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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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NASA NTRS2003

Reference architecture for space data systems

Architectures for terrestrial data systems that are built and managed by a single organization are inherently complex. In order to understand any large-scale system architecture, and to judge its applicability for its nominal task, a description of the system must be produced that exposes a number of distinct viewpoints. Within the CCSDS Architecture Working Group we have adapted the Reference Model for Open Distributed Processing to describe large, multi-national, space data systems.

CCSDS space communication reference architecture s↗
NASA NTRS2015

SPHERES: From Ground Development to Operations on ISS

SPHERES (Synchronized Position Hold Engage and Reorient Experimental Satellites) is an internal International Space Station (ISS) Facility that supports multiple investigations for the development of multi-spacecraft and robotic control algorithms. The SPHERES Facility on ISS is managed and operated by the SPHERES National Lab Facility at NASA Ames Research Center (ARC) at Moffett Field California. The SPHERES Facility on ISS consists of three self-contained eight-inch diameter free-floating satellites which perform the various flight algorithms and serve as a platform to support the integration of experimental hardware. To help make science a reality on the ISS, the SPHERES ARC team supports a Guest Scientist Program (GSP). This program allows anyone with new science the possibility to interface with the SPHERES team and hardware. In addition to highlighting the available SPHERES hardware on ISS and on the ground, this presentation will also highlight ground support, facilities, and resources available to guest researchers. Investigations on the ISS evolve through four main phases: Strategic, Tactical, Operations, and Post Operations. The Strategic Phase encompasses early planning beginning with initial contact by the Principle Investigator (PI) and the SPHERES program who may work with the PI to assess what assistance the PI may need. Once the basic parameters are understood, the investigation moves to the Tactical Phase which involves more detailed planning, development, and testing. Depending on the nature of the investigation, the tactical phase may be split into the Lab Tactical Phase or the ISS Tactical Phase due to the difference in requirements for the two destinations. The Operations Phase is when the actual science is performed; this can be either in the lab, or on the ISS. The Post Operations Phase encompasses data analysis and distribution, and generation of summary status and reports. The SPHERES Operations and Engineering teams at ARC is composed of experts who can guide the Payload Developer (PD) and Principle Investigator (PI) in reaching critical milestones to make their science a reality using the SPHERES platform. From performing integrated safety and verification assessments, to assisting in developing crew procedures and operations products, to organizing, planning, and executing all test sessions, to helping manage data products, the SPHERES team at ARC is available to support microgravity research with the SPEHRES Guest Scientist Program.

ISS Research↗
NASA NTRSDate not supplied

Advancing Autonomy in Distributed Space Systems: Insights From on-Orbit Testing with the Starling 1.0 Mission

Autonomous decision-making is crucial for enhancing mission effectiveness in Distributed Space Systems (DSS), particularly in multi-spacecraft operations where communication constraints and mission complexity pose challenges. The Distributed Spacecraft Autonomy (DSA) team at NASA’s Ames Research Center is advancing autonomy in DSS through five key technical areas: distributed resource and task management, reactive operations, system modeling and simulation, human-swarm interaction, and ad hoc network communications. The DSA experiment onboard the Starling 1.0 Mission showcases collaborative resource allocation for multi-point science data collection with four small spacecraft. Autonomy in decision-making is highlighted as a crucial factor for multi-spacecraft missions, enabling spacecraft to operate independently, reducing reliance on ground control. This capability is particularly significant for future deep-space missions, where communication delays and limited data transmission capacity make traditional command and control approaches impractical. This demonstration focuses on a GPS Channel Selection Experiment, leveraging emergent capabilities like "shared sampling" and "simultaneous sampling" to optimize channel selection across the spacecraft swarm. The experiment aims to capture ionospheric phenomena such as the Equatorial Ionization Anomaly and Polar Patches. The DSA system's autonomous reconfiguration ability is showcased, emphasizing its adaptability to natural phenomena without significant integration efforts. The GPS Channel Selection Experiment utilizes a dual-band GPS receiver to estimate plasma density in the ionosphere. Explorative and exploitative channel selections are employed based on the nature of observed phenomena. The performance of DSA algorithms is evaluated in terms of optimal channel allocations and responsiveness to changes in observed features. The DSA Flight Software utilizes the Core Flight System (cFS) framework, ensuring compatibility with the Starling 1.0 flight mission software. DSA showcases results from RTI’s Connext DDS Micro communication middleware, enabling message routing over the Ad-Hoc Network of Starling 1.0. This paper provides a comprehensive overview of the DSA experiment's initial results, emphasizing the advancements in autonomy for Distributed Space Systems and the successful collaboration with the Starling 1.0 mission.

Caleb Ashmore Adams↗
NASA NTRS2025

Jemez Pueblo Agriculture: Monitoring Rangeland Conditions to Inform Drought and Land Management in New Mexico

The Jemez Pueblo, a community located in the semi-arid high desert region of northcentral New Mexico, faces challenges with drought mitigation and livestock management. NASA DEVELOP partnered with the Pueblo of Jemez Natural Resources Department and The Nature Conservancy to provide recent and historical rangeland conditions to aid present decision-making, which relies on cultural practices, site familiarity, available resources, and physical data. This partnership offers the opportunity to support management practices by leveraging remote sensing and virtual fencing technologies. Our project explored Rangeland Analysis Platform (RAP) products incorporating NASA Earth observation Landsat 5 TM, Landsat 7 ETM+, Landsat 8 OLI, and Landsat 9 OLI-2 remote-sensed imagery as an agricultural land management tool. We performed linear regression analysis to evaluate RAP data to field data and explored RAP annual herbaceous biomass, ground cover trends, and climatic factors at the pasture level. We then computed study area summary statistics, performed pixel-by-pixel trend analysis across the study period, and evaluated ground cover trends near water sources. Based on available data, RAP was poorly correlated to bare ground and herbaceous biomass, generally underestimating the former and overestimating the latter. To improve the evaluation of RAP products, we suggest increasing the spatiotemporal distribution of the field dataset. According to RAP, from 1986 to 2023, the site became hotter and drier, bare ground increased, and annual forbs and grasses increased while perennials decreased. RAP products did not agree with field-collected data; however, the trends over time may be useful for informing rangeland management actions.

cattle grazing management↗
NASA NTRS1974

A reconnaissance space sensing investigation of crustal structure for a strip from the eastern Sierra Nevada to the Colorado Plateau

The author has identified the following significant results. Studies were conducted in key field areas in the Sierra Nevada, the Basin Range Province and the Colorado Plateau to evaluate the origins and significance of geologic and structural anomalies expressed in the ERTS-1 data. The investigation included development of image enhancement and analysis techniques and comparison of remote sensing data available over the test site. The ERTS-1 MSS imagery has proven to be an effective tool for studying the interrelationsships between Cenozoic tectonic patterns and the distributions of Cenozoic plutonism and volcanism, seismic activity, geologic hazards, and known mineral, geothermal and ground water resources. Recommendations are made for applications of ERTS-1 data to natural and resource exploration and management.

Liggett, M. A.↗
NASA NTRS1988

Knowledge-based image data management - An expert front-end for the BROWSE facility

An intelligent user interface being added to the NASA-sponsored BROWSE testbed facility is described. BROWSE is a prototype system designed to explore issues involved in locating image data in distributed archives and displaying low-resolution versions of that imagery at a local terminal. For prototyping, the initial application is the remote sensing of forest and range land.

Stoms, David M.↗
NASA NTRS1990

The Planetary Data System - A solution to data management for the planetary science community

An overview of the first release of the Planetary Data System (PDS) is presented, and some of the challenges encountered during development of the system are described. The principal goals of the PDS are to distribute planetary science data and information about these data to NASA, to provide scientific knowledge to users of these data, and to provide for permanent storage. The current architecture and capabilities of the PDS (Version 1.0) are examined, and some of the special challenges encountered and lessons learned during the application are highlighted. Finally, implications for future versions of the PDS as well as for other science data systems are discussed.

Dobinson, Elaine R.↗
NASA NTRS1991

AIAA/NASA International Symposium on Space Information Systems, 2nd, Pasadena, CA, Sept. 17-19, 1990, Proceedings. Vols. 1 & 2

These proceedings overview major space information system projects and lessons learned from current missions. Other topics include the science information system requirements for the 1990s, an information systems design approach for major programs, the technology needs and projections, the standards for space data information systems, the artificial intelligence technology and applications, international interoperability, and spacecraft data systems and architectures advanced communications. Other topics include the software engineering technology and applications, the multimission multidiscipline information system architectures, the distributed planning and scheduling systems and operations, and the computer and information systems architectures. Paper presented include prospects for scientific data analysis systems for solar-terrestrial physics in the 1990s, the Columbus data management system, data storage technologies for the future, the German aerospace research establishment, and launching artificial intelligence in NASA ground systems.

Tavenner, Leslie A.↗
NASA NTRS2004

Standardized Sky Partitioning for the Next Generation Astronomy and Space Science Archives

The Johns Hopkins University and Space Telescope Science Institute are working together on this project to develop a library of standard software for data archives that will benefit the wider astronomical community. The ultimate goal was to develop and distribute a software library aimed at providing a common system for partitioning and indexing the sky in manageable sized regions and provide complex queries on the objects stored in this system. Whilst ongoing maintenance work will continue the primary goal has been completed. Most of the next generation sky surveys in the different wavelengths like 2MASS, GALEX, SDSS, GSC-II, DPOSS and FIRST have agreed on this common set of utilities. In this final report, we summarize work on the work elements assigned to the STScI project team.

Lal, Nand↗
NASA NTRS2011

Predictive Models of Duration of Ground Delay Programs in New York Area Airports

Initially planned GDP duration often turns out to be an underestimate or an overestimate of the actual GDP duration. This, in turn, results in avoidable airborne or ground delays in the system. Therefore, better models of actual duration have the potential of reducing delays in the system. The overall objective of this study is to develop such models based on logs of GDPs. In a previous report, we described descriptive models of Ground Delay Programs. These models were defined in terms of initial planned duration and in terms of categorical variables. These descriptive models are good at characterizing the historical errors in planned GDP durations. This paper focuses on developing predictive models of GDP duration. Traffic Management Initiatives (TMI) are logged by Air Traffic Control facilities with The National Traffic Management Log (NTML) which is a single system for automated recoding, coordination, and distribution of relevant information about TMIs throughout the National Airspace System. (Brickman, 2004 Yuditsky, 2007) We use 2008-2009 GDP data from the NTML database for the study reported in this paper. NTML information about a GDP includes the initial specification, possibly one or more revisions, and the cancellation. In the next section, we describe general characteristics of Ground Delay Programs. In the third section, we develop models of actual duration. In the fourth section, we compare predictive performance of these models. The final section is a conclusion.

Kulkarni, Deepak↗
NASA NTRS2023

Two Decades of Land Cover Change and Forest Fragmentation in Liberia: Consequences for the Contribution of Nature to People

The Guinean forests of West Africa have been identified as a global biodiversity hotspot due to its exceptional concentrations of endemic species and exceptional loss of habitats. The majority of what remains of the Guinean forests lies within Liberia, a country whose share of total wealth is nearly equally distributed into human and natural capital. The Liberian government seeks a more inclusive development agenda that forges a path for improved human capital while sustainably managing its natural capital wealth, which requires consistent data on land cover change and forest disturbance over time. To address this need, Landsat data were used to map and quantify land cover change and forest fragmentation in Liberia between 2000 and 2018. In addition, LiDAR data from the Global Ecosystem Dynamics Investigation (GEDI) mission were applied to assess the integrity of forest remnants. Between 2000 and 2018, only 1% of all forest cover classes (i.e., dense/primary, open/secondary and sparse/degraded) were converted into non-forest classes, with the most observed change being between these three forest classes. During the study period, 27% of the dense/primary forest class transitioned to either the open/secondary or sparse/degraded canopy classes through consistent fragmentation along the edges of the last large remaining blocks of dense/primary forest located in the north-west and south-east of Liberia and more than 14% of dense/primary forest areas identified in previous studies as “essential natural capital” for either biodiversity, forest carbon storage or provision of freshwater ecosystem services were degraded. The 2018 GEDI-based measurements show that the overall average height of dense/primary forest decreases by 24% and 48%, and canopy closure decreases by 33% and 59%, when transitioned to the open/secondary and sparse/degraded classes, respectively. The information derived from this analysis will be critical for informing the development of new policies and actions, leading to more sustainable forest management in Liberia.

Celio De Sousa↗
NASA NTRS2024

Architecture of High-Altitude Operations (HAO) Discovery and Synchronization Service (DSS)

The aviation industry is evolving at an unprecedented pace, necessitating the development of efficient, secure, and interoperable systems to manage increasingly complex air traffic. Moreover, the demand for High-Altitude Operations (HAO) is increasing. Furthermore, air traffic control services are limited in HAO environments. HAO industry participants will need airspace access and flexibility to perform their missions in this airspace that provides provisions for scalability. The Discovery and Synchronization Service (DSS) will be a cornerstone of the HAO ecosystem, enabling the effective sharing of critical airspace data, including operational intent, aircraft trajectories, and airspace usage among various stakeholders and operators. The DSS architecture addresses these challenges with a distributed, decentralized, and interoperable system that facilitates seamless integration across diverse airspaces. It prioritizes secure data exchange while safeguarding data ownership. This white paper presents the vision, architecture, and benefits of the DSS for HAO, underscoring its potential to streamline operations, reduce redundancies, and establish a foundation for safe and efficient airspace management.

HAO↗
NASA NTRS1982

The OSS-1/STS-3 mission

Integration, test, flight operations, program and science management, and experiment results from the OSS-1/STS-3 flight are reviewed. The experimental pallet, manufactured by ESA members, carried instrumentation for astronomy, space plasma studies, physics, planetology, solar physics, and life sciences. The ability of the equipment to operate in a worst-case Orbiter thermal environment was tested, as was the plasma environment around the Orbiter. The solar UV spectral irradiance monitor microprocessor was found to reset concurrently with start-up of the Shuttle hydraulic pumps. Degradations were also observed in one of the three solar flare X ray polarimeter modules, the thermal cannister experiment microprocessor, and the scientific data recorder no. 2. The Orbiter was determined to perform well during firing of an electron beam. A contamination monitor recorded matter accretion to be dependent on the solar orientation of the Orbiter. Finally, the distribution of the responsibilities and tasks for mission management are reviewed.

Kissin, K.↗
NASA NTRS2005

Health Management Applications for International Space Station

Traditional mission and vehicle management involves teams of highly trained specialists monitoring vehicle status and crew activities, responding rapidly to any anomalies encountered during operations. These teams work from the Mission Control Center and have access to engineering support teams with specialized expertise in International Space Station (ISS) subsystems. Integrated System Health Management (ISHM) applications can significantly augment these capabilities by providing enhanced monitoring, prognostic and diagnostic tools for critical decision support and mission management. The Intelligent Systems Division of NASA Ames Research Center is developing many prototype applications using model-based reasoning, data mining and simulation, working with Mission Control through the ISHM Testbed and Prototypes Project. This paper will briefly describe information technology that supports current mission management practice, and will extend this to a vision for future mission control workflow incorporating new ISHM applications. It will describe ISHM applications currently under development at NASA and will define technical approaches for implementing our vision of future human exploration mission management incorporating artificial intelligence and distributed web service architectures using specific examples. Several prototypes are under development, each highlighting a different computational approach. The ISStrider application allows in-depth analysis of Caution and Warning (C&W) events by correlating real-time telemetry with the logical fault trees used to define off-nominal events. The application uses live telemetry data and the Livingstone diagnostic inference engine to display the specific parameters and fault trees that generated the C&W event, allowing a flight controller to identify the root cause of the event from thousands of possibilities by simply navigating animated fault tree models on their workstation. SimStation models the functional power flow for the ISS Electrical Power System and can predict power balance for nominal and off-nominal conditions. SimStation uses realtime telemetry data to keep detailed computational physics models synchronized with actual ISS power system state. In the event of failure, the application can then rapidly diagnose root cause, predict future resource levels and even correlate technical documents relevant to the specific failure. These advanced computational models will allow better insight and more precise control of ISS subsystems, increasing safety margins by speeding up anomaly resolution and reducing,engineering team effort and cost. This technology will make operating ISS more efficient and is directly applicable to next-generation exploration missions and Crew Exploration Vehicles.

Alena, Richard↗
NASA NTRS2008

Using Hyperspectral Imagery to Identify Turfgrass Stresses

The use of a form of remote sensing to aid in the management of large turfgrass fields (e.g. golf courses) has been proposed. A turfgrass field of interest would be surveyed in sunlight by use of an airborne hyperspectral imaging system, then the raw observational data would be preprocessed into hyperspectral reflectance image data. These data would be further processed to identify turfgrass stresses, to determine the spatial distributions of those stresses, and to generate maps showing the spatial distributions. Until now, chemicals and water have often been applied, variously, (1) indiscriminately to an entire turfgrass field without regard to localization of specific stresses or (2) to visible and possibly localized signs of stress for example, browning, damage from traffic, or conspicuous growth of weeds. Indiscriminate application is uneconomical and environmentally unsound; the amounts of water and chemicals consumed could be insufficient in some areas and excessive in most areas, and excess chemicals can leak into the environment. In cases in which developing stresses do not show visible signs at first, it could be more economical and effective to take corrective action before visible signs appear. By enabling early identification of specific stresses and their locations, the proposed method would provide guidance for planning more effective, more economical, and more environmentally sound turfgrass-management practices, including application of chemicals and water, aeration, and mowing. The underlying concept of using hyperspectral imagery to generate stress maps as guides to efficient management of vegetation in large fields is not new; it has been applied in the growth of crops to be harvested. What is new here is the effort to develop an algorithm that processes hyperspectral reflectance data into spectral indices specific to stresses in turfgrass. The development effort has included a study in which small turfgrass plots that were, variously, healthy or subjected to a variety of controlled stresses were observed by use of a hand-held spectroradiometer. The spectroradiometer readings in the wavelength range from 350 to 1,000 nm were processed to extract hyperspectral reflectance data, which, in turn, were analyzed to find correlations with the controlled stresses. Several indices were found to be correlated with drought stress and to be potentially useful for identifying drought stress before visible symptoms appear.

Hutto, Kendall↗
NASA NTRS1991

Performance evaluation of Platform Data ManagementSystem under various degrees of protocol implementation

The Platform Data Management System (DMS) collects Housekeeping (H/K), Payload (P/L) Engineering, and Payload Science data from various subsystems and payloads on the platform for transmission to the ground through the downlink via TDRSS. The DMS also distributes command data received from the ground to various subsystems and payloads. In addition, DMS distributes timing and safemode data. The function of collection and distribution of various types of data is performed by the Command and Data Handling (C&DH) subsystem of DMS. The C&DH subsystem uses for this purpose a number of data buses namely, Housekeeping, Payload Engineering, Payload Science, and Time and Safemode buses. Out of these buses, the H/K, P/L Engineering, and P/L Science buses are planned to be implemented by using MIL-STD 1553 bus. Most of the period covered was spent in developing a queue theoretic model of the 1553 Bus as used in the DMS. The aim is to use this model to test the performance and suitability of the 1553 Bus to the DMS under a number of alternative design scenarios.

Arozullah, Mohammed↗
NASA NTRS1992

A self-defining hierarchical data system

The Self-Defining Data System (SDS) is a system which allows the creation of self-defining hierarchical data structures in a form which allows the data to be moved between different machine architectures. Because the structures are self-defining they can be used for communication between independent modules in a distributed system. Unlike disk-based hierarchical data systems such as Starlink's HDS, SDS works entirely in memory and is very fast. Data structures are created and manipulated as internal dynamic structures in memory managed by SDS itself. A structure may then be exported into a caller supplied memory buffer in a defined external format. This structure can be written as a file or sent as a message to another machine. It remains static in structure until it is reimported into SDS. SDS is written in portable C and has been run on a number of different machine architectures. Structures are portable between machines with SDS looking after conversion of byte order, floating point format, and alignment. A Fortran callable version is also available for some machines.

Bailey, J.↗
NASA NTRS2004

Data processing pipeline with transaction-oriented data sharing

This paper makes three contributions to the area of modern science data processing systems. First, the paper describes the science data processing pipeline, developed at the Multi-mission Image Processing Lab of JPL, for transforming raw space data into high quality image data and automating the distribution of data using a high-performance file transaction service. File Exchange Interface is the file transaction service developed MIPL. Second, it presents the FEI component architecture in the are of file transaction management, security,a nd file integrity verfication. Finally, the paper presents the federated model for the FEI service to demonstrate how to create a pool of file trasaction services to support load balancing and service fallover, and simplify service management.

science data processing↗