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At least 343 records · Page 19

Seismic identification of geothermal prospecting in Harrat Rahat, Northern Arabian Shield

Harrat Rahat volcanic field lies along the Makkah-Madinah-Nafud active volcanic line. It has extensive linear weak zones of wrench faults that could provide ideal conduits for upwelling magma and hydrothermal fluids as well. Here, passive seismic data recorded by seismic stations installed within and around Harrat Rahat has been processed for the detection of microseismic events. Moreover, ambient noise was also gathered and analyzed to construct a subsurface velocity model. This model indicates low velocity zone in Harrat Rahat, and two areas with coincident basement faults and possibly with enhanced subsurface temperatures were identified. It is concluded that Harrat Rahat has high geothermal potential and promising for geothermal renewable power.

58 GEOSCIENCES↗

Novel method for the identification of the production flavor of neutral charmed mesons

We propose a new algorithm for the identification of the production flavor of neutral D mesons in the Belle II experiment. The algorithm exploits the correlation between the flavor of a reconstructed neutral D meson (signal D meson) and the electric charges of particles reconstructed in the rest of the e + e – →$c\bar{c}$ event. These include those originating from the decay of the other charm hadron produced in the event, as well as those possibly produced in association with the signal D meson. We develop the algorithm using simulation and calibrate it in data using decay modes that identify the flavor of the decaying neutral D meson. We use a data sample of e + e – collisions, corresponding to 362 fb –1 of integrated luminosity, collected by Belle II at center-of-mass energies near the Υ(4S) mass. The effective tagging efficiency in data is (47.91±0.07 (stat) ±0.51 (syst)) %, independent of the neutral-D-meson decay mode. This charm flavor tagger will approximately double the effective sample size of many CP-violation and charm-mixing measurements that so far have exclusively relied on neutral D mesons originating from D* ± decays. While developed for Belle II, the basic principles underlying the charm flavor tagger can be used in other experiments, including those at hadron colliders.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

Expanded Phylogenetic Diversity and Metabolic Flexibility of Mercury-Methylating Microorganisms

Methylmercury is a potent bioaccumulating neurotoxin that is produced by specific microorganisms that methylate inorganic mercury. Methylmercury production in diverse anaerobic bacteria and archaea was recently linked to the hgcAB genes. However, the full phylogenetic and metabolic diversity of mercury-methylating microorganisms has not been fully unraveled due to the limited number of cultured experimentally verified methylators and the limitations of primer-based molecular methods. Here, we describe the phylogenetic diversity and metabolic flexibility of putative mercury-methylating microorganisms by hgcAB identification in publicly available isolate genomes and metagenome-assembled genomes (MAGs) as well as novel freshwater MAGs. We demonstrate that putative mercury methylators are much more phylogenetically diverse than previously known and that hgcAB distribution among genomes is most likely due to several independent horizontal gene transfer events. The microorganisms we identified possess diverse metabolic capabilities spanning carbon fixation, sulfate reduction, nitrogen fixation, and metal resistance pathways. We identified 111 putative mercury methylators in a set of previously published permafrost metatranscriptomes and demonstrated that different methylating taxa may contribute to hgcA expression at different depths. Overall, we provide a framework for illuminating the microbial basis of mercury methylation using genome-resolved metagenomics and metatranscriptomics to identify putative methylators based upon hgcAB presence and describe their putative functions in the environment.

59 BASIC BIOLOGICAL SCIENCES↗

Ubiquity and Causes of Soil Water Preferential Flow Across 17 Ecoregions

Abstract Preferential flow (PF) in soil causes the rapid transport of water, nutrients, and contaminants into the subsurface, influencing groundwater recharge and streamflow. Data scarcity has hindered the quantification of PF occurrence and the identification of its drivers across diverse ecoregions. We address this gap by analyzing high‐frequency, multi‐depth soil moisture data across 17 ecoregions in the USA, using ∼1,500 sensors at 40 sites. We discovered that PF is widespread, with sites experiencing PF in up to 60% of rainfall events ≥2 mm. Multiple approaches consistently show that PF is more likely to occur with increased peak rainfall intensity, finer textured material, low soil moisture variability, humid climate, and higher net primary productivity. This suggests that PF patterns could shift with projected climate changes, increasing uncertainty in predictions of groundwater recharge, water quality, and streamflow generation. Plain Language Summary Water can bypass part of the soil's matrix through a process called preferential flow (PF). This quick transport of water through the soil brings with it nutrients and contaminants and eventually makes it to groundwater and streams. To ensure ample amounts of good quality groundwater and surface water we need to understand when and where PF occurs. We inferred when PF occurred at 40 different sites across 17 ecoregions in the USA using soil moisture and rainfall data. We found that PF happened at all sites and in up to 60% of rainfall events ≥2 mm. Preferential flow was most likely at sites with high rainfall intensities, high clay content in soils, low variability in soil moisture, and high vegetation productivity. As rainfall intensities are predicted to increase due to climate change and vegetation becomes more productive, PF occurrence becomes more important for predicting groundwater recharge, water quality, and streamflow generation. Key Points Preferential flow (PF) is ubiquitous across the USA and occurs in up to 60% of all rainfall events ≥2 mm Rainfall intensity, soil texture, and antecedent soil moisture emerge as critical in generating PF across diverse ecoregions Two different PF detection approaches show similar relationships between key drivers and occurrence of PF

Li, Bonan↗

Mechanistic roles of metal- and ligand-protonated species in hydrogen evolution with [Cp*Rh] complexes

Protonation reactions involving organometallic complexes are ubiquitous in redox chemistry and often result in the generation of reactive metal hydrides. However, some organometallic species supported by η 5 -pentamethylcyclopentadienyl (Cp*) ligands have recently been shown to undergo ligand-centered protonation by direct proton transfer from acids or tautomerization of metal hydrides, resulting in the generation of complexes bearing the uncommon η 4 -pentamethylcyclopentadiene (Cp*H) ligand. Here, time-resolved pulse radiolysis (PR) and stopped-flow spectroscopic studies have been applied to examine the kinetics and atomistic details involved in the elementary electron- and proton-transfer steps leading to complexes ligated by Cp*H, using Cp*Rh(bpy) as a molecular model (where bpy is 2,2′-bipyridyl). Stopped-flow measurements coupled with infrared and UV-visible detection reveal that the sole product of initial protonation of Cp*Rh(bpy) is [Cp*Rh(H)(bpy)] + , an elusive hydride complex that has been spectroscopically and kinetically characterized here. Tautomerization of the hydride leads to the clean formation of [(Cp*H)Rh(bpy)] + . Variable-temperature and isotopic labeling experiments further confirm this assignment, providing experimental activation parameters and mechanistic insight into metal-mediated hydride-to-proton tautomerism. Spectroscopic monitoring of the second proton transfer event reveals that both the hydride and related Cp*H complex can be involved in further reactivity, showing that [(Cp*H)Rh] is not necessarily an off-cycle intermediate, but, instead, depending on the strength of the acid used to drive catalysis, an active participant in hydrogen evolution. Identification of the mechanistic roles of the protonated intermediates in the catalysis studied here could inform design of optimized catalytic systems supported by noninnocent cyclopentadienyl-type ligands.

08 HYDROGEN↗

In Situ Oxygen Isotope Determination in Serpentine Minerals by SIMS: Addressing Matrix Effects and Providing New Insights on Serpentinisation at Hole BA1B (Samail ophiolite, Oman)

The ability to constrain the petrogenesis of multiple serpentine generations recorded at the microscale is crucial for estimating the extent and conditions of modern versus fossil serpentinisation in ophiolites. To address matrix bias effects during oxygen isotope analysis by SIMS, we present the first investigation analysing antigorite in the compositional range Mg# = 77.5–99.5 mole %, using a CAMECA IMS–1280 secondary ion mass spectrometer. Spot–to–spot homogeneity is ≤ 0.5‰ (2s) for the new antigorite reference materials. The relative bias between antigorite reference materials with different Mg/Fe ratios is described by a second order polynomial, and a maximum difference in bias of ~ 1.8‰ was measured for Mg# ~ 78 to 100. We observed a bias up to ~ 1.0‰ between lizardite and antigorite attributed to their different crystal structure. Orientation effects up to ~ 1‰ were observed in chrysotile. The new analytical protocol allowed the identification of oxygen isotope zoning up to ~ 7‰ in serpentine minerals from two serpentinites recovered from an area of active serpentinisation in the Samail ophiolite. Furthermore in situ analysis is capable of resolving isotopic heterogeneity that may directly reflect changes in the physical and chemical conditions of multiple serpentinisation events in the Samail ophiolite.

47 OTHER INSTRUMENTATION↗

Final Design and Current Status of the Mu2e Crystal Calorimeter

The Mu2e experiment at Fermi National Accelerator Laboratory will search for the CLFV neutrino-less conversion of a negative muon into an electron in the field of an aluminum nucleus. The Mu2e design has been studied to improve the single event sensitivity of four orders of magnitude with respect to the previous experiments and provide an indirect probe for New Physics energy scales up to thousands TeV. Mu2e is composed of a tracker, an electromagnetic calorimeter, and an external veto for cosmic rays. The calorimeter provides a powerful particle identification and an online trigger while operating in a harsh environment. We report on the status of the calorimeter components production, the quality assurance tests, and the tests performed with a reduced-scale prototype.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗

Measurement of $\nu_\mu$ CC Interactions With Two-Proton Final State in MINERvA

This dissertation presents a measurement of charged–current (CC) muon–neutrino interactions with exactly two protons and no pions in the final state (CC~$2p\,0\pi$), using data collected by the MINERvA detector in the NuMI medium–energy beam at Fermilab. Such two–proton topologies are a sensitive probe of nuclear dynamics in the few–GeV regime, including multi–nucleon correlations (npnh, notably $2p2h$) and intranuclear final–state interactions (FSI) such as pion absorption and nucleon rescattering. A precise experimental characterization of these processes is essential both for neutrino–interaction theory and for reducing systematic uncertainties in oscillation experiments that rely on accurate modeling of neutrino–nucleus interactions. Events are selected by requiring a $\nu_\mu$ CC interaction with a reconstructed $\mu^-$ and two proton tracks originating from a common vertex in MINERvA’s finely segmented scintillator tracker, with no reconstructed mesons. Muon charge and momentum are constrained by matching to the MINOS Near Detector, while proton identification exploits energy–loss profiles and stopping–proton features. Backgrounds from pion–producing channels that enter the signal region through FSI or reconstruction effects are constrained with data–driven sidebands (Michel–electron and isolated–cluster “blob” samples) and tuned via a simultaneous fit across signal and sideband regions. To correct detector resolution and acceptance effects, the analysis employs iterative Bayesian unfolding with extensive validation: statistical pseudo–experiments, and robustness checks against generator systematic “universes” and additional strong shape warps. Single–differential cross sections are reported for three observables tailored to the two–proton final state: the opening–angle cosine $\cos\!\left(\theta_{pp}\right)$, the leading–proton momentum, and the subleading–proton momentum. Systematic uncertainties include contributions from neutrino flux, interaction modeling (e.g., npnh and resonance parameters, pion FSI), and detector response (calibration, reconstruction efficiencies). The resulting distributions provide targeted constraints on the interplay of multi–nucleon dynamics and FSI that shape CC~$2p\,0\pi$ final states on hydrocarbon. Comparisons to modern GENIE–based simulations highlight kinematic regions where model components require refinement. These measurements thus inform generator tuning and improve the reliability of neutrino–energy reconstruction strategies for current and future long–baseline oscillation programs.

Syrotenko, Vladyslav S. [Tufts U.]↗

Identifying a regional aerosol baseline in the eastern North Atlantic using collocated measurements and a mathematical algorithm to mask high-submicron-number-concentration aerosol events

Abstract. High-time-resolution measurements of in situ aerosol and cloud properties provide the ability to study regional atmospheric processes that occur on timescales of minutes to hours. However, one limitation to this approach is that continuous measurements often include periods when the data collected are not representative of the regional aerosol. Even at remote locations, submicron aerosols are pervasive in the ambient atmosphere with many sources. Therefore, periods dominated by local aerosol should be identified before conducting subsequent analyses to understand aerosol regional processes and aerosol–cloud interactions. Here, we present a novel method to validate the identification of regional baseline aerosol data by applying a mathematical algorithm to the data collected at the U.S. Department of Energy's (DOE) Atmospheric Radiation Measurement (ARM) user facility in the eastern North Atlantic (ENA). The ENA central facility (C1) includes an aerosol observing system (AOS) for the measurement of aerosol physical, optical, and chemical properties at time resolutions from seconds to minutes. A second temporary supplementary facility (S1), located ∼0.75 km from C1, was deployed for ∼1 year during the Aerosol and Cloud Experiments (ACE-ENA) campaign in 2017. First, we investigate the local aerosol at both locations. We associate periods of high submicron number concentration (Ntot) in the fine-mode condensation particle counter (CPC) and size distributions from the Ultra-High Sensitivity Aerosol Spectrometer (UHSAS) as a function of wind direction using a meteorology sensor with local sources. Elevated concentrations of Aitken-mode (< 100 nm diameter) particles were observed in correspondence with the wind directions associated with airport operations. At ENA, the Graciosa Airport and its associated activities were found to be the main sources of high-concentration aerosol events at ENA, causing peaks in 1 min Ntot that exceeded 8000 and 10 000 cm−3 at C1, in summer and winter, respectively, and 5000 cm−3 at S1 in summer. Periods with high Ntot not associated with these wind directions were also observed. As a result, the diverse local sources at ENA yielded a poor relationship between Ntot measurements collected at C1 and S1 (R2=0.03 with a slope =0.05±0.001). As a first approach to mask these events, the time periods when the wind direction was associated with the airport operations (west to northwest and southeast to south at C1 and east to south at S1) were applied. The meteorological masks removed 38.9 % of the data at C1 and 43.4 % at S1, and they did not significantly improve the relationship between the two sites (R2=0.18 with a slope =0.06±0.001). Due to the complexity of high-Ntot events observed at ENA, we develop and validate a mathematical ENA Aerosol Mask (ENA-AM) to identify high-Ntot events using 1 min resolution data from the AOS CPC at C1 and S1. After its parameterization and application, ENA-AM generated a high correlation between Ntot in the summer at C1 and S1 (R2=0.87 with a slope =0.84±0.001). We identified the regional baseline at ENA to be 428±228 cm−3 in the summer and 346±223 cm−3 in the winter. Lastly, we compared masked measurements from the AOS with the ARM Aerial Facility (AAF) during flights over C1 in the summer to understand submicron aerosol vertical mixing over C1. The high correlation (R2=0.71 with a slope of 1.04±0.01) observed between C1 and the AAF Ntot collected within an area of 10 km surrounding ENA and at altitudes < 500 m indicated that the submicron aerosol at ENA was well mixed within the first 500 m of the marine boundary layer during the month of July during ACE-ENA. Our novel method for determining a regional aerosol baseline at ENA can be applied to other time periods and at other locations with validation by a secondary site or additional collocated measurements.

54 ENVIRONMENTAL SCIENCES↗

Using Systems Theoretic Process Analysis and Causal Analysis to Map and Manage Organizational Information to Enable Digitalization and Information Automation

The overarching goal of this Light Water Reactor Sustainability Program–supported research and development project is to provide planning tools and comprehensive guidance to utilities considering or undertaking full nuclear plant modernization. The results of this research will provide the nuclear industry with a comprehensive and usable solution, including guidance, lessons learned, methods, and planning tools. This research is currently working to provide guidance on digitalization and information automation to enable the evolution of data to information, insight, and action—thereby allowing utilities to operate safely and cost-competitively with all other electrical generation sources. Light Water Reactor Sustainability Program researchers have also recently started investigating how human and technology integration principles, information automation, and digitalization enable data evolution. These researchers are currently in the process of validating the use of System-Theoretic Process Analysis to define high-level safety constraints in the United States Nuclear Regulatory Commission’s problem identification and resolution process (i.e., a plant compliance information gathering activity). The next step in this research, which is described in the following sections of this report, is to map out data evolution in a use case to identify inefficiencies in another aspect of plant compliance information gathering and communication activities—event investigations and root cause analyses.

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗

Electrical Fault Detection, Power Quality, Distributed Energy Resource Use Cases, and Cyber Event Applications with the Cyber Grid Guard System Using Distributed Ledger Technology

Electrical utilities continue to deploy more intelligent electronic devices (IEDs) inside and outside electrical substation and are associated with distributed energy resources (DERs). The integrity and confidentiality of data from IEDs is crucial, and distributed ledger technology (DLT) could improve the resilience of microgrids by helping to make these data more secure. The most popular applications using blockchain technology for electrical utilities is in the field is based on energy trading. However, the dynamism of the penetration of customer owned DERs and the deployment of sensors with IEDs have led to the identification of new applications using DLT that are focused on other areas, such as monitoring, operation and management of the grid and its assets. In addition, the majority of studies on electrical grid applications with blockchain were validated with software simulations. Although general monitoring of power systems for using DLT could be evaluated in operational electric grids, other DLT research applications such as defense against cyber-attacks and/or electrical fault detection are not likely to be performed in a real infrastructure because of possible risks to the network/equipment security. This report summarizes the application of power system applications using distributed ledger technology (DLT), providing a secure DLT framework for collecting data from IEDs like power meters and protective relays inside and outside of an electrical substation and/or between two different electrical utilities. In this study, the use case scenarios were created and assessed for different power system application by using DLT. The electrical fault detection for faulted phases (1), power quality monitoring of phase voltage magnitudes, frequency levels and load power factor (2), DERs use case monitoring (3), and cyber-event applications (4) were performed in a test bed with a Cyber-Grid Guard (CGG) system using DLT. It had a real-time simulator with power meters and protective relays in-the-loop. The first section of this report presents a literature review of power system applications using blockchain at research level. The second section shows the theory and equations used on this report. The third section shows the description of the test bed, equipment, architecture, and electrical grid diagrams. The fourth section shows the experimental models and use case scenarios that were performed for the electrical fault detection, power quality, DERs use case, and cyber event applications with the CGG system using DLT. The fifth section shows the results collected from the tests based on comparing the time stamped events of the analog signals from the IEDs, DLT computer and real time simulator. The sixth section performed the discussion of the results for the use case scenarios. Finally, section seven presents the conclusions for this report were presented.

24 POWER TRANSMISSION AND DISTRIBUTION↗

Identifying atmospheric rivers and their poleward latent heat transport with generalizable neural networks: ARCNNv1

Abstract. Atmospheric rivers (ARs) are extreme weather events that can alleviate drought or cause billions of US dollars in flood damage. By transporting significant amounts of latent energy towards the poles, they are crucial to maintaining the climate system's energy balance. Since there is no first-principle definition of an AR grounded in geophysical fluid mechanics, AR identification is currently performed by a multitude of expert-defined, threshold-based algorithms. The variety of AR detection algorithms has introduced uncertainty into the study of ARs, and the thresholds of the algorithms may not generalize to new climate datasets and resolutions. We train convolutional neural networks (CNNs) to detect ARs while representing this uncertainty; we name these models ARCNNs. To detect ARs without requiring new labeled data and labor-intensive AR detection campaigns, we present a semi-supervised learning framework based on image style transfer. This framework generalizes ARCNNs across climate datasets and input fields. Using idealized and realistic numerical models, together with observations, we assess the performance of the ARCNNs. We test the ARCNNs in an idealized simulation of a shallow-water fluid in which nearly all the tracer transport can be attributed to AR-like filamentary structures. In reanalysis and a high-resolution climate model, we use ARCNNs to calculate the contribution of ARs to meridional latent heat transport, and we demonstrate that this quantity varies considerably due to AR detection uncertainty.

54 ENVIRONMENTAL SCIENCES↗

Jefferson Laboratory C100 Superconducting Radio-Frequency Cavity Fault Data, 2020

The dataset was created to train machine learning models for the task of identifying the (1) cavity and (2) fault type from C100-type cryomodules at the Thomas Jefferson National Accelerator Facility (Jefferson Lab), thereby replacing the time-consuming efforts of a subject matter expert. Superconducting radio-frequency (SRF) cavity trips represent a significant source of accelerator downtime. Real-time – rather than post-mortem – identification of the offending cavity and classification of the fault type would give control room operators valuable feedback for corrective action planning. The anticipated benefit is increased beam-on-target time for users and provides performance metrics that can be used to improve future cavity designs. A series of 17 RF signals are recorded for each of the 8 cavities in a C100 cryomodule every time a cavity trips. These time-series signals are written to file using a specially designed data acquisition system. The dataset represents fault events recorded during Continuous Electron Beam Accelerator Facility (CEBAF) beam operations between January 18, 2019 and March 9, 2020. The following filtering steps were applied to collected data; (1) only 4 of the 17 signals per cavity are retained (GMES, GASK, CRFP, DETA2) (2) only events with data from each of the eight cavities in the cryomodule are kept, (3) only events that were sampled at 5 kHz were kept, (4) events from cryomodule 0L04 were neglected, (5) events occurring between February 4, 3PM and February 5, 12PM were neglected. As a result of preprocessing, the dataset is comprised of 2,375 unique events. The full dataset is comprised of three files: features.csv, cavity_labels.csv, fault_labels.csv. Each instance in faults.csv includes a timestamp (“date_time”), a label for the cryomodule which experienced the trip (“zone_label”), and 192 features (“feature_1”, “feature_2”... “feature_192”). The features correspond to 6 autoregressive features for each of 4 signals per cavity for each of the 8 cavities (6 × 4 signals/cavity × 8 cavities/cryomodule = 192). To deal with the large variation of signal amplitudes, time-series standardization via the z-score (standard score) function was applied prior to computing the features. For each instance, there is an associated label for the (1) cavity which faulted first (cavity_labels.csv) and (2) the type of fault that caused the trip (fault_labels.csv). The cavity identification can take values of [0, 1, 2, 3, 4, 5, 6, 7, 8] and the fault type can take values of [‘Microphonics’, ‘Quench_100ms’, ‘Controls_Fault’, ‘E_Quench’, ‘Quench_3ms’, ‘Single_Cav_Turn_Off’ , ‘Heat_Riser_Choke’, ‘Multi_Cav_Turn_Off’].

43 PARTICLE ACCELERATORS↗

Along-Trajectory Acoustic Signal Variations Observed During the Hypersonic Re-Entry of the OSIRIS-REx Sample Return Capsule

The re-entry of the Origins, Spectral Interpretation, Resource Identification, and Security-Regolith Explorer (OSIRIS-REx) sample return capsule (SRC) on 24 September 2023 presented a rare opportunity to study atmospheric entry dynamics through a dense network of ground-based infrasound sensors. As the first interplanetary capsule to re-enter over the United States since Stardust in 2006, this event allowed for unprecedented observations of infrasound signals generated during hypersonic descent. We deployed 39 single-sensor stations across Nevada and Utah, strategically distributed to capture signals from distinct trajectory points. Infrasound data were analyzed to examine how signal amplitude and period vary with altitude and propagation path for a nonablating hypersonic object with well-defined physical and aerodynamic properties. Raytracing simulations incorporated atmospheric specifications from the ground-2-space model to estimate source altitudes for observed signals. Results confirmed ballistic arrivals at all stations, with source altitudes ranging from 44 to 62 km along the trajectory. Signal period and amplitude exhibited strong dependence on source altitude, with higher altitudes corresponding to lower amplitudes, longer periods, and reduced high-frequency content. Regression analysis demonstrated strong correlations between signal characteristics and both altitude and propagation geometry. Our results suggest, when attenuation is considered, the amplitude is primarily determined by the source, with the propagation path playing a secondary role over the distances examined. These findings emphasize the utility of controlled SRC re-entries for advancing our understanding of natural meteoroid dynamics, refining atmospheric entry models, and improving methodologies for planetary defense. The OSIRIS-REx SRC campaign represents the most comprehensive infrasound study of a hypersonic re-entry to date, showcasing the potential of coordinated geophysical observational networks for high-energy atmospheric phenomena, including space debris re-entries.

58 GEOSCIENCES↗

A section 110 evaluation of the huron king test chamber, area 3, nevada national security site, nye county, nevada

The U.S. Department of Energy, National Nuclear Security Administration Nevada Field Office tasked Desert Research Institute (DRI) with the identification and evaluation of the Huron King Test Chamber as part of their cultural resources program obligations under Section 110 of the National Historic Preservation Act. The Huron King nuclear test was a vertical line-of-sight weapons effects test that took place in Area 3 on June 24, 1980. Unique to this event was a specially designed aboveground test chamber that held a model defense communications satellite in a vacuum tank meant to replicate the space environment. Sponsored by the Defense Nuclear Agency, the purpose of the experiment was to understand the response of the satellite and its materials and equipment to an electromagnetic pulse and attendant radiation. Between July and August 2022, DRI conducted an archival review on the Huron King experiment and its associated test chamber. Subsequently, pedestrian fieldwork was undertaken at the Huron King Test Chamber by DRI on September 29, 2022. During fieldwork, the outside of the test chamber was documented using a Nevada State Historic Preservation Office Architectural Resource Assessment form. This effort included verifying the substructures that compose the test chamber as determined by the archival review, as well as obtaining a detailed photographic recordation of the exterior and assessing its current condition. Notably, the site where the Huron King test took place has been abandoned and almost entirely naturalized. All of the portable instrumentation trailers, communications and data cabling, and winch systems used to retract the test chamber following the detonation were removed after completion of the experiment in 1980. Only the subsidence crater and the test chamber remain as physical evidence of this experiment. Based on these findings, DRI recommends that the Huron King Test Chamber is eligible for listing in the National Register of Historic Places (NRHP) at the local level under Significance Criteria A and C and that it meets Criteria Consideration G for properties less than 50 years old.

54 ENVIRONMENTAL SCIENCES↗

Ultrasonic Characterization of Lithium Ion Thermal Runaway Conditions for Real-time Ultrasonic Enabled BMS Integration

The demand for energy storage is growing, and lithium-ion batteries are a promising technology to meet this need due to their high power/energy density, high round-trip efficiency, rapid response time, and portability. However, recent catastrophic events caused by thermal runaway have slowed their adoption, highlighting the need for an early warning system for battery failure. In this work, ultrasound is used to detect physical changes in 950 mAh batteries by identifying material property changes independent of voltage and current. [Ultrasound signal features (e.g., time of flight, maximum frequency component) were extracted as the batteries were cycled and subjected to both constant current and constant voltage overcharge and were used to develop two metrics identifying failure: a warning to detect the start of overcharge and an emergency stop (E-stop) to immediately take the battery out of service. The identification method involved locating magnitude differences of several ultrasound features compared to baseline operation considering different currents and temperatures, and the warning/stopping metrics were consistent across all experiments. For an average overcharge time of 140 minutes, the average warning was issued 124 minutes before the failure and the average E-stop was triggered 94 minutes before failure. As a test of using ultrasound for early warning detection, a battery was forced into overcharge and returned to normal cycling conditions based on the previously determined warning metric. Both the voltage profile and the ultrasound measurements returned to their baseline behavior, indicating that ultrasonic detection can not only identify battery failure before a catastrophic event, but can also provide early enough warnings such that overcharges can be detected and corrected quickly enough so the battery does not need to be decommissioned.]

25 ENERGY STORAGE↗

Search for new phenomena in final states with b-jets and missing transverse momentum in $ \sqrt{\mathrm{s}} $ = 13 TeV pp collisions with the ATLAS detector

The results of a search for new phenomena in final states with b -jets and missing transverse momentum using 139 fb - 1 of proton-proton data collected at a centre-of-mass energy s = 13 TeV by the ATLAS detector at the LHC are reported. The analysis targets final states produced by the decay of a pair-produced supersymmetric bottom squark into a bottom quark and a stable neutralino. The analysis also seeks evidence for models of pair production of dark matter particles produced through the decay of a generic scalar or pseudoscalar mediator state in association with a pair of bottom quarks, and models of pair production of scalar third-generation down-type leptoquarks. No significant excess of events over the Standard Model background expectation is observed in any of the signal regions considered by the analysis. Bottom squark masses below 1270 GeV are excluded at 95% confidence level if the neutralino is massless. In the case of nearly mass-degenerate bottom squarks and neutralinos, the use of dedicated secondary-vertex identification techniques permits the exclusion of bottom squarks with masses up to 660 GeV for mass splittings between the squark and the neutralino of 10 GeV. These limits extend substantially beyond the regions of parameter space excluded by similar ATLAS searches performed previously.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

Calorimetric classification of track-like signatures in liquid argon TPCs using MicroBooNE data

The MicroBooNE liquid argon time projection chamber located at Fermilab is a neutrino experiment dedicated to the study of short-baseline oscillations, the measurements of neutrino cross sections in liquid argon, and to the research and development of this novel detector technology. Accurate and precise measurements of calorimetry are essential to the event reconstruction and are achieved by leveraging the TPC to measure deposited energy per unit length along the particle trajectory, with mm resolution. We describe the non-uniform calorimetric reconstruction performance in the detector, showing dependence on the angle of the particle trajectory. Such non-uniform reconstruction directly affects the performance of the particle identification algorithms which infer particle type from calorimetric measurements. This work presents a new particle identification method which accounts for and effectively addresses such non-uniformity. The newly developed method shows improved performance compared to previous algorithms, illustrated by a 93.7% proton selection efficiency and a 10% muon mis-identification rate, with a fairly loose selection of tracks performed on beam data. The performance is further demonstrated by identifying exclusive final states in ν μ CC interactions. While developed using MicroBooNE data and simulation, this method is easily applicable to future LArTPC experiments, such as SBND, ICARUS, and DUNE.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗