Engineering Papers⌕ Search

SEARCH · Engineering Papers

Results for “depth”

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.

Quote a phrase for an exact phrase match. Source license links do not imply unrestricted reuse.

At least 739 records · Page 41
All sourcesNASA NTRSDOE OSTI
DOE OSTI2025

Groundwater table elevation and temperature from 2015 to 2024 at the Lower Montane site in the East River Watershed, Colorado.

This groundwater level elevation and temperature data package is aimed at improving the predictive understanding of hydro-biogeochemical processes at the lower montane site in the East River Watershed, Colorado. The dataset is obtained using pressure transducers placed in shallow wells in the floodplain. This dataset contains data from wells with Location ID's ER-DOW (alias DO1West), ER-DOE (alias DO2East), ER-MBA1 (alias M1Bend1), ER-MBA2 (alias M1Bend2), ER-UPW (alias UP1West), ER-UPM (alias UP2), ER-UPE (alias UP3East). Another dataset contains the data from wells with Location ID's ER-CPA1 to ER-CPA6. Each file contains the water level elevation and the water temperature. Water level elevation has been obtained using the barometric pressure from the pressure transducer (Hobos sensor) in the well, barometric pressure from a sensor in air located at the same site (lower montane), depth from top-of-casing (TOC) to sensor measurement point, and TOC elevation. Data have been checked with a few measurements of water table depths. A real-time kinematic (RTK) global positioning system (GPS) has been used to survey the TOC (data in file Well_Location.csv). The water level elevation is given in UTM13N Geoid2012AB. While depth to water level is not present in the data files, it can be easily calculated with the TOC and distance to ground provided in the GPS coordinate file. The dataset quality is discussed in Collection/Analysis section of the methods. Time-series of measurements were initially added to the archive for the period 2015 to 2019, and later updated with time-series until 2024 (end of data collection). The dataset contains 8 *.csv data files, and 3 *.csv metadata files. Feel free to contact the author with any questions or collaboration interests. The publication year was updated from "2020" to "2025" to reflect the revised version of this dataset.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2025

Groundwater table elevation and temperature from 2015 to 2024 across Meander C at the Lower Montane site in the East River Watershed, Colorado.

This groundwater level elevation and temperature data package is aimed at improving the predictive understanding of hydro-biogeochemical processes at the lower montane site in the East River Watershed, Colorado. The dataset is obtained using pressure transducers placed in shallow wells in the floodplain. This dataset contains data from wells ER-CPA1 to ER-CPA6. Another dataset contains the data from wells at nearby Locations. Each file contains the water level elevation and the water temperature. Water level elevation has been obtained using the barometric pressure from the pressure transducer (Hobos sensor) in the well, barometric pressure from a sensor in air located at the same site (lower montane), depth from top-of-casing (TOC) to sensor measurement point, and TOC elevation. Data have been checked with a few measurements of water table depths. A real-time kinematic (RTK) global positioning system (GPS) has been used to survey the TOC (data in file Well_Location.csv). The water level elevation is given in UTM13N Geoid2012AB. While depth to water level is not present in the data files, it can be easily calculated with the TOC and distance to ground provided in the GPS coordinate file. The dataset quality is discussed in Collection/Analysis section of the methods. Time-series of measurements were initially added to the archive for the period 2015 to 2019, and later updated with time-series until 2024 (end of data collection). The dataset contains 7 *.csv data files, and 3 *.csv metadata files. Feel free to contact the author with any questions or collaboration interests. The publication year was updated from "2020" to "2025" to reflect the revised version of this dataset.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2020

Soil Environmental Conditions in the East River Watershed, CO

This dataset contains depth-resolved soil environmental variables collected between June 2016 and October 2018 from the Bradley Meadow site in the East River watershed. Datalogger output from 7 Campbell CS655 12 cm Soil Moisture and Temperature Sensors including depth, temperature, volumetric water content, and electrical conductivity are included in ‘BM_Merged_T_VWC_0616_10_18.csv’. Sensors were installed in June 2016. Data have been processed to merge raw sensor data and to remove additional variables. No additional QA/QC was performed. Measured pCO2 and depth are contained in ‘BM_EGM_WELL_CO2.csv’. These data represent gas well samples measured via injection using a PP Systems EGM-5 infra-red gas analyzer as described in the methods section. Measured CO2 surface flux values are contained in 'BM_EGM_Surface_Flux.csv'. These were measured using the PP Systems EGM-5 with the Soil Respiration Chamber attachment. Multiple reps are reported for each measurement including CO2 flux rate calculations using built-in linear and quadratic function methods, and average and standard deviations are taken across all reps and calculation methods.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2020

Hydrologic Model Files (PRMS) for Historical Conditions in the East River Watershed, Colorado between 1987-2019

The data package contains model input and output file for the East River watershed (85 km2) located in the headwaters of the Colorado River. The model is the U.S. Geological Survey (USGS) Precipitation-Modeling Runoff System (PRMS) for the historical, or baseline, condition (1987-2019) to assess the efficiency of summer monsoon rains to generate streamflow. The finite difference grid resolution is 100 m with elevations resampled from the USGS National Elevation Dataset. LANDFIRE raster data is used to derive parameters of dominant cover type, summer and winter cover density, canopy interception characteristics for snow and rain and transmission coefficient for shortwave radiation. Climate forcing uses minimum and maximum daily temperature lapse rates defined by the two Snow Telemetry (SNOTEL) stations located in the vicinity of the East River adjusted for aspect. Schofield SNOTEL snowfall is spatially distributed using LiDAR derived snow depth observations from the Airborne Snow Observatory (ASO) flown 4 April 2016. Snow depths are converted to snow water equivalent based on ground surveys and density modeling. Rainfall is spatially distributed using the monthly Parameter-elevation Relationships on Independent Slopes Model 30-year monthly averages. Simulated solar radiation is calibrated to match weather station observations. Model verification of snow water equivalent (SWE) accumulation and ablation relies on the 2018 and 2019 ASO maps and weather station snow depth. The data package contains model input files in text format, model documentation in pfd and a readme.txt file to help users understand the file structure to run the program.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2021

Bedrock weathering rates, reactive nitrogen influxes and effluxes, and nitrous oxide emissions rates from the Pumphouse Hillslope, East River Watershed, Colorado

Atmospheric nitrous oxide contributes directly to global warming, yet models of the nitrogen cycle do not account for bedrock, the largest pool of terrestrial nitrogen, as a source of nitrous oxide. Although it is known that release rates of nitrogen from bedrock are large, there is an incomplete understanding of the connection between bedrock-hosted nitrogen and atmospheric nitrous oxide. Here, we quantify nitrogen fluxes and mass balances at a hillslope underlain by marine shale. We found that at this site bedrock weathering contributes 78% of the subsurface reactive nitrogen, while atmospheric sources (commonly regarded as the sole sources of reactive nitrogen in pristine environments) account for only the remaining 22%. About 56% of the total subsurface reactive nitrogen denitrifies, including 14% emitted as nitrous oxide. The remaining reactive nitrogen discharges in porewaters to a floodplain where additional denitrification likely occurs. We also found that the release of bedrock nitrogen occurs primarily within the zone of the seasonally fluctuating water table and suggest that the accumulation of nitrate in the vadoes zone, often attributed to fertilization and soil leaching, may also include contributions from weathered nitrogen-rich bedrock. Our hillslope study suggests that under oxygenated and moisture-rich conditions, weathering of deep, nitrogen-rich bedrock makes an important contribution to the nitrogen cycle. The data files are in Excel, which can be accessed using Microsoft Office, and consist of many data sets from the Pumphouse Hillslope PLM (Pumphouse Lower Montane) 1, 2, 3, and 4. They include soil to rock (0-10 meters) solid phase minerals and elements compositions; time- and depth-resolved pore-water chemistry and pore-gas compositions; time- and depth-resolved water table depths and water fluxes; subsurface weathering rates; nitrogen influxes and effluxes and mass balance. The attached paper is in a Word document, which can be accessed using Microsoft Office, and in pdf format.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2021

Data from : "Warming promotes loss of subsoil carbon through accelerated degradation of plant-derived organic matter". Blodgett warming experiment

This dataset contains data used for the paper: Warming promotes loss of subsoil carbon through accelerated degradation of plant-derived organic matter. Soil Biology and Biochemistry 156, 108185. doi:10.1016/j.soilbio.2021.108185On April 2018 (after 4.5 years of warming), we collected O-horizon (organic horizon) material and soil core down to 90 cm depth from a whole-soil warming experiment in a mixed-coniferous temperate forest, located at the University of California Blodgett experimental forest in the foothills of the Sierra Nevada, CA USA. The goal was to assess how 4.5 years of +4 °C whole-soil warming affected the quantity and quality of soil organic matter. Cores were collected from 6 experimental plots (three replicated blocks); samples were collected in 10 cm increments from 0 to 90 cm depth.This dataset contains a compressed (.zip) archive of the data used for this manuscript. The dataset includes files in .xlsx format, which can be accessed and processed using MS Excel or R. Carbon and nitrogen concentrations, as well as stable carbon isotope composition ((δ13C) and solvent extractable lipid biomarker (alkanoic acids and alkanes) data are provided as processed data files. Diffuse reflectance infrared Fourier transform (DRIFT) spectroscopy data are provided as raw output and processed data files.The dataset files "Blodgett_warming_Data" and "Blodgett_warming_raw_data.xlsx" were updated on July 7, 2021. The following updates were made: (1) specification of the units of measurements in the dataset (the unit of measurement was missing in some parameters) and (2) the column name "pulled depth" was changed to "pooled depth" in the updated data files.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2021

Model, data, and code for paper "Modeling of streamflow in a 30-kilometer-long reach spanning 5 years using OpenFOAM 5.x"

The data package includes data, model, and code that support the analyses and conclusions in the paper titled “modeling of streamflow in a 30-kilometer-long reach spanning 5 years using OpenFOAM 5.x”. The primary goal of this paper is to demonstrate that key streamflow properties such as water depth, flow velocity, and dynamic pressure in a natural river at 30-kilometer scale over 5 years can be reliably and efficiently modeled using the computational framework presented in this paper. To support the paper, various data types from remote sensing, field observations, and computational models are used. Specific details are described as follows. Firstly, the river bathymetry data was obtained from a Light Detection and Ranging (LiDAR) survey. This data is then converted to a triangulated surface format, STL, for mesh generation in OpenFOAM. The STL data can be found in Model_Setups/BaseCase_2013To2015/constant/triSurface. The OpenFOAM mesh generated using this STL file can be found in constant/polyMesh. Other model setups, boundary and initial conditions can be found in /system and /0.org under folder BaseCase_2013To2015. A similar data structure can also be found in BaseCase_2018To2019 for the simulations during 2018 and 2019. Secondly, the OpenFOAM simulations need the upstream discharge and water depth information at the upstream boundary to drive the model. These data are generated from a one-dimensional hydraulic model and the data can be found under the folder Model_Setups /1D model Mass1 data. The mass1_65.csv and mass1_191.csv files include the results of the 1D model at the model inlet and outlet, respectively. The Matlab source code Mass1ToOFBC20182019.m is used to convert these data into OpenFOAM boundary condition setups.With the above OpenFOAM model, it can generate data for water surface elevation, flow velocity, and dynamic pressure. In this paper, the water surface elevation was measured at 7 locations during different periods between 2011 and 2019. The exact survey locations (see Fig1_SurveyLocations.txt) can be found in folder Fig_1. The variation of water stage over time at the 7 locations can be found in folder /Observation_WSE. The data type include .txt, .csv, .xlsx, and .mat. The .mat data can be loaded by Matlab.We also measured the flow velocities at 12 cross-sections along the river. At each cross-section, we recorded the x, y locations, depth, three velocity components u,v,w. These data are saved to a Matlab format which can be found under folder /Observation_Velocity and /Fig_1. The relative locations of velocity survey locations to the river bathymetry can be found in Figure 1c.The water stage data at the 7 locations from OpenFOAM, 1D, and 2D hydraulic models are also provided to evaluate the long-term performance of 3D models vs 1D/2D models. The water stage data for the 7 locations from OpenFOAM have been saved to .mat format and can be found in /OpenFOAM_WSE. The water stage data from the 1D model are saved in .csv format and can be found in /Mass1_WSE. The water stage from the 2D model is saved as .mat format and can be found in / Mass2_WSEIn addition, the OpenFOAM model outputs the information of hydrostatic and hydrodynamic pressure. They are saved as .mat format under folder /Fig_11/2013_1. As the files are too large, we only uploaded the data for January 2013. The area of different ratio of dynamic pressure to static pressure for all simulation range, i.e., 2013-2015, are saved to .mat format. They can be found in /Fig_11/PA. Further, the data of wall clock time versus the solution time of the OpenFOAM modeling are also saved to .mat format under folder /Fig_13/LogsMat. In summary, the data package contains seven data types, including .txt, .csv, .xlsx, .dat, .stl, .m, and .mat. The former 4 types can be directly open using a text editor or Microsoft Office. The .mat format needs to be read by Matlab. The Matlab source code .m files need to be run with Matlab. The OpenFOAM setups can be visualized in ParaView. The .stl file can be opened in ParaView or Blender. The data in subfolders Fig_1 to Fig_10 and Fig_12 are copied from the aforementioned data folders to generate specific figures for the paper. A readME.txt file is included in each subfolder to further describe how the data in each folder are generated and used to support the paper.Please use the data package's DOI to cite the data package. Please contact yunxiang.chen@pnnl.gov if you need more data related to the paper.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2024

Biogeochemistry simulations for the Salt Marsh Accretion Response to Temperature eXperiment (SMARTX)

Coastal ecosystems have been largely ignored in Earth system models but are important zones for carbon and nutrient processing. Interactions between water, microbes, soil, sediments, and vegetation are important for mechanistic representation of coastal processes and ecosystem function. To investigate the role of these feedbacks, we used a reactive transport model (PFLOTRAN) that has the capability to be connected to the Energy Exascale Earth System Model (E3SM). PFLOTRAN was used to incorporate redox reactions and track chemical species important for coastal ecosystems as well as define simple representations of vegetation dynamics. Our goal was to incorporate oxygen flux, salinity, pH, sulfur cycling, and methane production along with plant-mediated transport of gases and tidal flux. Using porewater profile and incubation data for model calibration and evaluation, we were able to create depth-resolved biogeochemical soil profiles for saltmarsh habitat and use this updated representation to simulate direct and indirect effects of elevated CO2 and temperature on subsurface biogeochemical cycling. We found that simply changing the partial pressure of CO2 or increasing temperature in the model did not fully reproduce observed changes in the porewater profile, but the inclusion of plant or microbial responses to CO2 and temperature manipulations was more accurate in representing porewater concentrations. This indicates the importance of characterizing tightly coupled vegetation-subsurface processes for developing predictive understanding and the need for measurement of plant-soil interactions on the same time scale to understand how hotspots or moments are generated.Included in this data package are PFLOTRAN input (PFLOTRAN input files and chemical database) files for simulating single column biogeochemistry, root, and tide interactions at the Global Change Research Wetland (Kirkpatrick Marsh; Edgewater, MD). The biogeochemical network includes soil organic matter decomposition, nitrogen, iron, and sulfur cycling, and methanogenesis. Reduced species can be oxidized and plant processes include oxygen and nutrient priming, methane release, and nutrient uptake.Inputs:TAI_database.dat - geochemical database for reactions, more information on database structure and variables can be found here https://www.pflotran.org/documentation/user_guide/cards/pages/geochemical_database.htmlswamp.in - input file for biogeochemical network in PFLOTRANswamp_eCO2.in - input file for biogeochemical network in PFLOTRAN with input gas partial pressures/concentrations adjusted for elevated CO2 treatmentsOutputs:swamp_obs_0.tec - hourly porewater concentrations from from multiple depths in the soil columnswamp_eCO2_obs_0.tec - hourly porewater concentrations from multiple depths in the soil column for elevated CO2 treatmentsPFLOTRAN code access: https://github.com/fmyuan/pflotran-elm-interface.git

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2025

Metagenome-assembled genomes from Slate River floodplain sediments near Crested Butte, CO, USA (June to October 2020)

Microorganisms play a key role in cycling nutrients and contaminants in the terrestrial environment depending on their genetic potential. Here we present metagenome-assembled genomes (MAGs) for the bacterial and archaeal community in floodplain sediment samples taken June to October 2020 at two locations (OBJ1 and OBJ2) near the confluence of the Oh-Be-Joyful Creek and Slate River. The site is one of the field sites in focus for the SLAC National Accelerator Laboratory Groundwater Quality Science Focus Area (SFA) program. Sediment samples from a deep soil pit were collected from 30 cm depth below surface to just above the cobble layer (~190-250 cm depth) at discrete depths every 40 cm for microbial analyses. A total of 35 metagenomes were sequenced through the Joint Genome Institute (JGI) and can be found under Genomes Online Database (GOLD) sequencing project: Gs0142591. Metagenomes were assembled, binned, and refined using metawrap to generate MAGs (>50% complete and < 10% contamination based on checkM scores). This dataset includes a zip file of 2848 MAG fasta files and a csv file with quality, taxonomic classification (Genome Taxonomy Database Release RS220), and metagenome accessions for MAGs. This dataset also includes a file-level metadata (flmd.csv) file that lists each file contained in the dataset with associated metadata and a data dictionary (dd.csv) file that contains column/row headers used throughout the files along with a definition, units, and data type.Part of this work was performed at SLAC Accelerator Laboratory funded by the US Department of Energy, Office of Science, Biological and Environmental Research under Contract No. DE-AC02-76SF00515.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2026

Zero Resistance Ammetry (ZRA) Measurements of Sediment Electrochemical Gradients, Old Woman Creek, Ohio, USA, June–November 2022

This dataset contains raw and processed zero resistance ammetry (ZRA) measurements collected from wetland sediments at Old Woman Creek, a freshwater estuary on Lake Erie, Ohio, USA, between June and November 2022. Measurements were obtained using a vertically deployed electrode array positioned at multiple depths within the sediment profile to capture electrochemical gradients associated with microbial activity and sediment geochemistry. The raw dataset consists of parsed instrument log files containing timestamps, electrode pair identifiers, and measured electrical potential (mV). The processed dataset includes standardized and quality-controlled values with instrument saturation limits removed and timestamps converted to ISO 8601 format. Electrode line identifiers were mapped to physical depths, enabling interpretation of depth-resolved electrochemical gradients. Instrument saturation values (−2048, −2047, 2047, and 2048 mV) were identified as measurement limits and excluded from quantitative analyses. All data parsing, processing, and quality control steps are documented in an accompanying R Markdown script, ensuring full reproducibility from raw instrument logs to final datasets.

EARTH SCIENCE > AGRICULTURE > SOILS > ELECTRICAL C↗
DOE OSTI2024

On the length scale and rate-dependent mechanical behavior of monolithic (oxy)sulfidic glassy solid-state electrolytes

In the controlled atmosphere of a dedicated glove box, nanoindentation performed with a diamond Berkovich indenter tip has been used to examine the mechanical behavior of three (oxy)sulfide solid-state electrolytes (SSEs), 70Li 2 S·(30–x)P 2 S 5 ·xP 2 O 5 (x = 0, 2, and 5). At a drive frequency of 120 Hz, the elastic modulus is found to be predominantly depth independent over the range of 100 nm to 1 μm and generally insensitive to the varying mol fraction of oxygen (0, 2, and 5%) as well as the imposed strain rates of 0.025, 0.05, and 0.1 1/s. All three SSEs exhibit significant room-temperature creep. Strain burst activity observed during loading (potentially representative of pore collapse or cracking) is attenuated with the addition of oxygen. The hardness is found to be insensitive to the imposed strain rates but varying with depth and oxygen content. Furthermore, the highest oxygen concentration yields the lowest hardness and strongest depth dependence.

36 MATERIALS SCIENCE↗
DOE OSTI2024

AmeriFlux AR-Bal Balcarce BA

This is the AmeriFlux version of the carbon flux data for the site AR-Bal Balcarce BA. Site Description - The study was carried out in a 19-ha rainfed soybean plot at the Unidad Integrada Balcarce, located southeast of Buenos Aires, Argentina. The site is located in an environment of gentle hills at 130 m.a.s.l. Its soil was classified as a typical Argiudoll, with a loamy clayey texture up to 0.30 m and between 0.80 to 1.10 m depth, and a clayey texture between 0.30 and 0.80 m depth. The slope was 1:50 and oriented NE to SW. A caliche layer was found at 1 to 1.2 m depth thus the water table was considered beneath that level. The soybean variety used was DM 3810, Maturity Group III with an indeterminate growing habit. It was sown on November 21, 2012, and emerged on December 1. The crop archive had a maximum height of 0.75 m.

Gassmann, Maria Isabel↗
DOE OSTI2025

AmeriFlux FLUXNET-1F AR-Bal Balcarce BA

This is the AmeriFlux Management Project (AMP) created FLUXNET-1F version of the carbon flux data for the site AR-Bal Balcarce BA. This is the FLUXNET version of the carbon flux data for the site AR-Bal Balcarce BA produced by applying the standard ONEFlux (1F) software. Site Description - The study was carried out in a 19-ha rainfed soybean plot at the Unidad Integrada Balcarce, located southeast of Buenos Aires, Argentina. The site is located in an environment of gentle hills at 130 m.a.s.l. Its soil was classified as a typical Argiudoll, with a loamy clayey texture up to 0.30 m and between 0.80 to 1.10 m depth, and a clayey texture between 0.30 and 0.80 m depth. The slope was 1:50 and oriented NE to SW. A caliche layer was found at 1 to 1.2 m depth thus the water table was considered beneath that level. The soybean variety used was DM 3810, Maturity Group III with an indeterminate growing habit. It was sown on November 21, 2012, and emerged on December 1. The crop archive had a maximum height of 0.75 m.

Gassmann, Maria Isabel [Universidad de Buenos Aire↗
DOE OSTI2023

Explosive Yield Estimation Using Regional Seismic Moment Tensors

Here, we use the Pasyanos and Chiang (2022) data set to calculate the seismic moment M 0 for each explosion and use the measured explosive yield W to validate the W~M 0 relationship in Denny and Johnson (1991; hereafter, DJ91). The M 0 is corrected by transforming to a potency tensor and applying more appropriate near-source geophysical parameter values in the moment estimate. The mean residual between observed and predicted yield is near zero; however, the standard deviation of the residuals results in an F-value (a 95% confidence factor) of about 5. We re-estimate the coefficients in the DJ91 model and find similar values and only a slight improvement in the F-value. Next, we embark on a similar model selection process as DJ91, allowing for non-cube-root yield scaling and other plausible near-source elastic moduli. As was found by DJ91, the yield dependence is not significantly different from unity, and a cube root assumption is valid. Therefore, we yield scale the seismic moment and test the significance of all plausible explanatory variables. Isotropic moment performs better in the response variable than total moment. The preference for isotropic moment could be due to its relationship to volume change, which would be more directly affected by explosive yield. Surprisingly, we find that the overburden pressure, which is a function of depth, is not a significant parameter in the model. We hypothesize that this is due to the competing depth effects on source asymmetry and the incorporation of depth in the Green’s functions used to calculate the seismic moment tensors. Importantly, this emphasizes that only seismic moment tensor-derived moments should be used in these models. After removing insignificant model parameters, we are left with a simple model to predict explosive yield $\widehat{W}$ in kt from isotropic moment M I in N·m, $\widehat{W}$=κ –1.4132 10 0.035626GP M I , in which κ and GP are the near-source bulk modulus and gas porosity in Pa and %, respectively. The F-value for this model is approximately 3.

58 GEOSCIENCES↗
DOE OSTI2023

Hydrologic Impacts of a Strike-Slip Fault Zone: Insights from Joint 3D Body-Wave Tomography of Rock Valley

The Rock Valley fault zone (RVFZ), an intraplate strike-slip fault zone in the southern Nevada National Security Site (NNSS), hosted a series of very shallow (<3 km) earthquakes in 1993. The RVFZ may also have hydrological significance within the NNSS, potentially playing a role in regional groundwater flow, but there is a lack of local hydrological data. In the Spring of 2021, we collected active-source accelerated weight drop seismic data over part of the RVFZ to better characterize the shallow subsurface. Here, we manually picked ~17,000 P-wave travel times and over 14,000 S-wave travel times, which were inverted for P-wave velocity (V P ), S-wave velocity (V S ), and V P /V S ratio in a 3D joint tomographic inversion scheme. Seismic velocities are imaged as deep as ~700 m in areas and generally align with geologic and structural expectations. V P and V S are relatively reduced near mapped and inferred faults, with the most prominent lower V P and V S zone around the densest collection of faults. We image V P /V S ratios ranging from ~1.5 to ~2.4, the extremes of which occur at a depth of ~100 m and are juxtaposed across a fault. One possible interpretation of the imaged seismic velocities is enhanced fault damage near the densest collection of faults with relatively higher porosity and/or crack density at ~100 m depth, with patches of semiperched groundwater present in the sedimentary rock in higher V P /V S areas and drier rock in lower V P /V S areas. A relatively higher V P /V S area beneath the densest faults persists at depth, which suggests percolation of groundwater via the fault damage zone to the regionally connected lower carbonate aquifer. Potentially, the presence and movement of groundwater may have played a role in the 1993 earthquake aftershocks.

58 GEOSCIENCES↗
DOE OSTI2023

WELLS Database

The Wellbore Exploration and Location Logistic System (WELLS) is a living national wellbore database - created and maintained by the National Energy Technology Laboratory (NETL). This resource contains more than seven million public wellbore records from state, federal, and tribal resources. Sourced from over 65 authoritative, yet disparate resources, the WELLS Database combines and synthesizes well data from oil, gas, underground injection, research, geothermal, geotechnical, groundwater and other types of wells in a single, unified system. This resource can be explored and visualized through the WELLS Interactive Application, also on EDX: https://edx.netl.doe.gov/dataset/wells-interactive-application The WELLS Database (formerly titled CO2-Locate) is an integrated national well dataset, representing open-source wellbore data from disparate state, tribal, and federal entities. The database provides publicly available well header data with key attributes such as well age, depth, and status. The database contains a fully integrated CSV file with all values in numerical columns, such as depth, converted into numbers. This version has a NETL derived API (American Petroleum Institute) number column and has been handled for redundancies, resulting in one record for every unique API number. The database also contains a fully integrated CSV file, where all original data are kept as text values. Additionally, the database includes a shapefile containing key attributes and coordinates from the integrated dataset, reformatted public wells CSV files, and a proprietary well density grid shapefile. Notes for consideration: The WELLS Database will be updated periodically with new datasets and information. A field dictionary with field (i.e., attribute) coverage across acquired public well resources, and the resulting integrated public well datasets are available in the spreadsheet, WELLS_Field_Dictionary.xlsx. Summary layers provided in this database are derived from proprietary layers and do not always contain key features (status, type, true vertical depth, or spud year) and therefore might not be shown when data are queried for those features.

AS↗
DOE OSTI2025

WELLS Interactive Application

The Wellbore Exploration and Location Logistic System (WELLS) Interactive Application is an interactive tool to enable easy exploration and visualization of the living national wellbore database (WELLS Database (https://edx.netl.doe.gov/dataset/wells_database)). The tool and underlying database were created and are maintained by the National Energy Technology Laboratory (NETL), providing visualization of the more than six million public wellbore records from more than 65 authoritative state, federal, and tribal resources. The WELLS Interactive Application serves up wellbore data from oil, gas, underground injection, research, geothermal, geotechnical, groundwater, and other types of wells in a single, standardized, unified system. In addition to the surface location of these wells, the underlying database combines select key attributes for features such as well age, depth, and operating status. The system also provides users with references back to the original sources used in this unified platform. The underlying data can be accessed through the WELLS Database: https://edx.netl.doe.gov/dataset/wells_database Additional Information: The WELLS Interactive Application (formerly titled CO2-Locate) enables visualization and access to the public wellbore records through an intuitive web-based mapping tool. The WELLS Interactive Application was designed to help users visualize, query, analyze, and download wellbore records. Public wellbore points are included as a layer in the Map page, called Public Wells. Additionally, a multivariate hexagon grid summarizing well density from proprietary well data, called Well Density, is included to identify data gaps between the public and proprietary well data. Filtering functionalities in the tool allow these two layers to be spatially filtered by state, county, or basin as well as by status, type, true vertical depth, and spud year. The WELLS Interactive Application also contains a Near Me tool can be used to search and explore wellbore data within a user-defined distance of a specified location on the map, which can also be downloaded. The Query tool allows users to query the selected or filtered wells in the Public Wells layer and export the data. For additional information on these tool functionalities, see the help documentation on the About page of the tool. Notes for Consideration: The Well Density layer provided in this application is derived from proprietary wellbore data, the records of which do not always contain values for key features (status, type, true vertical depth, or spud year). Therefore, data might not be available when layers are queried for all filter combinations. Additionally, visualizing layers and applying filters may take additional time to load (i.e., draw on the map) due to the large size of the data.

ccs↗
DOE OSTI2020

Imaging of Calibrated Defects in Additively Manufactured Materials: Pulsed Thermal Tomography Nondestructive Examination of Additively Manufactured Reactor Materials and Components

Additive manufacturing (AM, or 3D printing) for commercial nuclear energy applications is an emerging method for cost-efficient manufacturing aimed at replacing aging nuclear reactor parts and reducing costs for new construction. Known material flaws in AM include low-density regions consisting of non-sintered powder, which have to be detected to ensure the safety of long-term performance nuclear reactor components. Currently, limited options are available for nondestructive evaluation (NDE), either during or post manufacturing. As a solution to NDE of AM, we are developing pulsed thermal imaging which is non-contact, one-sided, and scalable to arbitrary size and shape of the AM parts. Pulsed thermography (PT) system utilizes a high intensity flash lamp to rapidly heat surface of sample, and a high sensitivity fast-frame megapixel infrared (IR) camera to capture data of surface temperature variations. The acquired data cube consists of a stack of surface temperature images taken at different times. Information about material internal defects is extracted by analyzing the data cube. This report provides results of preliminary performance evaluation of pulsed thermal imaging capability in detection of imprinted flaws in AM metallic structures. The flaws were introduced into AM parts as imprinted hemispherical low density regions, consisting of trapped un-sintered metallic powder. Specimens for developed for this study consisted of AM stainless steel 316 and Inconel 718 plates. The diameters of imprinted defects varied from 1mm to 8mm, and their depths below the plate flat surface varied between 1mm and 6mm. Pulsed thermal tomography (PTT) processes the measured data cube to obtain 3D reconstructions of material effusivity using a unique inversion algorithm developed at Argonne. PTT has been previously used in imaging of similar size flat bottom hole (FBH) simulated defects in stainless steel 316 and Inconel 718 specimens. In the study involving AM specimens, PTT imaging results have shown that 1mm-diameter defects located 1mm and 2mm below the surface of specimens were detectable. Larger size defects were detectable at greater depth. We also explored an alternative approach to detection of material flaws in PT data cube, which is using neural learning-based approach to blind source separation. Detection of small material defects requires finding features in the data cube which have signal contrast levels approaching sensitivity limit of IR camera. In this study, an optimized Neural Learning based Blind Source Separation (NLBSS) algorithm, including Principal Component Analysis (PCA), and Independent Component Analysis (ICA) is demonstrated to automatically extract principal temporal and spatial features of thermography frames to enhance flaw detection. By using the NLBSS algorithm, material internal defects can be automatically detected. Furthermore, this processing approach compensates for experimental thermal imaging artifacts, such as noise and uneven heating. By merging artificial intelligence with phtotothermics, the NDE system detects internal calibrated defects of various sizes and depths in AM nuclear-grade metallic alloys.

36 MATERIALS SCIENCE↗