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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 307 records · Page 17
All sourcesNASA NTRSDOE OSTI
NASA NTRS2005

Spreading of thermonuclear flames on the neutron star in SAX J1808.4-3658: an observational tool

We analyse archival Rossi X-Ray Timing Explorer (RXTE) proportional counter array (PCA) data of thermonuclear X-ray bursts from the 2002 outburst of the accreting millisecond pulsar SAX 51808.4-3658. We present evidence of a complex frequency modulation of oscillations during burst rise, and correlations among the time evolution of the oscillation frequency, amplitude, and the inferred burning region area. We discuss these findings in the context of a model, based on thermonuclear flame spreading on the neutron star surface, that can qualitatively explain these features. From our model, we infer that for the 2002 Oct. 15 thermonuclear burst, the ignition likely occurred in the mid-latitudes, the burning region took approx. 0.2 s to nearly encircle the equatorial region of the neutron star, and after that the lower amplitude oscillation originated from the remaining asymmetry of the burning front in the same hemisphere where the burst ignited. We emphasize that studies of the evolution of burst oscillation properties during burst rise can provide a powerful tool to understand thermonuclear flame spreading on neutron star surfaces under extreme physical conditions.

Bhattacharyya, Sudip↗
DOE OSTI2019

Investigation of high X-ray conversion efficiency Kr filled gas sources at the National Ignition Facility

In this work, we report on the performance of high x-ray fluence Kr K-shell sources that are being developed for high energy density experiments. These targets are 4.1 mm in diameter 4.4 mm tall hollow epoxy tubes having a 40 μm thick wall holding 1.5 atm of Kr gas. For these shots, the National Ignition Facility laser delivered a nominally constant total energy of ≈750 kJ of 351 nm (3ω) light at the three power levels [e.g., ≈120 (low), ≈145 (medium), and ≈210 TW (high)]. The Kr K-shell (E photon = 8–20 keV) x-ray radiant intensity and radiant energy (kJ/sr) of these sources were found to increase as a function of laser power but began to plateau at the highest laser power. The Kr K-shell radiant energy increased from ≈1 kJ/sr at ≈120 TW to ≈2 kJ/sr at ≈210 TW. Radiation hydrodynamics simulations predict radiant energies to be always higher than these measurements. The increase in K-shell emission is attributed to its strong dependence on the electron temperature. Electron temperature distributions were inferred from measured Heα and Lyα line emission through the use of a genetic algorithm and Scram modeling. The inferred temperatures from the experiment are 20% to 30% higher than those predicted from modeling.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2014

Full-wavefield inversion of surface waves for mapping embedded low-velocity zones in permafrost

Surface waves are advantageous for mapping seismic structures of permafrost, in which irregular velocity gradients are common and thus the effectiveness of refraction methods are limited. Nevertheless, the complex velocity structures that are common in permafrost environments often yield unusual dispersion spectra, in which higher-order and leaky modes are dominant. Such unusual dispersion spectra were prevalent in the multichannel surface-wave data acquired from our permafrost study site at Barrow, Alaska. Owing to the difficulties in picking and identifying dispersion curves from these dispersion spectra, conventional surface-wave inversion methods become problematic to apply. Here, to overcome these difficulties, we adopted a full-wavefield method to invert for velocity models that can best fit the dispersion spectra instead of the dispersion curves. The inferred velocity models were consistent with collocated electric resistivity results and with subsequent confirmation cores, which indicated the reliability of the recovered seismic structures. The results revealed embedded low-velocity zones underlying the ice-rich permafrost at our study site — an unexpected feature considering the low ground temperatures of - 10 ° C to - 8 ° C . The low velocities in these zones ( ~ 70 % – 80 % lower than the overlying ice-rich permafrost) were most likely caused by saline pore-waters that prevent the ground from freezing, and the resultant velocity structures are vivid examples of complex subsurface properties in permafrost terrain. Finally, we determined that full-wavefield inversion of surface waves, although carrying higher computational costs than conventional methods, can be an effective tool for delineating the seismic structures of permafrost.

58 GEOSCIENCES↗
DOE OSTI2015

SU-E-T-144: Bayesian Inference of Local Relapse Data Using a Poisson-Based Tumour Control Probability Model

Purpose: The purpose of this project is to develop a robust method of parameter estimation for a Poisson-based TCP model using Bayesian inference. Methods: Bayesian inference was performed using the PyMC3 probabilistic programming framework written in Python. A Poisson-based TCP regression model that accounts for clonogen proliferation was fit to observed rates of local relapse as a function of equivalent dose in 2 Gy fractions for a population of 623 stage-I non-small-cell lung cancer patients. The Slice Markov Chain Monte Carlo sampling algorithm was used to sample the posterior distributions, and was initiated using the maximum of the posterior distributions found by optimization. The calculation of TCP with each sample step required integration over the free parameter α, which was performed using an adaptive 24-point Gauss-Legendre quadrature. Convergence was verified via inspection of the trace plot and posterior distribution for each of the fit parameters, as well as with comparisons of the most probable parameter values with their respective maximum likelihood estimates. Results: Posterior distributions for α, the standard deviation of α (σ), the average tumour cell-doubling time (Td), and the repopulation delay time (Tk), were generated assuming α/β = 10 Gy, and a fixed clonogen density of 10{sup 7} cm−{sup 3}. Posterior predictive plots generated from samples from these posterior distributions are in excellent agreement with the observed rates of local relapse used in the Bayesian inference. The most probable values of the model parameters also agree well with maximum likelihood estimates. Conclusion: A robust method of performing Bayesian inference of TCP data using a complex TCP model has been established.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2013

Effects of error covariance structure on estimation of model averaging weights and predictive performance

When conducting model averaging for assessing groundwater conceptual model uncertainty, the averaging weights are often evaluated using model selection criteria such as AIC, AICc, BIC, and KIC (Akaike Information Criterion, Corrected Akaike Information Criterion, Bayesian Information Criterion, and Kashyap Information Criterion, respectively). However, this method often leads to an unrealistic situation in which the best model receives overwhelmingly large averaging weight (close to 100%), which cannot be justified by available data and knowledge. It was found in this study that this problem was caused by using the covariance matrix, CE, of measurement errors for estimating the negative log likelihood function common to all the model selection criteria. This problem can be resolved by using the covariance matrix, Cek, of total errors (including model errors and measurement errors) to account for the correlation between the total errors. An iterative two-stage method was developed in the context of maximum likelihood inverse modeling to iteratively infer the unknown Cek from the residuals during model calibration. The inferred Cek was then used in the evaluation of model selection criteria and model averaging weights. While this method was limited to serial data using time series techniques in this study, it can be extended to spatial data using geostatistical techniques. The method was first evaluated in a synthetic study and then applied to an experimental study, in which alternative surface complexation models were developed to simulate column experiments of uranium reactive transport. It was found that the total errors of the alternative models were temporally correlated due to the model errors. The iterative two-stage method using Cek resolved the problem that the best model receives 100% model averaging weight, and the resulting model averaging weights were supported by the calibration results and physical understanding of the alternative models. Using Cek obtained from the iterative two-stage method also improved predictive performance of the individual models and model averaging in both synthetic and experimental studies.

error correlation↗
DOE OSTI2015

Analysis of calibration data for the uranium active neutron coincidence counting collar with attention to errors in the measured neutron coincidence rate

The declared linear density of 238 U and 235 U in fresh low enriched uranium light water reactor fuel assemblies can be verified for nuclear safeguards purposes using a neutron coincidence counter collar in passive and active mode, respectively. The active mode calibration of the Uranium Neutron Collar - Light water reactor fuel (UNCL) instrument is normally performed using a non-linear fitting technique. The fitting technique relates the measured neutron coincidence rate (the predictor) to the linear density of 235 U (the response) in order to estimate model parameters of the nonlinear Parte equation, which traditionally is used to model the calibration data. Alternatively, following a simple data transformation, the fitting can also be performed using standard linear fitting methods. This article compares performance of the nonlinear technique to the linear technique, using a range of possible error variance magnitudes in the measured neutron coincidence rate. We develop the required formalism and then apply the traditional (nonlinear) and alternative approaches (linear) to the same experimental and corresponding simulated representative datasets. Here, we find that, in this context, because of the magnitude of the errors in the predictor, it is preferable not to transform to a linear model, and it is preferable not to adjust for the errors in the predictor when inferring the model parameters.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
NASA NTRS2011

Deducing Electron Properties from Hard X-Ray Observations

X-radiation from energetic electrons is the prime diagnostic of flare-accelerated electrons. The observed X-ray flux (and polarization state) is fundamentally a convolution of the cross-section for the hard X-ray emission process(es) in question with the electron distribution function, which is in turn a function of energy, direction, spatial location and time. To address the problems of particle propagation and acceleration one needs to infer as much information as possible on this electron distribution function, through a deconvolution of this fundamental relationship. This review presents recent progress toward this goal using spectroscopic, imaging and polarization measurements, primarily from the Reuven Ramaty High Energy Solar Spectroscopic Imager (RHESSI). Previous conclusions regarding the energy, angular (pitch angle) and spatial distributions of energetic electrons in solar flares are critically reviewed. We discuss the role and the observational evidence of several radiation processes: free-free electron-ion, free-free electron-electron, free-bound electron-ion, photoelectric absorption and Compton backscatter (albedo), using both spectroscopic and imaging techniques. This unprecedented quality of data allows for the first time inference of the angular distributions of the X-ray-emitting electrons and improved model-independent inference of electron energy spectra and emission measures of thermal plasma. Moreover, imaging spectroscopy has revealed hitherto unknown details of solar flare morphology and detailed spectroscopy of coronal, footpoint and extended sources in flaring regions. Additional attempts to measure hard X-ray polarization were not sufficient to put constraints on the degree of anisotropy of electrons, but point to the importance of obtaining good quality polarization data in the future.

Kontar, E. P.↗
NASA NTRS2016

Rough Surfaces: Is the Dark Stuff Just Shadow?: "Who knows what evil lurks in the hearts of men? The shadow knows!"

Remote observations of the surfaces of airless planetary objects are fundamental to inferring the physical structure and compositional makeup of the surface material. A number of forward models have been developed to reproduce the photometric behavior of these surfaces, based on specific, assumed structural properties such as macroscopic roughness and associated shadowing. Most work of this type is applied to geometric albedos, which are affected by complicated effects near zero phase angle that represent only a tiny fraction of the net energy reflected by the object. Other applications include parameter fits to resolved portions of some planetary surface as viewed over a range of geometries. The spherical albedo of the entire object (when it can be determined) captures the net energy balance of the particle more robustly than the geometric albedo. In most treatments involving spherical albedos, spherical albedos and particle phase functions are often treated as if they are independent, neglecting the effects of roughness. In this paper we take a different approach. We note that whatever function captures the phase angle dependence of the brightness of a realistic rough, shadowed, flat surface element relative to that of a smooth granular surface of the same material, it is manifested directly in both the integral phase function and the spherical albedo of the object. We suggest that, where broad phase angle coverage is possible, spherical albedos may be easily corrected for the effects of shadowing using observed (or assumed) phase functions, and then modeled more robustly using smooth-surface regolith radiative transfer models without further imposed (forward-modeled) shadowing corrections. Our approach attributes observed "power law" phase functions of various slope (and "linear" ranges of magnitude-vs.-phase angle) to shadowing, as have others, and goes on to suggest that regolith-model-based inferences of composition based on shadow-uncorrected spherical albedos overestimate the amount of absorbing material contained in the regolith.

geometric albedos↗
DOE OSTI2022

Uncertainty Analysis in Multi‐Sector Systems: Considerations for Risk Analysis, Projection, and Planning for Complex Systems

Abstract Simulation models of multi‐sector systems are increasingly used to understand societal resilience to climate and economic shocks and change. However, multi‐sector systems are also subject to numerous uncertainties that prevent the direct application of simulation models for prediction and planning, particularly when extrapolating past behavior to a nonstationary future. Recent studies have developed a combination of methods to characterize, attribute, and quantify these uncertainties for both single‐ and multi‐sector systems. Here, we review challenges and complications to the idealized goal of fully quantifying all uncertainties in a multi‐sector model and their interactions with policy design as they emerge at different stages of analysis: (a) inference and model calibration; (b) projecting future outcomes; and (c) scenario discovery and identification of risk regimes. We also identify potential methods and research opportunities to help navigate the tradeoffs inherent in uncertainty analyses for complex systems. During this discussion, we provide a classification of uncertainty types and discuss model coupling frameworks to support interdisciplinary collaboration on multi‐sector dynamics (MSD) research. Finally, we conclude with recommendations for best practices to ensure that MSD research can be properly contextualized with respect to the underlying uncertainties.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2015

TU-CD-BRA-05: Atlas Selection for Multi-Atlas-Based Image Segmentation Using Surrogate Modeling

Purpose: The growing size and heterogeneity in training atlas necessitates sophisticated schemes to identify only the most relevant atlases for the specific multi-atlas-based image segmentation problem. This study aims to develop a model to infer the inaccessible oracle geometric relevance metric from surrogate image similarity metrics, and based on such model, provide guidance to atlas selection in multi-atlas-based image segmentation. Methods: We relate the oracle geometric relevance metric in label space to the surrogate metric in image space, by a monotonically non-decreasing function with additive random perturbations. Subsequently, a surrogate’s ability to prognosticate the oracle order for atlas subset selection is quantified probabilistically. Finally, important insights and guidance are provided for the design of fusion set size, balancing the competing demands to include the most relevant atlases and to exclude the most irrelevant ones. A systematic solution is derived based on an optimization framework. Model verification and performance assessment is performed based on clinical prostate MR images. Results: The proposed surrogate model was exemplified by a linear map with normally distributed perturbation, and verified with several commonly-used surrogates, including MSD, NCC and (N)MI. The derived behaviors of different surrogates in atlas selection and their corresponding performance in ultimate label estimate were validated. The performance of NCC and (N)MI was similarly superior to MSD, with a 10% higher atlas selection probability and a segmentation performance increase in DSC by 0.10 with the first and third quartiles of (0.83, 0.89), compared to (0.81, 0.89). The derived optimal fusion set size, valued at 7/8/8/7 for MSD/NCC/MI/NMI, agreed well with the appropriate range [4, 9] from empirical observation. Conclusion: This work has developed an efficacious probabilistic model to characterize the image-based surrogate metric on atlas selection. Analytical insights lead to valid guiding principles on fusion set size design.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗
DOE OSTI2016

MERGERS AND STAR FORMATION: THE ENVIRONMENT AND STELLAR MASS GROWTH OF THE PROGENITORS OF ULTRA-MASSIVE GALAXIES SINCE Z = 2

The growth of galaxies is a key problem in understanding the structure and evolution of the universe. Galaxies grow their stellar mass by a combination of star formation and mergers, with a relative importance that is redshift dependent. Theoretical models predict quantitatively different contributions from the two channels; measuring these from the data is a crucial constraint. Exploiting the UltraVISTA catalog and a unique sample of progenitors of local ultra-massive galaxies selected with an abundance matching approach, we quantify the role of the two mechanisms from z = 2 to 0. We also compare our results to two independent incarnations of semi-analytic models. At all redshifts, progenitors are found in a variety of environments, ranging from being isolated to having 5–10 companions with mass ratio at least 1:10 within a projected radius of 500 kpc. In models, progenitors have a systematically larger number of companions, entailing a larger mass growth for mergers than in observations, at all redshifts. Generally, in both observations and models, the inferred and the expected mass growth roughly agree, within the uncertainties. Overall, our analysis confirms the model predictions, showing how the growth history of massive galaxies is dominated by in situ star formation at z ∼ 2, both star formation and mergers at 1 < z < 2, and by mergers alone at z < 1. Nonetheless, detailed comparisons still point out tensions between the expected mass growth and our results, which might be due to either an incorrect progenitors-descendants selection, uncertainties on star-formation rate and mass estimates, or the adopted assumptions on merger rates.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2019

Cosmic distance inference from purely geometric BAO methods: Linear point standard ruler and correlation function model fitting

Leveraging the baryon acoustic oscillations (BAO) feature present in clustering 2-point statistics, we aim to measure cosmological distances independently of the underlying background cosmological model. However this inference is complicated by late-time nonlinearities that introduce model and tracer dependencies in the clustering correlation function and power spectrum, which must be properly accounted for. With this in mind, we introduce the “purely geometric-BAO,” which provides a rigorous tool to measure cosmological distances without assuming a specific background cosmology. We focus on the 2-point clustering correlation function monopole, and show how to implement such an inference scheme employing two different methodologies: the linear point standard ruler (LP) and correlation-function model-fitting (CF-MF). For the first time we demonstrate how, by means of the CF-MF, we can measure very precisely the sound-horizon/isotropic-volume-distance ratio, r d /DV(z¯), while correctly propagating all the uncertainties. Using synthetic data, we compare the outcomes of the two methodologies, and find that the LP provides up to 50% more precise measurements than the CF-MF. Finally, we test a procedure widely employed in BAO analyses: fitting the 2-point function while fixing the cosmological and the non-linear-damping parameters at fiducial values. We find that this underestimates the distance errors by nearly a factor of 2. Furthermore, we recommend that this practice be reconsidered, whether for parameter determination or model selection.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2013

A COSMIC MICROWAVE BACKGROUND LENSING MASS MAP AND ITS CORRELATION WITH THE COSMIC INFRARED BACKGROUND

We use a temperature map of the cosmic microwave background (CMB) obtained using the South Pole Telescope at 150 GHz to construct a map of the gravitational convergence to z {approx} 1100, revealing the fluctuations in the projected mass density. This map shows individual features that are significant at the {approx}4{sigma} level, providing the first image of CMB lensing convergence. We cross-correlate this map with Herschel/SPIRE maps covering 90 deg{sup 2} at wavelengths of 500, 350, and 250 {mu}m. We show that these submillimeter (submm) wavelength maps are strongly correlated with the lensing convergence map, with detection significances in each of the three submm bands ranging from 6.7{sigma} to 8.8{sigma}. We fit the measurement of the cross power spectrum assuming a simple constant bias model and infer bias factors of b = 1.3-1.8, with a statistical uncertainty of 15%, depending on the assumed model for the redshift distribution of the dusty galaxies that are contributing to the Herschel/SPIRE maps.

79 ASTRONOMY AND ASTROPHYSICS↗
NASA NTRS2012

Polarimetric Imaging of Large Cavity Structures in the Pre-transitional Protoplanetary Disk around PDS 70: Observations of the Disk

We present high resolution H-band polarized intensity (PI; FWHM = 0."1: 14 AU) and L'-band imaging data (FWHM = 0."11: 15 AU) of the circumstellar disk around the weak-lined T Tauri star PDS 70 in Centaurus at a radial distance of 28 AU (0."2) up to 210 AU (1."5). In both images, a giant inner gap is clearly resolvro for the first time, and the radius of the gap is approx 70 AU. Our data show that the geometric center of the disk shifts by approx 6 AU toward the minor axis. We confirm that the brown dwarf companion candidate to the north of PDS 70 is a background star based on its proper motion. As a result of SED fitting by Monte Carlo radiative transfer modeling, we infer the existence of an optically thick inner disk at a few AU. Combining our observations and modeling, we classify the disk of PDS 70 as a pre-transitional disk. Furthermore, based on the analysis of L'-band imaging data, we put an upper limit mass of companions at approx 30 to approx 50M(sub J) within the gap. Taking account of the presence of the large and sharp gap, we suggest that the gap could be formed by dynamical interactions of sub-stellar companions or multiple unseen giant planets in the gap.

Hashimoto, J.↗
NASA NTRS2012

Polarimetric Imaging of Large Cavity Structures in the Pre-transitional Protoplanetary Disk Around PDS 70: Observations of the Disk

We present high resolution H-band polarized intensity (PI; FWHM = 0."1: 14 AU) and L'-band imaging data (FWHM = 0."11: 15 AU) of the circumstellar disk around the weak-lined T Tauri star PDS 70 in Centaurus at a radial distance of 28 AU (0."2) up to 210 AU (1."5). In both images, a giant inner gap is clearly resolved for the first time, and the radius of the gap is approx.70 AU. Our data show that the geometric center of the disk shifts by approx.6 AU toward the minor axis. We confirm that the brown dwarf companion candidate to the north of PDS 70 is a background star based on its proper motion. As a result of SED fitting by Monte Carlo radiative transfer modeling, we infer the existence of an optically thick inner disk at a few AU. Combining our observations and modeling, we classify the disk of PDS 70 as a pre-transitional disk. Furthermore, based on the analysis of L'-band imaging data, we put an upper limit mass of companions at approx.30 to approx.50MJ within the gap. Taking account of the presence of the large and sharp gap, we suggest that the gap could be formed by dynamical interactions of sub-stellar companions or multiple unseen giant planets in the gap. Subject headings: planetary systems - protoplanetary disks - stars: individual (PDS 70) - stars: pre-main sequence - polarization

Hashimoto, J.↗
NASA NTRS2012

Polarimetric Imaging of Large Cavity Structures in the Pre-transitional Protoplanetary Disk Around PDS 70: Observations of the Disk

We present high-resolution H-band polarized intensity (FWHM=0".1:14AU) and L'-band imaging data(FWHM= 0".11:15 AU) of the circumstellar disk around the weak-lined T Tauri star PDS 70 in Centaurus at a radial distance of 28 AU (0".2) up to 210 AU (1".5). In both images, a giant inner gap is clearly resolved for the first time, and the radius of the gap is approx.70 AU. Our data show that the geometric center of the disk shifts by approx.6 AU toward the minor axis. We confirm that the brown dwarf companion candidate to the north of PDS 70 is a background star based on its proper motion. As a result of spectral energy distribution fitting by Monte Carlo radiative transfer modeling, we infer the existence of an optically thick inner disk at a few AU. Combining our observations and modeling, we classify the disk of PDS 70 as a pre-transitional disk. Furthermore, based on the analysis of L'-band imaging data, we put an upper limit of approx.30 to approx.50 M(sub J) on the mass of companions within the gap. Taking into account the presence of the large and sharp gap, we suggest that the gap could be formed by dynamical interactions of sub-stellar companions or multiple unseen giant planets in the gap. Key words: planetary systems - polarization - protoplanetary disks - stars: individual (PDS 70) - stars: pre-main sequence.

Hashimoto, J.↗
DOE OSTI2024

Application of advanced causal analyses to identify processes governing secondary organic aerosols

Abstract Understanding how different physical and chemical atmospheric processes affect the formation of fine particles has been a persistent challenge. Inferring causal relations between the various measured features affecting the formation of secondary organic aerosol (SOA) particles is complicated since correlations between variables do not necessarily imply causality. Here, we apply a state-of-the-art information transfer measure coupled with the Koopman operator framework to infer causal relations between isoprene epoxydiol SOA (IEPOX-SOA) and different chemistry and meteorological variables derived from detailed regional model predictions over the Amazon rainforest. IEPOX-SOA represents one of the most complex SOA formation pathways and is formed by the interactions between natural biogenic isoprene emissions and anthropogenic emissions affecting sulfate, acidity and particle water. Since the regional model captures the known relations of IEPOX-SOA with different chemistry and meteorological features, their simulated time series implicitly include their causal relations. We show that our causal model successfully infers the known major causal relations between total particle phase 2-methyl tetrols (the dominant component of IEPOX-SOA over the Amazon) and input features. We provide the first proof of concept that the application of our causal model better identifies causal relations compared to correlation and random forest analyses performed over the same dataset. Our work has tremendous implications, as our methodology of causal discovery could be used to identify unknown processes and features affecting fine particles and atmospheric chemistry in the Earth’s atmosphere.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗