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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 577 records · Page 32
All sourcesNASA NTRSDOE OSTI
DOE OSTI2016

Lamost observations in the Kepler field. Analysis of the stellar parameters measured with LASP based on low-resolution spectra

All 14 subfields of the Kepler field were observed at least once with the Large Sky Area Multi-Object Fiber Spectroscopic Telescope (lamost, Xinglong Observatory, China) during the 2012–2014 observation seasons. There are 88,628 reduced spectra with a signal-to-noise ratio in the g band (S/N{sub g}) ≥ 6 after the first round (2012–2014) of observations of the lamost– Kepler project (LK-project). By adopting the upgraded version of the lamost Stellar Parameter pipeline (lasp), we have determined the atmospheric parameters (T{sub eff}, logg, and [Fe/H]) and heliocentric radial velocity v {sub rad} for 51,406 stars with 61,226 spectra. Compared with the atmospheric parameters derived from both high-resolution spectroscopy and asteroseismology for common stars in Huber et al., an external calibration of lasp atmospheric parameters was made, leading to the determination of the external errors for giants and dwarfs. Multiple spectroscopic observations of the same objects in the LK-project were used to estimate the internal uncertainties of the atmospheric parameters as a function of S/N{sub g} with the unbiased estimation method. The lasp atmospheric parameters were calibrated based on both the external and internal uncertainties for the giants and dwarfs. A general statistical analysis of the stellar parameters leads to the discovery of 106 candidate metal-poor stars, 9 candidate very metal-poor stars, and 18 candidate high-velocity stars. Fitting formulae were obtained segmentally for both the calibrated atmospheric parameters of the LK-project and the Kepler Input Catalog (KIC) parameters with common stars. The calibrated atmospheric parameters and radial velocities of the LK-project will be useful for studying stars in the Kepler field.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2023

Numerical evaluation of photosensitive tracers as a strategy for separating surface and subsurface transient storage in streams

For this work, we numerically evaluated photosensitive tracers as a potential strategy for separating the effects of surface and hyporheic storage zones (SSZs and HSZs, respectively) on stream corridor transport. Correctly separating HSZ and SSZ effects is critical to estimating the hydro-biogeochemical function of a stream because HSZs and SSZs expose solutes to significantly different biogeochemical conditions, like sunlight exposure, microbial processes, and oxygen availability. Our numerical experiments used a multiscale river-corridor transport model implemented in the ATS code, which accommodates multiple storage zones with distinct travel time distributions and biogeochemical reactions. For parameter inferences, we used Bayesian inverse modeling. We found that breakthrough curves for photo-decaying tracers from day and night injection can delineate surface and hyporheic transient storage contributions, but only when interpreted jointly through a two-storage zone model. Numerical experiments that used only daytime injection or interpreted breakthrough curves with a single storage zone model yielded good fit to breakthrough curves, but parameter estimates were biased and controlling processes misattributed, examples of good model fits for the wrong reasons. Using those biased parameter estimates in reactive transport simulations resulted in significantly different projections of denitrification, which underscores the potential for stream function to be mischaracterized if tracer tests are interpreted through an inappropriately simplified model for transient storage. More generally, this study highlights the role of modeling in evaluating the experimental design and identifying the potential of system mischaracterization and its implications.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2024

Primordial black hole mass functions as a probe of cosmic origin

Here, we discuss a novel window to probe the origin of our universe via the mass functions of primordial black holes (PBHs). The mass functions of PBHs are simply estimated using the conventional Press-Schechter formalism for two paradigms of cosmic origin, including inflationary ΛCDM and bounce cosmology. The standard inflationary ΛCDM model cannot generate an appreciable number of massive PBHs; however, non-trivial inflation models with blue-tilted power spectra at small scales and matter bounce cosmology provide formation mechanisms for heavy PBHs, which in turn, may seed the observed supermassive black holes (SMBHs). By fitting the SMBH mass functions at high redshift (z ~ 6) derived from Sloan Digital Sky Survey (SDSS) and Canada-France High-z Quasar Survey (CFHQS) quasars, for two paradigms of cosmic origin, we derive constraints on the PBH density fraction $f$ PBH at z ~ 6 and the characteristic mass M $\ast$ , with the prior assumption that all SMBHs stem from PBHs. We demonstrate that this newly proposed procedure, relying on astronomical measurements that utilize deep-field surveys of SMBHs at high redshift, can be used to constrain models of cosmic origin. Additionally, although not the main focus of this paper, we evolve the mass function from z ~ 6 to z ~ 0 through an assumption of 3 × 10 8 -year Eddington’s accretion, and give a rough estimation of $f$ PBH at z ~ 0.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2016

SU-F-I-37: How Fat Distribution and Table Height Affect Estimates of Patient Size in CT Scanning: A Phantom Study

Purpose: Localizer projection radiographs acquired prior to CT scans are used to estimate patient size, affecting the function of Automatic Tube Current Modulation (ATCM) and hence CTDIvol and SSDE. Due to geometric effects, the projected patient size varies with scanner table height and with the orientation of the localizer (AP versus PA). This study sought to determine if patient size estimates made from localizer scans is affected by variations in fat distribution, specifically when the widest part of the patient is not at the geometric center of the patient. Methods: Lipid gel bolus material was wrapped around an anthropomorphic phantom to simulate two different body mass distributions. The first represented a patient with fairly rigid fat and had a generally oval shape. The second was bell-shaped, representing corpulent patients more susceptible to gravity’s lustful tug. Each phantom configuration was imaged using an AP localizer and then a PA localizer. This was repeated at various scanner table heights. The width of the phantom was measured from the localizer and diagnostic images using in-house software. Results: 1) The projected phantom width varied up to 39% as table height changed.2) At some table heights, the width of the phantom, designed to represent larger patients, exceeded the localizer field of view, resulting in an underestimation of the phantom width.3) The oval-shaped phantom approached a normalized phantom width of 1 at a table height several centimeters lower (AP localizer) or higher (PA localizer) than did the bell-shaped phantom. Conclusion: Accurate estimation of patient size from localizer scans is dependent on patient positioning with respect to scanner isocenter and is limited in large patients. Further, patient size is more accurately measured on projection images if the widest part of the patient, rather than the geometric center of the patient, is positioned at scanner isocenter.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2014

Determination of heat conductivity and thermal diffusivity of waste glass melter feed: Extension to high temperatures

The heat conductivity ({lambda}) and the thermal diffusivity (a) of reacting glass batch, or melter feed, control the heat flux into and within the cold cap, a layer of reacting material floating on the pool of molten glass in an all-electric continuous waste glass melter. After previously estimating {lambda} of melter feed at temperatures up to 680 deg C, we focus in this work on the {lambda}(T) function at T > 680 deg C, at which the feed material becomes foamy. We used a customized experimental setup consisting of a large cylindrical crucible with an assembly of thermocouples, which monitored the evolution of the temperature field while the crucible with feed was heated at a constant rate from room temperature up to 1100°C. Approximating measured temperature profiles by polynomial functions, we used the heat transfer equation to estimate the {lambda}(T) approximation function, which we subsequently optimized using the finite-volume method combined with least-squares analysis. The heat conductivity increased as the temperature increased until the feed began to expand into foam, at which point the conductivity dropped. It began to increase again as the foam turned into a bubble-free glass melt. We discuss the implications of this behavior for the mathematical modeling of the cold cap.

36 MATERIALS SCIENCE↗
DOE OSTI2015

SU-E-T-678: Response Calibration Using Electron Depth-Dose Data for MRI-Based 3D Polymer Gel Dosimetry

Purpose: To evaluate a calibration method using the depth-dose data of an electron beam for MRI-based polymer gel dosimetry. Methods: MAGAT was manufactured in-house to fill two 400mL-cylindrical phantoms and nine 22mL-glass vials. Phantom-A was irradiated along the cylinder axis with a 9MeV electron beam of 6 cm x 6 cm field size (FS). Phantom-B was irradiated with a 6MV photon beam of 3 cm x 3 cm FS by a 360-degree arc technique. Eight vials were irradiated in a water-bath to various doses with a 20 cm x 20 cm FS 6MV photon beam. All irradiated phantoms and one un-irradiated vial were scanned with a 3T MRI scanner to obtain the spin-spin relaxation rate (R2) distributions. By comparing the measured R2-to-depth data with the known depth-dose data for Phantom-A, R2-to-dose calibration data were obtained (e-beam method). Another calibration data were obtained from the 9 vials data (9-vial method). We tested two regression equations, i.e., third-order polynomial and tangent functions, and two dose normalization methods, i.e., one-point and two-point methods. Then, these two calibration methods were used to obtain the 3D dose distribution of Phantom-B and evaluated by comparing the measured data with the dose distribution from a treatment planning system. The comparison was made with gamma passing rate (2%/2mm criteria). Results: We did not observe a clear advantage of the e-beam method over the 9-vial method for the 3D dose comparison with the test case. Nevertheless, we found that the e-beam method required a smaller dose scaling for the dose comparison. Furthermore, the tangent function showed better data fitting than the polynomial function with smaller uncertainty of the estimated coefficients. Conclusions: Considering the overall superior performance, we recommend the e-beam method with the tangent function as the regression equation and one-point dose normalization for the MRI-based polymer gel dosimetry.

62 RADIOLOGY AND NUCLEAR MEDICINE↗
DOE OSTI2025

LTAU-FF: Loss Trajectory Analysis for Uncertainty in atomistic Force Fields

Model ensembles are effective tools for estimating prediction uncertainty in deep learning atomistic force fields. However, their widespread adoption is hindered by high computational costs and overconfident error estimates. In this work, we address these challenges by leveraging distributions of per-sample errors obtained during training and employing a distance-based similarity search in the model latent space. Our method, which we call LTAU (Loss Trajectory Analysis for Uncertainty), efficiently estimates the full probability distribution function of errors for any test point using the logged training errors, achieving speeds that are 2–3 orders of magnitudes faster than typical ensemble methods and allowing it to be used for tasks where training or evaluating multiple models would be infeasible. We apply LTAU towards estimating parametric uncertainty in atomistic force fields (LTAU-FF), demonstrating that it produces well-calibrated confidence intervals and predicts errors that correlate strongly with the true errors for data near the training domain. Furthermore, we show that the errors predicted by LTAU-FF can be used in practical applications for detecting out-of-domain data, tuning model performance, and predicting failure during simulations. We believe that LTAU will be a valuable tool for uncertainty quantification in atomistic force fields and is a promising method that should be further explored in other domains of machine learning.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2019

The total microbiome functions in bacteria and fungi

Unveiling the relationship between phylogeny and function of the microbiome is crucial to determine its contribution to ecosystem functioning. However, while there is a considerable amount of information on microbial phylogenetic diversity, our understanding of its relationship to functional diversity is still scarce. Here we predicted the total microbiome functions of bacteria and fungi on Earth using the total known functions from level 3 of KEGG Orthology by modelling the increase of functions with increasing diversity of bacteria or fungi. For bacteria and fungi, the unsaturated model described the data significantly better (for both P?<2.2e-16), suggesting the presence of two types of functions. Widespread functions ubiquitous in every living organism that make up two thirds of our current knowledge of microbiome functions are separated from rare functions from specialised enzymes present in only a few species. Given previous estimates on species richness, we predicted a global total of 35.5 million functions in bacteria and 3.2 million in fungi; of which only 0.02% and 0.14% are known today. Our approach highlights the necessity of novel and more sophisticated methods to unveil the entirety of rare functions to fully understand the involvement of the microbiome in ecosystem functioning. SIGNIFICANCE: The functionality of and within a microbial community is generally inferred based on the taxonomic annotation of the organism. However, our understanding of functional diversity and how it relates to taxonomy is still limited. Here we predict the total microbiome functionality in bacteria and fungi on Earth using known and annotated protein-coding sequences in species accumulation curves. Our estimates reveal that the majority of functionality (>99%) could be assigned to yet unknown and rare functions, highlighting that our current knowledge is incomplete and functional inference is thus lackluster.

Bacteria↗
DOE OSTI2018

Effect of Electron–Phonon Interaction on the Conductivity and Work Function of Epitaxial Graphene

In the context of the cluster model of epitaxial graphene, the condition for a stepwise change in the charge of carbon atoms under the action of graphene–substrate electron–phonon interaction and an external electric field is derived. Such charge transfer brings about corresponding steps of the static conductivity and work function of epitaxial graphene. Numerical estimates for the case of weak coupling of quasi-free graphene with metal and semiconductor substrates are given.

36 MATERIALS SCIENCE↗
DOE OSTI2013

THE FIRST CIRCUMSTELLAR DISK IMAGED IN SILHOUETTE AT VISIBLE WAVELENGTHS WITH ADAPTIVE OPTICS: MagAO IMAGING OF ORION 218-354

We present high-resolution adaptive optics (AO) corrected images of the silhouette disk Orion 218-354 taken with Magellan AO (MagAO) and its visible light camera, VisAO, in simultaneous differential imaging mode at Hα. This is the first image of a circumstellar disk seen in silhouette with AO and is among the first visible light AO results in the literature. We derive the disk extent, geometry, intensity, and extinction profiles and find, in contrast with previous work, that the disk is likely optically thin at Hα. Our data provide an estimate of the column density in primitive, ISM-like grains as a function of radius in the disk. We estimate that only ∼10% of the total submillimeter derived disk mass lies in primitive, unprocessed grains. We use our data, Monte Carlo radiative transfer modeling, and previous results from the literature to make the first self-consistent multiwavelength model of Orion 218-354. We find that we are able to reproduce the 1-1000 μm spectral energy distribution with a ∼2-540 AU disk of the size, geometry, small versus large grain proportion, and radial mass profile indicated by our data. This inner radius is a factor of ∼15 larger than the sublimation radius of the disk, suggesting that it is likely cleared in the very interior.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2018

A stochastic sampling approach to zircon eruption age interpretation

The accessory mineral zircon is widely used to constrain the timing of igneous processes such as magma crystallisation or eruption. However, zircon U-Pb ages record zircon crystallisation, which is not an instantaneous process. Zircon saturation calculations link zircon crystallisation, temperature, and melt fraction, allowing for the estimation of zircon crystallisation distributions as a function of time or temperature. Such distributions provide valuable prior information, enabling Bayesian estimates of magma eruption time and allowing for comparison of the relative accuracy of common weighted-mean and youngest-zircon age interpretations with synthetic datasets. We find that both traditional interpretations carry a risk of underestimating the uncertainty in eruption age; a low mean square of weighted deviates (MSWD) does not guarantee the accuracy of weighted-mean interpretations. In the absence of independent confirmation that crystallisation timescale is short relative to analytical uncertainties, a Bayesian approach frequently provides the most accurate results and is least likely to underestimate uncertainty. Finally, since U-Pb zircon studies now routinely resolve geological age dispersion due to increasing analytical precision, such considerations are increasingly critical to future progress in resolving rates and dates of Earth processes.

58 GEOSCIENCES↗
DOE OSTI2018

Galerkin finite element method for time-fractional stochastic diffusion equations

In this paper, Galerkin finite element method for solving the time-fractional stochastic diffusion equations with multiplicative noise is proposed and investigated. The pathwise regularity properties of solutions to the semidiscrete Galerkin approximations are demonstrated and the convergence of optimal rates are derived. And also we construct the fully discrete scheme which is based on the approximations of the Mittag–Leffler function and analyze the error estimates of convergence in L{sub 2}-norm space. Finally, numerical results are conducted to confirm our theoretical findings.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2013

A comparison of methods for representing sparsely sampled random quantities.

This report discusses the treatment of uncertainties stemming from relatively few samples of random quantities. The importance of this topic extends beyond experimental data uncertainty to situations involving uncertainty in model calibration, validation, and prediction. With very sparse data samples it is not practical to have a goal of accurately estimating the underlying probability density function (PDF). Rather, a pragmatic goal is that the uncertainty representation should be conservative so as to bound a specified percentile range of the actual PDF, say the range between 0.025 and .975 percentiles, with reasonable reliability. A second, opposing objective is that the representation not be overly conservative; that it minimally over-estimate the desired percentile range of the actual PDF. The presence of the two opposing objectives makes the sparse-data uncertainty representation problem interesting and difficult. In this report, five uncertainty representation techniques are characterized for their performance on twenty-one test problems (over thousands of trials for each problem) according to these two opposing objectives and other performance measures. Two of the methods, statistical Tolerance Intervals and a kernel density approach specifically developed for handling sparse data, exhibit significantly better overall performance than the others.

Romero, Vicente Jose↗
DOE OSTI2017

Detection of the pairwise kinematic Sunyaev-Zel'dovich effect with BOSS DR11 and the Atacama Cosmology Telescope

Here, we present a new measurement of the kinematic Sunyaev-Zel'dovich effect using data from the Atacama Cosmology Telescope (ACT) and the Baryon Oscillation Spectroscopic Survey (BOSS). Using 600 square degrees of overlapping sky area, we evaluate the mean pairwise baryon momentum associated with the positions of 50,000 bright galaxies in the BOSS DR11 Large Scale Structure catalog. A non-zero signal arises from the large-scale motions of halos containing the sample galaxies. The data fits an analytical signal model well, with the optical depth to microwave photon scattering as a free parameter determining the overall signal amplitude. We estimate the covariance matrix of the mean pairwise momentum as a function of galaxy separation, using microwave sky simulations, jackknife evaluation, and bootstrap estimates. The most conservative simulation-based errors give signal-to-noise estimates between 3.6 and 4.1 for varying galaxy luminosity cuts. We discuss how the other error determinations can lead to higher signal-to-noise values, and consider the impact of several possible systematic errors. Estimates of the optical depth from the average thermal Sunyaev-Zel'dovich signal at the sample galaxy positions are broadly consistent with those obtained from the mean pairwise momentum signal.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2019

Building and exploring libraries of atomic defects in graphene: Scanning transmission electron and scanning tunneling microscopy study

The presence and configurations of defects are primary components determining materials functionality. Their population and distribution are often nonergodic and dependent on synthesis history, and therefore rarely amenable to direct theoretical prediction. Here, dynamic electron beam–induced transformations in Si deposited on a graphene monolayer are used to create libraries of possible Si and carbon vacancy defects. Deep learning networks are developed for automated image analysis and recognition of the defects, creating a library of (meta) stable defect configurations. Density functional theory is used to estimate atomically resolved scanning tunneling microscopy (STM) signatures of the classified defects from the created library, allowing identification of several defect types across imaging platforms. This approach allows automatic creation of defect libraries in solids, exploring the metastable configurations always present in real materials, and correlative studies with other atomically resolved techniques, providing comprehensive insight into defect functionalities.

36 MATERIALS SCIENCE↗
DOE OSTI2020

The role of high-order electron correlation effects in a model system for non-valence correlation-bound anions

The diffusion Monte Carlo (DMC), auxiliary field quantum Monte Carlo (AFQMC), and equation-of-motion coupled cluster (EOM-CC) methods are used to calculate the electron binding energy (EBE) of the non-valence anion state of a model (H2O)4 cluster. Two geometries are considered, one at which the anion is unbound and the other at which it is bound in the Hartree–Fock (HF) approximation. It is demonstrated that DMC calculations can recover from the use of a HF trial wave function that has collapsed onto a discretized continuum solution, although larger EBEs are obtained when using a trial wave function for the anion that provides a more realistic description of the charge distribution and, hence, of the nodal surface. For the geometry at which the cluster has a non-valence correlation-bound anion, both the inclusion of triples in the EOM-CC method and the inclusion of supplemental diffuse d functions in the basis set are important. DMC calculations with suitable trial wave functions give EBE values in good agreement with our best estimate EOM-CC result. AFQMC using a trial wave function for the anion with a realistic electron density gives a value of the EBE nearly identical to the EOM-CC result when using the same basis set. For the geometry at which the anion is bound in the HF approximation, the inclusion of triple excitations in the EOM-CC calculations is much less important. The best estimate EOM-CC EBE value is in good agreement with the results of DMC calculations with appropriate trial wave functions.

Upadhyay, Shiv (ORCID:0000000285010501)↗
DOE OSTI2026

Neural Network‐Based Methods for Ocean Surface Wave Measurement Using Submarine Distributed Acoustic Sensing (DAS)

Two new data-driven models for estimating ocean surface waves from distributed acoustic sensing (DAS) submarine cable strain rate are developed using supervised machine learning on a 10-day data set collected offshore of Oliktok Point, Alaska. The new models were trained on target data from seafloor pressure moorings at three sites spaced evenly along 27.1 km of cable and were benchmarked against an empirical transfer function method previously used to estimate waves from DAS. A model which uses convolutional neural networks to transform 2-km frequency-wavenumber strain spectra to seafloor pressure spectra outperforms the benchmark in wave height prediction (RMSE of 0.15 vs. 0.41 m) and period prediction (0.29 vs. 0.37 s) when evaluated on a held-out test data set. When applied to a DAS data set collected on the same cable 2 years prior, the CNN-based model maintained similar significant wave height performance (RMSE = 0.23 m) relative to available satellite altimetry data. A two-hidden-layer, fully connected neural network which transforms 1-D strain spectra to seafloor pressure spectra also outperforms the benchmark in wave height prediction (RMSE of 0.19 vs. 0.41 m), but does not generalize as well to the prior data. Regression-based machine learning is useful for estimating waves from DAS data when the pressure-strain relationship varies temporally and spatially across different wave conditions. Models can be applied to DAS data to measure waves with higher spatial resolution and longer temporal coverage than traditional methods, which often measure waves only at a single point.

Davis, Jacob R. [Univ. of Washington, Seattle, WA ↗
DOE OSTI2014

Semi-analytic models for the CANDELS survey: comparison of predictions for intrinsic galaxy properties

We compare the predictions of three independently developed semi-analytic galaxy formation models (SAMs) that are being used to aid in the interpretation of results from the CANDELS survey. These models are each applied to the same set of halo merger trees extracted from the 'Bolshoi' high-resolution cosmological N-body simulation and are carefully tuned to match the local galaxy stellar mass function using the powerful method of Bayesian Inference coupled with Markov Chain Monte Carlo or by hand. The comparisons reveal that in spite of the significantly different parameterizations for star formation and feedback processes, the three models yield qualitatively similar predictions for the assembly histories of galaxy stellar mass and star formation over cosmic time. Comparing SAM predictions with existing estimates of the stellar mass function from z = 0-8, we show that the SAMs generally require strong outflows to suppress star formation in low-mass halos to match the present-day stellar mass function, as is the present common wisdom. However, all of the models considered produce predictions for the star formation rates (SFRs) and metallicities of low-mass galaxies that are inconsistent with existing data. The predictions for metallicity-stellar mass relations and their evolution clearly diverge between the models. We suggest that large differences in the metallicity relations and small differences in the stellar mass assembly histories of model galaxies stem from different assumptions for the outflow mass-loading factor produced by feedback. Importantly, while more accurate observational measurements for stellar mass, SFR and metallicity of galaxies at 1 < z < 5 will discriminate between models, the discrepancies between the constrained models and existing data of these observables have already revealed challenging problems in understanding star formation and its feedback in galaxy formation. The three sets of models are being used to construct catalogs of mock galaxies on light cones that have the same geometry as the CANDELS survey, which should be particularly useful for quantifying the biases and uncertainties on measurements and inferences from the real observations.

79 ASTRONOMY AND ASTROPHYSICS↗