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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 397 records · Page 22
All sourcesNASA NTRSDOE OSTI
DOE OSTI2023

Streaming Data from Experimental Facilities to Supercomputers for Real-Time Data Processing

In this paper we demonstrate direct data streaming from instruments and detectors at a large-scale experimental facility to a supercomputer for real-time data processing and feedback. Streaming data to supercomputers introduces the potential for novel scientific applications and workflow models, including the ability to provide real-time feedback from very large datasets during an experiment and the integration of real-time ML training and inference at scale. We discuss a successful demonstration for real-time processing of data from the Advanced Photon Source (APS) on the Polaris supercomputer using an EPICS-based streaming framework. We describe the capabilities of the streaming framework itself, and outline the architecture that allows us to process experimentally derived data on a supercomputer without file-based data transfers. We present throughput measurements that are indicative of system performance capable of sustaining the expected data production rates of the facility, as well as discuss some outstanding challenges and our future directions.

real-time processing↗
DOE OSTI2026

Asi Nuclear Energy Sensors Data Portal Chatbot And Data Structuring Tool

The Idaho National Laboratory (INL) is advancing the development of an AI-powered chatbot and data structuring tool specifically designed to accelerate data mining processes for sensor-related information and seamlessly integrate the results into the ASI Sensors Data Portal (https://nes.energy.gov/). By doing so, the software aims to enhance the accessibility, usability, and organization of sensor data for nuclear energy applications. The software initial phase focuses on retrieving comprehensive datasets, prioritizing the past five years of publicly available information from the Office of Scientific and Technical Information (OSTI). These datasets will be meticulously processed to ensure compatibility, employing cleaning and preprocessing steps to eliminate irrelevant, incomplete, or corrupted information, thus establishing a robust foundation for subsequent AI use. The data will serve as the backbone for training an AI model and chatbot, which will act as an interactive tool enabling users to ask complex, context-specific questions and receive accurate, validated answers derived from constrained literature. In parallel, the project incorporates a data structuring process supported by AI to organize sensor information from multiple sources into a standardized format. This structured data will include detailed sensor specifications, such as measurement range, applications, accuracy, and operating conditions, generated and documented with AI. These specifications will be systematically integrated into the sensor portal. To maintain the highest levels of accuracy and relevance, all AI-generated outputs will be reviewed and validated by subject matter experts (SMEs), with additional fields or parameters added as needed. Future stages of the project aim to expand the dataset beyond OSTI to include other sources and potentially incorporate unclassified controlled information (UCI) with restricted access protocols to address security and confidentiality requirements.

Mapes, NormanJ. [Idaho National Laboratory (INL), ↗
DOE OSTI2026

Raw Lidar and Camera Data Synchronized with Precipitation and Present Weather Data

As part of the sensor characterization task of the SMART 2.0 project, this dataset includes raw data from three spinning lidars ([Ouster OS2-128](https://ouster.com/products/scanning-lidar/os2-sensor/), [Velodyne Puck (VLP-16)](https://velodynelidar.com/products/puck/), and [Velodyne Ultra Puck (VLP-32)](https://velodynelidar.com/products/ultra-puck/)), one camera ([Mako G-319](https://www.alliedvision.com/en/camera-selector/detail/mako/g-319/)), and one present weather sensor ([Vaisala FD-70](https://www.vaisala.com/en/products/weather-environmental-sensors/forward-scatter-fd70)). All data were synchronized, with the log start time indicated in the file name (HHMMSS). The data can be filtered by date, log time (HHMMSS), sensor, frame ID, and weather classification. These data were gathered statically at the Argonne Testbed for Multiscale Observational Science (ATMOS). Two target stop signs were placed in view of the sensors to contribute a target for comparing sensor data under different conditions. The weather data for each day are stored in netCDF “.nc” files. The lidar data contain the X, Y, Z, intensity, reflectivity, and ring from Ouster OS2-128 rev6, Velodyne VLP-16, and Velodyne VLP-32 lidars. ![raw lidar image](LiDAR_pointcloud_ATMOS.png)

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2022

Rock Physics-Based Data Assimilation of Integrated Continuous Active-Source Seismic and Pressure Monitoring Data during Geological Carbon Storage

Summary There has been substantial controversy concerning the role of geological carbon storage (GCS) in sequestering anthropogenic carbon emissions to mitigate climate change and global warming. Arguments center on the inability to monitor a geological storage site precisely and continuously, especially highlighting the associated costs and spatiotemporal trade-offs when using conventional subsurface monitoring techniques (well logs, core samples, chemical tracers, and 4D seismics). Active surveillance of GCS sites is essential for managing and mitigating potential leaks but is also required by regulation. With the goal of enhancing the monitoring capability at GCS sites, we present a rock physics-based joint data assimilation model to study a popular GCS site at Cranfield, Mississippi, USA. Synthetic continuous active-source seismic monitoring (CASSM) data (in the form of Vp and Qp measurements) and wellbore pressure monitoring data are assimilated with an ensemble of reservoir realizations to monitor gas saturation and reservoir pressure changes over a period of 100 years. Synthetic seismic attributes are generated using rock physics models (RPMs) and wellbore pressure monitoring data are extracted from the ground truth. Two assimilation methods, ensemble Kalman filter (EnKF) and ensemble Kalman smoother (EnKS), are tested in an observation system simulation experiment (OSSE) environment to assess the prediction accuracy of the individual and composite observation systems. The joint monitoring system achieves more accurate estimates of gas saturation and pressure, across the time span from start of injection to end of forecast, as compared to a single type of monitoring tool and irrespective of data assimilation algorithm choice. These results indicate that jointly assimilated data from two types of sensors (in this case, crosswell seismic and downhole pressure) may lead to a more risk-reducing monitoring design. One would expect that more data, vis-à-vis inclusion of a new sensor type, will improve the accuracy of any GCS monitoring system. However, from a practical standpoint, one important question is whether such a gain in accuracy is worth the additional cost associated with the new sensor. This paper focuses on quantifying the gain in accuracy, such that a practitioner can answer this question.

Engineering↗
DOE OSTI2022

DOE COVID-19 Data Curation Effort: Overview of Initial Data Collection Coverage (March - June 2020)

During the COVID-19 pandemic of 2020, major case reporting outlets quickly coalesced around two or three primary vendors. Johns Hopkins University and The New York Times were among the more prominent, and all were of great value to the nation, particularly during the uncertain early stages of the pandemic. They primarily focused on three major attributes: number of new cases, deaths, and recovery, but only at the state level. Recognizing that many states were reporting very detailed data sets (e.g., hospital beds) at a count level or finer, the ORNL Pandemic Modeling team embarked on a major data curation effort from March to June 2020 for the purpose of capturing this wealth of detailed data. The challenge of curating this data was daunting. The number of attributes reported by the states grew on almost on a weekly basis. States were routinely shifting their web tool strategies away from easily parsable HTML-based formatting to new Tableau and ArcGIS content. This growth in the sheer number of attributes combined with the unpredictable shifts in data format meant an aggressive and agile combination of automated scripting and manual scraping was required to capture new daily streams. To keep up, the team had to scale up staff and widen its approach for capture and storage. The DOE COVID-19 data collection effort resulted in over 11 million data points being collected, covering over 13,000 unique geographies and over 2,000 unique attributes that spanned predominantly from early March through the end of June 2020.

96 KNOWLEDGE MANAGEMENT AND PRESERVATION↗
DOE OSTI2023

An Approach to Data Management Planning for Protected Data Projects

This report describes what is required in a data management plan for data that needs to be protected in some fashion. Here we provide an overview of what a data manager should consider, including the data ingestion and various extract-transform-load processes, metadata considerations and documentation, to what might need to be accounted for in the event of data loss. In addition, this report includes two appendices: forms that, when filled out, make the user compliant with DOE data management requirements as well as additional requirements for handling protected data at ORNL.

96 KNOWLEDGE MANAGEMENT AND PRESERVATION↗
DOE OSTI2024

Where are the Data? Automating a Workflow for Carbon Storage Data Gap Analyses

This presentation demonstrates a spatial analysis workflow to assess data availability for the many components of geologic carbon storage technical viability. The workflow relies upon a knowledge-data framework that links the different components of GCS technical viability to the data types needed for evaluation. Using this contextual information, a combination of data science methods (e.g., natural language processing) and spatial analyses are applied to identify areas where sufficient data exists for a given component. The results are aggregated into maps illustrating data density and spatial gaps across all technical viability factors and data categories, as well as the individual component and category level for a more nuanced understanding. Presented at the FECM NETL Carbon Management Program Review Meeting 2024.

Creason, Christopher↗
DOE OSTI2024

Where are the Data? Automating a Workflow for Carbon Storage Data Gap Analyses

This presentation demonstrates a spatial analysis workflow to assess data availability for the many components of geologic carbon storage technical viability. The workflow relies upon a knowledge-data framework that links the different components of GCS technical viability to the data types needed for evaluation. Using this contextual information, a combination of data science methods (e.g., natural language processing) and spatial analyses are applied to identify areas where sufficient data exists for a given component. The results are aggregated into maps illustrating data density and spatial gaps across all technical viability factors and data categories, as well as the individual component and category level for a more nuanced understanding. Presented at the Geological Society of America Connects 2024 Annual Meeting in Anaheim, California, 22-25 September 2024.

Creason, Christopher↗
DOE OSTI2022

UAE6 - Wind Tunnel Tests Data - UAE6 - Sequence P - Raw Data

Sequence P: Wake Flow Visualization, Upwind (P) This test sequence used an upwind, rigid turbine with a 0° cone angle. The wind speed ranged from 5 m/s to 15 m/s. Yaw angles of 0° to –60° were achieved. The blade tip pitch was 3°. The rotor rotated at 72 RPM. Blade and probe pressure measurements were collected. The teeter dampers were replaced with rigid links, and these two channels were flagged as not applicable by setting the measured values in the data file to –99999.99 Nm. The teeter link load cell was pre-tensioned to 40,000 N. The aluminum blade tip designed to contain a smoke generator was installed, and counterweights were installed in the non-instrumented blade tip to compensate. The turbine was positioned at the appropriate yaw angle, and the smoke generator was ignited remotely. The campaign duration was 3 minutes for all tests except P1000000, which was 2 minutes. The file name convention was the standard format except for P10000A0, which indicated a 3° pitch angle. File P1000000 used a 12° pitch angle. After these two campaigns were collected, it was determined that all subsequent data should be collected with a 3° pitch angle. Pressure data were not acquired during this sequence, so all associated data values were flagged as not applicable by setting the measured values in the data file to 0.000 Pa. Corresponding pressure data are available from Sequence H for the 3° pitch angle test points. Flow visualization data obtained from wall- and ceiling-mounted video cameras were recorded to videotape. The camera locations and calibration procedures are described in Appendix J.

17 WIND ENERGY↗
DOE OSTI2020

APOGEE Data and Spectral Analysis from SDSS Data Release 16: Seven Years of Observations Including First Results from APOGEE-South

The spectral analysis and data products in Data Release 16 (DR16; 2019 December) from the high-resolution near-infrared Apache Point Observatory Galactic Evolution Experiment (APOGEE)-2/Sloan Digital Sky Survey (SDSS)-IV survey are described. Compared to the previous APOGEE data release (DR14; 2017 July), APOGEE DR16 includes about 200,000 new stellar spectra, of which 100,000 are from a new southern APOGEE instrument mounted on the 2.5 m du Pont telescope at Las Campanas Observatory in Chile. DR16 includes all data taken up to 2018 August, including data released in previous data releases. All of the data have been re-reduced and re-analyzed using the latest pipelines, resulting in a total of 473,307 spectra of 437,445 stars. Changes to the analysis methods for this release include, but are not limited to, the use of MARCS model atmospheres for calculation of the entire main grid of synthetic spectra used in the analysis, a new method for filling “holes” in the grids due to unconverged model atmospheres, and a new scheme for continuum normalization. Abundances of the neutron-capture element Ce are included for the first time. A new scheme for estimating uncertainties of the derived quantities using stars with multiple observations has been applied, and calibrated values of surface gravities for dwarf stars are now supplied. Compared to DR14, the radial velocities derived for this release more closely match those in the Gaia DR2 database, and a clear improvement in the spectral analysis of the coolest giants can be seen. The reduced spectra as well as the result of the analysis can be downloaded using links provided on the SDSS DR16 web page.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2021

The Atacama Cosmology Telescope: Summary of DR4 and DR5 Data Products and Data Access

Two recent large data releases for the Atacama Cosmology Telescope (ACT), called DR4 and DR5, are available for public access. These data include temperature and polarization maps that cover nearly half the sky at arcminute resolution in three frequency bands; lensing maps and component-separated maps covering ~ 2,100 deg 2 of sky; derived power spectra and cosmological likelihoods; a catalog of over 4,000 galaxy clusters; and supporting ancillary products including beam functions and masks. The data and products are described in a suite of ACT papers; here we provide a summary. In order to facilitate ease of access to these data we present a set of Jupyter IPython notebooks developed to introduce users to DR4, DR5, and the tools needed to analyze these data. The data products (excluding simulations) and the set of notebooks are publicly available on the NASA Legacy Archive for Microwave Background Data Analysis (LAMBDA); simulation products are available on the National Energy Research Scientific Computing Center (NERSC).

79 ASTRONOMY AND ASTROPHYSICS↗
NASA NTRS1974

The data array, a tool to interface the user to a large data base

Aspects of the processing of spacecraft data is considered. Use of the data array in a large address space as an intermediate form in data processing for a large scientific data base is advocated. Techniques for efficient indexing in data arrays are reviewed and the data array method for mapping an arbitrary structure onto linear address space is shown. A compromise between the two forms is given. The impact of the data array on the user interface are considered along with implementation.

Foster, G. H.↗
NASA NTRS1975

Data availability and the role of the earth resources observation systems data center

With the launch of LANDSAT-1 in July 1972, and the follow-on launch of LANDSAT-2 in January of this year, routine availability of satellite imagery and electronic data of the earth's resources has become a reality. Federal data centers provide LANDSAT data to resource managers and the general public. These data centers have to date provided almost 500,000 frames of LANDSAT data at a cost of more than $2,000,000. Data from the LANDSAT satellite program, along with data and information from the Skylab manned program, are available over any location to anyone for the cost of reproduction.

Watkins, A. H.↗
NASA NTRS1980

The role of World Data Centers and the Lunar and Planetary Institute in the international exchange of lunar and planetary data

The success of many lunar and planetary investigations has resulted in the accumulation of a mass of data in a myriad of formats and medias. The application of these data to comparative planetology, origin of the solar system, and potential industrial applications of space has made it necessary for scientists from many disciplines to have access to the data. The collections of these data are so diverse that it is often difficult to select what is needed based on catalog information alone. The Lunar and Planetary Institute (LPI) proposes to bring the user and the data together. As a research support organization operated by the Universities Space Research Association, the LPI through its active Visiting Scientist Program, a balanced program of study workshops and topical conferences, and organized and supervised data collections has assisted scientists, educators, and students to review, study, and obtain the data necessary to the pursuit of their research.

Waranius, F. B.↗
NASA NTRS1980

Compatibility study of the Magsat data and aeromagnetic data in the eastern Piedmont of US

Data from a 2 day period recorded by Magsat were used to produce world magnetic maps of the scalar total field and three vector component total fields. Subtracting the reference field of Magsat 6/80, a scalar anomalous field and three vector component anomalous fields were also mapped. After removing 718 bad points from the original data, every fifth point was picked for contouring. While the main geomagnetic field of the Earth is surprisingly well mapped considering the short data period, the anomaly maps suffer from data sparseness. The entire Magsat file collected at altitudes of 500-700 m in nonmountainous terrain and at 900-1,000 m in mountainous terrain was averaged to reduce the total data to 6,500 measurements, yielding a 0.1 deg sampling interval along the flight path. A U.S. aeromagnetic anomaly surface map was produced and the field was upward continued to a 300 km altitude. Differences in anomaly structure between the POGO data and the map produced were attributed to insufficient removal of the reference field. Reprocessing of the data using the GSFC reference field (9/80-2) should remove the low harmonic field and improve the anomalous field structure.

Won, I. J.↗
NASA NTRS1984

Data engineering systems: Computerized modeling and data bank capabilities for engineering analysis

The Data Engineering System (DES) is a computer-based system that organizes technical data and provides automated mechanisms for storage, retrieval, and engineering analysis. The DES combines the benefits of a structured data base system with automated links to large-scale analysis codes. While the DES provides the user with many of the capabilities of a computer-aided design (CAD) system, the systems are actually quite different in several respects. A typical CAD system emphasizes interactive graphics capabilities and organizes data in a manner that optimizes these graphics. On the other hand, the DES is a computer-aided engineering system intended for the engineer who must operationally understand an existing or planned design or who desires to carry out additional technical analysis based on a particular design. The DES emphasizes data retrieval in a form that not only provides the engineer access to search and display the data but also links the data automatically with the computer analysis codes.

Kopp, H.↗
NASA NTRS1984

RIM as the data base management system for a material properties data base

Relational Information Management (RIM) was selected as the data base management system for a prototype engineering materials data base. The data base provides a central repository for engineering material properties data, which facilitates their control. Numerous RIM capabilities are exploited to satisfy prototype data base requirements. Numerical, text, tabular, and graphical data and references are being stored for five material types. Data retrieval will be accomplished both interactively and through a FORTRAN interface. The experience gained in creating and exercising the prototype will be used in specifying requirements for a production system.

Karr, P. H.↗