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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 91 records · Page 5
All sourcesNASA NTRSDOE OSTI
NASA NTRS2005

Team X Spacecraft Instrument Database Consolidation

In the past decade, many changes have been made to Team X's process of designing each spacecraft, with the purpose of making the overall procedure more efficient over time. One such improvement is the use of information databases from previous missions, designs, and research. By referring to these databases, members of the design team can locate relevant instrument data and significantly reduce the total time they spend on each design. The files in these databases were stored in several different formats with various levels of accuracy. During the past 2 months, efforts have been made in an attempt to combine and organize these files. The main focus was in the Instruments department, where spacecraft subsystems are designed based on mission measurement requirements. A common database was developed for all instrument parameters using Microsoft Excel to minimize the time and confusion experienced when searching through files stored in several different formats and locations. By making this collection of information more organized, the files within them have become more easily searchable. Additionally, the new Excel database offers the option of importing its contents into a more efficient database management system in the future. This potential for expansion enables the database to grow and acquire more search features as needed.

Wallenstein, Kelly A.↗
NASA NTRS2007

Organization's Orderly Interest Exploration: Inception, Development and Insights of AIAA's Topics Database

Since 2003, AIAA's Computer Systems and Software Systems Technical Committees (TCs) have developed a database that aids technical committee management to map technical topics to their members. This Topics/Interest (T/I) database grew out of a collection of charts and spreadsheets maintained by the TCs. Since its inception, the tool has evolved into a multi-dimensional database whose dimensions include the importance, interest and expertise of TC members and whether or not a member and/or a TC is actively involved with the topic. In 2005, the database was expanded to include the TCs in AIAA s Information Systems Group and then expanded further to include all AIAA TCs. It was field tested at an AIAA Technical Activities Committee (TAC) Workshop in early 2006 through live access by over 80 users. Through the use of the topics database, TC and program committee (PC) members can accomplish relevant tasks such as: to identify topic experts (for Aerospace America articles or external contacts), to determine the interest of its members, to identify overlapping topics between diverse TCs and PCs, to guide new member drives and to reveal emerging topics. This paper will describe the origins, inception, initial development, field test and current version of the tool as well as elucidate the benefits and insights gained by using the database to aid the management of various TC functions. Suggestions will be provided to guide future development of the database for the purpose of providing dynamics and system level benefits to AIAA that currently do not exist in any technical organization.

Marshall, Jospeh R.↗
NASA NTRS2006

Database of Properties of Meteors

A database of properties of meteors, and software that provides access to the database, are being developed as a contribution to continuing efforts to model the characteristics of meteors with increasing accuracy. Such modeling is necessary for evaluation of the risk of penetration of spacecraft by meteors. For each meteor in the database, the record will include an identification, date and time, radiant properties, ballistic coefficient, radar cross section, size, density, and orbital elements. The property of primary interest in the present case is density, and one of the primary goals in this case is to derive densities of meteors from their atmospheric decelerations. The database and software are expected to be valid anywhere in the solar system. The database will incorporate new data plus results of meteoroid analyses that, heretofore, have not been readily available to the aerospace community. Taken together, the database and software constitute a model that is expected to provide improved estimates of densities and to result in improved risk analyses for interplanetary spacecraft. It is planned to distribute the database and software on a compact disk.

Suggs, Rob↗
NASA NTRS2011

Detailed Uncertainty Analysis of the Ares I A106 Liftoff/Transition Database

The Ares I A106 Liftoff/Transition Force and Moment Aerodynamics Database describes the aerodynamics of the Ares I Crew Launch Vehicle (CLV) from the moment of liftoff through the transition from high to low total angles of attack at low subsonic Mach numbers. The database includes uncertainty estimates that were developed using a detailed uncertainty quantification procedure. The Ares I Aerodynamics Panel developed both the database and the uncertainties from wind tunnel test data acquired in the NASA Langley Research Center s 14- by 22-Foot Subsonic Wind Tunnel Test 591 using a 1.75 percent scale model of the Ares I and the tower assembly. The uncertainty modeling contains three primary uncertainty sources: experimental uncertainty, database modeling uncertainty, and database query interpolation uncertainty. The final database and uncertainty model represent a significant improvement in the quality of the aerodynamic predictions for this regime of flight over the estimates previously used by the Ares Project. The maximum possible aerodynamic force pushing the vehicle towards the launch tower assembly in a dispersed case using this database saw a 40 percent reduction from the worst-case scenario in previously released data for Ares I.

Hanke, Jeremy L.↗
NASA NTRS2013

Application Program Interface for the Orion Aerodynamics Database

The Application Programming Interface (API) for the Crew Exploration Vehicle (CEV) Aerodynamic Database has been developed to provide the developers of software an easily implemented, fully self-contained method of accessing the CEV Aerodynamic Database for use in their analysis and simulation tools. The API is programmed in C and provides a series of functions to interact with the database, such as initialization, selecting various options, and calculating the aerodynamic data. No special functions (file read/write, table lookup) are required on the host system other than those included with a standard ANSI C installation. It reads one or more files of aero data tables. Previous releases of aerodynamic databases for space vehicles have only included data tables and a document of the algorithm and equations to combine them for the total aerodynamic forces and moments. This process required each software tool to have a unique implementation of the database code. Errors or omissions in the documentation, or errors in the implementation, led to a lengthy and burdensome process of having to debug each instance of the code. Additionally, input file formats differ for each space vehicle simulation tool, requiring the aero database tables to be reformatted to meet the tool s input file structure requirements. Finally, the capabilities for built-in table lookup routines vary for each simulation tool. Implementation of a new database may require an update to and verification of the table lookup routines. This may be required if the number of dimensions of a data table exceeds the capability of the simulation tools built-in lookup routines. A single software solution was created to provide an aerodynamics software model that could be integrated into other simulation and analysis tools. The highly complex Orion aerodynamics model can then be quickly included in a wide variety of tools. The API code is written in ANSI C for ease of portability to a wide variety of systems. The input data files are in standard formatted ASCII, also for improved portability. The API contains its own implementation of multidimensional table reading and lookup routines. The same aerodynamics input file can be used without modification on all implementations. The turnaround time from aerodynamics model release to a working implementation is significantly reduced

Robinson, Philip E.↗
NASA NTRS2014

Building a Database for a Quantitative Model

A database can greatly benefit a quantitative analysis. The defining characteristic of a quantitative risk, or reliability, model is the use of failure estimate data. Models can easily contain a thousand Basic Events, relying on hundreds of individual data sources. Obviously, entering so much data by hand will eventually lead to errors. Not so obviously entering data this way does not aid linking the Basic Events to the data sources. The best way to organize large amounts of data on a computer is with a database. But a model does not require a large, enterprise-level database with dedicated developers and administrators. A database built in Excel can be quite sufficient. A simple spreadsheet database can link every Basic Event to the individual data source selected for them. This database can also contain the manipulations appropriate for how the data is used in the model. These manipulations include stressing factors based on use and maintenance cycles, dormancy, unique failure modes, the modeling of multiple items as a single "Super component" Basic Event, and Bayesian Updating based on flight and testing experience. A simple, unique metadata field in both the model and database provides a link from any Basic Event in the model to its data source and all relevant calculations. The credibility for the entire model often rests on the credibility and traceability of the data.

Kahn, C. Joseph↗
NASA NTRS2018

Building a QC Database of Meteorological Data from NASA KSC and the United States Air Force's Eastern Range

The National Aeronautics and Space Administration's (NASA) Marshall Space Flight Center (MSFC) Natural Environments Branch (EV44) provides atmospheric databases and analysis in support of space vehicle design and day-of-launch operations for NASA and commercial launch vehicle programs launching from the NASA Kennedy Space Center (KSC), co-located on the United States Air Force's Eastern Range (ER) at the Cape Canaveral Air Force Station. The ER complex is one of the most heavily instrumented sites in the United States with over 31 towers measuring various atmospheric parameters on a continuous basis. An inherent challenge with large datasets consists of ensuring erroneous data are removed from databases, and thus excluded from launch vehicle design analyses. EV44 has put forth great effort in developing quality control (QC) procedures for individual meteorological instruments, however no standard QC procedures for all databases currently exists resulting in QC databases that have inconsistencies in variables, development methodologies, and periods of record. The goal of this activity is to use the previous efforts to develop a standardized set of QC procedures from which to build meteorological databases from KSC and the ER, while maintaining open communication with end users from the launch community to develop ways to improve, adapt and grow the QC database. Details of the QC procedures will be described. As the rate of launches increases with additional launch vehicle programs, It is becoming more important that weather databases are continually updated and checked for data quality before use in launch vehicle design and certification analyses.

Brenton, J. C.↗
NASA NTRS2018

Building a Quality Controlled Database of Meteorological Data from NASA Kennedy Space Center and the United States Air Force's Eastern Range

The National Aeronautics and Space Administration's (NASA) Marshall Space Flight Center (MSFC) Natural Environments Branch (EV44) has provided atmospheric databases and analysis in support of space vehicle design and day-of-launch operations for NASA and commercial launch vehicle programs launching from the NASA Kennedy Space Center (KSC), co-located on the United States Air Force's Eastern Range (ER) at the Cape Canaveral Air Force Station. The ER complex is one of the most heavily instrumented sites in the United States with over 31 towers measuring various atmospheric parameters on a continuous basis. An inherent challenge with large sets of data consists of ensuring erroneous data is removed from databases, and thus excluded from launch vehicle design analyses. EV44 has put forth great effort in developing quality control (QC) procedures for individual meteorological instruments, however no standard QC procedures for all databases currently exists resulting in QC databases that have inconsistencies in variables, methodologies, and periods of record. The goal of this activity is to use the previous efforts by EV44 to develop a standardized set of QC procedures from which to build meteorological databases from KSC and the ER, while maintaining open communication with end users from the launch community to develop ways to improve, adapt and grow the QC database. Details of the QC procedures will be described. As the rate of launches increases with additional launch vehicle programs, it is becoming more important that weather databases are continually updated and checked for data quality before use in launch vehicle design and certification analyses.

Brenton, James C.↗
DOE OSTI2022

SERDP PFAS Database

The PNNL-PFAS database was constructed to provide quantitative infrared spectra of per- and polyfluoroalkyl substances (PFAS) in the gas phase. These fluorine-rich, organic compounds have been used as non-flammable solvents, cleaning agents, and in the manufacture of a diverse variety of consumer products. Due to their widespread use and relative inertness, PFAS have accumulated in the natural environment, and exposure to these chemicals may be linked to harmful health effects. Development of methods for detecting and remediating PFAS contamination are thus active areas of research. This database supports PFAS investigations where gas-phase infrared signatures may be measured (e.g., during treatment by thermal decomposition). The database currently contains infrared spectra for 15 compounds; these were selected based on the potential of these compounds being thermal degradation products of the manufactured chemicals mentioned above. • Additional compounds will be added to the database in the future. • Additional information about the database may be obtained from [link to future paper about the PFAS database].

PFAS, infrared(IR)spectroscopy, DATABASE, FTIR, sp↗
NASA NTRSDate not supplied

PALMO: An OVERFLOW Machine Learning Airfoil Performance Database

The OVERFLOW Machine Learning Airfoil Performance (PALMO) database has been created to enable robust modeling of airfoil performance in a variety of applications. The PALMO database uses OVERFLOW simulation data second-order accurate in time and fourth-order accurate in space with Spalart-Allmaras turbulence closure. The foundation of the in-development PALMO database is the airfoil base cube. Each base cube includes simulation data parametrized over a range of Mach numbers, Reynolds numbers, and angles-of-attack. This database includes the NACA 4-series airfoils, with parametrization in airfoil thickness and camber from an NACA 0006 to an NACA 4424. In total, 52,480 NACA 4-series OVERFLOW calculations were run on the NASA High-End Compute Capability (HECC) supercomputer. This provides high-order-accurate simulation data covering a wide range of aerospace design applications, which enables users to develop accurate airfoil performance look-up tables without additional high-performance computing. In addition to engineering design and analysis of aerospace vehicles, PALMO is well suited to be a benchmark dataset for the development and testing of machine learning methods in aerospace engineering. This work presents an example PALMO surrogate model that enables accurate airfoil performance predictions for any arbitrary combination of camber, thickness, Mach number, Reynolds number, and angle of attack within the bounds of the database. Airfoil performance tables predicted for an airfoil not used in training the model are used in three-dimensional OVERFLOW simulations to quantify the downstream accuracy on aggregate rotor performance metrics. For the NACA 3415 airfoil, which had no common thickness or camber with the training data, the surrogate predicted and CFD generated tables were within 2.1% of each other in the forward flight lift to drag metric. This suggests that performance tables generated for airfoils within the bounds of the PALMO database will yield aggregate rotor performance predictions on par with tables generated from directly running OVERFLOW airfoil calculations. The PALMO airfoil performance coefficients are available publicly.

Database↗
DOE OSTI2024

A new database of building-space-specific internal loads and load schedules for performance based code compliance modeling of commercial buildings

Building-level loads and load profiles prescribed by current modeling rules save modelers time and avoid gaming during whole building performance modeling. However, recent studies show that they sometimes insufficiently capture the entire building performance due to the varied loads and load profiles for different space types. As a solution to this issue, this paper develops a database of building-space-specific loads and load profiles used in code compliance modeling. The existing sets of loads and load profiles are reviewed and the challenges behind using them for specific research topics are discussed. Then, the proposed method to develop the building-space-specific loads and load profiles is introduced. After that, the database for these building-space-specific loads and load profiles is presented. In addition, one case is studied to demonstrate the applications of these loads and load profiles. In this case study, three methods are used to develop building energy models: space-specific (using knowledge of the distribution and location of space types and applying the space-specific data in the developed database), building-level (assuming a lack of knowledge of the space types and using the building-level data in the developed database), and calculated-ratio (assuming knowledge of the distribution of space types but not their locations and calculating weighted average values based on the space-specific data in the developed database). Finally, the energy results simulated by using these three methods are compared, which show building-level methods can produce energy results up to 20% different than the space-specific methods. Finally, this paper discusses the application scope and maintenance of this new database.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2022

Auto-generating databases of Yield Strength and Grain Size using ChemDataExtractor

Abstract The emerging field of material-based data science requires information-rich databases to generate useful results which are currently sparse in the stress engineering domain. To this end, this study uses the’materials-aware’ text-mining toolkit, ChemDataExtractor, to auto-generate databases of yield-strength and grain-size values by extracting such information from the literature. The precision of the extracted data is 83.0% for yield strength and 78.8% for grain size. The automatically-extracted data were organised into four databases: a Yield Strength, Grain Size, Engineering-Ready Yield Strength and Combined database. For further validation of the databases, the Combined database was used to plot the Hall-Petch relationship for, the alloy, AZ31, and similar results to the literature were found, demonstrating how one can make use of these automatically-extracted datasets.

36 MATERIALS SCIENCE↗
DOE OSTI2022

A Global Building Occupant Behavior Database

This paper introduces a database of 34 field-measured building occupant behavior datasets collected from 15 countries and 39 institutions across 10 climatic zones covering various building types in both commercial and residential sectors. This is a comprehensive global database about building occupant behavior. The database includes occupancy patterns (i.e., presence and people count) and occupant behaviors (i.e., interactions with devices, equipment, and technical systems in buildings). Brick schema models were developed to represent sensor and room metadata information. The database is publicly available, and a website was created for the public to access, query, and download specific datasets or the whole database interactively. The database can help to advance the knowledge and understanding of realistic occupancy patterns and human-building interactions with building systems (e.g., light switching, set-point changes on thermostats, fans on/off, etc.) and envelopes (e.g., window opening/closing). With these more realistic inputs of occupants’ schedules and their interactions with buildings and systems, building designers, energy modelers, and consultants can improve the accuracy of building energy simulation and building load forecasting.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2024

A database of thermally activated delayed fluorescent molecules auto-generated from scientific literature with ChemDataExtractor

A database of thermally activated delayed fluorescent (TADF) molecules was automatically generated from the scientific literature. It consists of 25,482 data records with an overall precision of 82%. Among these, 5,349 records have chemical names in the form of SMILES strings which are represented with 91% accuracy; these are grouped in a subsidiary database. Each data record contains one of the following four properties: maximum emission wavelength (λ EM ), photoluminescence quantum yield (PLQY), singlet-triplet energy splitting (ΔE ST ), and delayed lifetime (τ D ). The databases were created through text mining using ChemDataExtractor, a chemistry-aware natural-language-processing toolkit, which has been adapted for TADF research. The text-mined corpus consisted of 2,733 papers from the Royal Society of Chemistry and Elsevier. To the best of our knowledge, these databases are the first databases that have been auto-generated for TADF molecules from existing publications. The databases have been publicly released for experimental and computational applications in the TADF research field.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2024

A Database of Stress-Strain Properties Auto-generated from the Scientific Literature using ChemDataExtractor

Abstract There has been an ongoing need for information-rich databases in the mechanical-engineering domain to aid in data-driven materials science. To address the lack of suitable property databases, this study employs the latest version of the chemistry-aware natural-language-processing (NLP) toolkit, ChemDataExtractor, to automatically curate a comprehensive materials database of key stress-strain properties. The database contains information about materials and their cognate properties: ultimate tensile strength, yield strength, fracture strength, Young’s modulus, and ductility values. 720,308 data records were extracted from the scientific literature and organized into machine-readable databases formats. The extracted data have an overall precision, recall and F-score of 82.03%, 92.13% and 86.79%, respectively. The resulting database has been made publicly available, aiming to facilitate data-driven research and accelerate advancements within the mechanical-engineering domain.

Kumar, Pankaj↗
DOE OSTI2022

EXFOR-NSR PDF database: a system for nuclear knowledge preservation and data curation

Current needs of nuclear science and technology include complete, well-documented, and easily verifiable nuclear data. The complete data records require supporting nuclear bibliography, presently stored in dedicated libraries, in addition, to actual data. Additionally, experimental nuclear reaction data (EXFOR) and Nuclear Science References (NSR) databases contain compilations based on primary (journals) and secondary (conference proceedings, theses, preprints, etc.) publications, and data received from authors via private communications. The secondary library materials and private communications often represent a bottleneck for nuclear data verification, compilation, evaluation, and dissemination activities. To address this issue, bibliographic materials were scanned into PDF (Portable Document Format) files and uploaded in a relational database. The traditional scope of nuclear databases that includes meta-data and numbers derived from data in specialized formats was broadened to accommodate the large volumes of original nuclear data publications. The complete PDF publication files were stored in a relational database as Binary Large OBjects (BLOB). This unique collection of nuclear data compilations and supporting publications generate many opportunities for machine learning applications. The Web interfaces for authorized and public access to the EXFOR-NSR nuclear publications database were implemented at the U.S. National Nuclear Data Center, https://www.nndc.bnl.gov/ and IAEA Nuclear Data Section, https://www-nds.iaea.org/ . The current system is complementary to major nuclear libraries and narrowly focused on nuclear data compilation and evaluation procedures. The contents of the PDF database, details of implementation, and Web interface are described. New capabilities for data curation, knowledge preservation, worldwide dissemination, and natural language processing (NLP) applications are given.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2026

Database of virus genomes from ultra-deep sequencing of wastewater

Researchers at University of Missouri have conducted ultra-deep RNA sequencing of viral concentrates from wastewater (1 billion Illumina reads per sample). The resulting dataset spans 321 samples collected weekly from 11 cities between 2023-2025. As part of a tri-lab collaboration, scientists at LLNL and LANL cleaned, assembled, and annotated this metagenomic data, identifying nearly 200,000 viral genomes. Careful data curation resulted in a database containing 21,015 high-quality, near-complete viral genomes from wastewater. This database contains viruses predicted to infect a range of hosts including bacteria (most common viruses), plants (most abundant viruses), and vertebrates (rarest viruses). There are also numerous novel viruses that could not be well identified and whose host(s) are unknown. Just 7% of all genomes in the wastewater virus database had genus-level matches in the public NCBI database, and 17% matched to a recently created metagenomic virus database at that level (metaVR). The database will provide baseline information about viruses in wastewater that may be used to additional identify novel viruses during ongoing monitoring

Allen, Jonathan [Lawrence Livermore National Labor↗
DOE OSTI2020

Carbon Storage Open Database

The Carbon Storage Open Database is a collection of spatial data obtained from publicly available sources published by several NATCARB Partnerships and other organizations. The carbon storage open database was collected from open-source data on ArcREST servers and websites in 2018, 2019, 2021, and 2022. The original database was published on the former GeoCube, which is now EDX Spatial, in July 2020, and has since been updated with additional data resources from the Energy Data eXchange (EDX) and external public data resources. The shapefile geodatabase is available in total, and has also been split up into multiple databases based on the maps produced for EDX spatial. These are topical map categories that describe the type of data, and sometimes the region for which the data relates. The data is separated in case there is only a specific area or data type that is of interest for download. In addition to the geodatabases, this submission contains: 1. A ReadMe file describing the processing steps completed to collect and curate the data. 2. A data catalog of all feature layers within the database. Additional published resources are available that describe the work done to produce the geodatabase: Morkner, P., Bauer, J., Creason, C., Sabbatino, M., Wingo, P., Greenburg, R., Walker, S., Yeates, D., Rose, K. 2022. Distilling Data to Drive Carbon Storage Insights. Computers & Geosciences. https://doi.org/10.1016/j.cageo.2021.104945 Morkner, P., Bauer, J., Shay, J., Sabbatino, M., and Rose, K. An Updated Carbon Storage Open Database - Geospatial Data Aggregation to Support Scaling -Up Carbon Capture and Storage. United States: N. p., 2022. Web. https://www.osti.gov/biblio/1890730 Morkner, P., Rose, K., Bauer, J., Rowan, C., Barkhurst, A., Baker, D.V., Sabbatino, M., Bean, A., Creason, C.G., Wingo, P., and Greenburg, R. Tools for Data Collection, Curation, and Discovery to Support Carbon Sequestration Insights. United States: N. p., 2020. Web. https://www.osti.gov/biblio/1777195 Disclaimer: This project was funded by the United States Department of Energy, National Energy Technology Laboratory, in part, through a site support contract. Neither the United States Government nor any agency thereof, nor any of their employees, nor the support contractor, nor any of their employees, makes any warranty, express or implied, or assumes any legal liability or responsibility for the accuracy, completeness, or usefulness of any information, apparatus, product, or process disclosed, or represents that its use would not infringe privately owned rights. Reference herein to any specific commercial product, process, or service by trade name, trademark, manufacturer, or otherwise does not necessarily constitute or imply its endorsement, recommendation, or favoring by the United States Government or any agency thereof. The views and opinions of authors expressed herein do not necessarily state or reflect those of the United States Government or any agency thereof.

carbon storage↗