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At least 1,729 records · Page 96

CSAPR2 Optimized Convective Cell Tracking Data during TRACER

One of the challenges in analyzing convective cell properties is to observe the quick evolution of individual convective cells. While the operational radar data provide a volumetric data set to analyze radar observables of convective precipitation clouds, previous studies also suggested the quick evolution of cell life cycle that might not be captured by conventional radar volume scan strategies that take ~5-7 minutes. Aiming at enhancing our understanding of the links between convective cloud kinematic and microphysical processes as well as life cycles, the Tracking Aerosol Convection Interactions ExpeRiment (TRACER; Jensen et al. 2019) was conducted at Houston, Texas, in 2022. The TRACER campaign deployed the 2nd generation C-band Scanning ARM Precipitation Radar (CSAPR2), which performed frequent updates of range height indicator (RHI) and sector plan position indicator (PPI) scans to track individual convective cells every < 2 minutes, guided by a new cell tracking framework, Multisensor Agile Adaptive Sampling (MAAS; Kollias et al. 2020). This allows for capturing fast-evolving radar observables. We provide the processed CSAPR2 cell tracking data in CfRadial format collected during the TRACER field campaign from June to September 2022. The data files include processed radar variables: noise-masked reflectivity and differential reflectivity corrected for rain attenuation and systematic biases, noise-masked dealiased radial velocity, specific differential phase, locations of target cells (latitude, longitude, radar range), and radar-echo classification. Figure 1 provides an example of a 3D image of CSAPR2 reflectivity from the lowest PPI scan and an RHI scan after data processing.

54 ENVIRONMENTAL SCIENCES↗

Multivariate Analysis Based on Geochemical, Isotopic, and Mineralogical Compositions of Uranium-Rich Samples

The chemical and isotopic (U, Pb, Sr) signatures for a suite (n = 23) of pristine (>80 wt. % UO 2 ) and altered uraninite samples (>70–80 wt. % UO 2 ) from various locations worldwide have been determined for the purpose of identifying potential fingerprints for nuclear forensic analysis. The characterization of the uraninite samples included determination of major, minor and trace element contents, Sr, Pb, and U isotopic compositions, and secondary mineral assemblages. Due to the multivariate approach adopted in this study, principal component analysis (PCA) has been employed to allow the direct comparison of multiple variable types. The PCA results indicate that the geological origin (sandstone, metamorphite, intrusive, granite and unconformity) of pristine uraninite can be readily identified utilizing various combinations of major and/or trace element concentrations with isotopic compositions.

58 GEOSCIENCES↗

Deep Learning Classification of Cheatgrass Invasion in the Western United States Using Biophysical and Remote Sensing Data

Cheatgrass (Bromus tectorum) invasion is driving an emerging cycle of increased fire frequency and irreversible loss of wildlife habitat in the western US. Yet, detailed spatial information about its occurrence is still lacking for much of its presumably invaded range. Deep learning (DL) has demonstrated success for remote sensing applications but is less tested on more challenging tasks like identifying biological invasions using sub-pixel phenomena. We compare two DL architectures and the more conventional Random Forest and Logistic Regression methods to improve upon a previous effort to map cheatgrass occurrence at >2% canopy cover. High-dimensional sets of biophysical, MODIS, and Landsat-7 ETM+ predictor variables are also compared to evaluate different multi-modal data strategies. All model configurations improved results relative to the case study and accuracy generally improved by combining data from both sensors with biophysical data. Cheatgrass occurrence is mapped at 30 m ground sample distance (GSD) with an estimated 78.1% accuracy, compared to 250-m GSD and 71% map accuracy in the case study. Furthermore, DL is shown to be competitive with well-established machine learning methods in a limited data regime, suggesting it can be an effective tool for mapping biological invasions and more broadly for multi-modal remote sensing applications.

54 ENVIRONMENTAL SCIENCES↗

DMTN-118: Review of Timeseries Features

Rubin Observatory will compute timeseries variability features on lightcurves to aid users in identifying objects of interest, both during realtime Alert Production as well as in the annual Data Releases. The Data Products Definition Document (DPDD; LSE-163) allocates space for pre-computed timeseries features, and a sample set is baselined in LDM-151. However, in the subsequent decade the scientfic community has made a great deal of further progress in this area. This technote reviews the relevant literature, grouping related features where possible; discusses potential concerns and open questions; and proposes a new baseline feature set.

79 ASTRONOMY AND ASTROPHYSICS↗

Studies of $\Lambda n$ interaction through polarization observables for final-state interactions in exclusive $\Lambda$ photoproduction off the deuteron

Theoretical studies suggest that experimental observables for hyperon production reactions can place stringent constraints on the free parameters of hyperon-nucleon potentials, which are critical for the understanding of hypernuclear matter and neutron stars. Here we present preliminary experimental results for the polarization observables S, Py, Ox, Oz, Cx, and Cz for final-state interactions (FSI) in exclusive L photoproduction off the deuteron. The observables were obtained from data collected during the E06-103 (g13) experiment with the CEBAF Large Acceptance Spectrometer (CLAS) in Hall B at Jefferson Lab. The g13 experiment ran with unpolarized deuteron target and circularly- and linearly-polarized photon beams with energies between 0.5 GeV and 2.5 GeV and collected about 51010 events with multiple charged particles in the final state. To select the reaction of interest, the K+ and the L decay products, a proton and a negative pion, were detected in the CLAS. The missing-mass technique was used to identify exclusive hyperon photoproduction events. Final-state interaction events were selected by requesting that the reconstructed neutron has a momentum larger than 200 MeV/c. The large statistics of E06-103 provided statistically meaningful FSI event samples, which allow for the extraction of one- and two-fold differential single- and double-polarization observables. Here we present preliminary results for a set of six observables for photon energies between 0.9 GeV and 2.3 GeV and for several kinematic variables in the Ln center-of-mass frame. Our results are the very first estimates of polarization observables for FSI in hyperon photoproduction and will be used to constrain the free parameters of hyperon-nucleon potentials.

Ilieva, Yordanka↗

UQ Toolkit v. 3.0

The Uncertainty Quantification (UQ) Toolkit is a software library for the characterization and propagation of uncertainties in computational models. This library provides Bayesian inference tools to infer uncertain model parameters, Bayesian compressive sensing methods for discovering sparse representations of high-dimensional input-output response surfaces, methods for constructing Karhunen-Loève representations of stochastic processes, and global sensitivity analysis tools used to compute Sobol indices in order to characterize the importance of uncertain inputs or the interactions between them. The basis for many of these methods relies on representing random variables with Polynomial Chaos expansions (PCEs). This library implements several spectral basis function types (e.g. Hermite basis functions in terms of Gaussian random variables or Legendre basis functions in terms of uniform random variables) that can be used to represent random variables with PCEs. For the propagation of uncertainty, tools are provided to propagate PCEs that describe the input uncertainty through the computational model using either intrusive methods (Galerkin projection of equations onto basis functions) or non-intrusive methods (perform deterministic operation at sampled values of the random values and project the obtained results onto basis functions).

Sargsyan, Khachik↗

Building Alternative Indices of Socioeconomic Status for Population Modeling in Data-Sparse Contexts (Short Paper)

Population modeling requires clear definitions of socioeconomic status (SES) to ensure overall estimate accuracy and locate potentially underserved subpopulations. This presents a challenge as SES can be measured in myriad ways and for divergent purposes, and the data required to calculate these metrics may be lacking, particularly in low and middle income countries (LMICs). To support more refined SES measurement, we explore improvements upon the Demographic and Health Survey’s (DHS) Wealth Index (DHS-WI) using alternative characterizations of SES based on multiple correspondence analysis (MCA) and hierarchical clustering. We produce the MCA-derived metrics first on a full suite of household economic, demographic, and dwelling variables, then on a reduced set of occupant-only SES characteristics. We explore the utility of these metrics relative to DHS-WI based on their ability to 1) differentiate DHS household types and 2) identify mixtures of SES levels within DHS samples and mapped at high spatial resolution. We find that our full suite MCA yields more clearly defined SES segments and that our reduced MCA delineates occupant SES most clearly, suggesting potential pathways to improve upon the DHS-WI in future population modeling efforts for LMICs.

Cunningham, Angela↗

Melting rate correlation with batch properties and melter operating conditions during conversion of nuclear waste melter feeds to glasses

The rate of conversion of nuclear waste melter feed to glass is affected by the selection of melter feed materials and by melter design and operation. The melting rate correlation (MRC) is an equation that relates the glass production rate with two types of variables: (1) feed and melt properties: conversion heat, cold-cap bottom temperature, and glass melt viscosity; and (2) melter design and operation parameters: melter geometry, melter operating temperature, and gas bubbling rate. The MRC shows good agreement for an extended melting-rate data set of high-level waste (HLW) melter feeds and a data set generated for low-activity waste (LAW) melter feeds. Laboratory observation of heated melter feed samples is often used to assess the cold-cap bottom temperature of HLW melter feeds (moderately foaming feeds), but this technique appears inadequate for LAW melter feeds (vigorously foaming feeds). For LAW feeds, an adequate assessment of the cold-cap bottom temperature was achieved using evolved gas analysis, which allows identification of the collapse of primary foam for oxidized feeds. This assessment shows that the cold-cap bottom temperature for vigorously foaming LAW feeds is higher than that for moderately foaming HLW feeds. When the results of MRC are compared, LAW feeds are generally less sensitive to the bubbling rate and melt viscosity, and more sensitive to the cold-cap bottom temperature than HLW feeds. The MRC qualifies as a promising tool to support the selection of melter feed materials and melter operating conditions, which is determined from expensive independent scaled melter experiments, and sophisticated mathematical models.

Lee, Seung Min↗

Comparison of Experimental Methods for Estimating Matrix Diffusion Coefficients for Contaminant Transport Modeling

Diffusion cell and diffusion wafer experiments were conducted to compare methods for estimating matrix diffusion coefficients in rock core samples from Pahute Mesa at the Nevada Nuclear Security Site (NNSS). A diffusion wafer method, in which a solute diffuses out of a rock matrix that is pre-saturated with water containing the solute, is presented as a simpler alternative to the traditional through-diffusion (diffusion cell) method. Both methods yielded estimates of matrix diffusion coefficients that were within the range of values previously reported for NNSS volcanic rocks. The difference between the estimates of the two methods ranged from 14 to 30%, and there was no systematic high or low bias of one method relative to the other. From a transport modeling perspective, these differences are relatively minor when one considers that other variables (e.g., fracture apertures, fracture spacings) influence matrix diffusion to a greater degree and tend to have greater uncertainty than diffusion coefficients. For the same relative random errors in concentration measurements, the diffusion cell method yields diffusion coefficient estimates that have less uncertainty than the wafer method. However, the wafer method is easier and less costly to implement and yields estimates more quickly, thus allowing a greater number of samples to be analyzed for the same cost and time. Given the relatively good agreement between the methods, and the lack of any apparent bias between the methods, the diffusion wafer method appears to offer advantages over the diffusion cell method if better statistical representation of a given set of rock samples is desired.

98 NUCLEAR DISARMAMENT, SAFEGUARDS, AND PHYSICAL P↗

Annual and seasonal variability of metals and metalloids in urban and industrial soils in Alcalá de Henares (Spain)

Contamination of urban and industrial soils with trace metals has been recognized as a major concern at local, regional and global levels due to their implication on human health. In this study, concentrations of aluminum (Al), arsenic (As), beryllium (Be), cadmium (Cd), chromium (Cr), manganese (Mn), nickel (Ni), lead (Pb), tin (Sn), thallium (Tl), vanadium (V) and zinc (Zn) were determined in soil samples collected in Alcalá de Henares (Madrid, Spain) in order to evaluate the annual and seasonal variation in their levels. The results show that the soils of the industrial area have higher metals concentrations than the urban area. Principal component analysis (PCA) revealed that the two principal sources of trace metal contamination, especially Cd, Cu, Pb, and Zn in the urban soils of Alcalá can be attributed to traffic emissions, while As, Ni and Be primarily originated from industrial discharges. The seasonal variation analysis has revealed that the emission sources in the industrial area remain constant with time. However, in urban areas, both emissions and emission pathways significantly increase over time due to ongoing development. Currently, there is no hypothesis that explains the small seasonal fluctuations of trace metals in soils, since there are many factors affecting this. Owing to the fact that urban environments are becoming the human habitat, it would therefore be advisable to monitor metals and metalloids in urban soils because of the potential risks to human health. - Highlights: • Anthropogenic activities may affect the seasonal metal variation in Alcalá's soils. • Weather characteristics may also influence the seasonal metal variation in soils. • Alcalá's continual urban growth may have increased the levels of metals in its soils. • Metal variability in Alcalá's industrial soils might be dependent on their sources. • High soil metal content might make it difficult to identify temporal variation.

54 ENVIRONMENTAL SCIENCES↗

Sampling dynamics for pressurized electrochemical cells

A model describing the gas distribution within a constant pressure electrolysis system and how the distribution impacts electrochemical efficiencies is presented. The primary system of interest is the generation of syngas (CO and H2) associated with the co-electrolysis of H2O and CO2. The model developed for this system takes into account the primary process variables of operation including total system pressure, applied current, the in-flow of reactant gases. From these, and the chemical equilibria within the system, the impact on electrochemically generated gases is presented. Comparing the predicted and measured faradaic efficiency of electrode processes with the expected efficiency from experimental data indicates an offset between the two exists. Methods to minimize and account for the discrepancy are presented with the goal of being able to discern, in a real time manner, degradation of electrode performance. Comparison of the model to experimental data shows a strong correlation between the two with slight variation in experimental data which is attributed to reversible system dynamics such as wetting of the gas diffusion electrode used as the cell cathode.

10 SYNTHETIC FUELS↗

Turbulent, extreme multi-zone model for simulating flux and polarization variability in blazars

The author presents a model for variability of the flux and polarization of blazars in which turbulent plasma flowing at a relativistic speed down a jet crosses a standing conical shock. The shock compresses the plasma and accelerates electrons to energies up to γ{sub max} ≳ 10{sup 4} times their rest-mass energy, with the value of γ{sub max} determined by the direction of the magnetic field relative to the shock front. The turbulence is approximated in a computer code as many cells, each with a uniform magnetic field whose direction is selected randomly. The density of high-energy electrons in the plasma changes randomly with time in a manner consistent with the power spectral density of flux variations derived from observations of blazars. The variations in flux and polarization are therefore caused by continuous noise processes rather than by singular events such as explosive injection of energy at the base of the jet. Sample simulations illustrate the behavior of flux and linear polarization versus time that such a model produces. The variations in γ-ray flux generated by the code are often, but not always, correlated with those at lower frequencies, and many of the flares are sharply peaked. The mean degree of polarization of synchrotron radiation is higher and its timescale of variability shorter toward higher frequencies, while the polarization electric vector sometimes randomly executes apparent rotations. The slope of the spectral energy distribution exhibits sharper breaks than can arise solely from energy losses. All of these results correspond to properties observed in blazars.

79 ASTRONOMY AND ASTROPHYSICS↗

Fission gas bubble identification using MATLAB's image processing toolbox

Automated image processing routines have the potential to aid in the fuel performance evaluation process by eliminating bias in human judgment that may vary from person-to-person or sample-to-sample. This study presents several MATLAB based image analysis routines designed for fission gas void identification in post-irradiation examination of uranium molybdenum (U–Mo) monolithic-type plate fuels. Frequency domain filtration, enlisted as a pre-processing technique, can eliminate artifacts from the image without compromising the critical features of interest. This process is coupled with a bilateral filter, an edge-preserving noise removal technique aimed at preparing the image for optimal segmentation. Adaptive thresholding proved to be the most consistent gray-level feature segmentation technique for U–Mo fuel microstructures. The Sauvola adaptive threshold technique segments the image based on histogram weighting factors in stable contrast regions and local statistics in variable contrast regions. Once all processing is complete, the algorithm outputs the total fission gas void count, the mean void size, and the average porosity. The final results demonstrate an ability to extract fission gas void morphological data faster, more consistently, and at least as accurately as manual segmentation methods. - Highlights: •Automated image processing can aid in the fuel qualification process. •Routines are developed to characterize fission gas bubbles in irradiated U–Mo fuel. •Frequency domain filtration effectively eliminates FIB curtaining artifacts. •Adaptive thresholding proved to be the most accurate segmentation method. •The techniques established are ready to be applied to large scale data extraction testing.

36 MATERIALS SCIENCE↗

Metabolite composition of sinking particles differs from surface suspended particles across a latitudinal transect in the South Atlantic

Abstract Marine sinking particles transport carbon from the surface and bury it in deep‐sea sediments, where it can be sequestered on geologic time scales. The combination of the surface ocean food web that produces these particles and the particle‐associated microbial community that degrades them creates a complex set of variables that control organic matter cycling. We use targeted metabolomics to characterize a suite of small biomolecules, or metabolites, in sinking particles and compare their metabolite composition to that of the suspended particles in the euphotic zone from which they are likely derived. These samples were collected in the South Atlantic subtropical gyre, as well as in the equatorial Atlantic region and the Amazon River plume. The composition of targeted metabolites in the sinking particles was relatively similar throughout the transect, despite the distinct oceanic regions in which they were generated. Metabolites possibly derived from the degradation of nucleic acids and lipids, such as xanthine and glycine betaine, were an increased mole fraction of the targeted metabolites in the sinking particles relative to surface suspended particles, while algal‐derived metabolites like the osmolyte dimethylsulfoniopropionate were a smaller fraction of the observed metabolites on the sinking particles. These compositional changes are shaped both by the removal of metabolites associated with detritus delivered from the surface ocean and by production of metabolites by the sinking particle‐associated microbial communities. Furthermore, they provide a basis for examining the types and quantities of metabolites that may be delivered to the deep sea by sinking particles.

Johnson, Winifred M.↗

Magnetoelastic transition and magnetocaloric effect in induction melted Fe 100-x Rh x bulk alloys with x = 50, 51

Magnetoelastic transitions (METs) in bulk in nearly equiatomic Fe-Rh alloys produced by arc melting may show poor reproducibility related to insufficient chemical homogeneity and presence of impurity phases in variable concentrations. To better understand the synthesis conditions that reliably yield bulk FeRh materials with reproducible MET characteristics, Fe 100-x Rh x alloys with x = 50, 50.5 and 51 at. % were prepared by induction melting and thermal annealing under identical conditions. The fabricated samples were cut into several slices, followed by characterization of METs in each of the slices using isothermal and isofield magnetization measurements, differential scanning calorimetry, and direct measurements of the magnetocaloric effect. All of the slices exhibit METs between the AFM and FM states, but the transitions are abrupt with nearly the same change of magnetization, ΔM, when x = 50.5 and 51, whereas for the x = 50 alloy the transition spreads over a wide temperature interval and ΔM may fluctuate by as much as 10 % from one specimen to another. A comparison of the magnetocaloric responses of x = 50 and 51 materials is presented. The clearly different effect of the magnetic field on the transition in both directions leads to significant differences in the reversibility and maximum values of the magnetic field-induced entropy and adiabatic temperature changes, as well as average hysteresis losses. In terms of reproducibility, our results suggest that induction melting is a more appropriate technique to prepare these binary alloys.

36 MATERIALS SCIENCE↗

Human age and skin physiology shape diversity and abundance of Archaea on skin

The human skin microbiome acts as an important barrier protecting our body from pathogens and other environmental influences. Recent investigations have provided evidence that Archaea are a constant but highly variable component of the human skin microbiome, yet factors that determine their abundance changes are unknown. Here, we tested the hypothesis that the abundance of archaea on human skin is influenced by human age and skin physiology by quantitative PCR of 51 different skin samples taken from human subjects of various age. Our results reveal that archaea are more abundant in human subjects either older than 60 years or younger than 12 years as compared to middle-aged human subjects. These results, together with results obtained from spectroscopy analysis, allowed us gain first insights into a potential link of lower sebum levels and lipid content and thus reduced skin moisture with an increase in archaeal signatures. In conclusion, amplicon sequencing of selected samples revealed the prevalence of specific eury- and mainly thaumarchaeal taxa, represented by a core archaeome of the human skin.

60 APPLIED LIFE SCIENCES↗

Investigation Into LiCl-LiF+Li 2 O as a Low Temperature Electrolyte in Direct Electrolytic Reduction of UO 2

Direct electrolytic reduction (DER) of UO 2 in a binary LiCl-Li2O (1–3 wt%) at 650 °C has been widely reported. The process temperature can be reduced to 550 °C in theory by using a near eutectic ternary LiCl-LiF+Li 2O (∼2 wt%) electrolyte, which will result in substantial reduction in rate of salt vaporization. The feasibility of using the ternary electrolyte for the process was tested via material compatibility testing, electrochemical polarization testing, and controlled potential or current DER experiments. MgO, Pt, and 625 nickel samples were each contacted with the ternary salt for 168 h. Negligible changes to dimensions and mass of the samples were measured, and concentrations of corrosion products in the salt were 102 ppm or less. O2−oxidation was observed to occur at a lower potential than Cl-or F-on a Pt anode. DER of UO2was performed in six trials. Process variables included type of reference electrode, electrochemical control method, type of cathode basket, and electrolyte composition. UO 2conversion ranged from 28.2 to 99.9 % , and current efficiency ranged from 38 to 52%. Overall, results indicate that the use of the ternary salt is feasible for DER.

36 MATERIALS SCIENCE↗

Comparison between the Strength Levels of Baseline Nuclear-Grade Graphite and Graphite Irradiated in AGC-2

This report details the initial comparison of mechanical strength properties between the cylindrical nuclear-grade graphite specimens irradiated in the second Advanced Graphite Creep (AGC-2) experiment with the established baseline, or unirradiated, mechanical properties compiled in the Baseline Graphite Characterization program. The overall comparative analysis will describe the development of an appropriate test protocol for irradiated specimens, the execution of the mechanical tests on the AGC-2 sample population, and will further discuss the data in terms of developing an accurate irradiated property distribution in the limited amount of irradiated data by leveraging the considerably larger property datasets being captured in the Baseline Graphite Characterization program. Integrating information on the inherent variability in nuclear-grade graphite with more complete datasets is one of the goals of the VHTR Graphite Materials program. Between “sister” specimens, or specimens with the same geometry machined from the same sub-block of graphite from which the irradiated AGC specimens were extracted, and the Baseline datasets, a comprehensive body of data will exist that can provide both a direct and indirect indication of the full irradiated property distributions that can be expected of irradiated nuclear-grade graphite while in service in a VHTR system. While the most critical data will remain the actual irradiated property measurements, expansion of this data into accurate distributions based on the inherent variability in graphite properties will be a crucial step in qualifying graphite for nuclear use as a structural material in a VHTR environment.

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗