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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 919 records · Page 51
All sourcesNASA NTRSDOE OSTI
DOE OSTI2016

Using geochemical indicators to distinguish high biogeochemical activity in floodplain soils and sediments

A better understanding of how microbial communities interact with their surroundings in physically and chemically heterogeneous subsurface environments will lead to improved quantification of biogeochemical reactions and associated nutrient cycling. This paper develops a methodology to predict potential elevated rates of biogeochemical activity (microbial “hotspots”) in subsurface environments by correlating microbial DNA and aspects of the community structure with the spatial distribution of geochemical indicators in subsurface sediments. Multiple linear regression models of simulated precipitation leachate, HCl and hydroxylamine extractable iron and manganese, total organic carbon (TOC), and microbial community structure were used to identify sample characteristics indicative of biogeochemical hotspots within fluvially-derived aquifer sediments and overlying soils. The method has been applied to (a) alluvial materials collected at a former uranium mill site near Rifle, Colorado and (b) relatively undisturbed floodplain deposits (soils and sediments) collected along the East River near Crested Butte, Colorado. At Rifle, 16 alluvial samples were taken from 8 sediment cores, and at the East River, 46 soil/sediment samples were collected across and perpendicular to 3 active meanders and an oxbow meander. Regression models using TOC and TOC combined with extractable iron and manganese results were determined to be the best fitting statistical models of microbial DNA (via 16S rRNA gene analysis). Finally, fitting these models to observations in both contaminated and natural floodplain deposits, and their associated alluvial aquifers, demonstrates the broad applicability of the geochemical indicator based approach.

58 GEOSCIENCES↗
DOE OSTI2013

HerMES: COSMIC INFRARED BACKGROUND ANISOTROPIES AND THE CLUSTERING OF DUSTY STAR-FORMING GALAXIES

We present measurements of the auto- and cross-frequency power spectra of the cosmic infrared background (CIB) at 250, 350, and 500 {mu}m (1200, 860, and 600 GHz) from observations totaling {approx}70 deg{sup 2} made with the SPIRE instrument aboard the Herschel Space Observatory. We measure a fractional anisotropy {delta}I/I = 14% {+-} 4%, detecting signatures arising from the clustering of dusty star-forming galaxies in both the linear (2-halo) and nonlinear (1-halo) regimes; and that the transition from the 2- to 1-halo terms, below which power originates predominantly from multiple galaxies within dark matter halos, occurs at k{sub {theta}} {approx} 0.10-0.12 arcmin{sup -1} (l {approx} 2160-2380), from 250 to 500 {mu}m. New to this paper is clear evidence of a dependence of the Poisson and 1-halo power on the flux-cut level of masked sources-suggesting that some fraction of the more luminous sources occupy more massive halos as satellites, or are possibly close pairs. We measure the cross-correlation power spectra between bands, finding that bands which are farthest apart are the least correlated, as well as hints of a reduction in the correlation between bands when resolved sources are more aggressively masked. In the second part of the paper, we attempt to interpret the measurements in the framework of the halo model. With the aim of fitting simultaneously with one model the power spectra, number counts, and absolute CIB level in all bands, we find that this is achievable by invoking a luminosity-mass relationship, such that the luminosity-to-mass ratio peaks at a particular halo mass scale and declines toward lower and higher mass halos. Our best-fit model finds that the halo mass which is most efficient at hosting star formation in the redshift range of peak star-forming activity, z {approx} 1-3, is log(M{sub peak}/M{sub Sun }) {approx} 12.1 {+-} 0.5, and that the minimum halo mass to host infrared galaxies is log(M{sub min}/M{sub Sun }) {approx} 10.1 {+-} 0.6.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2016

PHOTOMETRIC SUPERNOVA CLASSIFICATION WITH MACHINE LEARNING

Automated photometric supernova classification has become an active area of research in recent years in light of current and upcoming imaging surveys such as the Dark Energy Survey (DES) and the Large Synoptic Survey Telescope, given that spectroscopic confirmation of type for all supernovae discovered will be impossible. Here, we develop a multi-faceted classification pipeline, combining existing and new approaches. Our pipeline consists of two stages: extracting descriptive features from the light curves and classification using a machine learning algorithm. Our feature extraction methods vary from model-dependent techniques, namely SALT2 fits, to more independent techniques that fit parametric models to curves, to a completely model-independent wavelet approach. We cover a range of representative machine learning algorithms, including naive Bayes, k -nearest neighbors, support vector machines, artificial neural networks, and boosted decision trees (BDTs). We test the pipeline on simulated multi-band DES light curves from the Supernova Photometric Classification Challenge. Using the commonly used area under the curve (AUC) of the Receiver Operating Characteristic as a metric, we find that the SALT2 fits and the wavelet approach, with the BDTs algorithm, each achieve an AUC of 0.98, where 1 represents perfect classification. We find that a representative training set is essential for good classification, whatever the feature set or algorithm, with implications for spectroscopic follow-up. Importantly, we find that by using either the SALT2 or the wavelet feature sets with a BDT algorithm, accurate classification is possible purely from light curve data, without the need for any redshift information.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2025

Assessing methods in fusion and fitting for time series construction in remote sensing-based earth observations

This study evaluates the comparative performance of spatiotemporal fusion and time-series fitting methods for constructing high-spatiotemporal-resolution remote sensing time-series data. Due to in-class similarity of fusion methods and fitting methods, we employ the Fit-FC (Fitting, spatial Filtering, and residual Compensation) model as a representative fusion method and the linear harmonic fitting model as a representative fitting method. Both Fit-FC and the linear harmonic fitting are widely used for high-spatiotemporal-resolution time-series data construction, and we modify the original Fit-FC model to enable automatic time-series fusion. To ensure data representativeness, we use 3 years (2019–2021) of Harmonized Landsat and Sentinel-2 surface reflectance datasets and Terra MCD43A4 products. Eight experimental regions are selected worldwide to guarantee generalization of the comparative performance between fusion and fitting methods, covering diverse land-use types (cropland, developed land, forest, and grassland) and varying climatological conditions. Time-series of NDVI and surface reflectance are analyzed under both actual observations and simulated data-missing scenarios. The constructed time-series data reveals that (1) the modified Fit-FC and linear harmonic fitting model achieve excellent performance in constructing high-resolution time-series images; (2) the fusion method outperforms the fitting method in constructing time-series of NDVI and surface reflectance images in cropland-, forest-, and grassland-dominated regions; (3) both methods achieve comparable performance in developed-dominated regions; (4) the fusion method is more robust to missing data, and better captures abrupt phenological transitions under conditions of continuous missing data; (5) the fitting method is computationally more efficient, making it suitable for large-scale time-series image reconstruction. This study provides valuable insights for selecting optimal strategies to generate high-resolution time-series images across diverse application scenarios and lays a foundation for extensions to other vegetation indices or land surface variables.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2013

ON THE ROBUSTNESS OF z = 0-1 GALAXY SIZE MEASUREMENTS THROUGH MODEL AND NON-PARAMETRIC FITS

We present the size-stellar mass relations of nearby (z = 0.01-0.02) Sloan Digital Sky Survey galaxies, for samples selected by color, morphology, Sérsic index n, and specific star formation rate. Several commonly employed size measurement techniques are used, including single Sérsic fits, two-component Sérsic models, and a non-parametric method. Through simple simulations, we show that the non-parametric and two-component Sérsic methods provide the most robust effective radius measurements, while those based on single Sérsic profiles are often overestimates, especially for massive red/early-type galaxies. Using our robust sizes, we show for all sub-samples that the mass-size relations are shallow at low stellar masses and steepen above ∼3-4 × 10{sup 10} M{sub ☉}. The mass-size relations for galaxies classified as late-type, low-n, and star-forming are consistent with each other, while blue galaxies follow a somewhat steeper relation. The mass-size relations of early-type, high-n, red, and quiescent galaxies all agree with each other but are somewhat steeper at the high-mass end than previous results. To test potential systematics at high redshift, we artificially redshifted our sample (including surface brightness dimming and degraded resolution) to z = 1 and re-fit the galaxies using single Sérsic profiles. The sizes of these galaxies before and after redshifting are consistent and we conclude that systematic effects in sizes and the size-mass relation at z ∼ 1 are negligible. Interestingly, since the poorer physical resolution at high redshift washes out bright galaxy substructures, single Sérsic fitting appears to provide more reliable and unbiased effective radius measurements at high z than for nearby, well-resolved galaxies.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2022

Augmented Adam-Gibbs model for glass melt viscosity and configuration entropy as functions of temperature and composition

As the temperature of glass melt increases, its structure approaches the state of a simple liquid while the configuration entropy approaches a maximum value. We describe this gradual change using a power law function of inverse temperature. The Adam-Gibbs model for glass viscosity as a function of temperature and glass composition augmented in this way is greatly simplified when applied to common glass families occupying moderate composition regions, such as float glass or nuclear waste glasses, on which properties can be approximated as linear functions of composition. The parsimonious model thus obtained is preferable for use in optimizing glass formulation and mathematical modeling of glass melting and forming. For multicomponent glasses with N viscosity-affecting components, the augmented Adam-Gibbs model requires 2N + 3 adjustable parameters. The model efficacy is demonstrated by fitting the model to a viscosity-temperature-composition dataset for low-activity nuclear waste glasses.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2022

Electron energy loss spectroscopy database synthesis and automation of core-loss edge recognition by deep-learning neural networks

Abstract The ionization edges encoded in the electron energy loss spectroscopy (EELS) spectra enable advanced material analysis including composition analyses and elemental quantifications. The development of the parallel EELS instrument and fast, sensitive detectors have greatly improved the acquisition speed of EELS spectra. However, the traditional way of core-loss edge recognition is experience based and human labor dependent, which limits the processing speed. So far, the low signal–noise ratio and the low jump ratio of the core-loss edges on the raw EELS spectra have been challenging for the automation of edge recognition. In this work, a convolutional-bidirectional long short-term memory neural network (CNN-BiLSTM) is proposed to automate the detection and elemental identification of core-loss edges from raw spectra. An EELS spectral database is synthesized by using our forward model to assist in the training and validation of the neural network. To make the synthesized spectra resemble the real spectra, we collected a large library of experimentally acquired EELS core edges. In synthesize the training library, the edges are modeled by fitting the multi-Gaussian model to the real edges from experiments, and the noise and instrumental imperfectness are simulated and added. The well-trained CNN-BiLSTM network is tested against both the simulated spectra and real spectra collected from experiments. The high accuracy of the network, 94.9%, proves that, without complicated preprocessing of the raw spectra, the proposed CNN-BiLSTM network achieves the automation of core-loss edge recognition for EELS spectra with high accuracy.

36 MATERIALS SCIENCE↗
DOE OSTI2025

Modeling ethanol/water adsorption in all-silica zeolites using the real adsorbed solution theory

A comprehensive set of single-component and binary isotherms were collected for ethanol/water adsorption into the siliceous forms of 185 known zeolites using grand-canonical Monte Carlo simulations. Using these data, a systematic analysis of ideal/real adsorbed-solution theory (IAST/RAST) was conducted and activity coefficients were derived for ethanol/water mixtures adsorbed in different zeolites based on RAST. It was found that activity coefficients of ethanol are close to unity while activity coefficients of water are larger in most zeolites, indicating a positive excess free energy of the mixture. This observation can be attributed to water/ethanol interactions being less favorable than water/water interactions in the single-component adsorption of water at comparable loadings. The deviation from ideal behavior can be highly structure-dependent but no clear correlation with pore diameters was identified. Furthermore, our analysis also demonstrates the following: (1) accurate unary isotherms in the low-loading regime are critical for obtaining physically sensible activity coefficients; (2) the global regression scheme to solve for activity model parameters performs better than fitting activity models to activity coefficients calculated locally at each binary state point; and (3) including the dependence on adsorption potential offers only a minor benefit for describing binary adsorption at the lowest fugacities. Finally, the Margules activity model was found incapable of capturing the non-ideal adsorption behavior over the entire range of fugacities and compositions in all zeolites, but for conditions typical of solution-phase adsorption, RAST predictions using zeolite-specific or even bulk Margules parameters provide an improved description compared to IAST.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2012

ON THE TRANSITIONAL DISK CLASS: LINKING OBSERVATIONS OF T TAURI STARS AND PHYSICAL DISK MODELS

Two decades ago 'transitional disks' (TDs) described spectral energy distributions (SEDs) of T Tauri stars with small near-IR excesses, but significant mid- and far-IR excesses. Many inferred this indicated dust-free holes in disks possibly cleared by planets. Recently, this term has been applied disparately to objects whose Spitzer SEDs diverge from the expectations for a typical full disk (FD). Here, we use irradiated accretion disk models to fit the SEDs of 15 such disks in NGC 2068 and IC 348. One group has a 'dip' in infrared emission while the others' continuum emission decreases steadily at all wavelengths. We find that the former have an inner disk hole or gap at intermediate radii in the disk and we call these objects 'transitional disks' and 'pre-transitional disks' (PTDs), respectively. For the latter group, we can fit these SEDs with FD models and find that millimeter data are necessary to break the degeneracy between dust settling and disk mass. We suggest that the term 'transitional' only be applied to objects that display evidence for a radical change in the disk's radial structure. Using this definition, we find that TDs and PTDs tend to have lower mass accretion rates than FDs and that TDs have lower accretion rates than PTDs. These reduced accretion rates onto the star could be linked to forming planets. Future observations of TDs and PTDs will allow us to better quantify the signatures of planet formation in young disks.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2013

MODELING THE HD 32297 DEBRIS DISK WITH FAR-INFRARED HERSCHEL DATA

HD 32297 is a young A-star ({approx}30 Myr) 112 pc away with a bright edge-on debris disk that has been resolved in scattered light. We observed the HD 32297 debris disk in the far-infrared and sub-millimeter with the Herschel Space Observatory PACS and SPIRE instruments, populating the spectral energy distribution (SED) from 63 to 500 {mu}m. We aimed to determine the composition of dust grains in the HD 32297 disk through SED modeling, using geometrical constraints from the resolved imaging to break the degeneracies inherent in SED modeling. We found the best fitting SED model has two components: an outer ring centered around 110 AU, seen in the scattered light images, and an inner disk near the habitable zone of the star. The outer disk appears to be composed of grains >2 {mu}m consisting of silicates, carbonaceous material, and water ice with an abundance ratio of 1:2:3 respectively and 90% porosity. These grains appear consistent with cometary grains, implying the underlying planetesimal population is dominated by comet-like bodies. We also discuss the 3.7{sigma} detection of [C II] emission at 158 {mu}m with the Herschel PACS instrument, making HD 32297 one of only a handful of debris disks with circumstellar gas detected.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2015

ULTRAVIOLET SPECTROSCOPY OF TYPE IIB SUPERNOVAE: DIVERSITY AND THE IMPACT OF CIRCUMSTELLAR MATERIAL

We present new Hubble Space Telescope (HST) multi-epoch ultraviolet (UV) spectra of the bright Type IIb SN 2013df, and undertake a comprehensive analysis of the set of four SNe IIb for which HST UV spectra are available (SN 1993J, SN 2001ig, SN 2011dh, and SN 2013df). We find strong diversity in both continuum levels and line features among these objects. We use radiative-transfer models that fit the optical part of the spectrum well, and find that in three of these four events we see a UV continuum flux excess, apparently unaffected by line absorption. We hypothesize that this emission originates above the photosphere, and is related to interaction with circumstellar material (CSM) located in close proximity to the SN progenitor. In contrast, the spectra of SN 2001ig are well fit by single-temperature models, display weak continuum and strong reverse-fluorescence features, and are similar to spectra of radioactive {sup 56}Ni-dominated SNe Ia. A comparison of the early shock-cooling components in the observed light curves with the UV continuum levels which we assume trace the strength of CSM interaction suggests that events with slower cooling have stronger CSM emission. The radio emission from events having a prominent UV excess is perhaps consistent with slower blast-wave velocities, as expected if the explosion shock was slowed down by the CSM that is also responsible for the strong UV, but this connection is currently speculative as it is based on only a few events.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2020

The completed SDSS-IV extended Baryon Oscillation Spectroscopic Survey: large-scale structure catalogues and measurement of the isotropic BAO between redshift 0.6 and 1.1 for the Emission Line Galaxy Sample

ABSTRACT We present the Emission Line Galaxy (ELG) sample of the extended Baryon Oscillation Spectroscopic Survey from the Sloan Digital Sky Survey IV Data Release 16. We describe the observations and redshift measurement for the 269 243 observed ELG spectra, and then present the large-scale structure catalogues, used for the cosmological analysis, and made of 173 736 reliable spectroscopic redshifts between 0.6 and 1.1. We perform a spherically averaged baryon acoustic oscillations (BAO) measurement in configuration space, with density field reconstruction: the data two-point correlation function shows a feature consistent with that of the BAO, the BAO model being only weakly preferred over a model without BAO (Δχ2 < 1). Fitting a model constrained to have a BAO feature provides a 3.2 per cent measurement of the spherically averaged BAO distance DV(zeff)/rdrag = 18.23 ± 0.58 at the effective redshift zeff = 0.845.

Raichoor, Anand↗
DOE OSTI2016

Centrality dependence of identified particle elliptic flow in relativistic heavy ion collisions at s N N = 7.7 – 62.4 GeV

Here, elliptic flow (v 2 ) values for identified particles at midrapidity in Au + Au collisions measured by the STAR experiment in the Beam Energy Scan at the Relativistic Heavy Ion Collider at √s NN = 7.7–62.4 GeV are presented for three centrality classes. The centrality dependence and the data at √s NN = 14.5 GeV are new. Except at the lowest beam energies, we observe a similar relative v 2 baryon-meson splitting for all centrality classes which is in agreement within 15% with the number-of-constituent quark scaling. The larger v 2 for most particles relative to antiparticles, already observed for minimum bias collisions, shows a clear centrality dependence, with the largest difference for the most central collisions. Also, the results are compared with a multiphase transport (AMPT) model and fit with a blast wave model.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2024

Three-Stage Adjusted Regression Forecasting for Software Defect Prediction

In this paper, a three-stage adjusted regression forecasting model is proposed to forecast the local regression model [6]. This is a growth curve approximation model that predicts the parameters for a future linear model based on a sliding window of previous linear models. The three stages of the model are as follows: • Initial fit: train regression models on a sliding window of the date and record model coefficients. • Prediction: fit new regression models to the coefficient lists and predict the value of the next coefficient. • Error correction: correct coefficient prediction error using the residual of the last point of the coefficient list and moving average. The resulting model from the multi-stage process is a forecast of the local regression model that represents the future window of data and is referred to as the predicted line. Results suggest the three-stage model demonstrates better prediction capability compared to existing solutions.

Pritchard, Shadow↗
DOE OSTI2016

A spectroscopic study of the chromatic properties of GafChromic™EBT3 films

Purpose: This work provides an interpretation of the chromatic properties of GafChromic™EBT3 films based on the chemical nature of the polydiacetylene (PDA) molecules formed upon interaction with ionizing radiation. The EBT3 films become optically less transparent with increasing radiation dose as a result of the radiation-induced polymerization of diacetylene monomers. In contrast to empirical quantification of the chromatic properties, less attention has been given to the underlying molecular mechanism that induces the strong decrease in transparency. Methods: Unlaminated GafChromic™EBT3 films were irradiated with a 6 MV photon beam to dose levels up to 20 Gy. The optical absorption properties of the films were investigated using visible (vis) spectroscopy. The presence of PDA molecules in the active layer of the EBT3 films was investigated using Raman spectroscopy, which probes the vibrational modes of the molecules in the layer. The vibrational modes assigned to PDA’s were used in a theoretical vis-absorption model to fit our experimental vis-absorption spectra. From the fit parameters, one can assess the relative contribution of different PDA conformations and the length distribution of PDA’s in the film. Results: Vis-spectroscopy shows that the optical density increases with dose in the full region of the visible spectrum. The Raman spectrum is dominated by two vibrational modes, most notably by the ν(C≡C) and the ν(C=C) stretching modes of the PDA backbone. By fitting the vis-absorption model to experimental spectra, it is found that the active layer contains two distinct PDA conformations with different absorption properties and reaction kinetics. Furthermore, the mean PDA conjugation length is found to be 2–3 orders of magnitude smaller than the crystals PDA’s are embedded in. Conclusions: Vis- and Raman spectroscopy provided more insight into the molecular nature of the radiochromic properties of EBT3 films through the identification of the excited states of PDA and the presence of two PDA conformations. The improved knowledge on the molecular composition of EBT3’s active layer provides a framework for future fundamental modeling of the dose–response.

38 RADIATION CHEMISTRY, RADIOCHEMISTRY, AND NUCLEA↗
DOE OSTI2021

A Gaussian Process Regression Reveals No Evidence for Planets Orbiting Kapteyn’s Star

Radial–velocity (RV) planet searches are often polluted by signals caused by gas motion at the star’s surface. Stellar activity can mimic or mask changes in the RVs caused by orbiting planets, resulting in false positives or missed detections. Here we use Gaussian process regression to disentangle the contradictory reports of planets versus rotation artifacts from Kapteyn’s star. To model rotation, we use joint quasiperiodic kernels for the RV and Hα signals, requiring that their periods and correlation timescales be the same. We find that the rotation period of Kapteyn’s star is 125 days, while the characteristic active-region lifetime is 694 days. Adding a planet to the RV model produces a best-fit orbital period of 100 yr, or 10 times the observing time baseline, indicating that the observed RVs are best explained by star rotation only. We also find no significant periodic signals in residual RV data sets constructed by subtracting off realizations of the best-fit rotation model and conclude that both previously reported “planets” are artifacts of the star’s rotation and activity. Our results highlight the pitfalls of using sinusoids to model quasiperiodic rotation signals.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2018

DeepHyper: Asynchronous Hyperparameter Search for Deep Neural Networks

Hyperparameters employed by deep learning (DL) methods play a substantial role in the performance and reliability of these methods in practice. Unfortunately, finding performance-optimizing hyperparameter settings is a notoriously difficult task. Hyperparameter search methods typically have limited production-strength implementations or do not target scalability within a highly parallel machine, portability across different machines, experimental comparison between different methods, and tighter integration with workflow systems. In this paper, we present DeepHyper, a Python package that provides a common interface for the implementation and study of scalable hyperparameter search methods. It adopts the Balsam workflow system to hide the complexities of running large numbers of hyperparameter configurations in parallel on high-performance computing (HPC) systems. We implement and study asynchronous model-based search methods that consist of sampling a small number of input hyperparameter configurations and progressively fitting surrogate models over the input-output space until exhausting a user-defined budget of evaluations. We evaluate the efficacy of these methods relative to approaches such as random search, genetic algorithms, Bayesian optimization, and hyperband on DL benchmarks on CPU- and GPU-based HPC systems.

Balaprakash, Prasanna↗
DOE OSTI2018

Constraints on dark energy dynamics and spatial curvature from Hubble parameter and baryon acoustic oscillation data

We use all available baryon acoustic oscillation distance measurements and Hubble parameter data to constrain the cosmological constant Λ, dynamical dark energy, and spatial curvature in simple cosmological models. Here, we find that the consensus spatially flat ΛCDM (Λ cold dark matter) model provides a reasonable fit to the data, but depending on the Hubble constant prior and cosmological model, it can be a little more than 1σ away from the best-fitting model, which can favour mild dark energy dynamics or non-flat spatial hypersurfaces.

79 ASTRONOMY AND ASTROPHYSICS↗