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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 109 records · Page 6
All sourcesNASA NTRSDOE OSTI
NASA NTRS1993

MAC Europe 1991 campaign: AIRSAR/AVIRIS data integration for agricultural test site classification

During summer 1991, multi-sensor data were acquired over the Italian test site 'Otrepo Pavese', an agricultural flat area in Northern Italy. This area has been the Telespazio pilot test site for experimental activities related to agriculture applications. The aim of the investigation described in the following paper is to assess the amount of information contained in the AIRSAR (Airborne Synthetic Aperture Radar) and AVIRIS (Airborne Visible/Infrared Imaging Spectrometer) data, and to evaluate classification results obtained from each sensor data separately and from the combined dataset. All classifications are examined by means of the resulting confusion matrices and Khat coefficients. Improvements of the classification results obtained by using the integrated dataset are finally evaluated.

Sangiovanni, S.↗
DOE OSTI2024

A Framework to Demonstrate a DNP3 Interface With a CIM-Based Data Integration Platform: Preprint

The contemporary electrical grid is characterized by its complexity and abundance of data. A control-rich environment supported by information and communication technologies within an Advanced Distribution Management System (ADMS) presents a viable and cost-effective option for utility companies aiming to implement advanced real-time analytical schemes for monitoring and remotely controlling distribution feeders. Modular platform-based approaches to distribution operations require a structured framework for acquiring field device measurements, performing analytics, converting the setpoint to the correct protocol, and sending it on the appropriate communications network to the field devices. We present the development and deployment of an application service to integrate an open-source standardsbased platform with an ADMS test bed with field devices using the Distributed Network Protocol (DNP3) for data exchange. The step-by-step procedure for establishing the DNP3-Master service on an open-source distribution platform is outlined, comprehensively explaining the Master setup process. Moreover, sample use case results highlight the capabilities of the DNP3- Master service setup. Results demonstrate the scalability and configurability of the DNP3-Master service, making it adaptable for integration with other relevant applications, thus providing potential opportunities for real-world field trials and real-time assessments.

ADMS↗
DOE OSTI2021

Abridged spectral matrix inversion: parametric fitting of X-ray fluorescence spectra following integrative data reduction

Recent improvements in both X-ray detectors and readout speeds have led to a substantial increase in the volume of X-ray fluorescence data being produced at synchrotron facilities. This in turn results in increased challenges associated with processing and fitting such data, both temporally and computationally. Herein an abridging approach is described that both reduces and partially integrates X-ray fluorescence (XRF) data sets to obtain a fivefold total improvement in processing time with negligible decrease in quality of fitting. The approach is demonstrated using linear least-squares matrix inversion on XRF data with strongly overlapping fluorescent peaks. This approach is applicable to any type of linear algebra based fitting algorithm to fit spectra containing overlapping signals wherein the spectra also contain unimportant (non-characteristic) regions which add little (or no) weight to fitted values, e.g. energy regions in XRF spectra that contain little or no peak information.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
NASA NTRS2016

NASA/GEWEX Surface Radiation Budget: Integrated Data Product With Reprocessed Radiance, Cloud, and Meteorology Inputs, and New Surface Albedo Treatment

The NASA/GEWEX Surface Radiation Budget (SRB) project produces shortwave and longwave surface and top of atmosphere radiative fluxes for the 1983-near present time period. Spatial resolution is 1 degree. The current release 3.0 (available at gewex-srb.larc.nasa.gov) uses the International Satellite Cloud Climatology Project (ISCCP) DX product for pixel level radiance and cloud information. This product is subsampled to 30 km. ISCCP is currently recalibrating and recomputing their entire data series, to be released as the H product, at 10km resolution. The ninefold increase in pixel number will allow SRB a higher resolution gridded product (e.g. 0.5 degree), as well as the production of pixel-level fluxes. In addition to the input data improvements, several important algorithm improvements have been made. Most notable has been the adaptation of Angular Distribution Models (ADMs) from CERES to improve the initial calculation of shortwave TOA fluxes, from which the surface flux calculations follow. Other key input improvements include a detailed aerosol history using the Max Planck Institut Aerosol Climatology (MAC), temperature and moisture profiles from HIRS, and new topography, surface type, and snow/ice. Here we present results for the improved GEWEX Shortwave and Longwave algorithm (GSW and GLW) with new ISCCP data, the various other improved input data sets and the incorporation of many additional internal SRB model improvements. As of the time of abstract submission, results from 2007 have been produced with ISCCP H availability the limiting factor. More SRB data will be produced as ISCCP reprocessing continues. The SRB data produced will be released as part of the Release 4.0 Integrated Product, recognizing the interdependence of the radiative fluxes with other GEWEX products providing estimates of the Earth's global water and energy cycle (I.e., ISCCP, SeaFlux, LandFlux, NVAP, etc.).

Cox, Stephen J.↗
DOE OSTI2025

Accelerating Nuclear-Integrated Data Centers in the USA: SWOT Analysis, Power-Thermal Management Strategies, and Industrial-Scale Demonstration and Potential Deployment

Driven by the growth in digital services, cloud computing, AI, and manufacturing, data centers face rising energy demands that challenge traditional power sources and cooling efficiency. This study explores using nuclear power to meet these demands, focusing on accelerated reactor technology deployment and highlighting needs such as N+1/N+2 power supplies and integrated power-thermal management. A SWOT analysis addresses grid connectivity, reactors, and site selection, particularly DOE sites. Reactor technology demonstration and deployment could be accelerated by leveraging test facilities such as MARVEL, MAGNET, TED, FAS, DOME, LOTUS, ATR, Energy System Proving Grounds, and upcoming Energy Launch Pads, along with modeling and simulation tools such as RELAP5, MOOSE, VERA, RAVEN, and FORCE. The potential power and thermal management options, including various cooling technologies, waste-heat utilization, and an industrial-scale demonstration plan, aim to accelerate the integration of nuclear power and data centers in the USA, while emphasizing community and stakeholder engagement and synergistic efforts.

21 - SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLAN↗
NASA NTRS1995

Analyses of TIMS and AVIRIS data, integrated with field and laboratory spectra, for lithological and mineralogical interpretation of Vulcano Island, Italy

Vulcano Island is part of the Eolian archipelago, located about 25 km from the northeast coast of Sicily. The archipelago comprises seven major volcanic islands, two of which are active volcanoes (Vulcano and Stromboli). Vulcano covers an area of about 50 square km, and is about 10 km long. Explosive volcanic activity has predominated in the geological evolution of Vulcano Island, and there is no evidence that this pattern has ceased. Rather, the current situation is one of unrest, so a strict regimen of continuous geophysical and geochemical monitoring has been undertaken over the last decade. Though the year-round population of Vulcano is small (under 1000), during the summer the island becomes a very popular resort, and has thousands of additional tourists at any time throughout the high season, thus substantially increasing the number of people potentially at risk from an explosive eruption or other hazards such as noxious gas emissions (e.g., CO2, H2S, SO2). During the past ten years, remote sensing data have been repetitively acquired with optical and microwave airborne sensors. The present work shows the preliminary results of a study based on the integration of various remote sensing data sets with field spectroscopy, and other laboratory analyses, for the geological and geomorphological mapping of the island. It is hoped that such work will also usefully contribute to the evaluation of the volcanic hazard potential of the islands as well as to the evaluation of the status of its current activity.

Buongiorno, M. Fabrizia↗
NASA NTRS2019

Overcoming the Challenges of Data Integration and Automation

Artificial Intelligence (AI) and machine learning (ML) are gaining increased attention as a way to leverage the world's data to solve problems. Although AI and ML offer much potential, there are often misconceptions about the application of such techniques. This panel discussion includes speakers from airlines and the research community who will present machine learning approaches they have developed on a variety of aviation data including digital flight data, safety reporting data, and traffic flow data. They will explain the purpose of the application, the data used, and the lessons learned in the development and deployment of their solutions. The panel discussion will focus on common pitfalls in developing and AI solution, the dangers of the current hype around AI, tips for gaining value from a machine learning solution, how to determine whether a machine learning approach is appropriate for a problem, and more.

Matthews, Bryan L.↗
NASA NTRS2018

RNAV Adherence Data Integration System Using Aviation and Environmental Sources

The RADI system described in this technical memorandum outlines a framework that can be used to fuse a variety of data including surveillance recordings, environmental observations, and procedural information to produce features that would otherwise not be observable by any single data source. The process is designed with scalability in mind so that large scale batch processing can be executed on a typical distributed cluster environment. This process was initially developed as a prototype to quickly assess adherence and iterate and engineer relevant features of interest that can assist in determining factors for non-adherence to procedural requirements.

Avrekh, Ilya↗
DOE OSTI2024

Risk-informed Hierarchical Control of Behind-the-Meter DERs with AMI Data Integration (Final Technical Report)

This project addresses several key barriers to implement the next generation demand response applications and provides a clear understanding of implementing hierarchical and standalone control using AMI data. Through this program, Eaton has developed and tested a meter-as-a-controller prototype with the help of other partners--- National Renewable Energy Laboratory (NREL), Electric Power Research Institute (EPRI), Pecan St Inc. (PSI), and Delaware Electric Cooperative (DEC). The controller can utilize residential controllable loads such as heating, ventilation, and air conditioner (HVAC), electric water heater and distributed energy resources like solar PV and battery energy storage systems for off-setting the demand that is required from the grid, thus providing reliable grid-services for demand reduction or peak shaving. The controller is also capable of coordinating the resources of the premises for better management and energy efficiency while meeting the comfort bound of the premises owner as quality-of-service. The development has been demonstrated in a three virtual-home setup at system performance lab of NREL with real appliances (HVAC, electric water heater, solar PV, and battery). The technology has also been proved through laboratory and field demonstration with successful interconnectivity (e.g., end-to-end communication and data exchange) between the residential appliances and utility through the RF network at Delaware Electric Co-op (DEC) in Delaware.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2021

Using machine learning and artificial intelligence to improve model-data integrated earth system model predictions of water and carbon cycle extremes

The research proposed here focuses on improving the predictive power of the land component of earth system models (ESMs) using (1) model-data fusion enabled by machine learning (ML) and artificial intelligence (AI), (2) predictive modeling through the combination of ML, AI, and big-data (comprising both model output and observations), and (3) insight of ESM structure and process mechanisms gleaned from complex data using ML and AI.

54 ENVIRONMENTAL SCIENCES↗
NASA NTRS2006

Linking Asthma Exacerbation and Air Pollution Data: A Step Toward Public Health and Environmental Data Integration

Studies have shown that reducing exposure to triggers such as air pollutants can reduce symptoms and the need for medication in asthma patients. However, systems that track asthma are generally not integrated with those that track environmental hazards related to asthma. Tlvs lack of integration hinders public health awareness and responsiveness to these environmental triggers. The current study is a collaboration between health and environmental professionals to utilize NASA-derived environmental data to develop a decision support system (DSS) for asthma prediction, surveillance, and intervention. The investigators link asthma morbidity data from the University of Mississippi Medical Center (UMMC) and Mississippi Department of Health (MDH) with air quality data from the Mississippi Department of Environmental Quality (MDEQ) and remote sensing data from NASA. Daily ambient environmental hazard data for PM2.5 and ozone are obtained from the MDEQ air quality monitoring locations and are combined with remotely sensed data from NASA to develop a state-wide spatial and time series profile of environmental air quality. These data are then used to study the correlation of these measures of air quality variation with the asthma exacerbation incidence throughout the state over time. The goal is to utilize these readily available measures to allow real-time risk assessment for asthma exacerbations. GeoMedStat, a DSS previously developed for biosurveillance, will integrate these measures to monitor, analyze and report the real-time risk assessment for asthma exacerbation throughout the state.

Faruque, Fazlay↗
NASA NTRSDate not supplied

GeneLab: Current and Future Omics Data Integration Between Space Biology and HRP

For the past five years, the Biological and Physical Sciences Division has pioneered Open Science in Space Biology by funding the NASA GeneLab project. Along with the Ames Life Sciences Data Archive, GeneLab has quickly become the world leader in archiving and scientifically curating spaceflight and spaceflight relevant multi-omics data. Specifically, the GeneLab Data System has become a full enterprise solution providing advanced mining capabilities, several application programming interfaces for data federation and machine learning approaches, and delivering to the world an analytical and visualization platform which has enabled collaboration within the scientific community. Over the past three years, large meta-analysis and modeling studies have been published by the GeneLab Analysis Working Groups (AWGs), which are comprised of ~200 volunteer scientists. One natural extension of GeneLab data reuse has recently turned towards linking animal data with human data, which is the next necessary step to further validate animal models for inferring biological risks to humans conducting LEO, lunar or Martian missions. As such, data from the Human Research Program are an essential component of GeneLab and ALSDA. At the moment, simulated space radiation experiments conducted at Brookhaven National Laboratory make the most of HRP GeneLab data, and the scientific community has been eager to also link their animal spaceflight results to actual Astronaut data and human analog data. We will discuss further the current status of knowledge and future approaches to accelerate our basics understanding of the impact of space stressors on humans using latest omics technology.

omics↗
NASA NTRS1973

Design specification for a general purpose Data Integration and Display System (DIDS)

The capability for any program written in FORTRAN or XSYMBOL to display its output is provided. Displays are presented on the Biomed Console CRT, the COMPLOT X-Y plotter or both. The display of data stored on magnetic tape is accomplished without the necessity of coding a program. The keyboard on the Biomed Console or the teletype was designed to be the user's interface with DIDS to call displays stored on magnetic tape.

Source record↗
DOE OSTI2025

High-frequency Data Integration for Landscape Model Calibration of Carbon Fluxes Across Diverse Tidal Marshes

Terrestrial Aquatic Interfaces (TAIs), and tidal wetlands in particular, store large amounts of carbon yet are not well represented in Earth System Models (ESMs). Predictions of carbon cycling and greenhouse gas (GHG) emissions in tidal wetlands are highly uncertain. Eddy covariance (EC) towers provide ecosystem-scale GHG flux data at a temporal resolution (every 30min) that is helpful for parameterizing and improving mechanistic realism in ESMs. We propose to use a network of eddy covariance towers and standardized ancillary data streams, along with mesocosm experiments and statistical analyses, across diverse tidal wetlands of North America to develop and improve biogeochemical modeling at the TAI. Our overarching objective is to improve understanding and process-based modeling of gross primary productivity (GPP) and CH4 emission responses, both non-linear and asynchronous, to stressors including plant inundation, disturbance, salinity and nitrogen loading.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2019

The Monarch Initiative in 2019: an integrative data and analytic platform connecting phenotypes to genotypes across species

In biology and biomedicine, relating phenotypic outcomes with genetic variation and environmental factors remains a challenge: patient phenotypes may not match known diseases, candidate variants may be in genes that haven’t been characterized, research organisms may not recapitulate human or veterinary diseases, environmental factors affecting disease outcomes are unknown or undocumented, and many resources must be queried to find potentially significant phenotypic associations. The Monarch Initiative (https://monarchinitiative.org) integrates information on genes, variants, genotypes, phenotypes and diseases in a variety of species, and allows powerful ontology-based search. We develop many widely adopted ontologies that together enable sophisticated computational analysis, mechanistic discovery and diagnostics of Mendelian diseases. Our algorithms and tools are widely used to identify animal models of human disease through phenotypic similarity, for differential diagnostics and to facilitate translational research. Launched in 2015, Monarch has grown with regards to data (new organisms, more sources, better modeling); new API and standards; ontologies (new Mondo unified disease ontology, improvements to ontologies such as HPO and uPheno); user interface (a redesigned website); and community development. Monarch data, algorithms and tools are being used and extended by resources such as GA4GH and NCATS Translator, among others, to aid mechanistic discovery and diagnostics.

59 BASIC BIOLOGICAL SCIENCES↗
NASA NTRS2012

Integrated Data Modeling and Simulation on the Joint Polar Satellite System Program

The Joint Polar Satellite System is a modern, large-scale, complex, multi-mission aerospace program, and presents a variety of design, testing and operational challenges due to: (1) System Scope: multi-mission coordination, role, responsibility and accountability challenges stemming from porous/ill-defined system and organizational boundaries (including foreign policy interactions) (2) Degree of Concurrency: design, implementation, integration, verification and operation occurring simultaneously, at multiple scales in the system hierarchy (3) Multi-Decadal Lifecycle: technical obsolesce, reliability and sustainment concerns, including those related to organizational and industrial base. Additionally, these systems tend to become embedded in the broader societal infrastructure, resulting in new system stakeholders with perhaps different preferences (4) Barriers to Effective Communications: process and cultural issues that emerge due to geographic dispersion and as one spans boundaries including gov./contractor, NASA/Other USG, and international relationships.

Roberts, Christopher J.↗
NASA NTRS1977

Development of an integrated data base for land use and water quality planning

To help understand the role played by different land resources in water quality management a computer based data system was created. The Land Resource Information System (LRIS) allows data to be readily retrieved or statistically analyzed for a variety of purposes. It is specifically formatted to perform coordination of water quality data with logy, etc. New understanding of the region gained through the use of LRIS has gone well beyond the initial purpose of assessing water quality conditions. The land use and natural features information has provided a well defined starting point for a systematic evaluation of proposed land uses, transportation, housing, and other public investments. It has laid the foundation for a comprehensive and integrated approach to many different planning and investment programs presently underway.

Adams, J.↗