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At least 73 records · Page 4

LDRD 226360 Final Project Report: Simulated X-ray Diffraction and Machine Learning for Optimizing Dynamic Experiment Analysis

This report is the final documentation for the one-year LDRD project 226360: Simulated X-ray Diffraction and Machine Learning for Optimizing Dynamic Experiment Analysis. As Sandia has successfully developed in-house X-ray diffraction tools for study of atomic structure in experiments, it has become increasingly important to develop computational analysis methods to support these experiments. When dynamically compressed lattices and orientations are not known a priori, the identification requires a cumbersome and sometimes intractable search of possible final states. These final states can include phase transition, deformation and mixed/evolving states. Our work consists of three parts: (1) development of an XRD simulation tool and use of traditional data science methods to match XRD patterns to experiments; (2) development of ML-based models capable of decomposing and identifying the lattice and orientation components of multicomponent experimental diffraction patterns; and (3) conducting experiments which showcase these new analysis tools in the study of phase transition mechanisms. Our target material has been cadmium sulfide, which exhibits complex orientation-dependent phase transformation mechanisms. In our current one-year LDRD, we have begun the analysis of high-quality c-axis CdS diffraction data from DCS and Thor experiments, which had until recently eluded orientation identification.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗

TOUGH-RFPA: Coupled thermal-hydraulic-mechanical Rock Failure Process Analysis with application to deep geothermal wells

This paper presents a coupled thermal-hydraulic-mechanical (THM) model for simulating failure processes in geological media. The coupling between stress/strain and heat transfer describing how thermal expansion affects stress is based on the theory of thermo-elasticity. Additionally, the coupling between stress/strain and fluid flow describing how pore-pressure affects stress is governed by Biot's consolidation theory. Stress/strain-dependent porosity/permeability/capillary-pressure defines the influence of stress on fluid flow and thermal fields. The THM model is implemented in the solver module that links the multiphase, multicomponent fluid flow simulator TOUGH2 with the geomechanical simulator RFPA (Rock Failure Process Analysis), which is based on the concept that heterogeneity leads to non-linearity and progressive failure behavior. Capability of TOUGH-RFPA simulator was verified by two benchmark problems related to hydraulic-mechanical and thermal-mechanical response in a hollow cylinder. Then the applicability of TOUGH-RFPA was demonstrated for modeling cooling-induced damage around a very deep geothermal well with mesoscopic heterogeneous properties, which showed complex damage evolution and fracturing during well cooling and fluid pressurization.

42 ENGINEERING↗

Surface-slip equations for low-Reynolds-number multicomponent gas flows

Equations have been obtained for jump (or slip) in the wall values of species concentration, pressure, velocity, and temperature for the low-Reynolds-number high-altitude flight regime of a space vehicle. The analysis, based on the Chapman-Enskog method as applied by Shidlovskiy for a single-species gas, includes multicomponent diffusion with finite-rate surface catalytic recombination. A consistent set of equations is provided for multicomponent, binary, and single species mixtures.

Gupta, R. N.↗

Surface-slip equations for low-Reynolds-number multicomponent gas flows

Equations have been obtained for jump (or slip) in the wall values of species concentration, pressure, velocity, and temperature for the low-Reynolds-number high-altitude flight regime of a space vehicle. The analysis, based on the Chapman-Enskog method as applied by Shidlovskiy for a single-species gas, includes multicomponent diffusion with finite-rate surface catalytic recombination. A consistent set of equations is provided for multicomponent, binary, and single species mixtures.

Gupta, R. N.↗

Ion-acoustic solitary waves in a magnetized plasma with arbitrary electron equation of state

The oblique propagation of fully nonlinear, slow ion-acoustic solitary waves in a collisionless, low-beta, magnetized plasma is examined. The analysis includes the effects of a finite ion pressure, electron trapping, and multicomponent particle populations. The existence of both compressive and rarefactive modes propagating obliquely to the magnetic field in a plasma with two distinct Boltzmann electron populations and cold ions is demonstrated. It is shown that paired electrostatic shocks observed over the earth's auroral zone may be closely related to the rarefactive modes. As a measure of the collisionless dissipation encountered by the solitary waves, the linear response of the plasma to slow ion-acoustic waves is also examined.

Witt, E.↗

Laser Doppler velocimeter measurements of boundary layer velocity and turbulent intensities in Mach 2.5 flow

In recent years, the interest in developing a high-speed civil transport has increased. This has led to an increase in research activity on compressible supersonic flows, in particular the boundary layer. The structure of subsonic boundary layers has been extensively documented using conditional sampling techniques which exploit the knowledge of both u and v velocities. Researchers using these techniques have been able to explore some of the complex three-dimensional motions which are responsible for Reynolds stress production and transport in the boundary layer. As interest in turbulent structure has grown to include supersonic flows, a need for simultaneous multicomponent velocity measurements in these flows has developed. The success of conditional analysis in determining the characteristics of coherent motions and structures in the boundary layer relies on accurate, simultaneous measurement of two instantaneous velocity components.

Sewell, Jesse↗

A new methodology to determine kinetic parameters for one- and two-step chemical models

In this paper, a new methodology to determine kinetic parameters for simple chemical models and simple transport properties classically used in DNS of premixed combustion is presented. First, a one-dimensional code is utilized to performed steady unstrained laminar methane-air flame in order to verify intrinsic features of laminar flames such as burning velocity and temperature and concentration profiles. Second, the flame response to steady and unsteady strain in the opposed jet configuration is numerically investigated. It appears that for a well determined set of parameters, one- and two-step mechanisms reproduce the extinction limit of a laminar flame submitted to a steady strain. Computations with the GRI-mech mechanism (177 reactions, 39 species) and multicomponent transport properties are used to validate these simplified models. A sensitivity analysis of the preferential diffusion of heat and reactants when the Lewis number is close to unity indicates that the response of the flame to an oscillating strain is very sensitive to this number. As an application of this methodology, the interaction between a two-dimensional vortex pair and a premixed laminar flame is performed by Direct Numerical Simulation (DNS) using the one- and two-step mechanisms. Comparison with the experimental results of Samaniego et al. (1994) shows a significant improvement in the description of the interaction when the two-step model is used.

Mantel, T.↗

Analysis of Ceramic Color by Special Reflectance

Radiometric and visual techniques are compared as quantitative methods for determining pottery color. An analysis of fifty-two prehistoric sherds selected at random from a multicomponent site indicates that there is an increase in the accuracy and efficiency in determining color using a spectroradiometer over subjective visual observations. Further, radiometric data can be transformed to CIE chromacity coordinates and Munsell color from spectral reflectance curves and analysed directly to access quantitative accuracy.

Giardino, Marco↗

Time-frequency representation of a highly nonstationary signal via the modified Wigner distribution

A new signal analysis technique called the modified Wigner distribution (MWD) is presented. The new signal processing tool has been very successful in determining time frequency representations of highly non-stationary multicomponent signals in both simulations and trials involving actual Space Shuttle Main Engine (SSME) high frequency data. The MWD departs from the classic Wigner distribution (WD) in that it effectively eliminates the cross coupling among positive frequency components in a multiple component signal. This attribute of the MWD, which prevents the generation of 'phantom' spectral peaks, will undoubtedly increase the utility of the WD for real world signal analysis applications which more often than not involve multicomponent signals.

Zoladz, T. F.↗

Fundamental electronic structure and multiatomic bonding in 13 biocompatible high-entropy alloys

High-entropy alloys (HEAs) have attracted great attention due to their many unique properties and potential applications. The nature of interatomic interactions in this unique class of complex multicomponent alloys is not fully developed or understood. We report a theoretical modeling technique to enable in-depth analysis of their electronic structures and interatomic bonding, and predict HEA properties based on the use of the quantum mechanical metrics, the total bond order density (TBOD) and the partial bond order density (PBOD). Application to 13 biocompatible multicomponent HEAs yields many new and insightful results, including the inadequacy of using the valence electron count, quantification of large lattice distortion, validation of mechanical properties with experiment data, modeling porosity to reduce Young’s modulus. This work outlines a road map for the rational design of HEAs for biomedical applications.

36 MATERIALS SCIENCE↗

Two-dimensional wind-tunnel tests of a NASA supercritical airfoil with various high-lift systems. Volume 1: Data analysis

High-lift systems for a NASA, 9.3%, method for calculating the viscous flow about two-dimensional multicomponent airfoils was evaluated by comparing its predictions with test data. High-lift systems derived from supercritical airfoils were compared in terms of performance to high-lift systems derived from conventional airfoils. The high-lift systems for the supercritical airfoil were designed to achieve maximum lift and consisted of: a single-slotted flap; a double-slotted flap and a leading-edge slat; and a triple-slotted flap and a leading-edge slat. Agreement between theoretical predictions and experimental results are also discussed.

Omar, E.↗

Revealing local order via high energy EELS

Short range order (SRO) is critical in determining the performance of many important engineering materials. However, accurate characterization of SRO with high spatial resolution – which is needed for the study of individual nanoparticles and at material defects and interfaces – is often experimentally inaccessible. Here, we locally quantify SRO via scanning transmission electron microscopy with extended energy loss fine structure analysis. Specifically, we use novel instrumentation to perform electron energy loss spectroscopy out to 12 keV, accessing energies which are conventionally only possible using a synchrotron. Our data is of sufficient energy resolution and signal-to-noise ratio to perform quantitative extended fine structure analysis, which allows determination of local coordination environments. To showcase this technique, we investigate a multicomponent metallic glass nanolaminate and locally quantify the SRO with <10 nm spatial resolution; this measurement would have been impossible with conventional synchrotron or electron microscopy methods. Finally, we discuss the nature of SRO within the metallic glass phase, as well as the wider applicability of our approach for determining processing–SRO–property relationships in complex materials.

36 MATERIALS SCIENCE↗

Non-Stationary Power System Forced Oscillation Analysis using Synchrosqueezing Transform

Non-stationary forced oscillations (FOs) have been observed in power system operations. However, most detection methods assume that the frequency of FOs is stationary. In this paper, we present a methodology for the analysis of nonstationary FOs. Firstly, Fourier synchrosqueezing transform (FSST) is used to provide a concentrated time-frequency representation of the signals that allows identification and retrieval of non-stationary signal components. To continue, the Dissipating Energy Flow (DEF) method is applied to the extracted components to locate the source of forced oscillations. The methodology is tested using simulated as well as real PMU data. In conclusion, the results show that the proposed FSST-based signal decomposition provides a systematic framework for the application of DEF Method to non-stationary FOs.

42 ENGINEERING↗

Analysis of hypersonic arcjet flow fields and surface heating of blunt bodies

A Gauss-Seidel implicit aerothermodynamic Navier-Stokes computational CFD code with thermochemical surface conditions (GIANTS) and with appropriate boundary conditions was developed for the analysis of hypersonic arcjet flows over large angle blunt bodies. Two-dimensional axisymmetric multicomponent full Navier-Stokes equations were solved, together with boundary conditions, to account for the surface slip, surface catalysis, and energy and mass conservation at the body surface. It is shown that the predictions for isothermal, noncatalytic, and no-slip surface conditions which are made using the GIANTS code with simple boundary conditions agree with those of the LAURA code, and the predicted normalized heating distributions over the forebody surface with boundary conditions for various cone angles are consistent with the trends of data from arcjet experiments.

Chen, Y.-K.↗

Isentropic Compression of Multicomponent Mixtures of Fuels and Inert Gases

In selected aerospace applications of the fuels hydrazine and monomethythydrazine, there occur conditions which can result in the isentropic compression of a multicomponent mixture of fuel and inert gas. One such example is when a driver gas such as helium comes out of solution and mixes with the fuel vapor, which is being compressed. A second example is when product gas from an energetic device mixes with the fuel vapor which is being compressed. Thermodynamic analysis has shown that under isentropic compression, the fuels hydrazine and monomethylhydrazine must be treated as real fluids using appropriate equations of state. The appropriate equations of state are the Peng-Robinson equation of state for hydrazine and the Redlich-Kwong-Soave equation of state for monomethylhydrazine. The addition of an inert gas of variable quantity and input temperature and pressure to the fuel compounds the problem for safety design or analysis. This work provides the appropriate thermodynamic analysis of isentropic compression of the two examples cited. In addition to an entropy balance describing the change of state, an enthalpy balance is required. The presence of multicomponents in the system requires that appropriate mixing rules are identified and applied to the analysis. This analysis is not currently available.

Barragan, Michelle↗

Machine learning approaches to streamline and enhance the analysis of multiscale imaging data for bioaerosol and soil particles

Bioaerosol and soil particles are ubiquitous in the environment. They are multicomponent and complex in nature displaying mixed inorganic and organic components. The way components are mixed in a bioaerosol sample is referred to as its mixing state. Soil particles are also a mixture of inorganic (mineral) and organic (soil organic matter) components. Bioaerosol particles contribute to a major fraction of coarse mode atmospheric particles, especially in the tropical areas, contributing up to 80 % of the particle mass concentration. The mixing state of particles is crucial to evaluate because it impacts several important environmental processes such as warm and cold cloud formation and radiation budget. Mixing states in aerosols are accompanied by chemical reactions across solid-liquid-gas interfaces. In this study, we utilized elemental compositions and microcopy images of thousands of atmospheric particles acquired by computer-controlled scanning electron microscope equipped with an energy-dispersive x-ray spectrometer to compute the mixing state of atmospheric particles. A 2D convolutional neural network (CNN), also known as convnet, was used to model the relationship between low resolution imaging data and higher resolution spectroscopy data, with the former as training input and the latter as target output. Two types of CNNs were implemented and tested; a basic CNN and an Inception-v3 network. For binary classification, the basic CNN achieved an accuracy of 84.29 % across all atom types, and the Inception-v3-like network achieved an accuracy 85.51 %. This study demonstrates the applicability of deep learning to handle large amounts of imaging/chemical spectroscopy data efficiently and evaluate particle mixing state from a range of environmental samples.

54 ENVIRONMENTAL SCIENCES↗

Mapping structural heterogeneity at the nanoscale with scanning nano-structure electron microscopy (SNEM)

Here, in this work, we explore the use of scanning electron diffraction (also known as 4D-STEM) coupled with electron atomic pair distribution function analysis (ePDF) to understand the local order (structure and chemistry) as a function of position in a complex multicomponent system, a hot rolled, Ni-encapsulated, Zr 65 Cu 17.5 Ni 10 Al 7.5 bulk metallic glass (BMG), with a spatial resolution of 3 nm. We show that it is possible to gain insight into the chemistry and chemical clustering/ordering tendency in different regions of the sample, including in the vicinity of nano-scale crystallites that are identified from virtual dark field images and in heavily deformed regions at the edge of the BMG. In addition to simpler analysis, unsupervised machine learning was used to extract partial PDFs from the material, modeled as a quasi-binary alloy, and map them in space. These maps allowed key insights not only into the local average composition, as validated by EELS, but also a unique insight into chemical short-range ordering tendencies in different regions of the sample during formation. The experiments are straightforward and rapid and, unlike spectroscopic measurements, don’t require energy filters on the instrument. We spatially map different quantities of interest (QoI’s), defined as scalars that can be computed directly from positions and widths of ePDF peaks or parameters refined from fits to the patterns. We developed a flexible and rapid data reduction and analysis software framework that allows experimenters to rapidly explore images of the sample on the basis of different QoI’s. The power and flexibility of this approach are explored and described in detail. Because of the fact that we are getting spatially resolved images of the nanoscale structure obtained from ePDFs we call this approach scanning nano-structure electron microscopy (SNEM), and we believe that it will be powerful and useful extension of current 4D-STEM methods.

36 MATERIALS SCIENCE↗

Orientation microscopy–assisted grain boundary analysis for protonic ceramic cell electrolytes

Abstract Grain boundaries in protonic ceramic cell (PCC) electrolytes hinder proton transport, reducing interfacial conductivity. In multicomponent PCC electrolytes, the inclusion of sintering aids further accentuates the complexity of grain boundaries. In this study, we synthesize nanocrystalline BaCe 0.4 Zr 0.4 Y 0.1 Yb 0.1 O 3− δ thin films via pulsed laser deposition and analyze their grain boundary character distributions using orientation data collected by precession electron diffraction technique. The results reveal an anisotropic distribution of grain boundary characters, with notably high populations of 180°‐tilt and twist grain boundaries. These findings provide critical insights into identifying the predominant grain boundaries in this PCC electrolyte material, assessing the vast five‐dimensional grain boundary space.

Patel, Sooraj [School of Aerospace and Mechanical ↗