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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 253 records · Page 14
All sourcesNASA NTRSDOE OSTI
NASA NTRS2018

Future of Big Earth Data Analytics

The state of the art of Big Earth Data Analytics can be expected to evolve rapidly in the coming years. The forces driving evolution come from both growth in the data and advancement in the field of data analytics. In the data area, advances in sensor instrumentation and platform miniaturization are increasing both data resolution and coverage, resulting in enormous growth in data Volume. Increases in temporal resolution in particular also generate demands for higher data Velocity. At the same time, the proliferation of instruments and the platforms on which they reside is increasing the Variety of datasets. The Variety increase in turn leads to questions about the Veracity of the data. In the algorithm area, powerful machine learning methods are coming to the fore, particularly Deep Neural Networks. These are powerful at detecting interesting features in the data, integrating many different measurements (i.e., data fusion), and classification problems. However, they are still challenging when seeking explanations of how natural or socio-economic phenomena work using Earth Observations. Thus, classical analysis techniques will remain relevant when the emphasis is on forming or testing explanations, as well as to support interactive data exploration.

Lynnes, Christopher↗
DOE OSTI2025

Summary of the 5th IAEA technical meeting on fusion data processing, validation and analysis (FDPVA)

The purpose of the 5th International Atomic Energy Agency technical meeting on fusion data processing, validation and analysis (FDPVA) (Ghent University, Ghent, Belgium, 12–15 June 2023) was to provide a platform during which a set of topics relevant to FDPVA were discussed with the view of meeting the needs of next step fusion devices such as ITER. The validation and analysis of experimental data obtained from diagnostics used to characterize fusion plasmas are crucial for a knowledge-based understanding of the physical processes governing the dynamics of these plasmas. This paper presents the recent progress and achievements in the domain of plasma diagnostics data analysis and synthetic diagnostics reported at the meeting, including concept description of new devices; fusion databases; integrated data analysis; inverse problems; uncertainty propagation, verification and validation; probabilistic methods and machine learning. The relevant results underline trends observed in the current major fusion confinement devices.

fusion databases↗
NASA NTRS1985

Application of laser anemometry to turbomachinery flow field measurements

The application of laser anemometry to the measurement of turbomachinery flow fields is reviewed. Choices of optical configuration, seed particle generation, and seed injection techniques are discussed. The modification of experimental facilities to gain optical access is considered. The efficiency of data acquisition schemes is analyzed and issues related to data integrity and error estimation are addressed. Data reduction and analysis techniques for extracting and understanding the flow physics from laser anemometer measurements are presented.

Strazisar, A. J.↗
NASA NTRS1998

Real-Time Sensor Validation System Developed

Real-time sensor validation improves process monitoring and control system dependability by ensuring data integrity through automated detection of sensor data failures. The NASA Lewis Research Center, Expert Microsystems, and Intelligent Software Associates have developed an innovative sensor validation system that can automatically detect automated sensor failures in real-time for all types of mission-critical systems. This system consists of a sensor validation network development system and a real-time kernel. The network development system provides tools that enable systems engineers to automatically generate software that can be embedded within an application. The sensor validation methodology captured by these tools can be scaled to validate any number of sensors, and permits users to specify system sensitivity. The resulting software reliably detects all types of sensor data failures.

Zakrajsek, June F.↗
NASA NTRS2007

GRO J1655-40: Early Stages of the 2005 Outburst

The black-hole X-ray binary transient GRO J1655-40 underwent an outburst beginning in early 2005. We present the results of our multi-wavelength observational campaign to study the early outburst spectral and temporal evolution, which combines data from X-ray (RXTE, INTEGRAL), radio (VLA) and optical (ROTSE, SMARTS) instruments. During the reported period the source left quiescence and went through four major accreting black hole states: low-hard, hard intermediate, soft intermediate and high-soft. We investigated dipping behavior in the RXTE band and compare our results to the 1996-1997 case, when the source was predominantly in the high-soft state, finding significant differences. We consider the evolution of the low frequency quasi-periodic oscillations and find that the frequency strongly correlates with the spectral characteristics, before shutting off prior to the transition to the high-soft state. We model the broad-band high-energy spectrum in the context of empirical models, as well as more physically motivated thermal and bulk-motion Comptonization and Compton reflection models. RXTE and INTEGRAL data together support a statistically significant high energy cut-off in the energy spectrum at approximately equal to 100 - 200 keV during the low-hard state. The RXTE data alone also show it very significantly during the transition, but cannot see one in the high-soft state spectra. We consider radio, optical and X-ray connections in the context of possible synchrotron and synchrotron self-Compton origins of X-ray emission in low-hard and intermediate states. In this outburst of GRO J1655-40, the radio flux does not rise strongly with the X-ray flux.

Shaposhnikov, N.↗
NASA NTRS2007

Improving an Atlantic Fisheries DSS using Sea Surface Salinity Data from NASA's Aquarius Mission

This report assesses the capacity of incorporating NASA#s Aquarius SSS (sea surface salinity) data into the SMAST (School of Marine Science and Technology) DSS for Fisheries Science. This data will enhance the SMAST DSS by providing SSS over a large area. Aquarius is a focused satellite mission designed to measure global SSS. SSS mapping is limited because conventional in situ SSS sampling is too sparse to give a large-scale view of the salinity variability. Aquarius will resolve missing physical processes that link the water cycle, the climate, and the ocean. The SMAST Fisheries program provides a DSS for fisheries science. It collects fisheries and environmental data, integrates them into a suite of data assimilation ocean models, and provides hindcasts, nowcasts, and forecasts for fisheries research, fisheries management, and the fishery industry. Currently, SMAST is using SSS data from the National Oceanic and Atmospheric Administration#s National Data Buoy Center. The SMAST DSS would be enhanced with SSS data from the Aquarius mission.

Guest, DeNeice↗
NASA NTRSDate not supplied

NASA GLOBE CLOUD GAZE: Creating Data Quality Flags for Citizen Science Cloud Observations Matched to NASA Satellite Data

The GLOBE Program, NASA’s largest and longest lasting citizen science program about the Earth, has been collecting cloud observations matched to multiple satellite data daily. The program’s cloud protocol is historically the most popular protocol as your eyes are the only instruments you need to collect observations of the sky. This dataset includes over 3,300,000 cloud observations with variables like total cloud cover, cloud type and opacity that are collocated to the nearest overpass times of geostationary satellites (GOES-15, GOES-16, GOES-17, Meteosat-8, Meteosat-11, or Himawari-8), or to Clouds and the Earth’s Radiant Energy System (CERES) instruments onboard Aqua and Terra, or the Cloud–Aerosol Lidar and Infrared Pathfinder Satellite Observations (CALIPSO) satellite. In order to increase the usability of this dataset, the Community science project Leveraging Online and User Data through GLOBE And Zooniverse Engagement (CLOUD GAZE) has been developed to generate data quality flags of these ground-up and top-down perspectives of sky and clouds. Recently funded through NASA’s Citizen Science for Earth Systems Program, CLOUD GAZE has partnered with the Zooniverse online platform to obtain reference data and image tagging of sky photographs collected through The GLOBE Program’s clouds protocol. This paper will present the GLOBE Clouds dataset matched to NASA satellite data, integration of CLOUD GAZE to develop data quality flags, and research applications of the dataset (includes ground-up and top-down perspective comparisons, ground observations of dust storms and smoke plumes, and cloud observations in polar regions). The paper will also present on techniques and recommendations for classroom use and for community engagement, particularly for those looking to online resources.

Marilé Colón Robles↗
DOE OSTI2024

4th Big Data for Nuclear Power Plants Workshop 2023

The Ohio State University and Idaho National Laboratory organized the 4 th Big Data for Nuclear Power Plants Workshop in November, 2023 in Columbus, Ohio. Workshop topics were chosen to understand the challenges and gaps that need to be addressed to maximize the impact of data on the nuclear industry, as well as the associated applications and risks. Discussions were focused around six specific application areas: Operation and Maintenance; Machine Learning in Nuclear Materials and Advanced Manufacturing; Cybersecurity; High-Performance Computing and Massive Computation; Big Data and Digital Twins; and Nuclear Non-Proliferation. The opportunities, challenges, and risks identified in the six focus areas explored in this workshop are diverse, but some common themes emerge, such as the importance of data integrity, quality, coverage, privacy, and traceability. Big data and AI/ML tools can be leveraged to reduce costs, optimize human tasking, and reduce human error across various application areas. In order for the nuclear industry to benefit from big data and advanced analytic capabilities, it is essential to address challenges and risks, such as data privacy, model reliability, and computational resource availability. Learning from other industries that have successfully implemented big data and AI/ML technologies, like the aerospace industry, can help the nuclear industry successfully integrate these technologies.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗
NASA NTRSDate not supplied

The Radiation Biology Ontology: A New Tool Supporting FAIR Principles Across Radiation Biology Facilitating Data Discovery and Integration

Development of the Radiation Biology Ontology (RBO) was motivated by the need for a comprehensive, well-structured ontology for encoding radiation biology metadata. The primary use-cases were archiving data in the STORE database (https://www.storedb.org/), the repository for the RadoNorm Project, and in GeneLab (https://genelab.nasa.gov), NASA’s ‘omics database. The scope of radiobiology research ranges from physics to radiation oncology to socio-legal studies; no existing ontology has the necessary breadth or depth. In addition, a formal ontology has the advantage of being usable for machine learning and, importantly, for tasks like data integration, knowledge extraction from the scientific literature and for query extension and data classification. Standardisation of metadata is one of the primary objectives of the FAIR principles for open data; RBO is an important landmark for FAIR radiation biology data.

ontology↗
DOE OSTI2025

An Efficient Storage-Driven Machine Learning Model for Performance in the Era of Multimodal Scientific Data

Scientific workflows are increasingly relying on machine learning (ML), simulation, and hybrid techniques to predict, understand, and optimize the behavior of complex experiments. High-performance computing has greatly improved researchers’ ability to acquire diverse data modalities in these workflows. Recent studies suggest that the performance of machine learning models can be improved by integrating data from various sources. Unfortunately, these workloads pose unprecedent pressure on the network storage to meet the demands associated with accessing these multimodal data. To mitigate the impact of intensive IO, we propose a solution that utilizes a multi-tier High-Performance Computing (HPC) distributed storage and data processing framework, placing computation where the data resides for better performance. By adopting this project, the scientific community will gain new opportunities to explore multimodal storage-driven possibilities, integrating multiple scientific data sources with advanced streaming frameworks. Additionally, our framework effectively utilizes computing resources and bridges the gaps identified by HPC experts. Our proposed approach tackles scalability and persistence challenges by leveraging native persistency, which has posed difficulties in traditional approaches. Furthermore, we seek to enhance fault-tolerance and load-balance of computations by leveraging real-time streaming in diverse scientific computing environments, thereby propelling advanced scientific computing research into the next generation.

97 MATHEMATICS AND COMPUTING↗
NASA NTRSDate not supplied

Supporting Exploration Missions by Enabling Exploration Mission System Software

Future exploration missions will consist of a multitude of data sources, systems, and operators collaborating to complete mission objectives. Presently, NASA is instantiating the contractual mechanisms, such as the xEVAS and HLS contracts, to produce these mission assets. Architectural planning is also underway to establish the networking protocols and infrastructure to digitally create and connect mission elements, such as LunaNET. However, without new horizontally integrated data systems, these advancements will be limited in their ability to get mission data appropriately integrated into the plan, train, fly, explore workflow of the operations workforce. Here we describe several mission system software development efforts underway that are designed to support human spaceflight missions. We describe the current iterations of a suite of tools to support EVA procedure authoring and execution, for both ISS and Artemis missions, as well as a software solution to establish and interact with mission context and data products. These tools have been developed iteratively and continue to be tested in several NASA facilities such as the Neutral Buoyancy Lab (NBL), Artemis field testing, and in present-day International Space Station (ISS) operations on orbit. Our solutions demonstrate how software development can be aligned with ongoing operations development activities to discover the features that best support future human spaceflight missions.

EVA Mission System Software↗
NASA NTRS1983

An interactive meteorological display and analysis system

The GEMPAK system, a general meteorological software package being developed at NASA/Goddard Space Flight Center to support mesoscale meteorological research programs, is described. The primary purpose of the system is to provide analysis support and data integration techniques for conventional and satellite derived data sets. Current capabilities of the system range from data listing and editing to interactive objective analysis procedures and coordinate transformations. Output graphics use a graphics subroutine package designed to support meteorological plotting functions. A flexible diagnostics package is currently under development.

Desjardins, M. L.↗
NASA NTRS1994

Global ozone observations from the UARS MLS: An overview of zonal-mean results

Global ozone observations from the Microwave Limb Sounder (MLS) aboard the Upper Atmosphere Research Satellite (UARS) are presented, in both vertically resolved and column abundance formats. The authors review the zonal-mean ozone variations measured over the two and a half years since launch in September 1991. Well-known features such as the annual and semiannual variations are ubiquitous. In the equatorial regions, longer-term changes are believed to be related to the quasi-biennial oscillation (QBO), with a strong semiannual signal above 20 hPa. Ozone values near 50 hPa exhibit an equatorial low from October 1991 to June 1992, after which the low ozone pattern splits into two subtropical lows (possibly in connection with residual circulation changes tied to the QBO) and returns to an equatorial low in September 1993. The ozone hole development at high southern latitudes is apparent in MLS column data integrated down to 100 hPa, the MLS data reinforce current knowledge of this lower-stratospheric phenomenon by providing a height-dependent view of the variations. The region from 30 deg S to 30 deg N (an area equal to half the global area) shows very little change in the ozone column from year to year and within each year. The most striking ozone changes have occurred at northern midlatitudes, with the October 1992 to July 1993 column values significantly lower than during the prior year. The zonal-mean changes manifest themselves as a slower rate of increase during the 1992/93 winter, and there is some evidence for a lower fall minimum. A recovery occurs during late summer of 1993; early 1994 values are significantly larger than during the two previous winters. The timing and latitudinal extent of the northern midlatitude decreases appear to rule out observed ClO enhancements in the Arctic vortex, with related chemical processing and ozone dilution effects, as a unique cause. Local depletion from ClO-related chemical mechanisms alone is also not sufficient, based on MLS ClO data. The puzzling asymmetric nature of the changes probably requires a dynamical component as an explanation. A combination of effects (including chemical destruction via heterogeneous processes and QBO phasing) apparently needs to be invoked. This dataset will place constraints on future modeling studies, which are required to better understand the source of the observed changes.

Froidevaux, Lucien↗
NASA NTRS2015

Update of Bisphosphonate Flight Experiment

Elevated bone resorption is a hallmark of human spaceflight and bed rest indicating that elevated remodeling is a major factor in the etiology of space flight bone loss. In a collaborative effort between the NASA and JAXA space agencies, we are testing whether an antiresorptive drug would provide additional benefit to in-flight exercise to ameliorate bone loss and hypercalciuria during long-duration spaceflight. Measurements of bone loss include DXA, QCT, pQCT, urinary and blood biomarkers. We have completed analysis of R+1year data from 7 crewmembers treated with alendronate during flight, as well as immediate post flight (R+<2wks) data from 6 of 10 concurrent controls without treatment. The treated astronauts used the Advanced Resistive Exercise Device (ARED) during their missions. The purpose of this report is twofold: 1) to report the results of inflight, post flight and one year post flight bone measures compared with available controls with and without the use of ARED; and 2) to discuss preliminary data on concurrent controls. The figure below compares the BMD changes in ISS crewmembers exercising with and without the current ARED protocol and the alendronate treated crewmembers also using the ARED. This shows that the use of ARED prevents about half the bone loss seen in early ISS crewmembers and that the addition of an antiresorptive provides additional benefit. Resorption markers and urinary Ca excretion are not impacted by exercise alone but are significantly reduced with antiresorptive treatment. Bone measures for treated subjects, 1 year after return from space remain at or near baseline. DXA data for the 6 concurrent controls using the ARED device are similar to DXA data shown in the figure below. QCT data for these six indicate that the integral data are consistent with the DXA data, i.e., comparing the two control groups suggests significant but incomplete improvement in maintaining BMD using the ARED protocol. Biochemical data of the concurrent control group await sample return and analysis. The preliminary conclusion is that an antiresorptive may be an effective adjunct to exercise during long-duration spaceflight.

LeBlanc, A.↗
NASA NTRS2016

GES DISC Datalist Enables Easy Data Selection for Natural Phenomena Studies

In order to investigate and assess natural hazards such as tropical storms, winter storms, volcanic eruptions, floods, and drought in a timely manner, the NASA Goddard Earth Sciences Data and Information Services Center (GES DISC) has been developing an efficient data search and access service. Called Datalist, this service enables users to acquire their data of interest all at once, with minimum effort. A Datalistis a virtual collection of predefined or user-defined data variables from one or more archived data sets. Datalistsare more than just data. Datalistseffectively provide users with a sophisticated integrated data and services package, including metadata, citation, documentation, visualization, and data-specific services (e.g., subset and OPeNDAP), all available from one-stop shopping. The predefined Datalists, created by the experienced GES DISC science support team, should save a significant amount of time that users would otherwise have to spend. The Datalistservice is an extension of the new GES DISC website, which is completely data-driven. A Datalist, also known as data bundle, is treated just as any other data set. Being a virtual collection, a Datalistrequires no extra storage space.

Earth events↗
NASA NTRSDate not supplied

Celestial Mapping System for Lunar Surface Mapping and Analytics

Celestial Mapping System (CMS) is a software platform to generate virtual 3D globe for celestial bodies within our solar system. Various layers are built on top of the virtual globe to provide visualization of high resolution imagery, enable precise measurements, build analytical capabilities and broad range of functionalities to assist planetary scientists and mission planners. CMS is built using OpenJDK 11 and will run on a wide variety of platforms such as Linux, Windows, OSX, etc. It has a thick client with less overhead to access hardware resources. This allows features such as terrain profiling and distance calculations to be performed on the client and on the fly. The present focus of CMS is on developing lunar mapping tool kits to provide features such as - 3D first person view with zoom and navigational capabilities, realistic terrain visualization based on LRO data, measurement tools, Apollo landing site annotations, stereoscopic view, elevation profiles, line of sight analysis and many more. The application is developed to provide situational and domain awareness on Lunar surface, planning capabilities for equipment placements and traverse path optimization. As data becomes available, CMS has the capabilities to integrate data sets that change dynamically in real-time, which will be useful for monitoring satellites and remotely-sensed data on Lunar surface. CMS utilizes NASA WorldWind Java library and OpenGL to achieve high-performance rendering of data and measurements, and also adheres to OGC standards. CMS supports importing synthetic features in a variety of 3D, 2D, vector and raster formats. Nomenclature is pulled from USGS Moon IAU2000 database, and lunar parameters are based of the standardized IAU2000 Moon ellipsoid. GDAL (Geospatial Data Abstraction Library) was used to modify and test the accuracy of datasets before integrating into the application. Our high-resolution global elevation model was compared with the LRO LOLA DEM elevation values and tested to ensure accuracy. Celestial Mapping System has several potential use cases for NASA including subsurface lava tubes visualization and analysis, soil analysis, resource visualization and representation on 3D globe.

GIS system↗
NASA NTRSDate not supplied

Supporting Exploration Missions by Enabling Exploration Mission System Software

Future exploration missions will consist of a multitude of data sources, systems, and operators collaborating to complete mission objectives. Presently, NASA is instantiating the contractual mechanisms, such as the Exploration Extravehicular Activity Services (xEVAS) and Human Landing System (HLS) contracts, to produce these mission assets. Architectural planning is also underway to establish the networking protocols and infrastructure to digitally create and connect mission elements, such as LunaNET. However, without new horizontally integrated data systems, these advancements will be limited in their ability to get mission data appropriately integrated into the plan, train, fly, explore workflow of the flight operations workforce. Here we describe several mission system software development efforts underway that are designed to support human spaceflight missions. This paper describes the current iterations of a suite of tools to support EVA procedure authoring and execution, and mission context creation for both International Space Station (ISS) and Artemis missions. These tools have been developed iteratively and continue to be used in present-day ISS operations on orbit and in several NASA facilities such as the Neutral Buoyancy Lab (NBL) and Artemis field testing. These solutions demonstrate how software development can be aligned with ongoing operations development activities to discover the features that best support both current and future human spaceflight missions.

Matthew J. Miller↗