Engineering Papers⌕ Search

SEARCH · Engineering Papers

Results for “Databases”

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 55 records · Page 3
All sourcesNASA NTRSDOE OSTI
DOE OSTI2020

CamRegBase: a gene regulation database for the biofuel crop, Camelina sativa

Abstract Camelina is an annual oilseed plant from the Brassicaceae family that is gaining momentum as a biofuel winter cover crop. However, a significant limitation in further enhancing its utility as a producer of oils that can be used as biofuels, jet fuels or bio-based products is the absence of a repository for all the gene expression and regulatory information that is being rapidly generated by the community. Here, we provide CamRegBase (https://camregbase.org/) as a one-stop resource to access Camelina information on gene expression and co-expression, transcription factors, lipid associated genes and genome-wide orthologs in the close-relative reference plant Arabidopsis. We envision this as a resource of curated information for users, as well as a repository of new gene regulation information.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2015

Demonstration of thermal control, microstructure control, defect mitigation and process parameter database generation for Ti-6Al-4V Direct Digital Manufacturing - Understanding defect mitigation and process parameter database generation for direct digital manufacturing

Researchers from Manufacturing Demonstration Facility (MDF) at Oak Ridge National Laboratory (ORNL) worked with Applied Optimization (AO) to understand and evaluate the propensity for defect formation in builds manufactured using DM3D-POM laser direct metal deposition. The main aim of this collaboration was to understand the character of powder jet behavior as a function of the nozzle parameters such as cover gas, carrier gas, and shaping gas. In order to evaluate the sensitivities of the parameters used in model, various experiments were performed with in-situ monitoring of the powder stream characteristics using a high speed camera. A wide variety of conditions while keeping the hopper motor rpm constant, including laser power and travel speed were explored. The cross sections of the deposits were characterized using optical microscopy.

47 OTHER INSTRUMENTATION↗
DOE OSTI2025

Existing Hydropower Assets (EHA) Capacity Plant Database, 2005-2024

Existing Hydropower Asset (EHA) Annual Capacity is a geospatial point-level dataset containing annual capacity over the years (2005-2024) and key characteristics of operational U.S. hydropower plants with 1 megawatt or greater of nameplate capacity. EIA form 860 and EHA are the primary sources of the derived data.

Johnson, Megan [ORNL] (ORCID:0000000290141741)↗
DOE OSTI2025

Existing Hydropower Assets (EHA) Capacity Factor Plant Database, 2005-2024

Existing Hydropower Asset (EHA) Annual Capacity Factor is a geospatial point-level dataset containing annual capacity factors over the years (2005-2024) and key characteristics of operational U.S. hydropower plants with 1 megawatt or greater of nameplate capacity. EIA form 860 and EHA are the primary sources of the derived data. Pumped storage and hybrid plants are excluded.

Johnson, Megan [ORNL] (ORCID:0000000290141741)↗
DOE OSTI2025

Comprehensive Database of Environmental Mitigations Extracted from FERC-Licensed Hydropower Projects Using Artificial Intelligence Techniques, 1998-2023

This dataset provides a comprehensive inventory of environmental mitigation measures required by Federal Energy Regulatory Commission (FERC) licensed hydropower facilities from 461 licenses that were issued from 1998 to 2023. These licenses constitute 446 of the 1015 FERC projects that were active at the end of 2023. 17,612 mentions of environmental mitigations were identified and categorized in 128 unique categories. Mitigations were identified using a Natural Language Processing (NLP) approach, specifically with a Bidirectional Encoder Representations from Transformer (BERT) model. Model-derived results were then reviewed and updated by a subject matter expert as needed. This dataset introduces important enhancements to previous efforts to inventory environmental mitigations, such as including associated license text for each mitigation, tracking the number of instances a mitigation was identified within a license, and providing improved location information. These enhancements significantly expand the dataset's utility, offering greater analytical capabilities and ensuring reproducibility. The dataset is downloadable as a zip file containing the metadata and dataset files.

Ruggles, Thomas [Oak Ridge National Laboratory (OR↗
DOE OSTI2019

An Overview of the Database Framework for GEM Detector under CMS Experiment at CERN

In this paper, we give an overview of the database framework which we have developed for the Gas Electron Multiplier (GEM) Detector at CERN. The GEM constitutes a powerful addition to the family of fast radiation detectors; originally developed for particle physics experiments, and has spawned a large number of developments and applications. The GEM database framework comprises four components. The first component is the database itself. There are three instances of the database which have been deployed. One is for the development purpose which contains test data, other one is for the integration purposes while the last one is for the production purpose which contains real data. The database further comprises various schemas and each schema consists of different tables in it. We use separate schemas for various types of tables. The second component of the database framework is called DB Loader. The DB Loader is used to load data into database. The data is prepared in the predefined format which is in the XML form. Then the xml file is copied into a spool area of the server in which DB loader is running. Once the file is copied, the DB Loader loads the file into the database. The loader returns appropriate status codes after performing database insertion/update operation. The status of the database operations is checked against the status code which is returned by the loader. The third component of the database framework comprises graphical user interface (GUI). This is a web-based interface which can be accessed from the internet. This interface is basically used for the detector construction and to perform various quality control tests on the detector and its components. The last component of the database framework is called online monitoring system (OMS). The OMS is data visualization framework for the various detectors of the CMS experiment at CERN. It is also used to display data for the GEM. It enables users to view and retrieve database contents without having to learn database specifics.

Imran, Muhammad↗
DOE OSTI2023

Optimizing metaproteomics database construction: lessons from a study of the vaginal microbiome

Metaproteomics, a method for untargeted, high-throughput identification of proteins in complex samples, provides functional information about microbial communities and can tie functions to specific taxa. Metaproteomics often generates less data than other omics techniques, but analytical workflows can be improved to increase usable data in metaproteomic outputs. Identification of peptides in the metaproteomic analysis is performed by comparing mass spectra of sample peptides to a reference database of protein sequences. Although these protein databases are an integral part of the metaproteomic analysis, few studies have explored how database composition impacts peptide identification. Here, we used cervicovaginal lavage (CVL) samples from a study of bacterial vaginosis (BV) to compare the performance of databases built using six different strategies. We evaluated broad versus sample-matched databases, as well as databases populated with proteins translated from metagenomic sequencing of the same samples versus sequences from public repositories. Smaller sample-matched databases performed significantly better, driven by the statistical constraints on large databases. Additionally, large databases attributed up to 34% of significant bacterial hits to taxa absent from the sample, as determined orthogonally by 16S rRNA gene sequencing. We also tested a set of hybrid databases which included bacterial proteins from NCBI RefSeq and translated bacterial genes from the samples. These hybrid databases had the best overall performance, identifying 1,068 unique human and 1,418 unique bacterial proteins, ~30% more than a database populated with proteins from typical vaginal bacteria and fungi. Our findings can help guide the optimal identification of proteins while maintaining statistical power for reaching biological conclusions.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2025

Addressing the dynamic nature of reference data: a new nucleotide database for robust metagenomic classification

Accurate metagenomic classification relies on comprehensive, up-to-date, and validated reference databases. While the NCBI BLAST Nucleotide (nt) database, encompassing a vast collection of sequences from all domains of life, represents an invaluable resource, its massive size—currently exceeding 10 12 nucleotides—and exponential growth pose significant challenges for researchers seeking to maintain current nt-based indices for metagenomic classification. Recognizing that no current nt-based indices exist for the widely used Centrifuge classifier, and the last public version currently available was released in 2018, we addressed this critical gap by leveraging advanced high-performance computing resources. We present new Centrifuge-compatible nt databases, meticulously constructed using a novel pipeline incorporating different quality control measures, including reference decontamination and filtering. These measures demonstrably reduce spurious classifications, as shown through our reanalysis of published metagenomic data where Plasmodium annotations were dramatically reduced using our decontaminated database, highlighting how database quality can significantly impact research conclusions. Through temporal comparisons, we also reveal how our approach minimizes inconsistencies in taxonomic assignments stemming from asynchronous updates between public sequence and taxonomy databases. These discrepancies are particularly evident in taxa such as Listeria monocytogenes and Naegleria fowleri, where classification accuracy varied significantly across database versions. These new databases, made available as pre-built Centrifuge indexes, respond to the need for an open, robust, nt-based pipeline for taxonomic classification in metagenomics. Applications such as environmental metagenomics, forensics, and clinical metagenomics, which require comprehensive taxonomic coverage, will benefit from this resource. Our work highlights the importance of treating reference databases as dynamic entities, subject to ongoing quality control and validation akin to software development best practices. This approach is crucial for ensuring accuracy and reliability of metagenomic analysis, especially as databases continue to expand in size and complexity.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2015

SU-E-T-255: Development of a Michigan Quality Assurance (MQA) Database for Clinical Machine Operations

Purpose: A unified database system was developed to allow accumulation, review and analysis of quality assurance (QA) data for measurement, treatment, imaging and simulation equipment in our department. Recording these data in a database allows a unified and structured approach to review and analysis of data gathered using commercial database tools. Methods: A clinical database was developed to track records of quality assurance operations on linear accelerators, a computed tomography (CT) scanner, high dose rate (HDR) afterloader and imaging systems such as on-board imaging (OBI) and Calypso in our department. The database was developed using Microsoft Access database and visual basic for applications (VBA) programming interface. Separate modules were written for accumulation, review and analysis of daily, monthly and annual QA data. All modules were designed to use structured query language (SQL) as the basis of data accumulation and review. The SQL strings are dynamically re-written at run time. The database also features embedded documentation, storage of documents produced during QA activities and the ability to annotate all data within the database. Tests are defined in a set of tables that define test type, specific value, and schedule. Results: Daily, Monthly and Annual QA data has been taken in parallel with established procedures to test MQA. The database has been used to aggregate data across machines to examine the consistency of machine parameters and operations within the clinic for several months. Conclusion: The MQA application has been developed as an interface to a commercially available SQL engine (JET 5.0) and a standard database back-end. The MQA system has been used for several months for routine data collection.. The system is robust, relatively simple to extend and can be migrated to a commercial SQL server.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2015

MINEs: Open access databases of computationally predicted enzyme promiscuity products for untargeted metabolomics

Metabolomics have proven difficult to execute in an untargeted and generalizable manner. Liquid chromatography–mass spectrometry (LC–MS) has made it possible to gather data on thousands of cellular metabolites. However, matching metabolites to their spectral features continues to be a bottleneck, meaning that much of the collected information remains uninterpreted and that new metabolites are seldom discovered in untargeted studies. These challenges require new approaches that consider compounds beyond those available in curated biochemistry databases. Here we present Metabolic In silico Network Expansions (MINEs), an extension of known metabolite databases to include molecules that have not been observed, but are likely to occur based on known metabolites and common biochemical reactions. We utilize an algorithm called the Biochemical Network Integrated Computational Explorer (BNICE) and expert-curated reaction rules based on the Enzyme Commission classification system to propose the novel chemical structures and reactions that comprise MINE databases. Starting from the Kyoto Encyclopedia of Genes and Genomes (KEGG) COMPOUND database, the MINE contains over 571,000 compounds, of which 93% are not present in the PubChem database. However, these MINE compounds have on average higher structural similarity to natural products than compounds from KEGG or PubChem. MINE databases were able to propose annotations for 98.6% of a set of 667 MassBank spectra, 14% more than KEGG alone and equivalent to PubChem while returning far fewer candidates per spectra than PubChem (46 vs. 1715 median candidates). Application of MINEs to LC–MS accurate mass data enabled the identity of an unknown peak to be confidently predicted. MINE databases are freely accessible for non-commercial use via user-friendly web-tools at http://minedatabase.mcs.anl.gov and developer-friendly APIs. MINEs improve metabolomics peak identification as compared to general chemical databases whose results include irrelevant synthetic compounds. MINEs complement and expand on previous in silico generated compound databases that focus on human metabolism. We are actively developing the database; future versions of this resource will incorporate transformation rules for spontaneous chemical reactions and more advanced filtering and prioritization of candidate structures.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2023

Carbon Storage Technical Viability Approach (CS TVA) Database

The Carbon Storage Technical Viability Approach (CS TVA) database was developed to support the implementation of the CS TVA Matrix to a national data availability assessment for technically viable carbon storage. This database leverages the efforts of multiple adjacent and overlapping databases by non-redundantly combining the databases into a single database along with additionally providing tags facilitating the CS TVA. The non-redundant aspect of the database permits an accurate assessment of the concentration of available data, aiding in spatial and categorical data gaps analysis relative to the individual CS TVA Matrix Components. Version 2.0 of the database is an expansion of Version 1.0. Version 2.0 was created to include additional data gathered to fill gaps in the existing data set. Downloading the CS TVA v2.0 database will result in two separate databases, the version 1.0 original .gdb, and a second addendum .gdb with the new data gathered, together these two databases make up v2.0. Please see the ReadMe file below for full details, metadata information, use disclaimer, and attributions.

Coal↗
DOE OSTI2019

Impact of non-specific normal databases on perfusion quantification of low-dose myocardial SPECT studies

Aim: To evaluate the impact of non-specific normal databases on the percent summed rest score (SR%) and stress score (SS%) from simulated low-dose SPECT studies by shortening the acquisition time/projection. Methods: Forty normal-weight and 40 overweight/obese patients underwent myocardial studies with a conventional gamma-camera (BrightView, Philips) using three different acquisition times/projection: 30, 15, and 8 s (100%-counts, 50%-counts, and 25%-counts scan, respectively) and reconstructed using the iterative algorithm with resolution recovery (IRR) Astonish{sup TM} (Philips). Three sets of normal databases were used: (1) full-counts IRR; (2) half-counts IRR; and (3) full-counts traditional reconstruction algorithm database (TRAD). The impact of these databases and the acquired count statistics on the SR% and SS% was assessed by ANOVA analysis and Tukey test (P < 0.05). Results: Significantly higher SR% and SS% values (> 40%) were found for the full-counts TRAD databases respect to the IRR databases. For overweight/obese patients, significantly higher SS% values for 25%-counts scans (+19%) are confirmed compared to those of 50%-counts scan, independently of using the half-counts or the full-counts IRR databases. Conclusions: Astonish{sup TM} requires the adoption of the own specific normal databases in order to prevent very high overestimation of both stress and rest perfusion scores. Conversely, the count statistics of the normal databases seems not to influence the quantification scores.

62 RADIOLOGY AND NUCLEAR MEDICINE↗
DOE OSTI2023

WELLS Database

The Wellbore Exploration and Location Logistic System (WELLS) is a living national wellbore database - created and maintained by the National Energy Technology Laboratory (NETL). This resource contains more than seven million public wellbore records from state, federal, and tribal resources. Sourced from over 65 authoritative, yet disparate resources, the WELLS Database combines and synthesizes well data from oil, gas, underground injection, research, geothermal, geotechnical, groundwater and other types of wells in a single, unified system. This resource can be explored and visualized through the WELLS Interactive Application, also on EDX: https://edx.netl.doe.gov/dataset/wells-interactive-application The WELLS Database (formerly titled CO2-Locate) is an integrated national well dataset, representing open-source wellbore data from disparate state, tribal, and federal entities. The database provides publicly available well header data with key attributes such as well age, depth, and status. The database contains a fully integrated CSV file with all values in numerical columns, such as depth, converted into numbers. This version has a NETL derived API (American Petroleum Institute) number column and has been handled for redundancies, resulting in one record for every unique API number. The database also contains a fully integrated CSV file, where all original data are kept as text values. Additionally, the database includes a shapefile containing key attributes and coordinates from the integrated dataset, reformatted public wells CSV files, and a proprietary well density grid shapefile. Notes for consideration: The WELLS Database will be updated periodically with new datasets and information. A field dictionary with field (i.e., attribute) coverage across acquired public well resources, and the resulting integrated public well datasets are available in the spreadsheet, WELLS_Field_Dictionary.xlsx. Summary layers provided in this database are derived from proprietary layers and do not always contain key features (status, type, true vertical depth, or spud year) and therefore might not be shown when data are queried for those features.

AS↗
DOE OSTI2017

SNaX: A Database of Supernova X-Ray Light Curves

We present the Supernova X-ray Database (SNaX), a compilation of the X-ray data from young supernovae (SNe). The database includes the X-ray fluxes and luminosities of young SNe, from days to years after outburst. The original goal and intent of this study was to present a database of Type IIn SNe (SNe IIn), which we have accomplished. Our ongoing goal is to expand the database to include all SNe for which published data are available. The database interface allows one to search for SNe using various criteria, plot all or selected data points, and download both the data and the plot. The plotting facility allows for significant customization. There is also a facility for the user to submit data that can be directly incorporated into the database. We include an option to fit the decay of any given SN light curve with a power-law. The database includes a conversion of most data points to a common 0.3–8 keV band so that SN light curves may be directly compared with each other. A mailing list has been set up to disseminate information about the database. We outline the structure and function of the database, describe its various features, and outline the plans for future expansion.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2015

An affinity-structure database of helix-turn-helix: DNA complexes with a universal coordinate system

Molecular interactions between proteins and DNA molecules underlie many cellular processes, including transcriptional regulation, chromosome replication, and nucleosome positioning. Computational analyses of protein-DNA interactions rely on experimental data characterizing known protein-DNA interactions structurally and biochemically. While many databases exist that contain either structural or biochemical data, few integrate these two data sources in a unified fashion. Such integration is becoming increasingly critical with the rapid growth of structural and biochemical data, and the emergence of algorithms that rely on the synthesis of multiple data types to derive computational models of molecular interactions. We have developed an integrated affinity-structure database in which the experimental and quantitative DNA binding affinities of helix-turn-helix proteins are mapped onto the crystal structures of the corresponding protein-DNA complexes. This database provides access to: (i) protein-DNA structures, (ii) quantitative summaries of protein-DNA binding affinities using position weight matrices, and (iii) raw experimental data of protein-DNA binding instances. Critically, this database establishes a correspondence between experimental structural data and quantitative binding affinity data at the single basepair level. Furthermore, we present a novel alignment algorithm that structurally aligns the protein-DNA complexes in the database and creates a unified residue-level coordinate system for comparing the physico-chemical environments at the interface between complexes. Using this unified coordinate system, we compute the statistics of atomic interactions at the protein-DNA interface of helix-turn-helix proteins. We provide an interactive website for visualization, querying, and analyzing this database, and a downloadable version to facilitate programmatic analysis. Lastly, this database will facilitate the analysis of protein-DNA interactions and the development of programmatic computational methods that capitalize on integration of structural and biochemical datasets. The database can be accessed at http://ProteinDNA.hms.harvard.edu.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2015

Nuclear Energy Infrastructure Database Fitness and Suitability Review

In 2014, the Deputy Assistant Secretary for Science and Technology Innovation (NE-4) initiated the Nuclear Energy-Infrastructure Management Project by tasking the Nuclear Science User Facilities (NSUF) to create a searchable and interactive database of all pertinent NE supported or related infrastructure. This database will be used for analyses to establish needs, redundancies, efficiencies, distributions, etc. in order to best understand the utility of NE’s infrastructure and inform the content of the infrastructure calls. The NSUF developed the database by utilizing data and policy direction from a wide variety of reports from the Department of Energy, the National Research Council, the International Atomic Energy Agency and various other federal and civilian resources. The NEID contains data on 802 R&D instruments housed in 377 facilities at 84 institutions in the US and abroad. A Database Review Panel (DRP) was formed to review and provide advice on the development, implementation and utilization of the NEID. The panel is comprised of five members with expertise in nuclear energy-associated research. It was intended that they represent the major constituencies associated with nuclear energy research: academia, industry, research reactor, national laboratory, and Department of Energy program management. The Nuclear Energy Infrastructure Database Review Panel concludes that the NSUF has succeeded in creating a capability and infrastructure database that identifies and documents the major nuclear energy research and development capabilities across the DOE complex. The effort to maintain and expand the database will be ongoing. Detailed information on many facilities must be gathered from associated institutions added to complete the database. The data must be validated and kept current to capture facility and instrumentation status as well as to cover new acquisitions and retirements.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗