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Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

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At least 253 records · Page 14
All sourcesNASA NTRSDOE OSTI
DOE OSTI2023

Development of the microcalorimeter and anticoincidence detector for the Line Emission Mapper x-ray probe

The Line Emission Mapper (LEM) is an x-ray probe mission concept that is designed to provide unprecedented insight into the physics of galaxy formation, including stellar and black-hole feedback and flows of baryonic matter into and out of galaxies. LEM incorporates a light-weight x-ray optic with a large-format microcalorimeter array. The LEM detector utilizes a 14k pixel array of transition-edge sensors (TESs) that will provide <2.5 eV spectral resolution over the energy range 0.2 to 2 keV, along with a field-of-view of 30 arcmin. The microcalorimeter array and readout builds upon the technology developed for the European Space Agency’s (ESA’s) Athena/x-ray Integral Field Unit. Here, we present a detailed overview of the base- line microcalorimeter design, its performance characteristics, including a detailed energy resolution budget and the expected count-rate capability. In addition, we outline the current status and plan for continued technology maturation. Behind the LEM array sits a high-efficiency TES-based anticoincidence (antico) detector that will reject cosmic-ray background events. We will briefly describe the design of the antico and plan for continued development.

47 OTHER INSTRUMENTATION↗
DOE OSTI2024

Simulating water dynamics related to pedogenesis across space and time: Implications for four-dimensional digital soil mapping

Digital soil mapping (DSM) relies on machine-learning and geostatistics to represent soil property observations across space. DSM techniques are powerful but often empirical, being limited to the quality and density of point samples. Water dynamics are closely related to soil variability, and the physics that govern water movement are well known. Hydrological properties can hence be simulated by physical models through space and time, unveiling key characteristics about soils. We propose the use of hydrologic models to map soils across the surface (2D), depth (1D), and time (1D)–which provides a 4D approach to digital soil mapping (4DSM). The Distributed Hydrology Soil Vegetation Model (DHSVM) was applied to a watershed currently under pasture. Moisture sensors and wells were installed at different depths in the watershed on summit, sideslope and toeslope positions to validate the model. DHSVM simulations of soil moisture distribution and depth to saturation were performed during the hydrological year (October 2008-September 2009). Clusters of similar pixels based on soil moisture values were determined using Dynamic Time Warping (DTW) to align temporal data and K-means. Clustering was performed both seasonally and for the entire year. Temporal patterns simulated by DHSVM matched measurements given by moisture sensors and wells. Seasonal clusters differed from the annual cluster. Distinct clusters were observed for each season and with depth, showing that spatiotemporal soil variability is lost when statically assessing soils. Spatiotemporal clusters corroborated field observations of fragipan occurrence not explicitly spatially mapped by Soil Survey Geographic Database (SSURGO). If a connection can be made between water and soils, static and dynamic soil variability can be predicted using physically based hydrologic models. Hydrologic models can benefit soil mapping by enabling reliable 4D simulation of water dynamics, which are fundamental to soil variability and soil classification and directly relate to biological, physical and chemical soil processes not captured by typical soil sampling protocols.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2025

Illuminating the Night: A Survey of Super-Resolution Methods for Nighttime Light Images

Nighttime Light (NTL) images provide critical insights into urbanization, disaster response, and energy consumption. The VIIRS Day/Night Band (DNB) sensor offers high-quality NTL imagery with daily revisit rates, but the available spatial resolution hinders fine-grained accurate analysis. Super-resolution techniques aim to increase the resolution of NTL images, enabling more detailed assessments of infrastructure, light pollution, economic activity, and power outages. However, existing state-of-the-art super-resolution methods designed for natural images struggle with the unique characteristics of NTL data. This work provides a comprehensive review of super-resolution methods across multiple image modalities, evaluates their effectiveness on VI-IRS DNB data, and proposes a multi-modal super-resolution approach tailored to NTL imagery. The proposed approach integrates VIIRS DNB data with road networks and land use information to improve reconstruction accuracy and spatial detail. Code is available for this project athttps://code.ornl.gov/viirs-sr/sr-demos.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2023

Spatiotemporal features of traffic help reduce automatic accident detection time

Quick and reliable automatic detection of traffic accidents is of paramount importance to save human lives in transportation systems. However, automatically detecting when accidents occur has proven challenging, and minimizing the time to detect accidents (TTDA) by using traditional features in machine learning (ML) classifiers has plateaued. We hypothesize that accidents affect traffic farther from the accident location than previously reported. Therefore, leveraging traffic signatures from neighboring sensors that are adjacent to accidents should help improve their detection. We confirm this hypothesis by using verified ground-truth accident data, traffic data from radar detection system sensors, and light and weather conditions and show that we can minimize the TTDA while maximizing classification performance by considering spatiotemporal features of traffic. Specifically, we compare the performance of different ML classifiers (i.e, logistic regression, random forest, and XGBoost) when controlling for different numbers of neighboring sensors and TTDA horizons. We use data from interstates 75 and 24 in the metropolitan area that surrounds Chattanooga, TN. Our results show that the XGBoost classifier produces the best results by detecting accidents as quickly as 1.0 min after their occurrence with an area under the receiver operating characteristic curve of up to 83% and an average precision of up to 49%. We describe limitations, open challenges, and how the proposed framework can be used for quicker operational accident detection.

33 ADVANCED PROPULSION SYSTEMS↗
DOE OSTI2020

Pre-Sinkhole Seismicity at the Napoleonville Salt Dome: Implications for Local Seismic Monitoring of Underground Caverns

The formation of a sinkhole at the Napoleonville salt dome located near Bayou Corne in Assumption Parish, Louisiana, was preceded by an increase in seismicity, as observed 10 km away by a continuously recording broadband seismic sensor. The seismicity rate in the days prior to the sinkhole formation contained hundreds of long-period events, some of which could be detected using a power detector (short-term to long-term energy ratio) tuned to the duration and frequency content of the seismicity. A characteristic of some of these events is a resonance near 0.4 Hz, which could be due to either an acoustic resonance within the brine-filled cavity or possibly due to unsteady fluid flow through a crack. In this work, a more exhaustive catalog was obtained using some of the events detected by the power detector as templates in a correlation detector. Furthermore, the full pre-sinkhole sequence of detections could offer lessons in remote monitoring of underground caverns.

58 GEOSCIENCES↗
DOE OSTI2023

Controllable Phase Transition Properties in VO 2 Films via Metal-Ion Intercalation

VO 2 has shown great promise for sensors, smart windows, and energy storage devices, because of its drastic semiconductor-to-metal transition (SMT) near 340 K coupled with a structural transition. To push its application toward room-temperature, effective transition temperature (T c ) tuning in VO 2 is desired. Here, in this study, tailorable SMT characteristics in VO 2 films have been achieved by the electrochemical intercalation of foreign ions (e.g., Li ions). By controlling the relative potential with respect to Li/Li + during the intercalation process, T c of VO 2 can be effectively and systematically tuned in the window from 326.7 to 340.8 K. The effective T c tuning could be attributed to the observed strain and lattice distortion and the change of the charge carrier density in VO 2 introduced by the intercalation process. This demonstration opens up a new approach in tuning the VO 2 phase transition toward room-temperature device applications and enables future real-time phase change property tuning.

77 NANOSCIENCE AND NANOTECHNOLOGY↗
DOE OSTI2021

Data Processing Package for Cyclic Integrated Reversible Bending Fatigue Testing

A data processing software package has been introduced. The package was developed using MATLAB with the aid of the Curve Fitting Toolbox. The package is made up of four modules: pre-processing, data processing for static testing, data processing for monitoring, and data processing for measurements. CIRFT data are structured with multiple levels of architecture involving group, specimen, session, and scan/block. The degree of complexity of the data structure depends on whether a test is static or cyclic.The test results are presented in figures, scatter plots, and tables. For static testing, the output in tables provides bending mechanical properties and characteristic points of moment–curvature relation: flexural rigidities in linear segments of loading and unloading stages, intersection points between characteristic segments of the curve, and equivalent stress and strain quantities. For cyclic testing, the table output lists control and fatigue life and responsive/dependent quantities including moment, curvature, flexural rigidity, flexural hysteresis, rigidity phase angle, and equivalent stresses and strains. In addition, derivatives such as half-gage length and sensor spacing correction are included. The output also provides standard deviations of the reported quantities when they are applicable or available. The data processing package can serve as a fundamental characterization tool in mechanical study of materials. The package is intended primarily for data processing for the CIRFT process and can also be used in applications for which similar testing requirements exist.

36 MATERIALS SCIENCE↗
DOE OSTI2026

Deep Learning and Photogrammetric Reconstruction for Automated Crack Detection and Dimensional Measurement in Mining Operations

Surface crack detection and dimensional measurement at active mining sites present significant safety and operational challenges. Manual inspection methods are labor-intensive, spatially incomplete, and expose personnel to hazardous environments, while existing automated approaches have been developed primarily for concrete civil infrastructure and have not been validated on the complex, variable surfaces characteristic of mining environments. This dissertation presents an automated pipeline that integrates deep learning semantic segmentation with Structure-from-Motion photogrammetry to detect surface cracks and measure their aperture, length, and vertical displacement from standard RGB imagery acquired during routine Uncrewed Aerial Vehicle (UAV) survey operations, without requiring additional sensor hardware or manual measurement. The pipeline combines a U-Net architecture with an EfficientNet-B0 encoder, pretrained on the SDNET2018 concrete crack dataset and fine-tuned on a mining-specific dataset spanning laboratory concrete specimens, coal refuse impoundment embankments, and post-blast limestone quarry benches. Photogrammetric reconstruction is performed using COLMAP Structure-from-Motion and Multi-View Stereo, with crack segmentation masks projected into the reconstructed point cloud to enable three-dimensional vertical displacement measurement through local plane fitting and bimodal surface detection. The pipeline was validated across 36 controlled laboratory specimens at three imaging distances and four vertical displacement levels, achieving aperture measurement RMSE of 0.047 cm and R² of 0.954, and vertical displacement RMSE of 0.140 cm and R² of 0.966, against independent caliper measurements. Field application at a coal refuse impoundment in southwestern Pennsylvania detected 71 crack components across the embankment crest, with a dominant longitudinal crack exhibiting aperture values reaching 28 cm and a 95th percentile vertical displacement of 35.53 cm, consistent in magnitude and spatial distribution with simultaneously acquired LiDAR-derived estimates. Application across four post-blast limestone quarry bench datasets in California successfully characterized blast-induced fracture networks at ground sampling distances ranging from 0.59 to 1.23 cm/pixel, with detected crack geometries physically consistent with observable surface conditions at each site. The results demonstrate that deep learning-based crack detection and photogrammetric measurement can be integrated into routine UAV inspection workflows at mining sites, providing repeatable, scalable, and quantitative crack characterization across surface types, crack scales, and displacement magnitudes not previously addressed in the literature. The pipeline requires no dedicated surveying equipment beyond the UAV platforms already deployed at mine sites for survey and monitoring purposes, supporting practical adoption within existing operational workflows.

Crack detection, Dimensional Measurement↗
DOE OSTI2024

A semi–automatic analytical methodology for characterizing the energy consumption of MRI systems using load duration curves

Background and purpose: Magnetic resonance imaging (MRI) scanners are a major contributor to greenhouse gas emissions from the healthcare sector, and efforts to improve energy efficiency and reduce energy consumption rely on quantification of the characteristics of energy consumption. The purpose of this work was to develop a semi-automatic analytical methodology for the characterization of the energy consumption of MRI systems using only the load duration curve (LDC). LDCs are a fundamental tool used across various fields to analyze and understand the behavior of loads over time. Methods: An electric current transformer sensor and data logger were installed on two 3T MRI scanners from two vendors, termed M1 (outpatient scanner) and M2 (inpatient/emergency scanner). Data was collected for 1 month (7/11/2023 to 8/11/2023). Active power was calculated, assuming a balanced three-phase system, using the average current measured across all three phases, a 480 V reference voltage for both machines, and vendor-provided power factors. An LDC was constructed for each system by sorting the active power values in descending order and computing the cumulative time (in units of percentage) for each data point. The first derivative of the LDC was then computed (LDC’), smoothed by convolution with a window function (sLDC’), and used to detect transitions between different system modes including (in descending power levels): scan, prepared-to-scan, idle, low-power, and off. The final, segmented LDC was used to measure time (% total time), total energy (kWh), and mean power (kW) for each system mode on both scanners. The method was validated by comparing mean power values, computed using the segmented 1-month LDC, for each nonproductive system mode (i.e., prepared-to-scan, idle, lower-power, and off) against power levels measured after a deliberate system shutdown was performed for each scanner (1 day worth of data). Results: The validation revealed differences in mean power values <1.4% for all nonproductive modes and both scanners. In the scan system mode, the mean power values ranged from 29.8 to 37.2 kW and the total energy consumed for 1 month ranged from 11 106 to 14 466 kWh depending on the scanner. Over the course of 1 month, the portion of time the scanners were in nonproductive modes ranged from 76% to 80% across scanners and the nonproductive energy consumption ranged from 8010 to 6722 kWh depending on the scanner. The M1 (outpatient) scanner consumed 99.9 and 183.9 kWh/day in idle mode for weekdays and weekends, respectively, because the scanner spent 23% more time proportionally in idle mode on the weekends. Conclusions: A semi-automatic method for quantifying energy consumption characteristics of MRI scanners was introduced and validated. This method is relatively simple to implement as it requires only power data from the scanners and avoids the technical challenges associated with extracting and processing scanner log files. Finally, the methodology enables quantitative evaluation of the power, time, and energy characteristics of MRI scanners in scan and nonproductive system modes, providing baseline data and the capability of identifying potential opportunities for enhancing the energy efficiency of MRI scanners.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2022

Thermocouple Testing in Support of the AGR-5/6/7 Experiment

This report documents thermocouple testing performed in IRC Lab C-15 over a period of seven years. This testing supported selection and characterization of the thermocouple set used in the AGR-5/6/7 experiment. The following summary was taken directly from the report. Temperature measurement is a challenging aspect of very high temperature irradiation experiments because commonly used high-temperature commercial thermocouples such as platinum-rhodium (Types S, R, and B) and tungsten-rhenium (Type C), suffer dramatic drift because of neutron-induced transmutation. As a result, these types of thermocouples, which are used routinely for industrial temperature measurements outside of reactors, are used only in very special circumstances for reactor experiments. Conversely, because of their low neutron cross-sections, Type N thermocouples are affected to only a limited extent by neutron irradiation. However, the use of these nickel-based thermocouples is limited when the temperature exceeds 1050°C due to drift arising from minor alloying elements migrating from the thermocouple's metal sheath to the thermoelements. This change in the composition of the thermo-elements results in significant decalibration of the signal. The issues described above were recognized during the early planning stages of the final AGR experiment (designated AGR-5/6/7), and a thermocouple furnace testing program was performed over a seven-year period (2014-2019, 2021) to first select and then characterize the best thermocouple set for the high temperature regions of the AGR-5/6/7 irradiation experiment. The calculated temperature range of the AGR-5/6/7 experiment was 600–1500°C. For temperatures below 1000°C standard Type N thermocouples were deemed adequate. The furnace testing campaign identified two thermocouple types suitable for measuring temperatures above 1000°C, a Mo/Nb thermocouple developed at INL called HTIR-TC, and a Type N thermocouple developed by Cambridge University (called herein Cambridge Type N), which featured a custom high nickel alloy sheath. One of the original goals of the furnace testing program was to identify a thermocouple capable of low drift operation near the peak temperature expected in AGR-5/6/7, i.e., about 1400°C. The HTIR-TC design appeared promising in this regard, however a manufacturing difficulty proved to be a barrier and instead the furnace testing focused on drift performance at 1250°C. The manufacturing difficulty was that the Nb sheaths of the HTIR-TCs experienced extreme embrittlement when heat treated at 1600°C or greater. Heat treatment is needed to stabilize the emf output of this TC type, and the higher the heat treatment temperature the higher the peak temperature of stable operation. Because of the sheath embrittlement the heat treatment temperature had to be lowered to 1450°C resulting in a stable operating temperature of about 1250°C. One of the successes of the furnace testing program was identification of a shortcoming in the heat treatment procedure that had been traditionally used in the production of HTIR-TCs. The shortcoming was that the entire heated length of the HTIR-TC sensor was not being heat treated, but rather only the part of the sensor expected to experience temperatures above 1000°C. The problem manifested itself when the thermocouples were removed from the heat treat furnace and placed in another furnace with a different geometry, their indicated temperatures would be widely scattered, but mostly in the negative direction. The solution was to heat treat the entire heated length of the sensor. Since the deepest immersion depth in the AGR-5/6/7 experiment was about 40 inches, a heat treatment length of 48 inches was used. After this change was implemented, thermocouples which were moved into a new environment with a different temperature profile (i.e., a different furnace), produced accurate temperature measurements. Although assembly of the AGR-5/6/7 experiment was completed in September of 2017 (and irradiation begun in 2018), furnace testing of thermocouples continued in 2018 and 2019. The main purpose of this testing was to establish very long-term drift characteristics of the HTIR and Cambridge Type N thermocouples installed in the experiment. Representative thermocouples from the same lots as those installed in the AGR-5/6/7 experiment were used. Additionally, thermocouples of different designs, (particularly variations on the HTIR-TC design) were "piggy-backed" on this testing program to provide insights for instrumenting future very high temperature irradiation experiments. This two-year testing program demonstrated that HTIR-TCs and Cambridge Type N TCs could operate at 1250°C for up to 10,000 hrs (and in some cases longer) while experiencing negative drifts on the order of 2-4°C/1000 hrs. This performance was considered acceptable given the extreme operating environment the sensors faced.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2024

Extraction of Vibration Data with Imaging

To date, the primary sensing technology used to measure the vibration response has been accelerometers and strain gages mounted directly to the structure and using either wired or, more recently, wireless telemetry. Cost issues with these sensors and the associated data acquisition systems typically limit the numbers that are deployed on in situ structures. Although there are a few structures with larger sensing counts that in some cases exceed over 1000 sensors, more typical numbers range from ten to one hundred sensors resulting in low spatial resolution when they are applied to physically large systems. When one considers that nuclear power plant structures usually have complex geometries, material properties, connectivity and boundary conditions, it is clear these current approaches to vibration measurements can only provide limited information about a system’s dynamics response characteristics. As an alternative, many non-contact measurement technologies have emerged, including point wise measurement methods such as Global Positioning System (GPS), microwave interferometry, and laser Doppler vibrometry (LDV), as well as simultaneous full-field measurement methods such as electronic speckle pattern interferometry, holography interferometry, and muon tomography, some of which can provide high spatial resolution measurements. Among these methods, digital video imaging techniques have emerged as a feasible solution for full-field vibration measurements that provide significantly more detailed dynamic response information because every pixel becomes a measurement point. Furthermore, recent advances in image processing and computer vision algorithms have been successfully used to process video data for experimental and operational modal analysis. Such full-field measurements have the potential to significantly improve many current structural assessment procedures including system identification (modal parameter estimation), structural health monitoring, load reconstruction, model validation, and model updating. Furthermore, more recent full-field imaging techniques can be accomplished with relatively low-cost, commercially-available off-the-shelf cameras. However, these measurement procedures have other limitations that must be considered such as the ability to only measure visibly accessible points on a structure and a more limited dynamic range and bandwidth than can be achieved with accelerometers or strain gages.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2024

Phase-Slip Lines and Anomalous Josephson Effects in Tungsten Nanoscale Cluster-Based Topological Insulator Nanobridges: Implications for Topologically Protected Qubits and Quantum Sensors

Superconducting topological systems formed by a strong 3D topological insulator (TI) in proximity to a conventional s-wave superconductor (SC) have been intensely studied, as they may host Majorana zero modes. However, there are limited experimental realizations of TI-SC systems in which robust superconducting pairing is induced on the surface states of the TI and a topological superconducting state is established. Here, we fabricate a TI-SC system by depositing, via a focused ion beam, tungsten (W) nanoscale clusters on the surface of TI Bi 0.91 Sb 0.09 . We find that the resulting heterostructure supports phase-slip lines (PSLs) that act as effective Josephson junctions (JJs). Here, we probe the response of the system to microwave radiation. We find that for some ac frequencies, and powers, the resulting Shapiro steps’ structure of the voltage–current characteristic exhibits a missing first step and an unexpectedly wide second Shapiro step. The theoretical analysis of the measurements shows that the unusual Shapiro response arises from the interplay between a static JJ and a dynamic one and allows us to identify the conditions under which the missing first step can be attributed to the topological nature of the JJs formed by the PSLs. Our results suggest an approach to induce superconductivity in a TI, a route to realizing highly transparent topological JJs, and show how the response of superconducting systems to microwave radiation can be used to infer the dynamics of PSLs. Highly transparent topological junctions are promising candidates to realize vector field sensors with very high sensitivity. In addition, due to the nontrivial Berry phase of the TI’s surface states such junctions can be in a topological state which is ideal to create topologically protected qubits.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
DOE OSTI2020

Battery Monitoring System

The component that is powered by the battery pack being monitored is a valuable asset and must be in working condition at all times. Battery chemistry and characteristics have a major role in how to evaluate the state of the battery. The battery monitoring system has many parts that lead to an accurate battery reading. The components consist of a coulomb counting device, end of life voltage detection, a consideration of use for a real-time clock (RTC), temperature sensor, and non-volatile random-access memory (NVRAM). The combination of these elements allows the monitoring system to be highly reliant. Moving forward a better implementation of the ideas in this paper and further testing should ensure a high-quality battery monitoring system.

25 ENERGY STORAGE↗
DOE OSTI2025

Monitoring pipeline integrity of underground gas storage facilities using membrane-based electrochemical sensors

Effective monitoring of internal corrosion risk is crucial to ensuring the safety and longevity of natural gas pipeline infrastructure. While electrochemical sensors are commonly used to assess corrosion rates and corrosion indicators in aqueous fluids, they are rarely used in gas pipelines as these fluids lack the ionic conductivity needed for electrochemical measurements. The inclusion of ion-conductive membranes into electrochemical sensors can extend their functionality into humidified gas streams, providing critical information about emerging corrosion events that are common during withdrawal season in pipeline systems downstream from underground storage facilities. In parallel, new protective films, like those obtained through cold spray coating, are being developed to protect oil and gas pipelines and recover losses in structural integrity due to corrosion damage. Herein, we demonstrate how membrane-based electrochemical sensors (MBES) can be used to monitor fluid corrosivity by examining their response to changes in water content for a wide range of fluid compositions. It was found that MBES readings were highly sensitive to water content changes with membrane conductivity measurements varying from 10 –6 to 10 –1 S cm -1 , and corrosion rate measurements which varied from 10 –7 to 1 mm y -1 . Electron microscopy confirmed that the self-healing characteristics of metal coating films were still active despite their inclusion into an MBES probe. In conclusion, these findings indicate that membrane-based corrosion monitoring can be expanded to monitor coated-pipeline materials and provide early detection of emerging corrosion upsets relevant to underground gas storage facilities.

Electrochemical sensor↗
DOE OSTI2020

Revealing Three-Dimensional Morphology in Nanoporous Gold Using Three-Dimensional X-Ray Fresnel Coherent Diffractive Imaging Tomography

Nanoporous metals fabricated by dealloying have a unique bi-continuous, sponge-like porous structure with ultra-high surface area. The unique properties of these materials, especially nanoporous gold, have numerous potential applications in sensors and actuators and in energy-related applications such as catalytic materials, super-capacitors, and battery supports. The degree of porosity and size of the metal ligaments are critical parameters that determine many properties and thus govern the functionalities of nanoporous metals in many applications including energy storage and conversion. Additionally, we used Fresnel coherent diffractive imaging combined with tomographic reconstruction to quantify the nanoscale three-dimensional spatial distribution and homogeneity of the porosity and ligament size within a bulk sample of nanoporous gold. The average porosity and its standard deviation along the axial direction through the sample were determined, as well as the characteristic feature size and its standard deviation. The result shows that free corrosion is an effective way to create homogeneous nanoporous metals with sample sizes on the order of 1 µm.

36 MATERIALS SCIENCE↗
DOE OSTI2024

Monitoring of ground water table depth and soil moisture at the Point Reyes field site

Ground water table (GWT) depth and soil moisture (SM) have been monitored at several locations at the Point Reyes field site (Californian coastal grassland) from 2021 to 2024. Monitoring is still on-going and data may be added to this archive at later time. The SM data have been acquired using Teros 12 Meter soil moisture sensors placed at 10, 30, 60 and 90 cm depth at 5 locations along a small hillslope. These sensors also collect soil temperature and bulk conductance. In addition, some collocated sensors provide pore pressure and Photochemical Reflectance Index (PRI). The GWT depth has been inferred from various type of Onset pressure transducers. The pressure measurements have been corrected for atmospheric pressure variations and sensor position relative to the ground surface to infer GWT depth, as well as with RTK GPS data to infer GWT elevation. The GWT data have been acquired at 5 distinct locations from 2020 to 2024 with the sensors placed at about 4 m depth. In addition, GWT data has been acquired for the 2023-2024 period with sensors located in 1 m deep shallow wells installed near each deeper well. This data is intended to evaluate possibly different dynamic in shallow (perched) and deep aquifer. The datasets are all provided in csv format. Please note that the interpretation of the GWT data needs to be done with consideration of environmental and well characteristics at the site and uncertainty in various variables. For more information on GWT and SM data, please contact the author.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2025

A dedicated mirror-magnet experiment to study quench characteristics and dependencies in $Nb_{3}Sn$ coils and explore improvements of diagnostics capabilities

A single Nb3Sn short quadrupole coil in a mirror-magnet configuration was employed to investigate a wide range of phenomena and to serve as test-bed for diagnostics developments. A configurable array of spot-heaters was installed on the inner coil surface for control of induced quench conditions. Several different quench antenna arrays were positioned along the coil inner surface, and included significant sensor overlap for assessment of their relative efficiency and operation. Multiple acoustic sensors were placed on the pole and at coil ends. Optical fibers in grid configurations were put in different places on the coil and magnet for strain assessment, along with standard resistive strain gauges. Current spikes in the magnet circuit were monitored. This plethora of instrumentation aimed to support investigations on induced and spontaneous quenches, among other goals, and was supplemented by standard voltage-tap-based measurements. Voltage tap data of induced quenches from various spot-heater configurations was investigated for similarities to voltage development in spontaneous quenches. Quench antennas provided insights about current redistribution in the quenching coil and coil splices. The Quench Current-boosting Device was applied and the effect on coil training examined. This paper describes motivations behind the research, the overall test setup and main results.

Stoynev, Stoyan [Fermilab]↗
DOE OSTI2024

Observing low-altitude features in ozone concentrations in a shoreline environment via uncrewed aerial systems

Abstract. Ozone is a pollutant formed in the atmosphere by photochemical processes involving nitrogen oxides (NOx) and volatile organic compounds (VOCs) when exposed to sunlight. Tropospheric boundary layer ozone is regularly measured at ground stations and sampled infrequently through balloon, lidar, and crewed aircraft platforms, which have demonstrated characteristic patterns with altitude. Here, to better resolve vertical profiles of ozone within the atmospheric boundary layer, we developed and evaluated an uncrewed aircraft system (UAS) platform for measuring ozone and meteorological parameters of temperature, pressure, and humidity. To evaluate this approach, a UAS was flown with a portable ozone monitor and a meteorological temperature and humidity sensor to compare to tall tower measurements in northern Wisconsin. In June 2020, as a part of the WiscoDISCO20 campaign, a DJI M600 hexacopter UAS was flown with the same sensors to measure Lake Michigan shoreline ozone concentrations. This latter UAS experiment revealed a low-altitude structure in ozone concentrations in a shoreline environment showing the highest ozone at altitudes from 20–100 m a.g.l. These first such measurements of low-altitude ozone via a UAS in the Great Lakes region revealed a very shallow layer of ozone-rich air lying above the surface.

Meteorology & Atmospheric Sciences↗