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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 1,099 records · Page 61
All sourcesNASA NTRSDOE OSTI
NASA NTRS1999

Global Measurements of Stratospheric Mountain Waves from Space

Temperatures acquired by the Cryogenic Infrared Spectrometers and Telescopes for the Atmosphere (CRISTA) during shuttle mission STS-66 have provided measurements of stratospheric mountain waves from space. Large-amplitude, long-wavelength mountain waves at heights of 15 to 30 kilometers above the southern Andes Mountains were observed and characterized, with vigorous wave breaking inferred above 30 kilometers. Mountain waves also occurred throughout the stratosphere (15 to 45 kilometers) over a broad mountainous region of central Eurasia. The global distribution of mountain wave activity accords well with predictions from a mountain wave model. The findings demonstrate that satellites can provide the global data needed to improve mountain wave parameterizations and hence global climate and forecast models.

Eckermann, Stephen D.↗
NASA NTRS2012

The Kinematic and Microphysical Control of Storm Integrated Lightning Flash Extent

Objective: To investigate the kinematic and microphysical control of lightning properties, particularly those that may govern the production of nitrogen oxides (NOx) in thunderstorms, such as flash rate, type (intracloud [IC] vs. cloud-to-ground [CG] ) and extent. Data and Methodology: a) NASA MSFC Lightning Nitrogen Oxides Model (LNOM) is applied to North Alabama Lightning Mapping Array (NALMA) and Vaisala National Lightning Detection Network(TradeMark) (NLDN) observations following ordinary convective cells through their lifecycle. b) LNOM provides estimates of flash type, channel length distributions, lightning segment altitude distributions (SADs) and lightning NOx production profiles (Koshak et al. 2012). c) LNOM lightning characteristics are compared to the evolution of updraft and precipitation properties inferred from dual-Doppler (DD) and polarimetric radar analyses of UAHuntsville Advanced Radar for Meteorological and Operational Research (ARMOR, Cband, polarimetric) and KHTX (S-band, Doppler).

Carey, Lawrence D.↗
DOE OSTI2021

Transport Estimations of Final State Interaction Effects on Short-range Correlation Studies Using the $(e,e'p)$ and $(e,e'pp)$ Reactions

Short range correlated (SRC) nucleon-nucleon pairs in nuclei are typically studied using measurements of electron-induced hard nucleon-knockout reactions (e.g. $(e,e'p)$ and $(e,e'pN)$), where the kinematics of the knocked-out nucleons are used to infer their initial state prior to the interaction. The validity of this inference relies on our understanding of the scattering reaction, most importantly how rescattering of the detected nucleons (final state interactions or FSI) distort their kinematical distributions. Recent SRC measurements on medium to heavy nuclei have been performed at high-$x_B$ (i.e., anti-parallel kinematics) where calculations of light nuclei indicate that such distortion effects are small. Here we study the impact of FSI on recent $^{12}$C$(e,e'p)$ and $^{12}$C$(e,e'pp)$ measurements using a transport approach. We find that while FSI can significantly distort the measured kinematical distributions of SRC breakup events, selecting high-$x_B$ anti-parallel events strongly suppresses such distortions. In addition, including the effects of FSI improves the agreement between Generalized Contact Formalism-based calculations and data and can help identify those observables that have minimal sensitivity to FSI effects. This result helps confirm the interpretation of experimental data in terms of initial-state momentum distributions and provides a new tool for the study of SRCs using lepton-scattering reactions.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2023

A Data Processing Pipeline for Adversarial Socio-Technical Network Analysis

With the rapid adoption of emerging technologies, there is a need to catalog and model sociotechnical interdependencies that have been historically used to influence the operation of Critical Infrastructure networks including the impacts of mergers and acquisitions, hostile takeovers, and foreign investment. Our research intends to address this need with two primary contributions. First, we have developed a data curation and processing pipeline to generate sociotechnical networks extracted from a variety of data sources including SEC filings and infrastructure asset databases. The pipeline, implemented in Apache Airflow, extracts and normalizes the representation of entities and relations, specified within ontologies. Our intent is to provide an extensible, machine-actionable approach to quickly communicate such models, reproduce previous results, and adapt them to new, unanticipated situations. Second, networks produced by our pipeline enable the development of graph-theoretic metrics that consider the properties of network components in addition to its topology. Metadata associated with network components---whether semantic, temporal, or geospatial---affects the alignment of generated networks with assumptions underlying complexity metrics. Validation of generated networks relative to component types defined by an ontology, may allow the research community to adapt metrics to the semantics of the domains being studied. Generated networks may be processed as knowledge, dynamic, or spatial graphs and enables a variety of analyses including automated reasoning and measures of network complexity. Automated reasoning views extracted entities and relations as a knowledge graph; this enables application of inference rules that represent historically-attested adversarial business methods and applies that behavior to a specific geographic context. Measures of network complexity, including degree distribution, reachability analyses, temporal analysis, and community detection can be adapted to indicate adversarial organizational influence.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2022

Estimation of process steady state with autoregressive models and Bayesian inference

To improve efficiency, separations engineers will typically design process circuits containing recirculating streams, which mix one or more of the process outputs with the feed material. Doing so can improve efficiency, but will cause a delay in the system reaching steady state conditions until the recirculating load mass flows stabilize. In testing separation circuits, engineers will often test a variety of factors and complete an analysis from sample results. Knowledge of if a process is at steady state, as well as the steady state conditions of a process, is essential for a valid techno-economic analysis. However, the definition of process steady state is often poorly defined, or does not include uncertainty quantification. If the performance of a process operating under two different sets of conditions are compared, an engineer who does not test for steady state or quantify steady state conditions risks producing a faulty analysis. In this work, a Bayesian statistical method for testing if all streams are at steady state is further motivated and then derived. Then after testing for steady state, the same model is used with a prior distribution that enforces a steady state assumption to estimate steady state conditions. Further, these methods were validated in a solvent extraction pilot plant where steady state conditions for all outflows were inferred with uncertainty quantification. Analysis is completed with functions available to the reader as part of the BayesMassBal (V 1.1.0) software package written in R.

01 COAL, LIGNITE, AND PEAT↗
NASA NTRS1999

A Neural Network Aero Design System for Advanced Turbo-Engines

An inverse design method calculates the blade shape that produces a prescribed input pressure distribution. By controlling this input pressure distribution the aerodynamic design objectives can easily be met. Because of the intrinsic relationship between pressure distribution and airfoil physical properties, a Neural Network can be trained to choose the optimal pressure distribution that would meet a set of physical requirements. Neural network systems have been attempted in the context of direct design methods. From properties ascribed to a set of blades the neural network is trained to infer the properties of an 'interpolated' blade shape. The problem is that, especially in transonic regimes where we deal with intrinsically non linear and ill posed problems, small perturbations of the blade shape can produce very large variations of the flow parameters. It is very unlikely that, under these circumstances, a neural network will be able to find the proper solution. The unique situation in the present method is that the neural network can be trained to extract the required input pressure distribution from a database of pressure distributions while the inverse method will still compute the exact blade shape that corresponds to this 'interpolated' input pressure distribution. In other words, the interpolation process is transferred to a smoother problem, namely, finding what pressure distribution would produce the required flow conditions and, once this is done, the inverse method will compute the exact solution for this problem. The use of neural network is, in this context, highly related to the use of proper optimization techniques. The optimization is used essentially as an automation procedure to force the input pressure distributions to achieve the required aero and structural design parameters. A multilayered feed forward network with back-propagation is used to train the system for pattern association and classification.

Sanz, Jose M.↗
DOE OSTI2024

Microstructural stability and mechanical properties of the as-cast and heat-treated newly developed TiNbCrTa refractory complex concentrated alloy

In this study, a TiNbCrTa refractory complex concentrated alloy (RCCA) was prepared using vacuum arc remelting. The microstructural evolution and mechanical properties of both as-cast and heat-treated RCCA samples were analyzed. Heat treatment (HT) was performed at 800–1200 °C for 1 h in a vacuum-sealed environment. These samples exhibited a formation of Cr 2 Nb and Cr 2 Ti Laves phases. A variation in elemental distribution was observed, with interdendritic (ID) regions showing higher fractions of Ti and Cr, while the dendritic regions had a greater concentration of Ta and Nb. Micro-segregation at the IDs was confirmed through energy dispersive x-ray spectroscopy mapping, which inferred the formation of Cr- and Ti-rich phases during HT at 800–1200 °C. High-temperature HT at 1200 °C for 1 h led to the evolution of the hcp omega phase. Prolonged HT at 1200 °C for 96 h resulted in the evolution of a Cr-rich Laves phase (Cr 2 Ta), which was homogeneously distributed within the microstructure, indicating an unstable microstructure. Furthermore, despite prolonged HT, a variation in the elemental distribution persisted due to the presence of dendritic and ID regions. Electron backscattered diffraction analysis revealed the presence of bcc and hcp phases in the dendritic and ID regions, respectively, of the as-cast and HTed samples. The as-cast samples demonstrated a high compressive strength of approximately 2 GPa. Micro-hardness values increased with the HT temperature up to 1000 °C. Further increases under HT conditions did not significantly reduce the microhardness value, whereas prolonged HT at 1200 °C led to an increase in the microhardness value. Overall, the newly developed TiNbCrTa RCCA exhibited high-strength behavior even after the phase transformation.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
NASA NTRS1999

GHRS Observations of Cool, Low-Gravity Stars: The Outer Atmosphere and Wind of the Nearby K Supergiant Lambda Velorum - 5

UV spectra of lambda Velorum taken with the Goddard High Resolution Spectrograph (GHRS) on the Hubble Space Telescope are used to probe the structure of the outer atmospheric layers and wind and to estimate the mass-loss rate from this K5 lb-II supergiant. VLA radio observations at lambda = 3.6 cm are used to obtain an independent check on the wind velocity and mass-loss rate inferred from the UV observations, Parameters of the chromospheric structure are estimated from measurements of UV line widths, positions, and fluxes and from the UV continuum flux distribution. The ratios of optically thin C II] emission lines indicate a mean chromospheric electron density of log N(sub e) approximately equal 8.9 +/- 0.2 /cc. The profiles of these lines indicate a chromospheric turbulence (v(sub 0) approximately equal 25-36 km/s), which greatly exceeds that seen in either the photosphere or wind. The centroids of optically thin emission lines of Fe II and of the emission wings of self-reversed Fe II lines indicate that they are formed in plasma approximately at rest with respect to the photosphere of the star. This suggests that the acceleration of the wind occurs above the chromospheric regions in which these emission line photons are created. The UV continuum detected by the GHRS clearly traces the mean flux-formation temperature as it increases with height in the chromosphere from a well-defined temperature minimum of 3200 K up to about 4600 K. Emission seen in lines of C III] and Si III] provides evidence of material at higher than chromospheric temperatures in the outer atmosphere of this noncoronal star. The photon-scattering wind produces self-reversals in the strong chromospheric emission lines, which allow us to probe the velocity field of the wind. The velocities to which these self-absorptions extend increase with intrinsic line strength, and thus height in the wind, and therefore directly map the wind acceleration. The width and shape of these self-absorptions reflect a wind turbulence of approximately equal 9-21 km/s. We further characterize the wind by comparing the observations with synthetic profiles generated with the Lamers et al. Sobolev with Exact Integration (SEI) radiative transfer code, assuming simple models of the outer atmospheric structure. These comparisons indicate that the wind in 1994 can be described by a model with a wind acceleration parameter beta approximately 0.9, a terminal velocity of 29-33 km/s, and a mass-loss rate approximately 3 x 10(exp -9) solar M/yr. Modeling of the 3.6 cm radio flux observed in 1997 suggests a more slowly accelerating wind (higher beta) and/or a higher mass-loss rate than inferred from the UV line profiles. These differences may be due to temporal variations in the wind or from limitations in one or both of the models. The discrepancy is currently under investigation.

Carpenter, Kenneth G.↗
NASA NTRS1979

Martian canyons and African rifts - Structural comparisons and implications

The resistant parts of the canyon walls of the Martian rift complex Valles Marineris have been used to infer an earlier, less eroded reconstruction of the major troughs. The individual canyons are compared with individual rifts of East Africa. When measured in units of planetary radius, Martian canyons show a distribution of lengths nearly identical to those in Africa, both for individual rifts and for compound rift systems. A common mechanism which scales with planetary radius is suggested. Martian canyons are significantly wider than African rifts. This is consistent with the longstanding idea that rift width is related to crustal thickness: most evidence favors a crust on Mars at least 50% thicker than that of Africa. The overall patterns of the rift systems of Africa and Mars are quite different in that the African systems are composed of numerous small faults with highly variable trend. On Mars the trends are less variable; individual scraps are straighter for longer than on earth. The basement and lithosphere of Mars are inferred to be simple, reflecting a relatively inactive tectonic history prior to the formation of the canyonlands.

Frey, H.↗
DOE OSTI2024

Uncertainty Propagation within Chained Models for Machine Learning Reconstruction of Neutrino-LAr Interactions

Sequential or chained models are increasingly prevalent in machine learning for scientific applications, due to their flexibility and ease of development. Chained models are particularly useful when a task is separable into distinct steps with a hierarchy of meaningful intermediate representations. In reliability-critical tasks, it is important to quantify the confidence of model inferences. However, chained models pose an additional challenge for uncertainty quantification, especially when input uncertainties need to be propagated. In such cases, a fully uncertainty-aware chain of models is required, where each step accepts a probability distribution over the input space, and produces a probability distribution over the output space. In this work, we present a case study for adapting a single model within an existing chain, designed for reconstruction within neutrino-Argon interactions, developed for neutrino oscillation experiments such as MicroBooNE, ICARUS, and the future DUNE experiment. We test the performance of an input uncertainty-enabled model against an uncertainty-blinded model using a method for generating synthetic noise. By comparing these two, we assess the increase in inference quality achieved by exposing models to upstream uncertainty estimates.

97 MATHEMATICS AND COMPUTING↗
NASA NTRS1989

Confidence set inference with a prior quadratic bound

In the uniqueness part of a geophysical inverse problem, the observer wants to predict all likely values of P unknown numerical properties z=(z sub 1,...,z sub p) of the earth from measurement of D other numerical properties y (sup 0) = (y (sub 1) (sup 0), ..., y (sub D (sup 0)), using full or partial knowledge of the statistical distribution of the random errors in y (sup 0). The data space Y containing y(sup 0) is D-dimensional, so when the model space X is infinite-dimensional the linear uniqueness problem usually is insoluble without prior information about the correct earth model x. If that information is a quadratic bound on x, Bayesian inference (BI) and stochastic inversion (SI) inject spurious structure into x, implied by neither the data nor the quadratic bound. Confidence set inference (CSI) provides an alternative inversion technique free of this objection. Confidence set inference is illustrated in the problem of estimating the geomagnetic field B at the core-mantle boundary (CMB) from components of B measured on or above the earth's surface.

Backus, George E.↗
NASA NTRS1978

Martian canyons and African rifts: Structural comparisons and implications

The resistant parts of the canyon walls of the Martian rift complex Valled Marineris were used to infer an earlier, less eroded reconstruction of the major roughs. The individual canyons were then compared with individual rifts of East Africa. When measured in units of planetary radius, Martian canyons show a distribution of lengths nearly identical to those in Africa, both for individual rifts and for compound rift systems. A common mechanism which scales with planetary radius is suggested. Martian canyons are significantly wider than African rifts. The overall pattern of the rift systems of Africa and Mars are quite different in that the African systems are composed of numerous small faults with highly variable trend. On Mars the trends are less variable; individual scarps are straighter for longer than on earth. This is probably due to the difference in tectonic histories of the two planets: the complex history of the earth and the resulting complicated basement structures influence the development of new rifts. The basement and lithosphere of Mars are inferred to be simple, reflecting a relatively inactive tectonic history prior to the formation of the canyonlands.

Frey, H. V.↗
DOE OSTI2022

Revisiting stellar properties of star-forming galaxies with stellar and nebular spectral modelling

Spectral synthesis is a powerful tool for interpreting the physical properties of galaxies by decomposing their spectral energy distributions (SEDs) into the main luminosity contributors (e.g. stellar populations of distinct age and metallicity or ionised gas). However, the impact nebular emission has on the inferred properties of star-forming (SF) galaxies has been largely overlooked over the years, with unknown ramifications to the current understanding of galaxy evolution. The objective of this work is to estimate the relations between stellar properties (e.g. total mass, mean age, and mean metallicity) of SF galaxies by simultaneously fitting the stellar and nebular continua and comparing them to the results derived through the more common purely stellar spectral synthesis approach. The main galaxy sample from SDSS DR7 was analysed with two distinct population synthesis codes: FADO, which estimates self-consistently both the stellar and nebular contributions to the SED, and the original version of STARLIGHT, as representative of purely stellar population synthesis codes. Differences between codes regarding average mass, mean age and mean metallicity values can go as high as ~0.06 dex for the overall population of galaxies and ~0.12 dex for SF galaxies (galaxies with EW(Hα) > 3 Å), with the most prominent difference between both codes in the two populations being in the light-weighted mean stellar age. FADO presents a broader range of mean stellar ages and metallicities for SF galaxies than STARLIGHT, with the latter code preferring metallicity solutions around the solar value (Z ⊙ = 0.02). A closer look into the average light- and mass-weighted star formation histories of intensively SF galaxies (EW(Hα) > 75 Å) reveals that the light contributions of simple stellar populations (SSPs) younger than ≤10 7 (10 9 ) years in STARLIGHT are higher by ~5.41% (9.11%) compared to FADO. Moreover, FADO presents higher light contributions from SSPs with metallicity ≤ Z ⊙ /200 (Z ⊙ /50) of around 8.05% (13.51%) when compared with STARLIGHT. This suggests that STARLIGHT is underestimating the average light-weighted age of intensively SF galaxies by up to ~0.17 dex and overestimating the light-weighted metallicity by up to ~0.13 dex compared to FADO (or vice versa). The comparison between the average stellar properties of passive, SF and intensively SF galaxy samples also reveals that differences between codes increase with increasing EW(Hα) and decreasing total stellar mass. Moreover, comparing SF results from FADO in a purely stellar mode with the previous results qualitatively suggests that differences between codes are primarily due to mathematical and statistical differences and secondarily due to the impact of the nebular continuum modelling approach (or lack thereof). However, it is challenging to adequately quantify the relative role of each factor since they are likely interconnected. This work finds indirect evidence that a purely stellar population synthesis approach negatively impacts the inferred stellar properties (e.g. mean age and mean metallicity) of galaxies with relatively high star formation rates (e.g. dwarf spirals, ‘green peas’, and starburst galaxies). In turn, this can bias interpretations of fundamental relations such as the mass-age or mass-metallicity, which are factors worth bearing in mind in light of future high-resolution spectroscopic surveys at higher redshifts (e.g. MOONS and 4MOST-4HS).

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2022

A Conditional Autoencoder for Galaxy Photometric Parameter Estimation

Astronomical photometric surveys routinely image billions of galaxies, and traditionally infer the parameters of a parametric model for each galaxy. This approach has served us well, but the computational expense of deriving a full posterior probability distribution function is a challenge for increasingly ambitious surveys. In this paper, we use deep learning methods to characterize galaxy images, training a conditional autoencoder on mock data. The autoencoder can reconstruct and denoise galaxy images via a latent space engineered to include semantically meaningful parameters, such as brightness, location, size, and shape. Our model recovers galaxy fluxes and shapes on mock data with a lower variance than the Hyper Suprime-Cam photometry pipeline, and returns reasonable answers even for inputs outside the range of its training data. When applied to data in the training range, the regression errors on all extracted parameters are nearly unbiased with a variance near the Cramr-Rao bound.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2022

White Dwarf Binaries across the H-R Diagram

We created the APOGEE-GALEX-Gaia catalog to study white dwarf (WD) binaries. This database aims to create a minimally biased sample of WD binary systems identified from a combination of GALEX, Gaia, and APOGEE data to increase the number of WD binaries with orbital parameters and chemical compositions. We identify 3414 sources as WD binary candidates, with nondegenerate companions of spectral types between F and M, including main-sequence stars, main-sequence binaries, subgiants, sub-subgiants, red giants, and red clump stars. Among our findings are (a) a total of 1806 systems having inferred WD radii R < 25 R ⊕ , which constitute a more reliable group of WD binary candidates within the main sample; (b) a difference in the metallicity distribution function between WD binary candidates and the control sample of most luminous giants (M H < -3.0); (c) the existence of a population of sub-subgiants with WD companions; (d) evidence for shorter periods in binaries that contain WDs compared to those that do not, as shown by the cumulative distributions of APOGEE radial velocity shifts; (e) evidence for systemic orbital evolution in a sample of 252 WD binaries with orbital periods, based on differences in the period distribution between systems with red clump, main-sequence binary, and sub-subgiant companions and systems with main-sequence or red giant companions; and (f) evidence for chemical enrichment during common envelope (CE) evolution, shown by lower metallicities in wide WD binary candidates (P > 100 days) compared to post-CE (P < 100 days) WD binary candidates.

79 ASTRONOMY AND ASTROPHYSICS↗
NASA NTRS1973

Analysis of Mossbauer Fe-57 absorption in an F.C.C. Fe-Co-V alloy

Mossbauer Fe-57 absorption spectra of superparamagnetic F.C.C. Fe sub .34 Co sub .52 V sub 14 (Vicalloy II) have been analyzed using a cluster model and magnetic resonance relaxation theory. The number and magnetic moment of the clusters were determined from magnetization data. A least squares fit to the spectrum at 4.2 K gives sub Hhyp = 175. kG, substantially greater than the value 55 kG inferred just from the observed broadening of the single line spectrum. From this broadening an estimate of 40 kG is obtained for the width of the distribution in Hhyp at 4.2 K arising from compositional fluctuations sub and small cluster effects.

Bambakidis, G.↗
NASA NTRS1989

A study on cloud-radiation interaction

Most empirical studies estimating the climate sensitivity due to cloud amount are based on calculating a cloud sensitivity parameter by means of satellite measurements. A different way to estimate the interaction between clouds and radiation is to determine the effect of radiative heating and cooling by clouds on the generation of available potential energy (GAPE). This provides a measure of the influence of clouds on the general circulation. The radiative contribution of clouds to the GAPE is given by the net cloud generated radiative heating (CGRH) and an efficiency factor. The CGRH, parameterized in terms of cloud type, height, and optical depth, can be estimated from satellite measurements. The efficiency factor is only a function of the temperature distribution of the atmosphere. Thus, taking satellite measurements as for instance those of the ISCCP, the radiative impact of clouds on the general circulation can be inferred.

Stuhlmann, R.↗
NASA NTRS1989

A technique for interpretation of auroral bremsstrahlung X-ray spectra

A procedure is described for determining the average energy and the energy flux of precipitating electrons from the resulting bremsstrahlung X-rays based on the assumption that the precipitating electrons have an exponential electron distribution. It is shown that, for nonexponential electron distributions, this method yields an exponential electron distribution that produces an altitude profile of ionization very similar to that expected from the actual spectrum. The Hall and Pedersen electrical conductances calculated from the inferred ionization profile were also found to be close to the true values.

Robinson, Robert M.↗