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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 163 records · Page 9
All sourcesNASA NTRSDOE OSTI
DOE OSTI2020

Distributed Resources for the Earth System Grid Federation (ESGF) Advanced Management (DREAM). Final Report

Distributed Resources for the Earth System Grid Federation (ESGF) Advanced Management (DREAM) is a proposed system that will enable data from an infinite number of diverse sources to be organized and accessed from anywhere using any handheld or other computer device. The approach offers a powerful roadmap for the creation and integration of a unified knowledge base of an entire ecosystem, including its many geophysical, geographical, social, political, agricultural, energy, transportation, and cyber aspects. The resulting aggregation of data has the potential to generate an informational universe of unprecedented size that has never before been possible due to the prohibitive costs, managerial complexity, and technical barriers associated with ever-changing exponential-growth data flows. We envision that DREAM will accelerate discovery by enabling climate researchers, among other types of researchers, to manage, analyze, and visualize data from earth-scale measurements and simulations. DREAM’s success will be built on proven components that leverage existing services and resources. A key building block for DREAM will be the ESGF, chaired by Dean N. Williams. Expanding on the existing ESGF, the project will ensure that the access, storage, movement, and analysis of the large quantities of data that are processed and produced by diverse science projects can be dynamically distributed with proper resource management. Much of the Office of Science data is currently generated by multiple stand-alone facilities. DREAM can collect data accumulated from these facilities and incorporate it into a fully integrated network accessible from anywhere in the world. The result is a completely new paradigm shift for data management, analysis, and visualization enabling researchers to: Manage their calculations, data, tools, and research results; Ensure that all data are sharable, reproducible and (re)usable—accompanied by appropriate metadata describing its provenance, syntax, and semantics at creation; Advance application performance by selectively adapting APIs and services in response to scientific requirements and architectural complexities; and Provide scalable interactive resource management—navigate data and metadata at multiple levels, provide architecture-aware data integration, analysis and visualization tools. We will engage closely with DOE, NASA, and NOAA science groups working at the leading edge of computing. These engagements—in domains such as biology, climate, and hydrology—will allow us to advance disciplinary science goals and inform our development of technologies that can accelerate discovery across DOE more broadly. We will advertise and promote our technologies via dedicated workshops, tutorials, and sessions at conferences, stand-alone events with broad inter-disciplinary invitation, and engagements with leadership facilities.

54 ENVIRONMENTAL SCIENCES↗
NASA NTRS2010

The New Face of Data Accessibility

Management of medical and research data at NASA's Johnson Space Center has been addressed with two separate, independent systems: the Lifetime Surveillance of Astronaut Health (formerly, The Longitudinal Study of Astronaut Health) (LSAH) and the Life Sciences Data Archive (LSDA). Project management for these has been autonomous with little or no cross-over of goals, objectives or strategy. The result has been limited debate and discussion regarding how contents from one repository might impact or guide the direction of the other. It is decidedly more efficient to use existing data and information than to re-generate them. Ensuring that both clinical and research data / information are accessible for review is a central concept to the decision to unify these repositories. In the past, research data from flight and ground analogs has been held in the LSDA and medical data held in the Electronic Medical Record or in console flight surgeon logs and records. There was little cross-pollination between medical and research findings and, as a result, applicable research was not being fully incorporated into clinical, in-flight practice. Conversely, findings by the console surgeon were not being picked up by the research community. The desired life cycle for risk mitigation was not being fully realized. The goal of unifying these repositories and processes is to provide a closely knit approach to handling medical and research data, which will not only engender discussion and debate but will also ensure that both categories of data and information are used to enhance the use of medical and research data to reduce risk and promote the understanding of space physiology, countermeasures and other mitigation strategies

Fitts, Mary A.↗
NASA NTRS1993

Development of a naming convention and data ma nagement system

This contract covered work in data management, acquisition, and analysis for the Earth Science and Applications Division (ESAD) of the Space Science Laboratory of MSFC. Under this contract, a naming convention and data management system were developed for ESAD data sets, data visualization, and standard data format issues were investigated, and specific data analysis and management needs were addressed for several ESAD projects and data sets. In the following sections, details of the research performed over the duration of this contract are summarized.

Mcnider, Richard T.↗
NASA NTRSDate not supplied

Materials Informatics at NASA GRC: Machine Learning Surrogate Modeling, Data Management, and Integrated Toolsets for Establishing/Maintaining the Digital Thread

Integrated Computational Materials Engineering (ICME) has recently received widespread attention due to its promises in reducing dependence on physical testing for engineering design by relying on simulation, reducing both time and cost to market for various applications. ICME however requires validated multiscale material models, which heavily depend on available test data with full material and test pedigree, including material processing, test and measurement equipment, raw data collection, and analysis methodology and results that is findable and usable, along with integrated, efficient toolsets for effectively passing information across various length and time scales across such models. At the NASA Glenn Research Center under the Transformational Tools and Technologies Project, significant recent efforts have been directed towards establishing the required cyberinfrastructure to enable optimized ICME processes and the design of “fit-for-purpose” materials to achieve the goals outlined in the NASA Vision 2040 report. Such efforts include development of multiscale physics-based material models, which can be used to train highly efficient surrogate machine learning models, development of best practices and infrastructure for effective, traceable materials information management, and development of toolsets that integrate with physics-based codes, machine learning models, and an information management system to enable high throughput of materials data collection and analysis, establishment of digital twins and the digital thread, and automation of the ICME design process for material optimization.

Machine Learning↗
NASA NTRS2010

The Kepler DB, a Database Management System for Arrays, Sparse Arrays and Binary Data

The Kepler Science Operations Center stores pixel values on approximately six million pixels collected every 30-minutes, as well as data products that are generated as a result of running the Kepler science processing pipeline. The Kepler Database (Kepler DB) management system was created to act as the repository of this information. After one year of ight usage, Kepler DB is managing 3 TiB of data and is expected to grow to over 10 TiB over the course of the mission. Kepler DB is a non-relational, transactional database where data are represented as one dimensional arrays, sparse arrays or binary large objects. We will discuss Kepler DB's APIs, implementation, usage and deployment at the Kepler Science Operations Center.

McCauliff, Sean↗
NASA NTRSDate not supplied

A CFD Validation Study using Artemis 1 Orbital Slosh Test Data

Advancements in liquid propellant management science and technologies are key to increasing safety, decreasing cost, and increasing payload mass of NASA space missions. Liquid propellant usually comprises a large portion of the total mass of launch vehicles and spacecraft, so predicting and controlling the motion of it are important. Computational fluid dynamics (CFD) programs are critical to predicting slosh dynamics, but CFD programs require experimental validation with physically relevant test data before the results can be trusted. Low-gravity slosh test data is lacking, and most of what exists is inadequate for CFD validation. A potential slosh risk for Orion, and the lack of validated low-gravity slosh models, led to performing on-orbit slosh tests during the Artemis 1 mission to assess the impacts of slosh on the guidance, navigation, and control of Orion. This work details the validation of a coupled slosh-motion CFD model using the Orion orbital slosh test data set.

CFD↗
NASA NTRSDate not supplied

A CFD Validation Study Using Artemis 1 Orbital Slosh Test Data

Advancements in liquid propellant management science and technologies are key to increasing safety, decreasing cost, and increasing payload mass of NASA space missions. Liquid propellant usually comprises a large portion of the total mass of launch vehicles and spacecraft, so predicting and controlling the motion of it are important. Computational fluid dynamics (CFD) programs are critical to predicting slosh dynamics, but CFD programs require experimental validation with physically relevant test data before the results can be trusted. Low-gravity slosh test data is lacking, and most of what exists is inadequate for CFD validation. A potential slosh risk for Orion, and the lack of validated low-gravity slosh models, led to performing on-orbit slosh tests during the Artemis 1 mission to assess the impacts of slosh on the guidance, navigation, and control of Orion. This work details the validation of a coupled slosh-motion CFD model using the Orion orbital slosh test data set.

CFD↗
NASA NTRS2007

NASA Tech Briefs, December 2007

Topics include: Ka-Band TWT High-Efficiency Power Combiner for High-Rate Data Transmission; Reusable, Extensible High-Level Data-Distribution Concept; Processing Satellite Imagery To Detect Waste Tire Piles; Monitoring by Use of Clusters of Sensor-Data Vectors; Circuit and Method for Communication Over DC Power Line; Switched Band-Pass Filters for Adaptive Transceivers; Noncoherent DTTLs for Symbol Synchronization; High-Voltage Power Supply With Fast Rise and Fall Times; Waveguide Calibrator for Multi-Element Probe Calibration; Four-Way Ka-Band Power Combiner; Loss-of-Control-Inhibitor Systems for Aircraft; Improved Underwater Excitation-Emission Matrix Fluorometer; Metrology Camera System Using Two-Color Interferometry; Design and Fabrication of High-Efficiency CMOS/CCD Imagers; Foam Core Shielding for Spacecraft CHEM-Based Self-Deploying Planetary Storage Tanks Sequestration of Single-Walled Carbon Nanotubes in a Polymer PPC750 Performance Monitor Application-Program-Installer Builder Using Visual Odometry to Estimate Position and Attitude Design and Data Management System Simple, Script-Based Science Processing Archive Automated Rocket Propulsion Test Management Online Remote Sensing Interface Fusing Image Data for Calculating Position of an Object Implementation of a Point Algorithm for Real-Time Convex Optimization Handling Input and Output for COAMPS Modeling and Grid Generation of Iced Airfoils Automated Identification of Nucleotide Sequences Balloon Design Software Rocket Science 101 Interactive Educational Program Creep Forming of Carbon-Reinforced Ceramic-Matrix Composites Dog-Bone Horns for Piezoelectric Ultrasonic/Sonic Actuators Benchtop Detection of Proteins Recombinant Collagenlike Proteins Remote Sensing of Parasitic Nematodes in Plants Direct Coupling From WGM Resonator Disks to Photodetectors Using Digital Radiography To Image Liquid Nitrogen in Voids Multiple-Parameter, Low-False-Alarm Fire-Detection Systems Mosaic-Detector-Based Fluorescence Spectral Imager Plasmoid Thruster for High Specific-Impulse Propulsion Analysis Method for Quantifying Vehicle Design Goals Improved Tracking of Targets by Cameras on a Mars Rover Sample Caching Subsystem Multistage Passive Cooler for Spaceborne Instruments GVIPS Models and Software Stowable Energy-Absorbing Rocker-Bogie Suspensions

Source record↗
DOE OSTI2024

Urbanization and malaria have a contextual relationship in endemic areas: A temporal and spatial study in Ghana

In West Africa, malaria is one of the leading causes of disease-induced deaths. Existing studies indicate that as urbanization increases, there is corresponding decrease in malaria prevalence. However, in malaria-endemic areas, the prevalence in some rural areas is sometimes lower than in some peri-urban and urban areas. Therefore, the relationship between the degree of urbanization, the impact of living in urban areas, and the prevalence of malaria remains unclear. This study explores this association in Ghana, using epidemiological data at the district level (2015–2018) and data on health, hygiene, and education. We applied a multilevel model and time series decomposition to understand the epidemiological pattern of malaria in Ghana. Then we classified the districts of Ghana into rural, peri-urban, and urban areas using administratively defined urbanization, total built areas, and built intensity. We converted the prevalence time series into cross-sectional data for each district by extracting features from the data. To predict the determinant most impacting according to the degree of urbanization, we used a cluster-specific random forest. We find that prevalence is impacted by seasonality, but the trend of the seasonal signature is not noticeable in urban and peri-urban areas. While urban districts have a slightly lower prevalence, there are still pockets with higher rates within these regions. These areas of high prevalence are linked to proximity to water bodies and waterways, but the rise in these same variables is not associated with the increase of prevalence in peri-urban areas. The increase in nightlight reflectance in rural areas is associated with an increased prevalence. We conclude that urbanization is not the main factor driving the decline in malaria. However, the data indicate that understanding and managing malaria prevalence in urbanization will necessitate a focus on these contextual factors. Finally, we design an interactive tool, ’malDecision’ that allows data-supported decision-making.

60 APPLIED LIFE SCIENCES↗
NASA NTRSDate not supplied

Leveraging Nurse Informaticists for Development of the Impact Tool

The American Nurses Association (ANA) defines nursing informatics as the integration of “nursing science, computer science, and information science to manage and communicate data, information, knowledge, and wisdom in nursing practice. [1]” In additional to nursing education and clinical experience, this field requires additional education in areas of data analysis, database management, and clinical information systems. Nursing informaticists help bridge the communication gap between clinical and technical stakeholders which help align common goals. NASA is currently developing a new medical system trade analysis and decision support tool called IMPACT (Informing Mission Planning via Analysis of Complex Tradespaces). The development team is comprised of multiple specialties including but not limited to clinicians (pharmacists, physicians, and nurse informaticists), software and program developers, human factors experts, and engineers. The nurse informaticists play a significant role in the development, operation, and results interpretation of IMPACT. Their expert knowledge and skills in both clinical nursing, information science, and database management place them in a unique position to collaborate and integrate with the clinical, engineering, and software development members of the team to achieve a cohesive, functional, and user-friendly model.

Lynn Boley↗
DOE OSTI2023

Data Privacy for the Grid: Toward a Data Privacy Standard for Inverter-Based and Distributed Energy Resources

The traditional approach to planning the distribution grid has focused on reliability in the context of gradual and reasonably predictable load growth. Forecasts of load growth, combined with asset management practices, were used by system planners to identify upgrades to the system to maintain or improve reliability. The decisions, typically based within load flow analysis tools, included considerations about contingency scenarios and corporate forecasts (i.e., top-down predictions at a summary level of what would happen in a particular area that could impact load growth and behavior). As a result, today, this traditional approach no longer fits all purposes.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗
NASA NTRS2020

Accelerating Space Life Sciences: Successes and Challenges of Biospecimen and Data Sharing

NASA's current human space flight research is directed towards enabling human space exploration beyond Low Earth Orbit (LEO). To that end, NASA Space Flight Payload Projects; Rodent Research, Cell Science, and Microbial Labs, flown on the International Space Station (ISS), benefit the global life sciences and commercial space communities. Verified data sets, science results, peer-reviewed publications, and returned biospecimens, collected and analyzed for flight and ground investigations, are all part of the knowledge base collected by NASA's Human Exploration and Operations Mission Directorate's Space Life and Physical Sciences Research and Applications (SLPSRA) Division, specifically the Human Research and Space Biology Programs. These data and biospecimens are made available through the public Life Sciences Data Archive (LSDA) website to promote basic discovery, pre-clinical and clinical science.The NASA Institutional Scientific Collection (ISC), stores flight and ground biospecimens from Space Shuttle and ISS programs. These specimens are curated and managed by the Ames Life Sciences Data Archive (ALSDA), an internal node of NASA's LSDA. The ISC stores over 30,000 specimens from experiments dating from 1984 to present. Currently available specimens include tissues from the circulatory, digestive, endocrine, excretory, integumentary, muscular, neurosensory, reproductive, respiratory and skeletal systems.NASA's biospecimen collection represents a unique and limited resource of unique spaceflight payload and ground control research subjects. These specimens are harvested according to well established SOPs that maintain their quality and integrity. Once the primary scientific objectives have been met, the remaining specimens are made available to provide secondary opportunities for complementary studies or new investigations to broaden research without large expenditures of time or resources. Website: https://lsda.jsc.nasa.gov/

Scott, Ryan T.↗
NASA NTRS2008

Experiences in Bridging the Gap between Science and Decision Making at NASA's GSFC Earth Science Data and Information Services Center (GES DISC)

Recognizing the significance of NASA remote sensing Earth science data in monitoring and better understanding our planet s natural environment, NASA has implemented the Decision Support Through Earth Science Research Results program (NASA ROSES solicitations). a) This successful program has yielded several monitoring, surveillance, and decision support systems through collaborations with benefiting organizations. b) The Goddard Space Flight Center (GSFC) Earth Sciences Data and Information Services Center (GES DISC) has participated in this program on two projects (one complete, one ongoing), and has had opportune ad hoc collaborations gaining much experience in the formulation, management, development, and implementation of decision support systems utilizing NASA Earth science data. c) In addition, GES DISC s understanding of Earth science missions and resulting data and information, including data structures, data usability and interpretation, data interoperability, and information management systems, enables the GES DISC to identify challenges that come with bringing science data to decision makers. d) The purpose of this presentation is to share GES DISC decision support system project experiences in regards to system sustainability, required data quality (versus timeliness), data provider understanding of how decisions are made, and the data receivers willingness to use new types of information to make decisions, as well as other topics. In addition, defining metrics that really evaluate success will be exemplified.

Kempler, Steven↗
NASA NTRS1994

Automatic cataloguing and characterization of Earth science data using SE-trees

In the future, NASA's Earth Observing System (EOS) platforms will produce enormous amounts of remote sensing image data that will be stored in the EOS Data Information System. For the past several years, the Intelligent Data Management group at Goddard's Information Science and Technology Office has been researching techniques for automatically cataloguing and characterizing image data (ADCC) from EOS into a distributed database. At the core of the approach, scientists will be able to retrieve data based upon the contents of the imagery. The ability to automatically classify imagery is key to the success of contents-based search. We report results from experiments applying a novel machine learning framework, based on Set-Enumeration (SE) trees, to the ADCC domain. We experiment with two images: one taken from the Blackhills region in South Dakota; and the other from the Washington DC area. In a classical machine learning experimentation approach, an image's pixels are randomly partitioned into training (i.e. including ground truth or survey data) and testing sets. The prediction model is built using the pixels in the training set, and its performance is estimated using the testing set. With the first Blackhills image, we perform various experiments achieving an accuracy level of 83.2 percent, compared to 72.7 percent using a Back Propagation Neural Network (BPNN) and 65.3 percent using a Gaussain Maximum Likelihood Classifier (GMLC). However, with the Washington DC image, we were only able to achieve 71.4 percent, compared with 67.7 percent reported for the BPNN model and 62.3 percent for the GMLC.

Rymon, Ron↗
DOE OSTI2024

DMTN-102: LSST Alerts: Key Numbers

A quantitative review of the key numbers associated with the Legacy Survey of Space and Time (LSST) Alert Stream.

79 ASTRONOMY AND ASTROPHYSICS↗
NASA NTRS1982

NASA-ESA Spacelab systems and programs; Proceedings of the Seminar, Washington, DC, April 23, 24, 1981

Topics discussed include the development status of the Space Shuttle and Spacelab, with attention to Spacelab subsystem performance capabilities and Shuttle-Spacelab flight operations; Spacelab data management and software for science applications, ESA and Space Shuttle pointing systems, and the Space Shuttle's Office of Space and Terrestrial Applications (OSTA)-1 payload. Also covered are the lessons learned from the first Spacelab mission, the pallet-only mode verification flight of the second Spacelab mission, the objectives of the Spacelab mission D1, its role in the German space program, and its implementation, the impact of Spacelab on space-based life sciences research, the high resolution, large area modular reflector array X-ray telescope to be used by Spacelab, and Space Shuttle contamination effects on UV coronagraphic observations.

Moore, J. W.↗
NASA NTRS1985

An innovative, multidisciplinary educational program in interactive information storage and retrieval. Presentation visuals

This Working Paper Series entry represents a collection of presentation visuals associated with the companion report entitled An Innovative, Multidisciplinary Educational Program in Interactive Information Storage and Retrieval, USL/DBMS NASA/RECON Working Paper Series report number DBMS.NASA/RECON-12. The project objectives are to develop a set of transportable, hands-on, data base management courses for science and engineering students to facilitate their utilization of information storage and retrieval programs.

Dominick, Wayne D.↗
NASA NTRS2017

Kepler: A Search for Terrestrial Planets - SOC 9.3 DR25 Pipeline Parameter Configuration Reports

This document describes the manner in which the pipeline and algorithm parameters for the Kepler Science Operations Center (SOC) science data processing pipeline were managed. This document is intended for scientists and software developers who wish to better understand the software design for the final Kepler codebase (SOC 9.3) and the effect of the software parameters on the Data Release (DR) 25 archival products.

exoplanet↗