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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 541 records · Page 30

“When I talk about it, my eyes light up!” Impacts of a national laboratory internship on community college student success

Participation in technical/research internships may improve undergraduate graduation rates and persistence in science, technology, engineering, and mathematics (STEM), yet little is known about the benefits of these activities a) for community college students, b) when hosted by national laboratories, and c) beyond the first few years after the internship. We applied Social Cognitive Career Theory (SCCT) to investigate alumni perspectives about how CCI at Lawrence Berkeley National Laboratory (LBNL) impacted their academic/career activities. We learned that alumni had low confidence and expectations of success in STEM as community college students. Participation in CCI increased their professional networks, expectations of success, and STEM skills, identity, and self-efficacy/confidence. Hispanic/Latinx alumni recalled the positive impact of mentors who prioritized personal connections, and women valued "warm" social environments. We propose several additions to the SCCT model, to better reflect the supports and barriers to STEM persistence for community college students.

careers↗

Chemistry of the thermal water samples of the Camas Prairie area in Idaho, USA

This dataset includes chemistry of geothermal water samples of the Camas Prairie area in Idaho. The samples included in this dataset were collected over the period of 2016-2019. Collection/analysis of new water samples and compilation of existing water chemistry database were conducted for Snake River Play Fairway Project. All chemical analysis of the samples were conducted in the Analytical Laboratory at the Center of Advanced Energy Studies (unless otherwise indicated) in Idaho Falls, Idaho. Isotope analysis were conducted in analytical/isotope measurement labs at Lawrence Berkeley National Laboratory, Utah State University, and University of Utah.

15 GEOTHERMAL ENERGY↗

Kilauea Magnetotelluric Dataset

In 2002 and 2003 a collaborative effort was undertaken between Lawrence Berkeley National Laboratory, Sandia National Laboratories, the USGS Menlo Park, the USGS Hawaiian Volcano Observatory, and Electromagnetic Instruments Inc. to study the Kilauea volcano in Hawaii using the magnetotelluric (MT) technique. The work was motivated by a desire to improve understanding of the magma reservoirs and conduits within Kilauea and the East and Southwest Rift zones, which has implications for understanding Kilaueas plumbing system. An improved understanding of the rift zones has implications in understanding large-scale landslides that are generated in the Hilina Slump, which produce significant impacts on coastal communities. Up to eight stations operated simultaneously, with multiple remote reference sites, and data were processed using multi-station robust processing techniques. In total, data were acquired at 70 sites over the Southwest and East rift zones. Good to excellent quality data were obtained even in the harshest conditions, such as those encountered on the fresh lava flows of the East Rift Zone (ERZ), where electrical contact resistances are on the order of 100 kOhm. This data supports the continuing efforts to increase geothermal power on the island of Hawaii. Each of the 70 EDI files are the MT impedance tensors for 1 site. There is also a description of the processing of the data and a site map showing the locations of each site.

15 GEOTHERMAL ENERGY↗

Reactive Transport Simulations of High-Tempertature Geologic Thermal Energy Storage (GeoTES) in Deep Saline Formations - I/O Files

Simulation input and output files, post-processed figures and excel tables, and tecplot layout files for generating figures. These simulations were run with TOUGHREACT V4.12 by Lawrence Berkeley National Laboratory in 2021. This work was completed as part of the geologic thermal energy storage (GeoTES) research project reported in the final report for Phase I of this work, which is linked below.

15 GEOTHERMAL ENERGY↗

Utah FORGE 2-2446: Closing the Loop Between In-situ Stress Complexity and EGS Fracture Complexity - Workshop Presentation

This is a presentation on the Closing the Loop Between In-situ Stress Complexity and EGS Fracture Complexity project by Lawrence Livermore National Laboratory, presented by Dr. Matteo Cusini. The project's objective was to employ a combination of high-fidelity simulations and true-triaxial block fracturing tests at high temperature to explore the intricate relationship between in-situ stress and hydraulic fracture patterns and better characterize the in-situ stress at Utah FORGE. This presentation was featured in the Utah FORGE R&D Annual Workshop on September 7, 2023. The workshop provided a valuable opportunity to explore the progress made in each of the 17 Research and Development projects funded under Solicitation 2020-1 which aim to enhance our understanding of the crucial factors influencing the development of Enhanced Geothermal Systems (EGS) reservoirs and resources.

15 GEOTHERMAL ENERGY↗

Utah FORGE 3-2535: Joint EM-Seismic-InSAR Imaging of Fracture Properties - Workshop Presentation

This is a presentation on the Joint Electromagnetic/Seismic/InSAR Imaging of Spatial-Temporal Fracture Growth and Estimation of Physical Fracture Properties During EGS Resource Development project by Lawrence Berkeley National Laboratory, presented by Dr. David Alumbaugh, Staff Scientist. The project's objective was to develop a set of technologies and workflow to image induced fracture generation and growth for an Enhanced Geothermal System (EGS). The project anticipates imaging of the fracture generation and growth at FORGE using a combination of passive seismic, active source borehole EM, and INSAR technology. This presentation was featured in the Utah FORGE R&D Annual Workshop on September 8, 2023. The workshop provided a valuable opportunity to explore the progress made in each of the 17 Research and Development projects funded under Solicitation 2020-1 which aim to enhance our understanding of the crucial factors influencing the development of Enhanced Geothermal Systems (EGS) reservoirs and resources.

15 GEOTHERMAL ENERGY↗

Utah FORGE 5-2428: Fracture Permeability Impact on Reservoir Stress and Seismic Slip Behavior - Workshop Presentation

This is a presentation on the Fracture Permeability Impact on Seismic Slip Behavior project by Lawrence Livermore National Laboratory, presented by Dr. Kayla A. Kroll. The project's objective is to develop, apply and validate a holistic thermal, hydrologic, mechanical, and chemical (THMC) workflow that includes evaluation of induced seismic slip in EGS reservoirs. This presentation was featured in the Utah FORGE R&D Annual Workshop on September 8, 2023. The workshop provided a valuable opportunity to explore the progress made in each of the 17 Research and Development projects funded under Solicitation 2020-1 which aim to enhance our understanding of the crucial factors influencing the development of Enhanced Geothermal Systems (EGS) reservoirs and resources.

15 GEOTHERMAL ENERGY↗

Utah FORGE 3-2514: Strain Sensing Array for Deformation Characterization - 2024 Annual Workshop Presentation

This is a presentation on the Strain Sensing Array to characterize deformation at the FORGE site project by Clemson University, presented by Lawrence Murdoch. The project's objective was to evaluate the feasibility of measuring and interpreting tensor strain data to improve the performance of EGS. This presentation was featured in the Utah FORGE R&D Annual Workshop on August 23, 2024.

15 GEOTHERMAL ENERGY↗

Post survey report for AOP Assignable Asset collection of Crested Butte, CO

This report contains details of the National Ecological Observatory Network Airborne Observation Platform (NEON AOP) assignable asset (AA) flight over Crested Butte, Colorado (CO). The report is being prepared for Lawrence Berkeley National Lab (LBNL), the primary clients for the flights who contracted the NEON AOP for flights during June 2018. The report includes a summary of the acquired flight lines over the planned area, results of calibration surveys, and quality assurance (QA) results of the acquired data. Detailed reports on the acquired data and processing results were also delivered with the data. LBNL contracted the AA NEON AOP flights to observe watersheds of interest at Crested Butte with remotely sensed data including high resolution LiDAR, imaging spectroscopy, and high-resolution camera imagery. The remote sensing imagery acquired by the AOP intendeds to support LBNL on an interdisciplinary project on hydrology, biogeochemistry, and ecosystem functioning in the area surrounding the Rocky Mountain Biological Laboratory (RMBL), one of the most prominent ecological study sites in the United States.

2018 NEON and 2025 CHESS Campaigns↗

NEON AOP Imaging Spectroscopy Survey of Upper East River Colorado Watersheds: Raw-Space Radiance and Observational Variable Dataset

Lawrence Berkeley National Laboratory (LBNL) contracted the National Ecological Observatory Network Airborne Observation Platform (NEON AOP) to observe watersheds of interest near Crested Butte, CO with remotely sensed data including imaging spectroscopy. The flight box design encompassed the watersheds, and flight design targeted a minimum of 30% overlap between adjacent flight lines. The total area surveyed was 334 km2 across 72 lines. Flight lines were oriented north-south for consistency in solar illumination geometry. Seven days were required to cover the flight area. Some areas were flown additional times to improve data quality or temporal coincidence between airborne acquisitions and field sampling. In total, 102 lines were collected and can be downloaded here: https://portal.nersc.gov/wfsfa/doi-10-15485-1617204/. The instrument used for the acquisition was an Airborne Visible-Infrared Imaging Spectrometer - Next Generation (AVIRIS-NG), which records radiance within 426 contiguous spectral bands in the wavelength range from 380 to 2510 nm. The instrument was flown at a target aboveground altitude of 1000 m for a processed data spatial resolution of 1 m. These data are non-orthorectified, radiance data that require further processing prior to use as a surface reflectance data set.

2018 NEON and 2025 CHESS Campaigns↗

Time-domain reflectometer survey across the East River Watershed, Colorado

Lawrence Berkeley National Laboratory (LBNL) collected near-surface point-measurements of soil temperature (file variable TDR_T(C)), volumetric water content (file variable TDR_SM(VWC%)), and soil electrical conductivity (file variable TDR_EC(mS/m)) using a time-domain reflectometer (TDR) at a depth of 25 cm. The survey aimed to characterize the spatial heterogeneity of near-surface hydrological properties at the hillslope scale considering sites with different aspects and elevation within the watershed. The East River is part of the Watershed Function Scientific Focus Area (WFSFA) located in the Upper Colorado River Basin, United States. These data were collected in early July 2019 over four hillslope sites: Pumphouse (north-east facing slope), Bradley (west and east-facing slopes), and Snodgrass (east-facing slope) within the East River watershed. Part of this survey was used to investigate soil-plant interactions at the hillslope scale in Jashvina et al. 2020.

54 ENVIRONMENTAL SCIENCES↗

Global gross primary production simulated by three terrestrial biosphere models to analyse smoothing of limiting rates

Processed global terrestrial gross primary production (GPP) from three terrestrial biosphere models (TBMs). Two simulations were run with each model, one that selects the rate limiting process of photosynthesis based on the minimum of the potential rates (following Farquhar et al. 1980) and the other that uses quadratic smoothing between the potential rates (following Collatz et al. 1991). The three TBMs are: 1) the Energy Exascale Earth System Model (E3SM) land model (ELM) (release: v1.1.0) (Burrows et al., 2020), a coupled carbon, nitrogen, and phosphorus model with sun/shade big-leaf canopy photosynthesis scaling. 2) The Functionally Assembled Terrestrial Ecosystem Simulator (FATES, tag: sci.1.30.0_api.8.0.0) (Koven et al., 2019), coupled with the Community Land Model (CLM, version 5; Lawrence et al., 2019), a carbon-only vegetation demography model with multi-leaf and multi-canopy layers for scaling photosynthesis, and with a leaf area index (LAI) optimisation scheme. 3) The Sheffield Dynamic Global Vegetation Model (SDGVM, tag: Walkeretal2020_GCB), a carbon-only model with multi-leaf-layer canopy photosynthesis scaling and also with an LAI optimisation scheme (Walker et al., 2017; Woodward & Lomas, 2004). These data were generated to evaluate the effect of Collatz smoothing of limiting rates on simulated GPP across a range of terrestrial biosphere models. Analysis of results can be found in Walker et al. (2020). This dataset is comprised of R scripts to process data and produce figures and .RDS files, a binary format specific to R and read with the 'readRDS' function.

54 ENVIRONMENTAL SCIENCES↗

Shale drilling field notes, lithologic descriptions, and core photographs of wells PLM5, PLM8, GUM1, and GLS1 at the East River Watershed, Colorado

The purpose of this dataset is to maintain a record of the shale drilling field notes, lithologic descriptions, and core photographs taken at the PLM5 (Pumphouse Lower Montane Borehole #5), PLM8 (Pumphouse Lower Montane Borehole #8), GUM1 (Gothic Upper Montane Borehole #1), and GLS1 (GLS1 = Gothic Lower Subalpine Borehole #1) wells at the East River Watershed, Colorado during October 2018 through November 2019. The wells were created as part of data collection for the Lawrence Berkeley National Laboratory Watershed Function Scientific Focus Area (WF SFA). This dataset consists of (1) detailed field notes and metadata (well locations, elevations, completion depths, and pressure transducer deployments) associated with drilling and coring activities accompanying the 2018 and 2019 installations of wells PLM5, PLM8, GUM1, and GLS1 and (2) high resolution photographs (*.png format) of all shale core recovered during the installations. Core photographs are labeled with location- and depth-specific names (e.g. PLM5_134-144ft), with the prefix (e.g. PLM5) indicating the well location and the suffix (e.g. 134-144ft) indicating the depth below ground surface of the recovered core. With the exception of core collected from well PLM5 from depths 0-59 feet, which were photographed by Tetsu Tokunaga in Berkeley, CA, all core was photographed by Kenneth H. Williams at the US Geological Survey core repository in Denver, Colorado, where all core samples are permanently archived.

54 ENVIRONMENTAL SCIENCES↗

Continuous sensor suite measurements of weather, energy, soil and flux at four PumpHouse sites at the East River, Colorado

The purpose of this package is to monitor energy and water fluxes using a comprehensive set of sensors integrated on a tripod set up at 4 locations at the East River watershed in Colorado in the Upper Colorado River Basin as part of the Scientific Focus Area (SFA) research led by the Lawrence Berkeley National Lab (LBNL). This is a continuous sensor suite measurements of weather, energy, soil and flux at four East River pumphouse sites (ER-PHS1, ER-PHS2, ER-PHS3 and ER-PHS4) include: (1) soil CO2 concentration, CO2 flux and heat flux from soil surface; (2) photosynthetic active radiation flux at 1 m; (3) incoming/outcoming short and long wave radiation at 1 m, and user calculated net short and long wave radiation; (4) oxygen concentration and surface infrared temperature; (5) soil volumetric water content, temperature, and electrical conductivity at 10, 30, 60, 115 cm depth 115 cm depth; (6) soil matric potential and temperature at 30 cm depth; (7) incoming short wave radiation at 3 m height; (8) rainfall precipitation; (9) lightning strikes and strike distances; (10) wind direction and speed, maximum wind gust at 3 m; (11) air temperature, vapor pressure and barometric pressure at 3 m; (12) X _axis_level and Y_axis_level_(degree), tilt of the ATMOS 41 sensor; (13) maximum rainfall rate; (14) relative humidity sensor temperature at 3 m; (15) internally calculated vapor pressure deficit at 3 m with vapor pressure, relative humidity and sensor temperature measurements; (16) user calculated vapor pressure.These datasets contain data from Oct 11 2019 to March 20, 2020, and new datasets will be updated on annual basis. Files uploaded in Excel and Word, with copies in csv and pdf format.

54 ENVIRONMENTAL SCIENCES↗

Waterlevel, geochemical, and borehole data from Rifle, Colorado from 2006-2016

The files included in this data package provide site wide water level data, geochemical data, and borehole information associated with the Rifle site in Colorado during the Lawrence Berkeley National Lab (LBNL) led Integrated Field Research Challenge (IFRC) and Scientific Focus Area (SFA) research projects. The data informs hydrogeochemical interactions occurring in the watershed. The readme file contains detailed metadata for the files, including naming conventions, column headers, and data validation.The borehole information is provided in the file called rifle_boreholes.csv. It provides names and location for boreholes/wells at the Rifle. The waterlevel data is provided in the folder rifle_waterlevels. The geochemical data is provided in two folders: the rifle_floodplain_geochemistry folder has data which was collected from wells across the floodplain and a variety of offsite locations that contribute solutes to the floodplain given their upgradient locations. The rifle_plotC_geochemistry folder has data which was collected primarily in plot C, which was a focused study area in which a large number of groundwater manipulation / biostimulation experiments were conducted. While not all geochemical constituents are included for each well location and sampling date, they include anions, cations, trace metals, dissolved organic and inorganic carbon, stable isotopes of water and sulfur (as sulfate), and water quality parameters including pH, groundwater electrical conductivity (EC) and dissolved oxygen (DO). All files are in csv or txt format.

54 ENVIRONMENTAL SCIENCES↗

East River Watershed Stable Water Isotope Data in Precipitation, Snowpack and Snowmelt 2016-2020

Stable water isotopes (d18O, d2H and d-excess) are important tracers in hydrologic research to understand water partitioning between vegetation, groundwater, and runoff but are rarely applied to large watersheds with persistent snowpack and complex topopgraphy. Data were collected for the Lawrence Berkeley National Laboratory Watershed Function Science Focus Area supported by the U.S Department of Energy in the East River, CO Hydrologic Unit Code (140200010) with limited data also collected in adjacent watersheds Ohio Creek and Taylor River. Data are provided in csv and includes isotopic information for precipitation (years 2014-2016), snowmelt (years 2016-2017) and snowpits (years 2016-2020). Snowpit data contain depth resolved information at 10 cm intervals for density, snow water equivalent (SWE) and stable water isotopes. Bulk isotopic data for 86 snowpits contain depth, SWE, density and SWE-weighted isotope values. Sampling locations and elevations are provided within the data files, while kmz files are provided to view sampling locations using Google Earth software.

54 ENVIRONMENTAL SCIENCES↗

Chemistry data from soils and soil incubation experiments from the whole-soil warming experiment at Blodgett Forest, CA, 2018, from: “Metabolic capabilities mute positive response to direct and indirect impacts of warming throughout the soil profile”

This dataset contains soil chemistry data of soils from the whole-soil warming experiment at Blodgett Forest in June 2018, and from laboratory incubation experiments conducted with a subset of those soils. Soil samples were collected at five different depths down to 80 cm from soil plots continuously heated by 4°C above ambient temperature for 4.5 years, and from the respective unheated control plots. Incubation experiments were conducted for 28 days with soils collected between 10-30 cm (“surface soils”) and 60-80 cm (“subsoils”) from heated and unheated field plots, amended in the laboratory with cellobiose (C, carbon amendment), or cellobiose plus ammonium and phosphate (CNP, combined carbon, nitrogen and phosphorus amendment). The dataset includes separate files for: (i) total carbon and nitrogen concentrations of initial field soils; (ii) carbon dioxide efflux rates at multiple times throughout the incubation experiments, and respective cumulative carbon dioxide efflux rates, as well as inorganic nitrogen concentrations at the beginning and end of the incubations, and net nitrogen mineralization rates and carbon use efficiency calculated at the end of the incubation. Analysis of these data has been published in Dove et al., (2021), “Metabolic capabilities mute positive response to direct and indirect impacts of warming throughout the soil profile. Nat. Commun. 12:2089”, https://doi.org/10.1038/s41467-021-22408-5. This research was performed as part of the TES Belowground Biogeochemistry SFA project at Lawrence Berkeley National Laboratory.

54 ENVIRONMENTAL SCIENCES↗

Community Based Data of Uranium Adsorption onto Quartz

This data upload includes a compilation of experiments for quantifying uranium adsorption onto quartz. The provided .csv file has been compiled from the literature in a findable, accessible, interoperable, reusable (FAIR) data format. This was accomplished using the Lawrence Livermore National Laboratory Surface Complexation Database Converter (SCDC) code written in the R programming language (free licensing available at https://ipo.llnl.gov/technologies/software/llnl-surface-complexation-database-converter-scdc). This constitutes all current data compiled on uranium-quartz interactions in the L-SCIE (LLNL Surface Complexation/Ion Exchange) database (as of 02/28/2022). This data was used to develop surface complexation models that fit the global community dataset (https://doi.org/10.1021/acs.est.1c07109). The FAIR-formatted dataset also enables the implementation of alternative machine-learning approaches that can be explored in the future.

54 ENVIRONMENTAL SCIENCES↗