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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 793 records · Page 44

Effects of 9.5 years warming on SOC concentration and composition in bulk soil and density fractions

Original data of whole-soil warming experiment after 9.5 years at Blodgett Forest Research Station. The Blodgett Forest is a mixed coniferous temperate forest with Mediterranean climate. The annual air temperature is 12.5℃ and the annual precipitation is 1774 mm yr-1- The soil is mesic ultic Alfisol of granitic origin, equivalent to Dystric Cambisol according to The World Reference Base for Soil Resources (WRB) system. The soil is warmed down to 1 m at + 4℃ by vertically installed heating cables. At the time of soil sampling on 1 May 2023, the whole-soil warming experiment had been running for approximately 9.5 years, from January 2014 to May 2023. The dataset includes: - Bulk_EA: C, N content, δ13C, and CN ratio of bulk soil; - Density_fractionation: organic carbon concentration, δ13C, and C/N ratio of free light fraction (fLF), occluded ligh fraction (oLF), and heavy fraction (HF); - PCA_DRIFT_AUC: original data of area under the curve (AUC) values of eight carbon bond types integrated on diffuse reflectance infrared fourier transform spectroscopy for each soil sample and soil fraction, which are consequently used for principal component analysis (PCA); - DRIFTS_stability_index: the calculation of aliphatic C–H (3000–2800 cm-1) to aromatic C=C (1670–1600 cm-1) ratios for each bulk soil sample and soil fraction. All data are provided in CSV format and can be viewed using Microsoft Excel.

Climate change↗

pvlib python: a python package for modeling solar energy systems

pvlib python is a community-supported open source tool that provides a set of functions and classes for simulating the performance of photovoltaic energy systems. pvlib python aims to provide reference implementations of models relevant to solar energy, including for example algorithms for solar position, clear sky irradiance, irradiance transposition, DC power, and DC-to-AC power conversion. pvlib python is an important component of a growing ecosystem of open source tools for solar energy (William F. Holmgren, Hansen, Stein, & Mikofski, 2018).

14 SOLAR ENERGY↗

Calendar Year 2010 Groundwater Monitoring Report, U.S. Department Of Energy Y-12 National Security Complex, Oak Ridge, Tennessee

This report contains the groundwater and surface water monitoring data that were obtained during calendar year (CY) 2010 at the U.S. Department of Energy (DOE) Y-12 National Security Complex (hereafter referenced as Y-12) on the DOE Oak Ridge Reservation (ORR) in Oak Ridge, Tennessee. The CY 2010 monitoring data were obtained from wells, springs, and surface water sampling locations in three hydrogeologic regimes at Y-12 (Figure A.1). The Bear Creek Hydrogeologic Regime (Bear Creek Regime) encompasses a section of Bear Creek Valley (BCV) between the west end of Y-12 and the west end of the Bear Creek Watershed (directions are in reference to the Y-12 grid system). The Upper East Fork Poplar Creek Hydrogeologic Regime (East Fork Regime) encompasses the Y-12 industrial facilities and support structures in BCV. The Chestnut Ridge Hydrogeologic Regime (Chestnut Ridge Regime) encompasses a section of Chestnut Ridge directly south of Y-12. Section 2 of this report provides background information pertinent to groundwater and surface water quality monitoring in each hydrogeologic regime, including the topography and bedrock geology, surface water drainage, groundwater system, and extent of groundwater contamination. The CY 2010 groundwater and surface water monitoring data in this report were obtained from sampling and analysis activities implemented under the Y-12 Groundwater Protection Program (GWPP) managed by Babcock & Wilcox Technical Services Y-12, LLC (B&W Y-12) and from sampling and analysis activities implemented under several monitoring programs managed by Bechtel Jacobs Company LLC (BJC). Cooperative implementation of the monitoring programs directed by the Y-12 GWPP and BJC (i.e., coordinating sample collection and sharing data) ensures that the CY 2010 monitoring results fulfill requirements of all the applicable monitoring drivers with no duplication of sampling and analysis efforts. Section 3 of this report contains a summary of information regarding the groundwater and surface water sampling and analysis activities implemented under the Y-12 GWPP including sampling locations and frequency; quality assurance (QA)/quality control (QC) sampling; sample collection and handling; field measurements and laboratory analytes; data management and data quality objective (DQO) evaluation; and groundwater elevation monitoring. However, this report does not include equivalent QA/QC or DQO evaluation information regarding the groundwater and surface water sampling and analysis activities associated with the monitoring programs implemented by BJC. Such details are deferred to the respective programmatic plans and reports issued by BJC (see Section 3.0). Collectively, the groundwater and surface water monitoring data obtained during CY 2010 by the Y-12 GWPP and BJC address DOE Order 450.1A (Environmental Protection Program) requirements for monitoring groundwater and surface water quality in areas: (1) which are, or could be, affected by operations at Y-12 (surveillance monitoring); and (2) where contaminants from Y-12 are most likely to migrate beyond the boundaries of the ORR (exit pathway/perimeter monitoring). Section 4 of this report presents a summary evaluation of the monitoring data with regard to the respective objectives of surveillance monitoring and exit pathway/perimeter monitoring, based on the analytical results for the principal groundwater contaminants at Y-12: nitrate, uranium, volatile organic compounds (VOCs), gross alpha activity, and gross beta activity. Section 5 of this report summarizes the most pertinent findings regarding the principal contaminants, along with recommendations proposed for ongoing groundwater and surface water quality monitoring performed under the Y-12 GWPP.

54 ENVIRONMENTAL SCIENCES↗

Calendar Year 2011 Groundwater Monitoring Report, U.S. Department of Energy Y-12 National Security Complex

This report contains the groundwater and surface water monitoring data that were obtained during calendar year (CY) 2011 at the U.S. Department of Energy (DOE) Y-12 National Security Complex (Y-12) on the DOE Oak Ridge Reservation (ORR) in Oak Ridge, Tennessee. The CY 2011 monitoring data were obtained from wells, springs, and surface water sampling locations in three hydrogeologic regimes at Y-12. The Bear Creek Hydrogeologic Regime (Bear Creek Regime) encompasses a section of Bear Creek Valley (BCV) between the west end of Y-12 and the west end of the Bear Creek Watershed (directions are in reference to the Y-12 grid system). The Upper East Fork Poplar Creek Hydrogeologic Regime (East Fork Regime) encompasses the Y-12 industrial facilities and support structures in BCV. The Chestnut Ridge Hydrogeologic Regime (Chestnut Ridge Regime) encompasses a section of Chestnut Ridge directly south of Y-12. This report provides background information pertinent to groundwater and surface water quality monitoring in each hydrogeologic regime, including the topography and bedrock geology, surface water drainage, groundwater system, and known extent of groundwater contamination.

54 ENVIRONMENTAL SCIENCES↗

Recovery Act: High-Temperature Circuit Boards for use in Geothermal Well Monitoring Applications

The U.S. Department of Energy is leading the development of alternative energy sources that will ensure the long-term energy independence of our nation. One of the key renewable resources currently being advanced is geothermal energy. To tap into the large potential offered by generating power from the heat of the earth, and for geothermal energy to be more widely used, it will be necessary to drill deeper wells to reach the hot, dry rock located up to 10 km beneath the earth’s surface. In this instance, water will be introduced into the well to create a geothermal reservoir. A geothermal well produced in this manner is referred to as an enhanced geothermal system (EGS). EGS reservoirs are typically at depths of 3 to 10 km, and the temperatures at these depths have become a limiting factor in the application of existing downhole technologies. These high temperatures are especially problematic for electronic systems such as downhole data-logging tools, which are used to map and characterize the fractures and high-permeability regions in underground formations. Information provided by these tools is assessed so that underground formations capable of providing geothermal energy can be identified, and the subsequent drilling operations can be accurately directed to those locations. The mapping of geothermal resources involves the design and fabrication of sensor packages, including the electronic control modules, to quantify downhole conditions (300°C temperature, high pressure, seismic activity, etc.). Because of the extreme depths at which these measurements are performed, it is most desirable to perform the sensor signal processing downhole and then transmit the information to the surface. This approach necessitates the use of high-temperature electronics that can operate in the downhole environment. Downhole signal processing in EGS wells will require the development and demonstration of circuit boards that can withstand the elevated temperatures found at these depths. At present, the highest-temperature commercially available circuit boards are based on polyimide materials, and those have maximum use temperatures of 200 to 250°C. In addition to thermal stability, downhole electronics must also be fabricated into high-aspect-ratio packages. For example, the multilayer assemblies produced at SNL were approximately 2.5 cm wide and 50 cm long. Because of this very high form factor, glass-fiber-reinforced polymers are much more desirable than multilayer ceramic modules (MCM). MCMs have many advantages for some applications, but are susceptible to damage induced by the mechanical and vibrational loads commonly experienced by data-logging tools. Thus, as EGS technology continues to advance, there is a strong need for multilayer electronics that can provide the necessary thermal performance while also being compatible with high-form-factor circuit designs. This project involved the design and development of high-temperature circuit materials, as well as the fabrication and testing of circuit components. The material development included the evaluation of various polymer/fiberglass composites, whereas the circuit components were tested using conventional microelectronic evaluation techniques. This effort targeted development of a new class of high-temperature multilayer circuit boards for use in downhole data-logging applications where temperatures are on the order of 300°C. This is consistent with DOE’s multiyear plan for advancing technologies for use in enhanced geothermal systems. Organic and inorganic polymer systems, both with glass reinforcements, were considered to provide the following performance at elevated temperatures: • Mechanical strength and durability • High dielectric strength and electrical resistivity • Thermal stability • Strong adhesion to copper to ensure the reliability of the multilayer assemblies • Processing characteristics that are consistent with state-of-the-art multilayer circuit board manufacturing practices

15 GEOTHERMAL ENERGY↗

Future Grid State Modeling for Transactive Systems

The simulation design and evaluation of a transactive energy system is contingent on the setting in which it would exist, which could vary significantly with the many drivers that impact the potential future states of the power system. This report summarizes the development of the Transactive Future Grid State (TFGS) model, which is a lightweight capacity expansion model that will support transactive energy research by allowing users to explore alternative future states. The TFGS model determines the long-term generation capacity needs of a given power system that satisfy specified constraints and support a least cost hourly dispatch. This is accomplished by solving a single optimization problem that simultaneously finds the generation fleet with capacity sufficient to meet peak load and the flexibility to meet hourly operational dispatch, all at lowest cost. The TFGS model was applied to a larger ongoing study taking place that will be simulating how distribution system operators (DSOs) could use a transactive energy system to manage distributed energy resources. The larger study, commonly referred to as the DSO+T study, involves two parallel analyses; one that represents the system today and one that represents a future system with a high degree of renewable energy penetration. The TFGS model provided the generation mix of the high renewable base case. As the TFGS model was being used to provide inputs to the DSO+T study, two issues became apparent. First, additional functionality would have been useful, and second, a larger-than-anticipated amount of user inputs and data were required to successfully use the TFGS model. These discoveries have lead to the recommendation of specific functionality that can be added in future development of the tool.

24 POWER TRANSMISSION AND DISTRIBUTION↗

RSE-Ops

If DevOps is the intersection of "Developer" and "Operations," then how does this concept map to high performance computing? The answer is RSE-ops, or the intersection of Research Software Engineering and Operations. Research Software Engineers (RSEs) are the individuals writing code for scientific software, and supporting researchers to use codes on high performance computing systems. RSE-ops, then, generally refers to best practices for development and operations of scientific software, which typically happens in a high performance computing environment. A comparison can be made to Cloud Native Devops, which is a similar term that has emerged around Cloud Native Computing. It refers to the application of DevOps practices to the cloud.

97 MATHEMATICS AND COMPUTING↗

Ground Truth for CSP Mirror Metrology (Full-Length)

The high optical accuracy required for concentrating solar power (CSP) systems in turn requires accurate metrology to assess mirror optical parameters during design, manufacturing, and operation. To meet this need, researchers have developed a variety of CSP optical metrology systems, which include complex calculations and calibration terms. This raises the question: How do we know these methods’ accuracy? One approach is to compare metrology system measurements against a ground truth reference.

14 SOLAR ENERGY↗

Site G - Atmospheric Sensor / Reviewed Data

This dataset contains meteorological measurements including temperature, pressure, and relative humidity at multiple heights deployed on tethered balloon system at AWAKEN site G. Z07 refers to the seventh height position of the iMet-XQ2 mounted on the tethered balloon.

17 WIND ENERGY↗

Site G - Atmospheric Sensor / Reviewed Data

This dataset contains meteorological measurements including temperature, pressure, and relative humidity at multiple heights deployed on tethered balloon system at AWAKEN site G. Z06 refers to the sixth height position of the iMet-XQ2 mounted on the tethered balloon.

17 WIND ENERGY↗

Site G - Atmospheric Sensor / Reviewed Data

This dataset contains meteorological measurements including temperature, pressure, and relative humidity at multiple heights deployed on tethered balloon system at AWAKEN site G. Z05 refers to the fifth height position of the iMet-XQ2 mounted on the tethered balloon.

17 WIND ENERGY↗

Site G - Atmospheric Sensor / Reviewed Data

This dataset contains meteorological measurements including temperature, pressure, and relative humidity at multiple heights deployed on tethered balloon system at AWAKEN site G. Z04 refers to the fourth height position of the iMet-XQ2 mounted on the tethered balloon.

17 WIND ENERGY↗

Site G - Atmospheric Sensor / Reviewed Data

This dataset contains meteorological measurements including temperature, pressure, and relative humidity at multiple heights deployed on tethered balloon system at AWAKEN site G. Z03 refers to the third height position of the iMet-XQ2 mounted on the tethered balloon.

17 WIND ENERGY↗

Site G - Atmospheric Sensor / Reviewed Data

This dataset contains meteorological measurements including temperature, pressure, and relative humidity at multiple heights deployed on tethered balloon system at AWAKEN site G. Z02 refers to the second height position of the iMet-XQ2 mounted on the tethered balloon.

17 WIND ENERGY↗

Site G - Atmospheric Sensor / Reviewed Data

This dataset contains meteorological measurements including temperature, pressure, and relative humidity at multiple heights deployed on tethered balloon system at AWAKEN site G. Z01 refers to the first height position of the iMet-XQ2 mounted on the tethered balloon.

17 WIND ENERGY↗

Site A1 - Atmospheric Sensor / Reviewed Data

This dataset contains meteorological measurements including temperature, pressure, and relative humidity at multiple heights deployed on tethered balloon system at AWAKEN site A1. Z06 refers to the sixth height position of the iMet-XQ2 mounted on the tethered balloon.

17 WIND ENERGY↗

Site A1 - Atmospheric Sensor / Reviewed Data

This dataset contains meteorological measurements including temperature, pressure, and relative humidity at multiple heights deployed on tethered balloon system at AWAKEN site A1. Z01 refers to the first height position of the iMet-XQ2 mounted on the tethered balloon.

17 WIND ENERGY↗

Site A1 - Atmospheric Sensor / Reviewed Data

This dataset contains meteorological measurements including temperature, pressure, and relative humidity at multiple heights deployed on tethered balloon system at AWAKEN site A1. Z04 refers to the fourth height position of the iMet-XQ2 mounted on the tethered balloon.

17 WIND ENERGY↗