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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 649 records · Page 36

X-Ray Diffraction and Electron Microscopy Studies of the Size Effects on Pressure-Induced Phase Transitions in CdS Nanocrystals

In recent years, investigations of the phase transition behavior of semiconducting nanoparticles under high pressure has attracted increasing attention due to their potential applications in sensors, electronics, and optics. However, current understanding of how the size of nanoparticles influences this pressure-dependent property is somewhat lacking. In particular, phase behaviors of semiconducting CdS nanoparticles under high pressure have not been extensively reported. Therefore, in this work, CdS nanoparticles of different sizes are used as a model system to investigate particle size effects on high-pressure-induced phase transition behaviors. In particular, 7.5, 10.6, and 39.7 nm spherical CdS nanoparticles are synthesized and subjected to controlled high pressures up to 15 GPa in a diamond anvil cell. Analysis of all three nanoparticles using in-situ synchrotron wide-angle X-ray scattering (WAXS) data shows that phase transitions from wurtzite to rocksalt occur at higher pressures than for bulk material. Bulk modulus calculations not only show that the wurtzite CdS nanomaterial is more compressible than rocksalt, but also that the compressibility of CdS nanoparticles depends on their particle size. Furthermore, sintering of spherical nanoparticles into nanorods was observed for the 7.5 nm CdS nanoparticles. Our results provide new insights into the fundamental properties of nanoparticles under high pressure that will inform designs of new nanomaterial structures for emerging applications.

Meng, Lingyao↗

MIRACAL: A mission radiation calculation program for analysis of lunar and interplanetary missions

A computational procedure and data base are developed for manned space exploration missions for which estimates are made for the energetic particle fluences encountered and the resulting dose equivalent incurred. The data base includes the following options: statistical or continuum model for ordinary solar proton events, selection of up to six large proton flare spectra, and galactic cosmic ray fluxes for elemental nuclei of charge numbers 1 through 92. The program requires an input trajectory definition information and specifications of optional parameters, which include desired spectral data and nominal shield thickness. The procedure may be implemented as an independent program or as a subroutine in trajectory codes. This code should be most useful in mission optimization and selection studies for which radiation exposure is of special importance.

Nealy, John E.↗

FiXR : a framework to reconstruct fiber cross-sections from X-ray fiber diffraction experiments

Ab initio reconstruction methods have revolutionized the capabilities of small-angle X-ray scattering (SAXS), allowing the data-driven discovery of previously unknown molecular conformations, exploiting optimization heuristics and assumptions behind the composition of globular molecules. While these methods have been successful for the analysis of small particles, their impact on fibrillar assemblies has been more limited. The micrometre-range size of these assemblies and the complex interaction of their periodicities in their scattering profiles indicate that the discovery of fibril structures from SAXS measurements requires novel approaches beyond extending existing tools for molecular discovery. In this work, it is proposed to use SAXS measurements, together with diffraction theory, to infer the electron distribution of the average cross-section of a fiber. This cross-section is modeled as a discrete electron density with continuous support, allowing representations beyond binary distributions. Additional constraints, such as non-negativity or smoothness/connectedness, can also be added to the framework. The proposed approach is tested using simulated SAXS data from amyloid β fibril models and using measured data of Tobacco mosaic virus from SAXS experiments, recovering the geometry and density of the cross-sections in all cases. The approach is further tested by analyzing SAXS data from different amyloid β fibril assemblies, with results that are in agreement with previously proposed models from cryo-EM measurements. The limitations of the proposed method, together with an analysis of the robustness of the method and the combination with different experimental sources, are also discussed.

Biochemistry & Molecular Biology↗

Hierarchical Analysis of Halo Center in Cosmology

Ever-increasing data size raises many challenges for scientific data analysis. Particularly in cosmological N-body simulation, finding the center of a dark matter halo suffers heavily from the large computational cost associated with the large number of particles (up to 20 million). In this work, we exploit the latent structure embed in a halo, and we propose a hierarchical approach to approximate the exact gravitational potential calculation for each particle in order to more efficiently find the halo center. Tests of our method on data from N-body simulations show that in many cases the hierarchical algorithm performs significantly faster than existing methods with a desirable accuracy.

97 MATHEMATICS AND COMPUTING↗

Pele: An Exascale-Ready Suite of Combustion Codes

High fidelity simulations of realistic combustion devices are extremely demanding computationally because of the requirements to capture complex fuel chemical decomposition, its intricate interactions with turbulent, often multiphase, flows, and the wide separation of space and time scales between the thin flame and the device boundaries. Software required to carry out such computations tends to be extremely complex, particularly when designed to exploit hardware accelerators, and can be difficult to port and maintain. We present Pele, a performance portable suite of tools for the simulation of combustion systems, including codes to evolve reactive multiphase configurations in the low Mach number and compressible flow regimes, along with a set of inter-compatible post processing and in situ analysis tools. The Pele suite of tools is built on top of the AMReX framework for block-structured adaptive mesh refinement, which provides efficient data structures and algorithms that enable the development of a wide variety of efficient mesh and particle based PDE integration schemes. A hierarchical MPI+X parallelism scheme supports CPU-only and accelerated architectures, where X can be OpenMP, CUDA, and HIP based approaches for intra-node computational work distribution. The algorithms and data structures underlying the Pele simulation and analysis tools are highly scalable and performant across a wide variety of high-performance computing platforms, including DOEs newest exascale-class machines, Frontier and Aurora. The simulation and analysis tools are fully documented and freely distributed as open source via GitHub. We present key algorithmic and software challenges, solution strategies, performance and resulting set of capabilities.

AMReX↗

Control And Optimization Modular Modeling Application For Nuclear Deployment

The purpose of the COMMAND code is to provide a flexible, scalable tool for use in developing, integrating, and testing the technologies necessary for achieving autonomous operations of advanced nuclear reactors. The code enables users to efficiently implement custom simulations and experiments by combining key methods from different software modules. These modules are focused on: modeling and simulation tools, such as nuclear simulation tools used for high-fidelity modeling (e.g., Reactor Excursion and Leak Analysis Program [RELAP5-3D] and Monte Carlo N-Particle [MCNP]); machine learning and optimization tools (e.g., anomaly detection and data-driven modeling techniques); advanced control in its digital, high-performance, and supervisory control forms (e.g., proportional integral derivative (PID) control and model predictive control (MPC); and integration with hardware through industrial communication protocols. To ensure flexibility and scalability, COMMAND was designed to be both modular—the software “pieces” all inherit from generic building blocks and can be combined and connected to create complicated simulations—and high performing—designed for parallel processing, enabling simulations and experiments to take advantage of multi-core computers, servers, and nodes. The code is written in the Python programming language due to the language's popularity, active community, and open-source and cross-platform nature. Maintaining consistency with other simulation tools used within the nuclear energy community, users implement simulations and experiments through text input files, which define components, parameters, connections, etc., through lines of text. Given that COMMAND is written in Python, these input files are native Python scripts, and so use the standard Python structure and formatting. This also enables users to take advantage of Python's extensive package library to develop custom capabilities for their specific use cases.

Faber, Jacob [Idaho National Laboratory (INL), Ida↗

Effects of additively manufactured surface roughness on small diameter plenums with multiple side discharges for high temperature gas turbine blade cooling applications

Combined heat and power (CHP) applications have significant environmental and economic benefits that are consistent with the goals of the U.S. Department of Energy (DOE). One area that is currently being studied includes the potential benefits of CHP turbine operation at higher turbine inlet temperatures. Internal cooling concepts enabled by additive manufacturing (AM) are of primary interest. Here, the effectiveness of internal cooling is hindered by many factors such as velocity distribution of the cooling air to the hot surface considering impingement cooling. To simulate cooling air exiting from a series of orifices for internal cooling in an airfoil, a straight smooth wall tubing with multiple side discharging orifices is used and compared to additively manufactured tubing (Ti6Al4V Grade 23) with orifice size and spacing as well as inner and outer diameters identical to the smooth wall tubing. Similar to flow discharging form perforated pipes, the flow discharged from individual orifices along the tubes in this study is found to be nonuniformly distributed, and the horizontal (axial direction) momentum can be observed from the experimental data. Discharge velocities have been measured with two-dimensional (2D) particle imaging velocimetry (PIV) and single element hot wire anemometry. Numerical analysis has also been conducted to predict the velocity distributions along the orifices in the smooth wall and additive manufacturing (AM) tubing, which are inherited with surface roughness. Numerical and measured results in this study are compared, presented, and discussed.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

Air pollution source identification

The techniques available for source identification are reviewed: remote sensing, injected tracers, and pollutants themselves as tracers. The use of the large number of trace elements in the ambient airborne particulate matter as a practical means of identifying sources is discussed. Trace constituents are determined by sensitive, inexpensive, nondestructive, multielement analytical methods such as instrumental neutron activation and charged particle X-ray fluorescence. The application to a large data set of pairwise correlation, the more advanced pattern recognition-cluster analysis approach with and without training sets, enrichment factors, and pollutant concentration rose displays for each element is described. It is shown that elemental constituents are related to specific source types: earth crustal, automotive, metallurgical, and more specific industries. A field-ready source identification system based on time and wind direction resolved sampling is described.

Fordyce, J. S.↗

Magnetospheric protons and electrons encountered by the moon in the plasma sheet

Results are summarized for a study of plasma-sheet particles (and their flow) encountered by the moon during its passage through the geomagnetic tail. The study is based on analysis of data obtained with a modulated Faraday cup on board the lunar-anchored spacecraft Explorer 35. It is shown that the electrons have a rapidly fluctuating non-Maxwellian energy distribution with a mean energy of several hundred electron volts and a density of approximately 0.2 per cu cm. Protons with energies of the order of 1 keV were usually detected above the instrument background when flowing towards earth at about 200 km/sec. It is suggested that strong terrestrial polar winds during the early history of the earth-moon system could have caused some erosion of the front side of the moon and that the relative smoothness of the same side could be explained in terms of gravitational shielding by the earth from the interplanetary rock flux.

Prakash, A.↗

Data and analysis procedures for improved aerial applications mission performance

An analysis procedure is given and cases analyzed for the effects of wing geometry on lateral transport of a variety of agricultural particles released in the wake of an agricultural airplane. The cases analyzed simulate the release of particles from a fuselage centerline-mounted dry material spreader; however, the procedure applies to particles released anywhere along the wing span. Consideration is given to the effects of taper ratio, aspect ratio, wing loading, and deflected flaps. It is noted that significant lateral transport of large particles can be achieved using high-lift devices positioned to create a strong vortex near the location of particle release.

Holmes, B. J.↗

Use of the thin sheath approximation for obtaining ion temperatures from the ISEE 1 limited aperture RPA

A procedure for analyzing low-energy (less than approximately 100 eV) ion data from the plasma composition experiment on ISEE 1 is set forth. The method is based on a derived analytic expression for particle flux to a limited aperture retarding potential analyzer (RPA) in the thin sheath approximation, which makes allowance for some effects of a charged spacecraft on plasma particle trajectories. Calculations using simulated data are employed in testing the efficacy and accuracy of the technique. On the basis of an analysis of these calculation results and the mathematical model, the method is seen as being able to provide accurate ion temperatures from all good plasmaspheric RPA data. It is noted that corresponding densities and spacecraft potentials should be accurate when spacecraft potentials are negative but that they are subject to error for positive spacecraft potentials, particularly when ion Mach numbers are much less than 1. An analysis of data from a representative ISEE 1 pass produces a plasmasphere temperature profile that is consistent in overall structure with previous observations.

Comfort, R. H.↗

Angular distribution and multiplicity of backward hadrons in hFe interactions at 0.5-5.0 TeV energies (PION Experiment)

Based on the analysis of approximates 5 X 1000 events registered on the PION installation, data are obtained on the angular distribution and multiplicity of particles, flying back into the laboratory coordinate system (LCS) that are identified mainly as hadrons produced in the reactions of hFe yield h prime X type. The inclusively produced hadron energy is 200 MeV. The experimental data are compared to the results of the cumulative particle production in hA processes observed on accelerators at lower energies.

Avakian, V. V.↗

Quantitative determination of mineral types and abundances from reflectance spectra using principal components analysis

A procedure was developed for analyzing remote reflectance spectra, including multispectral images, that quantifies parameters such as types of mineral mixtures, the abundances of mixed minerals, and particle sizes. Principal components analysis reduced the spectral dimensionality and allowed testing the uniqueness and validity of spectral mixing models. By analyzing variations in the overall spectral reflectance curves, the type of spectral mixture was identified, mineral abundances quantified and the effects of particle size identified. The results demonstrate an advantage in classification accuracy over classical forms of analysis that ignore effects of particle-size or mineral-mixture systematics on spectra. The approach is applicable to remote sensing data of planetary surfaces for quantitative determinations of mineral abundances.

Smith, M. O.↗

Image analysis of particle field by means of computed tomography

In order to visualize and investigate spray structures, computed tomography technique is applied to analyze droplet information. From the transmitted light intensity through the spray and/or the data of particle size distribution obtained from a Fraunhofer diffraction principle, the quantitative volume of spray droplet or local particle size was calculated and the reconstruction of spray structures was made. The background of computed tomography is described along with some experimental results of the structure of intermittent spray such as diesel spray.

Nakayama, Mitsushige↗

Applied Meteorology Unit (AMU)

This report summarizes the Applied Meteorology Unit (AMU) activities for the first quarter of Fiscal Year 2010 (October - December 2009). A detailed project schedule is included in the Appendix. Included tasks are: (1) Peak Wind Tool for User Launch Commit Criteria (LCC), (2) Objective Lightning Probability Tool, Phase III, (3) Peak Wind Tool for General Forecasting, Phase II, (4) Upgrade Summer Severe Weather Tool in Meteorological Interactive Data Display System (MIDDS), (5) Advanced Regional Prediction System (ARPS) Data Analysis System (ADAS) Update and Maintainability, (5) Verify 12-km resolution North American Model (MesoNAM) Performance, and (5) Hybrid Single-Particle Lagrangian Integrated Trajectory (HYSPLIT) Graphical User Interface.

Bauman, William↗

Multitiered computational methodology for extracting three-dimensional rotational diffusion coefficients from x-ray photon correlation spectroscopy data without structural information

X-ray photon correlation spectroscopy (XPCS) is a powerful technique for analyzing particle systems by investigating their dynamics in suspensions across a broad range of temporal and spatial scales. This is done by illuminating samples with coherent x-ray beams and calculating the correlation function of the obtained x-ray scattering images. XPCS is uniquely suited for studying Brownian dynamics, consisting of translational and rotational diffusion. While traditional XPCS image analysis techniques can extract translational diffusion components, they are unable to estimate rotational diffusion coefficients. Here, we introduce a methodology that combines the angular-temporal cross-correlation analysis and a algorithmic framework called Multi-Tiered Estimation for Correlation Spectroscopy in 3D for estimating three-dimensional rotational diffusion coefficients from XPCS images of three-dimensional particle systems. We demonstrate our methodology for extracting rotational diffusion coefficients from XPCS data by applying it to simulated noisy x-ray images of systems of crossing nanotubes and proteins that evolve under translational and rotational Brownian motion for different diffusion rates. Furthermore, our results show that our approach determines rotational diffusion coefficients within a few percent error.

97 MATHEMATICS AND COMPUTING↗

Multivariate discrimination in quantum target detection

In this work, we describe a simple multivariate technique of likelihood ratios for improved discrimination of signal and background in multi-dimensional quantum target detection. Furthermore, the technique combines two independent variables, time difference and summed energy, of a photon pair from the spontaneous parametric down-conversion source into an optimal discriminant. The discriminant performance was studied in experimental data and in Monte-Carlo modelling with clear improvement shown compared to previous techniques. As novel detectors become available, we expect this type of multivariate analysis to become increasingly important in multi-dimensional quantum optics.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

Towards Autonomous Experiments by Connecting High Performance Microscopy with High Performance Computing

The digitization of controls, data, and analysis in microscopy is bringing the idea of autonomous microscopes closer to reality than ever before. Automated transmission electron microscopy (TEM) is already fairly routine for some experiments the only require simple repetitive tasks such as imaging biological macromolecules for single particle cryoEM [1], tilt series for electron tomography [2], and movies for crystallography [3]. The vast majority of TEM experiments are conducted completely by human operators who choose the regions of interest, optimize experimental parameters, and make decisions about data quality visually during an experiment. The field is still a long way from having completely autonomous TEMs that can adapt to sample difficulties and tune experimental parameters based on data quality and desired experimental outcomes. Part of the issue is the lack of capability for feeding information learned from on-line, live data analysis back into the on-going experiment [4]. Furthermore, this presentation will discuss current capabilities for large scale data reduction and analysis using high performance computing (i.e. supercomputing) and progress towards developing a true feed-back loop that places data analysis and theory in the experimental loop.

97 MATHEMATICS AND COMPUTING↗