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At least 1,225 records · Page 68

Explanation of the seasonal variation of cosmic multiple muon events observed with the NOvA Near Detector

The flux of cosmic ray muons at the Earth’s surface exhibits seasonal variations due to changes in the temperature of the atmosphere affecting the production and decay of mesons in the upper atmosphere. Using 1473 live days of data collected by the NuMI Off-axis 𝜈 𝑒 Appearance (NOvA) Near Detector during 2018–2022, we studied the seasonal pattern in the multiple-muon event rate. The data confirm an anticorrelation between the multiple-muon event rate and effective atmospheric temperature, consistent across all the years of data. Previous analyses from MINOS and NOvA saw a similar anticorrelation but did not include an explanation. We find that this anticorrelation is driven by altitude–geometry effects as the average muon production height changes with the season. This has been studied with a CORSIKA cosmic ray simulation package by varying atmospheric parameters, and provides an explanation to a longstanding discrepancy between the seasonal phases of single and multiple-muon events.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

Observation of Enhanced Long-Range Elliptic Anisotropies Inside High-Multiplicity Jets in p p Collisions at s = 13 TeV

A search for collective effects inside jets produced in proton-proton collisions is performed via correlation measurements of charged particles using the CMS detector at the CERN LHC. The analysis uses data collected at a center-of-mass energy of s = 13 TeV , corresponding to an integrated luminosity of 138 fb − 1 . Jets are reconstructed with the anti- k T algorithm with a distance parameter of 0.8 and are required to have transverse momentum greater than 550 GeV and pseudorapidity | η jet | < 1.6 . Two-particle correlations among the charged particles within the jets are studied as functions of the particles’ azimuthal angle and pseudorapidity separations ( Δ ϕ * and Δ η * ) in a jet coordinate basis, where particles’ η * , ϕ * are defined relative to the direction of the jet. The correlation functions are studied in classes of in-jet charged-particle multiplicity up to N ch j ≈ 100 . Fourier harmonics are extracted from long-range azimuthal correlation functions to characterize azimuthal anisotropy for | Δ η * | > 2 . For low- N ch j jets, the long-range elliptic anisotropic harmonic, v 2 * , is observed to decrease with N ch j . This trend is well described by Monte Carlo event generators. However, a rising trend for v 2 * emerges at N ch j ≳ 80 , hinting at a possible onset of collective behavior, which is not reproduced by the models tested. This observation yields new insights into the dynamics of jet evolution in the vacuum. © 2024 CERN, for the CMS Collaboration 2024 CERN

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

Generic Data Display (GD2)

SAND2023-11967O Generic Data Display (GD2) is a real-time data visualization application that can display user-defined input data. The open-source software is comprised of a back end system written in Python, and a front end user interface written in JavaScript. The back end system collects data from a variety of input sources, such as message queue, HTTP, XML, JSON, and others. The front end displays data in an Open MCT web interface, and users can configure the system by providing JSON formatted configuration files. Sandia National Laboratories is a multimission laboratory managed and operated by National Technology & Engineering Solutions of Sandia, LLC, a wholly owned subsidiary of Honeywell International Inc., for the U.S. Department of Energy’s National Nuclear Security Administration under contract DE-NA0003525.

Figueroa, Benjamin↗

Laboratory Drilling Test Data of PDC bits with Sierra White Granite Rock

This file contains unprocessed drilling data tests on Sierra White Granite (SWG) using two new PDC bits. The tests were conducted at Sandia National Laboratories (SNL) in the Hard Rock Drilling Facility (HRDF). The collected data includes ROP data at rotational speeds of 80, 120, and 160 RPMs, with incremental weight on bit (WOB) up to 5100 lbs. The diameter of the 4-bladed and 5-bladed PDC bits was 3 3/4" and supplied by National Oilwell Varco (NOV). Five tests modes were conducted for both bits, which are as follow: (1) Rigid configuration, with no vibration compliance (2) Flywheel configuration (3) Torsional compliance configuration (4) Axial Compliance configuration (5) Combined Axial and Torsional compliance configuration Note: the WOB and torque in the drilling data should be calibrated by zeroing the WOB and torque when the drill bit tags the rock sample.

15 GEOTHERMAL ENERGY↗

WHOLESCALE: Microseismic Event Catalog for San Emidio, Nevada 2022

This submission includes a high-precision seismic event catalog estimated from seismic data collected at San Emidio, Nevada from April to May 2022. The catalog lists the precise time, location, and magnitude of microseismic events recorded during this period. Both the seismic data and microseismic event catalog were produced as part of the Water & Hole Observations Leverage Effective Stress Calculations and Lessen Expenses (WHOLESCALE) project. Attached here are the microseismic event catalog, a link to the raw seismic data, and a detailed description of methods used to create the catalog.

15 GEOTHERMAL ENERGY↗

1990 Seattle Household Travel Survey Wave 2

The Seattle Household Travel Survey Wave 2, conducted in 1990, was the second wave in a 10-part longitudinal panel survey of the travel patterns of households in the Puget Sound region of Washington state. The survey series was initiated in 1989 by the Puget Sound Regional Council. Data collection for the second wave took place in the fall of 1990, which included full interviews and travel diaries, as well as some panel refreshment. Demographic and work trip data updates, but no travel diaries, were gathered for 2,023 households in four counties in the Seattle area. The survey relied on the willingness of study area residents to 1) provide demographic information about their household, its members, and its vehicles; 2) document all travel for each household member, aged 15 years or older, for an assigned two-day period; and 3) agree to participate in additional survey waves. After an initial telephone screening, survey participants received mailed travel diaries to aid in documenting travel information for the two-day assessment period. Respondents were instructed to record their mode of transportation, trip purpose, number of passengers, departure and arrival times, ride fare, and parking costs. Demographic information for this study includes age, gender, education, employment status, and household income.

1Hz data↗

Soil carbon, nitrogen, and ice content data (2014-2018) at Happy Valley and Sagwon Hills in Northern Alaska, United States

This dataset contains three data files from soil data collected by sampling soil cores and pits across a toposequence on two hillslopes in permafrost affected soils in Northern Alaska, USA. Soil cores and profiles were excavated to 3m or until auger refusal. Samples were collected by genetic soil horizons for laboratory analysis and organized into complete soil profiles ordered depth. Soil carbon, nitrogen, and ice stocks (stocks_by_core.csv) were calculated from the core dataset . Data for mean values by depth increments (20,50,100,150,200 cm) of total soc, total nitrogen, bulk density, and ice content were determined and made available in this dataset (soc-tn-bd-ice-slab_tables.csv). Stocks by site are included in a separate file (stocks_by_site.csv). Each of these three files also has an associated data dictionary file (stocks_by_core_dd.csv, soc-tn-bd-ice-slab_tables_dd.csv, stocks_by_site_dd.csv). Finally, an FLMD file is also included (FLMD_Happy_Valley_Sagwon.csv).

54 ENVIRONMENTAL SCIENCES↗

Arctic shrub and Eriophorum leaf and root decomposition, northern Alaska, 2017-2018

This data package contains litter decomposition data collected from 170 plots of rapidly expanding shrub genera (Alnus, Betula, and Salix) and a widespread sedge (Eriophorum vaginatum) along a latitudinal and temperature gradient in northern Alaska. These data were produced from a litter bag experiment that took place from July 2017 to July 2018 and include mass loss and nitrogen loss decomposition metrics for both leaf and root litters. These raw data support a submitted manuscript that examines the variability in decomposition between shrub and graminoid leaf and root litters across a 1-year experiment across the graminoid-dominated Arctic tundra and reveals how deciduous shrub expansion affects litter decomposition in tundra ecosystems. Data are presented by site (n=5) and patch (shrub or sedge plot) in csv files. The site and plot location data and environmental measurement data are provided in Fraterrigo and Chen (2020). Additional methods regarding plot distribution and environmental measurements are in Chen et al. (2020) and Fraterrigo et al. (2024).

54 ENVIRONMENTAL SCIENCES↗

Data from a four-day long microcosm experiment addressing the destabilization of artificial mineral-associated organic matter by model root exudates embedded in a soil matrix from the Rocky Mountain Biological Laboratory (Gothic, CO, USA), 2019

This dataset provides data collected during a four-day long laboratory soil microcosm experiment testing the efficacy of root exudate-driven mineral-associated organic matter destabilization. This dataset contains four data files in comma-separate values (*.csv). The files provide the metadata and the experimental results on microbial respiration, MAOM-derived respiration, and sequential mineral-extractions. This data was used to produce the figures in Bölscher et al., 2026. The results of the experiment can be found in the open access article Bölscher et al., 2026 (https://doi.org/10.1016/j.soilbio.2026.110276). Abstract: Mineral-associated organic matter (MAOM) is often considered stable, but root exudates can destabilize MAOM via various pathways. Theory and model system studies suggest that direct MAOM destabilization by strong ligands, like oxalic acid, or reducing agents, like catechol, is more effective than indirect, microbial-mediated MAOM destabilization, stimulated by less reactive compounds like glucose. Here, we demonstrate that the presence of a soil matrix alters the efficacy of exudate-driven MAOM destabilization pathways. Glucose and catechol destabilized significantly greater amounts of MAOM from ferrihydrite and aluminum hydroxide (Al (OH)3) embedded in a soil matrix than oxalic acid. Our findings indicate that indirect, microbial-mediated MAOM destabilization may play a larger role than direct MAOM destabilization in soil environments.

Destabilization↗

Alaska North Slope 2018 Hydrate-01 Stratigraphic Test Well: Technical Results

The Hydrate-01 Stratigraphic Test Well was drilled in December 2018 to confirm that a seismically-identified location within the western Prudhoe Bay Unit might be suitable for extended-duration scientific production testing. The well featured the acquisition of a full suite of logging-while-drilling data, collection of side-wall pressure cores, and installation of distributed temperature and distributed acoustic sensor (DTS, DAS) fiber-optic cables. Evaluation of the logging-while-drilling data confirms gas hydrate is present at high saturation in two target sands of high reservoir quality. Acquired logs and samples enable critical petrophysical information to be compiled for input into production models. The well tested two primary targets: the deeper Unit B is highly favorable due to optimal reservoir temperature and minimal observed risk for direct communication with permeable, hydrate-free water-bearing zones. The shallower Unit D provides a secondary target and opportunity to

Boswell, Ray↗

Using Cosmic Ray Muons to Assess Geological Characteristics in the Subsurface

Cosmic rays are energetic nuclei and elementary particles that originate from stars and intergalactic events. The interaction of these particles with the upper atmosphere produces a wide range of secondary particles that reach the surface of the earth, of which muons are the most prominent. With enough energy, muons can travel up to a few kilometers beneath the surface of the earth before being stopped completely. The terrestrial muon flux profile and associated zenith angle can be utilized to determine geological characteristics of a location (e.g., rock overburden and density) without having to use conventional methods such as boreholes. This work uses a low-power plastic scintillator-based muon detection system as a prototype for this non-destructive geological assay methodology. Four custom designed 102 cm x 51 cm x 5 cm plastic scintillation panels are used to realize two orthogonal detection planes. Optical photons from each scintillation panel are read using OnSemi J-Series 4x4 silicon photomultiplier (SiPM) arrays in conjunction with preamplifiers. Simultaneous triggers between detectors from two planes indicate a coincidence event which is recorded using the QuarkNet data acquisition system (DAQ) from Fermi National Accelerator Laboratory. A custom detector holder was designed to securely mount the detection system and rotate the panels along the zenith to collect data at variable angles. In order to quantify the systematic uncertainties associated with the detector, such as energy depositions and angular resolution of the detector design, a Monte Carlo (MC) simulation using Geant4 is being developed. Cosmic ray flux prediction will be included in the project by adding the CORSIKA MC code to the simulation toolchain. Simulated and experimental data will drive the development and validation of a reconstruction algorithm that, upon completion, is expected to predict average overburden and rock density. Extended detector exposure to muons can be used as a means to understand changes in the surrounding environment like rock porosity. On the experimental front, muons will initially be measured at the surface, establishing the baseline flux. This is followed by recording the muon flux at variable depths and zenith angles, where the data will be used by the reconstruction algorithm to predict the overburden. The result will be benchmarked against geological surveys. The measured flux data will also be used to benchmark independent and established models. Successful proof-of-concept demonstration of this technology can open doors for long term non-invasive geological monitoring. The detector design, experimental methodology, and the benchmarking efforts are detailed in this work.

Gadey, Harish Reddy↗

A Plan to Qualify New Fuel for the High Flux Isotope Reactor for Material Minimization

The High Flux Isotope Reactor (HFIR) at Oak Ridge National Laboratory (ORNL) is one of five high power research reactors the Office of Material Management and Minimization (M3) Program, Office of Conversion is working to convert from using highly enriched uranium (HEU) fuel to using low-enriched uranium (LEU) fuel. This effort stems from the primary objective within the U.S. Department of Energy (DOE) National Nuclear Security Administration (NNSA) to achieve permanent threat reduction by minimizing, and when possible, eliminating weapon-usable nuclear material around the world. Under M3’s Office of Conversion, the U.S. High Performance Research Reactor (USHPRR) Project is pursuing fuel qualification and licensing of LEU fuels to support the high-performance reactors. All high-performance reactors except HFIR will be converted to LEU monolithic uranium-molybdenum alloy fuel. HFIR will be evaluated for conversion to LEU using a uranium silicide fuel, namely, U3Si2-Al dispersion fuel. The mission of the USHPRR Project is to develop the technology needed to reduce, and eventually eliminate, worldwide use of HEU in civilian applications. The goal is to develop the technical means needed to use low enriched uranium (LEU) instead of HEU fuel in research and test reactors without significant penalties in performance, economics, or safety of the reactors. The USHPRR Project has four major elements, called Pillars: Fuel Qualification (FQ) managed at Idaho National Laboratory (INL), Fuel Fabrication (FF) managed at Pacific Northwest National Laboratory (PNNL), Reactor Conversion (RC) managed at Argonne National Laboratory (Argonne), and Cross-Cutting (CC) managed at Savannah River National Laboratory (SRNL). FQ is responsible for the qualification of the fuel type. RC is responsible for supporting reactor conversion analysis and overseeing licensing submittals leading to conversions of domestic reactors to LEU fuel. For the FQ effort, FQ (INL) worked in collaboration with RC (Argonne) and ORNL to develop the plan for the uranium silicide fuel qualification for HFIR. The resulting HFIR Fuel Qualification Plan provides the general approach for the USHPRR team to move the selected uranium silicide fuel design for HFIR conversion through qualification. Authorization and use in HFIR will be approved through the DOE’s Office of Science. Uranium silicide fuel was previously qualified in NUREG-1313 at an approximate maximum heat flux of 1.4 MW/m2 and a maximum fuel section temperature of about 130°C. In addition to the different regulator process utilized by DOE, these upper limits will be exceeded in HFIR; therefore, further testing will be necessary to ensure the fuel can meet HFIR qualification requirements. The HFIR fuel loading may exceed 4.8 gU/cm3 which was determined in the NUREG-1313 safety evaluation to be acceptable for use in non-power NRC-licensed reactors provided there exist no other safety considerations. In addition, the uranium silicide fuel will need to be qualified in a HFIR-specific design. This plan includes the currently available information from the USHPRR Project Functions and Requirements document and expands these requirements to ensure that planned tests have traceable results providing evidence that the requirements have been met. Data collection methods are discussed as well as the process to show that the requirements have been met. This document is designed to provide a pathway for researchers to obtain data necessary and at the appropriate quality level for HFIR fuel qualification

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗

A Plan to Qualify New Fuel for the High Flux Isotope Reactor for Material Minimization

The High Flux Isotope Reactor (HFIR) at Oak Ridge National Laboratory (ORNL) is one of five high power research reactors the Office of Material Management and Minimization (M3) Program, Office of Conversion is working to convert from using highly enriched uranium (HEU) fuel to using low-enriched uranium (LEU) fuel. This effort stems from the primary objective within the U.S. Department of Energy (DOE) National Nuclear Security Administration (NNSA) to achieve permanent threat reduction by minimizing, and when possible, eliminating weapon-usable nuclear material around the world. Under M3’s Office of Conversion, the U.S. High Performance Research Reactor (USHPRR) Project is pursuing fuel qualification and licensing of the high-performance reactors to operate with LEU fuels. All high-performance reactors except HFIR will be converted to LEU monolithic uranium-molybdenum alloy fuel. HFIR will be evaluated for conversion to LEU using a uranium silicide fuel, namely, U3Si2-Al dispersion fuel.The mission of the USHPRR Project is to develop the technology needed to reduce, and eventually eliminate, worldwide use of HEU in civilian applications. The goal is to develop the technical means needed to use low enriched uranium (LEU) instead of HEU fuel in research and test reactors without significant penalties in performance, economics, or safety of the reactors. The USHPRR Project has four major elements, called Pillars: Fuel Qualification (FQ) managed at Idaho National Laboratory (INL), Fuel Fabrication (FF) managed at Pacific Northwest National Laboratory (PNNL), Reactor Conversion (RC) managed at Argonne National Laboratory (Argonne), and Cross-Cutting (CC) managed at Savannah River National Laboratory (SRNL). FQ is responsible for the qualification of the fuel type. RC is responsible for supporting reactor conversion analysis and overseeing licensing submittals leading to conversions of domestic reactors to LEU fuel. For the FQ effort, FQ (INL) worked in collaboration with RC (Argonne) and ORNL to develop the plan for the uranium silicide fuel qualification for HFIR.The resulting HFIR Fuel Qualification Plan provides the general approach for the USHPRR team to move the selected uranium silicide fuel design for HFIR conversion through qualification. Authorization and use in HFIR will be approved through the DOE’s Office of Science. Uranium silicide fuel was previously qualified in NUREG-1313 at an approximate maximum heat flux of 1.4 MW/m2 and a maximum fuel section temperature of about 130°C. In addition to the different regulator process utilized by DOE, these upper limits will be exceeded in HFIR; therefore, further testing will be necessary to ensure the fuel can meet HFIR qualification requirements. The HFIR fuel loading may exceed 4.8 gU/cm3 which was determined in the NUREG-1313 safety evaluation to be acceptable for use in non-power NRC-regulated reactors provided there exist no other safety considerations. In addition, the uranium silicide fuel will need to be qualified in a HFIR-specific design. This plan includes the currently available information from the USHPRR Project Functions and Requirements document and expands these requirements to ensure that planned tests have traceable results providing evidence that the requirements have been met. Data collection methods are discussed as well as the process to show that the requirements have been met. This document is designed to provide a pathway for researchers to obtain data necessary and at the appropriate quality level for HFIR fuel qualification.

Shokes, Tamara↗

Validating Irradiance Models for High-Latitude Vertical Bifacial Photovoltaic Systems

Bifacial photovoltaic systems oriented vertically facing east-west are an emerging design, targeting production in morning and afternoon hours and providing competitive annual energy yield to traditional south-tilted modules for high latitude locations. The accuracy of existing bifacial PV models when modules are oriented vertically has yet to be examined in detail. Here, we compare four bifacial PV irradiance models in ~150 locations between 15-80 degrees N on the utility-scale, finding higher inter-model deviations for vertical PV systems than south-tilted across all latitudes less than 75 degrees N. We validate model-predicted irradiance with test-site data collected in Golden, Colorado and Fairbanks, Alaska for E-W vertical and south-tilted arrays. View factor models agree with E-W vertical test-site data in Golden with RMSE=15%. Modelling error increases for the Alaskan test-site to RMSE values between 21-30%, driven in part by high albedo measurement uncertainty during snowy months.

bifacial↗

Statistical Estimation of EV Driver Charging Behavior and Influential Factors

INL received data collected via telematics from battery electric vehicles (BEVs), and these vehicles were owned by retail customers who had entered into a telematics user agreement. The goal of analyzing these data was to develop mathematical models to characterize how different sets of BEV drivers use charging infrastructure at home and away from home (i.e., public charging) and quantify how various factors influence BEV drivers’ decision to charge and use available infrastructure. The data used in this analysis are unique because they provide real world BEV driving and charging behavior at the individual driving and parking event level. In this study we seek to leverage this data to quantify BEV charging and driving metrics to help inform models that predict quantities like the specific times when loads are imposed on the electrical grid due to BEV charging. Most models that have been developed to predict electrical grid load due to BEV charging, use simulations of BEV driving events and rely on assumptions such as every vehicle charges every night. Using a statistical modelling framework, we seek to investigate BEV charging behavior and quantitatively assess these common assumptions of BEV charging behavior.

33 - ADVANCED PROPULSION SYSTEMS↗

A primer on forest structure measurement with lidar for ecologists

Light detection and ranging (lidar) technology has fundamentally advanced the way we measure forest structure, facilitating new insights into ecological processes. Lidar for forest ecology applications is deployed on multiple types of platforms that operate from the ground, air, or space, and each has associated strengths and limitations. Ideally, the choice of what kind of lidar to use in a particular study should be guided by the ecological question of interest; however, practical considerations of cost, data availability, and processing tools can be equally important. This synthesis is a practical introduction to how different lidar platforms characterize forest structure (e.g., tree size/location, wood volume, branching structure, aboveground biomass, leaf properties), designed for a general audience of ecologists (not remote sensing scientists) seeking an accessible introduction to the use of lidar. We also provide examples of novel ecological insights from recent lidar research and describe current limitations and areas of expected improvement. Last, we include an appendix of data collected from terrestrial, mobile, unoccupied aerial system, airplane, and satellite lidar platforms within a common temperate forest area, with associated code to allow new lidar users to visualize and manipulate data in R.

Cushman, KC [ORNL] (ORCID:0000000234641151)↗

A non-intrusive optical (NIO) approach to characterize heliostats in utility-scale power tower plants: Sensitivity study

Power towers, a type of concentrating power tower technology, use a large number of heliostats to concentrate sunlight and produce renewable energy. Optical errors of heliostats can cause drastic losses in the efficiency of power-tower plants. Accurately measuring optical errors is crucial to assessing and improving plant performance. This analysis discusses an innovate non-intrusive optical (NIO) approach to measure slope, canting, and tracking errors by detecting distortions in the reflected tower structure in heliostat images. Further in this work a sensitivity study is carefully conducted to determine the uncertainty requirements to allow the method to calculate slope errors with an accuracy of 0.25 mrad. Measurement uncertainty sources include camera resolution and position uncertainty, tower position uncertainty, and number of collected images. Each uncertainty source is investigated to determine its impact on the accuracy of the slope-error calculation. A combination of theoretical results and experimental results obtained from data collected on a heliostat at Sandia National Laboratories is used to determine and validate uncertainty requirements. The analysis shows that a measurement uncertainty of 0.25 mrad can be realized by realistically controlling uncertainty sources when implementing the NIO method. It demonstrates the superior performance of NIO in performing in-situ optical characterization.

14 SOLAR ENERGY↗

A dynamic kinetic model captures cell-free metabolism for improved butanol production

Cell-free systems are useful tools for prototyping metabolic pathways and optimizing the production of various bioproducts. Mechanistically-based kinetic models are uniquely suited to analyze dynamic experimental data collected from cell-free systems and provide vital qualitative insight. However, to date, dynamic kinetic models have not been applied with rigorous biological constraints or trained on adequate experimental data to the degree that they would give high confidence in predictions and broadly demonstrate the potential for widespread use of such kinetic models. In this work, we construct a large-scale dynamic model of cell-free metabolism with the goal of understanding and optimizing butanol production in a cell-free system. Using a combination of parameterization methods, the resultant model captures experimental metabolite measurements across two experimental conditions for nine metabolites at timepoints between 0 and 24 hours. Here, we present analysis of the model predictions, provide recommendations for butanol optimization, and identify the aldehyde/alcohol dehydrogenase as the primary bottleneck in butanol production. Sensitivity analysis further reveals the extent to which various parameters are constrained, and our approach for probing valid parameter ranges can be applied to other modeling efforts.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗