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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 145 records · Page 8
All sourcesNASA NTRSDOE OSTI
DOE OSTI2014

Graph Databases for Large-Scale Healthcare Systems: A Framework for Efficient Data Management and Data Services

Designing a database system for both efficient data management and data services has been one of the enduring challenges in the healthcare domain. In many healthcare systems, data services and data management are often viewed as two orthogonal tasks; data services refer to retrieval and analytic queries such as search, joins, statistical data extraction, and simple data mining algorithms, while data management refers to building error-tolerant and non-redundant database systems. The gap between service and management has resulted in rigid database systems and schemas that do not support effective analytics. We compose a rich graph structure from an abstracted healthcare RDBMS to illustrate how we can fill this gap in practice. We show how a healthcare graph can be automatically constructed from a normalized relational database using the proposed 3NF Equivalent Graph (3EG) transformation.We discuss a set of real world graph queries such as finding self-referrals, shared providers, and collaborative filtering, and evaluate their performance over a relational database and its 3EG-transformed graph. Experimental results show that the graph representation serves as multiple de-normalized tables, thus reducing complexity in a database and enhancing data accessibility of users. Based on this finding, we propose an ensemble framework of databases for healthcare applications.

Park, Yubin↗
DOE OSTI2018

The International Experimental Thermal Hydraulic Systems database – TIETHYS: A new NEA validation tool

Nuclear reactor codes require validation with appropriate data representing the plant for specific scenarios. The thermal-hydraulic data is scattered in different locations and in different formats. Some of the data is in danger of being lost. A relational database is being developed to organize the international thermal hydraulic test data for various reactor concepts and different scenarios. At the reactor system level, that data is organized to include separate effect tests and integral effect tests for specific scenarios and corresponding phenomena. The database relies on the phenomena identification sections of expert developed PIRTs. The database will provide a summary of appropriate data, review of facility information, test description, instrumentation, references for the experimental data and some examples of application of the data for validation. The current database platform includes scenarios for PWR, BWR, VVER, and specific benchmarks for CFD modelling data and is to be expanded to include references for molten salt reactors. There are place holders for high temperature gas cooled reactors, CANDU and liquid metal reactors. This relational database is called The International Experimental Thermal Hydraulic Systems (TIETHYS) database and currently resides at Nuclear Energy Agency (NEA) of the OECD and is freely open to public access. Going forward the database will be extended to include additional links and data as they become available. https://www.oecd-nea.org/tiethysweb/

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2015

In-Memory Graph Databases for Web-Scale Data

RDF databases have emerged as one of the most relevant way for organizing, integrating, and managing expo- nentially growing, often heterogeneous, and not rigidly structured data for a variety of scientific and commercial fields. In this paper we discuss the solutions integrated in GEMS (Graph database Engine for Multithreaded Systems), a software framework for implementing RDF databases on commodity, distributed-memory high-performance clusters. Unlike the majority of current RDF databases, GEMS has been designed from the ground up to primarily employ graph-based methods. This is reflected in all the layers of its stack. The GEMS framework is composed of: a SPARQL-to-C++ compiler, a library of data structures and related methods to access and modify them, and a custom runtime providing lightweight software multithreading, network messages aggregation and a partitioned global address space. We provide an overview of the framework, detailing its component and how they have been closely designed and customized to address issues of graph methods applied to large-scale datasets on clusters. We discuss in details the principles that enable automatic translation of the queries (expressed in SPARQL, the query language of choice for RDF databases) to graph methods, and identify differences with respect to other RDF databases.

GEMS↗
DOE OSTI2012

Nuclear Concrete Materials Database Phase I Development

The FY 2011 accomplishments in Phase I development of the Nuclear Concrete Materials Database to support the Light Water Reactor Sustainability Program are summarized. The database has been developed using the ORNL materials database infrastructure established for the Gen IV Materials Handbook to achieve cost reduction and development efficiency. In this Phase I development, the database has been successfully designed and constructed to manage documents in the Portable Document Format generated from the Structural Materials Handbook that contains nuclear concrete materials data and related information. The completion of the Phase I database has established a solid foundation for Phase II development, in which a digital database will be designed and constructed to manage nuclear concrete materials data in various digitized formats to facilitate electronic and mathematical processing for analysis, modeling, and design applications.

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗
DOE OSTI2013

Materials Inventory Database for the Light Water Reactor Sustainability Program

Scientific research involves the purchasing, processing, characterization, and fabrication of many sample materials. The history of such materials can become complicated over their lifetime – materials might be cut into pieces or moved to various storage locations, for example. A database with built-in functions to track these kinds of processes facilitates well-organized research. The Material Inventory Database Accounting System (MIDAS) is an easy-to-use tracking and reference system for such items. The Light Water Reactor Sustainability Program (LWRS), which seeks to advance the long-term reliability and productivity of existing nuclear reactors in the United States through multiple research pathways, proposed MIDAS as an efficient way to organize and track all items used in its research. The database software ensures traceability of all items used in research using built-in functions which can emulate actions on tracked items – fabrication, processing, splitting, and more – by performing operations on the data. MIDAS can recover and display the complete history of any item as a simple report. To ensure the database functions suitably for the organization of research, it was developed alongside a specific experiment to test accident tolerant nuclear fuel cladding under the LWRS Advanced Light Water Reactor Nuclear Fuels Pathway. MIDAS kept track of materials used in this experiment from receipt at the laboratory through all processes, test conduct and, ultimately, post-test analysis. By the end of this process, the database proved to be right tool for this program. The database software will help LWRS more efficiently conduct research experiments, from simple characterization tests to in-reactor experiments. Furthermore, MIDAS is a universal tool that any other research team could use to organize their material inventory.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2015

Weapon Systems Engineering Material Database Requirements

The Weapon Systems Engineering Material Database, often called ‘Granta’ (due to the use of Granta MI software by Granta Design) but referred to in this document as ‘the database’, stores and distributes material information to W-division at Los Alamos National Laboratory (LANL). The database is constantly evolving as data is imported and methods of retrieving data are developed. Because limited resources necessitate prioritization of data to be imported and retrieval method development, a definition is needed of how the database is to be used, both currently and in the future. This document, to be used by the database developers, is intended to provide that definition in the form of requirements for the database.

36 MATERIALS SCIENCE↗
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 OSTI2017

UNF-ST&DARDS Unified Database and the Automatic Document Generator

The U.S. Department of Energy, Office of Nuclear Energy is sponsoring development of a database to store information related to spent nuclear fuel (SNF) in support of its Spent Fuel and Waste Disposition efforts. This database, referred to as the Unified Database (UDB), is part of a larger engineering analysis tool, the Used Nuclear Fuel Storage, Transportation & Disposal Analysis Resource and Data System (UNF-ST&DARDS). The UDB provides a comprehensive, controlled source of SNF information, including dry cask attributes, assembly data, economic attributes, transportation infrastructure attributes, potential future facility attributes, and federal government radioactive waste attributes. There are a number of existing and envisioned data reports that can be expected to use data stored within the UDB; however, previously, there was not a streamlined method to couple the database to such data reports. Therefore, to streamline the creation of these reports, two methods were developed to generate documents from information in the database automatically. The first method used Java and LaTeX for automatically generating the report, and the second method used the Python programming language along with Sphinx, a Python documentation generator. There are some advantages and disadvantages to both approaches, but both methods produced equally high-quality, automatically generated reports that were directly coupled to the database. Finally, this study describes data currently available in the UDB; explains the two different methods for automatically generating reports from these data; and shows examples of inline text, figures, and tables automatically generated using both approaches.

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗
DOE OSTI2011

THE Be STAR SPECTRA (BeSS) DATABASE

Be stars vary on many timescales, from hours to decades. A long time base of observations to analyze certain phenomena in these stars is therefore necessary. Collecting all existing and future Be star spectra into one database has thus emerged as an important tool for the Be star community. Moreover, for statistical studies, it is useful to have centralized information on all known Be stars via an up-to-date catalog. These two goals are what the Be Star Spectra (BeSS, http://basebe.obspm.fr) database proposes to achieve. The database contains an as-complete-as-possible catalog of known Be stars with stellar parameters, as well as spectra of Be stars from all origins (any wavelength, any epoch, any resolution, etc.). It currently contains over 54,000 spectra of more than 600 different Be stars among the {approx}2000 Be stars in the catalog. A user can access and query this database to retrieve information on Be stars or spectra. Registered members can also upload spectra to enrich the database. Spectra obtained by professional as well as amateur astronomers are individually validated in terms of format and science before being included in BeSS. In this paper, we present the database itself as well as examples of the use of BeSS data in terms of statistics and the study of individual stars.

79 ASTRONOMY AND ASTROPHYSICS↗
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 OSTI2011

The LANL hemorrhagic fever virus database, a new platform for analyzing biothreat viruses

Hemorrhagic fever viruses (HFVs) are a diverse set of over 80 viral species, found in 10 different genera comprising five different families: arena-, bunya-, flavi-, filo- and togaviridae. All these viruses are highly variable and evolve rapidly, making them elusive targets for the immune system and for vaccine and drug design. About 55 000 HFV sequences exist in the public domain today. A central website that provides annotated sequences and analysis tools will be helpful to HFV researchers worldwide. The HFV sequence database collects and stores sequence data and provides a user-friendly search interface and a large number of sequence analysis tools, following the model of the highly regarded and widely used Los Alamos HIV database [Kuiken, C., B. Korber, and R.W. Shafer, HIV sequence databases. AIDS Rev, 2003. 5: p. 52–61]. The database uses an algorithm that aligns each sequence to a species-wide reference sequence. The NCBI RefSeq database [Sayers et al. (2011) Database resources of the National Center for Biotechnology Information. Nucleic Acids Res., 39, D38–D51.] is used for this; if a reference sequence is not available, a Blast search finds the best candidate. Using this method, sequences in each genus can be retrieved pre-aligned. The HFV website can be accessed via http://hfv.lanl.gov.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2014

SU-E-T-153: Establish a Comprehensive Patient-Specific Plan QA Database for Instituitional Quality Control Program

Purpose: Since the publication of TG-119, several new treatment techniques requiring new QA devices have been implemented in the clinic. To monitor and analyze our institutional QA performance, we have created a comprehensive QA database using Research Electronic Data Capture (REDCap). The database will also assist us in creating IMRT QA Analysis practice guidelines. Methods: Since Oct. 2013, 336 patient plan QA results were entered into the database. Plan parameters such as plan ID, treatment site, technique, energy, optimization constraints, modulation factor, leaf speed, leaf opening.etc were automatically extracted from the Varian Eclipse database to allow us to refine our evaluation and analysis method. Specific QA device, LINAC-related information, and measurement and analysis results were manually entered by the QA team. IMRT plans were measured using MapCHECK2 while RapidArc plans were measured using ArcCHECK. Distance-To-Agreement 3%/3mm without global maximum normalization was used. Results: The data indicates that different treatment techniques might benefit from a different site-specific action level(AL) depending on the complexity of the plan and optimization parameter used (e.g., breast IMRT QA= 97.8% and pelvis IMRT QA=93.1%). Different QA devices may also benefit from a different AL (MapCHECK2 = 94.1% while ArcCHECK = 83.0%). The relationship between the parameters and passing rate suggests that the complexity of each plan, characterized by leaf travel, leaf opening and modulation factor, affect the passing rate significantly. The database is reviewed regularly, and any abnormal point of the QA result or a trend of lower QA passing rate on a specific LINAC is further investigated. Conclusion: Establishing a comprehensive QA database provides an overview of the quality assurance program. It not only helps in answering the question “what is a reasonable and achievable standard for each institution”, but also saves time in monitoring and investigating the daily machine and QA performance.

07 ISOTOPE AND RADIATION SOURCES↗