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At least 1,621 records · Page 90

Fission Product Yields from 232Th, 238U, and 235U Using 14 MeV Neutrons

Neutron-induced fission yield studies using deuterium-tritium fusion-produced 14 MeV neutrons have not yet directly measured fission yields from fission products with half-lives on the order of seconds (far from the line of nuclear stability). Fundamental data of this nature are important for improving and validating the current models of the nuclear fission process. Cyclic neutron activation analysis (CNAA) was performed on three actinide targets–thorium-oxide, depleted uranium metal, and highly enriched uranium metal–at the University of Michigan's Neutron Science Laboratory (UM-NSL) using a pneumatic system and Thermo-Scientific D711 accelerator-based fusion neutron generator. This was done to measure the fission yields of short-lived fission products and to examine the differences between the delayed fission product signatures of the three actinides. The measured data were compared against previously published results for 89Kr, -90, and -92 and 138Xe, -139, and -140. The average percent deviation of the measured values from the Evaluated Nuclear Data Files VII.1 (ENDF/B-VII.1) for thorium, depleted-uranium, and highly-enriched uranium were -10.2%, 4.5%, and -12.9%, respectively. In addition to the measurements of the six known fission products, 23 new fission yield measurements from 84As to 146La are presented.

Pierson, Bruce D.↗

Impact of electrode porosity architecture on electrochemical performances of 1 mm-thick LiFePO4 binder-free Li-ion electrodes fabricated by Spark Plasma Sintering

Thick electrodes with high active material loadings have been intensively studied over the last couple of decades in pursuit of achieving high energy density systems. To optimize and enhance the electrochemical performance of such electrodes, one has to control the pore morphology by, for example, varying the pore size and shape, and the level of porosity. In the present work, the fabrication of thick binder-free LiFePO4 (LFP) electrodes with two different pore sizes (12 and 20 mu m) and porosities (21 vol% and 44 vol%) using Spark Plasma Sintering (SPS) and templating approach is reported. The well-controlled porous architecture inside the thick electrodes is realized by fine-tuning experimental parameters. The impact of porosity architecture on electrochemical performance is quantified and correlated with the 3D tortuosity values determined from both micro-computed tomography and electrochemical impedance-based experimental methods. Based on the micro-computed tomography data analysis, estimated tortuosity values along X, Y, and Z axes reveal an anisotropic effect perpendicularly to the SPS compression axis (Z-direction). This is particularly profoundly observed in the samples with larger pores (20 mu m). The correlation between morphological properties and the rate capability performance is established indicating that the capacity loss happens mainly due to the Li-ion diffusion limitations.

Cathode material↗

Machine-learning-informed scattering correlation analysis of sheared colloids

We have carried out theoretical analysis, Monte Carlo simulations and machine-learning analysis to quantify microscopic rearrangements of dilute dispersions of spherical colloidal particles from coherent scattering intensity. Both monodisperse and polydisperse dispersions of colloids were created and underwent a rearrangement consisting of an affine simple shear and non-affine rearrangement using the Monte Carlo method. We calculated the coherent scattering intensity of the dispersions and the correlation function of intensity before and after the rearrangement and generated a large data set of angular correlation functions for varying system parameters, including number density, polydispersity, shear strain and non-affine rearrangement. Singular value decomposition of the data set shows the feasibility of machine-learning inversion from the correlation function for the polydispersity, shear strain and non-affine rearrangement using only three parameters. A Gaussian process regressor is then trained on the data set and can retrieve the affine shear strain, non-affine rearrangement and polydispersity with relative errors of 3%, 1% and 6%, respectively. Altogether, our model provides a framework for quantitative studies of both steady and non-steady microscopic dynamics of colloidal dispersions using coherent scattering methods.

Gaussian process regression↗

Implications from ${B\to K^*\ell^+\ell^-}$ observables using $3 \text{fb}^{-1}$ of LHCb data

The decay mode${B\to K^*\ell^+\ell^-}$ is regarded as one of the attractive mode to look for physics beyond standard model (SM) due to the measurement of large number of observables in experiments. Starting with the most general parametric form of the decay amplitude within SM, two differ- ent analyses have been carried out. First we show how recent LHCb data can be used without any approximations to extract theoretical parameters describing the decay. We find significant discrepancies in the form factor values obtained from experimental data when compared with theoretical expectations in several dilepton invariant mass squared (q 2 ) bins. We emphasize that the discrepancy observed in certain variables cannot arise due to resonances and non-factorizable contributions from charm loops. Secondly, the same model independent framework has been implemented in the maximum q 2 limit to highlight strong evidence of right-handed currents, which are absent in the SM. The conclusions derived are free from hadronic corrections. Our approach differs from other approaches that probe new physics at low q 2 as it does not require estimates of hadronic parameters but relies instead on heavy quark symmetries that are reliable at the maximum q 2 kinematic endpoint.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

A two-dimensional, iterative solution for the jet flap

A solution is presented for the jet-flapped wing in two dimensions. The main flow is assumed to be inviscid and incompressible. The flow inside the jet is considered irrotational and the upper and lower boundaries between the jet and free stream are assumed to behave as vortex sheets which allow no mixing. The solution is found to be in satisfactory agreement with two dimensional experimental results and other theoretical work for intermediate values of momentum coefficient, but the regions of agreement vary with jet exit angle. At small values of momentum coefficient, the trajectory for the jet, as computed by this method, has more penetration than that of other available data, while at high values of moment coefficient this solution results in less penetration of the jet into the main flow.

Herold, A. C.↗

Coordinated ionospheric and magnetospheric observations from the ISIS 2 satellite by the ISIS 2 experimenters. Volume 1: Optical auroral images and related direct measurements

A representative set of data from ISIS 2 covering a range of operating modes and geophysical conditions is presented. The data show the typical values and range of ionospheric and magnetospheric characteristics, as viewed from 1400 km with the ISIS 2 instruments. The definition of each data set depends partly on geophysical parameters and partly on satellite operating mode. Preceding the data set is a description of the organizational parameters and a review of the objectives and general characteristics of the data set. The data are shown as a selection from 12 different data formats. Each data has a different selection of formats, but uniformity of a given format selection is preserved throughout each data set.

Murphree, J. S.↗

Feasibility Study on the Use of On-line Multivariate Statistical Process Control for Safeguards Applications in Natural Uranium Conversion Plants

The objective of this work was to determine the feasibility of using on-line multivariate statistical process control (MSPC) for safeguards applications in natural uranium conversion plants. Multivariate statistical process control is commonly used throughout industry for the detection of faults. For safeguards applications in uranium conversion plants, faults could include the diversion of intermediate products such as uranium dioxide, uranium tetrafluoride, and uranium hexafluoride. This study was limited to a 100 metric ton of uranium (MTU) per year natural uranium conversion plant (NUCP) using the wet solvent extraction method for the purification of uranium ore concentrate. A key component in the multivariate statistical methodology is the Principal Component Analysis (PCA) approach for the analysis of data, development of the base case model, and evaluation of future operations. The PCA approach was implemented through the use of singular value decomposition of the data matrix where the data matrix represents normal operation of the plant. Component mole balances were used to model each of the process units in the NUCP. However, this approach could be applied to any data set. The monitoring framework developed in this research could be used to determine whether or not a diversion of material has occurred at an NUCP as part of an International Atomic Energy Agency (IAEA) safeguards system. This approach can be used to identify the key monitoring locations, as well as locations where monitoring is unimportant. Detection limits at the key monitoring locations can also be established using this technique. Several faulty scenarios were developed to test the monitoring framework after the base case or normal operating conditions of the PCA model were established. In all of the scenarios, the monitoring framework was able to detect the fault. Overall this study was successful at meeting the stated objective.

Ladd-Lively, Jennifer L↗

TU-D-201-04: Veracity of Data Elements in Radiation Oncology Incident Learning Systems

Purpose: Incident learning systems encompass volumes, varieties, values, and velocities of underlying data elements consistent with the V’s of big data. Veracity, the 5th V however exists only if there is high inter-rater reliability (IRR) within the data elements. The purpose of this work was to assess IRR in the nationally deployed RO-ILS: Radiation Oncology-Incident Learning System (R) sponsored by the American Society for Radiation Oncology (ASTRO) and the American Association of Physicists in Medicine (AAPM). Methods: Ten incident reports covering a wide range of scenarios were created in standardized narrative and video formats and disseminated to 67 volunteers of multiple disciplines from 26 institutions along with two published narratives from the International Commission of Radiological Protection to assess IRR on a nationally representative level. The volunteers were instructed to independently enter the associated data elements in a test version of RO-ILS over a 3-week period. All responses were aggregated into a spreadsheet to assess IRR using free-marginal kappa metrics. Results: 48 volunteers from 21 institutions completed all reports in the study period. The average kappa score for all raters across all critical data elements was 0.659 [range 0.326–1.000]. Statistically significant differences (p <0.05) were noted between reporters of different disciplines and raters with varying levels of experience. Kappa scores were high for event classification (0.781) and contributory factors (0.777) and low for likelihood-of-harm (0.326). IRR was highest among AAPM-ASTRO members (0.672) and lowest among trainees (0.463). Conclusion: A moderate-to-substantial level of IRR in RO-ILS was noted in this study. Although the number of events reviewed in this study was small, opportunities for improving the taxonomy for the lower scoring data elements as well as specific educational targets for training were identified by assessing data veracity quantitatively. This is expected to improve the quality of the data garnered from RO-ILS.

60 APPLIED LIFE SCIENCES↗

SERVIR: Cross-Comparison of Carbon Emission Estimates Based on Variable Land Use Land Cover Changes within SERVIR Focus Regions

Deforestation in the tropics contributes approximately one-fifth of the annual global greenhouse gas (GHG) emissions. In an effort to reduce GHG emissions, SERVIR - a joint USAID and NASA initiative - is currently implementing the SERVIR CArbon Pilot (S-CAP) activity. By developing a comprehensive CO2 tracking system in Google Earth Engine based on both remotely sensed data and in situ observations, S-CAP aims to build capacity within the SERVIR regional hubs to improve decision making and local monitoring efforts surrounding GHG emissions. The S-CAP estimations are being completed throughout 11 pilot countries within the SERVIR regions of Asia, Africa, and the Americas to integrate partner contributions and local input into the development process. These emission estimate calculations use country-level REDD+ FREL reported values, global remotely sensed data (e.g. Global Forest Watch) and regional datasets and are completed using the IPCC Guidelines for National Greenhouse Gas Inventories. From the S-CAP activity thus far, country CO2 estimations had varied differences, ranging from 56% to 197% between their lowest and highest estimates. The results from this study show that CO2 emission estimates can differ greatly depending on the land cover data sets used as well as the biomass values, and how a comprehensive database is essential in understanding the full range of impacts that land cover change has in these regions. Using this ensemble approach, SERVIR hubs can better select the most appropriate datasets available for estimating emissions.

Carbon Emission↗

ESS-DIVE Unoccupied Aerial Systems (UAS) Reporting Format v1

Here we present documentation of the ESS-DIVE reporting format for Unoccupied Aerial System (UAS) data and metadata. This reporting format provides guidance to data contributors on how to store data to maximize their discoverability, facilitate their efficient reuse, and add value to individual datasets. For data users, the reporting format will better allow data repositories to optimize data search and extraction, and more readily integrate similar data into harmonized synthesis products. The reporting format provides templates and guidance for the reporting of metadata for UAS experimental campaigns, individual flights, platform and sensor description. To improve data access and discoverability, the reporting format proposes a data description scheme of Levels based on the degree of processing, where Level 0 includes raw data, through to Level 3 being derived data end products. A range of examples of data types for each Level are given, with suggested file naming schemes. The reporting format presented here is intended to form a foundation for future development that will accommodate new UAS technologies and approaches to data access and use in the future. The reporting format documentation is maintained and updated on the ESS-DIVE Community Space GitHub at https://github.com/ess-dive-community/essdive-uas. This data package is the first published version of this reporting format, and comprises a zip file of the complete content of https://github.com/ess-dive-community/essdive-uas v1.0. The zip contains the reporting format description, instructions and variable definitions in GitHub markdown language (*.md) and metadata templates in csv format. The reporting format is designed to be compatible with other ESS-DIVE formats, and it is specifically recommended that this reporting format be used in conjunction with the File-level metadata (FLMD) and comma separated values (csv) reporting formats for submission to the ESS-DIVE repository.

54 ENVIRONMENTAL SCIENCES↗

Earth Observing-1 Advanced Land Imager Flight Performance Assessment: Absolute Radiometry and Stability During the First Year

The absolute radiometry of the Advanced Land Imager during the first year on orbit (November 21,2000 - November 21, 2001) is presented. Results derived from solar, lunar, ground truth, and internal reference lamp measurements are presented. An 18% drop in the radiometric response of the Band 1p data since preflight calibration at Lincoln Laboratory is observed using all techniques. This decrease cannot be accounted for by preflight calibration errors, stray light, or contamination of the focal plane. A slight drooping of the VNIR response toward the blue and a 5-12% increase in the Band 5 response is also apparent in all the data. Radiometric response correction factors have been calculated and preflight calibration coefficients have been updated in order to provide +/- 5% agreement between the measured solar, lunar, and ground truth data and the expected values. The radiometric stability of the ALI during the first year of operation is also presented for each spectral band. Internal reference lamp data indicate the focal plane has been stable to within 1% for bands 1p, 1, 2, 5p, 5, 7, pan and 3% for Bands 3,4, 4p since launch. Solar, lunar, and ground truth measurements indicate the optical train and solar diffuser of the instrument has been stable to within 1% since initial measurements on orbit in late December 2000.

Mendenhall, J. A.↗

A National Framework for Energy Audit Ordinances

A handful of U.S. cities have begun to incorporate energy audits into their building energy performance policies. Cities are beginning to recognize an opportunity to use several information tools to bring to real estate markets both motivation to improve efficiency and actionable pointers on how to improve. Care is necessary to combine such tools as operational ratings, energy audits, asset ratings, and building retro-commissioning in an effective policy regime that maximizes market impact. In this paper, the authors focus on energy audits and consider both the needs of the policies' implementers in local governments and the emerging standards and federal tools to improve data collection and practitioner engagement. Over the past two years, we have compared several related data formats such as New York City's existing audit reporting spreadsheet, ASHRAE guidance on building energy auditing, and the DOE Building Energy Asset Score, to identify a possible set of required and optional fields for energy audit reporting programs. Doing so revealed tensions between the ease of data collection and the value of more detailed information, which had implications for the effort and qualifications needed to complete the energy audit. The resulting list of data fields is now feeding back into the regulatory process in several cities currently working on implementing or developing audit policies. Using complementary policies and standardized tools for data transmission, the next generation of policies and programs will be tailored to local building stock and can more effectively target improvement opportunities through each building's life.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

Nuclear Data Covariances and Sampling

In this report, we present an overview of the task of producing sample nuclear data sets for the purpose of exploring the effects of nuclear data uncertainties on physics simulations. These sample data sets (or, as we sometimes call them variations) are produced based on uncertainties specified in the ENDF/B-VIII nuclear data library, although the principles discussed here apply to sampling based on similar libraries, such as JENDL. The uncertainties in ENDF and similar libraries are given in the form of mean values (a mean vector) and a covariance matrix. The components of the mean vector are what are normally thought of as the values of the nuclear data (cross sections, $\bar{v}$, the prompt fission neutron spectrum, etc.) and the covariance matrix contains the information about the uncertainties in these values and correlations between them, including correlations across different energies in a single channel and correlations across different channels.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗

Visualizing 2D Probability Distributions from Satellite Image-Derived Data

Creating maps of biophysical and geophysical variables using Earth Observing System (EOS) satellite image data is an important component of Earth science. These 2D maps have a single value at every location and standard techniques are used to visualize them. Current tools fall short, however, when it is necessary to describe a distribution of values at each location. Distributions may represent a frequency of occurrence over time, frequency of occurrence from multiple runs of an ensemble forecast or possible values from an uncertainty model. 'Distribution data sets' are described, then a case study is presented to visualize such 2D distributions. Distribution data sets are different from multivariate data sets in the sense that the values are for a single variable instead of multiple variables. Our case study data consists of multiple realizations of percent forest cover, generated using a geostatistical technique that combines ground measurements and satellite imagery to model uncertainty about forest cover. We present several approaches for analyzing and visualizing such data sets. The first is a pixel-wise analysis of the probability density functions for the 2D image while the second is an analysis of features identified within the image. Such pixel-wise and feature-wise views will give Earth scientists a more complete understanding of distribution data sets.

Kao, David↗

The properties of clusters in the gas phase. IV - Complexes of H2O and HNOx clustering on NOx/-/

Thermodynamic quantities for the gas-phase clustering equilibria of NO2(-) and NO3(-) were determined with high-pressure mass spectrometry. A comparison of values of the free energy of hydration derived from the data shows good agreement with formerly reported values at 296 K. New data for larger NO2(-) and NO3(-) hydrates as well as NO2(-)(HNO2)n were obtained in this study. To aid in understanding the bonding and stability of the hydrates of nitrite and nitrate ions, CNDO/2 calculations were performed, and the results are discussed. A correlation between the aqueous-phase total hydration enthalpy of a single ion and its gas-phase hydration enthalpy was obtained. Atmospheric implications of the data are also briefly discussed.

Lee, N.↗

SPRUCE Root Production Assessed with Manual Minirhizotrons Resolved to Plant Functional Type, 2015-2021

This dataset contains raw root length and diameter for individual roots and estimated root population production measurements from the Spruce and Peatland Responses Under Changing Environments (SPRUCE) experimental site within the Marcell Experimental Forest in northern Minnesota, USA. Measurements started at the beginning of whole ecosystem warming manipulations in 2015 through 2021 (2015-05-26 to 2021-09-01). Root morphology and estimated production were quantified throughout the peat profile with manual minirhizotrons deployed within SPRUCE plots. Images were processed using commercial software to quantify the length and diameter of individual roots. Roots were visually assigned to a plant functional type (PFT) of either (ericaceous) shrub, herb (sedges and Maianthemum trifolium), or tree (Larix laricina, Picea mariana) based on expert opinion. The biomass of individual roots was estimated using PFT-specific allometric equations (Iversen et al., 2018). Production per day was estimated as the length of new roots produced between imaging sessions, divided by the number of days between imaging sessions. These values were placed on a m2 aboveground area basis and scaled to a standard depth of 1m (roots are not evenly distributed with depth, do not interpret value as being on a m3 basis). Maximum and average (weighted by production length) depth of each PFT were also estimated within each minirhizotron tube. Annual production was interpolated as the average of four methods to scale these data (see Weber et al, 2026). Standing crop of roots was estimated for each tube as the maximum visible amount (both length and mass) of roots of that PFT for that year. These data expand the ability of researchers to accurately estimate the belowground dynamics of peatland vegetation, as well as the role that fine roots may play in impacting the fluxes of carbon within peatlands. This dataset contains three data files in comma-separate values (*.csv) format. This dataset contains one data file in comma-separate values (.csv) format. Additional metadata are provided: three data dictionaries and a file-level metadata file in comma-separate values (.csv) format and a user guide in PDF (*.pdf) format.

54 ENVIRONMENTAL SCIENCES↗

Neutrino masses and cosmology with Lyman-alpha forest power spectrum

We present constraints on neutrino masses, the primordial fluctuation spectrum from inflation, and other parameters of the ΛCDM model, using the one-dimensional Lyα-forest power spectrum measured by [1] from the Baryon Oscillation Spectroscopic Survey (BOSS) of the Sloan Digital Sky Survey (SDSS-III), complemented by Planck 2015 cosmic microwave background (CMB) data and other cosmological probes. This paper improves on the previous analysis by [2] by using a more powerful set of calibrating hydrodynamical simulations that reduces uncertainties associated with resolution and box size, by adopting a more flexible set of nuisance parameters for describing the evolution of the intergalactic medium, by including additional freedom to account for systematic uncertainties, and by using Planck 2015 constraints in place of Planck 2013. Fitting Lyα data alone leads to cosmological parameters in excellent agreement with the values derived independently from CMB data, except for a weak tension on the scalar index n{sub s}. Combining BOSS Lyα with Planck CMB constrains the sum of neutrino masses to ∑ m{sub ν} < 0.12 eV (95% C.L.) including all identified systematic uncertainties, tighter than our previous limit (0.15 eV) and more robust. Adding Lyα data to CMB data reduces the uncertainties on the optical depth to reionization τ, through the correlation of τ with σ{sub 8}. Similarly, correlations between cosmological parameters help in constraining the tensor-to-scalar ratio of primordial fluctuations r. The tension on n{sub s} can be accommodated by allowing for a running dn{sub s}/d ln k. Allowing running as a free parameter in the fits does not change the limit on ∑ m{sub ν}. We discuss possible interpretations of these results in the context of slow-roll inflation.

79 ASTRONOMY AND ASTROPHYSICS↗

Estimation of longitudinal aerodynamic coefficients and comparison with wind-tunnel values

Some recent experience at Ames Research Center in the estimation of aerodynamic coefficients for the Lear-Jet and the Augmentor Wing Jet STOL Research Aircraft is reviewed. The coefficients estimated from flight data are compared with values based on large-scale wind-tunnel tests. The results obtained by the regression and quasilinearization identification techniques are also compared. The regression method generally provides the lower standard deviation in the coefficient estimates and provides the better fit to the wind-tunnel values. The addition of nonlinear terms in the aerodynamic equations decreases the difference between the estimated and measured time histories but also increases the standard deviation in the estimated coefficient values.

Wingrove, R. C.↗