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At least 1,585 records · Page 88

All sources NASA NTRS DOE OSTI

DOE OSTI2022

A measurement of stellar surface gravity hidden in radial velocity differences of comoving stars

The gravitational redshift induced by stellar surface gravity is notoriously difficult to measure for non-degenerate stars, since its amplitude is small in comparison with the typical Doppler shift induced by stellar radial velocity. In this study, we make use of the large observational data set of the Gaia mission to achieve a significant reduction of noise caused by these random stellar motions. By measuring the differences in velocities between the components of the pairs of comoving stars and wide binaries, in this work we are able to statistically measure the combined effects of gravitational redshift and convective blueshifting of spectral lines, and nullify the effect of the peculiar motions of the stars. For the subset of stars considered in this study, we find a positive correlation between the observed differences in Gaia radial velocities and the differences in surface gravity and convective blueshift inferred from effective temperature and luminosity measurements. The results rule out a null signal at the 5σ level for our full data set. Additionally, we study the subdominant effects of binary motion, and possible systematic errors in radial velocity measurements within Gaia. Results from the technique presented in this study are expected to improve significantly with data from the next Gaia data release. Such improvements could be used to constrain the mass–luminosity relation and stellar models that predict the magnitude of convective blueshift.

(stars:) binaries: general↗

DOE OSTI2017

( d , n ) proton-transfer reactions on Be 9 , B 11 , C 13 , N 14 , 15 , and F 19 and spectroscopic factors at E d = 16 MeV

The (d,n) reaction has been studied with targets of 9 Be, 11 B, 13 C, 14,15 N, and 19F at E d = 16MeV using a deuterated liquid-scintillator array. Advanced spectral unfolding techniques with accurately measured scintillator response functions were employed to extract neutron energy spectra without the need for long-path neutron time-of-flight. An analysis of the proton-transfer data at forward angles to the ground states of the final nuclei, using finite-range distorted-wave Born approximation analysis with common bound-state, global, and local optical-model parameter sets, yields a set of self-consistent spectroscopic factors. These are compared with the results of several previous time-of-flight measurements, most done many years ago for individual nuclei at lower energy and often analyzed using zero-range transfer codes. In contrast to some of the earlier published data, our data generally compare well with simple shell-model predictions, with little evidence for uniform quenching (reduction from shell-model values) that has previously been reported from analysis of nucleon knock-out reactions. Data for low-lying excited states in 14 N from 13 C(d,n) also is analyzed and spectroscopic information relevant to nuclear astrophysics obtained. Here, a preliminary study of the radioactive ion beam induced reaction 7 Be(d,n), E( 7 Be) = 30MeV was carried out and indicates further improvements are needed for such measurements, which require detection of neutrons with E n < 2MeV.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗

DOE OSTI2017

Goal-Oriented Optimal Approximations of Bayesian Linear Inverse Problems

We propose optimal dimensionality reduction techniques for the solution of goal-oriented linear-Gaussian inverse problems, where the quantity of interest (QoI) is a function of the inversion parameters. These approximations are suitable for large-scale applications. In particular, we study the approximation of the posterior covariance of the QoI as a low-rank negative update of its prior covariance and prove optimality of this update with respect to the natural geodesic distance on the manifold of symmetric positive definite matrices. Assuming exact knowledge of the posterior mean of the QoI, the optimality results extend to optimality in distribution with respect to the Kullback--Leibler divergence and the Hellinger distance between the associated distributions. We also propose the approximation of the posterior mean of the QoI as a low-rank linear function of the data and prove optimality of this approximation with respect to a weighted Bayes risk. Both of these optimal approximations avoid the explicit computation of the full posterior distribution of the parameters and instead focus on directions that are well informed by the data and relevant to the QoI. These directions stem from a balance among all the components of the goal-oriented inverse problem: prior information, forward model, measurement noise, and ultimate goals. We illustrate the theory using a high-dimensional inverse problem in heat transfer.

97 MATHEMATICS AND COMPUTING↗

NASA NTRS1973

Supply support of NASA tracking networks

The extent which supply support for Jet Propulsion Laboratory's Deep Space Network and Goddard Space Flight Center's Space Flight Tracking and Data Network should be consolidated is considered along with the Identification of opportunities for improvements in each of the supply systems without regard to consolidation. There is a considerable amount of commonality between the items in the stock catalogs at the two network depots, 58% for federal stock number items and 30% overall. The workload at the DSIF Supply Depot (DSD) is small (less than 20%) compared to the Network Logistics Depot (NLD). A number of important benefits in supply support would result from a consolidation of DSD into NLD. LMI found that a consolidation as is, without any changes in inventory management techniques, would reduce annual operating costs by from $208,000 to $358,000. However, if the consolidation were coupled with a change to use of economic order quantities, the annual operating cost reduction would range from $930,000 to $1,078,000.

Source record↗

NASA NTRS1992

A fundamental study of suction for Laminar Flow Control (LFC)

This report covers the period forming the first year of the project. The aim is to experimentally investigate the effects of suction as a technique for Laminar Flow Control. Experiments are to be performed which require substantial modifications to be made to the experimental facility. Considerable effort has been spent developing new high performance constant temperature hot-wire anemometers for general purpose use in the Fluid Mechanics Laboratory. Twenty instruments have been delivered. An important feature of the facility is that it is totally automated under computer control. Unprecedently large quantities of data can be acquired and the results examined using the visualization tools developed specifically for studying the results of numerical simulations on graphics works stations. The experiment must be run for periods of up to a month at a time since the data is collected on a point-by-point basis. Several techniques were implemented to reduce the experimental run-time by a significant factor. Extra probes have been constructed and modifications have been made to the traverse hardware and to the real-time experimental code to enable multiple probes to be used. This will reduce the experimental run-time by the appropriate factor. Hot-wire calibration drift has been a frustrating problem owing to the large range of ambient temperatures experienced in the laboratory. The solution has been to repeat the calibrations at frequent intervals. However the calibration process has consumed up to 40 percent of the run-time. A new method of correcting the drift is very nearly finalized and when implemented it will also lead to a significant reduction in the experimental run-time.

Watmuff, Jonathan H.↗

NASA NTRS2003

F/A-18 Performance Benefits Measured During the Autonomous Formation Flight Project

The Autonomous Formation Flight (AFF) project at the NASA Dryden Flight Research Center (Edwards, California) investigated performance benefits resulting from formation flight, such as reduced aerodynamic drag and fuel consumption. To obtain data on performance benefits, a trailing F/A-18 airplane flew within the wing tip-shed vortex of a leading F/A-18 airplane. The pilot of the trail airplane used advanced station-keeping technology to aid in positioning the trail airplane at precise locations behind the lead airplane. The specially instrumented trail airplane was able to obtain accurate fuel flow measurements and to calculate engine thrust and vehicle drag. A maneuver technique developed for this test provided a direct comparison of performance values while flying in and out of the vortex. Based on performance within the vortex as a function of changes in vertical, lateral, and longitudinal positioning, these tests explored design-drivers for autonomous stationkeeping control systems. Observations showed significant performance improvements over a large range of trail positions tested. Calculations revealed maximum drag reductions of over 20 percent, and demonstrated maximum reductions in fuel flow of just over 18 percent.

Vachon, M. Jake↗

NASA NTRS2011

Carbon Isotope Systematics in Mineral-Catalyzed Hydrothermal Organic Synthesis Processes at High Temperature and Pressures

Observation of methane in the Martian atmosphere has been reported by different detection techniques. Reduction of CO2 and/or CO during serpentization by mineral surface catalyzed Fischer-Tropsch Type (FTT) synthesis may be one possible process responsible for methane generation on Mars. With the evidence a recent study has discovered for serpentinization in deeply buried carbon rich sediments, and more showing extensive water-rock interaction in Martian history, it seems likely that abiotic methane generation via serpentinization reactions may have been common on Mars. Experiments involving mineral-catalyzed hydrothermal organic synthesis processes were conducted at 750 C and 5.5 Kbars. Alkanes, alcohols and carboxylic acids were identified as organic compounds. No "isotopic reversal" of delta C-13 values was observed for alkanes or carboxylic acids, suggesting a different reaction pathway than polymerization. Alcohols were proposed as intermediaries formed on mineral surfaces at experimental conditions. Carbon isotope data were used in this study to unravel the reaction pathways of abiotic formation of organic compounds in hydrothermal systems at high temperatures and pressures. They are instrumental in constraining the origin and evolution history of organic compounds on Mars and other planets.

Fu, Qi↗

NASA NTRS1983

Data processing techniques used with MST radars: A review

The data processing methods used in high power radar probing of the middle atmosphere are examined. The radar acts as a spatial filter on the small scale refractivity fluctuations in the medium. The characteristics of the received signals are related to the statistical properties of these fluctuations. A functional outline of the components of a radar system is given. Most computation intensive tasks are carried out by the processor. The processor computes a statistical function of the received signals, simultaneously for a large number of ranges. The slow fading of atmospheric signals is used to reduce the data input rate to the processor by coherent integration. The inherent range resolution of the radar experiments can be improved significant with the use of pseudonoise phase codes to modulate the transmitted pulses and a corresponding decoding operation on the received signals. Commutability of the decoding and coherent integration operations is used to obtain a significant reduction in computations. The limitations of the processors are outlined. At the next level of data reduction, the measured function is parameterized by a few spectral moments that can be related to physical processes in the medium. The problems encountered in estimating the spectral moments in the presence of strong ground clutter, external interference, and noise are discussed. The graphical and statistical analysis of the inferred parameters are outlined. The requirements for special purpose processors for MST radars are discussed.

Rastogi, P. K.↗

DOE OSTI2020

Milestone 2.7: Evaluation of Techniques for the Measurement of Molecular Hydrogen Gas in Helium Matrices

Published data by Task 2 (Oxyhydroxide Layer Radiolytic Gas Generation Resolution) for Technical Considerations and Challenges for Extended (>50 yrs) Dry Storage of Aluminum Cladded Spent Nuclear Fuel (ASNF), demonstrated that radiolytic molecular hydrogen (H2) production from gamma irradiated aluminum alloy 1100 (Al-1100) coupons exhibited significant dependence on backfill gaseous environment conditions: air, due to the presence of oxygen, completely inhibited H2 production; nitrogen promoted H2 production; and argon yielded more H2 than nitrogen environments. The concern here is that helium has been proposed as the backfill gas for extended storage and is more inert than argon, which may translate into significantly more H2 production than current Task 3 argon-based models predict. However, the measurement of H2 in helium media was not possible using the previously establish gas chromatography (GC) flame ionization detector, due to similarities in thermal conductivity. This milestone was initiated to evaluate an alternative GC approach that employed a mercuric oxide (HgO) reduction gas detector (RGD). Using the HgO RGD setup, H2 was successfully calibrated in the presence of a helium carrier gas, and then subsequently measured in control and irradiated crush-tube sample vials, consistent with previous sample measurements. Overall, the HgO RGD approach was found to be sufficient for future helium environment irradiations.

38 RADIATION CHEMISTRY, RADIOCHEMISTRY, AND NUCLEA↗

DOE OSTI2019

Machine-learning error models for approximate solutions to parameterized systems of nonlinear equations

Here, this work proposes a machine-learning framework for constructing statistical models of errors incurred by approximate solutions to parameterized systems of nonlinear equations. These approximate solutions may arise from early termination of an iterative method, a lower-fidelity model, or a projection-based reduced-order model, for example. The proposed statistical model comprises the sum of a deterministic regression-function model and a stochastic noise model. The method constructs the regression-function model by applying regression techniques from machine learning (e.g., support vector regression, artificial neural networks) to map features (i.e., error indicators such as sampled elements of the residual) to a prediction of the approximate-solution error. The method constructs the noise model as a mean-zero Gaussian random variable whose variance is computed as the sample variance of the approximate-solution error on a test set; this variance can be interpreted as the epistemic uncertainty introduced by the approximate solution. This work considers a wide range of feature-engineering methods, data-set-construction techniques, and regression techniques that aim to ensure that (1) the features are cheaply computable, (2) the noise model exhibits low variance (i.e., low epistemic uncertainty introduced), and (3) the regression model generalizes to independent test data. Finally, numerical experiments performed on several computational-mechanics problems and types of approximate solutions demonstrate the ability of the method to generate statistical models of the error that satisfy these criteria and significantly outperform more commonly adopted approaches for error modeling.

97 MATHEMATICS AND COMPUTING↗

DOE OSTI2025

Personalized and uncertainty-aware coronary hemodynamics simulations: From Bayesian estimation to improved multi-fidelity uncertainty quantification

Non-invasive simulations of coronary hemodynamics have improved clinical risk stratification and treatment outcomes for coronary artery disease, compared to relying on anatomical imaging alone. However, simulations typically use empirical approaches to distribute total coronary flow amongst the arteries in the coronary tree, which ignores patient variability, the presence of disease, and other clinical factors. Further, uncertainty in the clinical data often remains unaccounted for in the modeling pipeline. We present an end-to-end uncertainty-aware pipeline to (1) personalize coronary flow simulations by incorporating vessel-specific coronary flows as well as cardiac function; and (2) predict clinical and biomechanical quantities of interest with improved precision, while accounting for uncertainty in the clinical data. We assimilate patient-specific measurements of myocardial blood flow from clinical CT myocardial perfusion imaging to estimate branch-specific coronary artery flows. Simulated noise in the clinical data is used to estimate the joint posterior distributions of the model parameters using adaptive Markov Chain Monte Carlo sampling. Additionally, the posterior predictive distribution for the relevant quantities of interest is determined using a new approach combining multi-fidelity Monte Carlo estimation with non-linear, data-driven dimensionality reduction. This leads to improved correlations between high- and low-fidelity model outputs. Our framework accurately recapitulates clinically measured cardiac function as well as branch-specific coronary flows under measurement noise uncertainty. We observe substantial reductions in confidence intervals for estimated quantities of interest compared to single-fidelity Monte Carlo estimation and state-of-the-art multi-fidelity Monte Carlo methods. This holds especially true for quantities of interest that showed limited correlation between the low- and high-fidelity model predictions. In addition, the proposed multi-fidelity Monte Carlo estimators are significantly cheaper to compute than traditional estimators, under a specified confidence level or variance. The proposed pipeline for personalized and uncertainty-aware predictions of coronary hemodynamics is based on routine clinical measurements and recently developed techniques for CT myocardial perfusion imaging. The proposed pipeline offers significant improvements in precision and reduction in computational cost.

Bayesian parameter estimation↗

DOE OSTI2022

Scalable training of graph convolutional neural networks for fast and accurate predictions of HOMO-LUMO gap in molecules

Abstract Graph Convolutional Neural Network (GCNN) is a popular class of deep learning (DL) models in material science to predict material properties from the graph representation of molecular structures. Training an accurate and comprehensive GCNN surrogate for molecular design requires large-scale graph datasets and is usually a time-consuming process. Recent advances in GPUs and distributed computing open a path to reduce the computational cost for GCNN training effectively. However, efficient utilization of high performance computing (HPC) resources for training requires simultaneously optimizing large-scale data management and scalable stochastic batched optimization techniques. In this work, we focus on building GCNN models on HPC systems to predict material properties of millions of molecules. We use HydraGNN, our in-house library for large-scale GCNN training, leveraging distributed data parallelism in PyTorch. We use ADIOS, a high-performance data management framework for efficient storage and reading of large molecular graph data. We perform parallel training on two open-source large-scale graph datasets to build a GCNN predictor for an important quantum property known as the HOMO-LUMO gap. We measure the scalability, accuracy, and convergence of our approach on two DOE supercomputers: the Summit supercomputer at the Oak Ridge Leadership Computing Facility (OLCF) and the Perlmutter system at the National Energy Research Scientific Computing Center (NERSC). We present our experimental results with HydraGNN showing (i) reduction of data loading time up to 4.2 times compared with a conventional method and (ii) linear scaling performance for training up to 1024 GPUs on both Summit and Perlmutter.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

NASA NTRS2014

Experimental Investigation of a Flexible Wing with a Variable Camber Continuous Trailing Edge Flap Design

This paper presents experimental results of a flexible wing wind tunnel model with a variable camber continuous trailing edge flap (VCCTEF) design for drag minimization, tested at the University of Washington Aeronautical Labo- ratory (UWAL). The wind tunnel test was designed to explore the relative merit of the VCCTEF concept for improved cruise efficiency through the use of low-cost aeroelastic model test techniques. The flexible wing model is a 10-scaled model of a typical transport wing and is constructed of woven fabric composites and foam core. The wing structural stiffness in bending is tailored to be half of the stiffness of a Boeing 757-era transport wing, while the torsional stiffness is about the same. This stiffness reduction results in a wing tip deflection of about 10 of the wing semi-span. The VCCTEF is a multi-segment flap design having three chordwise camber segments and five spanwise flap sections for a total of 15 individual flap elements. The three chordwise camber segments can be positioned appropriately to create a desired trailing edge camber. Elastomeric material is used to cover the gaps in between the spanwise flap sections, thereby creating a continuous trailing edge. Wind tunnel data indicate a high degree of data correlation and repeata- bility. The VCCTEF can achieve a drag reduction of up to 6.31 and an improvement in the lift-to-drag ratio (LD) of up to 4.85. The paper also presents two methods for estimating the lift coefficient of a rigid wing using a dynamic pressure correction and an aeroelastic deflection correction. Both methods provide good estimates of the rigid-wing lift coefficient.

Aerodynamics↗

NASA NTRSDate not supplied

Hydrogen Plasma Reduction of Silicates for Lunar Oxygen Liberation

As crewed missions to the moon become closer, the focus on in-situ resource utilization efforts has increased. Since lunar soil has abundant oxygen on the surface of the moon, work has been done to process this resource in an efficient manner. Hydrogen reduction of lunar regolith has emerged as a method of liberating oxygen that can be used for fuel and water production. Traditional reduction techniques require high temperatures and increased complexity when dealing with high amounts of silicates. Plasma can reduce silicates efficiently and thus has become of high interest for use in the lunar highlands where silicates exist in high quantities. NASA’s Kennedy Space Center is exploring the use of low temperature plasmas for the reduction of silicates. This work shows that exposing silicates to a hydrogen plasma produces water. Residual gas analysis and optical emission spectroscopy were used to measure the relative quantities of water vapor production and OH (A-X) emission for hydrogen plasma interactions with lunar highland simulant and silica. X-ray photo-electron spectroscopy and scanning electron microscopy/energy-dispersive X-ray spectroscopy were also used to observe surface modifications to the silicates that reflect the key chemical reactions that occurred. From this data, plasma has emerged as a promising solution to produce oxygen on the lunar surface. *Work supported by NASA's Science Technology Mission Directorate Center Innovation Fund.

R. P. Gott↗

NASA NTRSDate not supplied

Plasma Reduction of Regolith for Oxygen Liberation

Ryan Gott↗

DOE OSTI2018

Lensing reconstruction in post-Born cosmic microwave background weak lensing

The study of the cosmic microwave background (CMB) lensing potential has established itself by now as a robust way of probing the physics of large-scale structure growth. The most common estimators of the lensing potential are derived under the assumption of Gaussianity of the matter distribution and in the Born approximation of the photon diffusion. In this paper we study the performance of quadratic estimators when applied to realistic sky maps extracted from multiple-lens ray tracing techniques in cosmological $N$-body simulations. These are expected to model accurately the effects due to the non-Gaussianity of the matter distribution induced by its nonlinearity and the deviation from the Born approximation. We show that both these effects on their own lead to reconstruction biases, but these tend to partially cancel each other when both these effects are considered together. We forecast the impact of these biases on the estimation of cosmological parameters for future high-sensitivity CMB experiments like CMB-S4. We find that the cold dark matter density, $Ω_{cdm}$, the optical depth to reionization $τ$, the amplitude of primordial inflationary perturbations, $A_s$, and the sum of neutrino masses, $M_ν$, could be biased at the $1–2σ$ level, if no external data set is used. We also observe a reduction of the bias if external data like baryon acoustic oscillations is included.

79 ASTRONOMY AND ASTROPHYSICS↗

NASA NTRS2001

Routine detection of Epstein-Barr virus specific T-cells in the peripheral blood by flow cytometry

The ability to detect cytomegalovirus-specific T-cells (CD4(+)) in the peripheral blood by flow cytometry has been recently described by Picker et al. In this method, cells are incubated with viral antigen and responding (cytokine producing) T-cells are then identified by flow cytometry. To date, this technique has not been reliably used to detect Epstein-Barr virus (EBV)-specific T-cells primarily due to the superantigen/mitogenic properties of the virus which non-specifically activate T-cells. By modifying culture conditions under which the antigens are presented, we have overcome this limitation and developed an assay to detect and quantitate EBV-specific T-cells. The detection of cytokine producing T-cells by flow cytometry requires an extremely strong signal (such as culture in the presence of PMA and ionomycin). Our data indicate that in modified culture conditions (early removal of viral antigen) the non-specific activation of T-cells by EBV is reduced, but antigen presentation will continue uninhibited. Using this method, EBV-specific T-cells may be legitimately detected using flow cytometry. No reduction in the numbers of antigen-specific T-cells was observed by the early removal of target antigen when verified using cytomegalovirus antigen (a virus with no non-specific T-cell activation properties). In EBV-seropositive individuals, the phenotype of the EBV-specific cytokine producing T-cells was evaluated using four-color flow cytometry and found to be CD45(+), CD3(+), CD4(+), CD45RA(-), CD69(+), CD25(-). This phenotype indicates the stimulation of circulating previously unactivated memory T-cells. No cytokine production was observed in CD4(+) T-cells from EBV-seronegative individuals, confirming the specificity of this assay. In addition, the use of four color cytometry (CD45, CD3, CD69, IFNgamma/IL-2) allows the total quantitative assessment of EBV-specific T-cells while monitoring the interference of EBV non-specific mitogenic activity. This method may have significant utility for the monitoring of the immune response to latent virus infection/reactivation.

Non-NASA Center↗

NASA NTRS2011

Inter-Annual and Decadal Changes in Tropospheric and Stratospheric Ozone

Ozone data beginning October 2004 from the Aura Ozone Monitoring Instrument (OMI) and Aura Microwave Limb Sounder (MLS) are used to evaluate the accuracy of the Cloud slicing technique in effort to develop long data records of tropospheric and stratospheric ozone and studying their long-term changes. Using this technique, we have produced a 32-year (1979-2010) long record of tropospheric and stratospheric ozone from the combined Total Ozone Mapping Spectrometer (Toms) and OMI. The analyses of these time series suggest that the quasi-biennial oscillation (QBO) is the dominant source of inter-annual changes of 30-40 Dobson Units (DU). Tropospheric ozone also indicates a QBO signal in the peak to peak changes varying from 2 to 7 DU. Decadal changes in global stratospheric ozone indicate a turnaround in ozone loss around mid 1990's with most of these changes occurring in the Northern Hemisphere from the subtropics to high latitudes. The trend results are generally consistent with the prediction of chemistry climate models which include the reduction of ozone destroying substances beginning in the late 1980's mandated by the Montreal Protocol.

Ziemke, Jr. R.↗