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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 433 records · Page 24
All sourcesNASA NTRSDOE OSTI
NASA NTRS1990

Database Management System

In 1981 Wayne Erickson founded Microrim, Inc, a company originally focused on marketing a microcomputer version of RIM (Relational Information Manager). Dennis Comfort joined the firm and is now vice president, development. The team developed an advanced spinoff from the NASA system they had originally created, a microcomputer database management system known as R:BASE 4000. Microrim added many enhancements and developed a series of R:BASE products for various environments. R:BASE is now the second largest selling line of microcomputer database management software in the world.

Source record↗
NASA NTRS2022

ThermoBase: A Database of the Phylogeny and Physiology of Thermophilic and Hyperthermophilic Organisms

Thermophiles and hyperthermophiles are those organisms which grow at high temperature (> 40°C). The unusual properties of these organisms have received interest in multiple fields of biological research, and have found applications in biotechnology, especially in industrial processes. However, there are few listings of thermophilic and hyperthermophilic organisms and their relevant environmental and physiological data. Such repositories can be used to standardize definitions of thermophile and hyperthermophile limits and tolerances and would mitigate the need for extracting organism data from diverse literature sources across multiple, sometimes loosely related, research fields. Therefore, we have developed ThermoBase, a web-based and freely available database which currently houses comprehensive descriptions for 1238 thermophilic or hyperthermophilic organisms. ThermoBase reports taxonomic, metabolic, environmental, experimental, and physiological information in addition to literature resources. This includes parameters such as coupling ions for chemiosmosis, optimal pH and range, optimal temperature and range, optimal pressure, and optimal salinity. The database interface allows for search features and sorting of parameters. As such, it is the goal of ThermoBase to facilitate and expedite hypothesis generation, literature research, and understanding relating to thermophiles and hyperthermophiles within the scientific community in an accessible and centralized repository. ThermoBase is freely available online at the Astrobiology Habitable Environments Database (AHED; https://ahed.nasa.gov), at the Database Center for Life Science (TogoDB; http://togodb.org/db/thermobase), and in the S1 File.

Thermophiles↗
DOE OSTI2023

Predicting oxidation damage of ultra high-temperature carbide ceramics in extreme environments using machine learning

Determining the oxidation resistance of UHTC carbides in extreme environments is challenging theoretically and experimentally due to the high dimensional complexity of influencing variables and intricate testing setups. Herein we demonstrate the use of machine learning (ML) models trained with experimental literature data to predict the oxide thickness of UHTC carbides exposed to air based on composition, mean grain size, relative densification, holding time, and temperature. A multi-dimensional database with 76 occurrences is created containing experimental results of Hf, Zr, and Ta carbides plus additives. In this study, the preprocessed database is then used to train ML models to predict their oxidation behavior. The trained model predicts the oxidation damage in the form of an average oxide thickness in UHTC carbides with a Mean Absolute Error (MAE) of ±65.45 μm for samples in the testing set that developed thicknesses up to 1000 μm. The model successfully predicted oxidation damage for a recession rate lower than 60 μm/min. It is noticed that the ensemble method MAE is increased to ±134.34 μm while forecasting the oxidation of samples with a recession rate higher than the threshold. The unprecedented approach is a novel way to predict the damage through the oxidation of carbide compounds before processing for a smarter design with room for improvement.

36 MATERIALS SCIENCE↗
DOE OSTI2024

Diagnosing hot-spot symmetry in surrogate ignition experiments via secondary DT-neutron spectroscopy at the NIF

The directional energy spectrum of neutrons generated from the in-flight fusion reaction of 1-MeV tritons contains information about the hot-spot symmetry. The National Ignition Facility (NIF) fields Symmetry Capsule (Symcap) implosions, which have historically measured the symmetry of the radiation, drive by measuring the hot-spot shape via x-ray self-emission. Symcaps are used to tune the hot-spot symmetry for ignition experiments at the NIF. This work shows the relationship between directional secondary DT-n spectra and x-ray imaging data for a large database of Symcap implosions. A correlation is observed between the relative widths of the DT-n spectra measured with nTOFs and the shape measured with x-ray imaging. A Monte Carlo model, which computes the directional secondary DT-n spectrum, is used to interpret the results. A comparison of the x-ray and secondary DT-n data with the Monte Carlo model indicates that 56% of the variance between the two datasets is explained by a P2 asymmetry. More advanced simulations using HYDRA suggest that the unaccounted variance is due to P1 and P4 asymmetries present in the hot spot. The comparison of secondary DT-n data and x-ray imaging data to the modeling shows the DT-n data contain important information that supplements current P2 measurements and contain new information about the P1 asymmetry.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
NASA NTRS2004

Gamma-Ray Burst Intensity Distributions

We use the lag-luminosity relation to calculate self-consistently the redshifts, apparent peak bolometric luminosities L(sub B1), and isotropic energies E(sub iso) for a large sample of BATSE bursts. We consider two different forms of the lag-luminosity relation; for both forms the median redshift, for our burst database is 1.6. We model the resulting sample of burst energies with power law and Gaussian dis- tributions, both of which are reasonable models. The power law model has an index of a = 1.76 plus or minus 0.05 (95% confidence) as opposed to the index of a = 2 predicted by the simple universal jet profile model; however, reasonable refinements to this model permit much greater flexibility in reconciling predicted and observed energy distributions.

Band, David L.↗
NASA NTRS2008

Supplier Management System

Supplier Management System (SMS) allows for a consistent, agency-wide performance rating system for suppliers used by NASA. This version (2.0) combines separate databases into one central database that allows for the sharing of supplier data. Information extracted from the NBS/Oracle database can be used to generate ratings. Also, supplier ratings can now be generated in the areas of cost, product quality, delivery, and audit data. Supplier data can be charted based on real-time user input. Based on these individual ratings, an overall rating can be generated. Data that normally would be stored in multiple databases, each requiring its own log-in, is now readily available and easily accessible with only one log-in required. Additionally, the database can accommodate the storage and display of quality-related data that can be analyzed and used in the supplier procurement decision-making process. Moreover, the software allows for a Closed-Loop System (supplier feedback), as well as the capability to communicate with other federal agencies.

Ramirez, Eric↗
NASA NTRS2011

Use of Smoothed Measured Winds to Predict and Assess Launch Environments

Since many of the larger launch vehicles are operated near their design limits during the ascent phase of flight to optimize payload to orbit, it often becomes necessary to verify that the vehicle will remain within certification limits during the ascent phase as part of the go/no-go review made prior to launch. This paper describes the approach used to predict Ares I-X launch vehicle structural air loads and controllability prior to launch which represents a distinct departure from the methodology of the Space Shuttle and Evolved Expendable Launch Vehicle (EELV) programs. Protection for uncertainty of key environment and trajectory parameters is added to the nominal assessment of launch capability to ensure that critical launch trajectory variables would be within the integrated vehicle certification envelopes. This process was applied by the launch team as a key element of the launch day go/no-go recommendation. Pre-launch assessments of vehicle launch capability for NASA's Space Shuttle and the EELV heavy lift versions require the use of a high-resolution wind profile measurements, which have relatively small sample size compared with low-resolution profile databases (which include low-resolution balloons and radar wind profilers). The approach described in this paper has the potential to allow the pre-launch assessment team to use larger samples of wind measurements from low-resolution wind profile databases that will improve the accuracy of pre-launch assessments of launch availability with no degradation of mission assurance or launch safety.

Cordova, Henry S.↗
NASA NTRS1992

Strongly transitive fuzzy relations: A more adequate way to describe similarity

The notion of a transitive closure of a fuzzy relation is very useful for clustering in pattern recognition, for fuzzy databases, etc. It is based on translating the standard definition of transitivity and transitive closure into fuzzy terms. This definition works fine, but to some extent it does not fully capture our understanding of transitivity. The reason is that this definition is based on fuzzifying only the positive side of transitivity: if R(a,b) and R(b,c), then R(a,c); but transitivity also includes a negative side: if R(a,b) and not R(a,c), then not R(b,c). In classical logic, this negative statement follows from the standard 'positive' definition of transitivity. In fuzzy logic, this negative part of the transitivity has to be formulated as an additional demand. A strongly transitive fuzzy relation as the one that satisfies both the positive and the negative transitivity demands is defined, the existence of strongly transitive closure is proven, and the relationship between strongly transitive similarity and clustering are found.

Kreinovich, Vladik YA.↗
DOE OSTI2024

What Are Ontologies and When Should They Be Used?

Data without description is at best unusable, and at worst, misused. If we do not understand the assumptions and meaning of our data, we are unable to confidently use it. Data today is largely described within a database’s schema, detailing structure and primitive datatypes as part of a relational model, but if we require assurance some data value can be correctly evaluated alongside others beyond the immediate systems in which they are defined, a more portable, richer semantics is needed. Ontologies define knowledge unambiguously across systems and establish the means to reason upon said knowledge using logical inference. They model neutral domains of information rather than data definitions from software or databases that would only serve to enrich a single system’s idiosyncrasies. In this paper, we take a casual stance to explore what ontologies are, how they are built, why they are useful, and when they should be used.

97 MATHEMATICS AND COMPUTING↗
NASA NTRS1994

The design and implementation of EPL: An event pattern language for active databases

The growing demand for intelligent information systems requires closer coupling of rule-based reasoning engines, such as CLIPS, with advanced data base management systems (DBMS). For instance, several commercial DBMS now support the notion of triggers that monitor events and transactions occurring in the database and fire induced actions, which perform a variety of critical functions, including safeguarding the integrity of data, monitoring access, and recording volatile information needed by administrators, analysts, and expert systems to perform assorted tasks; examples of these tasks include security enforcement, market studies, knowledge discovery, and link analysis. At UCLA, we designed and implemented the event pattern language (EPL) which is capable of detecting and acting upon complex patterns of events which are temporally related to each other. For instance, a plant manager should be notified when a certain pattern of overheating repeats itself over time in a chemical process; likewise, proper notification is required when a suspicious sequence of bank transactions is executed within a certain time limit. The EPL prototype is built in CLIPS to operate on top of Sybase, a commercial relational DBMS, where actions can be triggered by events such as simple database updates, insertions, and deletions. The rule-based syntax of EPL allows the sequences of goals in rules to be interpreted as sequences of temporal events; each goal can correspond to either (1) a simple event, or (2) a (possibly negated) event/condition predicate, or (3) a complex event defined as the disjunction and repetition of other events. Various extensions have been added to CLIPS in order to tailor the interface with Sybase and its open client/server architecture.

Giuffrida, G.↗
NASA NTRS2010

ICESat Lidar and Global Digital Elevation Models: Application to DESDynI

Geodetic control is extremely important in the production and quality control of topographic data sets, enabling elevation results to be referenced to an absolute vertical datum. Global topographic data with improved geodetic accuracy achieved using global Ground Control Point (GCP) databases enable more accurate characterization of land topography and its change related to solid Earth processes, natural hazards and climate change. The multiple-beam lidar instrument that will be part of the NASA Deformation, Ecosystem Structure and Dynamics of Ice (DESDynI) mission will provide a comprehensive, global data set that can be used for geodetic control purposes. Here we illustrate that potential using data acquired by NASA's Ice, Cloud and land Elevation Satellite (ICEsat) that has acquired single-beam, globally distributed laser altimeter profiles (+/-86deg) since February of 2003 [1, 2]. The profiles provide a consistently referenced elevation data set with unprecedented accuracy and quantified measurement errors that can be used to generate GCPs with sub-decimeter vertical accuracy and better than 10 m horizontal accuracy. Like the planned capability for DESDynI, ICESat records a waveform that is the elevation distribution of energy reflected within the laser footprint from vegetation, where present, and the ground where illuminated through gaps in any vegetation cover [3]. The waveform enables assessment of Digital Elevation Models (DEMs) with respect to the highest, centroid, and lowest elevations observed by ICESat and in some cases with respect to the ground identified beneath vegetation cover. Using the ICESat altimetry data we are developing a comprehensive database of consistent, global, geodetic ground control that will enhance the quality of a variety of regional to global DEMs. Here we illustrate the accuracy assessment of the Shuttle Radar Topography Mission (SRTM) DEM produced for Australia, documenting spatially varying elevation biases of several meters in magnitude.

Carabajal, Claudia C.↗
DOE OSTI2025

TropiRoot 1.0: Database of tropical root characteristics across environments

Tropical ecosystems contain the world's largest biodiversity of vascular plants. Yet, our understanding of tropical functional diversity and its contribution to global diversity patterns is constrained by data availability. This discrepancy underscores an urgent need to bridge data gaps by incorporating comprehensive tropical root data into global datasets. Here, we provide a database of tropical root characteristics. This new database, TropiRoot 1.0, will be instrumental in evaluating an array of hypotheses pertaining to root functional ecology and plant biogeography, both within the tropics and relative to other global biomes. The data compilation was conducted by the TropiRoot Initiative, in partnership with the Fine-Root Ecology Database (FRED) and the Global Root Trait (GRooT) database, Colorado State University (CSU) and the Smithsonian Tropical Research Institute (STRI). Literature search and data extraction were conducted between 2020 and 2024. Literature was identified using Web of Science, Scopus, and complemented using the expert knowledge of members of TropiRoot. To provide broad environmental and geographical distributions, literature searches included root characteristics (traits) across global change drivers, natural gradients, and from different continents. We adopted FRED standardized data columns and streamlined the format to enhance accessibility for data extraction across various user groups. This optimized framework resulted in a smaller, yet comprehensive datasheet. To make the database compatible with other global root trait initiatives, column identification was standardized following the codes provided by FRED. These efforts culminated in data extracted from 104 new sources, resulting in more than 8000 rows of data (either species or community data). Most of the data in TropiRoot 1.0 include root characteristics such as root biomass, morphology, root dynamics, mass fraction, architecture, anatomy, physiology, and root chemistry. This initiative represents a 30% increase in the currently available data for tropical roots in FRED. TropiRoot 1.0 contains root characteristics from 25 different countries, where seven are located in Asia, six in South America, five in Central America and the Caribbean, four in Africa, two in North America, and 1 in Oceania. Due to the volume of data, when ancillary data were available, including soil data, these data were either extracted and included in the database or its availability was recorded in an additional column. Multiple contributors checked the entries for outliers during the collation process to ensure data quality. For text-based observations, we examined all cells to ensure that their content relates to their specific categories. For numerical observations, we ordered each numerical value from least to greatest and plotted the values, checking apparent outliers against the data in their respective sources and correcting or removing incorrect or impossible values. Some data (soil and aboveground) have different columns for the same variable presented in different units, including originally published units, but root characteristics data had units converted to match those reported in FRED. By filling a gap from global databases, TropiRoot 1.0 expands our knowledge of otherwise so far underrepresented regions and our ability to assess global trends. This advancement can be used to improve tropical forest representation in vegetation models. The data are freely available and should be cited when used.

FRED↗
NASA NTRSDate not supplied

The NASA Open Science Data Repository: Biomedical Data, Analysis Tools, and Informatic Collaborations

Increased biomedical risks and challenges associated with deep space missions require knowledge discovery, health countermeasures, and biomedical support capabilities. Maximally open-access and reusable data is needed by developers, scientists, and engineers to develop these systems. The NASA Open Science Data Repository (OSDR) is a maximally open access and FAIR database (ie., findable, accessible, interoperable, and reusable), and meets various scientific, technical, and operational needs. It offers users and submitters the ability to upload, download, search, share, analyze, cite, and visualize data across ‘omics, physiological, phenotypic, payload, hardware, behavioral, bioimaging, video, and environmental monitoring telemetry datasets. OSDR is an expanded database, based upon the successes of NASA GeneLab. OSDR has >460 studies with datasets covering model organisms to non-NASA human astronauts. There are ~12 datasets from the Inspiration 4 (I4) mission, spanning metagenomics, comprehensive metabolic panels, clonal hematopoiesis, spatial transcriptomics, proteomics, and cytokine panels. In the interest of data privacy, two I4 datasets with raw files relating to the epitranscriptome, and a new request feature is live in OSDR (with a backend review process established) developed from industry norms. OSDR is collecting and curating biomedical human data from a new sub-orbital research flight and is open to more space life science/biomedical submissions from the international and commercial sectors. OSDR also recently began a collaboration with the European Space Agency (ESA) to collect and curate >200 terabytes of human and model organism data. The OSDR submission portal is designed to ingest and curate ~25 ‘omics and ~50 physiological-phenotypic-imaging assay data types. Tools available for OSDR users include: 1) an Environmental Data Application to compare radiation, CO2, relative humidity, temperature, and other telemetry across missions and subjects, 2) the RadLab database, a collaboration between NASA, ESA, the German and Italian Space Agencies, and the Bulgarian Academy of Sciences, and 3) a Multi-study visualization tool which enables users to look across and combine ‘omics datasets. There are ~600 volunteer OSDR Analysis Working Group (AWG) members providing feedback on scientific data/metadata standards and collaborating to mine-reuse OSDR in research. OSDR/GeneLab has enabled ~60 publications reusing data as of October 2023.

space biology↗
NASA NTRS2017

Mass and Reliability Source (MaRS) Database

The Mass and Reliability Source (MaRS) Database consolidates components mass and reliability data for all Oribital Replacement Units (ORU) on the International Space Station (ISS) into a single database. It was created to help engineers develop a parametric model that relates hardware mass and reliability. MaRS supplies relevant failure data at the lowest possible component level while providing support for risk, reliability, and logistics analysis. Random-failure data is usually linked to the ORU assembly. MaRS uses this data to identify and display the lowest possible component failure level. As seen in Figure 1, the failure point is identified to the lowest level: Component 2.1. This is useful for efficient planning of spare supplies, supporting long duration crewed missions, allowing quicker trade studies, and streamlining diagnostic processes. MaRS is composed of information from various databases: MADS (operating hours), VMDB (indentured part lists), and ISS PART (failure data). This information is organized in Microsoft Excel and accessed through a program made in Microsoft Access (Figure 2). The focus of the Fall 2017 internship tour was to identify the components that were the root cause of failure from the given random-failure data, develop a taxonomy for the database, and attach material headings to the component list. Secondary objectives included verifying the integrity of the data in MaRS, eliminating any part discrepancies, and generating documentation for future reference. Due to the nature of the random-failure data, data mining had to be done manually without the assistance of an automated program to ensure positive identification.

Valdenegro, Wladimir↗
DOE OSTI2024

Tornadoes in Southeast South America: Mesoscale to Planetary-Scale Environments

Abstract A multiscale analysis of the environment supporting tornadoes in southeast South America (SESA) was conducted based on a self-constructed database of 74 reports. Composites of environmental and convective parameters from ERA5 were generated relative to tornado events. The distribution of the reported tornadoes maximizes over the Argentine plains, while events are rare close to the Andes and south of Sierras de Córdoba. Events are relatively common in all seasons except in winter. Proximity environment evolution shows enhanced instability, deep-layer vertical wind shear, storm-relative helicity, reduced convective inhibition, and a lowered lifting condensation level before or during the development of tornadic storms in SESA. No consistent signal in low-level wind shear is seen during tornado occurrence. However, a curved hodograph with counterclockwise rotation is present. The Significant Tornado Parameter (STP) is also maximized prior to tornadogenesis, most strongly associated with enhanced CAPE. Differences in the convective environment between tornadoes in SESA and the U.S. Great Plains are discussed. On the synoptic scale, tornado events are associated with a strong anomalous trough crossing the southern Andes that triggers lee cyclogenesis, subsequently enhancing the South American low-level jet (SALLJ) that increases moisture advection to support deep convection. This synoptic trough also enhances vertical shear that, along with enhanced instability, sustains organized convection capable of producing tornadic storms. At planetary scales, the tornadic environment is modulated by Rossby wave trains that appear to be forced by convection near northern Australia. Madden–Julian oscillation phase 3 preferentially occurs 1–2 weeks ahead of tornado occurrence. Significance Statement The main goal of this study is to describe what atmospheric conditions (from local to global scales) are present prior to and during tornadic storms impacting southeast South America (SESA). Increasing potential for deep convection, wind shear, and potential for rotating updrafts, as well as reducing convective inhibition and cloud-base height, are predominant a few hours before and during the events in connection to low-level northerly winds enhancing moisture transport to the region. Remote convective activity near northern Australia appears to influence large-scale atmospheric circulation that subsequently triggers convective storms supporting tornadogenesis 1–2 weeks later in SESA. Our findings highlight the importance of accounting for atmospheric processes occurring at different scales to understand and predict tornado occurrences.

Meteorology & Atmospheric Sciences↗
DOE OSTI2024

Catalog of topological phonon materials

Phonons play a crucial role in many properties of solid-state systems, and it is expected that topological phonons may lead to rich and unconventional physics. On the basis of the existing phonon materials databases, we have compiled a catalog of topological phonon bands for more than 10,000 three-dimensional crystalline materials. Using topological quantum chemistry, we calculated the band representations, compatibility relations, and band topologies of each isolated set of phonon bands for the materials in the phonon databases. Additionally, we calculated the real-space invariants for all the topologically trivial bands and classified them as atomic or obstructed atomic bands. We have selected more than 1000 “ideal” nontrivial phonon materials to motivate future experiments. The datasets were used to build the Topological Phonon Database.

Science & Technology - Other Topics↗
DOE OSTI2025

A database and meta-analysis on the performance of exploding pusher implosions conducted at OMEGA

A database of 222 exploding pusher implosions conducted at the OMEGA Laser Facility is presented. The dataset consists of glass-shell capsules filled with varying pressures of D 2 , T 2 , and 3 He, which were imploded using square laser pulses with intensities ranging from 1 to 1 × 10 15 W/cm 2 . The database includes measurements of bang times, ion temperatures, and yields from the DD, D 3 He, and DT fusion reactions. A semi-analytic exploding pusher model is introduced, which effectively captures the observed trends in the data. This model predicts that the measurements scale according to a power-law relation based on the initial capsule and laser conditions. A generalized power-law scaling relation is directly fit to each dataset, providing a useful interpolation of the entire database. Overall, the database provides a valuable resource to estimating bang times, temperatures, and yields for the design of future experiments. Additionally, it provides a diverse set of data for validating more advanced implosion physics models.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2021

Improved departure from nucleate boiling prediction in rod bundles using a physics-informed machine learning-aided framework

The critical heat flux (CHF) corresponding to the departure from nucleate boiling (DNB) crisis is a regulatory limit for the licensing of pressurized water reactors (PWRs) worldwide. Despite the abundance of predictive tools available to the reactor thermal-hydraulics community, the path for an accurate CHF model remains elusive. This work approaches the prediction of DNB through a physics-informed machine learning-aided framework (PIMLAF) with the objective of achieving superior predictive capabilities for a rod bundle. In view of the limitations in existing macro-scale physics-driven tools, an improved mechanistic model is first proposed, leveraging key concepts in the liquid sublayer dryout and bubble crowding mechanisms. Furthermore, the proposed mechanistic model is able to predict DNB in different heater geometries for a broad range of flow conditions without the need for recalibration. This model is then incorporated as the physics-informed component of the hybrid framework PIMLAF, which takes advantage of established understanding in the field (i.e., domain knowledge [DK]) and uses machine learning (ML) to capture undiscovered information from the mismatch between the actual and DK-predicted output. Two bundle-related case studies using the PWR subchannel and bundle tests (PSBT) database are carried out to illustrate the PIMLAF’s improved performance over traditional approaches for both interpolation and extrapolation purposes. In light of the PIMLAF’s promising potential to reduce prediction error, reactor vendors are encouraged to leverage their in-house experimental efforts and apply the hybrid framework to potentially achieve margin reductions in the minimum DNB ratio (MDNBR) for the designs of interest.

42 ENGINEERING↗