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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 289 records · Page 16
All sourcesNASA NTRSDOE OSTI
DOE OSTI2024

Catalyzing deep decarbonization with federated battery diagnosis and prognosis for better data management in energy storage systems

Industrial data analytics methods play a central role in improving energy storage performance and efficiency, impacting the future of electrified transportation and renewable electricity generation. However, significant challenges hinder the large-scale deployment of batteries. Conventional methods rely on centralized collection and processing of fleet-level data, leading to database size issues and privacy concerns due to potential data breaches. To enable scalable deployment of battery management systems, this article proposes a federated battery diagnosis and prognosis model, which distributes the processing of battery standard current-voltage-time-usage data in a privacy-preserving manner. Instead of transferring the raw data, this approach communicates only the locally processed parameters, thus reducing communication load and preserving data confidentiality. The federated model offers a paradigm shift in battery health management through privacy-preserving distributed methods for battery data processing and lifetime prediction, ensuring the reliable and sustainable deployment of lithium-ion batteries in a rapidly evolving world.

asset health management↗
NASA NTRS1976

A synthetic aperture processor using CCD signal processing techniques

Synthetic aperture radar (SAR) imaging was the most suitable technique for achieving high resolution imagery through atmospheric cloud cover. This feature was important for planetary as well as earth orbiting satellite systems, and for military aircraft applications. Such applications require onboard data processing or wide-band data transmission systems in order to handle the large amounts of raw data produced by such systems. A number of techniques were utilized in implementing SAR processors. Frequency filtering and Fourier transform operations using both optical and digital techniques were utilized in SAR processing.

Bailey, W. H.↗
NASA NTRS1984

Materials properties data base computerization

Material property data plays a key role in the design of jet engine components. Consistency, accuracy and efficient use of material property data is of prime importance to the engineering community. The system conception, development, implementation, and future plans for computer software that captures the Material Properties Handbook into a scientific data base are described. The engineering community is given access to raw data and property curves, display of multiple curves for material evaluation and selection, direct access by design analysis computer programs, display of the material specification, and a historical repository for the material evolution. The impact of this activity includes significant productivity gains and cost reductions; all users have access to the same information nd provides consistent, rapid response to the needs of the engineering community. Future plans include incorporating the materials properties data base into a network environment to access information from other data bases and download information to engineering work stations.

Baur, R. G.↗
NASA NTRS1992

The Airborne Ocean Color Imager - System description and image processing

The Airborne Ocean Color Imager was developed as an aircraft instrument to simulate the spectral and radiometric characteristics of the next generation of satellite ocean color instrumentation. Data processing programs have been developed as extensions of the Coastal Zone Color Scanner algorithms for atmospheric correction and bio-optical output products. The latter include several bio-optical algorithms for estimating phytoplankton pigment concentration, as well as one for the diffuse attenuation coefficient of the water. Additional programs have been developed to geolocate these products and remap them into a georeferenced data base, using data from the aircraft's inertial navigation system. Examples illustrate the sequential data products generated by the processing system, using data from flightlines near the mouth of the Mississippi River: from raw data to atmospherically corrected data, to bio-optical data, to geolocated data, and, finally, to georeferenced data.

Wrigley, Robert C.↗
NASA NTRS1994

Recalculated values of the total ozone amount over Oslo, 60 deg N, for the period 1979-1992

The total ozone amount over Oslo has been measured with the Dobson spectrophotometer No 56. The instrument was modified, calibrated, and intercompared in 1977 in Boulder. A new intercomparison was made in 1986 in Arosa. Much work has been done to make the zenith charts reliable. A new method has been introduced where one takes into account the change in the shape of the zenith chart curves which is caused by a change of the ozone profile when the ozone amount changes. According to the conclusion derived from the intercomparison in Arosa 1986, the instrument has not been stable. The R-N tables had to be altered, but not the Q-tables. We have tried to account for this change in our handling of the observation data. No statistical analyses of these data has yet been made, but the monthly averages of the raw data show a negative linear trend of about 4 percent for the whole period.

Larsen, Soren H. H.↗
NASA NTRS1999

Quantification of Operational Risk Using A Data Mining

What is Data Mining? - Data Mining is the process of finding actionable information hidden in raw data. - Data Mining helps find hidden patterns, trends, and important relationships often buried in a sea of data - Typically, automated software tools based on advanced statistical analysis and data modeling technology can be utilized to automate the data mining process

Perera, J. Sebastian↗
NASA NTRS2004

Safety Aboard the International Space Station

As with any task that NASA takes on, safety is of utmost importaqce. There are pages of safety codes and procedures that must be followed before any idea can be brought to life. Unfortunately, the International Space Station s (ISS) safety regulations and procedures are based on lg standards rather than on Og. To aide in making this space age home away from home a less hazardous environment, I worked on several projects revolving around the dangers of flammable items in microgravity. The first task I was assigned was to track flames. This involves turning eight millimeter video recordings, of tests run in the five second drop tower, into avi format on the computer. The footage is then compressed and altered so that the flame can be seen more clearly. Using another program called Spotlight, line profiles were used to collect data describing the luminescence of the flame at different points. These raw data are saved as text files and run trough a macro so that a Matlab program can analyze it. By fitting the data to a curve and determining the areas of brightest luminescence, the behavior of the flame can be recorded numerically. After entering the data into a database, researchers can come back later and easily get information on flames resulting from different gas and liquid mixtures in microgravity. I also worked on phase two of the FATE project, which deals with safety aboard the ISS. This phase involves igniting projected droplets and determining how they react with secondary materials. Such simulations represent, on a small scale, the spread of onboard fires due to the effervescence of burning primary materials. I set up existing hardware to operate these experiments and ran tests with it, photographing the results. I also made CAD drawings of the apparatus and the area available on the (SF)2 rig for it to fit into. The experiment will later be performed on the KC-135, and the results gathered will be used to reanalyze current safety standards for the ISS, including the distance of required separation for flammable materials. Additional information is included in the original extended abstract.

Mintz, Shauna M.↗
NASA NTRS2005

NASA Earth Observations (NEO): Data Access for Informal Education and Outreach

The NEO (NASA Earth Observations) web space is currently under development with the goal of significantly increasing the demand for NASA remote sensing data while dramatically simplifying public access to georeferenced images. NEO will target the unsophisticated, nontraditional data users who are currently underserved by the existing data ordering systems. These users will include formal and informal educators, museum and science center personnel, professional communicators, and citizen scientists and amateur Earth observers. Users will be able to view and manipulate georeferenced browse imagery and, if they desire, download directly or order the source HDF data from the data provider (e.g., NASA DAAC or science team) via a single, integrated interface. NE0 will accomplish this goal by anticipating users expectations and knowledge level, thus providing an interface that presents material to users in a more simplified manner, without relying upon the jargon/technical terminology that make even the identification of the appropriate data set a significant hurdle. NEO will also act as a gateway that manages users expectations by providing specific details about images and data formats, developing tutorials regarding the manipulation of georeferenced imagery and raw data, links to software tools and ensuring that users are able to get the image they want in the format they want as easily as possible.

Ward, Kevin↗
NASA NTRS2017

Engine Icing Data - An Analytics Approach

Engine icing researchers at the NASA Glenn Research Center use the Escort data acquisition system in the Propulsion Systems Laboratory (PSL) to generate and collect a tremendous amount of data every day. Currently these researchers spend countless hours processing and formatting their data, selecting important variables, and plotting relationships between variables, all by hand, generally analyzing data in a spreadsheet-style program (such as Microsoft Excel). Though spreadsheet-style analysis is familiar and intuitive to many, processing data in spreadsheets is often unreproducible and small mistakes are easily overlooked. Spreadsheet-style analysis is also time inefficient. The same formatting, processing, and plotting procedure has to be repeated for every dataset, which leads to researchers performing the same tedious data munging process over and over instead of making discoveries within their data. This paper documents a data analysis tool written in Python hosted in a Jupyter notebook that vastly simplifies the analysis process. From the file path of any folder containing time series datasets, this tool batch loads every dataset in the folder, processes the datasets in parallel, and ingests them into a widget where users can search for and interactively plot subsets of columns in a number of ways with a click of a button, easily and intuitively comparing their data and discovering interesting dynamics. Furthermore, comparing variables across data sets and integrating video data (while extremely difficult with spreadsheet-style programs) is quite simplified in this tool. This tool has also gathered interest outside the engine icing branch, and will be used by researchers across NASA Glenn Research Center. This project exemplifies the enormous benefit of automating data processing, analysis, and visualization, and will help researchers move from raw data to insight in a much smaller time frame.

Engine Icing↗
DOE OSTI2024

An R Shiny graphical user interface for analyzing, visualizing, and interpreting high precision mass spectrometric data

There is currently a lack of software that meets the needs for the analysis of raw data produced by modern isotope ratio mass spectrometers for both R&D and routine use at SRNL and other US national labs • Needs to accommodate multiple isotope systems, instruments, and manufacturers • Include modern statistical methods and handling/visualization of uncertainty • Flexible software with transparent (no “black box”) and reproducible methods • This project is inspired by existing discipline-specific data analysis software (e.g., Tripoli1 , ET_Redux2 , IsoplotR3) used in the geochemical community • Our goal is to build an open source data analysis software package that focuses on flexibility, transparency, and reproducibility

Labone, Elizabeth↗
NASA NTRSDate not supplied

MISR Level 1A CCD Science data, all cameras (MIL1A_V1)

The Level 1A data are raw MISR data that are decommutated, reformatted 12-bit Level 0 data shifted to byte boundaries, i.e., reversal of square-root encoding applied and converted to 16 bit, and annotated (e.g., with time information). These data are used by the Level 1B1 processing algorithm to generate calibrated radiances. The science data output preserves the spatial sampling rate of the Level 0 raw MISR CCD science data. CCD data are collected during routine science observations of the sunlit portion of the Earth. Each product represents one 'granule' of data. A 'granule' is defined to be the smallest unit of data required for MISR processing. Also, included in the Level 1A product are pointers to calibration coefficient files provided for Level 1B processing. [Location=GLOBAL] [Temporal_Coverage: Start_Date=2000-02-24; Stop_Date=] [Spatial_Coverage: Southernmost_Latitude=-90; Northernmost_Latitude=90; Westernmost_Longitude=-180; Easternmost_Longitude=180].

CCD↗
NASA NTRSDate not supplied

MISR Level 1A CCD Science data, all cameras (MIL1A_V2)

The Level 1A data are raw MISR data that are decommutated, reformatted 12-bit Level 0 data shifted to byte boundaries, i.e., reversal of square-root encoding applied and converted to 16 bit, and annotated (e.g., with time information). These data are used by the Level 1B1 processing algorithm to generate calibrated radiances. The science data output preserves the spatial sampling rate of the Level 0 raw MISR CCD science data. CCD data are collected during routine science observations of the sunlit portion of the Earth. Each product represents one 'granule' of data. A 'granule' is defined to be the smallest unit of data required for MISR processing. Also, included in the Level 1A product are pointers to calibration coefficient files provided for Level 1B processing. [Location=GLOBAL] [Temporal_Coverage: Start_Date=2000-02-24; Stop_Date=] [Spatial_Coverage: Southernmost_Latitude=-90; Northernmost_Latitude=90; Westernmost_Longitude=-180; Easternmost_Longitude=180].

AM-1↗
DOE OSTI2025

An R shiny graphical user interface for highprecision mass spectrometric data analysis

• There is currently a lack of software that meets the needs for the analysis of raw data produced by modern isotope ratio mass spectrometers for both R&D and routine use at SRNL and other US national labs • Needs to accommodate multiple isotope systems, instruments, and manufacturers • Include modern statistical methods and handling/visualization of uncertainty • Flexible software with transparent (no “black box”) and reproducible methods • This project is inspired by existing discipline-specific data analysis software (e.g., Tripoli1 , ET_Redux2, IsoplotR3) used in the geochemical community • Our goal is to build an open source data analysis software package that focuses on flexibility, transparency, and reproducibility

LABONE, ELIZABETH↗
NASA NTRS1974

Operators manual for the magnetograph program (section 2)

This manual for use of the magnetograph program describes: (1) black box use of the programs; (2) the magtape data formats used; (3) the adjustable control parameters in the program; and (4) the algorithms. With no adjustments on the control parameters this program may be used purely as a black box. For optimal use, however, the control parameters may be varied. The magtape data formats are of use in adopting other programs to look at raw data or final magnetograph data.

November, L.↗
NASA NTRS1985

Integrated Exhaust-Gas-Analysis System

Gas-Analysis system includes eight commercial gas analyzers and data-processing and calibration electronics. Two microprocessors range analyzers, calibrate system, process raw data to units of concentration, and make all system information available to facility research computer and to operator. After initial setup, system operates several hours without significant operator attention. Saves considerable operator time.

Anderson, R.↗
NASA NTRS1984

Spatial variation analyses of Thematic Mapper data for the identification of linear features in agricultural landscapes

A need exists for digitized information pertaining to linear features such as roads, streams, water bodies and agricultural field boundaries as component parts of a data base. For many areas where this data may not yet exist or is in need of updating, these features may be extracted from remotely sensed digital data. This paper examines two approaches for identifying linear features, one utilizing raw data and the other classified data. Each approach uses a series of data enhancement procedures including derivation of standard deviation values, principal component analysis and filtering procedures using a high-pass window matrix. Just as certain bands better classify different land covers, so too do these bands exhibit high spectral contrast by which boundaries between land covers can be delineated. A few applications for this kind of data are briefly discussed, including its potential in a Universal Soil Loss Equation Model.

Pelletier, R. E.↗