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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 235 records · Page 13
All sourcesNASA NTRSDOE OSTI
DOE OSTI2021

How different power plant types contribute to electric grid reliability, resilience, and vulnerability: a comparative analytical framework

Abstract This work explores the dependability tradeoffs provided by the most common types of central power plants in the United States. Historically, the electricity sector has lacked consensus on how reliability , resilience , and vulnerability differ and how those metrics change depending on the power plant fleet composition. We propose distinct definitions for these metrics and an analytical framework to evaluate power plant fleet dependability. Using data analysis and literature review, we identify fifteen dependability attributes across which we rank eleven power plant types relative to natural gas combined-cycle (NGCC) plants. We use NGCC as the benchmark because it is common to many locations and is of relatively recent vintage. The framework shows that each power plant type has unique dependability benefits and drawbacks. We provide examples of how researchers may use the framework to evaluate grid dependability qualitatively under different scenarios. We find that assuming all attributes that contribute to grid dependability are equally important and additive, electric grid dependability is best supported when power plant fleets include a mixture of power generation technologies. Then, we discuss scenario characteristics that could alter the prioritization and relationships of attributes. We also find that if current capacity installation trends continue to favor low- and zero-carbon power plants, US power grids may benefit from increased resilience and reduced vulnerability at the cost of decreased reliability. We conclude by recommending methods for adapting the framework and quantifying relationships between attributes in individual scenarios.

Ramirez-Meyers, K. (ORCID:0000000291216952)↗
DOE OSTI2022

Searching for axionlike time-dependent cosmic birefringence with data from SPT-3G

Ultralight axionlike particles (ALPs) are compelling dark matter candidates because of their potential to resolve small-scale discrepancies between Λ CDM predictions and cosmological observations. Axion-photon coupling induces a polarization rotation in linearly polarized photons traveling through an ALP field; thus, as the local ALP dark matter field oscillates in time, distant static polarized sources will appear to oscillate with a frequency proportional to the ALP mass. We use observations of the cosmic microwave background from SPT-3G, the current receiver on the South Pole Telescope, to set upper limits on the value of the axion-photon coupling constant g φ γ over the approximate mass range 10 - 22 – 10 - 19 eV , corresponding to oscillation periods from 12 hours to 100 days. For periods between 1 and 100 days ( 4.7 × 10 - 22 eV ≤ m φ ≤ 4.7 × 10 - 20 eV ), where the limit is approximately constant, we set a median 95% C.L. upper limit on the amplitude of on-sky polarization rotation of 0.071 deg. Assuming that dark matter comprises a single ALP species with a local dark matter density of 0.3 GeV / cm 3 , this corresponds to g φ γ < 1.18 × 10 - 12 GeV - 1 × ( m φ 1.0 × 10 - 21 eV ) . These new limits represent an improvement over the previous strongest limits set using the same effect by a factor of ~ 3.8 .

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
NASA NTRS1993

Variable temperature pressure broadening of the 4(1,4)-3(2,1) transition of H2O by O2 and N2

The O2 and N2 pressure-broadening parameters of the 4(1,4)-3(2,1) rotational transition in the ground vibrational state of H2O have been measured in the temperature range between 100 and 520 K. Above 250 K the measurements were made in an equilibrium cell. Below 250 K a cell, which uses collisional cooling to circumvent the temperature limits imposed by the vapor pressure of the sample gas, was used. The data were fitted to an exponential temperature-dependence for data above 150 K with resultant n values of 0.81(3) for O2 and 0.70(3) for N2, where the entries in parentheses represent the error in the last significant figure of the parameter. Below 150 K the measured pressure-broadening parameters are smaller than those calculated using these values of n.

Goyette, Thomas M.↗
NASA NTRS1998

Inversion of Crater Morphometric Data to Gain Insight on the Cratering Process

In recent years, morphometric data for Venus and several outer planet satellites have been collected, so we now have observational data of complex Craters formed in a large range of target properties. We present general inversion techniques that can utilize the morphometric data to quantitatively test various models of complex crater formation. The morphometric data we use in this paper are depth of a complex crater, the diameter at which the depth-diameter ratio changes, and onset diameters for central peaks, terraces, and peak rings. We tested the roles of impactor velocities and hydrostatic pressure vs. crustal strength, and we tested the specific models of acoustic fluidization (Melosh, 1982) and nonproportional growth (Schultz, 1988). Neither the acoustic fluidization model nor the nonproportional growth in their published formulations are able to successfully reproduce the data. No dependence on impactor velocity is evident from our inversions. Most of the morphometric data is consistent with a linear dependence on the ratio of crustal strength to hydrostatic pressure on a planet, or the factor c/pg.

Herrick, Robert R.↗
DOE OSTI2022

Data from: "Warming and the dependence of limber pine (Pinus flexilis) establishment on summer soil moisture within and above its current elevation range"

This data package contains data that were used for analysis in “Warming and the dependence of limber pine (Pinus flexilis) establishment on summer soil moisture within and above its current elevation range”, by Moyes et al. 2013. All data collection and field research were completed on Niwot Ridge, Colorado, USA.This data package contains nine comma-separated-values (.csv) files, one text (.txt) file, and two zipped seedling folders that were used for leaf area analysis. One zipped folder contains 468 .jpg photographs of seedlings, and the second contains 468 corresponding Image J-processed .jpg images that include silhouette leaf area values. .csv and .txt files can be opened using any compatible simple text-editor software such as TextEdit (Mac) and Notepad (Windows); .csv’s can also be opened using R and Microsoft Excel. Image files can be opened using Preview (Mac) and Photos (Windows). In addition, there are a total of 31 Microsoft Excel files: three .xlsx files, and 28 raw Li-Cor output .xls files. This data user’s guide is available in .pdf format, and can be opened using Adobe Acrobat Reader, or any other compatible file viewing software. Geospatial data showing field site locations are also included in the archive for use and reference. There are two geospatial formats in this archive: ESRI shapefiles (.shp) and keyhole markup-language (.kml) files. Both file types contain bounding box information, with the former being polygons, and the latter containing corner coordinates for each site. ESRI shapefiles can be opened using any geospatial software compatible with the file type (such as ESRI’s ArcGIS suite and QGIS), and .kml files are compatible with Google Earth and Google Maps.--------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------Continued changes in climate are projected to alter the geographic distributions of plant species, in part by affecting where individuals can establish from seed. We tested the hypothesis that warming promotes uphill redistribution of subalpine tree populations by reducing cold limitation at high elevation and enhancing drought stress at low elevation. We seeded limber pine (Pinus flexilis) into plots with combinations of infrared heating and water addition treatments, at sites positioned in lower subalpine forest, the treeline ecotone, and alpine tundra. In 2010, first-year seedlings were assessed for physiological performance and survival over the snow-free growing season. Seedlings emerged in midsummer, about 5–8 weeks after snowmelt. Low temperature was not observed to limit seedling photosynthesis or respiration between emergence and October, and thus experimental warming did not appear to reduce cold limitation at high elevation. Instead, gas exchange and water potential from all sites indicated a prevailing effect of summer moisture stress on photosynthesis and carbon balance. Infrared heaters raised soil growing degree days (base 5 °C, p < 0.001) and August–September mean soil temperature (p < 0.001). Despite marked differences in vegetation cover and meteorological conditions across sites, volumetric soil moisture content (θ) at 5–10 cm below 0.16 and 0.08 m^3 m^(−3) consistently corresponded with moderate and severe indications of drought stress in midday stem water potential, stomatal conductance, photosynthesis, and respiration. Seedling survival was greater in watered plots than in heated plots (p = 0.01), and negatively related to soil growing degree days and duration of exposure to θ < 0.08 m^3 m^(−3) in a stepwise linear regression model (p < 0.0001). We concluded that seasonal moisture stress and high soil surface temperature imposed a strong limitation to limber pine seedling establishment across a broad elevation gradient, including at treeline, and that these limitations are likely to be enhanced by further climate warming.--------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------Maintenance log:Amended file name error in Data User's Guide May 19 2022

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2025

Data Readiness for AI: A 360-Degree Survey

Artificial Intelligence (AI) applications critically depend on data. Poor-quality data produces inaccurate and ineffective AI models that may lead to incorrect or unsafe use. Evaluation of data readiness is a crucial step in improving the quality and appropriateness of data usage for AI. R&D efforts have been spent on improving data quality. However, standardized metrics for evaluating data readiness for use in AI training are still evolving. In this study, we perform a comprehensive survey of metrics used to verify data readiness for AI training. This survey examines more than 140 papers published by ACM Digital Library, IEEE Xplore, journals such as Nature, Springer, and Science Direct, and online articles published by prominent AI experts. This survey aims to propose a taxonomy of data readiness for AI (DRAI) metrics for structured and unstructured datasets. We anticipate that this taxonomy will lead to new standards for DRAI metrics that would be used for enhancing the quality, accuracy, and fairness of AI training and inference.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2022

DRIPS: Dynamic Rebalancing of Pipelined Streaming Applications on CGRAs

Coarse-grained reconfigurable arrays (CGRAs) provide higher flexibility than application-specific integrated circuits (ASICs) and higher efficiency than fine-grained reconfigurable devices such as Field Programmable Gate Arrays (FPGAs). However, CGRAs are generally designed to support offloading of a single kernel. While their design, based on communicating functional units, appears to naturally suit data streaming applications composed of multiple cooperating kernels, current approaches only statically partition the resources across application kernels. However, emerging streaming applications at the edge (scientific instruments, sensor networks, network processing) perform much more than digital signal processing and often are data and input dependent. This leads to extremely variable kernel execution times, severely impacting the throughput of the entire pipeline if resources are only statically allocated. Therefore, in this paper, we propose DRIPS — a coarse-grained, dynamically, and partially reconfigurable array for data-dependent streaming applications. We present a unified compiler framework to facilitate the mapping of a given streaming application onto the DRIPS CGRA architecture. The experimental results show that DRIPS achieves an average throughput improvement of 1.46$\times$ across a set of representative applications over a statically partitioned solution. The additional area overhead to enable dynamic rebalancing consumes 16.34% of the entire area for a 5x5 CGRA prototype.

Tan, Cheng↗
NASA NTRS1978

OFT ascent/descent ancillary data requirements document

Requirements are presented for the ascent/descent (A/D) navigation and attitude-dependent ancillary data products to be generated for the space shuttle orbiter in support of orbital flight test requirements, MPAD guidance and navigation performance assessment, and the mission evaluation team. It was intended that this document serve as the sole requirements control instrument between MPB/MPAD and the A/D ancillary data users. The requirements are primarily functional in nature, but some detail level requirements are also included.

Bond, A. C., Jr.↗
NASA NTRS1980

Shuttle program: OFT ascent/descent ancillary data requirements document

Requirements are presented for the ascent/descent (A/D) navigation and attitude-dependent ancillary data products to be generated for the space shuttle orbiter in support of the orbital flight test (OFT) flight test requirements, MPAD guidance and navigation performance assessment, and the mission evaluation team. The A/D ancillary data support for OFT mission evaluation activities is confined to providing postflight position, velocity, attitude, and associated navigation and attitude derived parameters for the Orbiter over particular flight phases and time intervals.

Bond, A. C., Jr.↗
DOE OSTI2022

Excitation Intensity- and Size-Dependent Halide Photosegregation in CsPb(I 0.5 Br 0.5 ) 3 Perovskite Nanocrystals

Although broad consensus exists that photoirradiation of mixed-halide lead perovskites leads to anion segregation, no model today fully rationalizes all aspects of this near ubiquitous phenomenon. In this work, we quantitatively compare experimental, CsPb(I 0.5 Br 0.5 ) 3 nanocrystal (NC) terminal anion photosegregation stoichiometries and excitation intensity thresholds to a band gap-based, thermodynamic model of mixed-halide perovskite photosegregation. Mixed-halide NCs offer strict tests of theory given physical sizes, which dictate local photogenerated carrier densities. We observe that mixed-anion perovskite NCs exhibit significant robustness to photosegregation, with photosegregation propensity decreasing with decreasing NC size. Observed size- and excitation intensity-dependent photosegregation data agree with model predicted size- and excitation intensity-dependent terminal halide stoichiometries. Established correspondence between experiment and theory, in turn, suggests that mixed-halide perovskite photostabilities can be predicted a priori using local gradients of (empirical) Vegard’s law expressions of composition-dependent band gaps.

36 MATERIALS SCIENCE↗
NASA NTRS1995

Visualization Techniques in Space and Atmospheric Sciences

Unprecedented volumes of data will be generated by research programs that investigate the Earth as a system and the origin of the universe, which will in turn require analysis and interpretation that will lead to meaningful scientific insight. Providing a widely distributed research community with the ability to access, manipulate, analyze, and visualize these complex, multidimensional data sets depends on a wide range of computer science and technology topics. Data storage and compression, data base management, computational methods and algorithms, artificial intelligence, telecommunications, and high-resolution display are just a few of the topics addressed. A unifying theme throughout the papers with regards to advanced data handling and visualization is the need for interactivity, speed, user-friendliness, and extensibility.

Szuszczewicz, E. P.↗
NASA NTRS2003

Towards a distributed information architecture for avionics data

Avionics data at the National Aeronautics and Space Administration's (NASA) Jet Propulsion Laboratory (JPL consists of distributed, unmanaged, and heterogeneous information that is hard for flight system design engineers to find and use on new NASA/JPL missions. The development of a systematic approach for capturing, accessing and sharing avionics data critical to the support of NASA/JPL missions and projects is required. We propose a general information architecture for managing the existing distributed avionics data sources and a method for querying and retrieving avionics data using the Object Oriented Data Technology (OODT) framework. OODT uses XML messaging infrastructure that profiles data products and their locations using the ISO-11179 data model for describing data products. Queries against a common data dictionary (which implements the ISO model) are translated to domain dependent source data models, and distributed data products are returned asynchronously through the OODT middleware. Further work will include the ability to 'plug and play' new manufacturer data sources, which are distributed at avionics component manufacturer locations throughout the United States.

Information architecture↗
NASA NTRS1989

The dependence of the soft X ray spectral slope with radio property, luminosity, and redshift, for a large sample of AGN from the Einstein IPC data base

The dependence of the soft X-ray spectral slope on radio, optical and X-ray properties, and on redshift are reported for a large sample of Active Galactic Nuclei (AGN). The sample includes 317 optically and radio-selected AGN from a preliminary version of the Einstein Imaging Proportional Counter (IPC) quasar and AGN data base. The main results are: the difference in X-ray slope between radio-loud and radio-quiet AGN were confirmed for an independent and much larger sample of sources; a difference in X-ray slope between flat and steep radio spectrum AGN is observed only in high luminosity sub-sample; in flat radio spectrum AGNs there is an indication for a dependence of the X-ray spectral index on X-ray luminosity redshift and alpha sub 0x.

Brunner, H.↗
DOE OSTI2023

Measurements of dielectron production in Au + Au collisions at s N N = 27 , 39, and 62.4 GeV from the STAR experiment

We report systematic measurements of dielectron (e + e – ) invariant-mass M ee spectra at midrapidity in Au + Au collisions at s N N = 27 = 27, 39, and 62.4 GeV taken with the STAR detector at the Relativistic Heavy Ion Collider. For all energies studied, a significant excess yield of dielectrons is observed in the low-mass region ( 0.40 < M ee < 0.75 MeV / c 2 ) compared to hadronic cocktail simulations at freeze-out. Models that include an in-medium broadening of the ρ -meson spectral function consistently describe the observed excess. In addition, we report acceptance-corrected dielectron-excess spectra for Au + Au collisions at midrapidity ( |y ee | < 1) in the 0–80% centrality bin for each collision energy. The integrated excess yields for 0.4 < M ee < 0.75 GeV / c 2 , normalized by the charged particle multiplicity at midrapidity, are compared with previously published measurements for Au + Au at s N N = 27 = 19.6 and 200 GeV. Models that include an in-medium broadening of the ρ -meson spectral function consistently describe the observed excess. Furthermore, the normalized excess yields in the low-mass region show no significant collision energy dependence. The data, however, are consistent with model calculations that demonstrate a modest energy dependence.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2026

Atomistic Simulation of Glasses and Amorphous Materials: Challenges and Opportunities for the Next Decade

Atomistic simulations have become indispensable tools for understanding glass structure, dynamics, and properties, yet persistent challenges limit their predictive power. This perspective examines three interconnected issues, namely glass formation procedures, interatomic potential development, and machine learning applications, which emerged from the 5th International Workshop on Challenges of Atomistic Simulations of Glasses and Amorphous Materials. We identify convergent community priorities for (i) standardized validation protocols, (ii) curated benchmark datasets with complete metadata, and (iii) open repositories for glasses. A systematic was forward is provided by a hierarchical validation framework for assessing the structural fidelity, property prediction, and behavioral realism of simulation techniques. Looking ahead, transformative advances are promised by the fusion of classical techniques with machine learning based approaches, for instance, by integrating swap Monte Carlo with machine-learning (ML) potentials, leveraging foundation models through transfer learning, and finetuning ML potentials with experimental data. Progress depends on the community committing to validated models, reproducible protocols, and sustained data sharing.

Krishnan, N. M. Anoop↗
DOE OSTI2021

DEPRECATED AI-Batt-OS (Autonomous Identification of Battery Life Models - Open Source) [SWR 21-17]

DEPRECATED. This repository was archived by the owner on Jun 30, 2026. It is now read-only. Open source implementation of some of the methods utilized by AI-Batt, a battery lifetime modeling and analysis toolkit provided by the National Laboratory of the Rockies (NLR). This software demonstrates the use of bi-level optimization and symbolic regression techniques to semi-autonomously identify algebraic models predicting the capacity fade of lithium-ion batteries during calendar aging. Modeling the degradation of batteries is a complex task, due to the difficulty in separating the time-dependent and time-independent factors impacting cell level degradation, across multiple data series with different numbers of measurements and/or data quality. Bi-level optimization enables model parameters to be optimized to either the entire data set or to individual data series, allowing statistical disambiguation of global behaviors (data series independent) and local behaviors (data series dependent). Symbolic regression is used to automatically search for optimal low-dimesional models predicting the variation of locally optimized parameters versus time-independent experimental variables from millions of possible models, resulting in a more accurate and repeatable model identification process than is possible by a manual search. The provided tools also implement cross-validation and bootstrap resampling schemes, empowering statistical model comparison/selection and quantification of model uncertainties. An example script replicates the results from the manuscript "Challenging Practices of Algebraic Battery Life Models through Statistical Validation and Model Identification via Machine-Learning", submitted to ECS. All code is written in MATLAB. Requires the Statistics and Machine Learning Toolbox. Contact Dr. Paul Gasper at Paul.Gasper@nlr.gov for any questions.

Gasper, Paul↗
DOE OSTI2026

DOE EV Data Collection - Vehicle Data

Vehicle data consist of electric vehicle performance data collected directly from the vehicle during standard operations. Data were collected using onboard data loggers that were either installed by the project team or preinstalled by the original equipment manufacturer. Data recorded by the data loggers were made accessible via an online web portal or an application programming interface. Different data loggers were used (HEM, ViriCiti, and Geotab), and the method for each vehicle is defined in the vehicle attributes file. Some systems collected data on a “trip-level” basis, in which each row of a table represents a single trip (the period between a key-on and key-off event), whereas other data were collected on a per-day basis, in which each row represents a single day of operation. Data were collected over a range of data collection periods, depending on the project. Data have been anonymized by removing information or decreasing information resolution as necessary so that fleets are not identifiable. Due to the wide range of vehicle types represented and variation in data collection, data parameters and frequencies differ between vehicles and fleets The **Performance Data Daily/Trip Data Dictionaries** contain definitions for each available parameter associated with a vehicle’s operations, aggregated at either a daily or trip level. The parameters available will vary from vehicle to vehicle, but every possible parameter will be defined. The **Vehicle Attributes Data Dictionary** contains definitions for each available parameter associated with a vehicle’s physical and functional attributes and fleet context. The **Vehicle Attributes** table contains specific vehicle characteristics, coded to an anonymous Vehicle ID. This Vehicle ID can be used as a key between vehicle data and vehicle attribute tables. The **Vehicle Data** tables contain the data from each vehicle’s operations, aggregated at either a daily or trip level, coded to an anonymous Vehicle ID. This Vehicle ID can be used as a key between vehicle data and vehicle attribute tables. Data is being uploaded quarterly through 2023 and subject to change until the conclusion of the project.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗