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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 1,711 records · Page 95
All sourcesNASA NTRSDOE OSTI
NASA NTRS1991

Environmental analysis using integrated GIS and remotely sensed data - Some research needs and priorities

This paper discusses some basic scientific issues and research needs in the joint processing of remotely sensed and GIS data for environmental analysis. Two general topics are treated in detail: (1) scale dependence of geographic data and the analysis of multiscale remotely sensed and GIS data, and (2) data transformations and information flow during data processing. The discussion of scale dependence focuses on the theory and applications of spatial autocorrelation, geostatistics, and fractals for characterizing and modeling spatial variation. Data transformations during processing are described within the larger framework of geographical analysis, encompassing sampling, cartography, remote sensing, and GIS. Development of better user interfaces between image processing, GIS, database management, and statistical software is needed to expedite research on these and other impediments to integrated analysis of remotely sensed and GIS data.

Davis, Frank W.↗
DOE OSTI2016

Nuclear Data Testing Of Pu{sup 239} CIELO Evaluation With NDaST

Within the Collaborative International Evaluated Library Organisation (CIELO) project a coordinated effort is being made amongst the different nuclear data evaluation projects, ENDF, JEFF, JENDL etc. to improve the cross sections of six of the most important isotopes, Pu{sup 239}, U{sup 235}, U{sup 238}, Fe{sup 56}, O{sup 16} and H{sup 1}. Recently developed, the Nuclear Data and Sensitivity Tool (NDaST) is an online tool (http://www.oecd-nea.org/ndast/) that allows nuclear data evaluators to get rapid feedback about the consequences of changes to nuclear data on integral experiment benchmarks that exist within the International Criticality Safety Benchmark Evaluation Project (ICSBEP) and International Reactor Physics Evaluation (IRPhE) Project handbooks. NDaST links the thousands of nuclear data sensitivity profiles in the Database for ICSBEP (DICE) and the IRPhE Database and Analysis Tool (IDAT), with the nuclear data viewing tool JANIS. NDaST can be used to provide timely feedback to CIELO participants. Normally an evaluator changes the ENDF/B files based on differential data, and subsequently hands the new evaluation to testers who give feedback on the performance of the new evaluation in terms of accurately predicting the integral benchmark results. This process is often slow. With accurate sensitivity coefficients it is feasible to predict the results of changes to differential data without performing the direct substitution, by simply multiplying the change in cross section with the sensitivity. Furthermore, when multiple aspects of the file are changed simultaneously, the impact of each individual change can be muddled in the substitution testing. NDaST when used in conjunction with direct perturbation testing can help provide feedback as to which cross section changes are driving changes in the benchmarks. In this paper we focus on Pu{sup 239}, and comparing the NDaST predictions of CIELO files to direct substitution. (authors)

07 ISOTOPE AND RADIATION SOURCES↗
DOE OSTI2014

Wind Integration National Dataset (WIND) Toolkit

Wind resource data for North America was produced using the Weather Research and Forecasting Model (WRF). The WRF model was initialized with the European Centre for Medium Range Weather Forecasts Interim Reanalysis (ERA-Interm) data set with an initial grid spacing of 54 km. Three internal nested domains were used to refine the spatial resolution to 18, 6, and finally 2 km. The WRF model was run for years 2007 to 2014. While outputs were extracted from WRF at 5 minute time-steps, due to storage limitations instantaneous hourly time-step are provided for all variables while full 5 min resolution data is provided for wind speed and wind direction only. The following variables were extracted from the WRF model data: - Wind Speed at 10, 40, 60, 80, 100, 120, 140, 160, 200 m - Wind Direction at 10, 40, 60, 80, 100, 120, 140, 160, 200 m - Temperature at 2, 10, 40, 60, 80, 100, 120, 140, 160, 200 m - Pressure at 0, 100, 200 m - Surface Precipitation Rate - Surface Relative Humidity - Inverse Monin Obukhov Length

API↗
DOE OSTI2024

Federated Machine Learning-Based Anomaly Detection System for Synchrophasor Network Using Heterogeneous Data Sets: Preprint

Synchrophasor technology is widely deployed in the energy management system to monitor the grid health at micro level and perform necessary corrective actions in real time; however, integrated phasor devices and data aggregators are exposed to several cybersecurity threats. This paper proposes a federated ML(FML)-based ADS to detect several data integrity attacks in the synchrophasor network. The proposed approach integrates the horizontal FML technique and consists of substation-based local models and a control center-based global model. The proposed methodology includes training local models using heterogeneous data sets that include network and grid information and updating the global model through multiple iterations by sharing model gradients. Finally, the trained global model is applied to identify cyberattacks, normal operation, and physical events. To validate the proof of concept, we used synthetic data sets generated by Mississippi State University and Oak Ridge National Laboratory for training and testing the classification models using the National Renewable Energy Laboratory's high performance computing resources. Our experimental results, computed through several performance measures, reveal that the proposed approach shows consistent performance during the binary, three-class, and multiclass classifications while ensuring privacy of synchrophasor data.

anomaly detection system↗
DOE OSTI2026

Calibration of urban building energy model using smart meter data for district peak load prediction

Urban building energy modeling (UBEM) is a powerful approach to assessing baseline building energy performance and retrofits with new technologies across building stocks in cities. However, the accuracy of UBEM is often constrained by the limited availability of reliable data about building characteristics and operations, such as envelope efficiency levels, HVAC system performance, and end-use load patterns. Existing research has performed UBEM calibration using annual or monthly energy consumption data, which falls short when higher-resolution time series applications are needed, such as peak load prediction for utility operation planning. This study presents a new framework for calibrating building energy models at urban scale using smart meter data, targeting the accurate prediction of summer peak electricity loads to support robust grid planning. The framework first integrates various data sources to enhance baseline input assumptions for building models, and then calibrates the baseline models through a pattern-matching approach. A case study using CityBES and two years of AMI data from over 9000 residential customers in Portland, Oregon, demonstrated the workflow and its effectiveness. The calibrated models achieved a daily peak load mean absolute percentage error of 2.6 % during the heatwave in the calibration year, and 2.0 % in the validation year using another year of AMI data. Using the calibrated models, we analyzed the demand flexibility potential of the district building stock as an application of UBEM calibration. The findings affirm the appropriate use of UBEM for peak electric load forecasting and demand side management at the utility distribution system level.

AMI data↗
DOE OSTI2026

Leveraging Large Language Models for Understanding Fundamental Principles of Catalysis

Heterogeneous catalysis presents a distinct challenge for artificial intelligence (AI). Data sets are often small and inconsistently reported, catalyst representations are not standardized, and extracting fundamental knowledge requires integrating performance data, spectroscopic characterizations, and mechanistic models across multiple scales. Language offers a unifying representation across these modalities, making catalysis well suited for leveraging large language models (LLMs). By standardizing how catalytic data is represented, LLMs make dispersed experimental results more accessible to downstream statistical modeling. In this perspective, we focus our discussion around three opportunities where LLMs can significantly contribute to catalysis: (1) text to properties; (2) text to structure; and (3) text to mechanistic models. The discussion is followed by a perspective section on LLM-readiness of data, aligning LLM outputs with scientific correctness, and bridging lab-scale discovery to industrial deployment. Across each area, the most productive applications couple dispersed chemical knowledge with physics-grounded validation to produce verifiable hypotheses and actionable representations.

Catalysts↗
NASA NTRS1987

Development of an air ground data exchange concept: Flight deck perspective

The planned modernization of the U.S. National Airspace System (NAS) includes the development and use of a digital data link as a means to exchange information between aircraft and ground-based facilities. This report presents an operationally-oriented concept on how data link could be used for applications related directly to air traffic control. The specific goal is to establish the role that data link could play in the air-ground communications. Due regard is given to the unique characteristics of data link and voice communications, current principles of air traffic control, operational procedures, human factors/man-machine interfaces, and the integration of data link with other air and ground systems. The resulting concept is illustrated in the form of a paper-and-pencil simulation in which data link and voice communications during the course of a hypothetical flight are described.

Flathers, G. W., II↗
NASA NTRS1995

Parameterization and scaling of arctic ice conditions in the context of ice-atmospheric processes

The goals of this project are to observe how the open water/thin ice fraction in a high-concentration ice pack responds to different short-period atmospheric forcings, and how this response is represented in different scales of observation. The objectives can be summarized as follows: determine the feasibility and accuracy of ice concentration and ice typing by ERS-1 SAR backscatter data, and whether SAR data might be used to calibrate concentration estimates from optical and massive-microwave sensors; investigate methods to integrate SAR data with other satellite data for turbulent heat flux parameterization at the ocean/atmosphere interface; determine how the development and evolution of open water/thin ice areas within the interior ice pack vary under different atmospheric synoptic regimes; compare how open-water/thin ice fractions estimated from large-area divergence measurements differ from fractions determined by summing localized openings in the pack; relate these questions of scale and process to methods of observation, modeling, and averaging over time and space.

Barry, R. G.↗
NASA NTRS2007

Tracking-Data-Conversion Tool

Object Oriented Data Technology (OODT) is a software framework for creating a Web-based system for exchange of scientific data that are stored in diverse formats on computers at different sites under the management of scientific peers. OODT software consists of a set of cooperating, distributed peer components that provide distributed peer-topeer (P2P) services that enable one peer to search and retrieve data managed by another peer. In effect, computers running OODT software at different locations become parts of an integrated data-management system.

Flora-Adams, Dana↗
NASA NTRS2007

Software Framework for Peer Data-Management Services

Object Oriented Data Technology (OODT) is a software framework for creating a Web-based system for exchange of scientific data that are stored in diverse formats on computers at different sites under the management of scientific peers. OODT software consists of a set of cooperating, distributed peer components that provide distributed peer-to-peer (P2P) services that enable one peer to search and retrieve data managed by another peer. In effect, computers running OODT software at different locations become parts of an integrated data-management system.

Hughes, John↗
NASA NTRS2015

Complementary Aerodynamic Performance Datasets for Variable Speed Power Turbine Blade Section from Two Independent Transonic Turbine Cascades

Two independent experimental studies were conducted in linear cascades on a scaled, two-dimensional mid-span section of a representative Variable Speed Power Turbine (VSPT) blade. The purpose of these studies was to assess the aerodynamic performance of the VSPT blade over large Reynolds number and incidence angle ranges. The influence of inlet turbulence intensity was also investigated. The tests were carried out in the NASA Glenn Research Center Transonic Turbine Blade Cascade Facility and at the University of North Dakota (UND) High Speed Compressible Flow Wind Tunnel Facility. A large database was developed by acquiring total pressure and exit angle surveys and blade loading data for ten incidence angles ranging from +15.8deg to −51.0deg. Data were acquired over six flow conditions with exit isentropic Reynolds number ranging from 0.05×106 to 2.12×106 and at exit Mach numbers of 0.72 (design) and 0.35. Flow conditions were examined within the respective facility constraints. The survey data were integrated to determine average exit total-pressure and flow angle. UND also acquired blade surface heat transfer data at two flow conditions across the entire incidence angle range aimed at quantifying transitional flow behavior on the blade. Comparisons of the aerodynamic datasets were made for three "match point" conditions. The blade loading data at the match point conditions show good agreement between the facilities. This report shows comparisons of other data and highlights the unique contributions of the two facilities. The datasets are being used to advance understanding of the aerodynamic challenges associated with maintaining efficient power turbine operation over a wide shaft-speed range.

Cascade↗
NASA NTRS2015

Complementary Aerodynamic Performance Datasets for Variable Speed Power Turbine Blade Section from Two Independent Transonic Turbine Cascades

Two independent experimental studies were conducted in linear cascades on a scaled, two-dimensional mid-span section of a representative Variable Speed Power Turbine (VSPT) blade. The purpose of these studies was to assess the aerodynamic performance of the VSPT blade over large Reynolds number and incidence angle ranges. The influence of inlet turbulence intensity was also investigated. The tests were carried out in the NASA Glenn Research Center Transonic Turbine Blade Cascade Facility and at the University of North Dakota (UND) High Speed Compressible Flow Wind Tunnel Facility. A large database was developed by acquiring total pressure and exit angle surveys and blade loading data for ten incidence angles ranging from +15.8deg to −51.0deg. Data were acquired over six flow conditions with exit isentropic Reynolds number ranging from 0.05×106 to 2.12×106 and at exit Mach numbers of 0.72 (design) and 0.35. Flow conditions were examined within the respective facility constraints. The survey data were integrated to determine average exit total-pressure and flow angle. UND also acquired blade surface heat transfer data at two flow conditions across the entire incidence angle range aimed at quantifying transitional flow behavior on the blade. Comparisons of the aerodynamic datasets were made for three "match point" conditions. The blade loading data at the match point conditions show good agreement between the facilities. This report shows comparisons of other data and highlights the unique contributions of the two facilities. The datasets are being used to advance understanding of the aerodynamic challenges associated with maintaining efficient power turbine operation over a wide shaft-speed range.

Turbine↗
DOE OSTI2016

ACCELEROMETERS IN FLOW FIELDS: A STRUCTURAL ANALYSIS OF THE CHOPPED DUMMY INPILE TUBE

Four tests characterizing the structural response of the Chopped-Dummy In-Pile tube (CDIPT) experiment design were measured in the Hydro-Mechanical Fuel Test Facility (HMFTF). Four different test configurations were tried. These configurations tested the pressure drop and flow impact of various plate configurations and flow control orifices to be used later at different reactor power levels. Accelerometers were placed on the test vehicle and flow simulation housing. A total of five accelerometers were used with one on the top and bottom of the flow simulator and vehicle, and one on the outside of the flow simulator. Data were collected at a series of flow rates for 5 seconds each at an acquisition rate of 2 kHz for a Nyquist frequency of 1 kHz. The data were then analyzed using a Fast Fourier Transform (FFT) algorithm. The results show very coherent vibrations of the CDIPT experiment on the order of 50 Hz in frequency and 0.01 m/s2 in magnitude. The coherent vibrations, although small in magnitude pose a potential design problem if the frequencies coincide with the natural frequency of the fueled plates or test vehicle. The accelerometer data was integrated and combined to create a 3D trace of the experiment during the test. The merits of this data as well as further anomalies and artifacts are also discussed as well as their relation to the instrumentation and experiment design.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2016

Accelerometers in flow fields: a structural analysis of the chopped dummy in-pile tube

Four tests characterizing the structural response of the Chopped-Dummy In-Pile tube (CDIPT) experiment design were measured in the Hydro-Mechanical Fuel Test Facility (HMFTF). Four different test configurations were tried. These configurations tested the pressure drop and flow impact of various plate configurations and flow control orifices to be used later at different reactor power levels. Accelerometers were placed on the test vehicle and flow simulation housing. A total of five accelerometers were used with one on the top and bottom of the flow simulator and vehicle, and one on the outside of the flow simulator. Data were collected at a series of flow rates for 5 seconds each at an acquisition rate of 2 kHz for a Nyquist frequency of 1 kHz. The data were then analyzed using a Fast Fourier Transform (FFT) algorithm. The results show very coherent vibrations of the CDIPT experiment on the order of 50 Hz in frequency and 0.01 m/s{sup 2} in magnitude. The coherent vibrations, although small in magnitude pose a potential design problem if the frequencies coincide with the natural frequency of the fueled plates or test vehicle. The accelerometer data was integrated and combined to create a 3D trace of the experiment during the test. The merits of this data as well as further anomalies and artifacts are also discussed as well as their relation to the instrumentation and experiment design. (authors)

42 ENGINEERING↗
NASA NTRS1985

The integrated enstrophy budget of the winter stratosphere diagnosed from LIMS data

The quasi-geostrophic integrated enstrophy budget for the 1978 to 1979 winter has been analyzed from 10-0.1 mb using LIMS data. During January and late February periods a significant imbalance in the budget appears at 10mb. This imbalance is attributed to Rossby wave breaking. It is produced by the irreversible transfer of enstrophy to smaller scales not resolved by LIMS. The imbalance episodes correspond well to the appearance of Ertel vorticity filaments shown by McIntyre and Palmer (1984). From a seasonal viewpoint, the integrated enstrophy shows an average (although irregular) transfer from a zonal mean reservoir to waves which are then dissipated. On a shorter time scale the integrated enstrophy sloshes back and forth between the waves and mean flow in early winter; then, beginning with the January sudden warming, the total enstrophy is reduced more rapidly. Between 10 mb and 1 mb this reduction is more or less continuous until the end of February. However, in the mesosphere the total enstrophy decrease is very short lived, being quickly restored after the January warming. Even though the zonal mean integrated enstrophy is large, only about 10% can be utilized by the waves. The available integrated potential enstrophy is introduced, which is a better measure of how close the flow is to saturation by Rossby waves. The largest amount of available potential enstrophy in early January is at 1 mb with decreasing amounts above and below. Saturation of the flow by Rossby waves occurs below 1 mb only coincident with sudden warmings; however, at mesospheric heights the flow appears to be nearly saturated throughout the winter.

Schoeberl, M. R.↗
DOE OSTI2025

Identifying Nuclear Data Correlated Through Predicting Bias in Integral Experiments via Applying Principal Component Analysis to Random Forest

ABSTRACT Nuclear data (ND) are the input data for neutron‐transport simulations to answer questions related to nuclear technologies. Subsets of ND, here > 20,000 data points, are validated with respect to thousands of criticality experiments that represent various applications on a small scale. The aim of validation with these experiments is to find errors in ND or methods. The key challenge here is that several hundreds of ND are used to simulate one integral value. Hence, one cannot clearly identify what ND are leading to bias in criticality measurements. In fact, a mistake in one nuclear‐data observable can be compensated with an error in another, and the predicted criticality value would still be predicted in agreement with experimental data. Random forest (RF) was previously employed to predict bias in criticality measurements using sensitivities of simulated criticality experiments to ND. The SHapley Additive exPlanations (SHAP) metric was then applied to attribute the importance of each ND experiment and observable to bias prediction. This, however, did not highlight what ND were jointly related to predicting bias. This is important as it could inform us about where compensating errors in ND could hide. We tackle this shortcoming here by first decomposing the ND sensitivities to integral‐experiment simulations into principal components. Then we use principal component projections to predict bias via the RF and SHAP. The SHAP values and principal components are employed to reconstruct detailed SHAP values for each ND observable. We demonstrate that these extended SHAP bias predictions are more robust, less noisy, and more efficient. In addition, we show that this approach accounts for covariance in ND sensitivities and automates the identification of where compensating errors could hide in ND.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
NASA NTRSDate not supplied

Visualization of Near Real-Time Global Cloud Composites (GCC): Integration in ArcGIS

The NASA Langley Satellite ClOud and Radiation Property retrieval System (SatCORPS) team provides low latency LEO and GEO satellite derived cloud and radiation products to end users for use in near real-time (NRT) applications. Hourly mosaics are fused from LEO (SNPP, JPSS-1, AQUA, MODIS) and GEO Satellite imagers (GOES-West, GOES-East, Metesat-11, Metesat-8, and Himawari-8) to create global cloud composites (GCC). SatCORPS GCC data are integrated into Esri ArcGIS system and transformed into Analysis Rady Data (ARD) to provide more efficient data access to support disaster management, weather diagnoses/forecasting, and Earth Sciences remote sensing applications. GCC data are exposed as RESTful APIs, ArcGIS Image Services, and Open Geospatial Consortium (OGC) Web Mapping Services/Web Coverage Services to provide a variety of end points for integration into user applications. We will preview the new interactive SatCORPS GCC web visualization tool and discuss initial integration of GCC product into NASA Airborne Mission Tool Suite (MTS) to support NASA and NOAA field campaigns.

GIS↗