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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 NTRS1994

Assessment of the SFC database for analysis and modeling

SFC is one of the four clusters that make up the Integrated Work Control System (IWCS), which will integrate the shuttle processing databases at Kennedy Space Center (KSC). The IWCS framework will enable communication among the four clusters and add new data collection protocols. The Shop Floor Control (SFC) module has been operational for two and a half years; however, at this stage, automatic links to the other 3 modules have not been implemented yet, except for a partial link to IOS (CASPR). SFC revolves around a DB/2 database with PFORMS acting as the database management system (DBMS). PFORMS is an off-the-shelf DB/2 application that provides a set of data entry screens and query forms. The main dynamic entity in the SFC and IOS database is a task; thus, the physical storage location and update privileges are driven by the status of the WAD. As we explored the SFC values, we realized that there was much to do before actually engaging in continuous analysis of the SFC data. Half way into this effort, it was realized that full scale analysis would have to be a future third phase of this effort. So, we concentrated on getting to know the contents of the database, and in establishing an initial set of tools to start the continuous analysis process. Specifically, we set out to: (1) provide specific procedures for statistical models, so as to enhance the TP-OAO office analysis and modeling capabilities; (2) design a data exchange interface; (3) prototype the interface to provide inputs to SCRAM; and (4) design a modeling database. These objectives were set with the expectation that, if met, they would provide former TP-OAO engineers with tools that would help them demonstrate the importance of process-based analyses. The latter, in return, will help them obtain the cooperation of various organizations in charting out their individual processes.

Centeno, Martha A.↗
NASA NTRS1996

Database of Mechanical Properties of Textile Composites

This report describes the approach followed to develop a database for mechanical properties of textile composites. The data in this database is assembled from NASA Advanced Composites Technology (ACT) programs and from data in the public domain. This database meets the data documentation requirements of MIL-HDBK-17, Section 8.1.2, which describes in detail the type and amount of information needed to completely document composite material properties. The database focuses on mechanical properties of textile composite. Properties are available for a range of parameters such as direction, fiber architecture, materials, environmental condition, and failure mode. The composite materials in the database contain innovative textile architectures such as the braided, woven, and knitted materials evaluated under the NASA ACT programs. In summary, the database contains results for approximately 3500 coupon level tests, for ten different fiber/resin combinations, and seven different textile architectures. It also includes a limited amount of prepreg tape composites data from ACT programs where side-by-side comparisons were made.

Delbrey, Jerry↗
NASA NTRS1997

"TPSX: Thermal Protection System Expert and Material Property Database"

The Thermal Protection Branch at NASA Ames Research Center has developed a computer program for storing, organizing, and accessing information about thermal protection materials. The program, called Thermal Protection Systems Expert and Material Property Database, or TPSX, is available for the Microsoft Windows operating system. An "on-line" version is also accessible on the World Wide Web. TPSX is designed to be a high-quality source for TPS material properties presented in a convenient, easily accessible form for use by engineers and researchers in the field of high-speed vehicle design. Data can be displayed and printed in several formats. An information window displays a brief description of the material with properties at standard pressure and temperature. A spread sheet window displays complete, detailed property information. Properties which are a function of temperature and/or pressure can be displayed as graphs. In any display the data can be converted from English to SI units with the click of a button. Two material databases included with TPSX are: 1) materials used and/or developed by the Thermal Protection Branch at NASA Ames Research Center, and 2) a database compiled by NASA Johnson Space Center 9JSC). The Ames database contains over 60 advanced TPS materials including flexible blankets, rigid ceramic tiles, and ultra-high temperature ceramics. The JSC database contains over 130 insulative and structural materials. The Ames database is periodically updated and expanded as required to include newly developed materials and material property refinements.

Squire, Thomas H.↗
NASA NTRS2002

Database Reports Over the Internet

Most of the summer was spent developing software that would permit existing test report forms to be printed over the web on a printer that is supported by Adobe Acrobat Reader. The data is stored in a DBMS (Data Base Management System). The client asks for the information from the database using an HTML (Hyper Text Markup Language) form in a web browser. JavaScript is used with the forms to assist the user and verify the integrity of the entered data. Queries to a database are made in SQL (Sequential Query Language), a widely supported standard for making queries to databases. Java servlets, programs written in the Java programming language running under the control of network server software, interrogate the database and complete a PDF form template kept in a file. The completed report is sent to the browser requesting the report. Some errors are sent to the browser in an HTML web page, others are reported to the server. Access to the databases was restricted since the data are being transported to new DBMS software that will run on new hardware. However, the SQL queries were made to Microsoft Access, a DBMS that is available on most PCs (Personal Computers). Access does support the SQL commands that were used, and a database was created with Access that contained typical data for the report forms.

Dean Lance Smith↗
NASA NTRS1999

US Gateway to SIMBAD Astronomical Database

During the last year the US SIMBAD Gateway Project continued to provide services like user registration to the US users of the SIMBAD database in France. Currently there are over 3400 US users registered. We also provide user support by answering questions from users and handling requests for lost passwords when still necessary. We have implemented in cooperation with the CDS SIMBAD project access to the SIMBAD database for US users on an Internet address basis. This allows most US users to access SIMBAD without having to enter passwords. We have maintained the mirror copy of the SIMBAD database on a server at SAO. This has allowed much faster access for the US users. We also supported a demonstration of the SIMBAD database at the meeting of the American Astronomical Society in January. We shipped computer equipment to the meeting and provided support for the demonstration activities at the SIMBAD booth. We continued to improve the cross-linking between the SIMBAD project and the Astrophysics Data System. This cross-linking between these systems is very much appreciated by the users of both the SIMBAD database and the ADS Abstract Service. The mirror of the SIMBAD database at SAO makes this connection faster for the US astronomers. We exchange information between the ADS and SIMBAD on a daily basis. The close cooperation between the CDS in Strasbourg and SAO, facilitated by this project, is an important part of the astronomy-wide digital library initiative called Urania. It has proven to be a model in how different data centers can collaborate and enhance the value of their products by linking with other data centers.

Eichhorn, G.↗
NASA NTRS2004

Drinking Water Database

This summer I had the opportunity to work in the Environmental Management Office (EMO) under the Chemical Sampling and Analysis Team or CS&AT. This team s mission is to support Glenn Research Center (GRC) and EM0 by providing chemical sampling and analysis services and expert consulting. Services include sampling and chemical analysis of water, soil, fbels, oils, paint, insulation materials, etc. One of this team s major projects is the Drinking Water Project. This is a project that is done on Glenn s water coolers and ten percent of its sink every two years. For the past two summers an intern had been putting together a database for this team to record the test they had perform. She had successfully created a database but hadn't worked out all the quirks. So this summer William Wilder (an intern from Cleveland State University) and I worked together to perfect her database. We began be finding out exactly what every member of the team thought about the database and what they would change if any. After collecting this data we both had to take some courses in Microsoft Access in order to fix the problems. Next we began looking at what exactly how the database worked from the outside inward. Then we began trying to change the database but we quickly found out that this would be virtually impossible.

Murray, ShaTerea R.↗
NASA NTRS2005

A Model Based Mars Climate Database for the Mission Design

A viewgraph presentation on a model based climate database is shown. The topics include: 1) Why a model based climate database?; 2) Mars Climate Database v3.1 Who uses it ? (approx. 60 users!); 3) The new Mars Climate database MCD v4.0; 4) MCD v4.0: what's new ? 5) Simulation of Water ice clouds; 6) Simulation of Water ice cycle; 7) A new tool for surface pressure prediction; 8) Acces to the database MCD 4.0; 9) How to access the database; and 10) New web access

Source record↗
NASA NTRS2008

The Space Systems Environmental Test Facility Database (SSETFD), Website Development Status

The Aerospace Corporation has been developing a database of U.S. environmental test laboratory capabilities utilized by the space systems hardware development community. To date, 19 sites have been visited by The Aerospace Corporation and verbal agreements reached to include their capability descriptions in the database. A website is being developed to make this database accessible by all interested government, civil, university and industry personnel. The website will be accessible by all interested in learning more about the extensive collective capability that the US based space industry has to offer. The Environments, Test & Assessment Department within The Aerospace Corporation will be responsible for overall coordination and maintenance of the database. Several US government agencies are interested in utilizing this database to assist in the source selection process for future spacecraft programs. This paper introduces the website by providing an overview of its development, location and search capabilities. It will show how the aerospace community can apply this new tool as a way to increase the utilization of existing lab facilities, and as a starting point for capital expenditure/upgrade trade studies. The long term result is expected to be increased utilization of existing laboratory capability and reduced overall development cost of space systems hardware. Finally, the paper will present the process for adding new participants, and how the database will be maintained.

Snyder, James M.↗
NASA NTRS2010

Database for Safety-Oriented Tracking of Chemicals

SafetyChem is a computer program that maintains a relational database for tracking chemicals and associated hazards at Johnson Space Center (JSC) by use of a Web-based graphical user interface. The SafetyChem database is accessible to authorized users via a JSC intranet. All new chemicals pass through a safety office, where information on hazards, required personal protective equipment (PPE), fire-protection warnings, and target organ effects (TOEs) is extracted from material safety data sheets (MSDSs) and recorded in the database. The database facilitates real-time management of inventory with attention to such issues as stability, shelf life, reduction of waste through transfer of unused chemicals to laboratories that need them, quantification of chemical wastes, and identification of chemicals for which disposal is required. Upon searching the database for a chemical, the user receives information on physical properties of the chemical, hazard warnings, required PPE, a link to the MSDS, and references to the applicable International Standards Organization (ISO) 9000 standard work instructions and the applicable job hazard analysis. Also, to reduce the labor hours needed to comply with reporting requirements of the Occupational Safety and Health Administration, the data can be directly exported into the JSC hazardous- materials database.

Stump, Jacob↗
NASA NTRS2016

The Quality Control Algorithms Used in the Creation of NASA Kennedy Space Center Lightning Protection System Towers Meteorological Database

An accurate database of meteorological data is essential for designing any aerospace vehicle and for preparing launch commit criteria. Meteorological instrumentation were recently placed on the three Lightning Protection System (LPS) towers at Kennedy Space Center (KSC) launch complex 39B (LC-39B), which provide a unique meteorological dataset existing at the launch complex over an extensive altitude range. Data records of temperature, dew point, relative humidity, wind speed, and wind direction are produced at 40, 78, 116, and 139 m at each tower. The Marshall Space Flight Center Natural Environments Branch (EV44) received an archive that consists of one-minute averaged measurements for the period of record of January 2011 - April 2015. However, before the received database could be used EV44 needed to remove any erroneous data from within the database through a comprehensive quality control (QC) process. The QC process applied to the LPS towers' meteorological data is similar to other QC processes developed by EV44, which were used in the creation of meteorological databases for other towers at KSC. The QC process utilized in this study has been modified specifically for use with the LPS tower database. The QC process first includes a check of each individual sensor. This check includes removing any unrealistic data and checking the temporal consistency of each variable. Next, data from all three sensors at each height are checked against each other, checked against climatology, and checked for sensors that erroneously report a constant value. Then, a vertical consistency check of each variable at each tower is completed. Last, the upwind sensor at each level is selected to minimize the influence of the towers and other structures at LC-39B on the measurements. The selection process for the upwind sensor implemented a study of tower-induced turbulence. This paper describes in detail the QC process, QC results, and the attributes of the LPS towers meteorological database.

Orcutt, John M.↗
NASA NTRS2018

Greedy Sampling and Incremental Surrogate Model-Based Tailoring of Aeroservoelastic Model Database for Flexible Aircraft

This paper presents a data analysis and modeling framework to tailor and develop linear parameter-varying (LPV) aeroservoelastic (ASE) model database for flexible aircrafts in broad 2D flight parameter space. The Kriging surrogate model is constructed using ASE models at a fraction of grid points within the original model database, and then the ASE model at any flight condition can be obtained simply through surrogate model interpolation. The greedy sampling algorithm is developed to select the next sample point that carries the worst relative error between the surrogate model prediction and the benchmark model in the frequency domain among all input-output channels. The process is iterated to incrementally improve surrogate model accuracy till a pre-determined tolerance or iteration budget is met. The methodology is applied to the ASE model database of a flexible aircraft currently being tested at NASA/AFRC for flutter suppression and gust load alleviation. Our studies indicate that the proposed method can reduce the number of models in the original database by 67%. Even so the ASE models obtained through Kriging interpolation match the model in the original database constructed directly from the physics-based tool with the worst relative error far below 1%. The interpolated ASE model exhibits continuously-varying gains along a set of prescribed flight conditions. More importantly, the selected grid points are distributed non-uniformly in the parameter space, a) capturing the distinctly different dynamic behavior and its dependence on flight parameters, and b) reiterating the need and utility for adaptive space sampling techniques for ASE model database compaction. The present framework is directly extendible to high-dimensional flight parameter space, and can be used to guide the ASE model development, model order reduction, robust control synthesis and novel vehicle design of flexible aircraft.

numerical analysi↗
NASA NTRS2005

XML technology planning database : lessons learned

A hierarchical Extensible Markup Language(XML) database called XCALIBR (XML Analysis LIBRary) has been developed by Millennium Program to assist in technology investment (ROI) analysis and technology Language Capability the New return on portfolio optimization. The database contains mission requirements and technology capabilities, which are related by use of an XML dictionary. The XML dictionary codifies a standardized taxonomy for space missions, systems, subsystems and technologies. In addition to being used for ROI analysis, the database is being examined for use in project planning, tracking and documentation. During the past year, the database has moved from development into alpha testing. This paper describes the lessons learned during construction and testing of the prototype database and the motivation for moving from an XML taxonomy to a standard XML-based ontology.

prototype databases↗
DOE OSTI2025

The Natural Products Magnetic Resonance Database (NP-MRD) for 2025

The Natural Products Magnetic Resonance Database or NP-MRD (https://np-mrd.org) is a comprehensive, freely accessible, web-based resource for the deposition, distribution, extraction and retrieval of nuclear magnetic resonance (NMR) data on natural products. The NP-MRD was initially established to support compound de-replication and data dissemination for the natural products community. However, that community has now grown to include many users from the metabolomics, microbiomics, foodomics and nutrition science fields. Indeed, since its launch in 2021, the NP-MRD has expanded enormously in size, scope and popularity. The current version of NP-MRD now contains nearly 7X more compounds (281,859 vs. 40,908) and 7X more NMR spectra (5.1 million vs. 817,000) than the first release. More specifically, an additional 4.6 million predicted spectra and another 11,000 spectra simulated from experimental chemical shifts were deposited into the database. Likewise, the number of NMR raw spectral data depositions has grown from a 165 spectra per year to more than 10,000 per year. As a result of this expansion, the number of monthly webpage views has grown from 55 to 20,000 and the number of monthly visitors has increased from 7 to 2500. To address this growth and to better support the expanding needs of its diverse community of users, many additional improvements to the NP-MRD have been made. These include significant enhancements to the data submission process, important improvements to the visualization and display of NMR spectra, notable updates to the database’s spectral search utilities and useful additions to support better NMR spectral analysis/prediction. Significant efforts have also been undertaken to remediate and update many of NP-MRD’s database entries. This manuscript describes these database improvements and expansion efforts, along with how they have been implemented and what future upgrades to the NP-MRD are planned.

Artifical Intelligence↗
DOE OSTI2024

G2Aero Database of Airfoils - Curated Airfoils

This dataset contains a curated set of 19,164 airfoil shapes from various applications and the data-driven design space of separable shape tensors (PGA space), which can be used as a parameter space for machine-learning applications focused on airfoil shapes. We constructed the airfoil dataset in two main stages. First, we identified 13 baseline airfoils from the NREL 5MW and IEA 15MW reference wind turbines. We reparameterized these shapes using least-squares fits of 8-order CST parametrizations, which involve 18 coefficients. By uniformly perturbing all 18 CST coefficients by +/-20% around each baseline airfoil, we generated 1,000 unique airfoils. Each airfoil was sampled with 1,001 shape landmarks whose x-coordinates followed a cosine distribution along the chord. This process resulted in a total of 13,000 airfoil shapes, each with 1,001 landmarks. In the second phase, we gathered additional airfoils from the extensive BigFoil database, which consolidates data from sources such as the University of Illinois Urbana-Champaign (UIUC) airfoil database, the JavaFoil database, the NACA-TR-824 database, and others. We undertook a thorough pre-processing step to filter out shapes with sparse, noisy, or incomplete data. We also removed airfoils with sharp leading edge and those exceeding our threshold for trailing edge thickness. Additionally, we thinned out the collection of NACA airfoils-- parametric sweeps of NACA airfoils with increasing thickness and camber present in BigFoil database-- by selecting every fourth step in the parameter sweeps. Finally, we regularized the airfoils by reparametrizing them with an 8-order CST parametrization (with 1,001 shape landmarks with x coordinated following cosine distribution along the chord) and removing airfoils with high reconstruction errors. This data pre-processing resulted in a set of 6,164 airfoils. In total, our curated airfoil dataset comprises 19,164 airfoils, each with 1,001 landmarks, and is stored in the curated_airfoils.npz file. Using this curated airfoil dataset, we utilized the separable shape tensors framework to develop a data-driven parameterization of airfoils based on principal geodesic analysis (PGA) of separable shape tensors. This PGA space is provided in PGAspace.npz file.

airfoils↗
NASA NTRS2018

Small Spacecraft Systems Virtual Institute's Federated Databases and State of the Art of Small Spacecraft Technology Report

NASA's Small Spacecraft Systems Virtual Institute (S3VI) is collaborating with the Air Force Research Laboratory and Space Dynamics Laboratory on the development of a small spacecraft parts database called SmallSat Parts On Orbit Now (SPOON). The SPOON database contains small spacecraft parts and technologies categorized by major satellite subsystems developed by industry, academia and government. The State of the Art of Small Spacecraft Technology report reflects small spacecraft parts submitted to the SPOON database and technologies compiled from other sources that were assessed as the current state of the art in each of the major subsystems. The report, first commissioned by NASA's Small Spacecraft Technology Program in mid-2013, is developed in response to the continuing growth in interest in using small spacecraft for many types of missions in Earth orbit and beyond. Due to the high market penetration of CubeSats, particular emphasis is placed on the state of the art of CubeSat-related technology. The 2018 report is planned for release in late summer. A review of SPOON database functionality, federation of additional NASA-internal and external databases along with a common search capability, as well as an overview of the State of the Art of Small Spacecraft Technology report will be presented. The S3VI is jointly sponsored by NASA's Space Technology Mission Directorate and Science Mission Directorate.

Small spacecraft↗
NASA NTRS2020

Dynamic IT Security Database and Analytics for Launch Control Systems Software

During the Summer 2020 session, I worked with intern Destani S. Van Arsdalen of EGS Software. Together, we co-created a tool to aid the dynamic investigation, updated over time,of the security compliance of LCS COTS and open source software. We originally planned touse spreadsheet software for management and analysis, but through this exploratoryproject, chose to use Python and JSON after receiving feedback on our project’s current anddesired capabilities at that time.At first, the project was solely designed to help on-board new COTS software, based on aquestionnaire that could be filled out for each software package. This, combined with usingthe spreadsheet application’s web-query capabilities to fetch information from the NVD,allowed presentation and analytics cells to automatically populate as elements of themanually-filled questionnaire changed. While this system was promising, we decided tochange technologies for a few reasons. In the spreadsheet, single cells could not hold complexdata like arrays and objects. The automatic population of cells and dynamic updates made itdifficult to manage and add new features. And finally, it had limited extensibility sinceadding new software required significant understanding of how both the spreadsheet wasconstructed, and the more obscure, proprietary scripting languages packaged with it.The pivot to a standard computer science database language of JSON, aided by thescripting capabilities of Python, greatly helped to improve the project’s functionality. First,and most importantly, the script’s import and analysis of database data is easilyreproducible. Additional data analysis can be modularly added without requiringmodification of the script and is capable of routine scheduling. The revised process can besplit into three parts. First, the conversion of LCS asset and software documentation into theJSON hierarchical database format. Second, the merging of this database with the NVD,forming a new data structure, using CPEs of the CVE object as a linking element betweenthem. And third, the automatically performed analytics and analysis of the combined data,in a modular and extensible format, to produce better informed business decisions. The outputted graphs, for example, are automatically generated by the Python script inconnection with the combined database. This allows updated graphs and any analytics to be re-rendered automatically following updates to the LCS’s initial asset documentation. Afinal report can then be programmatically and easily constructed from these sources to allow fully reproducible metrics for heavily evidenced risk management decisions.

it↗
NASA NTRS2020

UV/Vis+ Photochemistry Database: Structure, Content and Applications

The “science-softCon UV/Vis+ Photochemistry Database” (www.photochemistry.org) is a large and comprehensive collection of EUV-VUV-UV–Vis-NIR spectral data and other photochemical information assembled from published peer-reviewed papers. The database contains photochemical data including absorption, fluorescence, photoelectron, and circular and linear dichroism spectra, as well as quantum yields and photolysis related data that are critically needed in many scientific disciplines. This manuscript gives an outline regarding the structure and content of the “science-softCon UV/Vis+ Photochemistry Database”. The accurate and reliable molecular level information provided in this database is fundamental in nature and helps in proceeding further to understand photon, electron and ion induced chemistry of molecules of interest not only in spectroscopy, astrochemistry, astrophysics, Earth and planetary sciences, environmental chemistry, plasma physics, combustion chemistry but also in applied fields such as medical diagnostics, pharmaceutical sciences, biochemistry, agriculture, and catalysis. In order to illustrate this, we illustrate the use of the UV/Vis+ Photochemistry Database in four different fields of scientific endeavor.

Photochemistry↗
NASA NTRS2021

Developing a Sustainable, User-Friendly Literature Database to Support the Microgravity Simulation Support Facility (MSSF) at NASA's Kennedy Space Center (KSC)

Established in 2017, the Microgravity Simulation Support Facility (MSSF) at NASA’s Kennedy Space Center is the only centralized, dedicated facility supporting ground microgravity research in the United States. The MSSF offers the research community the ability to conduct simulated microgravity research with experimental conditions functionally resembling those aboard the International Space Station (ISS) and in other flight-based experimental environments. Since its inception, the MSSF has supported numerous studies and has since collected an extensive library of relevant and pertinent literature. The goal of our research was to develop and implement a sustainable, user-friendly literature database to better house this literature at the MSSF. To achieve this, our team focused on sorting, optimizing, and analyzing preexisting literature libraries to determine a best suitable and sustainable platform for the MSSF. After establishing initial database platforms, the team worked to develop descriptive and structural metadata categories to best sort the literature, which was followed by rigorous testing and optimization of the database as it was implemented. The MSSF has now been outfitted with a reliable, accessible database that effectively houses literature and provides diverse analysis to the user. Our team is continuing to test and update our platform and parameters as we aim for the formal implementation, expansion, and evolution of our database to better sustain future research ventures at the MSSF and beyond.

Database Development↗