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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 433 records · Page 24
All sourcesNASA NTRSDOE OSTI
DOE OSTI2024

Equipping Neural Network Surrogates with Uncertainty for Propagation in Physical Systems

Coarse-grained or filtered models typically rely on closure models to account for unresolved scales. For instance, large eddy simulation for modeling turbulent fluid flows explicitly resolves the largest scales, but requires modeling closure terms to account for the sub-filter scales. With the vast amount of data available from high-fidelity simulations, there are unique opportunities to leverage data-driven modeling techniques to formulate expressive and flexible closure models. Despite their flexibility, data-driven models struggle in domain shift settings, i.e. when deployed in configurations not captured in the training dataset. In particular, the efficacy of neural network surrogates is difficult to assess a priori due to the deterministic, point-estimate nature of predictions. In high-consequence applications, such models require reliable uncertainty estimates in the data-informed and out-of-distribution regimes. To quantify uncertainties in both regimes, we employ Bayesian neural networks which are able to capture both epistemic and aleatoric uncertainties. We will discuss challenges associated with the training and evaluation of these networks. Furthermore, we will discuss uncertainty embedding strategies to enable efficient sampling and propagation of uncertainty through high-fidelity simulations.

Bayesian neural networks↗
NASA NTRS1973

Surface wind characteristics of some Aleutian Islands

The wind power potential of Alaska is assessed in order to determine promising windpower sites for construction of wind machines and for shipment of wind derived energy. Analyses of near surface wind data from promising Aleutian sites accessible by ocean transport indicate probable velocity regimes and also present deficiencies in available data. It is shown that winds for some degree of power generation are available 77 percent of the time in the Aleutians with peak velocities depending on location.

Wentink, T., Jr.↗
NASA NTRS1972

Highly differentiated subalkaline rhyolite from Glass Mountain, Mono County, California.

Available data on the partition of Sr between coexisting feldspar and melt phases re interpreted as an indication that a rhyolite from Glass Mountain represents about 25% of a hypothetical 'parent' magma of silicic composition having a norm ntent of 150 ppm. Available Sr and Pb isotope data on nearby Pleistocene rhyolite lavas suggest that the 'parent' magmas of volcanic rocks of the area came from mafic or ultramafic source marl.

Noble, D. C.↗
DOE OSTI2025

U.S. Agrivoltaics Irradiance Database

This is a foundational data set for research and deployment of agrivoltaics, which is the co-location of agriculture and solar power plants on the same land. This irradiance and shading dataset can be utilized to determine the suitability of agrivoltaics configurations for a given region and crop-type. The data is hourly, 4x4 km resolution across the contiguous United States and Hawaii. It is calculated from the National Solar Radiation Database sites, using the System Advisor Model (SAM) to simulate the shading patterns for 10 common agrivoltaics configurations. Sunlight availability data is reported for 10 locations on the ground between adjacent rows of solar panels, as well as averaged across areas of interest such as the average irradiance in the edge-to-edge open area or across 3-6 planting beds. Other available metrics include the input meteorological data from the NSRDB (e.g. global horizontal irradiance, wind speed, etc.) and estimates for comparing energy and agricultural characteristic across the 10 configurations, including power output per acre or per kW installed capacity and farmable land area per acre.

14 SOLAR ENERGY↗
NASA NTRSDate not supplied

From BERTopic to SysML: Informing Model-Based Failure Analysis With Natural Language Processing for Complex Aerospace Systems

The development of emerging complex aerospace systems will require new approaches for capturing safety incident scenarios as early as possible in the design phase. However, for novel systems, relevant data available is limited. In this work, we propose a framework informing model-based mission assurance activities with historical incident reports, lessons learned, or other relevant engineering documents using natural language processing. In doing so, we investigate whether there is useful information in data sets that are relevant, if not identical, to the system under design and whether, through rigorous systems engineering practice, this information can be effectively leveraged through model-based failure analysis. In a worked case study, we apply state-of-the-art topic modeling techniques to two data sets, a mission relevant data set and a system relevant data set. The sets of topics are merged and interpreted to form a preliminary list of failure topics that can be used to inform the identification of off-nominal modes in the model-based failure modes and effects analysis development. Once data from the system in operation is available, it can be used to update the topics identified. By extracting information about likely failures from relevant historical data sets and utilizing model-based mission assurance to ensure relevance and rigor, unanticipated failures can be reduced, and projects can more effectively learn from past missions.

Failure Analysis↗
NASA NTRSDate not supplied

From BERTopic to SysML: Informing Model-Based Failure Analysis With Natural Language Processing for Complex Aerospace Systems

The development of emerging complex aerospace systems will require new approaches for capturing safety incident scenarios as early as possible in the design phase. However, for novel systems, relevant data available is limited. In this work, we propose a framework informing model-based mission assurance activities with historical incident reports, lessons learned, or other relevant engineering documents using natural language processing. In doing so, we investigate whether there is useful information in data sets that are relevant, if not identical, to the system under design and whether, through rigorous systems engineering practice, this information can be effectively leveraged through model-based failure analysis. In a worked case study, we apply state-of-the-art topic modeling techniques to two data sets, a mission relevant data set and a system relevant data set. The sets of topics are merged and interpreted to form a preliminary list of failure topics that can be used to inform the identification of off-nominal modes in the model-based failure modes and effects analysis development. Once data from the system in operation is available, it can be used to update the topics identified. By extracting information about likely failures from relevant historical data sets and utilizing model-based mission assurance to ensure relevance and rigor, unanticipated failures can be reduced, and projects can more effectively learn from past missions.

Failure Analysis↗
DOE OSTI2025

Recommendations for Minimum Required Diagnostics Information

The rapid growth of electrified transportation, including light- and medium-duty electric vehicles (EVs) as a mobility solution requires a reliable EV-charging infrastructure. To advance charging reliability, the ChargeX Consortium reports “Recommendations for Minimum Required Error Codes for Electric Vehicle Charging Infrastructure” and “Implementation Guide for Minimum Required Error Codes in Electric Vehicle Charging Infrastructure” provided recommendations for a set of minimum required error codes (MRECs), their functional and responsibility classifications, and a guide for their implementation, using Open Charge Point Protocol (OCPP) versions 1.6J4 and 2.0.1.5 These reports outline a recommended practice for consistent error reporting and interpretation, which is essential for communicating issues uniformly across the complex and diverse EV-charging ecosystem. However, MRECs are just one part of diagnosing issues; another critical part is obtaining enough information about the current state and performance of the various charging components to identify root causes for each of the error codes. This additional diagnostics data can be used by technicians or automated systems to understand the context around an issue, allowing for timely resolution, decreased maintenance costs, and increased charging reliability. During everyday operations, data are regularly collected and analyzed across the ecosystem. Although sharing of all that available data would be great for diagnostics, concerns on data ownership, privacy, and original equipment manufacturer (OEM) intellectual property pose a challenge. To overcome this obstacle, this report proposes a set of minimum required diagnostic information (MRDI) and recommends that the industry implement these uniformly across the North American EV charging ecosystem. MRDI provides a means to exchange only data deemed necessary for root cause determination.

33 ADVANCED PROPULSION SYSTEMS↗
DOE OSTI2025

Recommendations for Minimum Required Diagnostics Information for Electric Vehicle Charging Infrastructure

The rapid growth of electrified transportation, including light- and medium-duty electric vehicles (EVs) as a mobility solution requires a reliable EV charging infrastructure. To advance charging reliability, the ChargeX Consortium reports “Recommendations for Minimum Required Error Codes for Electric Vehicle Charging Infrastructure” and “Implementation Guide for Minimum Required Error Codes in Electric Vehicle Charging Infrastructure” have provided recommendations for a set of minimum required error codes (MRECs), their functional and responsibility classifications, and a guide for their implementation using OCPP versions 1.6J and 2.0.1. These reports outline a recommended practice for consistent error reporting and interpretation, which is essential for communicating issues uniformly across the complex and diverse EV charging ecosystem. However, MRECs are just one part of diagnosing issues, another critical part is obtaining enough information about the current state and performance of the various charging components to identify root causes for each of the error codes. This additional diagnostics data can be used by technicians or automated systems to understand the context around an issue, allowing for timely resolution, decreased maintenance costs, and increased charging reliability. During everyday operations, data is regularly collected and analyzed across the ecosystem. Although sharing of all that available data would be great for diagnostics, concerns on data ownership, privacy, and OEM intellectual property pose a challenge. To overcome this obstacle, this report proposes a set of Minimum Required Diagnostic Information (MRDI) and recommends that the industry implement these uniformly across the North American EV charging ecosystem. MRDI provides a means to exchange only data deemed necessary for root cause determination.

32 - ENERGY CONSERVATION, CONSUMPTION, AND UTILIZA↗
DOE OSTI2025

GLBRC Soil Yearlong Incubation 13C-SIP-Lipidomics

Data package for Lipids represent a dynamic, yet stable pool of microbially-derived soil carbon This data is published under a CC0 license. The authors encourage data reuse and request attribution by referencing the below citations for the data packages and associated manuscript. Please cite as: Rempfert KR, Bell SL, Kasanke CP, Kyle JE, Hofmockel KS. 2025. GLBRC Soil Yearlong Incubation 13C-SIP-Lipidomics. [Data Set] PNNL DataHub. doi: Rempfert KR, Bell SL, Kasanke CP, Kyle JE, Hofmockel KS. 2025. MSV000097435: GLBRC soil yearlong incubation 13C-SIP-Lipidomics [Data Set] MassIVE. doi:10.25345/C57659T3K Rempfert KR, Bell SL, Kasanke CP, Kyle JE, Hofmockel KS. 2025. Lipids represent a dynamic, yet stable pool of microbially-derived soil carbon. In Prep This data package consists of compound-specific 13C SIP-lipidomics data from a yearlong tracer incubation experiment designed to investigate microbial lipid persistence in switchgrass bioenergy crop soils. In order to explore how lipid structure may modulate the persistence of C in soil lipids, we leveraged soils from two sites (Michigan - sandy texture, Wisconsin - silty texture) operated by the U.S. Department of Energy-funded Great Lakes Bioenergy Research Center (GLBRC). These sites had comparable climates, identical management practices, but contrasting soil textures, allowing us to assess the variability of lipid accrual or degradation in soils as well as provide insight regarding the degree to which edaphic properties may regulate the retention of soil lipids. Untargeted lipidomics analyses were performed to identify 13C-labeled lipids in the soil microbiome after long-term incubation. Soils were supplemented with 100 micrograms glucose per gram dry soil (99 atom % 13C or natural abundance for paired control) and incubated; samples were collected two months and one year after glucose addition. Lipid extracts (MPLEx) were analyzed by LC-MS/MS and identified using LIQUID. Calculation of isotopic enrichment of lipids was performed by targeted approach using TarMet to quantify lipid isotopologues and IsoCorrectoR to correct for natural abundance isotopes. Contents: Data package contents reported here are the first version and contain downstream analysis files for the raw LC-MS mass spectrometry files (.mzXML) deposited at the MassIVE database repository under accession MSV000097435 (80 experimental runs; 5.85 GB) | MassIVE DOI: 10.25345/C57659T3K. Support files include the additional data download 'Read Me' file containing data descriptor information. Reported data download contents are structured for compliance with project data sharing guidelines, community standards initiatives, and sponsor stakeholder policies supporting FAIR data principles. Data processing software, analysis tools, and data workflows are listed below corresponding to the host repository long-term location. Available Data Downloads (0.3 GB): "GLBRC soil yearlong incubation 13C-SIP-Lipidomics_readme.txt" - 'Read Me' data package content file (txt) "GLBRC_DataPackage_analysis files" - Data processing files (Rmd) and saved intermediate data processing outputs (rds, csv, xlsx) "GLBRC_13C_lipidomics_dataset.xlsx" - processed data in tabular format (xlsx) Linked Software: LIQUID LC-MS Analysis Software | 10.5281/zenodo.6459462 Lipid Mini-On Software Tools | 10.5281/zenodo.1492803 pmartR Omics Statistical Software | 10.5281/zenodo.6108667 xcms (v4.3.3) TarMet (v1.1.1) IsoCorrectoR (1.24.0) Funding Acknowledgments: This research was supported by an Early Career Research Program award funded by the U.S. Department of Energy, Office of Science, Office of Biological and Environmental Research (OBER) Genomic Science program under FWP 68292, FWP 07880 and EMSL Exploratory Research Project 51095. A portion of this work was performed in the William R. Wiley Environmental Molecular Sciences Laboratory, a national scientific user facility sponsored by OBER and located at Pacific Northwest National Laboratory (PNNL). PNNL is a multi-program national laboratory operated by Battelle for the DOE under Contract DE-AC05-76RLO1830.

Rempfert, Kaitlin R [Pacific Northwest National La↗
NASA NTRS1973

A mathematical model for jet engine combustor pollutant emissions

Mathematical modeling for the description of the origin and disposition of combustion-generated pollutants in gas turbines is presented. A unified model in modular form is proposed which includes kinetics, recirculation, turbulent mixing, multiphase flow effects, swirl and secondary air injection. Subelements of the overall model were applied to data relevant to laboratory reactors and practical combustor configurations. Comparisons between the theory and available data show excellent agreement for basic CO/H2/Air chemical systems. For hydrocarbons the trends are predicted well including higher-than-equilibrium NO levels within the fuel rich regime. Although the need for improved accuracy in fuel rich combustion is indicated, comparisons with actual jet engine data in terms of the effect of combustor-inlet temperature is excellent. In addition, excellent agreement with data is obtained regarding reduced NO emissions with water droplet and steam injection.

Boccio, J. L.↗
NASA NTRS1979

Free energy of formation of Mo2C and the thermodynamic properties of carbon in solid molybdenum

As part of a study of the thermodynamical properties of interstitial elements in refractory metals, the free energy of formation of Mo2C is determined, and the thermodynamical properties of C in solution in solid Mo evaluated. The activity of C in the two-phase region Mo + Mo2C is obtained from the C content of iron rods equilibrated with metal + carbide powder mixtures. The free energy of formation of alpha-Mo2C is determined from the activity data. The thermodynamic properties of C in the terminal solid solution are calculated from available data on the solid solubility of C in Mo. Lattice distortion due to misfit of the C atoms in the interstitial sites appears to play a significant role in determining the thermodynamic properties of C in solid Mo.

Seigle, L. L.↗
NASA NTRS1992

Future directions for LDEF ionizing radiation modeling and assessments

Data from the ionizing radiation dosimetry aboard LDEF provide a unique opportunity for assessing the accuracy of current space radiation models and in identifying needed improvements for future mission applications. Details are given of the LDEF data available for radiation model evaluations. The status is given of model comparisons with LDEF data, along with future directions of planned modeling efforts and data comparison assessments. The methodology is outlined which is related to modeling being used to help insure that the LDEF ionizing radiation results can be used to address ionizing radiation issues for future missions. In general, the LDEF radiation modeling has emphasized quick-look predictions using simplified methods to make comparisons with absorbed dose measurements and induced radioactivity measurements of emissions. Modeling and LDEF data comparisons related to linear energy transfer spectra are of importance for several reasons which are outlined. The planned modeling and LDEF data comparisons for LET spectra is discussed, including components of the LET spectra due to different environment sources, contribution from different production mechanisms, and spectra in plastic detectors vs silicon.

Armstrong, T. W.↗
NASA NTRS1992

Mean winds and momentum fluxes over Jicamarca, Peru, during June and August 1987

Data from the mesosphere-stratosphere-troposphere radar at Jicamarca, Peru, together with other available data, are used to diagnose the mean structure of winds and gravity-wave momentum fluxes from the surface to 90 km during two-ten-day campaigns in June and August of 1987. In the stratosphere a layer of maximum eastward flow associated with the quasi-biennial oscillation (QBO) was seen to strengthen and descend rapidly from June to August, overlying persistent westward flow. A layer of enhanced signal return, suggestive of a turbulent layer, was observed just above the descending QBO eastward maximum. Notable zonal asymmetries were present during this transition and the local meridional circulation departed from zonal-mean QBO theory. A substantial northeastward momentum flux was found below 25 km, which may be related to topographic gravity waves excited by southeastward flow across the Andes. In the lower mesosphere a relatively weak 'second' mesopause semiannual oscillation is confirmed. In both the lower stratosphere and mesosphere, body forces were comparable in magnitude to inferred Coriolis torques.

Hitchman, Matthew H.↗
NASA NTRS1995

Use of nonlinear identification in robust attitude and attitude rate estimation for SAMPEX

A method is described for obtaining optimal attitude estimation/identification algorithms for spacecraft lacking attitude rate measurement devices (rate gyros), and then demonstrated using actual flight data from the Solar, Anomalous, and Magnetospheric Particle Explorer (SAMPEX) spacecraft. SAMPEX does not have on-board rate sensing, and relies on sun sensors and a three-axis magnetometer for attitude determination. The absence of rate data normally reduces both the total amount of data available and the sampling density (in time) by a substantial fraction. In addition, attitude data is occasionally unavailable (for example, during sun occultation). As a result, the sensitivity of the estimates to model uncertainty and to measurement noise increases. In order to maintain accuracy in the attitude estimates, there is an increased need for accurate models of the rotational dynamics. The Minimum Model Error(MME)/Least Square Correlation(LSC) algorithm accurately identifies an improved model for SAMPEX to be used during periods of complete data loss or extreme noise. The model correction is determined by estimating only one orbit(the identification pass) just prior to the assumed data loss(the prediction pass). The MME estimator correctly predicted the states during the identification phase, but more importantly determines the necessary model correction trajectory, d(t). The LSC algorithm is then used to find this trajectory's functional form, H(x(t)). The results show significant improvement of the new corrected model's attitude estimates as compared to the original uncorrected model's estimates. The possible functional form of the correction term is limited at this point in the study to functions strictly of the estimated states. The results, however, strongly suggest that functions based on the relative position of the satellite may also be possible candidates for future consideration.

Mook, D. Joseph↗
NASA NTRS2001

Analysis and Quality Assurance of the SKYMAP 4.0 Guidance and Tracking Star Catalog: The NASA SKY2000 Spacecraft Attitude Determination Star Catalog

An updated and improved NASA spacecraft attitude determination catalog, now called SKY2000, Version 3, has been prepared and quality assured. The highest priority goals were to replace the astrometric (positions and motions) and photometric (brightnesses and colors) data with the most recent and accurate data available. Quality assurance has been performed in a fairly straightforward manner, i.e., without extensive data checking and analysis, and many errors and Inconsistencies were corrected. Additional work should eventually be done on the variability and multiple-star data In the catalog, while certain other data can be significantly Improved. The current version of the catalog can be found at the GSFC Flight Dynamics website: http://cheli.gsfc.nasa.gov/dist/attitude/skymap.html. Supporting information and reference materials (published papers, format and data descriptions, etc.) can also be found at the website.

Warren, Wayne H., Jr.↗
NASA NTRS2001

Estimation of Mesoscale Atmospheric Latent Heating Profiles from TRMM Rain Statistics Utilizing a Simple One-Dimensional Model

In this study, a model is developed to estimate mesoscale-resolution atmospheric latent heating (ALH) profiles. It utilizes rain statistics deduced from Tropical Rainfall Measuring Mission (TRMM) data, and cloud vertical velocity profiles and regional surface thermodynamic climatologies derived from other available data sources. From several rain events observed over tropical ocean and land, ALH profiles retrieved by this model in convective rain regions reveal strong warming throughout most of the troposphere, while in stratiform rain regions they usually show slight cooling below the freezing level and significant warming above. The mesoscale-average, or total, ALH profiles reveal a dominant stratiform character, because stratiform rain areas are usually much larger than convective rain areas. Sensitivity tests of the model show that total ALH at a given tropospheric level varies by less than +/- 10 % when convective and stratiform rain rates and mesoscale fractional rain areas are perturbed individually by 1 15 %. This is also found when the non-uniform convective vertical velocity profiles are replaced by one that is uniform. Larger variability of the total ALH profiles arises when climatological ocean- and land-surface temperatures (water vapor mixing ratios) are independently perturbed by +/- 1.0 K (+/- 5 %) and +/- 5.0 K (+/- 15 %), respectively. At a given tropospheric level, such perturbations can cause a +/- 25 % variation of total ALH over ocean, and a factor-of-two sensitivity over land. This sensitivity is reduced substantially if perturbations of surface thermodynamic variables do not change surface relative humidity, or are not extended throughout the entire model evaporation layer. The ALH profiles retrieved in this study agree qualitatively with tropical total diabatic heating profiles deduced in earlier studies. Also, from January and July 1999 ALH-profile climatologies generated separately with TRMM Microwave Imager and Precipitation Radar rain statistics, it is shown that ALH profiles can be retrieved utilizing diverse satellite-derived rain products that offer convective and stratiform discrimination. Therefore, the ALH retrieval model developed in this study can be used to make regional estimates of total diabatic heating profiles in the future Global Precipitation Measurement mission, and to assimilate these profiles into numerical weather forecast and climate models.

Iacovazzi, Robert A., Jr.↗
NASA NTRS2002

Determination of Receiver Susceptibility to Radio Frequency Interference from Portable Electronic Devices

With the increasing pressures to allow wireless devices on aircraft, the susceptibility of aircraft receivers to interference from Portable Electronic Devices (PEDs) becomes an increasing concern. Many investigations were conducted in the past, with limited success, to quantify device emissions, path loss, and receiver interference susceptibility thresholds. This paper outlines the recent effort in determining the receiver susceptibility thresholds for ILS, VOR and GPS systems. The effort primarily consists of analysis of data available openly as reported in many RTCA and ICAO documents as well as manufacturers data on receiver sensitivity. Shortcomings with the susceptibility threshold data reported in the RTCA documents are presented, and an approach for an in-depth study is suggested. In addition, intermodulation products were observed and demonstrated in a laboratory experiment when multiple PEDs were in the proximity of each other. These intermodulation effects generate spurious frequencies that may fall within aircraft communication or navigation bands causing undesirable effects. Results from a preliminary analysis are presented that show possible harmful combinations of PEDs and the potentially affected aircraft bands.

Nguyen, Truong X.↗
NASA NTRS2002

Estimation of Mesoscale Atmospheric Latent Heating Profiles from TRMM Rain Statistics Utilizing a Simple One-Dimensional Model

In this study, a model is developed to estimate mesoscale-resolution atmospheric latent heating (ALH) profiles. It utilizes rain statistics deduced from Tropical Rainfall Measuring Mission (TRMM) data, and cloud vertical velocity profiles and regional surface thermodynamic climatologies derived from other available data sources. From several rain events observed over tropical ocean and land, ALH profiles retrieved by this model in convective rain regions reveal strong warming throughout most of the troposphere, while in stratiform rain regions they usually show slight cooling below the freezing level and significant warming above. The mesoscale-average, or total, ALH profiles reveal a dominant stratiform character, because stratiform rain areas are usually much larger than convective rain areas. Sensitivity tests of the model show that total ALH at a given tropospheric level varies by less than +/- 10 % when convective and stratiform rain rates and mesoscale fractional rain areas are perturbed individually by +/- 15 %. This is also found when the non-uniform convective vertical velocity profiles are replaced by one that is uniform. Larger variability of the total ALH profiles arises when climatological ocean- and land-surface temperatures (water vapor mixing ratios) are independently perturbed by +/- 1.0 K (+/- 5%) and +/- 5.0 K (+/- 15%), respectively. At a given tropospheric level, such perturbations can cause a +/- 25% variation of total ALH over ocean, and a factor-of-two sensitivity over land. This sensitivity is reduced substantially if perturbations of surface thermodynamic variables do not change surface relative humidity, or are not extended throughout the entire model evaporation layer. The ALH profiles retrieved in this study agree qualitatively with tropical total diabatic heating profiles deduced in earlier studies. Also, from January and July 1999 ALH-profile climatologies generated separately with TRMM Microwave Imager and Precipitation Radar rain statistics, it is shown that ALH profiles can be retrieved utilizing diverse satellite-derived rain products that offer convective and stratiform discrimination. Therefore, the ALH retrieval model developed in this study can be used to make regional estimates of total diabatic heating profiles in the future Global Precipitation Measurement mission, and to assimilate these profiles into numerical weather forecast and climate models.

Iacovazzi, Robert A., Jr.↗