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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 1,639 records · Page 91
All sourcesNASA NTRSDOE OSTI
DOE OSTI2015

TU-AB-BRA-04: Quantitative Radiomics: Sensitivity of PET Textural Features to Image Acquisition and Reconstruction Parameters Implies the Need for Standards

Purpose: Despite increased use of heterogeneity metrics for PET imaging, standards for metrics such as textural features have yet to be developed. We evaluated the quantitative variability caused by image acquisition and reconstruction parameters on PET textural features. Methods: PET images of the NEMA IQ phantom were simulated with realistic image acquisition noise. 35 features based on intensity histograms (IH), co-occurrence matrices (COM), neighborhood-difference matrices (NDM), and zone-size matrices (ZSM) were evaluated within lesions (13, 17, 22, 28, 33 mm diameter). Variability in metrics across 50 independent images was evaluated as percent difference from mean for three phantom girths (850, 1030, 1200 mm) and two OSEM reconstructions (2 iterations, 28 subsets, 5 mm FWHM filtration vs 6 iterations, 28 subsets, 8.6 mm FWHM filtration). Also, patient sample size to detect a clinical effect of 30% with Bonferroni-corrected α=0.001 and 95% power was estimated. Results: As a class, NDM features demonstrated greatest sensitivity in means (5–50% difference for medium girth and reconstruction comparisons and 10–100% for large girth comparisons). Some IH features (standard deviation, energy, entropy) had variability below 10% for all sensitivity studies, while others (kurtosis, skewness) had variability above 30%. COM and ZSM features had complex sensitivities; correlation, energy, entropy (COM) and zone percentage, short-zone emphasis, zone-size non-uniformity (ZSM) had variability less than 5% while other metrics had differences up to 30%. Trends were similar for sample size estimation; for example, coarseness, contrast, and strength required 12, 38, and 52 patients to detect a 30% effect for the small girth case but 38, 88, and 128 patients in the large girth case. Conclusion: The sensitivity of PET textural features to image acquisition and reconstruction parameters is large and feature-dependent. Standards are needed to ensure that prospective trials which incorporate textural features are properly designed to detect clinical endpoints. Supported by NIH grants R01 CA169072, U01 CA148131, NCI Contract (SAIC-Frederick) 24XS036-004, and a research contract from GE Healthcare.

60 APPLIED LIFE SCIENCES↗
NASA NTRS1995

Validation of satellite retrievals of cloud microsphysics and liquid water path using observations from FIRE

Cloud effective radii (r(sub e)) and cloud liquid water path (LWP) are derived from ISCCP spatially sampled satellite data and validated with ground-based pyranometer and microwave radiometer measurements taken on San Nicolas Island during the 1987 FIRE IFO. Values of r(sub e) derived from the ISCCP data are also compared to values retrieved by a hybrid method that uses the combination of LWP derived from microwave measurement and optical thickness derived from GOES data. The results show that there is significant variability in cloud properties over a 100 km x 80 km area and that the values at San Nicolas Island are not necessarily representative of the surrounding cloud field. On the other hand, even though there were large spatial variations in optical depth, the r(sub e) values remained relatively constant (with sigma less than or equal to 2-3 microns in most cases) in the marine stratocumulus. Furthermore, values of r(sub e) derived from the upper portion of the cloud generally are representative of the entire stratiform cloud. When LWP values are less than 100 g m(exp -2), then LWP values derived from ISCCP data agree well with those values estimated from ground-based microwave measurements. In most cases LWP differences were less than 20 g m(exp -2). However, when LWP values become large (e.g., greater than or equal to 200 g m(exp -2)), then relative differences may be as large as 50%- 100%. There are two reasons for this discrepancy in the large LWP clouds: (1) larger vertical inhomogeneities in precipitating clouds and (2) sampling errors on days of high spatial variability of cloud optical thicknesses. Variations of r(sub e) in stratiform clouds may indicate drizzle: clouds with droplet sizes larger than 15 microns appear to be associated with drizzling, while those less than 10 microns are indicative of nonprecipitating clouds. Differences in r(sub e) values between the GOES and ISCCP datasets are found to be 0.16 +/- 0.98 micron.

Rossow, W.↗
DOE OSTI2026

Data and scripts associated with “Moisture content modulates DOM thermodynamic regulation of oxygen consumption in drying streambed sediments”

This data package is associated with the publication “Moisture content modulates DOM thermodynamic regulation of oxygen consumption in drying streambed sediments” published in Scientific Reports (Garayburu-Caruso et al., 2026). The package contains processed data products and scripts used to quantify how drying and re-inundation of riverbed sediments influence dissolved organic matter (DOM) thermodynamic properties and their relationship with sediment oxygen (O₂) consumption across 33 stream sites in the contiguous United States. The data package contains DOM thermodynamic metrics (e.g., Gibbs free energy of carbon oxidation and thermodynamic efficiency), and O₂ consumption along with watershed-scale climate and land-cover metrics used as explanatory variables in the analyses. Underlying unprocessed and processed ultrahigh-resolution mass spectrometry data, oxygen consumption rates from laboratory moisture-manipulation experiments, within-sample environmental properties, sediment moisture content and contextual field measurements are archived separately at https://data.ess-dive.lbl.gov/datasets/doi:10.15485/2428003 (Laan et al., 2024) and https://data.ess-dive.lbl.gov/datasets/doi:10.15485/1923689 (Forbes et al.,2023). A preliminary version of this data package was published in February 2026 at the time of manuscript submission. It was updated in June 2026, at the time of manuscript acceptance, to include the finalized data and additional metadata (readme, data dictionary, and file level metadata). For details on how to navigate data packages generated by this project, see https://data.ess-dive.lbl.gov/portals/PNNLRiverCorridorSFA/About. In addition to a readme, this data package also includes a file-level metadata (FLMD) file that describes each file and a data dictionary (DD) that describes all column/row headers and variable definitions. At the top level, the data package is organized into five main folders: (1) Data, (2)Figures, (3) Map, (4) GAM_Reulsts, and (5) src. The Data folder contains analysis-ready tabular files with oxygen consumption rates, DOM thermodynamic properties by site and treatment, site-level environmental variables, watershed-scale metrics, and other derived variables referenced in the manuscript. The Figures folder contains static image files associated with the main text and supplemental figures, while the Map folder includes spatial data and map-layer files used to create the sampling-location map. The GAM results folder contains the results for each of the general additive model (GAM).The src folder contains R scripts used to perform data processing, statistical analyses (including clustering, generalized additive models, and threshold analysis), and figure generation. This data package is associated with a GitHub repository found at https://github.com/WHONDRS-Hub/ECA_DOM_Thermodynamics.

Dissolved organic matter↗
DOE OSTI2022

High manganese redox variability and manganate predominance in temperate soil profiles as determined by X-ray absorption spectroscopy

Manganese speciation is a key to understanding the fate of contaminants, nutrients, and organic matter in soils. To date, quantification of Mn species in bulk soils has been performed mainly by sequential extraction methods and rarely supported by spectroscopic analysis. In order to obtain quantitative information on the Mn species inventory of soils, we investigated 46 soil horizons (<2-mm fraction, 45.1–2,280 mg/kg Mn) of nine typical Central European soils (Cambisols, Chernozems, Luvisols, Podzol, Stagnosol) by chemical Mn analyses and Mn K-edge X-ray absorption spectroscopy, and related speciation results to major soil properties. Amounts of Mn 2+ , Mn 3+ , and Mn 4+ and the average oxidation state of Mn were evaluated by linear combination fitting (LCF) of X-ray absorption near edge structure (XANES) spectra. Additionally, we used extended X-ray absorption fine structure (EXAFS) spectroscopy to identify and quantify major Mn species. For this, EXAFS spectra of 20 organic and mineral soil samples from five soils (Cambisols, Chernozem, Luvisol) were analyzed by LCF and shell fitting. XANES analyses revealed a high Mn redox variability in organic surface layers, with Mn 2+ being most abundant (≤100%, $\overline{x}$ = 54%), followed by Mn 3+ (≤80%, $\overline{x}$ = 32%) and Mn 4+ (≤55%, $\overline{x}$ = 14%). Mineral soil horizons contained significantly less Mn 2+ (≤56%, $\overline{x}$ = 23%), about equal quantities of Mn 3+ (≤68%, $\overline{x}$ = 31%), and were enriched in Mn 4+ (≤89%, $\overline{x}$ = 46%). EXAFS analyses implied the presence of six major Mn species groups: manganates, organically complexed Mn, Mn(III) oxyhydroxides, silicate-bound Mn, Mn oxides without tunnel- or layer structure, and physisorbed Mn. In litter horizons, Mn was mainly present in organic complexes (58–91%, $\overline{x}$ = 78%) and as physisorbed Mn (≤15%), but individual horizons also comprised manganates, Mn(III) oxyhydroxides, and silicate-bound Mn. Manganates, likely mixtures of phyllomanganates with hexagonal layer symmetry and tectomanganates, dominated in all mineral soil horizons (37–94%, $\overline{x}$ = 67%). Correlation analysis showed that manganates dissolve completely during dithionite-citrate and acid ammonium oxalate extractions, and suggested that Mn 4+ -rich manganates preferentially form under less acidic soil conditions, partly by oxidation of organically complexed Mn(II), and that they are enriched in the soil clay fraction. Mineral soil horizons also contained minor quantities of organically complexed Mn (≤39%, $\overline{x}$ = 11%), silicate-bound Mn (≤30%, $\overline{x}$ = 8%), Mn(III) oxyhydroxides (≤37%, $\overline{x}$ = 7%), Mn oxides without tunnel- or layer structure (≤18%, $\overline{x}$ = 5%), and physisorbed Mn (≤14%, $\overline{x}$ <1%). The detection of Mn(III) oxyhydroxides such as feitknechtite (β-MnOOH) or groutite (α-MnOOH) as well as the spinel hausmannite (Mn 3 O 4 ) in acidic soils is remarkable, since their formation is normally linked to neutral or alkaline pH conditions. Minor contributions of silicate-bound Mn indicate the release of Mn from primary minerals already at early stages of soil formation, and low concentrations of physisorbed Mn suggest that exchangeable Mn is rapidly converted into manganates in oxic soils. In conclusion, the predominance of manganates in mineral soils has far-reaching implications for the functioning of soils and biogeochemical element cycles, as these minerals play an important role in metal binding, plant nutrition, and redox-related processes.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2023

The role of oak species in long-term soil P loss in a humid river bottomland

There is a gap in our understanding of if and how bottomland forest type will affect long-term nutrient cycling and loss. This study aims to determine how different forests affect soil hydrologic variability and whole-soil P loss in a humid-subtropical setting. Here, we used replicate-sampling and measured soil physical, chemical, and mineralogical properties at 12 sites in two forest ecosystems, post oak (Quercus stellata) and cherry bark oak (Quercus pagoda) in Clarks River National Wildlife Refuge in Western Kentucky. We hypothesize that wetting–drying events in redox soils of forested bottomlands can cause positive feedback in whole-soil P loss. Trees with greater P demand (e.g., post oak) take up more water creating more frequent and pronounced episodes in swelling and shrinking of expandable clays. Repeated swelling and shrinking of clays occlude the surface of Fe-Mn oxides from further adsorption of P in acidic soil. This can lead to greater loss or plant uptake of available P. Our results show (i) a significant difference in mean whole-soil P loss between the oak species with more loss in soils underlying the post oak forest, and (ii) a difference in the total P found in the sap- and heartwood of the two oak species. Soil analysis reveals that the clay mineralogy of the post and cherry bark oak sites are similar, and thus, may only play a minor role in governing the whole-soil P loss difference. However, the leaf data analysis suggests that the post oak site could be P and nitrogen-limited, while the cherry bark is only nitrogen limited. Our study shows that differences in the oak forest ecosystem may affect the long-term balance in water and nutrient uptake and may alter the redistribution of nutrients in the canopy and the underlying soils.

58 GEOSCIENCES↗
DOE OSTI2015

KSwAGS: A Swift X-ray and UV survey of the Kepler field. I

We introduce the first phase of the Kepler–Swift Active Galaxies and Stars survey (KSwAGS), a simultaneous X-ray and UV survey of ∼6 square degrees of the Kepler field using the Swift X-ray telescope (XRT) and UV/Optical Telescope. We detect 93 unique X-ray sources with signal-to-noise ratio ⩾ 3 with the XRT, of which 60 have UV counterparts. We use the Kepler Input Catalog (KIC) to obtain the optical counterparts of these sources, and construct the f{sub X}/f{sub V} ratio as a first approximation of the classification of the source. The survey produces a mixture of stellar sources, extragalactic sources, and sources which we are not able to classify with certainty. We have obtained optical spectra for thirty of these targets, and are conducting an ongoing observing campaign to fully identify the sample. For sources classified as stellar or active galactic nuclei (AGNs) with certainty, we construct spectral energy distributions (SEDs) using the 2MASS, UBV, and GALEX data supplied for their optical counterparts by the KIC, and show that the SEDs differ qualitatively between the source types, and so can offer a method of classification in absence of a spectrum. Future papers in this series will analyze the timing properties of the stars and AGN in our sample separately. Our survey provides the first X-ray and UV data for a number of known variable stellar sources, as well as a large number of new X-ray detections in this well-studied portion of the sky. The KSwAGS survey is currently ongoing in the K2 ecliptic plane fields.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2026

The biogeography of soil and airborne fungi in the Southwestern USA in relation to climate and vegetation

To assess how fungal dispersal might respond to climate change, we examined how climate and geography influence the regional distribution of fungi in soil and air. Specifically, we hypothesized that neighboring fungal communities should be more similar than distant communities (i.e. spatially autocorrelated) and that fungal dispersal should be more limited in soil than in air. We collected soil and air samples from 60 sites across five states in the Southwestern USA. Then, we sequenced the ITS2 region to identify fungal taxa in each sample. Next, we used distance-based redundancy analysis to partition variation in fungal community composition between climate variables and spatial structure. Fungi were indeed spatially autocorrelated. Moreover, precipitation, maximum vapor pressure deficit, and soil moisture were significantly related to fungal community composition in soils. In comparison, only precipitation was significantly related to community composition in the air. After accounting for climate, the strength of spatial autocorrelation did not differ significantly in soilborne versus airborne fungi. Dispersal limitation was evident in soilborne fungi at short distances (<100 km) and was not observed at any distance in airborne fungi. Altogether, climate may influence which fungal taxa are present in soil and air, and fungi could feasibly wind disperse over regional scales.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2020

Asteroseismic modelling of solar-type stars: a deeper look at the treatment of initial helium abundance

ABSTRACT Detailed understanding of stellar physics is essential towards a robust determination of stellar properties (e.g. radius, mass, and age). Among the vital input physics used in the modelling of solar-type stars which remain poorly constrained, is the initial helium abundance. To this end, when constructing stellar model grids, the initial helium abundance is estimated either (i) by using the semi-empirical helium-to-heavy element enrichment ratio, (ΔY/ΔZ), anchored to the standard big bang nucleosynthesis value, or (ii) by setting the initial helium abundance as a free variable. Adopting 35 low-mass, solar-type stars with multiyear Kepler photometry from the asteroseismic ‘LEGACY’ sample, we explore the systematic uncertainties on the inferred stellar parameters (i.e. radius, mass, and age) arising from the treatment of the initial helium abundance in stellar model grids. The stellar masses and radii derived from grids with free initial helium abundance are lower compared to those from grids based on a fixed ΔY/ΔZ ratio. We find the systematic uncertainties on mean density, radius, mass, and age arising from grids which employ a fixed value of ΔY/ΔZ and those with free initial helium abundance to be ∼ 0.9 per cent, ∼ 2 per cent, ∼ 5 per cent, and ∼ 29 per cent, respectively. We report that the systematic uncertainties on the inferred masses and radii arising from the treatment of initial helium abundance in stellar grids lie within the expected accuracy limits of ESA’s PLATO, although this is not the case for the age.

Nsamba, Benard↗
DOE OSTI2018

Using refractive lenses to provide a variable spot size for Kirkpatrick–Baez mirrors

For many X-ray microprobe experiments it is desirable to be able to vary the beam size: using large beams for survey scans and a small beam for the final measurements. Beryllium refractive lenses were found to be a simple and controllable method for enlarging the focus in a Kirkpatrick–Baez-based microprobe. They can provide variable spot size, can be quickly inserted or removed and do not move the beam center on the sample.

47 OTHER INSTRUMENTATION↗
DOE OSTI2016

WE-H-BRC-06: A Unified Machine-Learning Based Probabilistic Model for Automated Anomaly Detection in the Treatment Plan Data

Purpose: The purpose of this work was to investigate the ability of a machine-learning based probabilistic approach to detect radiotherapy treatment plan anomalies given initial disease classes information. Methods In total we obtained 1112 unique treatment plans with five plan parameters and disease information from a Mosaiq treatment management system database for use in the study. The plan parameters include prescription dose, fractions, fields, modality and techniques. The disease information includes disease site, and T, M and N disease stages. A Bayesian network method was employed to model the probabilistic relationships between tumor disease information, plan parameters and an anomaly flag. A Bayesian learning method with Dirichlet prior was useed to learn the joint probabilities between dependent variables in error-free plan data and data with artificially induced anomalies. In the study, we randomly sampled data with anomaly in a specified anomaly space.We tested the approach with three groups of plan anomalies – improper concurrence of values of all five plan parameters and values of any two out of five parameters, and all single plan parameter value anomalies. Totally, 16 types of plan anomalies were covered by the study. For each type, we trained an individual Bayesian network. Results: We found that the true positive rate (recall) and positive predictive value (precision) to detect concurrence anomalies of five plan parameters in new patient cases were 94.45±0.26% and 93.76±0.39% respectively. To detect other 15 types of plan anomalies, the average recall and precision were 93.61±2.57% and 93.78±3.54% respectively. The computation time to detect the plan anomaly of each type in a new plan is ∼0.08 seconds. Conclusion: The proposed method for treatment plan anomaly detection was found effective in the initial tests. The results suggest that this type of models could be applied to develop plan anomaly detection tools to assist manual and automated plan checks. The senior author received research grants from ViewRay Inc. and Varian Medical System.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2025

Organic Matter Composition in June 2023 and September 2023 Across the McKenzie Sub-Basin Impacted by the 2020 Holiday Farm Fire

This dataset represents results from a field study aiming to understand the variability in post-fire responses of dissolved organic matter and determine drivers of post-fire responses. Samples were collected at 58 sites within the McKenzie River Watershed (Oregon, USA) that were upstream, within, and downstream of the Holiday Farm Fire burn perimeter. The samples were collected in June 2023 and September 2023 during storm events, approximately 3 years post-fire. Samples were characterized for benezenepolycarboxylic acids (BPCA) and ultra-high resolution mass spectrometry. Dissolved organic carbon and optics (absorbance and fluorescence) data can be found in a separate data packages (https://ir.library.oregonstate.edu/concern/datasets/zc77sz60m, https://ir.library.oregonstate.edu/concern/datasets/mc87q034m). Related data from a subset of sites from 2020-2022 can be found at https://data.ess-dive.lbl.gov/datasets/doi:10.15485/1869708 and https://data.ess-dive.lbl.gov/datasets/doi:10.15485/2478546. For details on how to navigate data packages generated by this project, see https://data.ess-dive.lbl.gov/portals/PNNLRiverCorridorSFA/About. This dataset contains (1) file-level metadata; (2) data dictionary; (3) data package readme; (4) metadata; (5) methods information; (6) benzene polycarboxylic acid (BPCA) concentration data; (7) Fourier transform ion cyclotron resonance mass spectrometry (FTICR-MS) methods; (8) folder of high resolution characterization of organic matter via 12 Tesla FTICR-MS data generated through the Environmental Molecular Sciences Laboratory (EMSL; https://www.pnnl.gov/environmental-molecular-sciences-laboratory). This package contains the following file types: csv, xml, pdf.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2017

Bayesian Regression of Thermodynamic Models of Redox Active Materials

Finding a suitable functional redox material is a critical challenge to achieving scalable, economically viable technologies for storing concentrated solar energy in the form of a defected oxide. Demonstrating e ectiveness for thermal storage or solar fuel is largely accomplished by using a thermodynamic model derived from experimental data. The purpose of this project is to test the accuracy of our regression model on representative data sets. Determining the accuracy of the model includes parameter tting the model to the data, comparing the model using di erent numbers of param- eters, and analyzing the entropy and enthalpy calculated from the model. Three data sets were considered in this project: two demonstrating materials for solar fuels by wa- ter splitting and the other of a material for thermal storage. Using Bayesian Inference and Markov Chain Monte Carlo (MCMC), parameter estimation was preformed on the three data sets. Good results were achieved, except some there was some deviations on the edges of the data input ranges. The evidence values were then calculated in a variety of ways and used to compare models with di erent number of parameters. It was believed that at least one of the parameters was unnecessary and comparing evidence values demonstrated that the parameter was need on one data set and not signi cantly helpful on another. The entropy was calculated by taking the derivative in one variable and integrating over another. and its uncertainty was also calculated by evaluating the entropy over multiple MCMC samples. Afterwards, all the parts were written up as a tutorial for the Uncertainty Quanti cation Toolkit (UQTk).

36 MATERIALS SCIENCE↗
DOE OSTI2022

A Multistage Stochastic Transmission Expansion Algorithm for Wide-Area Planning under Uncertainty

The overall objective for this project was to develop and demonstrate a set of methods for solving the transmission investment problem for a large network considering many possible scenarios of future conditions and multiple decision points when investments can be made. Project sub-objectives achieved this goal through a succession of extending the methods to apply to problems with increasing complexity or additional features, including the number of decision points, whether generation and transmission are co-optimized, and whether AC or DC power flow is used. A transmission model was developed for the Western Electric Coordinating Council (WECC) region, the high-voltage transmission system that serves the western third of the continental U.S. Using a dataset provided by WECC and by researchers from John Hopkins University, we have validated and demonstrated the model and used it to compare the new method for solving multi-stage stochastic transmission planning to several state-of-the-art techniques. The project has resulted in several key outcomes and achievements: The covariance-based method for choosing a small set of hours to represent short-term variability has superior performance in terms of accuracy to existing methods, including K-means clustering and Importance Sampling; The combined partitioning method for long-term uncertainty with the nested clustering approach for choosing representative hours for each long-term group has superior accuracy for equivalent computational effort compared with existing methods; Using the partitioning/clustering method combined with Sample Average Approximation provides both statistical bounds on the quality of the solution and at the same time, a complete investment plan for all contingencies in the full uncertainty set; no existing methods can provide both at the same time; The method is demonstrated to work well for choosing both transmission and generation investments; A variant on the method allows for both scenario selection and simultaneous correction for the error from the DC power flow approximation to provide a tractable method for AC power flow-based transmission planning under uncertainty; The method applied to the WECC case study demonstrates the additional value to the system operator and the consumer of identifying flexible investment options in the near-term decisions. In particular, the case study exhibits significant option value in postponing some transmission additions that appear useful but in some long-term system states create new congestion problems.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2016

SPRUCE Deep Peat Heating (DPH) Peat Water Content and Temperature for Experimental Plot Cores, June 2014 through June 2015

This data set provides the peat water content and peat temperature at time of sampling for peat cores collected before and during the SPRUCE Deep Peat Heating (DPH) study. Cores were collected during three sampling events: 03 June 2014, 09 September 2014, and 16 June 2015. Two cores were extracted from hollow locations in each of the 10 experimental plots (4, 6, 8, 10, 11, 13, 16, 17, 19, and 20). The five ambient plots (5, 7, 14, and 21) were not included in the DPH sampling efforts. See Table 1. Cores were partitioned into samples at 11 depth increments: 0-10, 10-20, 20-30, 30-40, 40-50, 50-75, 75-100, 100-125, 125-150, 150-175, and 175-200 cm below surface of the hollow. The DPH study was undertaken to evaluate possible rapid responses of deep peat carbon (C) stocks, microbial communities, and biogeochemical cycling processes to unprecedented temperatures. In June 2014, deep soil heating was initiated at 5 warming levels (+0, +2.25, +4.5, +6.75 and +9 °C) with 2 replicate plots per level. Warming levels at depth were achieved over a 25 (+ 2.25 °C) to 60-day (+9 °C) period depending on the target treatment temperatures. Data file – There is one comma-separated (*.csv) file with peat core water content and temperature at time of sampling, plus the amount of dried archived material retained after analyses. User Note: In this third release, four variables related to extrapolations of peat core temperature were removed. See the Data Set History table for additional details. 25-150, 150-175, and 175-200 cm below surface of the hollow.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2017

The Structure of the Young Star Cluster NGC 6231. I. Stellar Population

NGC 6231 is a young cluster (age ∼2–7 Myr) dominating the Sco OB1 association (distance ∼1.59 kpc) with ∼100 O and B stars and a large pre-main-sequence stellar population. We combine a reanalysis of archival Chandra X-ray data with multiepoch near-infrared (NIR) photometry from the VISTA Variables in the Vía Lactéa (VVV) survey and published optical catalogs to obtain a catalog of 2148 probable cluster members. This catalog is 70% larger than previous censuses of probable cluster members in NGC 6231. It includes many low-mass stars detected in the NIR but not in the optical and some B stars without previously noted X-ray counterparts. In addition, we identify 295 NIR variables, about half of which are expected to be pre-main-sequence stars. With the more complete sample, we estimate a total population in the Chandra field of 5700–7500 cluster members down to 0.08 M{sub ⊙} (assuming a universal initial mass function) with a completeness limit at 0.5 M{sub ⊙}. A decrease in stellar X-ray luminosities is noted relative to other younger clusters. However, within the cluster, there is little variation in the distribution of X-ray luminosities for ages less than 5 Myr. The X-ray spectral hardness for B stars may be useful for distinguishing between early-B stars with X-rays generated in stellar winds and B-star systems with X-rays from a pre-main-sequence companion (>35% of B stars). A small fraction of catalog members have unusually high X-ray median energies or reddened NIR colors, which might be explained by absorption from thick or edge-on disks or being background field stars.

79 ASTRONOMY AND ASTROPHYSICS↗
NASA NTRS1975

Snow survey and vegetation growth in high mountains (Swiss Alps) and additional ERTS investigations in Switzerland

The author has identified the following significant results. Two different methods, an analog and a digital one, have been developed for rapid and accurate mapping of the areal extent and changes in snow cover in high mountains. The quick-look method is based on individual visual control of each image using a photo quantizer which provides exact references for density slicing with high resolution lith-film. The digital snow classification system is based on discriminant analysis with the data of the four multispectral bands as variables and contains all preprocessing, feature extraction, and mapping steps for an operational application. Two different sets of sampling groups were established which apply to different conditions of snow cover. The first one serves for the normal situation with a uniform dry and new cover. The second one serves for situations with partly thawing and/or frozen snow.

Haefner, H.↗
NASA NTRS1975

Reproducibility of liquid oxygen impact test results

Results for 12,000 impacts on a wide range of materials were studied to determine the reproducibility of the liquid oxygen impact test method. Standard deviations representing the overall variability of results were in close agreement with the expected values for a binomial process. This indicates that the major source of variability is due to the go - no go nature of the test method and that variations due to sampling and testing operations were not significant.

Gayle, J. B.↗
NASA NTRS1982

On the adequacy of the fixed locations of the surface-based international network for inferring interannual ozone variability

The influence of the geographical distribution and the number of the surface stations in the ozone detecting network on changes in global ozone inferred from the surface measurements is investigated by comparison with information obtained from satellite backscattered UV observations on the Nimbus 4 with nearly complete global coverage for the period 1970-1972. Results show that the geographical distribution of the stations does not properly represent different latitudes. While the number of stations in the north temperate zone appears adequate to represent monthly ozone averages to within 0.5% except during the early phase of the Northern Hemisphere spring maximum, the resultant error in the derived change in north temperature zone ozone between 1970-1972 is 0.5%. In the tropical and south temperate zones the smaller number of stations reduces precision, and the ozone averages for use in deriving seasonal variability and trends are uncertain by about 1%. However, in the south temperature zone, the average from the sample may differ as much as 5% in some months from the averages derived from the full set. It is concluded that the resulting uncertainty in the global averages is comparable in size to typical yearly changes.

Heath, D. F.↗