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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 199 records · Page 11
All sourcesNASA NTRSDOE OSTI
DOE OSTI2016

A experimental research program on chirality at the LHC

Heavy-ion collisions provide a unique opportunity to investigate the fundamental laws of physics of the strong force. The extreme conditions created by the collisions within a finite volume are akin to the properties of the deconfined partonic state which existed very shortly after the Big Bang and just prior to visible matter formation in the Universe. In this state massless quarks and gluons (partons) are ``quasi free" particles, the so-called Quark Gluon Plasma (QGP). By following the expansion and cooling of this state, we will map out the process of nucleonic matter formation, which occurs during the phase transition. The fundamental properties of this early partonic phase of matter are not well understood, but they are essential for confirming QCD (Quantum Chromo-Dynamics) and the Standard Model. The specific topic, chiral symmetry restoration, has been called ``the remaining puzzle of QCD.'' This puzzle can only be studied in the dense partonic medium generated in heavy-ion collisions. The research objectives of this proposal are the development and application of new analysis strategies to study chirality and the properties of the medium above the QGP phase transition using hadronic resonances detected with the ALICE experiment at the Large Hadron Collider (LHC) at the CERN research laboratory in Switzerland. This grant funded a new effort at the University of Texas at Austin (UT Austin) to investigate the Quark Gluon Plasma (QGP) at the highest possible energy of 2.76 TeV per nucleon at the Large Hadron Collider (LHC) at CERN via the ALICE experiment. The findings added to our knowledge of the dynamical evolution and the properties of the hot, dense matter produced in heavy-ion collisions, and provided a deeper understanding of multi-hadron interactions in these extreme nuclear matter systems. Our group contributed as well to the hardware and software for the ALICE USA-funded Calorimeter Detector (EMCal). The LHC research program and its connection to fundamental questions in high energy, nuclear and astrophysics has triggered the imagination of many young students worldwide. The studies also promoted the early involvement of students and young postdocs in a large, multi-national research effort abroad, which provided them with substantial experience and skills prior to choosing their career path. The undergraduate program, in conjunction with the Freshman Research Initiative at UT Austin, allowed the students to complete a research project within the field of Nuclear Physics.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2019

Evaluation of Nondestructive Examination Responses from Chloride-Induced Stress Corrosion Cracks: Fabrication of Base Metal Test Specimens

This report documents efforts to create actual chloride-induced stress corrosion cracks (CISCCs) in stainless-steel specimens for evaluating application of nondestructive examination (NDE) technologies for detection and sizing of CISCC in stainless-steel canisters in dry storage systems (DSSs) for spent nuclear fuel. In the United States, several DSSs for commercial spent nuclear fuel are approaching the end of their initial licensed or certified term. Many of these systems were originally licensed or certified for 20 years, after which the licensing or certification may be renewed for periods up to 40 years, according to Title 10 of the Code of Federal Regulations (10 CFR), Part 72, “Licensing Requirements for the Independent Storage of Spent Nuclear Fuel, High-Level Radioactive Waste, and Reactor-Related Greater than Class C Waste.” Guidance for review of renewal applications is provided in NUREG-1927, Standard Review Plan for Renewal of Spent Fuel Dry Cask Storage System Licenses and Certificates of Compliance. A review of aging effects that could affect important-to-safety structures, systems, and components is required in renewal applications and applicants are required to address aging effects using either a time-limited aging analysis or an aging management program. The U.S. Nuclear Regulatory Commission (NRC) issued NUREG-2214, Managing Aging Processes In Storage (MAPS) Report, which provides guidance on the evaluation of known aging degradation mechanisms to determine if they could affect the ability of dry storage system components to fulfill their safety functions in the 20- to 60-year period of extended operation.

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗
DOE OSTI2020

Evaluation of Increased Peak Temperatures for Spent Fuel Cladding Performance during Dry Storage (Rev.1)

NUREG-2214, “Managing Aging Processes in Storage (MAPS) Report,” (2019) documents the technical basis for age-related degradation mechanisms on spent nuclear fuel assemblies during dry storage operations. The technical bases have been reviewed, and hoop cladding stress calculations were conducted using the Fuel Analysis under Steady-state and Transients (FAST) code at elevated normal condition temperatures of 425°C and 450°C, and at an off-normal and accident conditions temperature of 600°C. The NUREG-2214 conclusions are substantiated by the referenced literature. The calculations demonstrate that the aging mechanisms primarily driven by hoop stress such as hydride reorientation, delayed hydride cracking, thermal and athermal (low-temperature) creep, and localized mechanical overload are either not credible or do not compromise the fuel assembly’s performance for increased peak normal condition temperatures of 425°C or 450°C during the up to 60-year dry storage period. Other aging mechanisms considered are also not credible for compromising the fuel assembly’s performance during 60-year dry storage with a peak temperature of 400ºC as specified in ISG – 11 Rev. 3, and the same is indicated for the increased peak normal condition temperatures of 425°C or 450°C.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2021

SLOPE daily and 250 m gross primary productivity (GPP) for the CONUS, 2000-2019, Carbon Monitoring System (CMS)

The SatelLite Only Photosynthesis Estimation (SLOPE) GPP product is a daily, 250 m GPP dataset covering the Contiguous United States (CONUS) from 2000 to present with 1 day latency. Gross primary productivity (GPP) quantifies the amount of carbon dioxide (CO2) fixed by plants through photosynthesis. Although as a key quantity of terrestrial ecosystems, there is a lack of high-spatial-and-temporal-resolution, real-time, and observation-based GPP products. This product has been developed to address this critical gap, leveraging a number of MODIS land and atmosphere products. There are three distinct features of the SLOPE GPP production algorithm. (1) SLOPE couples machine learning models with MODIS atmosphere and land products to accurately estimate PAR. (2) SLOPE couples highly efficient and pragmatic gap-filling and filtering algorithms with surface reflectance acquired by both Terra and Aqua MODIS satellites to derive a soil-adjusted NIRv (SANIRv) dataset. (3) SLOPE couples a temporal pattern recognition approach with a long-term Crop Data Layer (CDL) product to predict dynamic C4 crop fraction. PAR, SANIRv and C4 fraction are used to drive a parsimonious model with only two slope parameters to estimate GPP along with a quantitative uncertainty on a per-pixel and daily basis. The slope GPP product has a R2 = 0.84 and a root-mean-square error (RMSE) of 1.65 gC m-2 d-1, evaluated against from 50 AmeriFlux eddy covariance sites (332 site-years). Archived data from 2000 to 2019 are publicly available at the NASA's Oak Ridge National Laboratory Distributed Active Archive Center (ORNL DAAC). Data from 2020 are available from the authors upon request. All data are projected in the standard MODIS Land Integerized Sinusoidal tile map projection. Each processing tile is in size of 4800 pixels by 4800 pixels, representing approximately 1200 km by 1200 km land region. In addition to the GPP product, SLOPE PAR, SANIRV, and C4 fraction, along with their uncertainties, are also released.

Jiang, Chongya↗
DOE OSTI2016

Type Ia Supernova Explosions From Hybrid Carbon–Oxygen–Neon White Dwarf Progenitors

Motivated by recent results in stellar evolution that predict the existence of hybrid white dwarf (WD) stars with a C–O core inside an O–Ne shell, we simulate thermonuclear (Type Ia) supernovae from these hybrid progenitors. We use the FLASH code to perform multidimensional simulations in the deflagration-to-detonation transition (DDT) explosion paradigm. Our hybrid progenitor models were produced with the MESA stellar evolution code and include the effects of the Urca process, and we map the progenitor model to the FLASH grid. We performed a suite of DDT simulations over a range of ignition conditions consistent with the progenitor's thermal and convective structure assuming multiple ignition points. To compare the results from these hybrid WD stars to previous results from C–O WDs, we construct a set of C–O WD models with similar properties and similarly simulate a suite of explosions. We find that despite significant variability within each suite, trends distinguishing the explosions are apparent in their ${}^{56}\mathrm{Ni}$ yields and the kinetic properties of the ejecta. We compare our results with other recent work that studies explosions from these hybrid progenitors.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2020

US East Coast synthetic aperture radar wind atlas for offshore wind energy

We present the first synthetic aperture radar (SAR) offshore wind atlas of the US East Coast from Georgia to the Canadian border. Images from RADARSAT-1, Envisat, and Sentinel-1A/B are processed to wind maps using the geophysical model function (GMF) CMOD5.N. Extensive comparisons with 6008 collocated buoy observations of the wind speed reveal that biases of the individual systems range from -0.8 to 0.6 m s -1 . Unbiased wind retrievals are crucial for producing an accurate wind atlas, and intercalibration of the SAR observations is therefore applied. Wind retrievals from the intercalibrated SAR observations show biases in the range of to -0.2 to 0.0 m s -1 , while at the same time improving the root-mean-squared error from 1.67 to 1.46 m s -1 . The intercalibrated SAR observations are, for the first time, aggregated to create a wind atlas at the height 10 m a.s.l. (above sea level). The SAR wind atlas is used as a reference to study wind resources derived from the Wind Integration National Dataset Toolkit (WTK), which is based on 7 years of modelling output from the Weather Research and Forecasting (WRF) model. Comparisons focus on the spatial variation in wind resources and show that model outputs lead to lower coastal wind speed gradients than those derived from SAR. Areas designated for offshore wind development by the Bureau of Ocean Energy Management are investigated in more detail; the wind resources in terms of the mean wind speed show spatial variations within each designated area between 0.3 and 0.5 m s -1 for SAR and less than 0.2m s -1 for the WTK. Our findings indicate that wind speed gradients and variations might be underestimated in mesoscale model outputs along the US East Coast.

17 WIND ENERGY↗
DOE OSTI2023

UAS remote sensing (3DR SOLO platform): multispectral reflectance and normalized difference vegetation index, Seward Peninsula, Alaska, 2022

Airborne remote sensing data collected using a Parrot Sequoia+ multispectral sensor installed on a 3DR SOLO unoccupied aerial system (UAS) – operated by the Terrestrial Ecosystem Science & Technology group https://www.bnl.gov/envsci/testgroup/ at Brookhaven National Laboratory. This package includes data from 19 flights flown over the NGEE-Arctic, Kougarok Mile Marker (MM) 80, Kougarok Fire Complex (KFC) and Teller MM 27 sites in July 2022. Derived image products include point cloud, ortho-mosaiced multispectral image, a digital surface model (DSM) using the structure from motion (SfM) technique, and a normalized difference vegetation index (NDVI) map. Unprocessed and processed data products are included in this package (processing levels 0-2). Data and metadata are provided as text (*.txt, *.json, *hdr,), tabular (*.dat, *.csv), point cloud (*.laz), Cloud Optimized GeoTIFF (COG, *.tif), and image (*.jpg, *.tif, *png) formats.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 OSTI2023

UAS remote sensing (3DR SOLO platform): multispectral reflectance, canopy height model, normalized difference vegetation index, Seward Peninsula, Alaska, 2021

Airborne remote sensing data collected using a Parrot Sequoia+ multispectral sensor installed on a 3DR SOLO unoccupied aerial system (UAS) - operated by the Terrestrial Ecosystem Science Technology group at Brookhaven National Laboratory. This package includes data from 10 flights flown over the NGEE-Arctic Council Mile Marker (MM) 71, Kougarok MM64, and Teller MM27 sites on the Seward Peninsula, Alaska, in August 2021. Derived image products include point cloud, ortho-mosaiced multispectral image, ortho-mosaiced RGB image, a digital surface model (DSM) using the structure from motion (SfM) technique, a canopy height model (CHM), and a normalized difference vegetation index (NDVI) map. Unprocessed and processed data products are included in this package (processing levels 0-2). Data and metadata are provided as text (*.txt, *.json, *hdr,), tabular (*.dat, *.csv), point cloud (*.laz), Cloud Optimized GeoTIFF (COG, *.tif), and image (*.jpg, *.tif, *png) formats. 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 OSTI2026

EAGLE-I Power Outage Data 2025

The provided EAGLE-I historic dataset includes power outage information at the county level for 2025 at 15-minute intervals collected by the EAGLE-I program at ORNL. The data has been collected from utility's public outage maps using an ETL process. The dataset details FIPS code, county name, state name, total number of customers without power, and a date/timestamp. For detailed metadata, refer to the linked metadata DOI.

EAGLE-I↗
DOE OSTI2021

Programs and Code for Geothermal Exploration Artificial Intelligence

The scripts below are used to run the Geothermal Exploration Artificial Intelligence developed within the "Detection of Potential Geothermal Exploration Sites from Hyperspectral Images via Deep Learning" project. It includes all scripts for pre-processing and processing, including: - Land Surface Temperature K-Means classifier - Labeling AI using Self Organizing Maps (SOM) - Post-processing for Permanent Scatterer InSAR (PSInSAR) analysis with SOM - Mineral marker summarizing - Artificial Intelligence (AI) Data splitting: creates data set from a single raster file - Artificial Intelligence Model: creates AI from a single data set, after splitting in Train, Validation and Test subsets - AI Mapper: creates a classification map based on a raster file

15 GEOTHERMAL ENERGY↗
DOE OSTI2018

Initial Reduction of the PdO(101) Surface: Role of Oxygen Vacancy Formation Kinetics

Here, we investigated the initial thermal reduction of the PdO(101) surface using density functional theory (DFT) calculations. The defect-free PdO(101) surface consists of parallel rows of undercoordinated Pd and O atoms (Pd cus and O cus , respectively). DFT was used to map out the elementary processes of O cus vacancy formation, oxygen surface atom diffusion along the Pd cus rows, and various O 2 formation pathways. Because oxygen vacancies form during the reduction of the surface, the elementary processes were examined with and without the presence of adjacent O cus vacancies. DFT calculations show that the presence of oxygen vacancies strongly affects the barriers of adjacent surface processes. Barriers for O vacancy formation are reduced by nearly 50% with an adjacent O vacancy. The barrier for O 2 formation along the Pd cus row drops from 1.54 eV on the defect-free PdO(101) surface to 0.81 eV in the presence of an O cus vacancy dimer. Yet, the presence of O cus vacancies also leads to more strongly bound O 2 on the Pd cus row. The strong neighbor effect of O vacancies on the PdO(101) surface will favor the growth of O vacancy chains and increase the rate of thermal reduction of the surface, both features that have been observed in recent ultrahigh vacuum isothermal reduction experiments of the PdO(101) surface.

Defects in solids↗
DOE OSTI2021

Common risk segment mapping: Streamlining exploration for carbon storage sites, with application to coastal Texas and Louisiana

Large-scale deployment of Carbon Capture and Storage (CCS) will require a commensurately large number of sites. Efficient screening methods are needed to create investment assurance and focus efforts on the most promising sites. The problem is similar to petroleum exploration, for which there are well-developed (though seldom published) workflows, including Common Risk Segment (CRS) mapping. In brief, the process requires 1) defining the key play elements; 2) identifying candidate geologic intervals for each; 3) creating fact-based maps for those intervals; 4) determining minimum criteria for the success of each element; 5) reinterpreting the fact-based maps in terms of chance of success; and 6) combining the individual maps to form a composite, basin-scale view of prospectivity. We adapt the CRS process to screening for CO 2 storage sites. Critically, we redefine the process in terms of cost of characterization and development, rather than chance of success. For illustration, we apply the process to the example of the Lower Miocene on the Texas and Louisiana Gulf Coast. We show that the predictions are consistent with historic hydrocarbon production volumes and rates. The power of the CRS method is that it creates a systematic approach to geologic evaluation and translates complex, multidimensional analysis into clear, graphical and easily comprehended business inputs. The results highlight sweet spots and identifies critical risks, suggesting a focus for further data collection and analysis. Furthermore, the method developed here can be applied to both surface and subsurface factors anywhere that there is interest in geologic storage of CO 2 .

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2020

A Data Processing Workflow for Fixed-wing Drone Based Radiation Mapping in the Chornobyl Exclusion Zone (CEZ) - 20119

April 2020 marks the 34. anniversary of the high-profile radiological release from the Chornobyl Nuclear Power Plant (ChNPP). The release of radioactive material from reactor number four began on the 26 April 1986 and continued over a period of about 10 days, releasing approximately 1700 PBq of radioactive material (including 85 PBq of 137-Cs) into the environment. To this day, the accident remains the most significant release of radioactive material since civil nuclear power generation began. In the years since the accident, automated and remote radiation monitoring technologies have advanced significantly in their capabilities. One such example of this is the use of unmanned aerial vehicles (UAVs) in radiation mapping investigations. In April 2019, a team of scientists from the University of Bristol showcased a novel radiation mapping system within the CEZ, specifically aiming to map radiation over a large portion of the area immediately surrounding the ChNPP. Over six days of data collection, the system flew a total distance of 583.8 km, covering an area of 14.6 sq.km with an exceptional spatial resolution (sub 20 m/pixel). The work presented herein outlines and explains the data processing procedure to convert the raw data into 137-Cs activity (kBq/sq.m) and cesium-equivalent dose-rate (CED) at 1 m above ground level (μSv/hr). A demonstration of the validity of the method is demonstrated through the successful reduction of the raw data into a single linear relationship between the measured {sup 137}Cs net peak intensity and the {sup 137}Cs activity. (authors)

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗
DOE OSTI2017

Electromagnetic compatibility qualification of power electronics for I and C power applications - 152

Electromagnetic Compatibility (EMC) is a growing field in nuclear equipment qualification. Previously confined to I and C equipment residing in control and cable spreading rooms, EMC qualification has expanded to include the inverters and battery chargers which often power safety-related I and C equipment, as well as adjustable speed drives and material handling equipment which could potentially affect sensitive safety-related I and C systems. Because much of the data collected to form the current EMC limits and guidance was collected from low-power equipment in relatively low EMI environments, the same guidance, applied to power electronic equipment, produces overly conservative estimations of the performance needed for EMC. Excessive modification in an attempt to bring the equipment into compliance with EMC limits may not be necessary. This paper provides a brief summary of current applicable EMC guidance and demonstrates a road map for the qualification of larger, more powerful devices which takes into account the entire EMC process, including design, testing, mapping of the installed location, and justification of EMC failures with the end goal being successful, timely, and cost-effective implementation of upgrades and compatibility with existing plant infrastructure (in the intended installation environment), even if equipment exceeds traditional operating envelopes. (authors)

42 ENGINEERING↗
DOE OSTI2020

RIFTA: A Robust Iterative Fourier Transform-based dwell time Algorithm for ultra-precision ion beam figuring of synchrotron mirrors

With the rapid evolution of synchrotron X-ray sources, the demand for high-precision X-ray mirrors has greatly increased. Single nanometer profile error is required to keep imaging capability at the diffraction limit. Ion Beam Figuring (IBF), as a highly deterministic surfacing technique, has been used for ultra-precision finishing of mirrors. One crucial step that guides the IBF process is dwell time calculation. A valid dwell time solution should be non-negative and duplicate the shape of the desired removal map. Another important aspect is to minimize the total dwell time. In this study, we propose a Robust Iterative Fourier Transform-based dwell time Algorithm (RIFTA) that automatically fulfills these requirements. First, the thresholded inverse filtering in Fourier transform-based deconvolution is stabilized and automated by optimizing the threshold value using the Nelder-Mead simplex algorithm. Second, a novel two-level iterative scheme is proposed to guarantee the minimized total dwell time with its non-negativity at each dwell point. Third, a bicubic resampling is employed to flexibly adapt the calculated dwell time map to any IBF process intervals. The performance of RIFTA is first studied with simulation, followed by a comparison with the other state-of-the-art dwell time algorithms. We then demonstrate with an experiment that, using the dwell time calculated by the RIFTA, the total dwell time is shortened by a factor of two and the RMS in a 5 × 50 mm clear aperture was reduced from 3.4 nm to 1.1 nm after one IBF run, which proves the effectiveness and the efficiency of the proposed algorithm.

42 ENGINEERING↗
DOE OSTI2024

Navigating high-dimensional process-structure–property relations in nanocrystalline Pt-Au alloys with machine learning

For decades, materials scientists have relied on the process-structure–property paradigm to guide investigations into material behaviors. Traditional studies often examine a limited number of process-structure–property variables, striving to elucidate mechanisms governing material response. However, this approach is time consuming and can limit exploration, as well as the discovery of process-structure–property relations in novel materials. In this paper, we combined combinatorial sputter deposition and multi-modal high-throughput materials characterization with feedforward neural networks to establish high-dimensional process-structure–property relations in Pt-Au alloys, yielding nanocrystalline alloys with high hardness and low resistivity relevant to electrical contact switch applications. We mapped three indicators of process conditions (composition and two atomic deposition characteristics) onto four indicators of material structure (X-ray diffraction, film thickness, density, and surface roughness) and two indicators of material properties (hardness and resistivity), resulting in 784 unique combinations evaluated over a 13-dimensional space. The neural networks predicted Pt-Au alloys with 18–24 at.% Au, when deposited at specific conditions, to have a nanoindentation hardness up to 7.2 GPa. This high hardness value, comparable to some steels, represents a 3-fold improvement in hardness over “hard gold”, a commonly used electrical contact alloy, while maintaining requisite electrical conductivity. The neural network models provide an avenue to identify expected process windows capable of maximizing material performance.

Electrical contact materials↗
DOE OSTI2022

Sequence ID Map (SeqIDMap) v1.0

This is a web service that allows users to request an identifier for a sequence in a specific database, given another identifier for the same sequence with respect to another given database. This process is called ID mapping. It's a minimalist service (fast, no database server) that will be significantly easier to use in a container environment.

Johnson, Jeffrey↗