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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 127 records · Page 7

Extracting structural insights from soft X-ray scattering of biological assemblies

Resonant soft X-ray scattering (RSoXS), a technique that combines X-ray absorption spectroscopy and X-ray scattering, can probe the nano- and meso-scale structure of biological assemblies with chemical specificity. RSoXS experiments yield scattering data collected at several photon energies, for example across an elemental absorption edge of interest. Collecting a near-edge X-ray absorption fine structure (NEXAFS) spectrum complements RSoXS experiments and determines X-ray energies that are best suited for RSoXS measurements. The analysis of RSoXS data is similar in many ways to analysis of small angle X-ray scattering using hard X-rays, with an added dimension that includes an X-ray energy dependence. This chapter discusses procedures for predicting scattering contrast and thereby identifying energies suitable for RSoXS measurements using NEXAFS spectra, analyses of 2D RSoXS images through integration into 1D profiles, and strategies for elucidating the origin of RSoXS scattering features. As a result, it also discusses existing and potential methods for interpretation of RSoXS data to gain detailed structural insights into biological systems.

59 BASIC BIOLOGICAL SCIENCES↗

Experimental data for damage mechanics simulation challenge

While there are many computational approaches for simulating damage in rock and other materials, few have been ground truth tested with either known experimental data or with blind data sets. Here, in this work, we present a bench-mark laboratory data set for a damage mechanics challenge to compare computational approaches on damage evolution in brittle-ductile materials. The samples were fabricated through additive manufacturing to produce repeatable specimens designed to fail in controlled ways. The failure was induced in the samples using a 3-point bending test to produce different Modes such as Mode I and mixed Modes including I-II, I-III and I-II-III Modes to generate a calibration data set and a blind challenge data set. Data collected included spatial and temporal measurements from traditional digital load–displacement sensors, 2D digital image correlation measurement to map surface deformations, 3D X-ray microscopy to ground-truth the crack-failure geometry, and laser profilometry to capture surface roughness. The data sets are available, on a data repository, to the community to advance computational models to improve our ability to predict damage in brittle-ductile materials.

3-point bending↗

Evolution of tensile and shear cracking in crystalline rocks under compression

Here we performed laboratory-scale unconfined compression experiments on Barre granite specimen with a single pre-existing flaw to study the evolution of tensile and shear cracking that occurs during different stress levels. Moment tensor inversion of acoustic emission (AE) events in combination with the nonelastic strain component obtained through the 2D digital image correlation (DIC) technique are used to track the changes in the source mechanisms of the stress-induced cracks. The mode of deformation computed from the image based strain profiles, enables visual comparison of the nucleation, growth and interaction of the tensile and shear cracks with the microseismic source mechanism observed by moment tensor inversion of the AE events. Comparing the results obtained from the two techniques on the same dataset demonstrates a quantitative correlation between the acoustic and visual observations in terms of the cracking mechanisms obtained at different stages of cracking from crack initiation at the flaw tips to the failure of the rock specimen.

58 GEOSCIENCES↗

The eROSITA Final Equatorial-Depth Survey (eFEDS)

Here, we investigate the physical properties – such as the stellar mass (M * ), star-formation rate, infrared (IR) luminosity (L IR ), X-ray luminosity (L X ), and hydrogen column density (N H ) – of mid-IR (MIR) galaxies and active galactic nuclei (AGN) at z < 4 in the 140 deg 2 field observed by eROSITA on SRG using the Performance-and-Verification-Phase program named the eROSITA Final Equatorial Depth Survey (eFEDS). By cross-matching the WISE 22 μm (W4)-detected sample and the eFEDS X-ray point-source catalog, we find that 692 extragalactic objects are detected by eROSITA. We have compiled a multiwavelength dataset extending from X-ray to far-IR wavelengths. We have also performed (i) an X-ray spectral analysis, (ii) spectral-energy-distribution fitting using X-CIGALE, (iii) 2D image-decomposition analysis using Subaru Hyper Suprime-Cam images, and (iv) optical spectral fitting with QSFit to investigate the AGN and host-galaxy properties. For 7088 WISE 22 μm objects that are undetected by eROSITA, we have performed an X-ray stacking analysis to examine the typical physical properties of these X-ray faint and probably obscured objects. We find that (i) 82% of the eFEDS–W4 sources are classified as X-ray AGN with log L X > 42 erg s –1 ; (ii) 67 and 24% of the objects have log(L IR /L ⊙ ) > 12 and 13, respectively; (iii) the relationship between L X and the 6 μm luminosity is consistent with that reported in previous works; and (iv) the relationship between the Eddington ratio and N H for the eFEDS–W4 sample and a comparison with a model prediction from a galaxy-merger simulation indicates that approximately 5.0% of the eFEDS–W4 sources in our sample are likely to be in an AGN-feedback phase, in which strong radiation pressure from the AGN blows out the surrounding material from the nuclear region. Thanks to the wide area coverage of eFEDS, we have been able to constrain the ranges of the physical properties of the WISE 22 μm-selected sample of AGNs at z < 4, providing a benchmark for forthcoming studies on a complete census of MIR galaxies selected from the full-depth eROSITA all-sky survey.

79 ASTRONOMY AND ASTROPHYSICS↗

Two-dimensional plasma density evolution local to the inversion layer during sawtooth crash events using Beam Emission Spectroscopy

Here, we present methods for analyzing Beam Emission Spectroscopy (BES) data to obtain the plasma density evolution associated with rapid sawtooth crash events at the DIII-D tokamak. BES allows coverage over a 2D spatial plane, inherently local measurements, with fast time responses, and, therefore, provides a valuable new channel for data during sawtooth events. A method is developed to remove sawtooth-induced edge-light pulses contained in the BES data. The edge light pulses appear to be from the D α emission produced by edge recycling during sawtooth events, and are large enough that traditional spectroscopic filtering and data analysis techniques are insufficient to deduce physically meaningful quantities. A cross-calibration of 64 BES channels is performed by using a novel method to ensure accurate measurements. For the large-amplitude density oscillations observed, we discuss and use the non-linear relationship between the BES signal δI/ I 0 and the plasma density variation δn e / n e0 . The 2D BES images cover an 8 × 20 cm 2 region around the sawtooth inversion layer and show large-amplitude density oscillations, with additional significant spatial variations across the inversion layer that grows and peaks near the time of the temperature crash. The edge light removal technique and method of converting large-amplitude δI/ I 0 to δn e / n e0 presented here may help analyze other impulsive MHD phenomena in tokamaks.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

First observations of edge instabilities in strongly shaped negative triangularity plasmas on DIII-D

Throughout the 2023 DIII-D negative triangularity (NT) campaign, unexpected magnetic fluctuations indicative of an edge localized instability were observed in the majority of strongly shaped (–0.55 ≤ δ ≤ –0.45) discharges. Moreover, these same fluctuations were found to be absent in weaker NT plasma shapes. Based on a database study, three separate mode behaviors are observed based primarily on the edge safety factor and normalized plasma beta β N . The main regime is the bursty state, in which short (~5 ms) magnetic bursts occur every 5–10 ms. Each burst drives a small reduction in the edge electron temperature (T e ) as measured by electron cyclotron emissions (ECE), which then rapidly recovers between the bursts. The quiescent regime appears to have governing mechanics similar to the bursty regime, but with multiple unique mode signatures observed in the magnetics. These additional modes greatly reduce the bursty nature of the plasma. Finally, a saturated state is observed in a number of discharges, particularly at early time slices. The saturated regime is often short-lived (maximum 500 ms), but can have a large impact on the dynamics of the plasma edge region, causing significant drops in electron temperature as observed in the ECE diagnostic. 2D ECE imaging (ECE-I) is utilized, showing large kink-like perturbations localized near the last closed flux surface that extend into the SOL indicative of an external kink/peeling behavior. Additionally, evidence of phase mixing and observed tearing-parity perturbations localized near the edge rational surfaces is observed in the quiescent regime plasmas. As a result, the various modes do not appear to have a large impact on global confinement but may play a role in regulating the transport of the NT edge and the observed edge gradients.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

Tracing cosmic gas in filaments and halos: Low-redshift insights from the kinematic Sunyaev-Zel’dovich effect

In this work, we leverage cosmic microwave background (CMB) data from the Atacama Cosmology Telescope (ACT) and LSS data from the imaging survey conducted by the Dark Energy Spectroscopic Instrument (DESI) to study the distribution of gas around galaxy groups at low redshift, z ≈ 0.3, via the kinematic Sunyaev-Zel'dovich (kSZ) effect. In particular, we perform velocity-weighted stacking on the photometric galaxies from the Bright Galaxy Survey (BGS) to isolate the monopole and quadrupole of the kSZ signal, orienting the stacked images along 2D filaments identified using the Hessian of the projected gravitational potential. We find a 7.2σ detection in the monopole of the signal (i.e., the gas density profile) and a 4σ detection in the quadrupole (m = 2), constituting the first measurement of the alignment between gas distribution and the cosmic web through the kSZ effect. As it is a linear probe of the local gas density, the kSZ has heightened sensitivity to the warm-hot intergalactic medium (WHIM), which is believed to house the majority of the "missing baryons."Mapping out the gas density at low redshifts, as enabled by our measurements, is crucial for weak lensing surveys, for which the impact of baryons on small scales is a major impediment. We compare the anisotropic signal against two hydrodynamical simulations, TNG300-1 and Illustris, which have very different baryonic feedback prescriptions. We find that the anisotropic signal measured in the data is comparable but slightly larger and more extended compared with the simulations. Further, this suggests that there is excess accretion and feedback taking place through the filaments, hinting at the possible presence of spin-filament alignment of the BGS objects.

79 ASTRONOMY AND ASTROPHYSICS↗

AXEAP : a software package for X-ray emission data analysis using unsupervised machine learning

The Argonne X-ray Emission Analysis Package ( AXEAP ) has been developed to calibrate and process X-ray emission spectroscopy (XES) data collected with a two-dimensional (2D) position-sensitive detector. AXEAP is designed to convert a 2D XES image into an XES spectrum in real time using both calculations and unsupervised machine learning. AXEAP is capable of making this transformation at a rate similar to data collection, allowing real-time comparisons during data collection, reducing the amount of data stored from gigabyte-sized image files to kilobyte-sized text files. With a user-friendly interface, AXEAP includes data processing for non-resonant and resonant XES images from multiple edges and elements. AXEAP is written in MATLAB and can run on common operating systems, including Linux, Windows, and MacOS.

97 MATHEMATICS AND COMPUTING↗

Distinguishing isotropic and anisotropic signals for X-ray total scattering using machine learning

Understanding structure–property relationships is essential for advancing technologies based on thin films. X-ray pair distribution function (PDF) analysis can access relevant atomic structure details spanning local-, mid- and long-range structure. While X-ray PDF has been adapted for thin films on amorphous substrates, measurements on single-crystal substrates are necessary to accurately determine structure origins for some thin film materials, especially those for which the substrate changes the accessible structure and properties. However, when measuring films on single-crystal substrates, high-intensity anisotropic Bragg spots saturate 2D detector images, overshadowing the thin films' isotropic scattering signal. This renders previous data processing methods for films on amorphous substrates unsuitable for films on single-crystal substrates. To address this measurement need, we developed IsoDAT2D, an innovative data processing approach using unsupervised machine learning algorithms. The program combines dimensionality reduction and clustering algorithms to separate thin film and single-crystal substrate X-ray scattering signals. We use SimDAT2D , a program we developed to generate simulated thin film data, to validate IsoDAT2D . Here we also use IsoDAT2D to isolate X-ray total scattering signal from a thin film on a single-crystal substrate. The resulting PDF data are compared with similar data processed using previous methods, especially substrate subtraction for single-crystal and amorphous substrates. PDF data from IsoDAT2D -identified X-ray total scattering data are significantly better than from single-crystal substrate subtraction, but not as reliable as PDF data from amorphous substrate subtraction. With IsoDAT2D , there are new opportunities to expand PDF to a wider variety of thin films, including those on single-crystal substrates, with which new structure–property relationships can be elucidated to enable fundamental understanding and technological advances.

36 MATERIALS SCIENCE↗

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↗

SU(n) and Quantum SU(n) Symmetries in Physical Systems [Slides]

Presence of SU(n) or other Lie group symmetry in a physical system is its powerful, usually underutilized property. In many cases it allows for finding analytical solutions to nonlinear differential equations describing this system. Power of the method is presented on diversified examples from mathematical physics: Lie-group symmetries in finding solutions of generalized, multidimensional theory of gravity; analytical Dirac–equation solutions for description of conducting polymers; stability of qubit states in quantum computers; spatial defects in condensed matter; reconstruction of 3D object from its 2D tomographic image; significant improvement of numerical solutions stability for Euler equations. The next question after obtaining such Lie group symmetric solution is: does a generalized solution with appropriate quantum group symmetry exists for the given physical system, and if yes what is the physical meaning of the deformation parameter q introduced by such solution. In many cases it can be identified. Any SU(n) solution is by its nature singular, assuming a perfect symmetry of the physical system discussed. Such solution gives a powerful insight to theoretical physics, yet the assumption may be too demanding for experimental applications. Deformation parameter q from a quantum group symmetry allows for a continuum of solutions, more applicable to experiments.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

Analysis of Defects in Metal Additive Manufacturing with Augmented Data Generation

Laser powder bed fusion (LPBF) is a method of additive manufacturing (AM) that selectively melts and fuses together microscopic metallic powder. LPBF offers the benefit of producing custom structures out of high strength metals that can be difficult to fabricate with conventional methods. The challenge of LPBF is that 3D printed structures often have internal pores due to process flaws. Pulsed thermal tomography (PTT) is a method for reconstructing the depth profile of materials, allowing the visualization internal voids in solids. In prior work, we developed a convolutional neural network (CNN) which, having been trained on simulated 2D PTT images of subsurface elliptical defects, was able to classify the semi-major radii, semi-minor radii, and angular orientation of the best-fit ellipses in previously unseen PTT images. The unseen PTT images contained subsurface irregular defect shapes imported from scanning electron microscopy (SEM) images of metallic LPBF-printed specimens. Training the CNN on irregular defect shapes instead of on elliptical shapes would make the resulting classifications more descriptive of actual defect shapes. However, this requires a much higher volume of SEM images of material defects, which are difficult to obtain because of random occurrence of defects in LPBF. To address this challenge, we developed a generative adversarial network (GAN) to augment the existing dataset of SEM defect images. The GAN model is demonstrated to create novel yet realistic defect shapes that can be used as input for simulated PTT images to train CNN.

36 MATERIALS SCIENCE↗

Report on RIA Relevant Modified Burst Testing of ATF Cladding Materials

The mechanical performance of accident-tolerant fuel (ATF) cladding candidates in light-water reactors (LWRs) must be similar to or better than that of current conventional nuclear fuel claddings to reduce dose to the public and ensure a that the core coolable geometry is maintained during a postulated reactivity-initiated accident (RIA) in light-water reactors (LWRs). During an RIA event, the rapid thermal expansion of nuclear fuel can deform the cladding once the fuel–cladding gap closes. In some cases, the pellet–cladding mechanical interaction (PCMI) can induce mechanical failure in ATF candidates. Thus, the mechanical response of ATF cladding must be investigated by mimicking the conditions of RIA and potentially performing Transient Reactor Test (TREAT) experiments to establish or verify the safety envelope. The work presented in this report investigated the failure behavior of as-received, hydrided, and chromium-coated (Cr-coated) Zircaloy-4 (Zry-4) cladding tube under strain-driven mechanical conditions, mimicking postulated RIA loading conditions. Mechanical testing was performed at 300°C via modified burst test (MBT) equipment with pulse width control previously developed under the Department of Energy’s (DOE’s) Advanced Fuel Campaign (AFC). The mechanical strains were determined using 2D digital image correlation (DIC) techniques. The base Zry-4 acquired by Cameco Inc. was in stress-relieved annealed (SRA) condition. Because of the observed large deformation of the cladding tubes, the failure strain definition was updated for the MBT, which can also be applied to other tube tests where significant bulging (out-of-plane deformation) is present. The failure strain was determined to be affected by the speed of the test or the RIA event. As the RIA-like event duration decreased from 75 to 15 ms, the failure strain decreased 5, 7 and 1% for as-received, hydrided, and Cr-coated specimens, respectively. Fractography on the Cr-coated specimens indicated the presence of two failure mechanisms: (i) crenulation at the outer surface of the coating due to the tensile tractional forces along with coatings grain microstructure and (ii) formation of critical defect at the coating/cladding interface that initiated coating rupture after severe plastic deformation of the Zry- 4 substrate. Based on the MBT results and fractography observations, performing mechanical property testing at high strain rates—in particular on Cr-coated tubes—and semi-integral TREAT experiments are required future efforts to ensure ATF cladding performance during transients. The testing recommended would also inform the development of long-term generalized cladding technologies.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗

Pluminate: Quantifying aerosol injection behavior from simulation, experimentation and observations

Marine aerosol injections are a key component in further understanding of both the potentials of deliberate injection for marine cloud brightening (MCB), a potential climate intervention (CI) strategy, and key aerosol-cloud interaction behaviors that currently form the largest uncertainty in global climate model (GCM) predictions of our climate. Since the rate of spread of aerosols in a marine environment directly translates to the effectiveness and ability of aerosol injections in impacting cloud radiative forcing, it is crucial to understand the spatial and temporal extent of injected-aerosol effects following direct injection into marine environments. The ubiquity of ship-injected aerosol tracks from satellite imagery renders observational validation of new parameterizations possible in 2D, however, 3D compatible data is more scarce, and necessary for the development of subgrid scale parameterizations of aerosol-cloud interactions in GCMs. This report introduces two novel parameterizations of atmospheric aerosol injection behavior suitable for both 3D (GCM-compatible) and 2D (observation-related) modeling. Their applicability is highlighted using a wealth of different observational data: small and larger scale salt-aerosol injection experiments conducted at SNL, 3D large eddy simulations of ship-injected aerosol tracks and 2D satellite images of ship tracks. The power of experimental data in enhancing knowledge of aerosol-cloud interactions is in particular emphasized by studying key aerosol microphysical and optical properties as observed through their mixing in cloud-like environments.

54 ENVIRONMENTAL SCIENCES↗

Neutron computed tomography of B12W and M8N socket sections of the Arecibo telescope

From neutron user principal investigator: We kindly request the public release of three neutron imaging datasets through ONCat. All datasets were collected from two forensic specimens, B12W and M8N, sectioned from zinc-filled steel-wire sockets recovered from the collapsed Arecibo Telescope. The dataset titled “Neutron radiographs of B12W and M8N socket sections of the Arecibo telescope” contains normalized two-dimensional (2D) neutron radiographs of the specimens, showing the geometry and spatial distribution of the steel wires embedded within the zinc matrix, as well as internal features such as voids and cracks. The dataset titled “Neutron computed tomography of B12W and M8N socket sections of the Arecibo telescope” contains normalized 2D neutron projection images acquired over a range of specimen rotation angles for one selected region of each specimen. These projection images were used to reconstruct three-dimensional (3D) tomographic volumes that reveal the embedded-wire geometry and internal defects. The dataset titled “Bragg edge imaging (BEI) of B12W and M8N socket sections of the Arecibo telescope” contains six time-of-flight (TOF) neutron imaging datasets, three from each specimen, acquired at regions of interest selected based on the radiographs. The spatially resolved 2D TOF images show the zinc matrix and embedded steel wires, and the wavelength-dependent neutron transmission data were used to characterize crystallographic texture within the zinc. All components and their condition are in the public domain as they are the property of the National Science Foundation (NSF). The neutron imaging data, part geometries, and detailed forensic information have been widely published in the Arecibo Telescope Collapse Forensic Report by Thornton Tomasetti Engineers and others (NASA report and NASEM report).

Bilheux, Hassina↗

Aerial 3D Building Reconstruction from Drone Imagery (A3DBR) v1

This toolkit is composed of several modules for extracting buildings geometrical and thermal characteristics from RGB and thermal imagery captured using a drone. - Building 3D reconstruction module: leverage a photogrammetry software to construct a 3D point cloud from RGB drone imagery, which is then used in conjunction with image processing and geometric methods to extract building footprint and building height (i.e., 3D model of the building). - Windows to wall ratio estimation module: leverage deep learning semantic segmentation modeling to detect windows on 2D drone RGB images. The detected windows are then projected onto the extracted building 3D model (using building 3D reconstruction module) and their area is computed to obtain window to wall ratio estimation. - Thermal anomalies detection module: leverage image processing and machine learning algorithm to detect on 2D drone thermal images potential thermal anomalies within building's facades and roofs.

Granderson, Jessica↗

Stochastic 3D reconstruction of cracked polycrystalline NMC particles using 2D SEM data

Li-ion battery performance is strongly influenced by the 3D microstructure of its cathode particles. Cracks within these particles develop during calendaring and cycling, reducing connectivity but increasing reactive surface, making their impact on battery performance complex. Understanding these contradictory effects requires a quantitative link between particle morphology and battery performance. However, informative 3D imaging techniques are time-consuming, costly and rarely available, such that analyses often have to rely on 2D image data. This paper presents a novel stereological approach for generating virtual 3D cathode particles exhibiting crack networks that are statistically equivalent to those observed in 2D sections of experimentally measured particles. Consequently, 2D image data suffices for deriving a full 3D characterization of cracked cathodes particles. Such virtually generated 3D particles could serve as geometry input for spatially resolved electro-chemo-mechanical simulations to enhance our understanding of structure-property relationships of cathodes in Li-ion batteries.

36 MATERIALS SCIENCE↗