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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 1,009 records · Page 56
All sourcesNASA NTRSDOE OSTI
NASA NTRS1994

The mass and dynamics of cD clusters with cooling flows. 1: ROSAT observations of A 496

As part of a program to determine the mass distribution of cD galaxy clusters with cooling flows, we obtained a ROSAT image of the cluster A 496. The image reveals sharply peaked emission centered on the cD galaxy. Both the peaked cooling flow emission and the more extended emission filling the cluster are centered on the cD galaxy to within 15 sec . The surface brightness profile is consistent with previous Einstein observations. We measure spatially resolved spectra for the X-ray emission, and find a significant decline in temperature in the innermost 2 min to 4 min. We also find a gradient in absorption due to cold neutral gas, with an excess above the neutral hydrogen column due to our own galaxy in the inner 4 min. The excess absorption, however, is far below previously reported values. The surface brightness profile and the spatially resolved temperature profile are indicative of a cooling flow in the cluster. Cooling flow models fit to the X-ray spectra in the innermost 2 min yield a mass flow rate of 59 solar mass yr(exp -1). The spatially resolved temperature and surface brightness profiles are used to derive the mass distribution of the cluster both in the hot, X-ray emitting plasma and in the unseen dark matter that binds the cluster. To a radius of 1.0 Mpc we find a total cluster mass of 3.44 x 10(exp 14) solar mass ; the X-ray emitting gas mass of 0.75 x 10(exp 14) solar mass to this radius comprises 16 percent of the total cluster mass.

Kriss, Gerard A.↗
DOE OSTI2024

Modeling neutrino-induced scale-dependent galaxy clustering for photometric galaxy surveys

Abstract The increasing statistical precision of photometric redshift surveys requires improved accuracy of theoretical predictions for large-scale structure observables to obtain unbiased cosmological constraints. In ΛCDM cosmologies, massive neutrinos stream freely at small cosmological scales, suppressing the small-scale power spectrum. In massive neutrino cosmologies, galaxy bias modeling needs to accurately relate the scale-dependent growth of the underlying matter field to observed galaxy clustering statistics. In this work, we implement a computationally efficient approximation of the neutrino-induced scale-dependent bias (NISDB). Through simulated likelihood analyses of Dark Energy Survey Year 3 (DESY3) and Legacy Survey of Space and Time Year 1 (LSSTY1) synthetic data that contain an appreciable NISDB, we examine the impact of linear galaxy bias and neutrino mass modeling choices on cosmological parameter inference. We find model misspecification of the NISDB approximation and neutrino mass models to decrease the constraining power of photometric galaxy surveys and cause parameter biases in the cosmological interpretation of future surveys. We quantify these biases and devise mitigation strategies.

Astronomy & Astrophysics↗
NASA NTRS1990

A model for the infrared emission from an OB star cluster environment

Researchers developed an interactive radiative transfer code that predicts the infrared emission from an HII region containing diffuse ionized and atomic gas and dense molecular clouds. This model complements the investigation of the redistribution of OB star luminosity in the interstellar medium (Leisawitz and Hauser 1988, Ap. J., 332, 954). The model can be used as a diagnostic tool to probe the radiation field and matter density in an HII region, place constraints on the proximity and orientation of an illuminated molecular cloud with respect to the ionizing stars, test for the presence of small, transiently heated dust grains, and determine whether the dust-to-gas ratio is normal. Predictions of the model agree qualitatively and quantitatively with observations of blister-type HII regions ionized by well-studied OB clusters in which the distribution of dense neutral material is known. This is illustrated by a model for Infrared Astronomy Satellite (IRAS) observations of the region around NGC 7380 (S142). Researchers plan to use the model in a survey of regions of massive star formation in the outer Galaxy to study OB stars embedded to various degrees in their parental molecular clouds.

Leisawitz, D.↗
NASA NTRS1972

Determination of bulk properties of tropical cloud clusters from large scale heat and moisture budgets, appendix B

The bulk properties of tropical cloud clusters, as the vertical mass flux, the excess temperature, and moisture and the liquid water content of the clouds, are determined from a combination of the observed large-scale heat and moisture budgets over an area covering the cloud cluster, and a model of a cumulus ensemble which exchanges mass, heat, vapor and liquid water with the environment through entrainment and detrainment. The method also provides an understanding of how the environmental air is heated and moistened by the cumulus convection. An estimate of the average cloud cluster properties and the heat and moisture balance of the environment, obtained from 1956 Marshall Islands data, is presented.

Yanai, M.↗
DOE OSTI2022

Ellipsoidal Fitting Methodology for Defect Clusters in Gallium Arsenide

In assessing the initial spatial distribution of defects from neutron or heavy ion irradiation, it is useful to have a reliable, automated, and fast-running tool to evaluate characteristic metrics such as the number of sub-clusters or the overall cluster volume. The latter metric, for instance, can be utilized to estimate a reference neutron fluence level at which inter-cluster interaction effects begin to become significant. This paper details a methodology to fit an arbitrarily complex defect map with a set of ellipsoids (one per identified sub-cluster) in which the constituent defects of a sub-cluster are determined using fuzzy degree-of-membership analysis. Specifically, a parameterized model is developed for point defects in gallium arsenide. Cluster volume calculations based on the model are compared against convex hull and single- ellipsoid representations. Results show that the parameterized sub-cluster model begins to deviate from the two reference models at a recoil energy of about 100 keV in GaAs, with the convex hull and single-ellipsoid representations increasingly overestimating the volume thereafter.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2023

Star cluster classification using deep transfer learning with PHANGS- HST

Currently available star cluster catalogues from the Hubble Space Telescope (HST) imaging of nearby galaxies heavily rely on visual inspection and classification of candidate clusters. Here, the time-consuming nature of this process has limited the production of reliable catalogues and thus also post-observation analysis. To address this problem, deep transfer learning has recently been used to create neural network models that accurately classify star cluster morphologies at production scale for nearby spiral galaxies (D ≲ 20 Mpc). Here, we use HST ultraviolet (UV)–optical imaging of over 20 000 sources in 23 galaxies from the Physics at High Angular resolution in Nearby GalaxieS (PHANGS) survey to train and evaluate two new sets of models: (i) distance-dependent models, based on cluster candidates binned by galaxy distance (9–12, 14–18, and 18–24 Mpc), and (ii) distance-independent models, based on the combined sample of candidates from all galaxies. We find that the overall accuracy of both sets of models is comparable to previous automated star cluster classification studies (~60–80 per cent) and shows improvement by a factor of 2 in classifying asymmetric and multipeaked clusters from PHANGS-HST. Somewhat surprisingly, while we observe a weak negative correlation between model accuracy and galactic distance, we find that training separate models for the three distance bins does not significantly improve classification accuracy. We also evaluate model accuracy as a function of cluster properties such as brightness, colour, and spectral energy distribution (SED)-fit age. Based on the success of these experiments, our models will provide classifications for the full set of PHANGS-HST candidate clusters (N ~ 200 000) for public release.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2021

Probing Active Sites in Cu x Pd y Cluster Catalysts by Machine-Learning-Assisted X-ray Absorption Spectroscopy

Size-selected clusters are important model catalysts because of their narrow size and compositional distributions, as well as enhanced activity and selectivity in many reactions. Still, their structure-activity relationships are, in general, elusive. The main reason is the difficulty in identifying and quantitatively characterizing the catalytic active site in the clusters when it is confined within subnanometric dimensions and under the continuous structural changes the clusters can undergo in reaction conditions. Using machine learning approaches for analysis of the operando X-ray absorption near-edge structure spectra, we obtained accurate speciation of the Cu x Pd y cluster types during the propane oxidation reaction and the structural information about each type. As a result, we elucidated the information about active species and relative roles of Cu and Pd in the clusters.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2016

Ferromagnetic bond of Li{sub 10} cluster: An alternative approach in terms of effective ferromagnetic sites

In this work, a model to explain the unusual stability of atomic lithium clusters in their highest spin multiplicity is presented and used to describe the ferromagnetic bonding of high-spin Li{sub 10} and Li{sub 8} clusters. The model associates the (lack of-)fitness of Heisenberg Hamiltonian with the degree of (de-)localization of the valence electrons in the cluster. It is shown that a regular Heisenberg Hamiltonian with four coupling constants cannot fully explain the energy of the different spin states. However, a more simple model in which electrons are located not at the position of the nuclei but at the position of the attractors of the electron localization function succeeds in explaining the energy spectrum and, at the same time, explains the ferromagnetic bond found by Shaik using arguments of valence bond theory. In this way, two different points of view, one more often used in physics, the Heisenberg model, and the other in chemistry, valence bond, come to the same answer to explain those atypical bonds.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2019

Numerical investigation of spin excitations in a doped spin chain

We study the doping evolution of spin excitations in a one-dimensional (1D) Hubbard model and its downfolded spin Hamiltonians, by using exact diagonalization combined with cluster perturbation theory. In all models we observe hardening (softening) of spin excitations upon electron (hole) doping, which are reminiscent of recent experiments on two-dimensional (2D) cuprate materials. We also find that the three-site and even higher-order terms are crucial for the low-energy effective spin models to reproduce the magnetic spectra of doped Hubbard systems at a quantitative level. To interpret the numerical results, we further employ a strong coupling slave-boson mean-field theory. The mean-field theory provides an intuitive understanding of the overall compact support of dynamic spin structure factors, including the shift of zero-energy modes and change of spin excitation bandwidth with doping. Our results can serve as predictive benchmarks for future inelastic x-ray or neutron scattering experiments on doped 1D antiferromagnetic Mott insulators.

Pärschke, Ekaterina M.↗
NASA NTRS1984

Cosmic background radiation anisotropies in universes dominated by nonbaryonic dark matter

Detailed calculations of the temperature fluctuations in the cosmic background radiation for universes dominated by massive collisionless relics of the big bang are presented. An initially adiabatic constant curvature perturbation spectrum is assumed. In models with cold dark matter, the simplest hypothesis - that galaxies follow the mass distribution leads to small-scale anisotropies which exceed current observational limits if omega is less than 0.2 h to the -4/3. Since low values of omega are indicated by dynamical studies of galaxy clustering, cold particle models in which light traces mass are probably incorrect. Reheating of the pregalactic medium is unlikely to modify this conclusion. In cold particle or neutrino-dominated universes with omega = 1, presented predictions for small-scale and quadrupole anisotropies are below current limits. In all cases, the small-scale fluctuations are predicted to be about 10 percent linearly polarized.

Bond, J. R.↗
DOE OSTI2015

A validation of a simple model for the calculation of the ionization energies in X-ray laser-cluster interactions

The outer-ionization of an electron from a cluster is an unambiguous quantity, while the inner-ionization threshold is not, resulting in different microscopic quantum-classical hybrid models used in laser-cluster interactions. A simple local ionization threshold model for the change in the ionization energy is proposed and examined, for atoms and ions, at distances in between the initial configuration of the cluster to well into the cluster's disintegration. This model is compared with a full Hartree-Fock energy calculation which accounts for the electron correlation effects using the coupled cluster method with single and double excitations with perturbative triples (CCSD(T)). Good agreement is found between the two lending a strong theoretical support to works which rely on such models for the final and transient properties of the laser-cluster interaction.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
NASA NTRS1989

Low-temperature transonic cooling flows in galaxy clusters

Calculations are presented which demonstrate that cooling flow models with large sonic radii may be consistent with observed cluster gas properties. It is found that plausible cluster parameters and cooling flow mass accretion rates can produce sonic radii of 10-20 kpc for sonic point temperatures of 1-3 x 10 to the 6th K. The numerical calculations match these cooling flows to hydrostatic atmosphere solutions for the cluster gas beyond the cooling flow region. The cooling flows produce no appreciable 'holes' in the surface brightness toward the cluster center, and the model can be made to match the observed X-ray surface brightness of three clusters in which cooling flows had been believed to be absent. It is suggested that clusters with low velocity dispersion may be the natural location for such 'cool' cooling flows, and fits of these models to the X-ray surface brightness profiles for three clusters are presented.

Sulkanen, Martin E.↗
DOE OSTI2016

Atomic structure of Pt nanoclusters supported by graphene/Ir(111) and reversible transformation under CO exposure

We investigate the atomic structure of graphene/Ir(111) supported platinum clusters with on average fewer than 40 atoms by means of surface x-ray diffraction (SXRD), grazing incidence small angle x-ray scattering (GISAXS), and normal incidence x-ray standing waves (NIXSW) measurements, in comparison with density functional theory calculations (DFT). GISAXS revealed that the clusters with 1.3 nm diameter form a regular array with domain sizes of 90 nm. SXRD shows that the 1–2 monolayer high, (111) oriented Pt nanoparticles grow epitaxially on the graphene support. From the combined analysis of the SXRD and NIXSW data, a three-dimensional (3D) structural model of the clusters and the graphene support can be deduced which is in line with the DFT results. For the clusters grown in ultrahigh vacuum the lattice parameter is reduced by (4.6±0.1)% compared to bulk platinum. The graphene layer undergoes a strong Pt adsorption induced buckling, caused by a rehybridization of the carbon atoms below the cluster. Lastly, in situ observation of the Pt clusters in CO and O 2 environments revealed a reversible change of the clusters' strain state while successively dosing CO at room temperature and O 2 at 575 K, pointing to a CO oxidation activity of the Pt clusters.

74 ATOMIC AND MOLECULAR PHYSICS↗
NASA NTRS2014

Use of Machine Learning Techniques for Iidentification of Robust Teleconnections to East African Rainfall Variability in Observations and Models

Providing advance warning of East African rainfall variations is a particular focus of several groups including those participating in the Famine Early Warming Systems Network. Both seasonal and long-term model projections of climate variability are being used to examine the societal impacts of hydrometeorological variability on seasonal to interannual and longer time scales. The NASA / USAID SERVIR project, which leverages satellite and modeling-based resources for environmental decision making in developing nations, is focusing on the evaluation of both seasonal and climate model projections to develop downscaled scenarios for using in impact modeling. The utility of these projections is reliant on the ability of current models to capture the embedded relationships between East African rainfall and evolving forcing within the coupled ocean-atmosphere-land climate system. Previous studies have posited relationships between variations in El Niño, the Walker circulation, Pacific decadal variability (PDV), and anthropogenic forcing. This study applies machine learning methods (e.g. clustering, probabilistic graphical model, nonlinear PCA) to observational datasets in an attempt to expose the importance of local and remote forcing mechanisms of East African rainfall variability. The ability of the NASA Goddard Earth Observing System (GEOS5) coupled model to capture the associated relationships will be evaluated using Coupled Model Intercomparison Project Phase 5 (CMIP5) simulations.

Roberts, J. Brent↗
NASA NTRS2020

Assisted Authoring of Model-Based Systems Engineering Documents

In systems engineering practices system design and analysis have historically been performed using a document-centric approach where stakeholders produce a number of documents that represent their views on a system under development. Given the ad-hoc, disparate, and informal nature of natural language documents, these views become quickly inconsistent. Rigor in engineering work is also lost in the transition from model based engineering design and analysis to engineering documents. Once the documents are delivered, the engineering portion of the work is disconnected. In the Open Model Based Engineering Environment (OpenMBEE), Cross-References (aka transclusions) synthesize data for engineering when the information is not simply hyperlinked, but referenced in place in a document, upgrading a document-based process with model-based engineering technology. Those Cross-References are nowadays partially created manually, putting a burden on the engineer who is authoring the document.This paper presents an approach which can assist the engineer by providing machine-generated suggestions for Cross-References using language processing, graph analysis, and clustering technologies on model data managed by the OpenMBEE infrastructure.

Gomes, Ivan↗