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At least 127 records · Page 7
All sourcesNASA NTRSDOE OSTI
DOE OSTI2018

Fallon FORGE: Lithology Logs and Well 21-31 Drilling Data

This submission includes lithology logs for all Fallon FORGE area wells; determined from core, cuttings, and thin section. Wells included are 84-31, 21-31, 82-36, FOH-3D, 62-36, 18-5, 88-24, 86-25, FOH-2, 14-36, 17-16, 34-33, 35A-11, 51A-20, 62-15, 72-7, 86-15, Carson_Strat_1_36-32, and several others. Lithology logs last updated 3/13/2018 with confirmation well 21-31 data, and revisited existing wells. Also included is well logging data for Fallon FORGE 21-31. Well logging data includes daily reports, well logs (drill rate, lithology, fractures, mud losses, minerals, temperature, gases, and descriptions), mud reports, drilling parameter plots, daily mud loss summaries, survey reports, progress reports, plan view maps (easting, northing), and wireline logs (caliper [with GR], triple combo [GR, caliper, SP, resistivity, array induction, density, photoelectric factor, and neutron porosity], array induction with linear correlation [GR, SP, Array Induction, caliper, conductivity], and monopole compression dipole shear [GR, SP, Caliper, sonic porosity, delta-T compressional, and delta-T shear])

15 GEOTHERMAL ENERGY↗
DOE OSTI2025

SPRUCE Measurements of Fine Root Production and Chemistry from Root Ingrowth Cores, Marcell Experimental Forest, Minnesota, 2022-2023

This dataset contains fine root production and tissue chemistry measurements from root ingrowth cores. Ingrowth cores were deployed in peat from June 28, 2022 to June 24, 2023 (2022-06-28 to 2023-06-24) inside SPRUCE Experiment plots at the Marcell Experimental Forest in northern Minnesota. The warming and elevated carbon dioxide (CO2) treatments in this dataset include +0 degrees Celsius (C) (+0 and +500 parts per million (ppm) elevated CO2), +4.5 degrees C (+0 and +500 ppm elevated CO2) and +9 degrees C (+0 and +500 ppm elevated CO2) for both hummocks and hollows, as well as +2.25 degrees C (+0 and +500 ppm) and +6.75 degrees C (+0 and +500 ppm) for hollows from minimum 10 cm depth from the peat surface. Measurements include root average diameter, root length, root biomass, and root tissue nitrogen (%N and δ15N) and carbon (%C and δ13C) concentration per plant functional type and microtopographical feature. Root length and biomass are standardized to 10 cm depth. These data were used to assess the warming and elevated CO2 response of fine roots across different peatland microtopographical features (hummocks and hollows) and plant functional types (shrub, spruce and larch). This dataset contains one data file in comma separate (.csv) format. Additional metadata are provided: one data dictionary and a file-level metadata file in comma separate (.csv) format and a user guide in PDF (*.pdf) format.

ESS-DIVE CSV File Formatting Guidelines Reporting ↗
DOE OSTI2018

Corrective Action Management Unit Report of Post-Closure Care Activities Calendar Year 2017.

The Corrective Action Management Unit (CAMU) at Sandia National Laboratories, New Mexico (SNL/NM) consists of a containment cell and ancillary systems that underwent regulatory closure in 2003 in accordance with the Closure Plan in Appendix D of the Class 3 Permit Modification (SNL/NM September 1997). The containment cell was closed with wastes in place. On January 27, 2015, the New Mexico Environment Department (NMED) issued the Hazardous Waste Facility Operating Permit (Permit) for Sandia National Laboratories (NMED January 2015). The Permit became effective February 26, 2015. The CAMU is undergoing post-closure care in accordance with the Permit, as revised and updated. This CAMU Report of Post-Closure Care Activities documents all activities and results for Calendar Year (CY) 2017 as required by the Permit. The CAMU containment cell consists of engineered barriers including a cover system, a bottom liner with a leachate collection and removal system (LCRS), and a vadose zone monitoring system (VZMS). The VZMS provides information on soil conditions under the cell for early leak detection. The VZMS consists of three monitoring subsystems, which include the primary subliner (PSL), a vertical sensor array (VSA), and the Chemical Waste Landfill (CWL) sanitary sewer (CSS) line. The PSL, VSA, and CSS monitoring subsystems are monitored quarterly for soil moisture concentration, the VSA is monitored quarterly for soil temperature, and the VSA and CSS monitoring subsystems are monitored annually for volatile organic compound (VOC) concentrations in the soil vapor at various depths. Baseline data for the soil moisture, soil temperature, and soil vapor were established between October 2003 and September 2004.

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗
DOE OSTI2018

Utility-Scale Solar: Empirical Trends in Project Technology, Cost, Performance, and PPA Pricing in the United States – 2018 Edition

The utility-scale solar sector has led the overall U.S. solar market in terms of installed capacity since 2012. In 2017, the utility-scale sector accounted for nearly 60% of all new solar capacity, and is expected to maintain its market-leading position for at least another six years. Two-thirds of all states, representing all regions of the country, are now home to one or more utility-scale solar projects. This report—the sixth in an ongoing annual series—provides in-depth data-driven analysis of the utility-scale solar project fleet in the United States. Drawing on empirical project-level data from a wide range of sources, this report analyzes technology trends, installed project prices, operating costs, capacity factors, power purchase agreement ("PPA") prices, the levelized cost of solar energy (LCOE), and the market value of solar. Given its current preeminence in the market, utility-scale PV also dominates much of this report, though data from CPV and CSP projects are also presented where appropriate. Highlights from this year's edition include: -Installation and Technology Trends: The use of solar trackers dominated 2017 installations with nearly 80% of all new capacity. In a reflection of the ongoing geographic expansion of the market beyond California and the high-insolation Southwest, the median insolation level at newly built project sites declined again in 2017. While new fixed-tilt projects are now seen predominantly in less-sunny regions, tracking projects are increasingly pushing into these same regions. The median inverter loading ratio grew to 1.32 in 2017, allowing the inverters to operate closer to full capacity for a greater percentage of the day. -Installed Prices: Median installed PV project prices have steadily fallen by two-thirds since the 2007-2009 period, to $2.0/WAC (or $1.6/WDC) for projects completed in 2017. The lowest 20th percentile of projects within our 2017 sample were priced at or below $1.8/WAC, with the lowest-priced projects around $0.9/WAC. Overall price dispersion across the entire sample has decreased steadily every year since 2013; similarly, price variation across regions decreased in 2017. -Operation and Maintenance ("O&M") Costs: PV O&M costs were in the neighborhood of $16/kWAC-year, or $8/MWh, in 2017. These numbers include only those costs incurred to directly operate and maintain the generating plant. -Capacity Factors: The cumulative net AC capacity factors of individual projects vary widely, from 14.3% to 35.2%, with a sample median of 26.3%. This project-level variation is based on a number of factors, including the strength of the solar resource at the project site, whether the array is mounted at a fixed tilt or on a tracking mechanism, the inverter loading ratio, degradation, and curtailment. Changes in at least the first three of these factors drove mean capacity factors higher from 2010-vintage to 2013-vintage projects, where they've remained fairly steady among more-recent project vintages as an ongoing increase in the prevalence of tracking has been offset by a build-out of lower resource sites. -PPA Prices and LCOE: Driven by lower installed project prices and improving capacity factors, levelized PPA prices for utility-scale PV have fallen dramatically over time, by $20-$30/MWh per year on average from 2006 through 2012, with a smaller price decline of ~$10/MWh per year evident from 2013 through 2016. Most recent PPAs in our sample—including many outside of California and the Southwest—are priced at or below $40/MWh levelized (in real 2017 dollars), with a few priced as aggressively as ~$20/MWh. The median LCOE among operational PV projects in our sample has followed PPA prices lower, suggesting a relatively competitive market for PPAs. -Solar's Wholesale Energy Market Value: Falling PPA prices have been offset to some degree by a decline in the wholesale energy market value of solar within higher-penetration markets like California, where solar earned just 79% of the average price across all hours within CAISO's real-time wholesale energy market in 2017 (down from 125% back in 2012). In other markets with less solar penetration, however, solar's hourly generation profile still earns more than the average wholesale price (e.g., 127% in ERCOT, 112% in PJM). -Solar+Storage: Adding battery storage is one way to at least partially restore the value of solar, and three recent PV+storage PPAs in Nevada (each using 4-hour batteries sized at 25% of PV nameplate capacity) suggest that the incremental PPA price adder for storage has fallen to ~$5/MWh, down from ~$15/MWh just a year ago for a similarly configured project. As PV plus battery storage becomes more cost-effective, a number of developers are regularly offering it as a viable upgrade to standalone PV. At the end of 2017, there were at least 188.5 GW of utility-scale solar power capacity within the interconnection queues across the nation. The 2017 growth within these queues is widely distributed across all regions of the country, but is most pronounced in the up-and-coming Midwest region, which accounts for 27% of the 99.2 GW of new queue capacity. The widening geographic distribution is as clear of a sign as any that the utility-scale market is maturing and expanding outside of its traditional high-insolation comfort zones.

14 SOLAR ENERGY↗
DOE OSTI2019

Utility-Scale Solar: Empirical Trends in Project Technology, Cost, Performance, and PPA Pricing in the United States (2019 Ed.)

The utility-scale solar sector has led the overall U.S. solar market in terms of installed capacity since 2012. In 2018, the utility-scale sector accounted for nearly 60% of all new solar capacity, and is expected to maintain its market-leading position for at least another six years. More than three-quarters of all states, representing all regions of the country, are now home to one or more utility-scale solar projects. This report—the seventh in an ongoing annual series—provides in-depth data-driven analysis of the utility-scale solar project fleet in the United States. Drawing on empirical project-level data from a wide range of sources, this report analyzes technology trends, installed project prices, operating costs, capacity factors, power purchase agreement (“PPA”) prices, the levelized cost of solar energy (LCOE), and the market value of solar. The report also includes data and observations about completed or recently announced solar+storage projects. Given its current preeminence in the market, utility-scale PV also dominates much of this report, though data from CPV and CSP projects are also presented where appropriate.

14 SOLAR ENERGY↗
DOE OSTI2023

Field Laboratory for Emerging Stacked Unconventional Plays in Central Appalachia

The goal of the Field Laboratory for Emerging Stacked Unconventional Plays (ESUP) in Central Appalachia project was to investigate and characterize the resource potential for multi-play production of emerging unconventional reservoirs in Central Appalachia. Project activities included drilling, logging and coring of a vertical characterization well drilled to basement to approximately 15,000 feet in depth. The data from drilling and well logs as well recovered core samples were used by the research team to support characterization of the geology and potential pay zones within the Nora Gas Field of southwestern Virginia and the greater Central Appalachian Basin. This project was led by Dr. Nino Ripepi of the Virginia Center for Coal and Energy Research (VCCER) in close collaboration with EnerVest Operating LLC (EnerVest). VCCER is housed in the Department of Mining and Minerals Engineering at Virginia Tech and was created by an Act of the Virginia General Assembly on March 30, 1977, as an interdisciplinary study, research, information, and resource facility for the Commonwealth of Virginia. EnerVest is a top tier, low-cost oil and natural gas company with a long history of traditional operating relationships with institutional investors as well as public and private companies. This report summarizes two major research activities: 1) Log and Core Analysis and 2) Numerical Modeling. Core analysis comprises the characterization efforts of the ESUP Field Laboratory and includes a discussion of the well logs run in the deep characterization wells, an initial analysis of those, the number, size and location of cores recovered, core testing and analysis done to date as well as plans for future analysis. Numerical modeling is comprised of seven major modeling efforts, including (1) Multiphysics shale transport modeling work, (2) the developed in-house compositional simulator studies, (3) reservoir modeling studies using GEM software, (4) fracture modeling work using EFRAC3D software and (5) numerical modeling efforts with ABAQUS software, (6) Numerical modeling efforts using FLAC3D and PFC3D, and (7) Automatic Machine Learning (AutoML) Studies.

02 PETROLEUM↗
DOE OSTI2024

2024 OES-Environmental 2024 State of the Science Report, Chapter 6: Strategies to Aid Consenting Processes for Marine Renewable Energy

While the marine renewable energy (MRE) industry has made positive strides in the past decade, challenges remain that stall forward progress, scaling up, and commercialization. For MRE to provide a viable solution to address the effects of climate change and achieve sustainable development and renewable energy goals, identifying and understanding barriers and opportunities to deployment is key. Barriers to date have included long consenting timelines, costly in-depth baseline data collection and monitoring requirements, and hesitancy in some countries to approve device and array deployments (Copping & Hemery 2020; Kramer et al. 2020). Some of the key drivers behind these barriers are 1) uncertainty about potential effects of MRE on marine animals, habitats, and the environment; 2) lack of familiarity with MRE technologies; or 3) challenges accessing available scientific information (Copping et al. 2020a).

16 TIDAL AND WAVE POWER↗
DOE OSTI2022

Metatransciptomic Analysis Data for Interactive effects of depth and differential irrigation on soil microbiome composition and functioning

RNA was collected from soil at different depths and after three different levels of irrigation T1 100% of normal field irrigation, T4: 18.75% or normal irrigation and T5: unirrigated controls. Total RNA was isolated using the Zymo Quick-RNA fecal/soil microbe miniprep (catalog no. R2040), incorporating the DNase I treatment using Zymo’s DNase I kit (catalog no. E1010). To increase the yield of RNA, we modified the manufacturer’s instructions by first doubling the amount of soil per extraction (from 0.25 g to 0.5 g) and by performing extractions in triplicate before pooling separate extractions together. Certain soil samples (largely those from deeper soil layers) had low yield (< 100 ng per extraction) so additional rounds of extraction were performed to obtain sufficient RNA. RNA concentration was assessed using a Qubit RNA HS assay kit (Thermo Fisher) and RNA quality was determined using an Agilent 2100 BioAnalyzer (Agilent; Santa Clara, CA). The resultant RNA samples were then sequenced by GENEWIZ using Illumina technology (GENEWIZ; South Plainfield, NJ). Sequences were then aligned to a soil metagenome previously obtained from the same site using the Burrows-Wheeler aligner (BWA). SAM files were then converted to raw counts using HTSeq.

Soil microbiome, metatranscriptomics↗
DOE OSTI2017

Uniform Silicon Isotope Ratios Across the Milky Way Galaxy

We report the relative abundances of the three stable isotopes of silicon, {sup 28}Si, {sup 29}Si, and {sup 30}Si, across the Galaxy using the v=0,J=1→0 transition of silicon monoxide. The chosen sources represent a range in Galactocentric radii (R{sub GC}) from 0 to 9.8 kpc. The high spectral resolution and sensitivity afforded by the Green Bank Telescope permit isotope ratios to be corrected for optical depths. The optical-depth-corrected data indicate that the secondary-to-primary silicon isotope ratios {sup 29}Si/{sup 28}Si and {sup 30}Si/{sup 28}Si vary much less than predicted on the basis of other stable isotope ratio gradients across the Galaxy. Indeed, there is no detectable variation in Si isotope ratios with R{sub GC}. This lack of an isotope ratio gradient stands in stark contrast to the monotonically decreasing trend with R{sub GC} exhibited by published secondary-to-primary oxygen isotope ratios. These results, when considered in the context of the expectations for chemical evolution, suggest that the reported oxygen isotope ratio trends, and perhaps those for carbon as well, require further investigation. The methods developed in this study for SiO isotopologue ratio measurements are equally applicable to Galactic oxygen, carbon, and nitrogen isotope ratio measurements, and should prove useful for future observations of these isotope systems.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2020

Understanding and improving model representation of aerosol optical properties for a Chinese haze event measured during KORUS-AQ

KORUS-AQ was an international cooperative air quality field study in South Korea that measured local and remote sources of air pollution affecting the Korean Peninsula during May–June 2016. Some of the largest aerosol mass concentrations were measured during a Chinese haze transport event (24 May). Air quality forecasts using the WRF-Chem model with aerosol optical depth (AOD) data assimilation captured AOD during this pollution episode but overpredicted surface particulate matter concentrations in South Korea, especially PM 2.5 , often by a factor of 2 or larger. Analysis revealed multiple sources of model deficiency related to the calculation of optical properties from aerosol mass that explain these discrepancies. Using in situ observations of aerosol size and composition as inputs to the optical properties calculations showed that using a low-resolution size bin representation (four bins) underestimates the efficiency with which aerosols scatter and absorb light (mass extinction efficiency). Besides using finer-resolution size bins (8–16 bins), it was also necessary to increase the refractive indices and hygroscopicity of select aerosol species within the range of values reported in the literature to achieve better consistency with measured values of the mass extinction efficiency (6.7 m 2 g –1 observed average) and light-scattering enhancement factor (ƒ(RH)) due to aerosol hygroscopic growth (2.2 observed average). Furthermore, an evaluation of the optical properties obtained using modeled aerosol properties revealed the inability of sectional and modal aerosol representations in WRF-Chem to properly reproduce the observed size distribution, with the models displaying a much wider accumulation mode. Other model deficiencies included an underestimate of organic aerosol density (1.0 g cm –3 in the model vs. observed average of 1.5 g cm –3 ) and an overprediction of the fractional contribution of submicron inorganic aerosols other than sulfate, ammonium, nitrate, chloride, and sodium corresponding to mostly dust (17 %–28 % modeled vs. 12 % estimated from observations). These results illustrate the complexity of achieving an accurate model representation of optical properties and provide potential solutions that are relevant to multiple disciplines and applications such as air quality forecasts, health impact assessments, climate projections, solar power forecasts, and aerosol data assimilation.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2015

SU-E-T-99: An Analysis of the Accuracy of TPS Extrapolation of Commissioning Data

Purpose: To investigate discrepancies between measured percent depth dose curves of a linear accelerator at depths beyond the commissioning data and those generated by the treatment planning system (TPS) via extrapolation. Methods: Relative depth doses were measured on an Elekta Synergy™ linac for photon beams of 6 -MV and 10-MV. SSDs for all curves were 100-cm and field sizes ranged from 4×4 to 35×35-cm{sup 2}. As most scanning tanks cannot provide depths greater than about 30-cm, percent depth dose measurements, extending 45-cm depths, were performed in Solid Water™ using a 0.125-cc ionization chamber (PTW model TN31012). The buildup regions of the curves were acquired with a parallel plate chamber (PTW model TN34001). Extrapolated curves were generated by the TPS (Phillips Pinnacle{sup 3} v. 9.6) by applying beams to CT images of 50-cm of Solid Water™ with density override set to 1.0-g/cc. Results: Percent difference between the two sets of curves (measured and TPS) was investigated. There is significant discrepancy in the buildup region to a depth of 7-mm. Beyond this depth, the two sets show good agreement. When analyzing the tail end of the curves, we saw percent difference of between 1.2% and 3.2%. The highest disagreement for the 6-MV curves was 10×10-cm{sup 2} (3%) and for the 10-MV curves it was the 35×35-cm{sup 2} (3.2%). Conclusion: A qualitative analysis of the measured data versus PDD curves generated by the TPS shows generally good agreement beyond 1-cm. However, a measurable percent difference was observed when comparing curves at depths beyond that provided by the commissioning data and at depths in the buildup region. Possible explanations for this include inaccuracies in modeling of the Solid Water™ or drift in beam energy since commissioning. Additionally, closer attention must be paid for measurements in the buildup region.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2014

Area 2: Inexpensive Monitoring and Uncertainty Assessment of CO 2 Plume Migration using Injection Data

In-depth understanding of the long-term fate of CO₂ in the subsurface requires study and analysis of the reservoir formation, the overlaying caprock formation, and adjacent faults. Because there is significant uncertainty in predicting the location and extent of geologic heterogeneity that can impact the future migration of CO₂ in the subsurface, there is a need to develop algorithms that can reliably quantify this uncertainty in plume migration. This project is focused on the development of a model selection algorithm that refines an initial suite of subsurface models representing the prior uncertainty to create a posterior set of subsurface models that reflect injection performance consistent with that observed. Such posterior models can be used to represent uncertainty in the future migration of the CO₂ plume. Because only injection data is required, the method provides a very inexpensive method to map the migration of the plume and the associated uncertainty in migration paths. The model selection method developed as part of this project mainly consists of assessing the connectivity/dynamic characteristics of a large prior ensemble of models, grouping the models on the basis of their expected dynamic response, selecting the subgroup of models that most closely yield dynamic response closest to the observed dynamic data, and finally quantifying the uncertainty in plume migration using the selected subset of models. The main accomplishment of the project is the development of a software module within the SGEMS earth modeling software package that implements the model selection methodology. This software module was subsequently applied to analyze CO₂ plume migration in two field projects – the In Salah CO₂ Injection project in Algeria and CO₂ injection into the Utsira formation in Norway. These applications of the software revealed that the proxies developed in this project for quickly assessing the dynamic characteristics of the reservoir were highly efficient and yielded accurate grouping of reservoir models. The plume migration paths probabilistically assessed by the method were confirmed by field observations and auxiliary data. The report also documents the application of the software to answer practical questions such as the optimum location of monitoring wells to reliably assess the migration of CO₂ plume, the effect of CO₂-rock interactions on plume migration and the ability to detect the plume under those conditions and the effect of a slow, unresolved leak on the predictions of plume migration.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2022

A Meteorology and Snow Data Set From Adjacent Forested and Meadow Sites at Crested Butte, CO, USA

We present meteorology and snow observation data collected at sites in the southwestern Colorado Rocky Mountains (USA) over three consecutive water years with different amounts of snow water equivalent (SWE) accumulation: A year with above average SWE (2019), a year with average SWE (2020), and a year with below average SWE (2021). This data set is distinguished by its emphasis on paired open-forest sites in a continental snow climate. Approximately once a month during February–May, we collected data from 15 to 20 snow pits and took 8 to 19 snow depth transects. Our sampling sites were in open and adjacent forested areas at 3,100 m and in a lower elevation aspen (3,035 m) and higher elevation conifer stand (3,395 m). In total, we recorded 270 individual snow pit density and temperature profiles and over 4,000 snow depth measurements. These data are complimented by continuous meteorological measurements from two weather stations: One in the open and one in the adjacent forest. Meteorology data—including incoming shortwave and longwave radiation, outgoing shortwave radiation, relative humidity, wind speed, snow depth, and air and infrared surface temperature—were quality controlled and the forcing data were gap-filled. These data are available to download from Bonner, Smyth, et al. at three levels of processing, including a level with downscaled, adjusted precipitation based on data assimilation using observed snow depth and a process-based snow model. We demonstrate the utility of these data with a modeling experiment that explores open-forest differences and identifies opportunities for improvements in model representation.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2024

Machine learning snow depth predictions at sites in Alaska, Norway, Siberia, Colorado and New Mexico

Temporally continuous snow depth estimates are vital for understanding changing snow patterns in the Arctic and impacts on permafrost. We trained random forest machine learning models to predict snow depth from temperature data recorded at or just below the ground surface. Training data was collected at the Teller 27 Watershed and Kougarok 64 Hillslope during the 2021 - 2022 water year on the Seward Peninsula, Alaska using distributed temperature profiling (DTP) systems. We then applied this model to other sites where ground surface or shallow soil temperature data was available for at least one water year (see Related Datasets). Many of these temperature measurements were collocated with snow depth observations. Ground surface temperature (i.e. snow-ground interface temperature) is easy to measure using small, cheap and easy-to-deploy temperature sensors such as iButtons and TinyTags, and such measurements have previously been used to calculate a variety of snow metrics (e.g. snow onset date). However, this is the first study to estimate snow depth directly from ground surface temperature data. The present dataset contains one *.csv file which includes machine learning snow depth predictions at sites in Alaska, Norway, Siberia, Colorado, and New Mexico and one *.kml file including the locations of sites with snow depth predictions. No training data predictions are included in the *.csv file. The Next-Generation Ecosystem Experiments: Arctic (NGEE Arctic), was a research effort to reduce uncertainty in Earth System Models by developing a predictive understanding of carbon-rich Arctic ecosystems and feedbacks to climate. NGEE Arctic was supported by the Department of Energy’s Office of Biological and Environmental Research. The NGEE Arctic project had two field research sites: 1) located within the Arctic polygonal tundra coastal region on the Barrow Environmental Observatory (BEO) and the North Slope near Utqiagvik (Barrow), Alaska and 2) multiple areas on the discontinuous permafrost region of the Seward Peninsula north of Nome, Alaska. Through observations, experiments, and synthesis with existing datasets, NGEE Arctic provided an enhanced knowledge base for multi-scale modeling and contributed to improved process representation at global pan-Arctic scales within the Department of Energy’s Earth system Model (the Energy Exascale Earth System Model, or E3SM), and specifically within the E3SM Land Model component (ELM).

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2019

OccuTherm: Occupant Thermal Comfort Inference using Body Shape Information

This repository contains the official data from a USDOE-funded project at Carnegie Mellon University and Bosch Research Pittsburgh. The primary goal of the project was to investigate the relationship between indoor commercial building occupant thermal comfort and various biometric and environmental predictors. We performed 77 individual comfort experiments, approved by our Institutional Review Board (IRB) and in satisfaction of participant consent guidelines. Our goal was to generate a dataset than enables comprehensive study of human thermal comfort preferences, in a commercial building environment, across a wide range of indoor environmental conditions. The data is comprised of the following feature groups: depth camera frames, biometrics sensor data, body shape information, subjective comfort data from the mobile device application, environmental sensor data from the commercial building HVAC system, and outdoor weather station data.

47 OTHER INSTRUMENTATION↗
DOE OSTI2013

Updated Subsurface Data Base For Bear Creek Valley, Chestnut Ridge, And Parts Of Bethel Valley On The U.S. Department of Energy Oak Ridge Reservation

This document represents a compilation of location, construction, and hydrologic information relating to boreholes, groundwater monitoring wells, and surface water locations that have been installed/established at the Y-12 National Security Complex (Y-12) through August 2013. To date, a total of 1422 boreholes and wells have been installed in and around the Y-12 area. Of those, 835 existing boreholes and wells continue to be utilized for groundwater monitoring programs, research, remedial investigations, plume characterization and delineation studies, and various other hydrogeologic endeavors. In addition, 215 surface water locations, such as rivers, streams, seeps, springs, lakes, ponds, and building sumps are included in this database. General data about boreholes and wells included in the database are survey coordinates, survey system, elevations, alternative names and well status. Surface water location information (Appendix I) includes name, alias, functional area, northing and easting coordinates, survey system, map number and sampling history. Tabulated construction data include total depth, completion method, borehole diameter, casing and screen materials, casing and screen diameters, casing and screen depths, filter pack depths, open-hole intervals, and open-hole diameters. Hydrogeological data summarized in this document include the aquifer monitored by the completion interval, depth to weathered and fresh bedrock, formations penetrated, well sampling history, and whether rock core and geophysical logs were obtained. This document (which is the sixth revision to Y/TS–881 and the ninth overall update of a previous compilation) is published on a regular basis by the Y-12 Groundwater Protection Program (GWPP), which serves as custodian of drilling records and well construction data for the network of wells and other groundwater monitoring stations at Y-12. The tabulations in this database are arranged in appendices of like information. An example application of the data compiled in this document would be the evaluation of the suitability of wells for continued use in groundwater investigations and monitoring studies. Other uses may include: the siting of hydrogeological characterization activities, background evaluations of sites prior to initiation of new drilling activities, and hydrogeological review of selected sites prior to the initiation of remedial actions or new construction activity. Existing boreholes, wells, and surface water locations are presented on a series of maps (Appendix K). Boreholes and wells that have been plugged and abandoned, destroyed, could not be located, or otherwise are of unknown status/condition appear on a second series of maps of identical coverage (Appendix L).

54 ENVIRONMENTAL SCIENCES↗