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All sourcesNASA NTRSDOE OSTI
NASA NTRS2023

Novel Observing Strategies for NASA Future Earth Science Missions

NASA's Advanced Information Systems Technology (AIST) Program is one of several Technology programs managed by the Earth Science Technology Office (ESTO) in the Earth Science Division (ESD). The AIST Program focuses on advanced information systems and novel computer science technologies that will be needed by NASA Earth Science in the next 5 to 10 years. The three main thrusts of the AIST Program deal with Novel Observing Strategies (NOS), Analytic Collaborative Frameworks (ACF) and Earth System Digital Twins (ESDT). This presentation summarizes the NOS thrust, its objectives and its benefits to NASA's Earth Science; it presents the projects funded by AIST under that thrust and its application to future AIST developments such as ESDT. It also includes one slide about the SCaN (Space Communications and Navigation) Program and its capabilities as they relate to NOS.

Jacqueline Le Moigne↗
NASA NTRS2007

Image and information management system

A system and methods through which pictorial views of an object's configuration, arranged in a hierarchical fashion, are navigated by a person to establish a visual context within the configuration. The visual context is automatically translated by the system into a set of search parameters driving retrieval of structured data and content (images, documents, multimedia, etc.) associated with the specific context. The system places hot spots, or actionable regions, on various portions of the pictorials representing the object. When a user interacts with an actionable region, a more detailed pictorial from the hierarchy is presented representing that portion of the object, along with real-time feedback in the form of a popup pane containing information about that region, and counts-by-type reflecting the number of items that are available within the system associated with the specific context and search filters established at that point in time.

Robertson, Tina L.↗
NASA NTRS2009

Image and information management system

A system and methods through which pictorial views of an object's configuration, arranged in a hierarchical fashion, are navigated by a person to establish a visual context within the configuration. The visual context is automatically translated by the system into a set of search parameters driving retrieval of structured data and content (images, documents, multimedia, etc.) associated with the specific context. The system places ''hot spots'', or actionable regions, on various portions of the pictorials representing the object. When a user interacts with an actionable region, a more detailed pictorial from the hierarchy is presented representing that portion of the object, along with real-time feedback in the form of a popup pane containing information about that region, and counts-by-type reflecting the number of items that are available within the system associated with the specific context and search filters established at that point in time.

Robertson, Tina L.↗
NASA NTRS2004

Development of an Information Fusion System for Engine Diagnostics and Health Management

Aircraft gas-turbine engine data are available from a variety of sources including on-board sensor measurements, maintenance histories, and component models. An ultimate goal of Propulsion Health Management (PHM) is to maximize the amount of meaningful information that can be extracted from disparate data sources to obtain comprehensive diagnostic and prognostic knowledge regarding the health of the engine. Data Fusion is the integration of data or information from multiple sources, to achieve improved accuracy and more specific inferences than can be obtained from the use of a single sensor alone. The basic tenet underlying the data/information fusion concept is to leverage all available information to enhance diagnostic visibility, increase diagnostic reliability and reduce the number of diagnostic false alarms. This paper describes a basic PHM Data Fusion architecture being developed in alignment with the NASA C17 Propulsion Health Management (PHM) Flight Test program. The challenge of how to maximize the meaningful information extracted from disparate data sources to obtain enhanced diagnostic and prognostic information regarding the health and condition of the engine is the primary goal of this endeavor. To address this challenge, NASA Glenn Research Center (GRC), NASA Dryden Flight Research Center (DFRC) and Pratt & Whitney (P&W) have formed a team with several small innovative technology companies to plan and conduct a research project in the area of data fusion as applied to PHM. Methodologies being developed and evaluated have been drawn from a wide range of areas including artificial intelligence, pattern recognition, statistical estimation, and fuzzy logic. This paper will provide a broad overview of this work, discuss some of the methodologies employed and give some illustrative examples.

Volponi, Allan J.↗
NASA NTRS1987

The RICIS concept

A cooperative program was initiated by JSC with the University of Houston - Clear Lake to support research in computing and information systems. The objective of this program is to provide continuing long-term research in support of the numerous mission and mission-related endeavors of NASA/JSC. The Research Institute for Computing and Information Systems (RICIS) concept is presented in form of viewgraphs. History of RICIS, its organization, and research status are discussed.

Macdonald, Robert B.↗
NASA NTRS1977

Effect of hand-based sensors on manipulator control performance

Manipulator task categories and motion phases require various hand-based information systems to meet the control performance requirements. The effect of proximity, tactile and force/torque sensors on the performance of remote manipulator control is discussed. An overview is presented on various experimental hand-based information systems which provide the manipulator controller some non-visual 'awareness' of the task environment. The rest of the paper describes and evaluates various control experiments performed at JPL using hand-mounted proximity sensors to guide and control hand motion near solid objects.

Bejczy, A. K.↗
NASA NTRS2021

Illinois Disasters: Utilizing NASA Earth Observations to Enhance Drought Monitoring in Illinois

Drought and flooding in Illinois have severe impacts on the communities and ecosystems of the state. Soil moisture is a valuable indicator of drought and flood vulnerability but can be difficult to measure since in situ monitoring is limited to discrete stations throughout the state. The team created a framework to compare in situ, modeled, and NASA satellite soil moisture measurements to increase the spatial coverage of soil moisture monitoring. The team partnered with the Illinois State Weather Survey, USDA Midwest Climate Hub, NOAA Regional Climate Services of the Central Region, NOAA National Integrated Drought Information System’s Midwest Drought Early Warning System, and the NOAA North Central River ForecastCenter. The team standardized and compared soil moisture data from NASA’s Soil Moisture Active Passive (SMAP) mission, modeled soil moisture outputs from NASA’s SPoRT Land Information System (SPoRT-LIS), and in situ measurements from the Illinois State Weather Survey’s Water and Atmospheric Resources Monitoring (WARM) program. Compared to the WARM data, the satellite and modeled data showed seasonally variable differences and bias. The difference was highest in the winter months and lowest in the late summer and early fall months for the SMAP and SPoRT-LIS data products. SPoRT-LIS produced lower seasonal variability and SMAP demonstrated higher correlation values and lower differences. These analyses suggest that both SMAP and SPoRT-LIS products offer unique strengths and limitations when used for soil moisture monitoring

Joshua Green↗
DOE OSTI2024

Carbon Management Projects (CONNECT) Database and Explorer

Overview The Carbon Management Projects (CONNECT) Toolkit is an online exploratory visualization tool developed by the U.S. Department of Energy's (DOE) Office of Fossil Energy and Carbon Management (FECM) with support from other federal agencies such as the U.S. Environmental Protection Agency (EPA) and the U.S. Department of Transportation (DOT). It provides a single point of access to authoritative information on federal agency investment in a portfolio of research, development, and demonstration (RD&D) projects that have been publicly announced to advance technologies for point source carbon capture, carbon dioxide removal, transport, storage, and conversion, collectively referred to as carbon management. The RD&D programs covered in this tool are authorized by annual congressional appropriations ("Base Program") and the 2021 Infrastructure Investment and Jobs Act (IIJA). The tool also incorporates public information on other federal initiatives, such as the Regional Clean Hydrogen Hubs, and public information released by other government agencies, such as the Environmental Protection Agency's (EPA) and Primacy States’ Underground Injection Control Class VI permits and EPA’s facility level greenhouse gas (GHG) emissions. Developed in a geographic information system, the tool organizes carbon management projects into five groups based on the primary technology that a project aims to advance, each visually represented as a digital layer ("carbon management project layer"). Only federally funded projects are included, which can be awarded projects that are completed or ongoing, or projects that have been selected but are currently under negotiation. Project information can be viewed in the map or in the attribute table below it when turned on. In the map view, each project is displayed at either its host site (for field work), where available, or its performer site (project lead's location, further explained in the table below). Host sites and performer sites are represented in distinct icons. Several reference layers offer additional public information on infrastructural and natural resource environment for carbon management. These reference layers, combined with multiple geographical basemaps, enable users to visualize the carbon management project layers in context. Carbon management project information will be updated monthly based on feedback and information availability. Carbon management project layers Point Source Carbon Capture (PSC) This layer contains DOE-funded projects focused on capturing carbon dioxide (CO2) from power plants or industrial facilities. Carbon Dioxide Removal (CDR) This layer contains DOE-funded projects focused on capturing CO2 from the atmosphere, including direct air capture (DAC) and DAC hubs, direct ocean capture, enhanced mineralization, and biomass carbon removal and storage. For projects with multiple host sites, each of the sites are displayed individually with the project cost and cost sharing information representing the total for the entire project. Carbon Transport This layer contains DOE- and DOT-funded projects focused on CO2 transport. The Transport Research and Development sublayer contains projects that do not involve physical infrastructure; the Proposed Transport Corridor sublayer contains projects for which either a route for the transport infrastructure has been proposed or a general area for the transport infrastructure has been identified. Carbon Storage This layer contains DOE-funded key projects focused on CO2 storage. For projects with multiple field-work sites, each of the sites are displayed individually on the map with the project cost and cost sharing information representing the overall total for the entire project. Carbon Conversion This layer contains DOE-funded projects focused on converting CO2 into economically valuable products. Reference layers The following layers provide additional information in the geographic proximity of carbon management projects. Users should reference the original sources for more details (weblinks provided below and in pop-up windows on the map). Regional Clean Hydrogen Hub and Facility These layers illustrate the approximate areas of the Regional Clean Hydrogen Hubs announced by DOE's Office of Clean Energy Demonstrations (OCED) and the approximate locations of individual facilities that constitute the hubs (see "Where are the H2Hubs located?" on the webpage linked above). EPA Facility Level GHG Emissions (direct emitter) This layer shows direct CO2 emissions from stationary sources in 2022, using data extracted from EPA's Facility Level Information on GreenHouse gases Tool (FLIGHT). Captured and injected CO2 are not deducted from direct emitters’ total emissions. Contact EPA for additional details. Underground Injection Control Class VI permit/permit application This layer shows the locations of CO2 injection wells that are granted or in the process of applying for an Underground Injection Control Class VI permit by EPA or a Primacy State (currently Louisiana, North Dakota, and Wyoming). The URLs for the permits or permit applications are provided in the pop-up windows associated with the well locations. Contact EPA for additional details. Carbon Storage Resource This layer contains information on prospective CO2 storage resources in saline formations and oil and gas reservoirs provided by the National Carbon Sequestration Database and Geographic Information System (NATCARB) spatial database. Contact NETL for additional details. Existing CO2 pipeline This layer shows active CO2 pipelines based on information digitized from the map issued by the Pipeline and Hazardous Materials Safety Administration (PHMSA). Contact PHMSA for additional details.

Carbon Conversion↗
DOE OSTI2025

Capturing Historic Reliability Performance Through Graph Databases: A Model Based System Engineering Approach

With the goal of improving the performance and reliability of high dependable technological systems such as nuclear power plants, advanced monitoring and health management systems are employed to inform system engineers on observed degradation processes and anomalous behaviors of assets and components. This information is captured in the form of large amount of data which can be heterogenous in nature (e.g., numeric, textual). Such large data availability poses challenges when system engineers are required to parse and analyze them in order to track historic reliability performance of assets and components. This paper tackles directly this challenge by providing means to organize data in the form of a graph: a knowledge graph. The presented approach distinguish itself from current knowledge graph-based methods by the fact that model-based system engineering (MBSE) models are used to “put data into context”. In particular, MBSE models are used as skeleton of a knowledge graph; numeric and textual data elements, once processed, are associated to MBSE model elements. Thus, a knowledge graph captures both system architecture (though MBSE models) and health/performance data. Such feature opens the door to new data analytics methods designed to identify causal relations between observed phenomena.

97 - MATHEMATICS AND COMPUTING↗
NASA NTRS1973

Wildland fire management. Volume 2: Wildland fire control 1985-1995

The preliminary design of a satellite plus computer earth resources information system is proposed for potential uses in fire prevention and control in the wildland fire community. Suggested are satellite characteristics, sensor characteristics, discrimination algorithms, data communication techniques, data processing requirements, display characteristics, and costs in achieving the integrated wildland fire information system.

Saveker, D. R.↗
NASA NTRS2023

Southeast U.S. Agriculture: Evaluating the Spatial and Temporal Distribution of Flash Droughts within Agricultural Areas and Regional Crop Calendars in the Southeast using Earth Observations

A flash drought refers to the rapid onset or intensification of drought-like conditions. Within the Southeastern United States, flash droughts are made worse by the presence of consumptive vegetation and poor water-holding soils. According to the United States Drought Monitor, a 2016 flash drought occurred with roughly 92% of Georgia, Alabama, Mississippi, and Tennessee experiencing “severe drought” or worse in the fall of that year. The event resulted in widespread wildfires, reservoir shortages that led to interstate disputes over water rights, significant deterioration of pasture and rangeland, and crop sale losses. The occurrence of a flash drought similar to that listed above can cost the Southeast hundreds of millions of dollars, with effects lasting for several years. For this reason, the development of flash drought monitoring, forecasting, and communication tools is needed to alert both states and their practitioners of possible flash drought events, offsetting the potential loss caused by a flash drought event. This research employed NASA's Short-Term Prediction and Transition Center-Land Information System, Landsat 7 Enhanced Thematic Mapper Plus, and Landsat 8 Operational Land Imager and other datasets to determine climatological trends during peak growing season from 2000-2022. These products can help partners at the Alabama Office of the State Climatologist, National Integrated Drought Information System, and National Coordinated Soil Moisture Monitoring Network better manage agricultural lands inside drought-prone zones and monitor crop sensitivity during different growing seasons.

Kindrea Gibbons↗
NASA NTRS1988

Telescience Testbed Pilot Program

The Telescience Testbed Pilot Program (TTPP) is intended to develop initial recommendations for requirements and design approaches for the information system of the Space Station era. Multiple scientific experiments are being performed, each exploring advanced technologies and technical approaches and each emulating some aspect of Space Station era science. The aggregate results of the program will serve to guide the development of future NASA information systems.

Gallagher, Maria L.↗
DOE OSTI2024

Toward High-Throughput Deposition of III-V Materials and Devices Using Halide Vapor Phase Epitaxy: Preprint

III-V devices are used in countless applications due to their excellent physical properties. They could become more prevalent, especially in area-intensive applications such as solar power, if they can achieve significant cost decreases through increasing scale. The development of high-throughput growth systems can help to achieve this scale, leading to the use of III-V devices in areas where they are not currently economically feasible. Here, we describe a pilot production, pseudo inline HVPE reactor with the potential to greatly increase the throughput of III-V devices. We show computational modeling results that both informed system design and the understanding of the impact of different process parameters on the deposition. We show the throughput possibilities of this reactor with an example solar cell device design but note that this system is agnostic to the device structure and can be used to increase the throughput of lasers, LEDs, transistors, and more III-V devices.

high throughput↗
NASA NTRS1992

Unification - An international aerospace information issue

Scientific and Technical Information (STI) represents the results of large investments in research and development (R&D) and the expertise of a nation and is a valuable resource. For more than four decades, NASA and its predecessor organizations have developed and managed the preeminent aerospace information system. NASA obtains foreign materials through its international exchange relationships, continually increasing the comprehensiveness of the NASA Aerospace Database (NAD). The NAD is de facto the international aerospace database. This paper reviews current NASA goals and activities with a view toward maintaining compatibility among international aerospace information systems, eliminating duplication of effort, and sharing resources through international cooperation wherever possible.

Cotter, Gladys A.↗
NASA NTRS1994

Advanced information processing system: The Army Fault-Tolerant Architecture detailed design overview

The Army Avionics Research and Development Activity (AVRADA) is pursuing programs that would enable effective and efficient management of large amounts of situational data that occurs during tactical rotorcraft missions. The Computer Aided Low Altitude Night Helicopter Flight Program has identified automated Terrain Following/Terrain Avoidance, Nap of the Earth (TF/TA, NOE) operation as key enabling technology for advanced tactical rotorcraft to enhance mission survivability and mission effectiveness. The processing of critical information at low altitudes with short reaction times is life-critical and mission-critical necessitating an ultra-reliable/high throughput computing platform for dependable service for flight control, fusion of sensor data, route planning, near-field/far-field navigation, and obstacle avoidance operations. To address these needs the Army Fault Tolerant Architecture (AFTA) is being designed and developed. This computer system is based upon the Fault Tolerant Parallel Processor (FTPP) developed by Charles Stark Draper Labs (CSDL). AFTA is hard real-time, Byzantine, fault-tolerant parallel processor which is programmed in the ADA language. This document describes the results of the Detailed Design (Phase 2 and 3 of a 3-year project) of the AFTA development. This document contains detailed descriptions of the program objectives, the TF/TA NOE application requirements, architecture, hardware design, operating systems design, systems performance measurements and analytical models.

Harper, Richard E.↗
NASA NTRS2009

An Intelligent Archive Testbed Incorporating Data Mining

Many significant advances have occurred during the last two decades in remote sensing instrumentation, computation, storage, and communication technology. A series of Earth observing satellites have been launched by U.S. and international agencies and have been operating and collecting global data on a regular basis. These advances have created a data rich environment for scientific research and applications. NASA s Earth Observing System (EOS) Data and Information System (EOSDIS) has been operational since August 1994 with support for pre-EOS data. Currently, EOSDIS supports all the EOS missions including Terra (1999), Aqua (2002), ICESat (2002) and Aura (2004). EOSDIS has been effectively capturing, processing and archiving several terabytes of standard data products each day. It has also been distributing these data products at a rate of several terabytes per day to a diverse and globally distributed user community (Ramapriyan et al. 2009). There are other NASA-sponsored data system activities including measurement-based systems such as the Ocean Data Processing System and the Precipitation Processing system, and several projects under the Research, Education and Applications Solutions Network (REASoN), Making Earth Science Data Records for Use in Research Environments (MEaSUREs), and the Advancing Collaborative Connections for Earth-Sun System Science (ACCESS) programs. Together, these activities provide a rich set of resources constituting a value chain for users to obtain data at various levels ranging from raw radiances to interdisciplinary model outputs. The result has been a significant leap in our understanding of the Earth systems that all humans depend on for their enjoyment, livelihood, and survival. The trend in the community today is towards many distributed sets of providers of data and services. Despite this, visions for the future include users being able to locate, fuse and utilize data with location transparency and high degree of interoperability, and being able to convert data to information and usable knowledge in an efficient, convenient manner, aided significantly by automation (Ramapriyan et al. 2004; NASA 2005). We can look upon the distributed provider environment with capabilities to convert data to information and to knowledge as an Intelligent Archive in the Context of a Knowledge Building system (IA-KBS). Some of the key capabilities of an IA-KBS are: Virtual Product Generation, Significant Event Detection, Automated Data Quality Assessment, Large-Scale Data Mining, Dynamic Feedback Loop, and Data Discovery and Efficient Requesting (Ramapriyan et al. 2004).

Ramapriyan, H.↗