Engineering Papers⌕ Search

SEARCH · Engineering Papers

Results for “relational database”

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.

Quote a phrase for an exact phrase match. Source license links do not imply unrestricted reuse.

At least 325 records · Page 18
All sourcesNASA NTRSDOE OSTI
NASA NTRSDate not supplied

Knowledge Discovery for Early Failure Assessment of Complex Engineered Systems Using Natural Language Processing

Emerging complex engineered systems may have unexpected safety issues due to novel operational environments, increasing autonomy, human-machine interaction, and other factors. To prevent failures in operation or testing that necessitate costly redesign, it is desirable to predict likely failure modes early in the design process. Text-based information about past engineering failures presents one possible solution by facilitating the retrieval of information that can inform new designs. However, identifying documents containing relevant information and extracting required information can be prohibitively time-consuming when implemented at scale. In this research, an automated natural language processing-based framework is proposed to discover relevant knowledge from documents containing failure-related design information. Documents containing usable information are filtered using sentiment analysis based on a custom lexicon specialized for engineering design and by filtering out documents containing only irrelevant topics. Next, from the identified usable documents, information relating to engineering failures, contributing factors that can be controlled at design time (“risk factors”), and recommended preventative actions are extracted. Semantic similarity is then used to group similar pieces of extracted information for improved generalizability. The proposed framework is applied to NASA’s Lessons Learned Information System (LLIS). The framework can be used to identify documents containing usable failure-related design information from other databases, extract relevant information from these documents, and generalize the acquired knowledge such that it can be applied to novel systems.

Sequoia R. Andrade↗
NASA NTRSDate not supplied

Knowledge Discovery for Early Failure Assessment of Complex Engineered Systems Using Natural Language Processing

Emerging complex engineered systems may have unexpected safety issues due to novel operational environments, increasing autonomy, human-machine interaction, and other factors. To prevent failures in operation or testing that necessitate costly redesign, it is desirable to predict likely failure modes early in the design process. Information about past engineering failures in natural language format presents one possible solution by enabling the retrieval of information that can inform new designs. However, identifying documents containing usable information and extracting the required information can be prohibitively time-consuming when implemented at scale. In this research, an automated natural language processing (NLP) framework is proposed to discover relevant knowledge from documents containing failure-related design information. The framework is applied to NASA’s Lessons Learned Information System (LLIS),which is publicly available. Documents containing usable information are filtered using two different NLP-based models. Next, from the identified usable documents, a failure taxonomy is extracted using a partitioned hierarchical topic modeling approach. Partitions of the document describe different sections of the failure taxonomy – i.e., failure, cause of failure, and recommendations – as indicated by the structure of the original document. The extracted failure taxonomy can be leveraged in early design failure assessment methods. Moreover, the framework can be used to identify documents containing usable failure-related design information from other databases and extract relevant information from these documents.

Documentation and Information Science↗
NASA NTRSDate not supplied

Knowledge Discovery for Early Failure Assessment of Complex Engineered Systems Using Natural Language Processing

Emerging complex engineered systems may have unexpected safety issues due to novel operational environments, increasing autonomy, human-machine interaction, and other factors. To prevent failures in operation or testing that necessitate costly redesign, it is desirable to predict likely failure modes early in the design process. Information about past engineering failures in natural language format presents one possible solution by enabling the retrieval of information that can inform new designs. However, identifying documents containing usable information and extracting the required information can be prohibitively time-consuming when implemented at scale. In this research, an automated natural language processing (NLP) framework is proposed to discover relevant knowledge from documents containing failure-related design information. The framework is applied to NASA’s Lessons Learned Information System (LLIS),which is publicly available. Documents containing usable information are filtered using two different NLP-based models. Next, from the identified usable documents, a failure taxonomy is extracted using a partitioned hierarchical topic modeling approach. Partitions of the document describe different sections of the failure taxonomy – i.e., failure, cause of failure, and recommendations – as indicated by the structure of the original document. The extracted failure taxonomy can be leveraged in early design failure assessment methods. Moreover, the framework can be used to identify documents containing usable failure-related design information from other databases and extract relevant information from these documents.

Documentation and Information Science↗
NASA NTRS2023

Sea-Level Rise Projections for Maryland 2023

This report provides updated projections of sea-level rise in the State of Maryland, as required at least every five years by the Maryland Commission on Climate Change Act of 2015. The Sixth Assessment Report (AR6) for the Intergovernmental Panel on Climate Change (IPCC) produced a database of probabilistic projections of relative sea-level rise for tide-gauge locations around the world that reflect differences caused by thermal expansion, glacier and polar ice sheet melting, winds and currents, and vertical land motion. These are available online for seven locations in Maryland and the District of Columbia. Considered together with extrapolations of tide gauge and satellite observations, these projections indicate that sea level rise will likely be between 0.3 m (1 ft) and 0.5 m (1.6 ft) by 2050 (from a 2005 starting point). Beyond the middle of the century, the pathway of greenhouse gas emissions increasingly matters. Under the Current Commitments scenario, the best estimate of sea-level rise in 2100 is 0.8 m (2.7 ft) and sea level will likely rise between 0.6 m (2.0 ft) and 1.1 m (3.5 ft), barring unexpected processes driving rapid ice-sheet melt. Even with exceptionally rapid ice loss, it is very unlikely that it would exceed 1.5 m (4.9 ft).

Donald F Boesch↗
NASA NTRS2018

NASA's Small Spacecraft Systems Virtual Institute and Small Spacecraft Enterprise

In January of 2017, NASA's Space Technology and Science Mission Directorates established the Small Spacecraft Systems Virtual Institute (S3VI). The mission of the agency-wide institute is to advance the field of small spacecraft systems and allied sciences by promoting innovation, exploring new concepts, identifying emerging technology opportunities, and establishing effective conduits for the collaboration and the dissemination of research results relevant to small spacecraft systems and subsystems. To achieve this, the S3VI serves as the common portal for NASA-related small spacecraft activities, hosts the Small Spacecraft Body of Knowledge as an online resource for the annual Small Spacecraft Technology State of the Art report, including a components and subsystems database, and also collects and organizes related knowledge such as small spacecraft reliability processes and best practices. The S3VI also serves as the front door for other governmental, non-governmental, and external agencies that wish to collaborate or interact with NASA small spacecraft organizations. NASA also presently has a growing number of small spacecraft related programs, projects, and efforts collectively termed the NASA Small Spacecraft Enterprise underway to advance the utility of small spacecraft instruments, technologies, and missions in order for NASA to achieve its exploration and science goals. These various activities will be outlined and described with a refocused emphasis on cis-lunar and deep space applications and supporting technologies.

Small spacecraft↗
NASA NTRS2018

NASA's Small Spacecraft Systems Virtual Institute and Small Spacecraft Enterprise

In January of 2017, NASA's Space Technology and Science Mission Directorates established the Small Spacecraft Systems Virtual Institute (S3VI). The mission of the agency-wide institute is to advance the field of small spacecraft systems to expand the capabilities and utility of small spacecraft to perform high-value science by promoting innovation, exploring new concepts, identifying emerging technology opportunities, and establishing effective conduits for the collaboration and the dissemination of research results relevant to small spacecraft systems and subsystems. To achieve this, the S3VI serves as the common portal for NASA-related small spacecraft activities, hosts the Small Spacecraft Body of Knowledge as an online resource for the annual Small Spacecraft Technology State of the Art report, including a components and subsystems database, and also collects and organizes related knowledge such as small spacecraft reliability processes and best practices. The S3VI also serves as the front door for other governmental, non-governmental, and external agencies that wish to collaborate or interact with NASA small spacecraft organizations. NASA also presently has a growing number of small spacecraft related programs, projects, and efforts underway to advance the utility of small spacecraft instruments, technologies, and missions to support NASA to achieve its exploration and science goals. These various activities will be outlined and described to include small spacecraft applications and supporting technologies for cis-lunar and deep space missions.

Small spacecraft↗
DOE OSTI2021

Analysis of Spectral Lines in Large Databases of Synthetic Spectra for Massive Stars

In this paper, we describe a program that identifies in the optical spectrum the main parameters of a spectral line, namely the initial and final wavelengths, and the line depth. Moreover, using numerical calculations, it identifies and removes adjacent lines. Next, the program calculates the equivalent width and the FWHM. The software was tested in a sample of 300 lines in two databases of synthetic spectra generated by the CMFGEN and PoWR codes, and 300 lines in observed spectra from the IACOB database, showing a Gaussian distribution of relative errors, from which it is inferred that 80% of the measured lines have errors less than 17% and only 5% of the lines have errors greater than 26%. The program was also run on the entire database of 45,000 CMFGEN and 202 POWR synthetic spectra, generating a library of H i, He i, and He ii lines necessary to feed the FITspec code for the derivation of stellar parameters: effective temperature, surface gravity, and luminosity.

47 OTHER INSTRUMENTATION↗
DOE OSTI2024

Advances in Metallic Fuel Database Development and Data Qualification

The Fuels Irradiation and Physics Database (FIPD [1]) is a comprehensive repository of data and documents related to Uranium-Zirconium based metallic fuel test pins. This database stores operational conditions of these pins, calculated using a suite of Argonne National Laboratory analysis codes developed during the Integral Fast Reactor (IFR) program. Key calculated data include axial distributions of power, temperature, fluence, burnup, and isotopic densities. Additionally, the FIPD holds post-irradiation examination (PIE) data such as fission gas release, gas chemistry measurements, and axial distributions derived from profilometry, gamma scanning, and neutron radiography. Complementing these data is an extensive archive of documents related to various pins and experiments. These include raw PIE records, design details, safety analyses, and operational reports. More detail about FIPD can be found in ref. [2]. The database development is an ongoing effort covering metallic fuel experiments from the Experimental Breeder Reactor II (EBR-II) and the Fast Flux Test Facility (FFTF). The recent improvements to the database and the data QA status are summarized in this paper.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
NASA NTRS1994

Jet aircraft engine exhaust emissions database development: Year 1990 and 2015 scenarios

Studies relating to environmental emissions associated with the High Speed Civil Transport (HSCT) military jet and charter jet aircraft were conducted by McDonnell Douglas Aerospace Transport Aircraft. The report includes engine emission results for baseline 1990 charter and military scenario and the projected jet engine emissions results for a 2015 scenario for a Mach 1.6 HSCT charter and military fleet. Discussions of the methodology used in formulating these databases are provided.

Landau, Z. Harry↗
NASA NTRS1983

Establishing homologies in protein sequences

Computer-based statistical techniques used to determine homologies between proteins occurring in different species are reviewed. The technique is based on comparison of two protein sequences, either by relating all segments of a given length in one sequence to all segments of the second or by finding the best alignment of the two sequences. Approaches discussed include selection using printed tabulations, identification of very similar sequences, and computer searches of a database. The use of the SEARCH, RELATE, and ALIGN programs (Dayhoff, 1979) is explained; sample data are presented in graphs, diagrams, and tables and the construction of scoring matrices is considered.

Dayhoff, M. O.↗
NASA NTRS2002

Transition Documentation on a Three-Element High-Lift Configuration at High Reynolds Numbers--Database

A 2-D (two dimensional) high-lift system experiment was conducted in August of 1996 in the Low Turbulence Pressure Tunnel at NASA Langley Research Center, Hampton, VA. The purpose of the experiment was to obtain transition measurements on a three element high-lift system for CFD (computational fluid dynamics) code validation studies. A transition database has been created using the data from this experiment. The present report details how the hot-film data and the related pressure data are organized in the database. Data processing codes to access the data in an efficient and reliable manner are described and limited examples are given on how to access the database and store acquired information.

Bertelrud, Arild↗
DOE OSTI2023

Glass formulation and composition optimization with property models: A review

Abstract Glass is a versatile material with a remarkable history and many practical applications. It plays a critical role in our everyday lives, the advancement of science, and the development of many technologies. The Edisonian type trial‐and‐error method was commonly used for conventional design of glass compositions, which was time‐consuming and costly. With the urgent need to develop new glass compositions for technology applications rapidly, it has become necessary to develop precise property models with predictive powers using large databases and efficient formulation approaches. This paper reviews the design of glass compositions using these analytical and numerical models of composition–structure–property relations of glasses, some based on large databases and machine learning approaches. Aspects of data collection, model fitting, feature extraction, model evaluation, and uncertainty quantification will be covered. Furthermore, advances in the glass optimization framework and available tools are summarized with examples. The outlook and perspective for further glass property model development and formulation approaches are discussed.

Lu, Xiaonan↗
NASA NTRS2001

An integrated software suite for surface-based analyses of cerebral cortex

The authors describe and illustrate an integrated trio of software programs for carrying out surface-based analyses of cerebral cortex. The first component of this trio, SureFit (Surface Reconstruction by Filtering and Intensity Transformations), is used primarily for cortical segmentation, volume visualization, surface generation, and the mapping of functional neuroimaging data onto surfaces. The second component, Caret (Computerized Anatomical Reconstruction and Editing Tool Kit), provides a wide range of surface visualization and analysis options as well as capabilities for surface flattening, surface-based deformation, and other surface manipulations. The third component, SuMS (Surface Management System), is a database and associated user interface for surface-related data. It provides for efficient insertion, searching, and extraction of surface and volume data from the database.

NASA Discipline Neuroscience↗
DOE OSTI2024

FatPlants: a comprehensive information system for lipid-related genes and metabolic pathways in plants

Abstract FatPlants, an open-access, web-based database, consolidates data, annotations, analysis results, and visualizations of lipid-related genes, proteins, and metabolic pathways in plants. Serving as a minable resource, FatPlants offers a user-friendly interface for facilitating studies into the regulation of plant lipid metabolism and supporting breeding efforts aimed at increasing crop oil content. This web resource, developed using data derived from our own research, curated from public resources, and gleaned from academic literature, comprises information on known fatty-acid-related proteins, genes, and pathways in multiple plants, with an emphasis on Glycine max, Arabidopsis thaliana, and Camelina sativa. Furthermore, the platform includes machine-learning based methods and navigation tools designed to aid in characterizing metabolic pathways and protein interactions. Comprehensive gene and protein information cards, a Basic Local Alignment Search Tool search function, similar structure search capacities from AphaFold, and ChatGPT-based query for protein information are additional features. Database URL: https://www.fatplants.net/

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2021

Multiresolution classification of turbulence features in image data through machine learning

During large-scale simulations, intermediate data products such as image databases have become popular due to their low relative storage cost and fast in-situ analysis. Serving as a form of data reduction, these image databases have become more acceptable to perform data analysis on. In this work, we present an image-space detection and classification system for extracting vortices at multiple scales through wavelet-based filtering. A custom image-space descriptor is used to encode a large variety of vortex-types and a machine learning system is trained for fast classification of vortex regions. By combining a radial-based histogram descriptor, a bag of visual words feature descriptor, and a support vector machine, our results show that we are able to detect and classify vortex features at various sizes at multiple scales. Once trained, our framework enables the fast extraction of vortices on new, unknown image datasets for flow analysis.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2025

Open database for GPD analyses

This article summarizes the main ideas behind creating an open database proposed for use in the exploration of generalized parton distributions (GPDs). This lightweight database is well suited for GPD phenomenology and is designed to store both experimental and lattice-QCD data. It can also aid in benchmarking GPD-related developments, such as GPD models. The database utilizes a new data format based on the YAML serialization language, enabling the storage of essential information for modern analyses, such as replica values. It includes interfaces for both Python and C++, allowing straightforward integration with analysis codes.

Burkert, V. D. [Thomas Jefferson National Accelera↗
DOE OSTI2020

Power Plant Water Risk and Adaptive Measures Database

Project objective was to understand water-related constraints affecting conventional powerplant operations, specifically coal-fired power plants. Of concern were threats related to drought and flood affecting both water supply and ability of plant to discharge wastewater. Also of interest were adaptive measures taken to mitigate identified threats. This spreadsheet contains the responses provided by the power plant operators and owners. Data have been "sanitized" (e.g., random plant ID, binned location and generation capacity information) to ensure anonymity of individual power plants.

Adaptive Measures↗