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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 1,171 records · Page 65
All sourcesNASA NTRSDOE OSTI
DOE OSTI2020

The Heavy Rainfall Mechanism Revealed by a Terrain-Resolving 4DVar Data Assimilation System—A Case Study

In this study, a newly developed terrain-resolving four-dimensional variational (4DVar)-based data assimilation system, Immersed Boundary Method_Variational Doppler Radar Analysis System (IBM_VDRAS), is applied to investigate the mechanisms leading to a heavy precipitation event that occurred in Taiwan during the Southwesterly Monsoon Experiment (SoWMEX) conducted in 2008. The multivariate analyses using IBM_VDRAS and surface observations reveal that the warm and moist southwesterly flow from the ocean decelerates after making landfall, forming a surface convergence zone along the coast, which is further strengthened during the passage of a prefrontal rainband. The flow ascends as it advances inland until reaching the mountains, producing persistent precipitation and the enhancement of evaporative cooling as well as a widespread high pressure zone. A very shallow (<0.4 km) layer of offshore flow can be identified over the southwestern plain, which helps to generate a quasi-stationary convergence zone near the coast. Furthermore, sensitivity studies are carried out to quantify the relative importance of the contributions made by topographic blockage, evaporative cooling, and their nonlinear interaction, to the evolution of this type of convective system. The influence of the topography is identified as the dominant factor in modulating the flow structure of the rainfall system. However, it is the nonlinear interaction between terrain and evaporation that determines the distribution of the temperature and pressure fields.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2022

The maximum extent of the filaments and sheets in the cosmic web: an analysis of the SDSS DR17

Filaments and sheets are striking visual patterns in cosmic web. The maximum extent of these large-scale structures are difficult to determine due to their structural variety and complexity. We construct a volume-limited sample of galaxies in a cubic region from the SDSS, divide it into smaller subcubes and shuffle them around. We quantify the average filamentarity and planarity in the 3D galaxy distribution as a function of the density threshold and compare them with those from the shuffled realizations of the original data. The analysis is repeated for different shuffling lengths by varying the size of the subcubes. The average filamentarity and planarity in the shuffled data show a significant reduction when the shuffling scales are smaller than the maximum size of the genuine filaments and sheets. We observe a statistically significant reduction in these statistical measures even at a shuffling scale of $\sim 130 \, {{\, \rm Mpc}}$, indicating that the filaments and sheets in three dimensions can extend up to this length scale. They may extend to somewhat larger length scales that are missed by our analysis due to the limited size of the SDSS data cube. We expect to determine these length scales by applying this method to deeper and larger surveys in future.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2023

rBahadur: efficient simulation of structured high-dimensional genotype data with applications to assortative mating

Existing methods for generating synthetic genotype data are ill-suited for replicating the effects of assortative mating (AM). We propose rb_dplr, a novel and computationally efficient algorithm for generating high-dimensional binary random variates that effectively recapitulates AM-induced genetic architectures using the Bahadur order-2 approximation of the multivariate Bernoulli distribution. The rBahadur R library is available through the Comprehensive R Archive Network at https://CRAN.R-project.org/package=rBahadur.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2015

Temperature-dependent ordering phenomena in single crystals of germanium antimony tellurides

The temperature-dependent behavior of quenched single-crystalline (GeTe){sub n}Sb{sub 2}Te{sub 3} (n~2.8, n~5 and n~11) was investigated by semiquantitative modeling of diffuse X-ray scattering. The structure at room temperature exhibits trigonal twin domains, each comprising a stacking-disordered sequence of distorted rocksalt-type slabs with variable thicknesses. Ge and Sb share the cation position and vacancies are partially ordered in defect layers (van der Waals gaps) between the slabs. The average structure determined with resonant diffraction data corresponds to a rocksalt-type structure whose cation position is split along the stacking direction. Upon heating, cation ordering leads to a metastable superstructure of the rocksalt type at ~400 °C, which transforms to a rocksalt-type high-temperature phase with randomly distributed cations and vacancies at ~500 °C; this structure was also refined using resonant diffraction. Cooling at high or intermediate rates does not yield the long-range ordered phase, but directly leads to the twinned disordered phase. - Graphical abstract: Development of the diffraction patterns of (GeTe){sub ~11}Sb{sub 2}Te{sub 3} upon heating; the insets symbolically sketch the real structure at the corresponding temperatures. - Highlights: • The structure of disordered (GeTe){sub n}Sb{sub 2}Te{sub 3} is described as a function of temperature. • Structural changes are tracked by modeling diffuse X-ray scattering. • Quenched crystals exhibit distorted NaCl-type slabs with different thicknesses. • Vacancy ordering upon heating leads to a metastable superstructure of the NaCl type. • Further heating leads to an undistorted disordered NaCl-type high-temperature phase.

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

Core–Shell to Doped Quantum Dots: Evolution of the Local Environment Using XAFS

Internal structure study at an atomic level is a challenging task with far reaching consequences to its material properties, specifically in the field of transition metal doping in quantum dots. Diffusion of transition metal ions in and out of quantum dots forming magnetic clusters has been a major bottleneck in this class of materials. Diffusion of the magnetic ions from the core into the nonmagnetic shell in a core/shell heterostructure architecture to attain uniform doping has been recently introduced and yet to be understood. In this work, we have studied the local structure variation of Fe as a function of CdS matrix thickness and annealing time during the overcoating of Fe 3 O 4 core with CdS using X-ray absorption spectroscopy. The data reveals that Fe 3 O 4 core initially forms a core/shell structure with CdS followed by alloying at the interface eventually completely diffusing all the way through the CdS matrix to form homogeneously Fe-doped CdS QDs with excellent control over size and size distribution. Study of Fe K-edge shows a complete change of Fe local environment from Fe–O to FeS.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2020

New interaction potentials for borate glasses with mixed network formers

Here, we adapt and apply a recently developed optimization scheme used to obtain effective potentials for aluminosilicate glasses to include the network former boron into the interaction parameter set. As input data for the optimization, we used the radial distribution functions of the liquid at high temperature generated by ab initio molecular dynamics simulations, and density, coordination, and elastic modulus of glass at room temperature from experiments. The new interaction potentials are shown to reliably reproduce the structure, coordination, and mechanical properties over a wide range of compositions for binary alkali borates. Furthermore, the transferability of these new interaction parameters allows mixing to reliably reproduce the properties of various boroaluminate and borosilicate glasses.

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

Modeling the aqueous interface of amorphous TiO 2 using deep potential molecular dynamics

Amorphous titanium dioxide (a-TiO 2 ) is widely used as a coating material in applications such as electrochemistry and self-cleaning surfaces where its interface with water has a central role. However, little is known about the structures of the a-TiO 2 surface and aqueous interface, particularly at the microscopic level. In this work, we construct a model of the a-TiO 2 surface via a cut-melt-and-quench procedure based on molecular dynamics simulations with deep neural network potentials (DPs) trained on density functional theory data. After interfacing the a-TiO 2 surface with water, we investigate the structure and dynamics of the resulting system using a combination of DP-based molecular dynamics (DPMD) and ab initio molecular dynamics (AIMD) simulations. Both AIMD and DPMD simulations reveal that the distribution of water on the a-TiO 2 surface lacks distinct layers normally found at the aqueous interface of crystalline TiO 2 , leading to an ~10 times faster diffusion of water at the interface. Bridging hydroxyls (Ti 2 –O b H) resulting from water dissociation decay several times more slowly than terminal hydroxyls (Ti–O w H) due to fast Ti–O w H 2 → Ti–O w H proton exchange events. These results provide a basis for a detailed understanding of the properties of a-TiO 2 in electrochemical environments. Moreover, the procedure of generating the a-TiO 2 -interface employed here is generally applicable to studying the aqueous interfaces of amorphous metal oxides.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2024

Alkali hydroxide (LiOH, NaOH, KOH) in water: Structural and vibrational properties, including neutron scattering results

Structural and vibrational properties of aqueous solutions of alkali hydroxides (LiOH, NaOH, and KOH) are computed using quantum molecular dynamics simulations for solute concentrations ranging between 1 and 10M. Element-resolved partial radial distribution functions, neutron and x-ray structure factors, and angular distribution functions are computed for the three hydroxide solutions as a function of concentration. The vibrational spectra and frequency-dependent conductivity are computed from the Fourier transforms of velocity autocorrelation and current autocorrelation functions. Our results for the structure are validated with the available neutron data for 17M concentration of NaOH in water [Semrouni et al., Phys. Chem. Chem. Phys. 21, 6828 (2019)]. We found that the larger ionic radius [rLi+

Chemistry↗
DOE OSTI2015

Alpha-spectrometry and fractal analysis of surface micro-images for characterisation of porous materials used in manufacture of targets for laser plasma experiments

We present the results of employing the alpha-spectrometry method to determine the characteristics of porous materials used in targets for laser plasma experiments. It is shown that the energy spectrum of alpha-particles, after their passage through porous samples, allows one to determine the distribution of their path length in the foam skeleton. We describe the procedure of deriving such a distribution, excluding both the distribution broadening due to statistical nature of the alpha-particle interaction with an atomic structure (straggling) and hardware effects. The fractal analysis of micro-images is applied to the same porous surface samples that have been studied by alpha-spectrometry. The fractal dimension and size distribution of the number of the foam skeleton grains are obtained. Using the data obtained, a distribution of the total foam skeleton thickness along a chosen direction is constructed. It roughly coincides with the path length distribution of alpha-particles within a range of larger path lengths. It is concluded that the combined use of the alpha-spectrometry method and fractal analysis of images will make it possible to determine the size distribution of foam skeleton grains (or pores). The results can be used as initial data in theoretical studies on propagation of the laser and X-ray radiation in specific porous samples. (laser plasma)

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
DOE OSTI2014

A deep Chandra observation of oxygen-rich supernova remnant B0049-73.6 in the Small Magellanic Cloud

We report on the initial results from our deep Chandra observation (450 ks) of O-rich supernova remnant (SNR) B0049-73.6 in the Small Magellanic Cloud. We detect small metal-rich ejecta features extending out to the outermost boundary of B0049-73.6, which were not seen in the previous data with a shorter exposure. The central nebula is dominated by emission from reverse-shocked ejecta material enriched in O, Ne, Mg, and Si. O-rich ejecta distribution is relatively smooth throughout the central nebula. In contrast, the Si-rich material is highly structured. These results suggest that B0049-73.6 was produced by an asymmetric core-collapse explosion of a massive star. The estimated abundance ratios among these ejecta elements are in plausible agreement with the nucleosynthesis products from the explosion of a 13-15 M{sub ☉} progenitor. The central ring-like (in projection) ejecta nebula extends to ∼9 pc from the SNR center. This suggests that the contact discontinuity may be located at a further distance from the SNR center than the previous estimate. We estimate the Sedov age of ∼17,000 yr and an explosion energy of E{sub 0} ∼1.7 × 10{sup 51} erg for B0049-73.6. We place a stringent upper limit on the 2-7 keV band luminosity of L{sub X} ∼ 8.5 × 10{sup 31} erg s{sup –1} for the embedded compact stellar remnant at the center of B0049-73.6.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2025

Neural-network extraction of unpolarised transverse-momentum-dependent distributions

We present the first extraction of transverse-momentum-dependent distributions of unpolarized quarks from experimental Drell-Yan data using neural networks to parametrize their nonperturbative part. We show that neural networks outperform traditional parametrizations providing a more accurate description of data. This Letter establishes the feasibility of using neural networks to explore the multidimensional partonic structure of hadrons and paves the way for more accurate determinations based on machine-learning techniques.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2025

Gamma Decay of the 154 Sm Isovector Giant Dipole Resonance: Smekal-Raman Scattering as a Novel Probe of Nuclear Ground-State Deformation

𝛾 decays of the isovector giant dipole resonance (IVGDR) of the deformed nucleus 154 Sm were measured using 2$^{+}_{1}$-Smekal-Raman and elastic scattering of linearly polarized, quasimonochromatic photon beams. The two scattering processes were disentangled through their distinct angular distributions. Their branching ratio and cross sections were determined at six excitation energies covering the 154 Sm IVGDR. Both agree with the predictions of the geometrical model for the IVGDR and confirm 𝛾 decay as an observable sensitive to the structure of the resonance. Consequently, the data place strong constraints on the nuclear shape, including the degree of triaxiality. The derived 154 Sm shape parameters 𝛽 = 0.2925⁢(25) and 𝛾 = 5.0⁢(15)° agree well with other measurements and recent Monte Carlo shell-model calculations.

150 ≤ A ≤ 189↗
DOE OSTI2024

The Pixel Anomaly Detection Tool : a user-friendly GUI for classifying detector frames using machine-learning approaches

Data collection at X-ray free electron lasers has particular experimental challenges, such as continuous sample delivery or the use of novel ultrafast high-dynamic-range gain-switching X-ray detectors. This can result in a multitude of data artefacts, which can be detrimental to accurately determining structure-factor amplitudes for serial crystallography or single-particle imaging experiments. Here, a new data-classification tool is reported that offers a variety of machine-learning algorithms to sort data trained either on manual data sorting by the user or by profile fitting the intensity distribution on the detector based on the experiment. This is integrated into an easy-to-use graphical user interface, specifically designed to support the detectors, file formats and software available at most X-ray free electron laser facilities. The highly modular design makes the tool easily expandable to comply with other X-ray sources and detectors, and the supervised learning approach enables even the novice user to sort data containing unwanted artefacts or perform routine data-analysis tasks such as hit finding during an experiment, without needing to write code.

47 OTHER INSTRUMENTATION↗
DOE OSTI2023

Alternatives to Contour Visualizations for Power Systems Data

Electrical grids are geographical and topological structures whose voltage states are challenging to represent accurately and efficiently for visual analysis. The current common practice is to use colored contour maps, yet these can misrepresent the data. We examine the suitability of four alternative visualization methods for depicting voltage data in a geographically dense distribution system - Voronoi polygons, H3 tessellations, S2 tessellations, and a network-weighted contour map. We find that Voronoi tessellations and network-weighted contour maps more accurately represent the statistical distribution of the data than regular contour maps.

MATHEMATICS AND COMPUTING,POWER TRANSMISSION AND D↗
DOE OSTI2018

Design and Analysis Progress of ITER Diagnostic Equatorial Port #09

ITER is the world's largest fusion device currently under construction in the South of France with >50 diagnostic systems to be installed inside the port plugs (PPs), the interspace (IS), or the port cell region of various diagnostic ports. The plasma facing diagnostic first wall (DFW) and its supporting diagnostic shield modules (DSM) are designed to protect front-end diagnostics from plasma neutron and plasma radiation, while providing apertures for diagnostic access to the plasma. The design of ITER port plug structures including the DFW and the DSM is largely driven by the electromagnetic loads included on the PP structural components during plasma major disruptions and the vertical displacement events (VDEs). Unlike DFW and DSM, the design of diagnostic system, however, is likely driven by the steady-state thermal loads from plasma volumetric and surface heating and the dynamic response of the in-port components attached to the port-specific DSM or closure plate under transient loads induced on the vacuum vessel and the port extension during asymmetric VDEs. Three tenant diagnostic systems are integrated into the equatorial port 09. The toroidal interferometer/polarimeter, or TIP system, is installed in the left drawer (DSM3, left looking from plasma) for measuring the plasma density so to control the fuel input. The electron cyclotron emission (ECE) system is installed in the middle drawer (DSM2) to provide the high spatial and temporal resolution measurements of electron temperature evolution and the electron thermal transport inferences. The visible/infrared wide angle viewing system is installed in the right drawer (DSM1) to provide visible and infrared viewing and temperature data of the first wall for its protection in support of machine operation. The port plug integration design and multiphysics analyses are performed following port integration requirements including the weight limit (45 tones total), shut down dose rate limits, the cooling/heating and structural integrity validation. Mass distribution for TIP and ECE DSMs has been optimized to minimize the total weight by a new design of the boron carbide shielding pocket. Furthermore, the lightened DSM maintains its front-end load distribution and the structural stiffness with minimum impact to the DFW so to better protect on-board diagnostics; while still provides sufficient front-end stiffness for its structural integrity as well as the diagnostics function requirements.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2022

Structural analyses of amorphous calcium carbonate before and after removing strontium ions from an aqueous solution

Amorphous calcium carbonate (ACC) is a precursor of crystalline calcium carbonate; hence, its structural information at the atomic level is very important for controlling the morphology of crystalline calcium carbonate. In this study, we attempted to elucidate the process of Sr extraction from aqueous solution by using ACC for the purpose of removal of radioactive Sr from the contaminated water leaked after the Fukushima Daiichi nuclear accident. Here, the pair distribution functions, g(r) obtained by X-ray and neutron diffraction (ND) measurements show that ACC has a structure partially similar to that of monohydrocalcite, suggesting that ACC is transferred to the crystalline calcium carbonate starting from its crystal nucleus. Rietveld analysis of the ND data showed that the ACC that removed Sr was crystallized to calcite. However, the Sr–O coordination analyzed using extended X-ray absorption fine structure (EXAFS) implies that the local environment of O around Sr is similar to that in crystalline calcium carbonate aragonite.

36 MATERIALS SCIENCE↗
DOE OSTI2016

Measuring and Modeling Bipartite Graphs with Community Structure

Network science is a powerful tool for analyzing complex systems in fields ranging from sociology to engineering to biology. This paper is focused on generative models of bipartite graphs, also known as two-way graphs. We propose two generative models that can be easily tuned to reproduce the characteristics of real-world networks, not just qualitatively, but quantitatively. The measurements we consider are the degree distributions and the bipartite clustering coefficient, which we refer to as the metamorphosis coefficient. We define edge, node, and degreewise metamorphosis coefficients, enabling a more detailed understand of the bipartite community structure. Our proposed bipartite Chung-Lu model is able to reproduce real-world degree distributions, and our proposed bipartite “BTER” model reproduces both the degree distributions as well as the degreewise metamorphosis coefficients. We demonstrate the effectiveness of these models on several real-world data sets.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2020

Predicting Emission Source Terms in a Reduced-Order Fire Spread Model—Part 1: Particulate Emissions

A simple, easy-to-evaluate, surrogate model was developed for predicting the particle emission source term in wildfire simulations. In creating this model, we conceptualized wildfire as a series of flamelets, and using this concept of flamelets, we developed a one-dimensional model to represent the structure of these flamelets which then could be used to simulate the evolution of a single flamelet. A previously developed soot model was executed within this flamelet simulation which could produce a particle size distribution. Executing this flamelet simulation 1200 times with varying conditions created a data set of emitted particle size distributions to which simple rational equations could be tuned to predict a particle emission factor, mean particle size, and standard deviation of particle sizes. These surrogate models (the rational equation) were implemented into a reduced-order fire spread model, QUIC-Fire. Using QUIC-Fire, an ensemble of simulations were executed for grassland fires, southeast U.S. conifer forests, and western mountain conifer forests. Resulting emission factors from this ensemble were compared against field data for these fire classes with promising results. Also shown is a predicted averaged resulting particle size distribution with the bulk of particles produced to be on the order of 1 μm in size.

54 ENVIRONMENTAL SCIENCES↗