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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 127 records · Page 7
All sourcesNASA NTRSDOE OSTI
NASA NTRS1990

Theoretical studies of important processes in planetary and comet atmospheres

Dissociative recombination (DR) reactions in planetary and comet atmospheres are discussed. A computer program was developed which determines DR cross sections and rates using potential curves and electronic capture widths. It uses Multi-Channel Quantum Defect Theory (MQDT) to include excited Rydberg resonance levels in the DR cross section and rate calculations. Each vibrational level of a molecular ion is the limit for an infinite series of Rydberg states. Above each ion vibrational level are Rydberg vibrational levels having higher ion levels as their series limit. These Rydberg vibrational levels are resonances, i.e., neutral states which are imbedded in the electron-molecular ion continuum. The process in which the Rydberg level causes an abrupt perturbation in the cross section for DR (because of interference between capture into the Rydberg level and capture into the repulsive dissociative state) is referred to as indirect recombination. The process in which the Rydberg levels are excluded and recombination goes from the entrance channel to the repulsive state is called direct recombination. The full DR process, i.e., both direct and indirect recombination, is the process of importance for planetary atmospheres. These ideas are illustrated with the new results for DR from excited ion vibrational levels of O2(+) into the dissociative state which leads to O(1S) + O(1D).

Guberman, Steven L.↗
DOE OSTI2025

Reference Fuel Development for Non-Aluminum Spent Nuclear Fuel Management

The Savannah River Site (SRS) L Area Facility provides for the safe receipt, storage, handling, and shipping of spent nuclear fuel (SNF) and has received more than 47,000 SNF assemblies since 1964. In order to consolidate receipt and storage analysis, L Area criticality safety has historically used several aluminum-clad “reference fuels” to establish bounding storage, handling, and cask loading limits and then applied a reactivity comparison approach to demonstrate that candidate fuels may be processed under the reference fuel limits. Currently, only aluminum-clad SNF from off-site research reactors are transferred on-site. The Accelerated Basin De-Inventory (ABD) program will begin the removal of bundled Non-Aluminum Spent Nuclear Fuel (NASNF) from the L Area disassembly basin for dissolution and disposition, which has driven the need for a non-aluminum reference fuel. This paper discusses the process and results of creating a new fictional homogenous NASNF highly enriched uranium reference fuel, “MITZ,” to be used in nuclear criticality safety evaluations for upcoming SNF disposition operations. Data demonstrating the relationship between neutron multiplication behavior and fuel spacing is generated for the new reference fuel MITZ as well as existing reference fuels representing several types of SNF assemblies.

Reference Fuel↗
DOE OSTI2025

Reference Fuel Development for Non-Aluminum Spent Nuclear Fuel Management

The Savannah River Site (SRS) L Area Facility provides for the safe receipt, storage, handling, and shipping of spent nuclear fuel (SNF) and has received more than 47,000 SNF assemblies since 1964. In order to consolidate receipt and storage analysis, L Area criticality safety has historically used several aluminum-clad “reference fuels” to establish bounding storage, handling, and cask loading limits and then applied a reactivity comparison approach to demonstrate that candidate fuels may be processed under the reference fuel limits. Currently, only aluminum-clad SNF from off-site research reactors are transferred on-site. The Accelerated Basin De-Inventory (ABD) program will begin the removal of bundled Non-Aluminum Spent Nuclear Fuel (NASNF) from the L Area disassembly basin for dissolution and disposition, which has driven the need for a non-aluminum reference fuel. This paper discusses the process and results of creating a new fictional homogenous NASNF highly enriched uranium reference fuel, “MITZ,” to be used in nuclear criticality safety evaluations for upcoming SNF disposition operations. Data demonstrating the relationship between neutron multiplication behavior and fuel spacing is generated for the new reference fuel MITZ as well as existing reference fuels representing several types of SNF assemblies.

Reference Fuel↗
DOE OSTI2021

Nonadiabatic couplings from a variational excited state method based on constrained DFT

Excited Costrained Density Functional Theory (XCDFT) is a variational excited state method that extends ground state DFT to the computation of low-lying excited states. It borrows much of the machinery of Constrained DFT (CDFT) with a crucial difference: the constraint imposes a population of one electron in the Hilbert space spanned by the virtuals of a reference ground state. Here, we present theory and implementation for evaluating nonadiabatic coupling vectors (NACVs) between the first excited state computed with XCDFT and the ground state. Our NACVs are computed analytically using density functional perturbation theory with a formalism that is general enough that could be applied to CDFT diabatic states. We showcase the new method with pilot NACV calculations for the conical intersection in H 3 , the avoided crossing in selenoacrolein, and the NACV magnitudes in azobenzene. Despite complications from the nonorthogonality of the wavefunctions, XCDFT’s energy surfaces and NACVs reproduce benchmark values and respect known sum rules within a reasonable degree. This shows that XCDFT is a viable method for nonadiabatic dynamics simulations.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
NASA NTRS1999

Measuring Greenland Ice Mass Variation With Gravity Recovery and the Climate Experiment Gravity and GPS

The response of the Greenland ice sheet to climate change could significantly alter sea level. The ice sheet was much thicker at the last glacial maximum. To gain insight into the global change process and the future trend, it is important to evaluate the ice mass variation as a function of time and space. The Gravity Recovery and Climate Experiment (GRACE) mission to fly in 2001 for 5 years will measure gravity changes associated with the current ice variation and the solid earth's response to past variations. Our objective is to assess the separability of different change sources, accuracy and resolution in the mass variation determination by the new gravity data and possible Global Positioning System (GPS) bedrock uplift measurements. We use a reference parameter state that follows a dynamic ice model for current mass variation and a variant of the Tushingham and Peltier ICE-3G deglaciation model for historical deglaciation. The current linear trend is also assumed to have started 5 kyr ago. The Earth model is fixed as preliminary reference Earth model (PREM) with four viscoelastic layers. A discrete Bayesian inverse algorithm is developed employing an isotropic Gaussian a priori covariance function over the ice sheet and time. We use data noise predicted by the University of Texas and JPL for major GRACE error sources. A 2 mm/yr uplift uncertainty is assumed for GPS occupation time of 5 years. We then carry out covariance analysis and inverse simulation using GRACE geoid coefficients up to degree 180 in conjunction with a number of GPS uplift rates. Present-day ice mass variation and historical deglaciation are solved simultaneously over 146 grids of roughly 110 km x 110 km and with 6 time increments of 3 kyr each, along with a common starting epoch of the current trend. For present-day ice thickness change, the covariance analysis using GRACE geoid data alone results in a root mean square (RMS) posterior root variance of 2.6 cm/yr, with fairly large a priori uncertainties in the parameters and a Gaussian correlation length of 350 km. Simulated inverse can successfully recover most features in the reference present-day change. The RMS difference between them over the grids is 2.8 cm/yr. The RMS difference becomes 1.1 cm/yr when both are averaged with a half Gaussian wavelength of 150 km. With a fixed Earth model, GRACE alone can separate the geoid signals due to past and current load fairly well. Shown are the reference geoid signatures of direct and elastic effects of the current trend, the viscoelastic effect of the same trend starting from 5 kyr ago, the Post Glacial Rebound (PGR), and the predicted GRACE geoid error. The difference between the reference and inverse modeled total viscoelastic signatures is also shown. Although past and current ice mass variations are allowed the same spatial scale, their geoid signals have different spatial patterns. GPS data can contribute to the ice mass determination as well. Additional information is contained in the original.

Wu, Xiao-Ping↗
DOE OSTI2023

Multi-Unit Dwelling Plug-in EV Charging Innovation Pilots (Final Report)

Nearly one-third of residences in the U.S. are multi-unit dwellings (MUDs), e.g., apartments and condominiums, and MUDs with five or more units account for approximately 45% of rental households. While 80% of EV charging takes place at home, less than 5% of home charging takes place at MUDs. With public electric vehicle (EV) charging still underdeveloped, lack of access to reliable home charging is a major barrier to EV adoption for MUD residents. Challenges to siting electric vehicle supply equipment (EVSE) at MUDs include the high upfront cost of EVSE installation, physical and/or electrical infrastructure constraints, a lack of clear incentives for property managers to invest in installing EV charging for tenants, and a limited number of EV charging service providers that offer solutions adapted to the unique needs of MUDs. Through award DE-EE0008473 from the U.S. Department of Energy’s Office of Energy Efficiency and Renewable Energy (EERE), Center for Sustainable Energy (CSE), Energetics, and Forth, along with a diverse team of partners, led a three-year project to address barriers to EV charging at MUDs by developing an online toolkit geared toward residents, homeowner associations (HOAs), and property managers. The project, referred to as Vehicle Charging Innovations – Multi-Unit Dwellings (VCI-MUD project), engaged stakeholders across the country to identify real and perceived barriers to EV charging at MUDs and explored innovative technologies that attempt to alleviate the identified barriers. Over the course of three and a half years, the project conducted 60 interviews with industry stakeholders, compiled findings in an easy-to-use toolkit, and disseminated the toolkit across national, regional, state, and local channels. Key findings and outcomes of the VCI-MUD project include: Identifying six primary barriers to the installation of EV charging at MUDs; Developing five fact sheets and eight case studies highlighting innovative charging solutions to address barriers, including real-world operational and financial data; Developing a user-friendly, online empowerment toolkit with five important points for “making your pitch” to support EV charging to assist residents, property managers, building managers, and HOAs explore options for MUD charging. The VCI-MUD online toolkit was designed with replicability in mind. It includes general tools and guides to evaluate EV charging demand, gauge readiness for EV charging installation, and develop actionable plans. The fact sheets and case studies highlight the diversity of emerging MUD EV charging solutions, featuring different geographic and structural installation scenarios and providing interested parties with a menu of options, rather than prescribing a one-size-fits-all solution. The following resources are included in the toolkit to provide MUD stakeholders with all the information needed to navigate EV charging installation at their MUD location: Empowerment Toolkit – Easy-to-read FAQ overview, stakeholder roles and responsibilities, and additional resources for MUD EV charging installations; Charging Basics – Glossary of terms and descriptions of charging features, installation and operating expenses; EV Charging Survey Templates – Resident-to-Resident, Property Manager-to-Resident and HOA-to-Resident template letters with pre-populated template questions; Technology Selection Tool – Charging barrier fact sheets and case study examples; Installation Checklist – Submittal document requirements for EVSE installations; MUD Building Self-Evaluation Survey – Self-guided evaluation of potential barriers to EV charging installation at MUD locations; Curbside Resources – Case studies and fact sheets for curbside charging options; Find a Certified Electrician – Approved list of certified EV charging installers; “Right-to-Charge” State Legal References – Legal requirements for charging equipment at MUD locations. The online toolkit was promoted extensively in the final six months of the project and will continue to be disseminated by the Clean Cities Coalitions and other partners after the end of the VCI-MUD project to encourage, support, and demonstrate viable solutions for vehicle charging infrastructure in MUDs.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2024

County Level Annual Population Projections for SSP3 and SSP5

This dataset consist of annual (2020-2100) county-level population projections for the United States (U.S.) for Shared Socioeconomic Pathways (SSPs) 3 and 5. The original decadal state-level data is used as an input to the gridded population data model to downscale the state-level projections for each SSP to a 1 km grid. The 1 km data is then aggregated to the county-level using the 2020 TIGER/Line county shapefiles from the U.S. Census Bureau. The two data files are shared as .csv files with the following structure: Rows = Data for individual counties which are identified using their Federal Information Processing Standard (FIPS) code. The FIPS code is stored in the first column. Columns = Each year from 2020-2100 is an individual column. For easier reference, the state name associated with each row is stored in the last column. Values in each cell are the downscaled estimated population for that county-year combination. Values are fractional due to the weighting scheme used in the downscaling. The paper and model source code cited in the "Related Works" section describes the initial source of the population projections.

FIPS↗
DOE OSTI2020

Complete collision data set for electrons scattering on molecular hydrogen and its isotopologues: I. Fully vibrationally-resolved electronic excitation of H 2 $X^1Σ^+_g)$

Here, we present a comprehensive set of vibrationally-resolved cross sections for electron-impact electronic excitation of molecular hydrogen suitable for implementation in collisional-radiative models. The adiabatic-nuclei molecular convergent close-coupling method is used to calculate cross sections for excitation of all bound vibrational levels and dissociative excitation of the B 1 Σ u + , C 1 Π u , E F 1 Σ g + , B ′ 1 Σ u + , G K 1 Σ g + , I 1 Π g , J 1 Δ g , D 1 Π u , H 1 Σ g + , b 3 Σ u + , c 3 Π u , a 3 Σ g + , e 3 Σ u + , d 3 Π u , h 3 Σ g + , g 3 Σ g + , i 3 Π g , and j 3 Δ g electronic states from all –14 bound vibrational levels of the ground electronic ($\text{X}$ $^1&#x3A3^+_g$) state. The data set consists of cross sections from threshold to 500 eV for over 5000 transitions, representing all possible electronic and vibrational transitions between the state and the –3 singlet and triplet states (where refers to the united-atoms-limit principle quantum number). The cross sections are presented in graphical form and provided as both numerical values and analytic fit functions in supplementary data files.

74 ATOMIC AND MOLECULAR PHYSICS↗
DOE OSTI2021

Compilation and Evaluation of Isomeric Fission Yield Ratios

Fission yields are essential data for reactor physics, forensics, and astrophysics. In some cases, the fission yield of a fragment is divided between the ground state and a long-lived excited state, and the relative population of the two states is referred to as the isomeric ratio. In this work, we present a comprehensive compilation of experimental isomeric fission yield ratios for all target and projectile combinations. When possible, these data are combined to provide recommended isomeric fission yield ratios for low energy neutron-induced fission and spontaneous fission. The recommended ratios are compared to the traditional Madland-England model, which attempts to describe the isomeric ratios with a single parameter relating to the angular momentum of the fragment. It is found that the model does not reliably reproduce isomeric ratios outside the few nuclei it was fitted to, and its simplified treatment of the statistical process following population in fission results in average spin values, which are neither constant nor follow a recently observed saw-tooth pattern.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2020

Statistically Steady State Large-Eddy Simulations Forced by an Idealized GCM: 1. Forcing Framework and Simulation Characteristics

Using large-eddy simulations (LES) systematically has the potential to inform parameterizations of subgrid-scale (SGS) processes in general circulation models (GCMs), such as turbulence, convection, and clouds. Here we show how LES can be run to emulate grid columns of GCMs to generate a library of LES across a cross-section of dynamical regimes. The LES setup replicates the thermodynamic and water budgets in GCM grid columns. Resolved horizontal and vertical transports of heat and water and large-scale pressure gradients from the GCM are prescribed as forcing in the LES. The LES satisfies the same (slab-ocean) surface boundary conditions as the GCM, leaving the LES temperatures free to adjust. Radiative transfer is treated in a unied but highly idealized manner (a semi-gray atmosphere without cloud radiative effects) in both the GCM and LES. We show that the LES with these forcing and boundary conditions reaches statistically steady states without nudging to reference profiles. These steady states provide a training dataset for developing GCM parameterizations. The same LES setup also provides a good basis for studying the cloud response to global warming.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2021

Reply to: Insufficient evidence for ageing in protein dynamics

Reference 1 states that we claimed that internal motions in single protein molecules exhibit ageing over 13 decades of time. In contrast, our primary conclusion, as expressed in the title, was that over these timescales the dynamics of single protein molecules is non-equilibrium and self-similar. Notwithstanding, we demonstrate in this reply that protein dynamics does indeed exhibit ageing according to the criteria of ref. 1.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2020

The U.S. Nuclear Test History

This paper describes a desktop application designed to introduce users to unclassified information for the series of nuclear experiments conducted by the United States, colloquially referred to within the nuclear weapons design community as simply, the “Test History.” The application facilitates simple browsing (by name, by date, and MMDD date code), and more complex analyses based on user-defiend relational database queries.

99 GENERAL AND MISCELLANEOUS↗
DOE OSTI2021

Evaluating China's Road to Cyber Super Power

This report examines open source, non-classified qualitative analysis to evaluate China’s current cyber maturity. Evidence for this document draws on materials from academia, private cybersecurity companies, and national security research institutions. Private sector threat intelligence firms produce high quality analysis on Chinese APTs tactics, techniques, and procedures (TTPs), and investigation from companies such as FireEye illuminate China’s ability to wield cyber means for its security ends. None of the materials cited in this assessment originate from classified United States or foreign government sources. Any references to United States government sources are sourced entirely to unclassified information.

45 MILITARY TECHNOLOGY, WEAPONRY, AND NATIONAL DEF↗
DOE OSTI2023

Machine Learning Downscaling of SoilMERGE in the United States Southern Great Plains

SoilMERGE (SMERGE) is a root-zone soil moisture (RZSM) product that covers the entire continental United States and spans 1978 to 2019. Machine learning techniques, Random Forest (RF), eXtreme Gradient Boosting (XGBoost), and Gradient Boost (GBoost) downscaled SMERGE to spatial resolutions straddling the field scale domain (100 to 3000 m). Study area was northern Oklahoma and southern Kansas. The coarse resolution of SMERGE (0.125 degree) limits this product’s utility. To validate downscaled results in situ data from four sources were used that included: United States Department of Energy Atmospheric Radiation Measurement (ARM) observatory, United States Climate Reference Network (USCRN), Soil Climate Analysis Network (SCAN), and Soil moisture Sensing Controller and oPtimal Estimator (SoilSCAPE). In addition, RZSM retrievals from NASA’s Airborne Microwave Observatory of Subcanopy and Surface (AirMOSS) campaign provided a nearly spatially continuous comparison. Three periods were examined: era 1 (2016 to 2019), era 2 (2012 to 2015), and era 3 (2003 to 2007). During eras 1 and 2, RF outperformed XGBoost and GBoost, whereas during era 3 no model dominated. Performance was better during eras 1 and 2 as opposed to the pre-L band era 3. Improvements across all eras, regions, and models realized from downscaling included an increase in correlation from 0.03 to 0.42 and a decrease in ub RMSE from -0.0005 to -0.0118 m 3 /m 3 . This study demonstrates the feasibility of SMERGE downscaling opening the prospect for the development of a long-term RZSM dataset at a more desirable field-scale resolution with the potential to support diverse hydrometeorological and agricultural applications.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2022

Validation of wind resource and energy production simulations for small wind turbines in the United States

Abstract. Due to financial and temporal limitations, the small wind community relies upon simplified wind speed models and energy production simulation tools to assess site suitability and produce energy generation expectations. While efficient and user-friendly, these models and tools are subject to errors that have been insufficiently quantified at small wind turbine heights. This study leverages observations from meteorological towers and sodars across the United States to validate wind speed estimates from the Wind Integration National Dataset (WIND) Toolkit, the European Centre for Medium-Range Weather Forecasts (ECMWF) Reanalysis v5 (ERA5), and the Modern-Era Retrospective Analysis for Research and Applications, version 2 (MERRA-2), revealing average biases within ±0.5 m s−1 at small wind hub heights. Observations from small wind turbines across the United States provide references for validating energy production estimates from the System Advisor Model (SAM), Wind Report, MyWindTurbine.com, and Global Wind Atlas 3 (GWA3), which are seen to overestimate actual annual capacity factors by 2.5, 4.2, 11.5, and 7.3 percentage points, respectively. In addition to quantifying the error metrics, this paper identifies sources of model and tool discrepancies, noting that interannual fluctuation in the wind resource, wind speed class, and loss assumptions produces more variability in estimates than different horizontal and vertical interpolation techniques. The results of this study provide small wind installers and owners with information about these challenges to consider when making performance estimates and thus possible adjustments accordingly. Looking to the future, recognizing these error metrics and sources of discrepancies provides model and tool researchers and developers with opportunities for product improvement that could positively impact small wind customer confidence and the ability to finance small wind projects.

17 WIND ENERGY↗
DOE OSTI2026

Xanthos-Lake Dataset

The Xanthos-Lake v1.0 dataset provides the input data, trained machine-learning models, and simulation outputs needed to characterize lake water balance, snow and ice conditions, and mixing-layer temperature within the Xanthos global hydrological modeling framework. The dataset supports lake representation across a wide range of lake sizes and hydroclimatic conditions by combining xLSIM, a basin-specific machine-learning emulator of lake snow, ice, ice-cover fraction, and mixing-layer temperature, with the Xanthos-Lake water-balance model. The archive contains NetCDF datasets used to train and evaluate xLSIM, trained model weights, processed meteorological and lake-property inputs, and basin- and lake-category-specific simulation outputs. These materials are organized into four primary data groups, described below. Snowice_model_inputs: Contains the NetCDF input data used to train xLSIM. The xLSIM machine-learning framework uses three lake-based datasets. The meteorological forcing dataset provides monthly relative humidity, specific humidity, surface wind speed, maximum and minimum air temperature, downward longwave and shortwave radiation, snowfall, surface air pressure, and total precipitation. Lake surface area is included as an additional static predictor. The target-state dataset provides lake ice thickness, snow depth, snow cover, and lake mixing-layer temperature, while a companion lake-surface dataset provides the lake ice-cover fraction. Before training, ice thickness and snow depth are converted from meters to centimeters, mixing-layer temperature is converted from kelvin to degrees Celsius and constrained to nonnegative values, and ice-cover fraction is converted from a fraction to a percentage. The predictor variables are normalized using statistics calculated across the selected lakes and time steps. Snowice_model_outputs: Contains the NetCDF outputs generated by xLSIM. For each basin, xLSIM produces a file containing observed and predicted lake-state variables for the training, validation, and testing periods. The modeled variables include lake ice thickness, snow depth, snow cover, mixing-layer temperature, and lake ice-cover fraction. For basins without a sufficiently persistent snow-and-ice signal, the emulator predicts only mixing-layer temperature. The outputs also include training and validation loss histories, the selected model configuration, identifiers of the lakes used in training, and SHAP-based feature-importance information at the global, lake, and seasonal-regime levels. The trained machine-learning model weights are provided separately within the dataset archive. Together, these files support model evaluation and subsequent coupling with the Xanthos-Lake water-balance framework. XanthosLAKES: Contains the NetCDF input data used by the Xanthos-Lake framework. Monthly meteorological inputs include relative and specific humidity, downward shortwave and longwave radiation, mean, maximum, and minimum air temperature, wind speed, precipitation, snowfall, and surface air pressure. Static lake-property datasets provide lake identifiers, geographic locations, surface area, volume, mean depth, elevation, drainage area, fetch, outlet-routing information, and associated Xanthos grid-cell attributes. Separate bathymetric datasets provide the coefficients of the area–depth and volume–depth relationships for each aggregated lake unit. GLEV-based records provide observed lake surface area and evaporation data used to initialize lake states, define reference conditions, and calibrate and evaluate the model. Xanthos-Lake Outputs: Contains the basin- and lake-category-specific NetCDF outputs generated by Xanthos-Lake. Monthly variables include lake surface area, storage volume, outlet discharge, evaporation rate, evaporation volume, lake–groundwater exchange, lake inflow, ice thickness, snow depth, snow-cover fraction, ice-cover fraction, and mixing-layer temperature. The files also contain lake-specific calibration and validation statistics, including normalized root-mean-square error, mean absolute error, Nash–Sutcliffe efficiency, Kling–Gupta efficiency, and percent bias. Stored calibrated and derived parameters include the weir discharge coefficient, fractional freeboard, groundwater exchange coefficient, reference water level, corresponding reference surface area and storage volume, weir-width adjustment factor, and the fraction of routed inflow entering the lake. Basin identifiers, lake category, simulation period, calibration and validation periods, and parameter-schema information are retained as NetCDF metadata.

Abeshu, Guta [Pacific Northwest National Laborator↗