Search NASA⌕ Search

SEARCH · Search NASA

Results for “Feature Extraction”

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.

Quote a phrase for an exact phrase match. Source license links do not imply unrestricted reuse.

At least 901 records · Page 50

Data-Driven Optimization of the Processing Window for 316H Components Fabricated Using Laser Powder Bed Fusion

The Advanced Materials and Manufacturing Technologies Program is focused on accelerating the development and deployment of advanced materials and components fabricated via additive manufacturing with a specific focus on laser powder bed fusion (LPBF). As an initial case study, the program has selected 316H stainless steel (SS) as an initial material around which to develop a code case development strategy. This strategy involves two parallel approaches: (1) an equivalency approach whereby round-robin testing across multiple collaborating laboratories demonstrates repeatability in processing and direct comparisons with conventional wrought 316H material and (2) a revolutionary approach to code qualification combining in situ data collection and high-fidelity modeling to capture, predict, and bound the performance of LPBF 316HSS components. As part of this campaign, this work package has initiated an extensive process optimization campaign across three laboratories, each printing variations of LPBF 316HSS using three different LPBF units (Concept Laser, EOS, and Renishaw). In FY23, ORNL has focused on unique experimental designs spanning wide ranges in energy inputs and turning knobs such as scan speed, laser power, hatch spacing, layer thickness, spot size, scan rotation, and more. On the Concept Laser M2, 72 different combinations of processing variables were investigated with duplicate samples and different powder compositions. In total, 252 samples were printed with combined in situ sensing data. A parallel design of experiments was conducted on the Renishaw AM400 with an additional 390 printed specimens for analysis. All 642 miniature specimens, each with unique features included in each print to capture geometry-related heterogeneity, were subjected to high-throughput x-ray computed tomography (XCT) analysis to enable the downselection of specific processing parameters of interest. Then, using electrical discharge machining (EDM), miniature tensile specimens were extracted for mechanical testing and microscopy investigations. From the analysis performed in FY23, it was found that powder composition drastically affects the resulting microstructure and mechanical performance of 316SS. Specifically, changing from 316L to 316HSS powder results in a wide range of grain sizes with varying degrees of preferred grain orientation, which increases as a function of energy density. It was also found that due to stored heat in thin fin–type features, large microstructural differences can be seen within one part printed with one set of processing parameters. These variations in microstructure features, including grain size, the nanoscale dislocation structure, and grain texture, will all affect the irradiation performance and high-temperature mechanical performance of LPBF 316HSS parts. Two sets of concept laser processing parameters, spanning both refined and columnar grain structures, were scaled to print larger 316H builds for campaign testing (high-temperature creep and irradiation). In addition, at least two optimized processing parameter sets were identified for the Renishaw AM400 for round-robin testing in FY24 with Argonne National Laboratory. Future work includes printing samples using identical parameters identified by partner institutions, providing material for corrosion and high-temperature mechanical testing, and continuing evaluations of heterogeneity in larger printed parts.

36 MATERIALS SCIENCE↗

Data-Driven Optimization of the Processing Window for 316H Components Fabricated Using Laser Powder Bed Fusion

The Advanced Materials and Manufacturing Technologies Program is focused on accelerating the development and deployment of advanced materials and components fabricated via additive manufacturing with a specific focus on laser powder bed fusion (LPBF). As an initial case study, the program has selected 316H stainless steel (SS) as an initial material around which to develop a code case development strategy. This strategy involves two parallel approaches: (1) an equivalency approach whereby round-robin testing across multiple collaborating laboratories demonstrates repeatability in processing and direct comparisons with conventional wrought 316H material and (2) a revolutionary approach to code qualification combining in situ data collection and high-fidelity modeling to capture, predict, and bound the performance of LPBF 316HSS components. As part of this campaign, this work package has initiated an extensive process optimization campaign across three laboratories, each printing variations of LPBF 316HSS using three different LPBF units (Concept Laser, EOS, and Renishaw). In FY23, ORNL has focused on unique experimental designs spanning wide ranges in energy inputs and turning knobs such as scan speed, laser power, hatch spacing, layer thickness, spot size, scan rotation, and more. On the Concept Laser M2, 72 different combinations of processing variables were investigated with duplicate samples and different powder compositions. In total, 252 samples were printed with combined in situ sensing data. A parallel design of experiments was conducted on the Renishaw AM400 with an additional 390 printed specimens for analysis. All 642 miniature specimens, each with unique features included in each print to capture geometry-related heterogeneity, were subjected to high-throughput x-ray computed tomography (XCT) analysis to enable the downselection of specific processing parameters of interest. Then, using electrical discharge machining (EDM), miniature tensile specimens were extracted for mechanical testing and microscopy investigations. From the analysis performed in FY23, it was found that powder composition drastically affects the resulting microstructure and mechanical performance of 316SS. Specifically, changing from 316L to 316HSS powder results in a wide range of grain sizes with varying degrees of preferred grain orientation, which increases as a function of energy density. It was also found that due to stored heat in thin fin–type features, large microstructural differences can be seen within one part printed with one set of processing parameters. These variations in microstructure features, including grain size, the nanoscale dislocation structure, and grain texture, will all affect the irradiation performance and high-temperature mechanical performance of LPBF 316HSS parts. Two sets of concept laser processing parameters, spanning both refined and columnar grain structures, were scaled to print larger 316H builds for campaign testing (high-temperature creep and irradiation). In addition, at least two optimized processing parameter sets were identified for the Renishaw AM400 for round-robin testing in FY24 with Argonne National Laboratory. Future work includes printing samples using identical parameters identified by partner institutions, providing material for corrosion and high-temperature mechanical testing, and continuing evaluations of heterogeneity in larger printed parts.

36 MATERIALS SCIENCE↗

A UNIONS view of the brightest central galaxies of candidate fossil groups

The formation process of fossil groups (FGs) is still under debate, and, because of their relative rarity, large samples of such objects are still missing. The aim of the present paper is to increase the sample of known FGs, to analyse the properties of their brightest group galaxies (BGGs), and to compare them with a control sample of non-FG BGGs. We extracted a sample of 87 FG and 100 non-FG candidates from a large spectroscopic catalogue of haloes and galaxies. For all the objects with data available in UNIONS (initially the Canada France Imaging Survey, CFIS) in the u and r bands, and/or in an extra r-band processed to preserve all low-surface-brightness features (rLSB), we performed a 2D photometric fit of the BGG with GALFIT with one or two Sérsic components. We also analysed how the subtraction of the intracluster light (ICL) contribution modifies the BGG properties. From the SDSS spectra available for the BGGs of 65 FGs and 82 non-FGs, we extracted the properties of their stellar populations with Firefly. To complement our study, and in order to provide a detailed illustration of the possible origin of emission lines in the FG BGGs, involving the presence or absence of an AGN, we investigated the origin of the emission lines in a nearby FG that is dominated by the NGC 4104 galaxy. Morphologically, a single Sérsic profile can fit most objects in the u band, while two Sérsics are needed in the r and rLSB bands, both for FGs and non-FGs. Non-FG BGGs cover a larger range of Sérsic index n. FG BGGs follow the Kormendy relation (mean surface brightness versus effective radius) previously derived for almost 1000 brightest cluster galaxies (BCGs), while the majority of non-FGs BGGs are located below this relation, with fainter mean surface brightnesses. This suggests that FG BGGs have evolved similarly to BCGs, and non-FG BGGs have evolved differently from both FG BGGs and BCGs. All the above properties can be strongly modified by the subtraction of the ICL contribution. Based on spectral fitting, the stellar populations of FG and non-FG BGGs do not differ significantly. FG and non-FG BGGs differ from one another in terms of their morphological properties and Kormendy relation, suggesting they have had different formation histories. However, it is not possible to trace differences in their stellar populations or in their large-scale distributions.

79 ASTRONOMY AND ASTROPHYSICS↗

Point Cloud of Cloud Points (PCCP) Value-Added Product Report

In this report, we refer to a pair of cameras that capture synchronized pictures with overlapping fields of view (FOV) as a stereo pair. Each stereo pair independently performs a stereo reconstruction of cloud points. Currently, there are three U.S. Department of Energy Atmospheric Radiation Measurement (ARM) user facility stereo pairs (six cameras in total) positioned around the Southern Great Plains (SGP) observatory’s Central Facility (CF; Romps and Oktem 2017). Time-synchronized pictures from the two cameras in a stereo pair can be paired together to obtain a three-dimensional (3D) reconstruction of feature points by triangulation. This document explains how we use ARM stereo cameras and stereophotogrammetric principles to generate the Point Cloud of Cloud Points (PCCP) Value-Added Product (VAP). The PCCP VAP is essentially a set of 3D positions representing the locations of cloud features in the sky. Thousands of cloud features can be reconstructed instantly in each stereo pair's FOV, which covers an area of tens of square kilometers. Cloud base and cloud top heights can be extracted from the PCCP product.

54 ENVIRONMENTAL SCIENCES↗

Retrieving Point Cloud of Cloud Points (PCCP) Value-Added Product from Stereo Cameras

In this report, we refer to a pair of cameras that capture synchronized pictures with overlapping fields of view (FOV) as a stereo pair. Each stereo pair independently performs a stereo reconstruction of cloud points. Currently, there are three U.S. Department of Energy Atmospheric Radiation Measurement (ARM) user facility stereo pairs (six cameras in total) positioned around the Southern Great Plains (SGP) observatory’s Central Facility (CF; Romps and Oktem 2017). Time-synchronized pictures from the two cameras in a stereo pair can be paired together to obtain a three-dimensional (3D) reconstruction of feature points by triangulation. This document explains how we use ARM stereo cameras and stereophotogrammetric principles to generate the Point Cloud of Cloud Points (PCCP) Value-Added Product (VAP). The PCCP VAP is essentially a set of 3D positions representing the locations of cloud features in the sky. Thousands of cloud features can be reconstructed instantly in each stereo pair's FOV, which covers an area of tens of square kilometers. Cloud base and cloud top heights can be extracted from the PCCP product.

42 ENGINEERING↗

Beyond Binary: Automated PLC Memory Forensics through RGB Image Analysis and Deep Learning

The introduction of Industry 4.0 and the evolution of industrial control systems (ICS) to adopt Internet-based technologies enhanced productivity, but have inadvertently increased their vulnerability to cyber-based malicious attacks. When an ICS system is compromised, security analysts need to identify the root cause quickly to start the recovery process and develop mitigation strategies to safeguard against future instances. Memory forensics is critical in the analysis process to ascertain what occurred. To date, approaches to analyze the persistent memory in ICS devices are limited, and almost nonexistent for volatile memory. This paper proposes an automated methodology, COMA, for PLC memory dump analysis using computer vision and deep learning techniques. Specifically, COMA converts the sequences of bytes in a PLC memory dump to RGB pixels and creates a deep learning model that learns the underlying patterns and features of pre-labeled forensic artifacts in images and segments them into distinct regions. COMA then uses the trained model to automatically segment new memory images and extract forensic artifacts. We evaluate COMA on a Schneider Electric Modicon M221 PLC involving two cyber-based attack scenarios: (i) code injection and (ii) code modification. The empirical results show that COMA can successfully detect attack artifacts in memory dumps in both scenarios.

Asmar Awad, Rima↗

Microfluidic Liquid-Liquid Extraction Chip with Integrated Raman Sensors (Phase I and Phase II Final Report)

As demand for electricity continues to increase worldwide, the world’s nuclear power generating capacity will continue to grow. Nuclear power is the most environmentally benign way of producing electricity on a large scale. The long-term successful use of nuclear power, however, is critically dependent upon adequate and safe processing and disposal of spent nuclear fuels. A very important feature of nuclear energy is that spent fuels can be reprocessed to recover fissile and fertile materials that can then be used as fresh fuel for nuclear power plants. The DOE-NE Fuel Cycle Research and Development (FCR&D) is currently developing nuclear material reprocessing technologies. In a typical nuclear fuel reprocessing system, centrifugal contactors are used as liquid-liquid extraction devices where two immiscible liquids are mixed at high speeds using a rotor, which creates a fine dispersion of droplets of organic phase in an aqueous phase that contains the analyte. Understanding the extraction efficiency at these contactors through modeling and simulation is important in the development of reprocessing technologies and the optimization of current technologies such as the PUREX process. The outcome of this program will be a liquid-liquid microfluidic flow cell chip with embedded spectroscopic sensors for the analysis of extracted analytes. This device will be useful in the optimization of new fuel reprocessing schemes as well as existing reprocessing processes by providing a microfluidic modeling platform to optimize extraction parameters. The Phase I and Phase II work developed a microfluidic chip design that allows integration of Raman and absorption fiber optic probes and successfully demonstrated the feasibility of using Raman and absorption probes to detect key analytes that partition into the aqueous and organic phases.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗

Solar-powered self-descaling seesaw extractor for lithium production from seawater

The low Li + concentration and the abundance of competing ions limit the efficiency of lithium extraction from seawater. Here, in this work, we report a solar-powered seesaw extractor (SPSE) to boost Li + adsorption while minimizing scaling caused by competing ions during photothermal evaporation. The SPSE features a sandwich architecture, with a hydrophilic adsorbent layer placed between two hydrophobic photothermal layers. The seesaw configuration enables Li + to be elevated and concentrated through evaporation to overcome sluggish adsorption kinetics, while the associated salt scaling is removed by the seesawing motion. As a demonstration, we assembled 60 SPSEs into a 3 × 20 array that achieved a 15.5-fold increase in local Li + concentration and a 69.1% improvement in Li + uptake over 120 h, with a Li + /Na + separation factor exceeding 370,000.

localized enrichment↗

Multiband Polarimetric Imaging of HR 4796A with the Gemini Planet Imager

HR4796A hosts a well-studied debris disk with a long history due to its high fractional luminosity and favorable inclination, which facilitate both unresolved and resolved observations. We present new J- and K {sub 1}-band images of the resolved debris disk HR4796A taken in the polarimetric mode of the Gemini Planet Imager (GPI). The polarized intensity features a strongly forward-scattered brightness distribution and is undetected at the far side of the disk. The total intensity is detected at all scattering angles and also exhibits a strong forward-scattering peak. We use a forward-modeled geometric disk in order to extract geometric parameters, polarized fraction, and total intensity scattering phase functions for these data as well as H-band data previously taken by GPI. We find the polarized phase function becomes increasingly more forward-scattering as wavelength increases. We fit Mie and distribution of hollow spheres (DHS) grain models to the extracted functions. We find that it is possible to generate a satisfactory model for the total intensity using a DHS model, but not with a Mie model. We find that no single grain population of DHS or Mie grains of arbitrary composition can simultaneously reproduce the polarized fraction and total intensity scattering phase functions, indicating the need for more sophisticated grain models.

79 ASTRONOMY AND ASTROPHYSICS↗

Investigation of the multiplet features of SrTiO 3 in X-ray absorption spectra based on configuration interaction calculations

Synchrotron-based L 2,3 -edge absorption spectra show strong sensitivities to the local electronic structure and chemical environment. However, detailed physical information cannot be extracted easily without computational aids. Here in this study using the experimental Ti L 2,3 -edges absorption spectrum of SrTiO 3 as a fingerprint and considering full multiplet effects, calculations yield different energy parameters characterizing local ground state properties. The peak splitting and intensity ratios of the L 3 and L 2 set of peaks are carefully analyzed quantitatively, giving rise to a small hybridization energy around 1.2 eV, and the different hybridization energy values reported in the literature are further addressed. Finally, absorption spectra with different linearly polarized photons under various tetragonal crystal fields are investigated, revealing a non-linear orbital–lattice interaction, and a theoretical guidance for material engineering of SrTiO 3 -based thin films and heterostructures is offered. Finally, detailed analysis of spectrum shifts with different tetragonal crystal fields suggests that the e g crystal field splitting is a necessary parameter for a thorough analysis of the spectra, even though it is not relevant for the ground state properties.

3 d transition metal oxide↗

Modification of an Agitated Tube Reactor for use in the Reprocessing of Spent Nuclear Fuel

Aims: Convert an Agitated Tube Reactor (ATR) into a counter-current solvent extraction device. Assess effect of liquid fill level on liquid dispersion. The agitated tube reactor (ATR) is an array of connected tubes. The ATR laterally shakes in a sinusoidal path, moving the agitator bar to create mixing. Originally designed by AM Technology as a cocurrent reactor, the ATR has many features that are potentially useful in the nuclear industry: Tubes are connected by non-moving seals; Reduction in seal damage and reduced risk of expensive repairs in radioactive environments; Minimal axial dispersion within a tube; Plug flow; Narrower residence time distributions that traditional technology; Multiple tubes allow for multiple reactions in series; Converting to a counter-current design allows the ATR to be used for solvent extraction; Reprocessing or decommissioning. A 180 ml PERSPEX ATR tube with no liquid flow through was constructed and filled with a 1:1 solvent:aqueous ratio of kerosene and water. The tube was filled such that the total liquid filled 25 %, 50 %, 75 % or 100 % of the tube. A Photron Fastcam SA5, positioned at the side and the end of the tube was set to a frame rate of 5400 fps with a resolution of 1024 x 1024 and 6000 fps with a resolution of 1024 x 896 respectively. Droplets were recorded after 2 minutes of shaking to ensure good mixing. Droplet sizes are used to determine optimum fill level in the ATR. The shaking frequency follows a sinusoidal path and was set to 5 Hz. The images shown in the results section were taken at the peak of the sinusoidal motion. To convert to a counter-current design the two liquids need to be separated at the end of each tube. Liquids have been allowed to separate under gravity separation. Inclusion of baffles to reduce remixing by sloshing. Wall with height corresponding to 25 % fill volume allows kerosene to overflow into separate outlet. Increase in liquid fill level decreases the dispersion of the two liquid phases. Higher dispersion of droplets decreases surface area and therefore increases mass transfer in solvent extraction. 25 % should provide the greatest mass transfer though more work needs to completed to confirm this.

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗

Single-colony MALDI mass spectrometry imaging reveals spatial differences in metabolite abundance between natural and cultured Trichodesmium morphotypes

Trichodesmium, a globally significant N 2 -fixing marine cyanobacterium, forms extensive surface blooms in nutrient-poor ocean regions. These blooms consist of a dynamic assemblage of Trichodesmium species that form distinct colony morphotypes and are inhabited by diverse microorganisms. Trichodesmium colony morphotypes vary in ecological niche, nutrient uptake, and organic molecule release, differentially impacting ocean carbon and nitrogen biogeochemical cycles. Here, we assessed the poorly studied spatial abundance of metabolites within and between three morphologically distinct Trichodesmium colonies collected from the Red Sea. We also compared these results with two morphotypes of the cultivable Trichodesmium strain IMS101. Using matrix-assisted laser desorption/ionization (MALDI) mass spectrometry imaging (MSI) coupled with liquid extraction surface analysis (LESA) tandem mass spectrometry (MS2), we identified and localized a wide range of small metabolites associated with single-colony Trichodesmium morphotypes. Our untargeted MALDI-MSI approach revealed 80 unique features (metabolites) shared between Trichodesmium morphotypes. Discrimination analysis showed spatial variations in 57 shared metabolites, accounting for 62% of the observed variation between morphotypes. The greatest variations in metabolite abundance were observed between the cultured morphotypes compared to the natural colony morphotypes, suggesting substantial differences in metabolite production between the cultivable strain IMS101 and the naturally occurring colony morphotypes that the cultivable strain is meant to represent. This study highlights the variations in metabolite abundance between natural and cultured Trichodesmium morphotypes and provides valuable insights into metabolites common to morphologically distinct Trichodesmium colonies, offering a foundation for future targeted metabolomic investigations.

59 BASIC BIOLOGICAL SCIENCES↗

A Review on Bioinspired Proton Exchange Membrane Fuel Cell: Design and Materials

With the climate crisis gathering recognition, there has been significant interest in clean energy. As a reliable and clean energy solution, markets transitioning toward sustainable energy have identified polymer electrolyte membrane fuel cells (PEMFCs) as a critical technology. The increasing interest in PEMFCs is primarily due to their high energy density, high efficiency and zero greenhouse gas emission. However, additional development is required to overcome the current barriers associated with fuel cell component design, high manufacturing cost, and insufficient stability. Bioinspired designs have the potential to provide new and valuable insights using novel techniques for extracting design inspirations from biological structures. Applying these design concepts to develop materials and structures for various fuel cell components can be transformative. The well–adapted structures and functional features of biological systems have been proven to greatly enhance the performance of current designs through novel and optimized pathways. Bioinspired designs have indeed lived up to performance expectations and even exceed them. Herein, the potential and value of using these bioinspired designs are discussed. Recent studies and advancements based on nature–inspired structures for components of PEMFCs and how these design considerations substantiate their claim as an attractive alternative to conventional designs are discussed.

25 ENERGY STORAGE↗

Ionic Control over Ferroelectricity in 2D Layered van der Waals Capacitors

The van der Waals layered material CuInP 2 S 6 features interesting functional behavior, including the existence of four uniaxial polarization states, polarization reversal against the electric field through Cu ion migration, a negative-capacitance regime, and reversible extraction of Cu ions. At the heart of these characteristics lies the high mobility of Cu ions, which also determines the spontaneous polarization. Therefore, Cu migration across the lattice results in unusual ferroelectric behavior. Here, we demonstrate how the interplay of polar and ionic properties provides a path to ionically controlled ferroelectric behavior, achieved by applying selected DC voltage pulses and subsequently probing ferroelectric switching during fast triangular voltage sweeps. Using current measurements and theoretical calculations, we observe that increasing DC pulse duration results in higher ionic currents, the buildup of an internal electric field that shifts polarization loops, and an increase in total switchable polarization by ~50% due to the existence of a high polarization phase which is stabilized by the internal electric field. Apart from tuning ferroelectric behavior by selected square pulses, hysteretic polarization switching can even be entirely deactivated and reactivated, resulting in three-state systems where polarization switching is either inhibited or can be performed in two different directions.

36 MATERIALS SCIENCE↗

Cascade of electronic transitions in magic-angle twisted bilayer graphene

Magic-angle twisted bilayer graphene exhibits a variety of electronic states, including correlated insulators, superconductors and topological phases. Understanding the microscopic mechanisms responsible for these phases requires determination of the interplay between electron–electron interactions and quantum degeneracy (the latter is due to spin and valley degrees of freedom). Signatures of strong electron–electron correlations have been observed at partial fillings of the flat electronic bands in recent spectroscopic measurements, and transport experiments have shown changes in the Landau level degeneracy at fillings corresponding to an integer number of electrons per moiré unit cell. However, the interplay between interaction effects and the degeneracy of the system is currently unclear. Here in this paper we report a cascade of transitions in the spectroscopic properties of magic-angle twisted bilayer graphene as a function of electron filling, determined using high-resolution scanning tunnelling microscopy. We find distinct changes in the chemical potential and a rearrangement of the low-energy excitations at each integer filling of the moiré flat bands. These spectroscopic features are a direct consequence of Coulomb interactions, which split the degenerate flat bands into Hubbard sub-bands. We find these interactions, the strength of which we can extract experimentally, to be surprisingly sensitive to the presence of a perpendicular magnetic field, which strongly modifies the spectroscopic transitions. The cascade of transitions that we report here characterizes the correlated high-temperature parent phase from which various insulating and superconducting ground-state phases emerge at low temperatures in magic-angle twisted bilayer graphene.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗

Automatic log analysis with NLP for the CMS workflow handling

The central Monte-Carlo production of the CMS experiment utilizes the WLCG infrastructure and manages daily thousands of tasks, each up to thousands of jobs. The distributed computing system is bound to sustain a certain rate of failures of various types, which are currently handled by computing operators a posteriori. Within the context of computing operations, and operation intelligence, we propose a Machine Learning technique to learn from the operators with a view to reduce the operational workload and delays. This work is in continuation of CMS work on operation intelligence to try and reach accurate predictions with Machine Learning. We present an approach to consider the log files of the workflows as regular text to leverage modern techniques from Natural Language Processing (NLP). In general, log files contain a substantial amount of text that is not human language. Therefore, different log parsing approaches are studied in order to map the log files’ words to high dimensional vectors. These vectors are then exploited as feature space to train a model that predicts the action that the operator has to take. This approach has the advantage that the information of the log files is extracted automatically and the format of the logs can be arbitrary. In this work the performance of the log file analysis with NLP is presented and compared to previous approaches.

Layer, Lukas↗

Octet baryon magnetic moments from lattice QCD: Approaching experiment from a three-flavor symmetric point

We used lattice QCD calculations with background magnetic fields to determine the magnetic moments of the octet baryons. Computations are performed at the physical value of the strange quark mass, and two values of the light quark mass, one corresponding to the SU(3) flavor-symmetric point, where the pion mass is m π ~ 800 MeV, and the other corresponding to a pion mass m π ~ 450 MeV. The moments are found to exhibit only mild pion-mass dependence when expressed in terms of appropriately chosen magneton units---the natural baryon magneton. This suggests that simple extrapolations can be used to determine magnetic moments at the physical point, and extrapolated results are found to agree with experiment within uncertainties. A curious pattern is revealed among the anomalous baryon magnetic moments which is linked to the constituent quark model, however, careful scrutiny exposes additional features. Relations expected to hold in the large-N c limit of QCD are studied; and, in one case, the quark model prediction is significantly closer to the extracted values than the large-N c prediction. The magnetically coupled Λ-Σ 0 system is treated in detail at the SU(3) F point, with the lattice QCD results comparing favorably with predictions based on SU(3) F symmetry. Our analysis enables the first extraction of the isovector transition magnetic polarizability. The possibility that large magnetic fields stabilize strange matter is explored, but such a scenario is found to be unlikely.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

Machine-Learning Architecture for Ultrasonic Thermometry

Temperature distribution in solids can be inverted from the speed of sound (SOS) measurements, as has been shown feasible by timing the propagation of the excitation pulse and the train of echoes in ultrasonically segmented waveguides (WGs) and metal components. However, complicated geometries and closely-space echogenic features (EFs) create complex waveforms, from which the segmental time of flights (TOFs) are impossible to estimate using traditional methods. This work describes a machine learning architecture shown to extract temperature information from complex ultrasonic waveforms without explicit measurements of segmental TOFs. We accomplish this by using an autoencoder neural network (NN) to map ultrasonic waveforms into a low-dimensional latent space. A second NN then maps the latent space into unknown temperature distribution along the WG. The proposed architecture was tested in simulations and experimentally. The autoencoder accurately reconstructs the waveforms from their latent representation, several orders of magnitude lower in dimensionality. The obtained latent space was successfully mapped into the temperature of the propagation path.

John, Mason↗