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Advances in phosphor two-color ratio method thermography for full-field surface temperature measurements

We report thermographic phosphors can be employed for optical sensing of surface, gas phase, and bulk material temperatures through different strategies including the time-decay method, time-integrated method, and frequency-domain method. We focus on the time-integrated method, also known as the ratio method, as it can be more practical in many situations. This work advances the ratio method using two machine vision cameras with CMOS detectors for full-field temperature measurements of a solid surface. A phosphor calibration coupon is fabricated using aerosol deposition and employed for in situ determination of the temperature-versus-intensity ratio relationship. Algorithms from digital image correlation are employed to determine the stereoscopic imaging system intrinsic and extrinsic parameters, and accurately register material points on the sample to subpixel locations in each image with 0.07 px or better accuracy. Detector nonlinearity is carefully characterized and corrected. Temperature-dependent, spatial non-uniformity of the full-field intensity ratio—posited to be caused by a blue-shift effect of the bandpass filter for non-collimated light and/or a wavelength-dependent transmission efficiency of the lens—is assessed and treated for cases where a standard flat-field correction fails to correct the non-uniformity. In sum, pixel-wise calibration curves relating the computed intensity ratio to temperature in the range of T = 300–430 K are generated, with an embedded error of less than 3 K. This work offers a full calibration methodology and several improvements on two-color phosphor thermography, opening the door for full-field temperature measurements in dynamic tests with deforming test articles.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Metal Bioavailability and Ecotoxicity of Bioremediated Oils and Tailings by BioTiger{sup TM}, a Microbial Consortium

Oil Sands and Mature Fine Tailings: Oil sand reserves are a major source of oil for the United States. Oil sands are a mixture of sand, clay, water, and bitumen. The refining process requires large volumes of water and generates hazardous Mature Fine Tailings (MFTs) that are stored in engineered settling ponds. They are of major environmental concern due to their persistence and difficulty to naturally biodegrade. MFT Contaminants of Concern: Naphthenic Acids (NAs), Polycyclic Aromatic Hydrocarbons (PAHs), Benzene, Toluene, Ethylbenzene and Xylene (BTEX), Metals, Residual Bitumen. BioTiger{sup TM} (BT{sup TM}), the SRNL patented 12 component microbial consortia was found to cometabolically degrade some NAs and PAHs. Previous studies performing short term exposure (48 hours and 7 days) to BT{sup TM} have resulted in increased toxicity due to the partial degradation of PAHs forming toxic intermediates. Objective: Evaluate the ecotoxicity of BT{sup TM} remediated MFTs exposed to a 2 week period w/ yeast (Y) extract. This work will determine BT{sup TM}'s remediation of MFTs from Fort McMurray, Alberta. Acute toxicity tests will be performed under section 9 of EPA's Method for Measuring Acute Toxicity using the freshwater organism, Ceriodaphnia dubia. Monitor BT{sup TM} growth through Most Probable Number (MPN) counts, pH, and metal bioavailability will also be evaluated. Preparing tailing solutions for biodegradation: BT{sup TM} components were grown in R2A media and combined. Mother BT{sup TM} was centrifuged at 7000 rpm for 20 minutes and resuspended in Bushnell Haus. 33 g of tailings were added to 1100 mL Bushnell Haus along with yeast extract (11 g) to create a 3% tailing solution. Treatments were performed in triplicate. Preparing solutions for toxicity tests using C. dubia: Supernatant was collected immediately after centrifuging at 7000 rpm for 20 min. Supernatant was filtered via a 0.22 μm sterile system. All treatments except MFT, Y peaked at T=4. This decrease in microbial growth could be associated with toxicity from intermediate byproducts. Treatments containing only MFTs decreased in the initial 11 days before growing significantly. Final solution for MFT, Y treatment had the highest pH. This could potentially be due to increased microbial activity linked with yeast consumption. All treatments except MFT, Y peaked at T=4. This decrease in microbial growth could be associated with toxicity from intermediate byproducts. Treatments containing only MFTs decreased in the initial 11 days before growing significantly. Future Direction: Await results from Acute Toxicity Tests and Metal Bioavailability Quantification of biosurfactant production. Evaluate hydrocarbon degradation byproducts using an analytical chemistry approach. More toxicity experiments with variations in time and conditions.

54 ENVIRONMENTAL SCIENCES↗

Calculating Potential Radiological Emissions for Waste Management Activities at INL - 20068

At Idaho National Laboratory (INL), work involving radionuclides is evaluated for potential emissions from a project in order to comply with the National Emission Standards for Hazardous Air Pollutants (NESHAP) regulations, 40 CFR 61 Subpart H. Emission calculations are documented in an Air Permitting Applicability Determination (APAD) to analyze unmitigated and mitigated emissions and determine if an Application to Construct (ATC) or continuous monitoring is required. To calculate the unmitigated and mitigated emissions, a spreadsheet was developed to provide ease in determining potential emissions by providing the maximum operating temperature and the material being used. The spreadsheet aids in determining the potential emissions for research projects and waste management activities at Materials and Fuels Complex (MFC) and other locations across the INL site. Furthermore, it can also be used for periodic confirmatory measurements (PCM) to justify low emissions. Elements that factor into the unmitigated and mitigated calculations include the amount of each radionuclide used (in curies or grams), specific activity (if amount is given in grams), the temperature the material is heated to in Celsius, the dose conversion factor which is derived from Clean Air Act Assessment Package - 1988 (CAP-88) modeling, and the number of HEPA filters used for mitigated measures. The main drivers for calculating the unmitigated emissions for a project are the amount used per radionuclide, the maximum operating temperature, and the location of the work. The maximum operating temperature determines the airborne release factor which is dependent on the physical state of the radionuclide. Prior to October 2017, if the radionuclide was heated to greater than 100 deg. C, the radionuclide was assumed to be a gas, which has the highest airborne release factor. This assumption would be overly conservative for radionuclides with high melting and boiling points, which provided a challenge to demonstrate low emissions. In October 2017, the Environmental Protection Agency (EPA) approved an alternative method for INL. This method allows the airborne release factor to be determined by using the melting point and 90% of the boiling point of the radionuclide. This methodology was included in the spreadsheet to allow unmitigated emission calculations for APADs to be completed more efficiently and effectively. Results show a reduction in time completing air emission calculations as well as lower total emissions across all facilities at INL. MFC annual emissions were reduced by 62% from the previous year and Research and Education Campus (REC) facilities were reduced by 38% due to implementation of the approved alternative method. Time spent on APADs, PCMs, and documentation for the annual NESHAP report was also reduced significantly. The spreadsheet provided in Table I provides the potential emission calculations for the 'Advanced Retrieval and Disposition Techniques for Remote Handled Mixed Low Level Waste (RH MLLW) at the Radioactive Scrap and Waste Facility (RSWF)' project. Calculations show the Potential Effective Dose Equivalent (PEDE) at RSWF to be 7.27 E-04 mrem/yr (7.27 E-09 Sv/yr) which is well below the 0.1 mrem/yr threshold. (authors)

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗

Zwitterion Moieties in Polypeptides Synergistically Enhance the Release of Cellulose and Amorphous Polysaccharides from Plant Cell Walls

This study demonstrated that covalently localized zwitterionic moieties in zwitterionic polypeptides (ZIPs) effectively disrupt hydrogen bonds in cellulosic substrates, including filter paper and plant cell wall materials, without significant cytotoxicity. ZIPs with varying densities of zwitterionic side chains were synthesized via the postpolymerization modification of histidinecontaining oligopeptides. The newly developed ZIPs predominantly comprised repeating units with zwitterionically converted side chains. Such ZIPs can cleave multiple hydrogen bonds by anchoring the zwitterionic structure at specific sites, thereby partially dissociating the polysaccharide chains in the cell wall. They are especially effective in dissolving amorphous cellulose, even at low concentrations in aqueous solutions. Importantly, this effect was achieved with minimal cellular toxicity, harnessing the advantages of ionic liquid-like properties while mitigating their high-toxicity limitations. This biofriendly approach to cell wall denaturation highlights a novel method for controlling hydrogen bond networks in polysaccharides and cell walls. These findings indicate a new approach for reducing biomass recalcitrance and developing next-generation biobased materials and fuels derived from plant cell walls.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Boosting H I -Galaxy Cross-Clustering Signal through Higher-Order Cross-Correlations

After reionization, neutral hydrogen (${\rm H\, \small {I}}$) traces the large-scale structure (LSS) of the Universe, enabling ${\rm H\, \small {I}}$ intensity mapping (IM) to capture the LSS in 3D and constrain key cosmological parameters. We present a new framework utilizing higher-order cross-correlations to study ${\rm H\, \small {I}}$ clustering around galaxies, tested using real-space data from the IllustrisTNG300 simulation. This approach computes the joint distributions of k-nearest neighbor (kNN) optical galaxies and the ${\rm H\, \small {I}}$ brightness temperature field smoothed at relevant scales (the kNN-field framework), providing sensitivity to all higher-order cross-correlations, unlike two-point statistics. To simulate ${\rm H\, \small {I}}$ data from actual surveys, we add random thermal noise and apply a simple foreground cleaning model, filtering out Fourier modes of the brightness temperature field with k ∥ < k min,∥ . Under current levels of thermal noise and foreground cleaning, typical of a Canadian Hydrogen Intensity Mapping Experiment (CHIME)-like survey, the ${\rm H\, \small {I}}$-galaxy cross-correlation signal in our simulations, using the kNN-field framework, is detectable at >30σ across r = [3, 12] h –1 Mpc. In contrast, the detectability of the standard two-point correlation function (2PCF) over the same scales depends strongly on the foreground filter: a sharp k ∥ filter can spuriously boost detection to 8σ due to position-space ringing, whereas a less sharp filter yields no detection. Nonetheless, we conclude that kNN-field cross-correlations are robustly detectable across a broad range of foreground filtering and thermal noise conditions, suggesting their potential for enhanced constraining power over 2PCFs.

79 ASTRONOMY AND ASTROPHYSICS↗

Innovative Nuclear Materials Outboard-A Project Specimen Preparation Guide

The Innovative Nuclear Materials (INM) Program was recently established by the U.S. Department of Energy (DOE) to develop advanced material technologies for use in nuclear reactors. The INM program is presently focused on researching in-core non-fueled materials for application in fast spectrum nuclear reactors. The widespread deployment of fast reactors continues to be a prominent aspiration for advanced nuclear technology developers. However, companies working to license these reactors have no choice but to rely on historic material technologies since further optimization and advancement of these materials is impeded by the lack of fast neutron irradiation test facilities. INM-OA is a non-fueled drop-in experiment which will irradiate material specimens of interest to fast reactor applications. This experiment will be irradiated at Idaho National Laboratory (INL) in the Advanced Test Reactor (ATR) outboard-A (OA) position during normal and high temperature steady state (HTSS) cycles. It will include material specimens supplied by members of the INM program and will utilize a cadmium-lined basket to filter out incident thermal neutrons, thus simulating a faster neutron energy spectrum. Material specimens will undergo post-irradiation examination including microscopy and mechanical testing. In addition to absorption reactions, fast neutrons cause microstructural damage in materials by atom displacement, which can cause exacerbated changes in physical properties and behavior. Thus, the data obtained from the INM-OA experiment will be crucial for understanding the engineering-scale behavior of reactor materials. This document is intended for the Principal Investigators providing samples for this project. Topics included are a general description of the experiment, the irradiation experiment/capsule design, sample geometries, number of samples to be provided, documentation to be provided, a brief list potentially useful characterization methods that can be leveraged at INL, and other miscellaneous requirements specific to this project. This document is intended for informational use only.

innovative nuclear materials↗

ORNL_AISD_NiPt

This dataset describes the nickel-platinum (NiPt) solid solution binary alloy, where the two constituent elements nickel (Ni) and platinum (Pt) are randomly placed on the face centered cubic (FCC) crystal structure, with the lattice constant of 3.840 angstroms. The dataset comprises data for three different sizes of the crystal structure: 256 atoms, 864 atoms, and 2,048 atoms, each of which contains 1900 configurations. For each size of the crystal structure, the data set was generated for concentrations ranging from 0at% of Pt to 100at% of Pt in the NiPt binary system, with increasing the concentration of Pt in the system every 5at%. For each one of the chemical compositions, 100 random configurations were generated, each with a different random seed. Each of the output files contains the mass, type, atomic coordinates, energy per atom, and forces in x, y, and z directions respectively. For each atomic configuration, the output was collected every 150 steps during the minimization stage and every 1000 steps during the replica exchange stage. Large-scale Atomic/Molecular Massively Parallel Simulator (LAMMPS) [1], which is a molecular dynamics code, was used to generate data for NiPt alloy. The simulation used the interatomic potential for NiPt binary system MEAM_LAMMPS_KimSeolJi_2017_PtNi__MO_020840179467_001 [3] from the OpenKIM library (Open Knowledgebase of Interatomic Models) [2]. This potential was developed based on the second nearest-neighbor modified embedded-atom method (2NN MEAM). The simulation process begins with the generation of the random NiPt structure and follows with the short minimization and replica exchange simulation. The minimization procedure adjusts atomic coordinates and performs energy minimization, which typically leads to a local potential energy minimum. The method used for the minimization was the conjugate gradient algorithm. A short replica exchange (parallel tempering) simulation involves four replicas (ensembles) of a system and follows the minimization stage. Multiple snapshots of the configuration were collected during the minimization and replica exchange stages. NiPt alloy is interesting due to its magnetic and charge transfer properties [4]. The data is provided in three compressed zipped folders: atoms256.zip, atoms864.zip, atoms2048.zip Each zipped folder contains the data that describes crystals of size 256 atoms, 864 atoms, and 2,048 atoms respectively. Each one of the three zipped folders contains the data structured in the following way: -Ni_ground_state.cfg --> atomic configuration for the pure nickel -Pt_ground_state.cfg --> atomic configuration for the pure platinum -Pt#_filtered --> folders containing atomic configurations for #at% concentration of platinum. The folder contains 100 atomic configurations, each saved in a subfolder. Each subfolder named config* is associated with a specific atomic configuration. Each of these subfolders contains files with .cfg format, corresponding to outputs for each atomic configuration The total number of atomic configurations contained in atoms256.zip is 65,046. The total number of atomic configurations contained in atoms864.zip is 63,936. The total number of atomic configurations contained in atoms2048.zip is 61,997. The total number of atomic configurations spanned by the entire dataset is 190,979. References [1] https://www.lammps.org/ [2] https://openkim.org/ [3] https://openkim.org/id/MEAM_LAMMPS_KimSeolJi_2017_PtNi__MO_020840179467_001 [4] El-Gendy, Ahmed A. and Hampel, Silke and Büccchner, Bernd and Klingeler, Rüdiger, Tuneable magnetic properties of carbon-shielded NiPt-nanoalloys, RSC Adv., volume 6, issue 57, pages 52427-52433, 2016, The Royal Society of Chemistry, doi:10.1039/C6RA05910D

36 MATERIALS SCIENCE↗

J-PLUS: Uncovering a large population of extreme [OIII] emitters in the local Universe

Over the past decades, several studies have discovered a population of galaxies that undergo very strong star formation events. They are called extreme emission line galaxies (EELGs). We exploit the capabilities of the Javalambre Photometric Local Universe Survey (J-PLUS), a wide-field multifilter survey, with which 2000 square degrees of the northern sky are already observed. We use it to identify EELGs at low redshift by their [OIII]5007 emission line. We intend to provide a more complete, deep, and less biased sample of local EELGs. We selected objects with an excess of flux in the J-PLUS medium-band J0515 filter, which covers the [OIII] line at z < 0.06. We removed contaminants (stars and higher-redshift systems) using J-PLUS and WISE infrared photometry, with SDSS spectra as a benchmark. We performed spectral energy distribution fitting to estimate the physical properties of the galaxies: line fluxes, equivalent widths (EWs), masses, stellar population ages, and so on. We identify 466 EELGs at z < 0.06 with [OIII] EW over 300 Å and an r-band magnitude below 20, of which 411 were previously unknown. Most show compact morphologies, low stellar masses (log(M • /M ⊙ ) ~ 8.13 –0.58 +0.61 ), low dust extinction (E( B–V ) ~ 0.1 –0.1 +0.2 ), and very young bursts of star formation (3.0 –2.0 +2.7 Myr). Our method is up to ~20 times more efficient in detecting EELGs per Mpc 3 than broadband surveys, and it is as complete as magnitude-limited spectroscopic surveys (but reaches fainter objects). The sample is not directly biased against strong Hα emitters, in contrast with works using broadband surveys. We demonstrate that J-PLUS can identify a large sample of previously unknown EELGs showing unique properties following a clear selection process. A fraction of the EELGs are probably similar to the first galaxies in the Universe, but they are at a much lower redshift, which makes them ideal targets for follow-up studies.

79 ASTRONOMY AND ASTROPHYSICS↗

MassIVE MSV000094084 - Data files for manuscript - Selected ion monitoring for orbitrap-based metabolomics: Please open README-data-for-SIM-paper-20240210.doc for details.

Orbitrap mass spectrometry in full scan mode enables the simultaneous detection of hundreds of metabolites and their isotope-labeled forms. Yet, sensitivity remains limiting for many metabolites, including low-concentration species, poor ionizers, and low-fractional-abundance isotope-labeled forms in isotope-tracing studies. Here, we explore selected ion monitoring (SIM) as a means of sensitivity enhancement. The analytes of interest are enriched in the orbitrap analyzer by using the quadrupole as a mass filter to select particular ions. In tissue extracts, SIM significantly enhances the detection of ions of low intensity, as indicated by improved signal-to-noise (S/N) ratios and measurement precision. In addition, SIM improves the accuracy of isotope-ratio measurements. SIM, however, must be deployed with care, as excessive accumulation in the orbitrap of similar m/z ions can lead, via space-charge effects, to decreased performance (signal loss, mass shift, and ion coalescence). Ion accumulation can be controlled by adjusting settings including injection time and target ion quantity. Overall, we suggest using a full scan to ensure broad metabolic coverage, in tandem with SIM, for the accurate quantitation of targeted low-intensity ions, and provide methods deploying this approach to enhance metabolome coverage. Please open README-data-for-SIM-paper-20240210.doc for details. [doi:10.25345/C5JH3DD3K] [dataset license: CC0 1.0 Universal (CC0 1.0)]

Rabinowitz, Joshua↗

Selected Ion Monitoring for Orbitrap-Based Metabolomics

Orbitrap mass spectrometry in full scan mode enables the simultaneous detection of hundreds of metabolites and their isotope-labeled forms. Yet, sensitivity remains limiting for many metabolites, including low-concentration species, poor ionizers, and low-fractional-abundance isotope-labeled forms in isotope-tracing studies. Here, we explore selected ion monitoring (SIM) as a means of sensitivity enhancement. The analytes of interest are enriched in the orbitrap analyzer by using the quadrupole as a mass filter to select particular ions. In tissue extracts, SIM significantly enhances the detection of ions of low intensity, as indicated by improved signal-to-noise (S/N) ratios and measurement precision. In addition, SIM improves the accuracy of isotope-ratio measurements. SIM, however, must be deployed with care, as excessive accumulation in the orbitrap of similar m/z ions can lead, via space-charge effects, to decreased performance (signal loss, mass shift, and ion coalescence). Ion accumulation can be controlled by adjusting settings including injection time and target ion quantity. Overall, we suggest using a full scan to ensure broad metabolic coverage, in tandem with SIM, for the accurate quantitation of targeted low-intensity ions, and provide methods deploying this approach to enhance metabolome coverage.

59 BASIC BIOLOGICAL SCIENCES↗

A Method of Estimating Sparse and Doubly-Dispersive Channels

The large delay and Doppler spreads of skywave high-frequency (HF) channels complicates channel acquisition, especially in low-SNR conditions. Using pilot-symbol assisted modulation, we develop a robust method to acquire channel information by first estimating the power-delay profile (PDP) of the channel, then applying that estimate to obtain the channel coefficients only where the PDP is nonzero. We find the presented approach to be robust at low-SNRs, making it suitable for spread-spectrum and underlay waveforms. We show that this two-stage channel acquisition procedure has three advantages: i),the channel is estimated with fewer terms, reducing complexity; ii), the MSE of the channel estimate is lower than assuming a fixed channel length; and iii), each propagation mode is reliably recovered in high-Doppler conditions. We conclude this paper by presenting results of the developed techniques as applied to a filter-bank multicarrier spread-spectrum (FBMC-SS) waveform.

42 ENGINEERING↗

DNA-assembled superconducting 3D nanoscale architectures

Studies of nanoscale superconducting structures have revealed various physical phenomena and led to the development of a wide range of applications. Most of these studies concentrated on one- and two-dimensional structures due to the lack of approaches for creation of fully engineered three-dimensional (3D) nanostructures. Here, we present a ‘bottom-up’ method to create 3D superconducting nanostructures with prescribed multiscale organization using DNA-based self-assembly methods. We assemble 3D DNA superlattices from octahedral DNA frames with incorporated nanoparticles, through connecting frames at their vertices, which result in cubic superlattices with a 48 nm unit cell. The superconductive superlattice is formed by converting a DNA superlattice first into highly-structured 3D silica scaffold, to turn it from a soft and liquid-environment dependent macromolecular construction into a solid structure, following by its coating with superconducting niobium (Nb). Through low-temperature electrical characterization we demonstrate that this process creates 3D arrays of Josephson junctions. This approach may be utilized in development of a variety of applications such as 3D Superconducting Quantum interference Devices (SQUIDs) for measurement of the magnetic field vector, highly sensitive Superconducting Quantum Interference Filters (SQIFs), and parametric amplifiers for quantum information systems.

77 NANOSCIENCE AND NANOTECHNOLOGY↗

Latent Stochastic Differential Equations for Modeling Quasar Variability and Inferring Black Hole Properties

Quasars are bright and unobscured active galactic nuclei (AGN) thought to be powered by the accretion of matter around supermassive black holes at the centers of galaxies. The temporal variability of a quasar’s brightness contains valuable information about its physical properties. The UV/optical variability is thought to be a stochastic process, often represented as a damped random walk described by a stochastic differential equation (SDE). Upcoming wide-field telescopes such as the Rubin Observatory Legacy Survey of Space and Time (LSST) are expected to observe tens of millions of AGN in multiple filters over a ten year period, so there is a need for efficient and automated modeling techniques that can handle the large volume of data. Latent SDEs are machine learning models well suited for modeling quasar variability, as they can explicitly capture the underlying stochastic dynamics. In this work, we adapt latent SDEs to jointly reconstruct multivariate quasar light curves and infer their physical properties such as the black hole mass, inclination angle, and temperature slope. Our model is trained on realistic simulations of LSST ten year quasar light curves, and we demonstrate its ability to reconstruct quasar light curves even in the presence of long seasonal gaps and irregular sampling across different bands, outperforming a multioutput Gaussian process regression baseline. Our method has the potential to provide a deeper understanding of the physical properties of quasars and is applicable to a wide range of other multivariate time series with missing data and irregular sampling.

79 ASTRONOMY AND ASTROPHYSICS↗

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↗

DER Inverter Control Fault Ride Through Model in Accordance with IEEE 1547-2018 Std

Distributed Energy Resources (DER) with smart inverters are becoming more prevalent as the need for renewable energy and grid stability increases. An important challenge arises when considering that inverterbased generation methods contribute less current during faults, rendering traditional overcurrent protection unsatisfactory. DERs have fault ride-through requirements when operating in high or low voltage, outlined by IEEE Std. 1547-2018. Faults cause the voltage to reach abnormal steady state magnitudes, depending on the fault resistance and fault type. There are several high voltage and low voltage ride-through zones defined by IEEE Std. 1547-2018. Each zone’s ride through duration decreases as the applicable voltage measurement, i.e., the phase RMS voltage, deviates from its nominal value. This presentation demonstrates the implementation of IEEE Std. 1547-2018 high and low voltage ridethrough grid support functions using a preexisting RSCAD model, discussing the challenges presented during this process. The implemented controls monitor the filtered phase voltages to have a more accurate reading of the applicable voltages. The controls sense the duration that the applicable voltage remains in a specific zone. The breaker trips and ceases energization to the grid when the duration is exceeded. The standard allows the operator to adjust the ride-through times and voltage zones from the default settings. These ranges are implemented into the runtime, which acts as the operator’s SCADA. The results show the accuracy of the voltage measurements, which remain within the IEEE Std. 1547-2018 for all cases.

24 POWER TRANSMISSION AND DISTRIBUTION↗

A Morphological Model to Separate Resolved–Unresolved Sources in the DESI Legacy Surveys: Application in the LS4 Alert Stream

Separating resolved and unresolved sources in large imaging surveys is a fundamental step to enable downstream science, such as searching for extragalactic transients in wide-field time-domain surveys. Here we present our method to effectively separate point sources from the resolved, extended sources in the Dark Energy Spectroscopic Instrument (DESI) Legacy Surveys (LS). We develop a supervised machine learning model based on the Gradient Boosting algorithm XGBoost. The features input to the model are purely morphological and are derived from the tabulated LS data products. We train the model using ∼2 × 10 5 LS sources in the COSMOS field with HST morphological labels and evaluate the model performance on LS sources with spectroscopic classification from the DESI Data Release 1 (∼2 × 10 7 objects) and the Sloan Digital Sky Survey Data Release 17 (∼3 × 10 6 objects), as well as on ∼2 × 10 8 Gaia stars. A significant fraction of LS sources are not observed in every LS filter, and we therefore build a “Hybrid” model as a linear combination of two XGBoost models, each containing features combining aperture flux measurements from the “blue” (gr) and “red” (iz) filters. The Hybrid model shows a reasonable balance between sensitivity and robustness, and achieves higher accuracy and flexibility compared to the LS morphological typing. With the Hybrid model, we provide classification scores for ∼3 × 10 9 LS sources, making this the largest ever machine learning catalog separating resolved and unresolved sources. The catalog has been incorporated into the real-time pipeline of the La Silla Schmidt Southern Survey (LS4), enabling the identification of extragalactic transients within the LS4 alert stream.

astrostatistics↗

Convective and turbulent motions in non-precipitating Cu. Part 1: Method of separation of convective and turbulent motions

Atmospheric motions in clouds and cloud surroundings have a wide range of scales, from several kilometers to centimeters. These motions have different impacts on cloud dynamics and microphysics. Larger-scale motions (hereafter referred to as convective motions) are responsible for mass transport over distances comparable with cloud scale, while motions of smaller scales (hereafter referred to as turbulent motions) are stochastic and responsible for mixing and cloud dilution. This distinction substantially simplifies the analysis of dynamic and microphysical processes in clouds. The present research is Part I of the study aimed at describing the method for separating the motion scale into a convective component and a turbulent component. An idealized flow is constructed, which is a sum of an initially prescribed field of the convective velocity with updrafts in the cloud core and downdrafts outside the core, and a stochastic turbulent velocity field obeying the turbulent properties, including the -5/3 law and the 2/3 structure function law. A wavelet method is developed allowing separation of the velocity field into the convective and turbulent components, with parameter values being in a good agreement with those prescribed initially. The efficiency of the method is demonstrated by an example of a vertical velocity field of a cumulus cloud simulated using the System for Atmospheric Modeling (SAM) with bin microphysics and resolution of 10 m. It is shown that vertical velocity in clouds indeed can be represented as a sum of convective velocity (forming zone of cloud updrafts and subsiding shell) and a stochastic velocity obeying laws of homogeneous and isotropic turbulence.

54 ENVIRONMENTAL SCIENCES↗

Lanczos algorithm for lattice QCD matrix elements

Recent work [M. L. Wagman, Lanczos, the transfer matrix, and the signal-to-noise problem, .] found that an analysis formalism based on the Lanczos algorithm allows energy levels to be extracted from Euclidean correlation functions with faster ground-state convergence than effective masses, convergent estimators for multiple states from a single correlator, and two-sided error bounds. After filtering out spurious eigenvalues and using outlier-robust estimators within a nested bootstrap framework, Lanczos estimators behave more like multistate fit results than effective masses—but without involving statistical fitting. We extend this formalism to the determination of matrix elements from three-point correlation functions and provide a physical picture of “spurious-state filtering” involving restriction to a Hermitian subspace. We demonstrate similar advantages for matrix elements as for spectroscopy through example applications to noiseless mock-data and (bare) forward matrix elements of the strange scalar current between both ground and excited states with the quantum numbers of the nucleon.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗