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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 613 records · Page 34
All sourcesNASA NTRSDOE OSTI
DOE OSTI2014

On the estimation of statistical uncertainties on powder diffraction and small-angle scattering data from two-dimensional X-ray detectors

Optimal methods are explored for obtaining one-dimensional powder pattern intensities from two-dimensional planar detectors with good estimates of their standard deviations. Methods are described to estimate uncertainties when the same image is measured in multiple frames as well as from a single frame. The importance of considering the correlation of diffraction points during the integration and the resampling process of data analysis is shown. It is found that correlations between adjacent pixels in the image can lead to seriously overestimated uncertainties if such correlations are neglected in the integration process. Off-diagonal entries in the variance–covariance (VC) matrix are problematic as virtually all data processing and modeling programs cannot handle the full VC matrix. It is shown that the off-diagonal terms come mainly from the pixel-splitting algorithm used as the default integration algorithm in many popular two-dimensional integration programs, as well as from rebinning and resampling steps later in the processing. When the full VC matrix can be propagated during the data reduction, it is possible to get accurate refined parameters and their uncertainties at the cost of increasing computational complexity. However, as this is not normally possible, the best approximate methods for data processing in order to estimate uncertainties on refined parameters with the greatest accuracy from just the diagonal variance terms in the VC matrix is explored.

Yang, X.↗
DOE OSTI2021

Universal dwell time optimization for deterministic optics fabrication

Computer-Controlled Optical Surfacing (CCOS) has been greatly developed and widely used for precision optical fabrication in the past three decades. It relies on robust dwell time solutions to determine how long the polishing tools must dwell at certain points over the surfaces to achieve the expected forms. However, as dwell time calculations are modeled as ill-posed deconvolution, it is always non-trivial to reach a reliable solution that 1) is non-negative, since CCOS systems are not capable of adding materials, 2) minimizes the residual in the clear aperture 3) minimizes the total dwell time to guarantee the stability and efficiency of CCOS processes, 4) can be flexibly adapted to different tool paths, 5) the parameter tuning of the algorithm is simple, and 6) the computational cost is reasonable. In this study, we propose a novel Universal Dwell time Optimization (UDO) model that universally satisfies these criteria. First, the matrix-based discretization of the convolutional polishing model is employed so that dwell time can be flexibly calculated for arbitrary dwell points. Second, UDO simplifies the inverse deconvolution as a forward scalar optimization for the first time, which drastically increases the solution stability and the computational efficiency. Finally, the dwell time solution is improved by a robust iterative refinement and a total dwell time reduction scheme. The superiority and general applicability of the proposed algorithm are verified on the simulations of different CCOS processes. A real application of UDO in improving a synchrotron X-ray mirror using Ion Beam Figuring (IBF) is then demonstrated. The simulation indicates that the estimated residual in the 92.3 mm × 15.7 mm CA can be reduced from 6.32 nm Root Mean Square (RMS) to 0.20 nm RMS in 3.37 min. After one IBF process, the measured residual in the CA converges to 0.19 nm RMS, which coincides with the simulation.

36 MATERIALS SCIENCE↗
DOE OSTI2022

Phase-field modeling of radiation-induced segregation for multicomponent alloys

Structural alloys under irradiation are known to undergo radiation-induced solute redistribution (RIS) at grain boundaries, leading to detrimental effects such as intergranular corrosion and stress-assisted cracking. To better understand the phenomenon, improved models of RIS applicable to concentrated, multicomponent alloys, and mesoscale microstructures are needed. In this talk, we present a novel grand-potential-based phase-field model to account for the complete set of multicomponent kinetic and thermodynamic couplings between atoms and point defects in the Onsager transport equations. We demonstrate multiscale modeling capability by deriving the Onsager coefficient matrix from atomistic-based Kinetic Monte Carlo simulations. Model predictions and validations of RIS and the effect of defect production, grain boundary sink strength and density are demonstrated for a model FCC FeCrNi system. We also demonstrate the novel capability to describe RIS in the presence of equilibrium segregation described using a density-based CALPHAD thermodynamic framework. This modeling approach overcomes certain limitations in conventional RIS models and provides a step closer towards multiscale modeling.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2022

Department of Energy Project DE-SC0012198: Probing Electron-Molecule Scattering with HHG: Theory and Experiment (Final Report)

The study of the motion of atoms in molecules is important to understanding many areas of physical and life sciences. Such motion occurs on many different times scales, with electronic motion occurring on a sub-femtosecond time scale, and simple vibrational motion in tens to hundreds of femtoseconds. One way to follow such processes in real time is by the use of shortpulsed lasers, and in particular by studying time-resolved photoionization and the related process of high-harmonic generation (HHG). Thus there has been much effort to develop the tools necessary to probe molecular systems using short pulse lasers and understanding the sensitivity of the different possible probes to the time dependent geometric structure as well as the electronic structure of molecules. Our research has particularly focused on the connection between high-field processes and the more traditional weak field photoionization processes. Strong field and weak field processes can be connected through models that involve the same matrix elements. We have demonstrated in our study of HHG from SF 6 that the spectrum is sensitive to the interplay between the angular dependence of the ionization step and recombination step. In our study of rescattering spectroscopy, we have shown that with a combination of experiment and theory, we can use this high-field spectroscopy to determine molecular structure in molecules such as C 2 H 4 . We have also developed new computational tools based on overset grids to enable studies on larger molecular systems which use much more robust numerical approaches so that the resulting code can be a tool that non-specialists can use to study related systems.

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

Capabilities of laser technology for manufacturing diagnostic peptide matrices with maximal density

The process of manufacturing a matrix-gel biochip is modelled by means of laser fused deposition of a layer of polymer microparticles, containing a sensitive peptide element, onto a glass substrate. The limits of acceptable ranges and the optimal values of laser parameters, at which the melting of the polymer coating occurs without damaging the sensitive elements of the biochip, are theoretically determined. The results of the experiments on laser fused deposition of a layer of microparticles having the size 3 – 4 μm confirm the conservation of the functions of the biological complexes at optimal irradiation regimes. The parameters of the laser impact affecting the possible minimal separation between the zones of laser fused deposition are investigated. The essential role of heat conductivity and thermoplasticity of the polymer in increasing the size of the melted droplet is demonstrated. Using the laser radiation with the wavelength 532 nm focused into a spot with the diameter 6 μm (the laser pulse duration being 10 ms) the laser fused deposition density of 110000 spots per 1 cm{sup 2} is achieved. The maximal estimated density of laser fused deposition for the studied system amounts to 250000 spots per 1 cm{sup 2}. (biophotonics)

36 MATERIALS SCIENCE↗
DOE OSTI2019

Stationary Distribution and Perturbation Bounds for a Stochastic Inventory Model

In this paper, we use the theory of generalized inverses to compute the stationary distribution of the (s, S) inventory model directly from the transition matrix of the underlying Markov chain and to provide perturbation bounds. Indeed, approximations are employed to build a tractable model, and statistical methods are used to estimate the unknown parameters and distributions. Hence, the system is subject to perturbations that may cause deviation in the characteristics. The proposed perturbation bound provides a means to estimate the impact of the perturbations on the performance measures of the considered inventory system.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2024

Diffusion-Model-Assisted Supervised Learning of Generative Models for Density Estimation

Here, we present a supervised learning framework of training generative models for density estimation. Generative models, including generative adversarial networks (GANs), normalizing flows, and variational auto-encoders (VAEs), are usually considered as unsupervised learning models, because labeled data are usually unavailable for training. Despite the success of the generative models, there are several issues with the unsupervised training, e.g., requirement of reversible architectures, vanishing gradients, and training instability. To enable supervised learning in generative models, we utilize the score-based diffusion model to generate labeled data. Unlike existing diffusion models that train neural networks to learn the score function, we develop a training-free score estimation method. This approach uses mini-batch-based Monte Carlo estimators to directly approximate the score function at any spatial-temporal location in solving an ordinary differential equation (ODE), corresponding to the reverse-time stochastic differential equation (SDE). This approach can offer both high accuracy and substantial time savings in neural network training. Once the labeled data are generated, we can train a simple, fully connected neural network to learn the generative model in the supervised manner. Compared with existing normalizing flow models, our method does not require the use of reversible neural networks and avoids the computation of the Jacobian matrix. Compared with existing diffusion models, our method does not need to solve the reverse-time SDE to generate new samples. As a result, the sampling efficiency is significantly improved. We demonstrate the performance of our method by applying it to a set of 2D datasets as well as real data from the University of California Irvine (UCI) repository.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2016

Implications of Grain-Scale Mineralogical Heterogeneity for Radionuclide Transport in Fractured Media

The geological disposal of nuclear waste is based on the multi-barrier concept, comprising various engineered and natural barriers, to confine the radioactive waste and isolate it from the biosphere. Some of the planned repositories for high-level nuclear waste will be hosted in fractured crystalline rock formations. The potential of these formations to act as natural transport barriers is related to two coupled processes: diffusion into the rock matrix and sorption onto the mineral surfaces available in the rock matrix. Different in situ and laboratory experiments have pointed out the ubiquitous heterogeneous nature of the rock matrix: mineral surfaces and pore space are distributed in complex microstructures and their distribution is far from being homogeneous (as typically assumed by Darcy-scale coarse reactive transport models). We use a synthetically generated fracture–matrix system to assess the implications of grain-scale physical and mineralogical heterogeneity on cesium transport and retention. The resulting grain-scale reactive transport model is solved using high-performance computing technologies, and the results are compared with those derived from two alternative models, denoted as upscaled models, where mineral abundance is averaged over the matrix volume. In the grain-scale model, the penetration of cesium into the matrix is faster and the penetration front is uneven and finger-shaped. The analysis of the cesium breakthrough curves computed at two different points in the fracture shows that the upscaled models provide later first-arrival time estimates compared to the grain-scale model. The breakthrough curves computed with the three models converge at late times. These results suggest that spatially averaged upscaled parameters of sorption site distribution can be used to predict the late-time behavior of breakthrough curves but could be inadequate to simulate the early behavior.

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗
DOE OSTI2015

Chemical composition analysis and product consistency tests to support enhanced Hanford waste glass models. Results for the third set of high alumina outer layer matrix glasses

In this report, the Savannah River National Laboratory provides chemical analyses and Product Consistency Test (PCT) results for 14 simulated high level waste glasses fabricated by the Pacific Northwest National Laboratory. The results of these analyses will be used as part of efforts to revise or extend the validation regions of the current Hanford Waste Treatment and Immobilization Plant glass property models to cover a broader span of waste compositions. The measured chemical composition data are reported and compared with the targeted values for each component for each glass. All of the measured sums of oxides for the study glasses fell within the interval of 96.9 to 100.8 wt %, indicating recovery of all components. Comparisons of the targeted and measured chemical compositions showed that the measured values for the glasses met the targeted concentrations within 10% for those components present at more than 5 wt %. The PCT results were normalized to both the targeted and measured compositions of the study glasses. Several of the glasses exhibited increases in normalized concentrations (NCi) after the canister centerline cooled (CCC) heat treatment. Five of the glasses, after the CCC heat treatment, had NC B values that exceeded that of the Environmental Assessment (EA) benchmark glass. These results can be combined with additional characterization, including X-ray diffraction, to determine the cause of the higher release rates.

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗
DOE OSTI2023

Enhanced Hanford High-Fluoride Waste Glass Property Data Development: Phase 1

This study focused on investigating the effects of fluorine concentration on simulated high-level waste glass properties to eventually establish a fluorine limit (as a single-component or multiple-component constraint) for glass formulations for high-fluoride Hanford wastes. This is a first step to provide data to understand the impacts of changing flowsheets on the mission duration and extent. A test matrix of 20 high-fluoride glasses was generated, and the chemical compositions were measured. The following properties were measured and tested against current model predictions: crystal formation after centerline canister cooling, crystallinity as a function of temperature, density, viscosity, electrical conductivity, toxic leaching characteristics using the toxicity characteristic leach profile (TCLP), product consistency using the product consistency test (PCT), and SO 3 solubility. Overall, current models failed to adequately predict most of the properties, possibly due to differences in compositional space used to generate the models and the current test matrix. Additional work is needed to more accurately assess the impacts of high-fluoride wastes on Hanford processing, including additional data collection over a broader composition region and model development for the key models of interest such as PCT and TCLP.

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗
DOE OSTI2019

Superconductor Nanometallic Photonic Crystals as a Novel Smart Window for Low-Temperature Applications

The control of electromagnetic wave propagation has played an essential role in recent technology. In this paper, we present a novel type of smart window using one-dimensional superconductor nanometallic photonic crystals. The present idea depends on the control of the transmittance values based on the angle of incidence of the electromagnetic waves. We have investigated the transmittance of the proposed novel smart window based on a two-fluid model and a characteristic matrix method. We also obtained the effect of the operating temperature, number of periods, and thicknesses of the constituent materials. Finally, the proposed design promises for useful applications such as space exploration, satellites, and low-temperature applications.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
DOE OSTI2019

A Tunable Optimized Low-Temperature Sensor Based on the Hybrid Photonic Crystals (F{sub 4}/Bg{sub 5}/F{sub 4}) and (Bg{sub 5}/F{sub 4}/Bg{sub 5})

In this paper, we present a novel type of low-temperature sensor based precisely on the symmetrical hybrid photonic crystals. Thanks to the two-fluid model and the transfer matrix method, we study the temperature sensitivity of the hybrid multilayers (F{sub 4}/Bg{sub 5}/F{sub 4}) and (Bg{sub 5}/F{sub 4}/Bg{sub 5}) where F{sub 4} represents the fourth iteration of the quasi-periodic Fibonacci sequence and Bg5 designates the multilayer Bragg mirror (HLS){sub 5}. We assume that the layers H, L, and S indicate precisely the dielectric materials of Bi{sub 4}Ge{sub 3}O{sub 12}, SiO{sub 2}, and YaBO{sub 2}CuO{sub 7} superconductor one. The analysis of the transmittance spectra shows that the hybrid photonic crystal is more sensitive to the temperature than the periodic one. A higher sensibility value is reached due to the possible combination of the periodic and quasi-periodic sequences. Our investigation reveals that the photonic crystal (F{sub 4}/Bg{sub 5}/F{sub 4}) is more sensitive to low temperature compared to (Bg{sub 5}/F{sub 4}/Bg{sub 5}). The sensitivity is significantly affected by the position of quasi-periodic sequences. The sensitivity of such photonic crystals can be adequately controlled by applying a symmetrical chirping. The designed structures pave the way toward the achievement of a potential low-temperature sensor.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
DOE OSTI2021

A microstructure-based modeling approach to predict the mechanical properties of Zr alloy with hydride precipitates

In nuclear reactors, hydrides can form in fuel cladding due to hydrogen absorption in ZIrcaloy and cause embrittlement. This work presents a microstructure-based finite element model to predict the stress-strain response of Zircaloy containing hydrides. Quantitative microstructural details extracted from scanning electron microscopy (SEM) images were used to generate heterogeneous microstructures including the morphology and spatial distribution of hydrides. The constitutive material model for zircaloy in this study is based on crystal plasticity theory which considers the hexagonal close-packed (HCP) atomic structure of Zircaloy material. The hydrides were modeled as brittle material along with a damage model. Hydride formation inside the zircoloy matrix results in residual stress. This phenomenon is also captured in this model. A parametric study has been conducted to understand the effect of volume fraction, orientation, and lamellae thickness of the hydride phase on the mechanical properties of the overall material.

Kulkarni, Shank S.↗
DOE OSTI2026

Designing the Protocols for Programmable Ammonia Catalysis

Programmable catalysis can provide a more energy-efficient and cost-effective route to enhancing commercial ammonia production, a key process in the advancement of renewable energy technologies and the manufacture of fertilizers and basic chemicals. This work explores the computational discovery of optimal forcing protocols to drive such dynamic catalysis models. By employing matrix-free time-stepper methods, coupled with an optimization approach, that integrates Bayesian optimization with a Bayesian continuation strategy to efficiently discover the periodic steady states of such periodically forced systems, we enable the discovery of complex optimal catalyst strain waveforms, while ensuring robust solver convergence. We demonstrate the flexibility of our approach to discover optimized forcing protocols under varying physical constraints on strain modulation or other catalyst operating parameters. We show that these can have a temporal structure more complex than simple step functions. In order to detect undesirable catalytic loops that may correlate with overall reduced performance, we perform a study using graph-theoretical analysis to investigate the dynamics of catalytic kinetic networks formed.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2014

Electronic band structure of magnetic bilayer graphene superlattices

Electronic band structure of the bilayer graphene superlattices with δ-function magnetic barriers and zero average magnetic flux is studied within the four-band continuum model, using the transfer matrix method. The periodic magnetic potential effects on the zero-energy touching point between the lowest conduction and the highest valence minibands of pristine bilayer graphene are exactly analyzed. Magnetic potential is shown also to generate the finite-energy touching points between higher minibands at the edges of Brillouin zone. The positions of these points and the related dispersions are determined in the case of symmetric potentials.

77 NANOSCIENCE AND NANOTECHNOLOGY↗
DOE OSTI2014

Study of possible chaotic, quasi-periodic and periodic structures in quantum dusty plasma

Existence of chaotic, quasi-periodic, and periodic structures of dust-ion acoustic waves is studied in quantum dusty plasmas through dynamical system approach. A system of coupled differential equations is derived from the fluid model and subsequently, variational matrix is obtained. The characteristic equation is obtained at the equilibrium point, and the behavior of nonlinear waves is studied numerically using Runge-Kutta method. The behavior of the dynamical system changes significantly when any of plasma parameters, such as the dust concentration parameter, temperature ratio, or the quantum diffraction parameter, is varied. The change of the characteristic of solution of the system is extensively studied. It is found that the system changes its behavior from chaotic pattern to limit cycle behavior.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2014

Lie, Santilli, and nanotechnology: From the elementary particles to the periodic table of the elements

Santilli’s revolutionary iso-, geno- and hypermathematics have provided the original straight line Lie groups and algebras with a span and coherence in all dimensions, and thus already at the infinitesimal level an extension in the Cartesian sense, allowing a continuous self-similar cyclical realization of matter from the elementary particle threshold level via the atomic to molecular and visible scale where it meets and marries with modern nanotechnology in the form of an isotropic vector matrix of space-filling octahedron-tetrahedron composition. This is distributed as an electron transition matrix with Bohr shell model stratified signature and is here directly outlining a new, centrally coordinated organic composition and chart of the periodic system as specifically exemplified by the noble gases.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2015

The effect of output-input isolation on the scaling and energy consumption of all-spin logic devices

All-spin logic (ASL) is a novel approach for digital logic applications wherein spin is used as the state variable instead of charge. One of the challenges in realizing a practical ASL system is the need to ensure non-reciprocity, meaning the information flows from input to output, not vice versa. One approach described previously, is to introduce an asymmetric ground contact, and while this approach was shown to be effective, it remains unclear as to the optimal approach for achieving non-reciprocity in ASL. In this study, we quantitatively analyze techniques to achieve non-reciprocity in ASL devices, and we specifically compare the effect of using asymmetric ground position and dipole-coupled output/input isolation. For this analysis, we simulate the switching dynamics of multiple-stage logic devices with FePt and FePd perpendicular magnetic anisotropy materials using a combination of a matrix-based spin circuit model coupled to the Landau–Lifshitz–Gilbert equation. The dipole field is included in this model and can act as both a desirable means of coupling magnets and a source of noise. The dynamic energy consumption has been calculated for these schemes, as a function of input/output magnet separation, and the results show that using a scheme that electrically isolates logic stages produces superior non-reciprocity, thus allowing both improved scaling and reduced energy consumption.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗