendering in cluster environments. We implement this technique in Intel’s open source OSPRay CPU ray tracing framework and demonstrate that it is particularly useful for rendering volumetric data with costly sampling functions.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2017

SPRUCE Geochemical Changes in Porewater from Northern Peatlands at Multiple Depths in Field Samples and over Time in Peat Incubations

This data set reports the results of the analysis of dissolved organic matter (DOM) in porewater samples collected from multiple depths in northern peatlands and during laboratory peat incubations to characterize the gain or loss of specific chemical moieties (e.g. CH2, H2, CH2O, etc.) that may be attributed to microbial degradation. During incubations, CO2 and CH4 concentrations and stable isotopes were determined by isotope ratio mass spectrometry. Porewater samples were collected from the S1 Bog (April 2015), a Sphagnum-dominated site at northern Minnesota peatland in the Marcell Experimental Forest, using permanently-installed piezometers, which provided profiles from the watertable surface to 200 cm depth. This is the site of the SPRUCE experiment. Porewater and peat samples were collected in July 2015 from an additional Sphagnum-dominated site within Stordalen Mire, Sweden, a palsa mire underlain by thawing permafrost, using perforated stainless steel tubes that were inserted into the peat to the desired depths (13 cm and 32 cm). Porewater samples were analyzed by Fourier transform ion cyclotron resonance mass spectrometry (FTICRMS) followed by Kendrick mass transform analysis. The Kendrick mass (i.e., Kendrick 1963) transform analysis identifies the gain or loss of specific chemical moieties (e.g. CH2, H2, CH2O, etc.) via mass differences, and was used to infer potential microbial degradation pathways by which compounds were consumed in these samples. Increasing depth would suggest more degradation of DOM with the greater length of time for peat accumulation and similarly, with increasing length of peat incubation. During incubations, CO2 and CH4 concentrations and stable isotopes were determined by isotope ratio mass spectrometry. There are four files provided in comma separated value (*.csv) format.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2021

Accessibility of Pores to Methane in New Albany Shale Samples of Varying Maturity Determined Using SANS and USANS

The accessibility of pores to methane has been investigated in Devonian New Albany Shale Formation early-mature (Ro = 0.50%) to post-mature (Ro = 1.40%) samples. A Marcellus Shale Formation sample was included to expand the maturation range to Ro 2.50%. These are organic matter-rich rocks with total organic carbon (TOC) values of 3.4 to 14.4% and porosity values of 2.19 to 6.88%. Contrast matching small-angle neutron scattering (SANS) and ultra-small angle neutron scattering (USANS) techniques were used to generate porosity-related data before and after pressure cycling under hydrostatic (in a vacuum and at 500 bar of deuterated methane) and uniaxial stress (0 to ca. 350 bar) conditions. Our results showed that the accessible porosity was small for the samples studied, ranging from zero to 2.9%. No correlation between the accessible porosity and TOC or mineralogical composition was revealed, and the most likely explanation for porosity variation was related to the thermal transformation of organic matter and hydrocarbon generation. Pressure caused improvements in accessible porosity for most samples, except the oil window sample (Ro = 0.84%). Our data show that densification of methane occurs in nanopores, generally starting at diameters smaller than 20 nm, and that the distribution of methane density is affected by pressure cycling.

03 NATURAL GAS↗
DOE OSTI2024

Reducing Sample Size While Improving Equity in Vaccine Clinical Trials: A Machine Learning-Based Recruitment Methodology with Application to Improving Trials of Hepatitis C Virus Vaccines in People Who Inject Drugs

Despite the availability of direct-acting antivirals that cure individuals infected with the hepatitis C virus (HCV), developing a vaccine is critically needed in achieving HCV elimination. HCV vaccine trials have been performed in populations with high incidence of new HCV infection such as people who inject drugs (PWID). Developing strategies of optimal recruitment of PWID for HCV vaccine trials could reduce sample size, follow-up costs and disparities in enrollment. We investigate trial recruitment informed by machine learning and evaluate a strategy for HCV vaccine trials termed PREDICTEE—Predictive Recruitment and Enrichment method balancing Demographics and Incidence for Clinical Trial Equity and Efficiency. PREDICTEE utilizes a survival analysis model applied to trial candidates, considering their demographic and injection characteristics to predict the candidate’s probability of HCV infection during the trial. The decision to recruit considers both the candidate’s predicted incidence and demographic characteristics such as age, sex, and race. We evaluated PREDICTEE using in silico methods, in which we first generated a synthetic candidate pool and their respective HCV infection events using HepCEP, a validated agent-based simulation model of HCV transmission among PWID in metropolitan Chicago. We then compared PREDICTEE to conventional recruitment of high-risk PWID who share drugs or injection equipment in terms of sample size and recruitment equity, with the latter measured by participation-to-prevalence ratio (PPR) across age, sex, and race. Comparing conventional recruitment to PREDICTEE found a reduction in sample size from 802 (95%: 642–1010) to 278 (95%: 264–294) with PREDICTEE, while also reducing screening requirements by 30%. Simultaneously, PPR increased from 0.475 (95%: 0.356–0.568) to 0.754 (95%: 0.685–0.834). Even when targeting a dissimilar maximally balanced population in which achieving recruitment equity would be more difficult, PREDICTEE is able to reduce sample size from 802 (95%: 642–1010) to 304 (95%: 288–322) while improving PPR to 0.807 (95%: 0.792–0.821). PREDICTEE presents a promising strategy for HCV clinical trial recruitment, achieving sample size reduction while improving recruitment equity.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2022

Multiple Mutations Associated with Emergent Variants Can Be Detected as Low-Frequency Mutations in Early SARS-CoV-2 Pandemic Clinical Samples

Genetic analysis of intra-host viral populations provides unique insight into pre-emergent mutations that may contribute to the genotype of future variants. Clinical samples positive for SARS-CoV-2 collected in California during the first months of the pandemic were sequenced to define the dynamics of mutation emergence as the virus became established in the state. Deep sequencing of 90 nasopharyngeal samples showed that many mutations associated with the establishment of SARS-CoV-2 globally were present at varying frequencies in a majority of the samples, even those collected as the virus was first detected in the US. A subset of mutations that emerged months later in consensus sequences were detected as subconsensus members of intra-host populations. Spike mutations P681H, H655Y, and V1104L were detected prior to emergence in variant genotypes, mutations were detected at multiple positions within the furin cleavage site, and pre-emergent mutations were identified in the nucleocapsid and the envelope genes. Because many of the samples had a very high depth of coverage, a bioinformatics pipeline, “Mappgene”, was established that uses both iVar and LoFreq variant calling to enable identification of very low-frequency variants. This enabled detection of a spike protein deletion present in many samples at low frequency and associated with a variant of concern.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2018

The MPLEx Protocol for Multi-omic Analyses of Soil Samples

Mass spectrometry (MS)-based integrated metaproteomic, metabolomic and lipidomic (multi-omic) studies are transforming our ability to understand and characterize microbial communities in environmental and biological systems. These measurements are even enabling enhanced analyses of complex soil microbial communities, which are the most complex microbial systems known to date. Multi-omic analyses, however, do have sample preparation challenges since separate extractions are typically needed for each omic study, thereby greatly amplifying the preparation time and amount of sample required. To address this limitation, a 3-in-1 method for simultaneous metabolite, protein, and lipid extraction (MPLEx) from the exact same soil sample was created by adapting a solvent-based approach. This MPLEx protocol has proven to be simple yet robust for many sample types and even when utilized for limited quantities of complex soil samples. The MPLEx method also greatly enabled the rapid multi-omic measurements needed to gain a better understanding of the members of each microbial community, while evaluating the changes taking place upon biological and environmental perturbations.

Environmental Molecular Sciences Laboratory↗
DOE OSTI2016

THE ALFALFA H α SURVEY. I. PROJECT DESCRIPTION AND THE LOCAL STAR FORMATION RATE DENSITY FROM THE FALL SAMPLE

The ALFALFA H α survey utilizes a large sample of H i-selected galaxies from the ALFALFA survey to study star formation (SF) in the local universe. ALFALFA H α contains 1555 galaxies with distances between ∼20 and ∼100 Mpc. We have obtained continuum-subtracted narrowband H α images and broadband R images for each galaxy, creating one of the largest homogeneous sets of H α images ever assembled. Our procedures were designed to minimize the uncertainties related to the calculation of the local SF rate density (SFRD). The galaxy sample we constructed is as close to volume-limited as possible, is a robust statistical sample, and spans a wide range of galaxy environments. In this paper, we discuss the properties of our Fall sample of 565 galaxies, our procedure for deriving individual galaxy SF rates, and our method for calculating the local SFRD. We present a preliminary value of log(SFRD[ M {sub ⊙} yr{sup −1} Mpc{sup −3}]) = −1.747 ± 0.018 (random) ±0.05 (systematic) based on the 565 galaxies in our Fall sub-sample. Compared to the weighted average of SFRD values around z ≈ 2, our local value indicates a drop in the global SFRD of a factor of 10.2 over that lookback time.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2020

The AMUSING++ Nearby Galaxy Compilation. I. Full Sample Characterization and Galactic-scale Outflow Selection

We present here AMUSING++: the largest compilation of nearby galaxies observed with the MUSE integral-field spectrograph so far. This collection consists of 635 galaxies from different MUSE projects covering the redshift interval 0.0002 < z < 0.1. The sample and its main properties are characterized and described here. It includes galaxies of almost all morphological types, with a good coverage in its color–magnitude diagram, within the stellar mass range between 10{sup 8} and 10{sup 12} M {sub ⊙}, and with properties resembling those of a diameter-selected sample. The AMUSING++ sample is, therefore, suitable for studying, with unprecendented detail, the properties of nearby galaxies at global and local scales, providing us with more than 50 million individual spectra. We use this compilation to investigate the presence of galactic outflows. We exploit the use of combined emission-line images to explore the shape of the different ionized components and the distribution along classical diagnostic diagrams to disentangle the different ionizing sources across the optical extension of each galaxy. We use the cross-correlation function to estimate the level of symmetry of the emission lines as an indication of the presence of shocks and/or active galactic nuclei. We uncovered a total of 54 outflows, comprising ∼8% of the sample. A large number of the discovered outflows correspond to those driven by active galactic nuclei (∼60%), suggesting some bias in the selection of our sample. No clear evidence was found that outflow host galaxies are highly star-forming, and outflows appear to be found within all galaxies around the star-formation sequence.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2017

The Statistics of Radio Astronomical Polarimetry: Disjoint, Superposed, and Composite Samples

A statistical framework is presented for the study of the orthogonally polarized modes of radio pulsar emission via the covariances between the Stokes parameters. To accommodate the typically heavy-tailed distributions of single-pulse radio flux density, the fourth-order joint cumulants of the electric field are used to describe the superposition of modes with arbitrary probability distributions. The framework is used to consider the distinction between superposed and disjoint modes, with particular attention to the effects of integration over finite samples. If the interval over which the polarization state is estimated is longer than the timescale for switching between two or more disjoint modes of emission, then the modes are unresolved by the instrument. The resulting composite sample mean exhibits properties that have been attributed to mode superposition, such as depolarization. Because the distinction between disjoint modes and a composite sample of unresolved disjoint modes depends on the temporal resolution of the observing instrumentation, the arguments in favor of superposed modes of pulsar emission are revisited, and observational evidence for disjoint modes is described. In principle, the four-dimensional covariance matrix that describes the distribution of sample mean Stokes parameters can be used to distinguish between disjoint modes, superposed modes, and a composite sample of unresolved disjoint modes. More comprehensive and conclusive interpretation of the covariance matrix requires more detailed consideration of various relevant phenomena, including temporally correlated subpulse modulation (e.g., jitter), statistical dependence between modes (e.g., covariant intensities and partial coherence), and multipath propagation effects (e.g., scintillation and scattering).

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2022

Extreme Variability Quasars in Their Various States. I. The Sample Selection and Composite SDSS Spectra

Extremely variable quasars (EVQs) are a population of sources showing large optical photometric variability revealed by time-domain surveys. The physical origin of such extreme variability is yet unclear. In this first paper of a series, we construct the largest-ever sample of 14,012 EVQs using more than 15 yr of photometric data from Sloan Digital Sky Survey (SDSS) and Pan-STARRS1. We divide the EVQs into five subsamples according to the relative brightness of each EVQ during SDSS spectroscopic observation compared with the mean brightness from photometric observations. Corresponding control samples of normal quasars are built with matched redshift, bolometric luminosity, and supermassive black hole mass. We obtain the composite SDSS spectra of EVQs in various states and their corresponding control samples. We find EVQs exhibit clearly bluer SDSS spectra during bright states and clearly redder spectra during dim states, consistent with the "bluer-when-brighter" trend widely seen in normal quasars. We further find that the line equivalent widths (EWs) of broad Mg II, C IV and [O III] (but not broad Hβ, which is yet puzzling) gradually decreases from the dim state to the bright state, similar to the so-called intrinsic Baldwin effect commonly seen in normal active galactic nuclei. In addition, EVQs have consistently larger line EWs compared with the control samples. We also see that EVQs show slight excess in the very broad line component compared with control samples. Possible explanations for the discoveries are discussed. Our findings support the hypothesis that EVQs are in the tail of a broad distribution of quasar properties but are not a distinct population.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2020

The effect of geographic sampling on evaluation of extreme precipitation in high-resolution climate models

Traditional approaches for comparing global climate models and observational data products typically fail to account for the geographic location of the underlying weather station data. For modern global high-resolution models with a horizontal resolution of tens of kilometers, this is an oversight since there are likely grid cells where the physical output of a climate model is compared with a statistically interpolated quantity instead of actual measurements of the climate system. In this paper, we quantify the impact of geographic sampling on the relative performance of high-resolution climate model representations of precipitation extremes in boreal winter (December–January–February) over the contiguous United States (CONUS), comparing model output from five early submissions to the HighResMIP subproject of the CMIP6 experiment. We find that properly accounting for the geographic sampling of weather stations can significantly change the assessment of model performance. Across the models considered, failing to account for sampling impacts the different metrics (extreme bias, spatial pattern correlation, and spatial variability) in different ways (both increasing and decreasing). We argue that the geographic sampling of weather stations should be accounted for in order to yield a more straightforward and appropriate comparison between models and observational data sets, particularly for high-resolution models with a horizontal resolution of tens of kilometers. While we focus on the CONUS in this paper, our results have important implications for other global land regions where the sampling problem is more severe.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2022

CondiDiag1.0: a flexible online diagnostic tool for conditional sampling and budget analysis in the E3SM atmosphere model (EAM)

Abstract. Numerical models used in weather and climate prediction take into account a comprehensive set of atmospheric processes (i.e., phenomena) such as the resolved and unresolved fluid dynamics, radiative transfer, cloud and aerosol life cycles, and mass or energy exchanges with the Earth's surface. In order to identify model deficiencies and improve predictive skills, it is important to obtain process-level understanding of the interactions between different processes. Conditional sampling and budget analysis are powerful tools for process-oriented model evaluation, but they often require tedious ad hoc coding and large amounts of instantaneous model output, resulting in inefficient use of human and computing resources. This paper presents an online diagnostic tool that addresses this challenge by monitoring model variables in a generic manner as they evolve within the time integration cycle. The tool is convenient to use. It allows users to select sampling conditions and specify monitored variables at run time. Both the evolving values of the model variables and their increments caused by different atmospheric processes can be monitored and archived. Online calculation of vertical integrals is also supported. Multiple sampling conditions can be monitored in a single simulation in combination with unconditional sampling. The paper explains in detail the design and implementation of the tool in the Energy Exascale Earth System Model (E3SM) version 1. The usage is demonstrated through three examples: a global budget analysis of dust aerosol mass concentration, a composite analysis of sea salt emission and its dependency on surface wind speed, and a conditionally sampled relative humidity budget. The tool is expected to be easily portable to closely related atmospheric models that use the same or similar data structures and time integration methods.

58 GEOSCIENCES↗
NASA NTRS1971

Preliminary description of Apollo 15 sample environments

Approximately 78 kg of lunar rock and soil samples were returned by Apollo 15. The rather complete documentation of the locations of nearly all of the samples allows for relating the samples to the specific and detailed geologic environments from which they were collected. This is especially important in an area as geologically complex as the Hadley-Apennine site. All of the material presented was derived from the pre-mission photogeologic maps, lunar surface television video tapes, air-to-ground transcript and crew debriefings, photographs taken on the lunar surface by the Apollo 15 crew, and information supplied by the Lunar Sample Preliminary Examination team from which the samples were categorized into groups consisting of, broadly, basalts and breccias. The breccias are considered loosely in terms of coherent breccias and soil breccias.

Swann, G. A.↗
NASA NTRS1972

Infrared and Raman spectroscopic studies of structural variations in minerals from Apollo 11, 12, 14 and 15 samples, volume 3

Infrared and Raman vibrational spectroscopic data, yielding direct information on molecular structure, were obtained for single grains ( 150 microns) of minerals, basalts, and glasses isolated from Apollo 11, 12, 14, and 15 rock and dust samples, and for grains in Apollo 14 polished butt samples. From the vibrational data, specification substitutions were determined for the predominant silicate minerals of plagioclase, pyroxene, and olivine. Unique spectral variations for grains of K-feldspar, orthopyroxene, pyroxenoid, and ilmenite were observed to exceed the ranges of terrestrial samples, and these variations may be correlatable with formation histories. Alpha-quartz was isolated as pure single grains, in granitic grains composited with sanidine, and in unique grains that were intimately mixed with varying amounts of glass. Accessory minerals of chromite and ulvospinel were isolated as pure grains and structurally characterized from their distinctive infrared spectra. Fundamental vibrations of the SiO4 tetrahedra in silicate minerals were used to classify bulk compositions in dust sieved fractions, basalt grains and glass particles, and to compare modal characteristics for maria, highland and rille samples. No hydrated minerals were found in any of the samples studied, indicating anhydrous formation conditions.

Estep, P. A.↗
NASA NTRS1971

Digital adaptive sampling.

Discussion of digital adaptive sampling, which is consistently better than fixed sampling in noise-free cases. Adaptive sampling is shown to be feasible and, it is considered, should be studied further. It should be noted that adaptive sampling is a class of variable rate sampling in which the variability depends on system signals. Digital rather than analog laws should be studied, because cases can arise in which the analog signals are not even available. An extremely important problem is implementation.

Breazeale, G. J.↗
NASA NTRS1972

Nondestructive determination of radionuclides in lunar samples using a large low-background gamma-ray spectrometer and a novel application of least-squares fitting

Dual-parameter gamma ray spectrometer systems with large volume Nal (Tl) crystals and low backgrounds were used for nondestructive determination of K, Th, U and cosmic ray produced radionuclides in 60 lunar samples. The total weight of samples measured with this system is 28 kg, and the individual sample weights varied from 2 to 2300 g. Samples from Apollo 11, 12, 14, 15 and 16 were measured. Operation of the spectrometers in the coincidence mode and analyzing single coincidence spectra permits the simultaneous determination of 8-10 radionuclides in each lunar sample.

Eldridge, J. S.↗
NASA NTRS1973

Automatic instrument for chemical processing to detect microorganism in biological samples by measuring light reactions

An automated apparatus is reported for sequentially assaying urine samples for the presence of bacterial adenosine triphosphate (ATP) that comprises a rotary table which carries a plurality of sample containing vials and automatically dispenses fluid reagents into the vials preparatory to injecting a light producing luciferase-luciferin mixture into the samples. The device automatically measures the light produced in each urine sample by a bioluminescence reaction of the free bacterial adenosine triphosphate with the luciferase-luciferin mixture. The light measured is proportional to the concentration of bacterial adenosine triphosphate which, in turn, is proportional to the number of bacteria present in the respective urine sample.

Kelbaugh, B. N.↗