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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 487 records · Page 27
All sourcesNASA NTRSDOE OSTI
NASA NTRS2011

CALIPSO Detection of an Asian Tropopause Aerosol Layer

The first four years of the CALIPSO lidar measurements have revealed the existence of an aerosol layer at the tropopause level associated with the Asian monsoon season in June, July and August. This Asian Tropopause Aerosol Layer (ATAL) extends geographically from Eastern Mediterranean (down to North Africa) to Western China (down to Thailand), and vertically from 13 to 18 km. The Scattering Ratio inferred from CALIPSO shows values between 1.10. 1.15 on average with associated depolarization ratio of less than 5%. The Gaussian distribution of the points indicates that the mean value is statistically driven by an enhancement of the background aerosol level and not by episodic events such as a volcanic eruption or cloud contamination. Further satellite observations of aerosols and gases as well as field campaigns are urgently needed to characterize this layer, which is likely to be a significant source of non-volcanic aerosols for the global upper troposphere with a potential impact on its radiative and chemical balance

Vemier, J.-P.↗
DOE OSTI2022

Fast Gaussian Process Estimation for Large-Scale In Situ Inference using Convolutional Neural Networks

Exascale computing will bring with it significant I/O limitations. One foreseeable consequence of such restrictions is that the user can save only a small fraction of complex simulation data to disk for subsequent analysis. An alternative is to fit statistical models to data in situ, that is, inside the simulation as it runs. This option requires extremely fast statistical estimation to avoid slowing down the simulation. Gaussian processes (GPs) have state-of-the-art predictive performance for modeling spatial data. However, standard estimation methods for GPs scale quite poorly to large data sets as parameter estimation requires inverting a covariance matrix to the size of the data set. In the presented work, we use a convolutional neural network (CNN) to predict the GP parameters for a spatial data set, from a simulation or otherwise, rather than optimize the parameters directly. Here, our presented case study models spatial data from E3SM, the Department of Energy’s Exascale climate model. The CNN is trained on synthetic data simulated from GP models with known parameters and then applied to data from the climate simulation. In the presented examples, the neural network scheme produces parameter estimates that compare well with standard methods such as maximum likelihood estimation in predictive performance but is obtained four orders of magnitude faster.

big data↗
DOE OSTI2025

Quantification and prediction of solidification textures under additive manufacturing conditions

Crystallographic textures are a major determinant of the macroscale anisotropic properties of polycrystalline metallic alloys produced in a wide range of additive manufacturing (AM) processes. Here, we introduce a statistical method that can accurately quantify the degree of orientational order of textures despite the large random fluctuations in the orientation of individual grains inherent in AM processes. The method, demonstrated for laser and resolidification of AlSi thin films, extends Z-scoring to a dynamical regime to assess the statistical significance of observed textures compared to randomly generated ones at different stages of solidification. We further show that, combined with phase-field modeling, this method can be used to infer fundamental anisotropic properties of the solid-liquid interface that are essential for texture prediction, and are compared here to the results of atomistic simulations. In addition, phase-field modeling reveals that, even at rapid AM solidification rates, the observed 〈110〉-dominated textures in the AlSi thin films are controlled predominantly by the anisotropy of the interface free-energy and sheds light on the physical mechanism of grain competition. These results significantly enhance both the existing tools for the quantification and prediction of AM crystallographic textures and our basic understanding of their formation.

36 MATERIALS SCIENCE↗
DOE OSTI2024

Visible core spectroscopy at Wendelstein 7-X

This paper presents an overview of recent hardware extensions and data analysis developments to the Wendelstein 7-X visible core spectroscopy systems. These include upgrades to prepare the in-vessel components for long-pulse operation, nine additional spectrometers, a new line of sight array for passive spectroscopy, and a coherence imaging charge exchange spectroscopy diagnostic. Progress in data analysis includes ion temperatures and densities from multiple impurity species, a statistical comparison with x-ray crystal spectrometer measurements, neutral density measurements from thermal passive Balmer-alpha emission, and a Bayesian analysis of active hydrogen emission, which is able to infer electron density and main ion temperature profiles.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2022

Comparison of All Solid Cancer Mortality and Incidence Dose-Response in the Life Span Study of Atomic Bomb Survivors, 1958–2009

Recent analysis of all solid cancer incidence (1958–2009) in the Life Span Study (LSS) revealed evidence of upward curvature in the radiation dose response among males but not females. Upward curvature in sex-averaged excess relative risk (ERR) for all solid cancer mortality (1950–2003) was also observed in the 0–2 Gy dose range. As reasons for non-linearity in the LSS are not completely understood, we conducted dose response analyses for all solid cancer mortality and incidence applying similar methods (1958–2009 follow-up, DS02R1 doses, including subjects notin-city (NIC) at the time of the bombing) and statistical models. Incident cancers were ascertained from Hiroshima and Nagasaki cancer registries, while cause of death was ascertained from death certificates over entire Japan. The study included 105,444 LSS subjects who were alive and not known to have cancer before Jan 1, 1958 (80,205 with dose estimates and 25,239 NIC subjects). Between 1958 and 2009, there were 3.1 million person-years (PY) and 22,538 solid cancers for incidence analysis and 3.8 million PY and 15,419 solid cancer deaths for mortality analysis. We fitted sex-specific ERR models adjusted for smoking to both types of data. Over the entire range of doses, solid cancer mortality dose response exhibited a borderline significant upward curvature among males (P=0.062) and significant upward curvature among females (P=0.010); for solid cancer incidence, as before, we found a significant upward curvature among males (P=0.001) but not among females (P=0.624). The sex difference in magnitude of dose response curvature was statistically significant for cancer incidence (P=0.017) but not for cancer mortality (P=0.781). The results of analyses in the 0–2 Gy range and restricted lower dose ranges generally supported inferences made about the sex-specific dose response shape over the entire range of doses for each outcome. Patterns of sex-specific curvature by calendar period (1958–1987 vs 1988–2009) and age at exposure (0–19 vs 20–83) varied between mortality and incidence data, particularly among females, although for each outcome there was an indication of curvature among 0–19 year old male survivors in both calendar periods and among 0–19 year old female survivors in the recent period. Collectively, our findings indicate that the upward curvature in all solid cancer dose response in the LSS is neither specific to males nor to incidence data; it appears to depend on composition of case series and age at exposure or time. Further follow-up and site-specific analyses of cancer mortality and incidence will be important to confirm the emerging trend in dose response curvature among young survivors and unveil the contributing factors and sites.

63 RADIATION, THERMAL, AND OTHER ENVIRON. POLLUTAN↗
DOE OSTI2025

Analysis of Polarized Dust Emission Using Data from the First Flight of SPIDER

Using data from the first flight of Spider and from the Planck High Frequency Instrument, we probe the properties of polarized emission from interstellar dust in the Spider observing region. Component-separation algorithms operating in both the spatial and harmonic domains are applied to probe their consistency and to quantify modeling errors associated with their assumptions. Analyses of diffuse Galactic dust emission spanning the full Spider region demonstrate (i) a spectral energy distribution that is broadly consistent with a modified-blackbody (MBB) model with a spectral index of β d = 1.45 ± 0.05 (1.47 ± 0.06) for E (B)-mode polarization, slightly lower than that reported by Planck for the full sky; (ii) an angular power spectrum broadly consistent with a power law; and (iii) no significant detection of line-of-sight polarization decorrelation. Tests of several modeling uncertainties find only a modest impact (~10% in σ r ) on Spider's sensitivity to the cosmological tensor-to-scalar ratio. The size of the Spider region further allows for a statistically meaningful analysis of the variation in foreground properties within it. Assuming a fixed dust temperature T d = 19.6 K, an analysis of two independent subregions of that field results in inferred values of β d = 1.52 ± 0.06 and β d = 1.09 ± 0.09, which are inconsistent at the 3.9σ level. Furthermore, a joint analysis of Spider and Planck 217 and 353 GHz data within one subregion is inconsistent with a simple MBB at more than 3σ, assuming a common morphology of polarized dust emission over the full range of frequencies. This evidence of variation may inform the component-separation approaches of future cosmic microwave background polarization experiments.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2026

Robust Measurement of Stellar Streams around the Milky Way: Correcting Spatially Variable Observational Selection Effects in Optical Imaging Surveys

Observations of density variations in stellar streams are a promising probe of low-mass dark matter substructure in the Milky Way. However, survey systematics such as variations in seeing and sky brightness can also induce artificial fluctuations in the observed densities of known stellar streams. These variations arise because survey conditions affect both object detection and star–galaxy misclassification rates. To mitigate these effects, we use Balrog synthetic source injections in the Dark Energy Survey (DES) Y3 data to calculate detection rate variations and classification rates as functions of survey properties. We show that these rates are nearly separable with respect to survey properties and can be estimated with sufficient statistics from the synthetic catalogs. Applying these corrections reduces the standard deviation of relative detection rates across the DES footprint by a factor of 5, and our corrections significantly change the inferred linear density of the Phoenix stream when including faint objects. Additionally, for artificial streams with DES-like survey properties we are able to recover density power spectra with reduced bias. We also find that uncorrected power-spectrum results for Legacy Survey of Space and Time (LSST)-like data can be around 5 times more biased, highlighting the need for such corrections in future ground-based surveys.

79 ASTRONOMY AND ASTROPHYSICS↗
NASA NTRS1981

Information theory lateral density distribution for Earth inferred from global gravity field

Information Theory Inference, better known as the Maximum Entropy Method, was used to infer the lateral density distribution inside the Earth. The approach assumed that the Earth consists of indistinguishable Maxwell-Boltzmann particles populating infinitesimal volume elements, and followed the standard methods of statistical mechanics (maximizing the entropy function). The GEM 10B spherical harmonic gravity field coefficients, complete to degree and order 36, were used as constraints on the lateral density distribution. The spherically symmetric part of the density distribution was assumed to be known. The lateral density variation was assumed to be small compared to the spherically symmetric part. The resulting information theory density distribution for the cases of no crust removed, 30 km of compensated crust removed, and 30 km of uncompensated crust removed all gave broad density anomalies extending deep into the mantle, but with the density contrasts being the greatest towards the surface (typically + or 0.004 g cm 3 in the first two cases and + or - 0.04 g cm 3 in the third). None of the density distributions resemble classical organized convection cells. The information theory approach may have use in choosing Standard Earth Models, but, the inclusion of seismic data into the approach appears difficult.

Rubincam, D. P.↗
NASA NTRS1986

A study of gravity-wave spectra in the troposphere and stratosphere at 5-min to 5-day periods with the Poker Flat MST radar

An analysis of frequency spectra at periods of about 5 days to 5 min from two 20-day sets of velocity measurements in the stratosphere and troposphere region obtained with the Poker Flat mesosphere-stratosphere-troposphere (MST) radar during January and June, 1984 is presented. A technique based on median filtering and averaged order statistics for automatic editing, smoothing and spectral analysis of velocity time series contaminated with spurious data points or outliers is outlined. The validity of this technique and its effects on the inferred spectral index was tested through simulation. Spectra obtained with this technique are discussed. The measured spectral indices show variability with season and height, especially across the tropopause. The discussion briefly outlines the need for obtaining better climatologies of velocity spectra and for the refinements of the existing theories to explain their behavior.

Bemra, R. S.↗
DOE OSTI2020

Debris Disk Results from the Gemini Planet Imager Exoplanet Survey's Polarimetric Imaging Campaign

We report the results of a ∼4 yr direct imaging survey of 104 stars to resolve and characterize circumstellar debris disks in scattered light as part of the Gemini Planet Imager (GPI) Exoplanet Survey. We targeted nearby (≲150 pc), young (≲500 Myr) stars with high infrared (IR) excesses (L {sub IR}/L {sub ⋆} > 10{sup −5}), including 38 with previously resolved disks. Observations were made using the GPI high-contrast integral field spectrograph in H-band (1.6 μm) coronagraphic polarimetry mode to measure both polarized and total intensities. We resolved 26 debris disks and 3 protoplanetary/transitional disks. Seven debris disks were resolved in scattered light for the first time, including newly presented HD 117214 and HD 156623, and we quantified basic morphologies of five of them using radiative transfer models. All of our detected debris disks except HD 156623 have dust-poor inner holes, and their scattered-light radii are generally larger than corresponding radii measured from resolved thermal emission and those inferred from spectral energy distributions. To assess sensitivity, we report contrasts and consider causes of nondetections. Detections were strongly correlated with high IR excess and high inclination, although polarimetry outperformed total intensity angular differential imaging for detecting low-inclination disks (≲70°). Based on postsurvey statistics, we improved upon our presurvey target prioritization metric predicting polarimetric disk detectability. We also examined scattered-light disks in the contexts of gas, far-IR, and millimeter detections. Comparing H-band and ALMA fluxes for two disks revealed tentative evidence for differing grain properties. Finally, we found no preference for debris disks to be detected in scattered light if wide-separation substellar companions were present.

79 ASTRONOMY AND ASTROPHYSICS↗
NASA NTRS2001

Inferring Instantaneous, Multivariate and Nonlinear Sensitivities for the Analysis of Feedback Processes in a Dynamical System: Lorenz Model Case Study

A new approach is presented for the analysis of feedback processes in a nonlinear dynamical system by observing its variations. The new methodology consists of statistical estimates of the sensitivities between all pairs of variables in the system based on a neural network modeling of the dynamical system. The model can then be used to estimate the instantaneous, multivariate and nonlinear sensitivities, which are shown to be essential for the analysis of the feedbacks processes involved in the dynamical system. The method is described and tested on synthetic data from the low-order Lorenz circulation model where the correct sensitivities can be evaluated analytically.

Aires, Filipe↗
DOE OSTI2020

Weak Lensing And Cosmology In The Dark Energy Survey

In this PhD Thesis, we present studies which aim at understanding and testing the fundamental assumptions of the $\Lambda$CDM cosmological model. We initially show that weak gravitational lensing can be derived as a consequence of General Relativity, and that it can be applied to astronomical data from the Dark Energy Survey (DES) in order to constrain the amplitude of matter fluctuations in the universe. This constraint can be used as an end-to-end cosmological test when it is compared to inferences from the Cosmic Microwave Background. We further extend the cosmological model to account for non-standard parameters which can point to novel physics, and use DES data to assess their statistical significance. We finally show that the Cold Dark Matter (CDM) paradigm can also be fundamentally tested with observational data using morphological signatures of disk galaxies in cluster environments if CDM is self-interacting.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2024

Bridging the gap between experiments and simulations using machine learning

The physics of inertial confinement fusion is rich and complex. Simulation codes that are used to design experiments are computationally expensive and lack the predictive capability required for extensive parameter exploration in search of a high-performing design for laser direct drive. In this work we use deep learning to build a fast emulator of experiments. To facilitate the development of the deep-learning model, an autoencoder is used to reduce the dimensionality of the input space. Two deep learning models are developed. One model is trained on a vast array of simulation data and is subsequently calibrated to expensive and limited experimental data using a technique known as “transfer learning.” The other model is trained on a statistical model and is subsequently calibrated using experimental data. A comparative study of the two predictive models is carried out. The models potentially reproduce key experimental observables with high accuracy and unprecedented inference times relative to those achieved with simulation codes. These models facilitate rapid exploration of a high dimensional input parameter space.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
NASA NTRS1987

The formation and movement in the stratosphere of very dry air

The possible sources of very dry stratospheric air are investigated, extending the analysis of Atticks and Robinson (1983), on the basis of data from about 16,000 radiosonde ascents obtained during the FGGE from December 1978 through November 1979, from high-resolution Tiros and GMS IR-radiance observations on January 28, 1979, and from LIMS zonal-mean H2O-mass-mixing-ratio (HMMR) observations in December 1978 and May 1979. The data are compiled in tables and graphs and analyzed statistically, and the occurrence of low radiance temperatures (below -86 C) in the IR data (0.00025) is shown to be much lower than that (about 0.25) in the radiosonde data. It is inferred that air with HMMR less than 1.5 x 10 to the -6th could be produced in Cb cloud turrets, but not by the mechanism proposed by Danielsen (1982).

Robinson, G. D.↗
NASA NTRS2003

Eastern Asian Emissions of Anthropogenic Halocarbons Deduced from Aircraft Concentration Data

The Montreal Protocol restricts production of ozone-depleting halocarbons worldwide. Enforcement of the protocol has relied mainly on annual government statistics of production and consumption of these compounds (bottom-up approach). We show here that aircraft observations of ha1ocarbon:CO enhancement ratios on regional to continental scales can be used to infer halocarbon emissions, providing independent verification of the bottom-up approach. We apply this topdown approach to aircraft observations of Asian outflow &om the TRACE-P mission over the western Pacific (March-April 2001) and derive emissions from eastern Asia (China, Japan, and Korea). We derive an eastern Asian carbon tetrachloride (CCl4) source of 21.5 Gg yr(sup -1), several-fold larger than previous estimates and amounting to -30% of the global budget for this gas. Our emission estimate for CFC-11 from eastern Asia is 50% higher than inventories derived from manufacturing records. Our emission estimates for methyl chloroform (CH3CC13) and CFC-12 are in agreement with existing inventories. For halon 1211 we find only a strong local source originating from the Shanghai area. Our emission estimates for the above gases result in a approximately equal to 40% increase in the ozone depletion potential (ODP) of Asian emissions relative to previous estimates, corresponding to a approximately equal to 10% global increase in ODP.

Palmer, Paul I.↗
NASA NTRS2019

Integrating Remote Sensing Observations with NASA's GEOS-5 Modeling Framework in Support of Retrospective Analyses and Seasonal Prediction of Biosphere-Atmosphere CO2 Flux

The absorption of nearly half of all anthropogenic carbon dioxide (CO2) emissions by terrestrial and marine ecosystems has played a critical role in mitigating climate change. However, a persistent lack of understanding of these uptake processes impedes attribution, and thereby introduces large uncertainties into projections of the trajectory of carbon and climate in coming decades. A better understanding and quantification of the seasonal and interannual variability of carbon flux between the atmosphere and ocean and terrestrial biospheres is critically needed to improve predictions from Earth system models. We propose to bring together a diverse suite of remote sensing observations, mechanistic models, and NASA's Goddard Earth Observing System, version 5 (GEOS-5) model to address two objective 1) quantify the processes controlling the temporal variability of biosphere-atmosphere CO2 flux on seasonal and interannual timescales from 1989 to 2018 and 2) evaluating the predictability of the components of carbon flux on seasonal timescales. Because GEOS-5 has been developed to incorporate a variety of Earth system observations and includes a complete and physically consistent depiction of the atmosphere, land, and ocean carbon cycles, it represents a unique and ideal synthesis framework for this effort. By expanding the realism of processes that could be included in GEOS-5 seasonal forecasts, this effort supports NASA's goals toward an integrated Earth system modeling and prediction framework.We propose to integrate a number of observations into the GEOS-5 modeling system to refine retrospective estimates of both terrestrial and marine carbon flux and to test hypotheses regarding the effects of climate drivers on terrestrial carbon flux. This will include assimilating several satellite ocean color products in the NASA Ocean Biogeochemistry Model (NOBM) to improve the representation of ocean biology. We will also utilize remote sensing datasets to increase the temporal resolution of global land-use change estimates and fire emissions to better constrain the temporal variability of the terrestrial carbon cycle. This information will be incorporated into two NASA terrestrial biosphere models Catchment-CN, a dynamic vegetation model that is integrated within GEOS-5 and the Ecosystem Demography (ED) model, a core modeling resource supporting the Global Ecosystem Dynamics Investigation (GEDI) mission to map biomass. Fluxes will be evaluated through 1) comparison to top-down flux estimates inferred from surface CO2 observations and 2) comparison against available aircraft and satellite observations.By combining predictions of net ecosystem exchange and air-sea CO2 flux from land and ocean models with statistical predictions of land use change, fire, and fossil fuel emissions, we propose to create the first dynamical CO2 forecast on seasonal timescales. Because of the experimental nature of this endeavor, an important project objective will be to evaluate the limits to the predictability of different carbon cycle processes over lead times of 1-12 months using different satellite and surface data streams.

Ott, Lesley↗
DOE OSTI2024

Machine Learning Inference of Random Medium Properties

Earth materials are heterogeneous across a range of spatial scales, but the resolvability of small structures is limited by sparse data coverage, noise, bandlimitedness, and other difficulties. In practice, heterogeneities below a certain size cannot be recovered from seismic data except through statistical medium descriptions, which even then can be difficult to uniquely determine. To improve the characterization of such heterogeneities, we develop a novel supervised machine learning (ML) model that provides insight about the recoverability of statistical medium properties from elastic waveform data and succeeds despite cycle-skipping and other challenges well known from elastic waveform inversion. We demonstrate the approach using random media generated by superimposing self-affine random variations on homogeneous and layered background structures. After training on sparsely-recorded, high-frequency waveforms from hundreds of different random medium realizations, we show the ability of our ML model to recover correlation lengths and other statistical properties of interest to near-surface and crustal seismology, among other fields. For frequency passbands and spatial offsets encountered in seismology, Gaussian correlation lengths and the amplitude of the random variations relative to the background model are recovered even in challenging scenarios involving unknown medium parameters, complex crustal structures, and low signal-to-noise ratio. In comparison, von Kármán correlation lengths, which are related to larger-wavelength variations of the medium than Gaussian correlation lengths, are not as well recovered. These results provide one of the first and most systematic investigations of the recoverability of statistical properties of heterogeneities below the resolution limit of deterministic seismic tomography, and suggest practical ML strategies for high-frequency waveform seismology.

58 GEOSCIENCES↗
DOE OSTI2023

Differentiating multi-MeV, multi-ion spectra with CR-39 solid-state nuclear track detectors

The development of high intensity petawatt lasers has created new possibilities for ion acceleration and nuclear fusion using solid targets. In such laser-matter interaction, multiple ion species are accelerated with broad spectra up to hundreds of MeV. To measure ion yields and for species identification, CR-39 solid-state nuclear track detectors are frequently used. However, these detectors are limited in their applicability for multi-ion spectra differentiation as standard image recognition algorithms can lead to a misinterpretation of data, there is no unique relation between track diameter and particle energy, and there are overlapping pit diameter relationships for multiple particle species. In this report, we address these issues by first developing an algorithm to overcome user bias during image processing. Second, we use calibration of the detector response for protons, carbon and helium ions (alpha particles) from 0.1 to above 10 MeV and measurements of statistical energy loss fluctuations in a forward-fitting procedure utilizing multiple, differently filtered CR-39, altogether enabling high-sensitivity, multi-species particle spectroscopy. To validate this capability, we show that inferred CR-39 spectra match Thomson parabola ion spectrometer data from the same experiment. Filtered CR-39 spectrometers were used to detect, within a background of ~ 2 × 10 11 sr -1 J -1 protons and carbons, (1.3 ± 0.7) × 10 8 sr -1 J -1 alpha particles from laser-driven proton-boron fusion reactions.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗