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At least 487 records · Page 27
All sourcesNASA NTRSDOE OSTI
DOE OSTI2026

Why Firn Quakes

Snow dampens sounds, but anecdotal reports concisely describe audible propagating collapse events—firnquakes—in Antarctic and Arctic snowfields. We propose combining granular and continuum mechanics to form a testable theory for conditioning, triggering, and propagation of firnquakes consistent with scarce data. A central condition for collapse events is unconsolidated firn at depth. As firn grains compact, stresses are transmitted along force chains which carry the overburden and transition into a continuous medium by pressure sintering. This granular legacy creates solid-like supports of denser layers that keep the material below unconsolidated. Dynamic amplification triggers local brittle failure of the supports, which induces a cascade of collapse propagation. Using bulk density from ice cores as proxy for stiffness, we find the flexural wave speed by collapsing supports matches the recorded firnquake velocities on the order of 100 m/s. Our theory is to be tested in firn sheets and other compacting granular materials.

Voigtländer, A. [Lawrence Berkeley National Labora↗
DOE OSTI2023

Superconductivity and magnetic and transport properties of single-crystalline CaK ( Fe 1 – x Cr x ) 4 As 4

Members of the CaK (Fe 1–x Cr x ) 4 As 4 series have been synthesized by high-temperature solution growth in single-crystalline form and characterized by x-ray diffraction, elemental analysis, and magnetic and transport measurements. The effects of Cr substitution on the superconducting and magnetic ground states of CaKFe 4 As 4 (T c = 35 K) have been studied. These measurements show that the superconducting transition temperature decreases monotonically and is finally suppressed below 1.8 K as x is increased from 0 to 0.038. For x-values greater than 0.012, signatures of a magnetic transition can be detected in magnetic measurements with the associated features in the transport measurements becoming detectable for x ≥ 0.038. The magnetic transition temperature increases in a roughly linear manner as Cr substitution increases. A temperature-composition (T – x) phase diagram is constructed, revealing a half-dome of superconductivity with the magnetic transition temperature, T*, appearing near 22 K for x ~ 0.017 and rising slowly up to 60 K for x ~ 0.077. The T – x phase diagrams for CaK (Fe 1–x T x ) 4 As 4 for T = Cr and Mn are essentially the same despite the nominally different band filling; this is in marked contrast to T = Co and Ni series for which the T – x diagrams scale by a factor of 2, consistent with the different changes in band filling Co and Ni would produce when replacing Fe. Superconductivity of CaK (Fe 1–x Cr x ) 4 As 4 is also studied as a function of magnetic field. A clear change in $H^{'}_{c2}$ (T)/T c , where $H^{'}_{c2}$ (T) is dH c2 (T)/dT, at x ~ 0.012 is observed and probably is related to a change of the Fermi surface due to magnetic order. Further, coherence length and the London penetration depths are also calculated based on H c1 and H c2 data. Both of them as a function of x show changes near x = 0.012, again consistent with Fermi surface changes associated with the magnetic ordering seen for higher x-values.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
DOE OSTI2024

Lightning and Radar Measures of Mixed-Phase Updraft Variability in Tracked Storms during the TRACER Field Campaign in Houston, Texas

Properties of 7488 thunderstorms are summarized for June–September 2022 during the Tracking Aerosol Convection Interactions Experiment (TRACER) field campaign Houston, Texas, using polarimetric weather radar and VHF 3D Lightning Mapping Array data. Automated tracking of storms linked each instrument’s measurements to a data-defined, time-evolving storm footprint. Within each storm, the depth and magnitude of episodic columns of radar differential reflectivity and specific differential phase quantified the prevalence of updrafts that activated mixed-phase precipitation pathways. Lightning measurements further distinguished the degree of rimed precipitation formation: the fraction of tracks with lightning varied from day to day and cells with lightning had stronger polarimetric columns. Track-level correlation of the lightning flash rate with radar polarimetric measures had substantial spread, showing that lightning provides an additional signal of mixed-phase precipitation processes that can complement future studies of thermodynamic and aerosol controls on cloud microphysics in the Houston region.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2020

Technical Gaps in Hanford High-Level Waste Solids Settling Behavior and Settling Time Evaluation for Direct Feed High-Level Waste (DFHLW) Operations

Settling of high-level waste (HLW) solids in process vessels is a key conceptual process step in providing HLW feed directly to the Hanford Waste Treatment and Immobilization Plant (WTP) HLW Vitrification Facility. Direct Feed High-Level Waste (DFHLW) is a potential approach to initiating HLW vitrification prior to completing of the WTP Pretreatment Facility. Settling would be used with subsequent supernatant decant to concentrate HLW feed. To support planning for DFHLW, Washington River Protection Solutions (WRPS) requested support from the Pacific Northwest National Laboratory to evaluate the current data set available to predict the time needed for HLW solids to settle, to identify gaps in the understanding and predictive capability of HLW solids waste settling times, and to provide scoping estimates of the potential settling time. Eight technical gaps were identified for predicting settling times and characteristics of the formed sediment layers including: Gap 1: In-Tank Settling Rates Faster than Settling of Laboratory Samples, Gap 2: Effect of Sludge Leaching/Washing on Predicted Settling Times, Gap 3: Predicting Waste Settling from Waste Chemistry (Waste Type), Gap 4: Predicting Waste Settling from Particle Size and Density Distributions (PSDDs), Gap 5: Insufficient Laboratory and In-Tank Settling Data to Represent Hanford Waste, Gap 6: Methods for Real-Time, In-Tank Tracking of Settling, Gap 7: Prediction of Sediment Erosion Resistance as a Function of Settling Time, and Gap 8: Prediction of Sediment Solids Content as a Function of Settling Time. In addition to the data gaps, an overarching observation of the settling rate and settled layer data is the significant variation in behavior. At similar solids concentrations, settling rates can vary by as much as 3 orders of magnitude depending on the source waste tank, and significantly different settling rates are noted between laboratory and in situ tests for the same waste tank. The range of average solids concentration in existing HLW sediment, which may have been quiescent for decades, can vary from less than 7 wt% to greater than 74 wt% solids. The shear strengths (or yield stresses) measured on laboratory samples range from less than 27 Pa to greater than 6400 Pa. These variations can challenge process planning for the application of a settle/decant process for DFHLW. This report describes the significance of the gaps to the settle/decant process and presents uncertainties by way of examples. Potential technical approaches for resolving these gaps are described and the estimated difficulty in resolving these gaps is evaluated. Based on the significance of the gap and the difficulty of resolution, recommendations are made to address specific gaps. Scoping estimates of the potential settling times for DFHLW solids have been made based on the existing data set with its associated gaps. Depending on the process vessel depth and final sediment concentration, substantial fractions of the scoping estimate results for settling times for characterized HLW exceed the 2-week period that has been previously assumed for process planning. There is also significant disparity, potentially greater than a factor of 5000 difference, in the estimated settling times depending on process vessel depth and final sediment solid concentration. This variation in results underscores the significance of the identified gaps and uncertainties with respect to process planning for utilizing settle/decant operations for DFHLW.

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗
DOE OSTI2024

GEESS as a Mechanism to Facilitate the Commercialization of Geologic Carbon Sequestration

This is a presentation featuring an overview of the Geoanalytical Economic Evaluation of Saline Storage (GEESS) project and latest results. The GEESS project has worked towards characterizing 57 geologic saline formations targeted for geologic carbon sequestration (GCS) using publicly available datasets. The GEESS system consists of high spatial resolution datasets (up to a 5 km grid spacing) that characterize critical geologic parameters such as depth, thickness, porosity, permeability, fracture pressure, and more. Further, GEESS geologic data were exercised using the FECM/NETL Saline Storage Cost Model (CO2_S_COM) to estimate CO2 plume sizes and the first-year break-even price of CO2 at the grid point level. GEESS is now available on NETL’s Energy Data Exchange (EDX).

Eppink, Jeffrey↗
DOE OSTI2020

Concrete Structure Health Monitoring Using Vibro-acoustic Testing and Machine Learning

Assessment and management of aging concrete structures in nuclear power plants require a more systematic approach than simple reliance on margins of safety in existing codes. Research is required to deploy online monitoring capability to assess the health of concrete structures in nuclear power plants and perform predictive analytics based on heterogeneous measurements, in order to reduce the operation and maintenance costs. The research effort described in this report focuses on the health monitoring of concrete slabs containing reactive aggregates using the vibro-acoustic modulation (VAM) technique and predictive modeling. The research is developing an approach to enable detection, localization, and estimation of the extent of degradation in concrete slabs due to alkali-silica reaction (ASR). The project outcomes are generic and extendable to other degradation modes in concrete. A concrete slab without reinforcements was cast at Vanderbilt University and cured in aggressive conditions to accelerate ASR degradation. In this report, we develop a methodology for the automation of VAM testing, and the construction of machine learning models to facilitate damage localization in concrete structures. We investigate how machine learning models based on physics simulation data can be effectively utilized for damage localization (damage location and depth) and estimation in a concrete slab specimen. Our study indicates that these models could potentially support damage localization and estimation for NPP structures.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2020

Spectral Variability of VHS J1256–1257b from 1 to 5 μm

Multiwavelength time-resolved observations of rotationally modulated variability from brown dwarfs and giant exoplanets are the most effective method for constraining their heterogeneous atmospheric structures. In a companion paper, we reported the discovery of strong near-infrared variability in HST/WFC3/G141 light curves of the very red L-dwarf companion VHS J1256–1257b. In this paper, we present a follow-up 36 hr Spitzer/IRAC Channel 2 light curve together with an in-depth analysis of the Hubble space telescope (HST) and the Spitzer data. The combined data set provides time-resolved light curves of VHS1256b sampling 1.1 to 4.5 μm. The Spitzer light curve is best fit with a single sine wave with a period of 22.04 ± 0.05 hr and a peak-to-peak amplitude of 5.76 ± 0.04%. Combining the period with a previously measured projected rotational velocity (v sin i), we find that VHS1256b is most consistent with equatorial viewing geometry. The HST/G141+Spitzer spectral energy distribution favors a model with a T{sub eff} of 1000 K and low surface gravity with disequilibrium chemistry. The spectral variability of VHS1256b is consistent with predictions from partly cloudy models, suggesting that heterogeneous clouds are the dominant source of the observed modulations. We find evidence at the 3.3σ level for amplitude variations within the 1.67 μm CH{sub 4} band, which is the first such detection for a variable L-dwarf. We compare the HST/G141 time-resolved spectra of three red L-dwarfs with high-amplitude near-infrared rotational modulations and find that although their time-averaged spectra are similar, their spectroscopic variabilities exhibit notable differences. This diversity reinforces the advantage of time-resolved spectroscopic observations for understanding the atmospheres of brown dwarfs and directly imaged exoplanets.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2024

Yet Another Sunshine Mystery: Unexpected Asymmetry in GeV Emission from the Solar Disk

The Sun is one of the most luminous γ-ray sources in the sky and continues to challenge our understanding of its high-energy emission mechanisms. This study provides an in-depth investigation of the solar disk γ-ray emission, using data from the Fermi Large Area Telescope spanning 2008 August to 2022 January. We focus on γ-ray events with energies exceeding 5 GeV, originating from 0°5 angular aperture centered on the Sun, and implement stringent time cuts to minimize potential sample contaminants. We use a helioprojection method to resolve the γ-ray events relative to the solar rotation axes and combine statistical tests to investigate the distribution of events over the solar disk. We found that integrating observations over large time windows may overlook relevant asymmetrical features, which we reveal in this work through a refined time-dependent morphological analysis. We describe significant anisotropic trends and confirm compelling evidence of energy-dependent asymmetry in the solar disk γ-ray emission. Intriguingly, the asymmetric signature coincides with the Sun's polar field flip during the cycle 24 solar maximum, around 2014 June. Our findings suggest that the Sun's magnetic configuration plays a significant role in shaping the resulting γ-ray signature, highlighting a potential link between the observed anisotropies, solar cycle, and the solar magnetic fields. These insights pose substantial challenges to established emission models, prompting fresh perspectives on high-energy solar astrophysics.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2021

mfrsr7nchaod1mich

The mfraod vap takes data from the mfrsr7nch datastream and calculations total and aerosol optical depths, plus auxiliary fields.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2024

Constraining models for the origin of ultra-high-energy cosmic rays with a novel combined analysis of arrival directions, spectrum, and composition data measured at the Pierre Auger Observatory

The combined fit of the measured energy spectrum and shower maximum depth distributions of ultra-high-energy cosmic rays is known to constrain the parameters of astrophysical models with homogeneous source distributions. Studies of the distribution of the cosmic-ray arrival directions show a better agreement with models in which a fraction of the flux is non-isotropic and associated with the nearby radio galaxy Centaurus A or with catalogs such as that of starburst galaxies. Here, we present a novel combination of both analyses by a simultaneous fit of arrival directions, energy spectrum, and composition data measured at the Pierre Auger Observatory. The model takes into account a rigidity-dependent magnetic field blurring and an energy-dependent evolution of the catalog contribution shaped by interactions during propagation. We find that a model containing a flux contribution from the starburst galaxy catalog of around 20% at 40 EeV with a magnetic field blurring of around 20° for a rigidity of 10 EV provides a fair simultaneous description of all three observables. The starburst galaxy model is favored with a significance of 4.5σ (considering experimental systematic effects) compared to a reference model with only homogeneously distributed background sources. By investigating a scenario with Centaurus A as a single source in combination with the homogeneous background, we confirm that this region of the sky provides the dominant contribution to the observed anisotropy signal. Models containing a catalog of jetted active galactic nuclei whose flux scales with the γ-ray emission are, however, disfavored as they cannot adequately describe the measured arrival directions.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2020

Comparison of four learning-based methods for predicting groundwater redox status

Knowing the location where groundwater denitrification occurs, or by proxy the groundwater redox status (oxic, mixed, and anoxic), is valuable information for assessing and managing potential agricultural land-use impacts on freshwater quality. We compare the efficacy of supervised (Linear Discriminant Analysis LDA; Boosted Regression Trees, BRT; and Random Forest, RF) and unsupervised (Modified Self-Organizing Map, MSOM) learning-based methods to predict groundwater redox status in the agriculturally dominated Tasman, Waikato, and Wellington regions of New Zealand. Thresholds applied to regional groundwater-quality samples provide redox status variables and learn heuristics constrained by these variables and applied to spatial factors (climate, elevation, geologic, hydrology soils, and well depth) identify optimal sets of regional predictor variables. A split-sample approach is used to train and test the learning methods ability to predict redox status using the optimal predictor variables. Overall, the supervised methods demonstrate a prediction bias toward oxic conditions and inability to perform statistically well when using independent regional data; for example, consider kappa statistics for BRT (Tasman: 0.42, Waikato: 0.38, Wellington: 0.17), RF (Tasman: 0.42, Waikato: 0.47, Wellington: 0.17 and LDA (Tasman: 0.46, Waikato: 0.32, Wellington: 0.17). By contrast, the unsupervised method performs statistically well when predicting oxic, mixed, and anoxic conditions and corresponding depths when using independent regional data; for example, consider MSOM kappa statistics for Tasman: 0.78, Waikato: 0.80, Wellington: 0.76. The unsupervised learning method provides the added benefits of being (1) able to combine predictions into 3D regional anoxic probability plots for interpreting the spatial influence of paleosols and groundwater flowpaths on redox status, and (2) readily extended to map 3D redox status across New Zealand and other countries despite data bias and sparsity.

machine learning algorithms, Random Forest, booste↗
DOE OSTI2022

Structural Characterization of a Toppling Rock Slab From Array-Based Ambient Vibration Measurements and Numerical Modal Analysis

Accurate assessments of the internal structure and boundary conditions of unstable rock slopes are imperative for evaluating landslide hazard scenarios. However, instability characterization at depth remains challenging and is often limited by costly or invasive subsurface investigations. Here, we develop a new approach coupling array-based ambient vibration modal analysis and numerical modeling to improve structural characterization of rock slope instabilities at depth. We used ambient noise cross-correlation on 4 hr of seismic data recorded by an array of 30 nodal geophones at a 500-m-long toppling rock slab in Utah, USA to identify modal frequencies between 0.8 and 3.5 Hz and derive modal displacements. We show that transverse and longitudinal bending modes span the length of the instability, indicating an interconnected slab. Further, statistical comparison of field results with outputs from >1,000 finite element models with varying boundary conditions showed that the instability depth varies between 40–70 and 10–20 m in the middle and lateral regions, respectively. Our approach yields new information on the structural conditions of rock cliff and column instabilities at depth, which is not easily obtained by other means but is imperative for change detection monitoring and improved hazard assessments.

58 GEOSCIENCES↗
DOE OSTI2022

Third data release of the Hyper Suprime-Cam Subaru Strategic Program

This work presents the third data release of the Hyper Suprime-Cam Subaru Strategic Program (HSC-SSP), a wide-field multi-band imaging survey with the Subaru 8.2 m telescope. HSC-SSP has three survey layers (Wide, Deep, and UltraDeep) with different area coverages and depths, designed to address a wide array of astrophysical questions. This third release from HSC-SSP includes data from 278 nights of observing time and covers about 670 deg 2 in all five broad-band filters (grizy) at the full depth (~26 mag at 5σ depending on filter) in the Wide layer. If we include partially observed areas, the release covers 1470 deg 2 . The Deep and UltraDeep layers have ~80% of the originally planned integration times, and are considered done, as we have slightly changed the observing strategy in order to compensate for various time losses. There are a number of updates in the image processing pipeline. Of particular importance is the change in the sky subtraction algorithm; we subtract the sky on small scales before the detection and measurement stages, which has significantly reduced the number of false detections. Thanks to this and other updates, the overall quality of the processed data has improved since the previous release. However, there are limitations in the data (for example, the pipeline is not optimized for crowded fields), and we encourage the user to check the quality assurance plots as well as a list of known issues before exploiting the data. The data release website is https://hsc-release.mtk.nao.ac.jp.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2023

NEWTS Well Summary by Hydrologic Regions and Subbasins in the U.S.

Oil and gas well production data (2000-2022), including water production and injection, as well as summary information (e.g., well count by status, total vertical depth statistics, etc.) spatially summarized by Watershed Boundary Dataset's (WBD) region (Hydrologic Unit Code (HUC) 2) and subbasin (HUC8). Energy-related produced waters data were acquired and summarized in support of the development of the National Energy Technology Laboratory's NEWTS (National Energy Water Treatment and Speciation Database). Due to the proprietary nature of the wellbore data, this derived product has been spatially compiled by key areas to support research and stakeholder needs.

Energy Infrastructure↗
DOE OSTI2021

A Unified User-Friendly Instrument Control and Data Acquisition System for the ORNL SANS Instrument Suite

In an effort to upgrade and provide a unified and improved instrument control and data acquisition system for the Oak Ridge National Laboratory (ORNL) small-angle neutron scattering (SANS) instrument suite—biological small-angle neutron scattering instrument (Bio-SANS), the extended q-range small-angle neutron scattering diffractometer (EQ-SANS), the general-purpose small-angle neutron scattering diffractometer (GP-SANS)—beamline scientists and developers teamed up and worked closely together to design and develop a new system. We began with an in-depth analysis of user needs and requirements, covering all perspectives of control and data acquisition based on previous usage data and user feedback. Our design and implementation were guided by the principles from the latest user experience and design research and based on effective practices from our previous projects. In this article, we share details of our design process as well as prominent features of the new instrument control and data acquisition system. The new system provides a sophisticated Q-Range Planner to help scientists and users plan and execute instrument configurations easily and efficiently. The system also provides different user operation interfaces, such as wizard-type tool Panel Scan, a Scripting Tool based on Python Language, and Table Scan, all of which are tailored to different user needs. The new system further captures all the metadata to enable post-experiment data reduction and possibly automatic reduction and provides users with enhanced live displays and additional feedback at the run time. We hope our results will serve as a good example for developing a user-friendly instrument control and data acquisition system at large user facilities.

47 OTHER INSTRUMENTATION↗
DOE OSTI2020

Lensinglike tensions in the Planck legacy release

We analyze the final release of the Planck satellite data to constrain the gravitational lensing potential in a model-independent manner. The amount of lensing determined from the smoothing of the acoustic peaks in the temperature and polarization power spectra is 2σ too high when compared with the measurements using the lensing reconstruction and 2.8σ too high when compared with Λ CDM expectation based on the "unlensed" portion of the temperature and polarization power spectra. The largest change from the previous data release is the Λ CDM expectation, driven by improved constraints to the optical depth to reionization. Here, the anomaly still is inconsistent with actual gravitational lensing, given that the lensing reconstruction constraints are discrepant independent of the model. Within the context of Λ CDM, improvements in its parameter constraints from lensing reconstruction bring this tension to 2.1σ and from further adding baryon acoustic oscillation and Pantheon supernova data to a marginally higher 2.2σ. Once these other measurements are included, marginalizing this lensing-like anomaly cannot substantially resolve tensions with low-redshift measurements of H 0 and S 8 in Λ CDM, Λ CDM + N eff or ΛCDM + Σm ν ; furthermore the artificial strengthening of constraints on Σm ν is less than 20%.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2026

Meteorological and Soil Data from Ecohydrology Sensor Towers at Pump House and Snodgrass Mountain in East River Watershed, Colorado, 2019-2025

This data package includes hourly meteorological and soil sensor data at eight ecohydrology monitoring sites in East River Watershed, Colorado as part of the Watershed Function Scientific Focus Area (WFSFA) research led by Lawrence Berkeley National Lab (LBNL). Four field sites were located on the hillslope of East River (ER) near Pump House (PH) at Mount Crested Butte (ER-PHS1 to 4), and the other four are in the Snodgrass Mountain (SG) area (SG-EHS5 to 8). In terms of vegetation cover, three sites are in montane grasslands (ER-PHS1, ER-PHS2, and SG-EHS5), three are below evergreen conifer canopy (ER-PHS3, SG-EHS6, and SG-EHS7), and two are below deciduous aspen canopy (ER-PHS4 and SG-EHS8). The monitoring period began in October 2019 at the East River sites, in October 2020 at SG-EHS5 and SG-EHS6, and in October 2021 at SG-EHS7 and SG-EHS8. In September 2024, all four East River sites were fully retired. The four Snodgrass Mountain sites remain active. Each site is equipped with a comprehensive suite of meteorological sensors on a tripod and soil sensors that measure weather, energy fluxes, and soil variables. This data package includes measurements from ten different types of sensors and up to thirteen individual sensors per site, including (1) a weather station (measurement height ranges from 2.8~3.8 meters (m) above ground), (2) a quantum sensor for photosynthetic active radiation (PAR) (2.4~3.3m), (3) a net radiometer (1.7~2.1m), (4) an infrared radiometer (1.6~2.2m), (5) a sonic distance sensor (1.5~1.9m), (6) a soil carbon dioxide (CO2) flux chamber (0m), (7) a soil heat flux plate (-0.05m below ground), (8) a soil oxygen sensor (-0.3m), (9) a soil water potential sensor (-0.3m), and (10) soil water content sensors at 3~4 depths (-1.15 ~ -0.1m). A total of twenty-three variables is reported in this data package, including (1) atmospheric variables: air temperature (TA), atmospheric pressure (PA), vapor pressure (VP), and vapor pressure deficit (VPD), (2) precipitation variables: rain precipitation (P) and snow depth (D_SNOW), (3) energy fluxes variables: four-component net radiation (NETRAD) (shortwave/longwave incoming/outgoing radiation, SW_IN, SW_OUT, LW_IN, LW_OUT), photosynthetic photon flux density (PPFD), and soil heat flux (G), (4) soil variables: soil water content (SWC), soil water potential (SWP), soil temperature (TS), soil bulk electrical conductivity (COND_SOIL), and soil gaseous oxygen concentration (O2_SOIL), (5) wind variables: two-dimensional wind speed (WS), gust speed (WS_MAX), and wind direction (WD), and (6) surface variables: surface infrared temperature (T_CANOPY) and soil CO2 flux (CO2_SOIL). Please see the Methods section for data processing and QA/QC steps taken to generate the hourly datasets. The following files are included in this data package (notes on version: v{x}-{y}, where x is the metadata version, and y is the data version, when applicable): (1) “metadata_site_v{x}-{y}.csv” - a site metadata file that summarizes location information of all sites, including site ID, description, coordinates, timeframe, elevation, and vegetation cover, (2) “metadata_instrument_v{x}-{y}.csv” - an instrument metadata file that summarizes sensor information of all sites, including sensor manufacturer and model, measurement height, and sampling and averaging interval of all variables, (3) "data_{SITE_ID}_v{x}-{y}.csv" - eight data files that contain hourly data of each site indicated by {SITE_ID} in the filename, (4) “/figure/data_{SITE_ID}_v{x}-{y}.png" - eight figures that help visualize data of each site indicated by {SITE_ID} in the filename, (5) “/photo/*” - photos of each site indicated by {SITE_ID} in the filename, and (6) four file level metadata (flmd.csv) and data dictionary (*_dd.csv) files that summarize file, header, column, and variable information of all files. Notes: (1) Measurement height: Each variable name is followed by conventional positional qualifiers “H_V_R”, where H indicates the relative horizontal positions of that specific variable, V the vertical positions, and R the replicates. In this data package, only the vertical qualifier V varies, and V increases from the highest vertical position (V=1) to the lowest. Variables with the same qualifier are not necessarily measured by the same sensor, and the same variable with the same qualifier across different sites are not necessarily measured at the same height. Please refer to “metadata_instrument.csv” for the sensor information and measurement heights, and whether a variable is measured below the canopy. (2) Variable availability: Snow depth is not available at ER-PHS3 and SG-EHS7. SWC, soil temperature, and soil bulk EC at the deepest depth (<-1m) are not available at SG-EHS6 and SG-EHS7. The missing value code for numeric variables is -9999, except for SWP. For SWP, the missing value code is +9999, because SWP values are negative. (3) Sampling frequency: Please refer to “metadata_instrument.csv” for the increase of sampling frequency of some variables from 30-min to 1-min at ER-PHS1 to 4 in July 2020. (4) Sensors: While the methods of each sensor are not detailed, all sensors are commercially available, and their methods can be found in their manuals. Please refer to “metadata_instrument.csv” for the sensor manufacturer and model information. This work was supported by the Watershed Function Science Focus Area at Lawrence Berkeley National Laboratory funded by the US Department of Energy, Office of Science, Biological and Environmental Research under Contract No. DE-AC02-05CH11231.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2022

Date Release Report for Large Surface Explosion Coupling Experiment (LSECE) Nevada National Security Site

The DTRA sponsored 2020-2022 Large Surface Explosion Coupling Experiment (LSECE) consists of two large ground surface chemical explosions, data collection, analysis and modeling carried out in 2020-2022. The LSECE chemical explosions were carried out at the site of prior NNSA sponsored buried chemical explosions that were part of the Source Physics Experiment (SPE) Phase II in Dry Alluvium Geology (DAG). This report described the data collected under LSECE that is being made publicly available. The prior buried explosion DAG data are described in a separate report (https://www.osti.gov/biblio/1825534) and are also publicly available. The LSECE explosions, data analysis and numerical modeling work sponsored by DTRA were intended to address three objectives: 1) Generate seismo-acoustic data to test and improve numerical models of explosion energy coupling in dry alluvium geology; 2) To improve seismo-acoustic yield estimation techniques as a function of depth and medium properties; 3) To study and improve acoustic propagation modeling under two different atmospheric conditions. The LSECE data that were collected have expanded the prior DAG buried explosion dataset to include surface chemical explosions recorded on a common set of seismo-acoustic stations. They have allowed a more detailed study of above and below surface seismo-acoustic energy coupling with applications to explosion monitoring and assessment. The two approximately 1-ton TNT equivalent yield LSECE explosions were detonated at different times of the day to explore the effects of the different atmospheric conditions. The first chemical explosion “Artemis” was conducted before dawn when temperature inversions were present. The second chemical explosion “Apollo” was conducted on a sunny afternoon when the temperature gradient was more linear. The LSECE chemical explosion data were also collected across a variety of different sensor types to allow evaluation of their effectiveness in recovering useful information. The LSECE instrumentation included fiber optic or Distributed Acoustic Sensing (DAS), a dense array or Large-N array of seismometers, borehole accelerometers, DAS and a velocity meter, airborne acoustic instruments and a variety of visual and remote sensing data.

58 GEOSCIENCES↗