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NASA NTRSDate not supplied

Distributed Spacecraft Autonomy - Development of Swarm Autonomy Capability and Scalability for Spacecraft

The Distributed Spacecraft Autonomy project is developing a suite of software tools that enable an operator to command and receive data from a swarm as a single entity, enable a swarm to autonomously coordinate its actions via distributed decision making and reactive closed-loop control, and model swarm behavior in the presence of anomalies or failures. Our use case is the mapping of the electron density of the ionosphere using radio tomography by coordinating the selection of appropriate GPS channels, and by recording Total Electron Count (TEC) measurements. DSA will be demonstrated onboard the NASA Ames Starling mission – a swarm of four small, LEO spacecraft, scheduled to launch in 2021. We will also perform a ground demonstration with simulated and hardware-in-the-loop elements, to validate the tools for controlling swarms of up to 100 assets. The capability to communicate autonomously between the swarm satellites is demonstrated via a sophisticated simulation architecture. Historical Plasmasphere TEC data obtained via dual-band Novatel GPS Receivers are utilized as a representative input dataset for the swarm. The representative TEC data and GPS satellite observability information is fed to the autonomous software package in place of a true real-time ground data collection process. The swarm satellites actively share status updates amongst one another and utilize multi-agent decision making to optimally identify regions of interest in the TEC distribution. The software, aware of the bandwidth limitations of the swarm satellites, prioritizes explorative measurements, which define the range of observability for the satellites, as well as exploitative measurements, which focus on maximizing the observance potential of regions with prolonged, elevated TEC density. The science of this study can ultimately be used to determine the dynamics and coupling of Earth’s magnetosphere, ionosphere, and atmosphere and their response to solar and terrestrial inputs. The findings can be applied to the imaging of critical, transient phenomena in the magnetosphere in later missions. Meanwhile, the swarm autonomy capabilities have far reaching potential in future satellite missions. As an experimental demonstration of the autonomous capabilities of the network, a message is first printed within a core Flight Executive (cFE) application. Two cFE applications that communicate with one another within the same core Flight System (cFS) are shown. Communication between mission applications on the internal cFE bus is extended to utilize Data Distribution Service (DDS) for vehicle-to-vehicle networking. The DDS middleware provides reliable delivery, routing, and topic subscription features over User Datagram Protocol (UDP). Leveraging Linux containerization, a networked set of satellite instances are generated by script to simulate swarm behavior. Swarm commanding and synchronization through the network is demonstrated under various topologies and data-loss conditions. Finally, autonomous swarm scalability from 2 satellites to 100 satellites is shown.

Distributed Autonomy↗
NASA NTRS2012

Mars Relay Lander and Orbiter Overflight Profile Estimation

This software allows science and mission operations to view graphs of geometric overflights of satellites and landers within the Mars (or other planetary) networks. It improves on the MaROS Web interface within any modern Web browser, in that it adds new capabilities to the MaROS suite. The profile for an overflight is an important element for selecting communication/ overflight opportunities between the landers and orbiters within the Mars network. Unfortunately, determining these estimates is very computationally expensive and difficult to compute by hand. This software allows the user to select different overflights (via the existing MaROS Web interface) and specify the smoothness of the estimation. Estimates for the geometric relationship between a lander and an orbiter are determined based upon the orbital conditions of the orbiter at the moment the orbiter rises above the horizon from the perspective of the lander. It utilizes 2-body orbital equations to propagate the trajectory through the duration of the view period, and returns profiles that represent the range between the two vehicles, and the elevation and azimuth angles of the orbiter as measured from the lander s position. The algorithms assume a 2-body relationship with an ideal, spherical planetary body, so therefore can see errors less than 2% at polar landing sites on Mars. These algorithms are being implemented to provide rough estimates rapidly for the geometry of a geometric view period where more complete data is unavailable, such as for planning purposes. While other software for this task exists, each at the time of this reporting has been contained within a much more complicated package. This tool allows science and mission operations to view the estimates with a few clicks of the mouse.

Wallick, Michael N.↗
NASA NTRS2007

NASA Tech Briefs, December 2007

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

Source record↗
NASA NTRS2016

Storage of Physical Sample Metadata in the Astrobiology Habitable Environments Database (AHED)

The National Aeronautics and Space Administration has begun an effort to store, curate, and publish information about physical samples collected and analyzed in conjunction with NASA-funded astrobiology research. Astrobiology is a multidisciplinary area of scientific research being conducted by collaborating teams of biologists, chemists, geologists, atmospheric scientists, oceanographers, astrophysicists, astronomers, and other specialists. Astrobiology studies the origin, evolution, and distribution of life in the Universe. NASA uses the results of astrobiology research to focus its future missions on targets of opportunity for the discovery of life off Earth. Astrobiology researchers conduct both field-based and laboratory-based research, during which physical samples are collected, processed, and catalogued. The cataloguing practices employed by different teams of astrobiologists vary widely, and there are no specific standards available to guide the collection and recording of astrobiology sample data. The disparity in data collection approaches and the lack of a centralized sample repository makes it difficult for astrobiology teams to share data and benefit from resultant synergies.To facilitate data sharing within the astrobiology community, NASA is developing a prototype database the Astrobiology Habitable Environments Database (AHED) and an associated set of data collection templates. The database will store information about samples, along with associated measurements and analyses, including information about biological cultures enriched or isolated from samples, and the results of analyses performed on the samples (e.g., via spectrography, microscopy, etc.). In addition, the system will store contextual information about field sites where samples were collected, the instruments or equipment used for analysis, and people and institutions involved in their collection. AHED is being implemented on top of Open Data Repository's Data Publisher [1], an open source software platform for the publication of scientific datasets. The data collection templates under development represent an initial attempt to propose a set of metadata for capture and storage within AHED. The design of these templates is being conducted by a consolidated group of astrobiologists from active research teams at NASA Ames Research Center, assisted by data science and software engineering specialists. These initial templates must be vetted with the broader astrobiology community through a defined process to ensure that they meet community needs. Each template captures a different type of data collection record. For each template, we are developing a list of fields to be captured, including a set of required entry fields, a set of recommended but optional fields, and a set of discretionary fields. A datatype selected from a variety of text and numeric types is specified for each field. Included is a 'choice' type that restricts user input to an enumerated list of values. Many of the fields and field values capture information of particular interest to the astrobiology community, and are intended to facilitate search and retrieval of relevant data across multiple datasets.

Keller, Rich↗
DOE OSTI2024

Nucleus++ : a new tool bridging AME and NUBASE for advancing nuclear data analysis

The newly developed software, Nucleus++ , is an advanced tool for displaying basic nuclear physics properties from NUBASE and integrating comprehensive mass information for each nuclide from Atomic Mass Evaluation. Additionally, it allows users to compare experimental nuclear masses with predictions from different mass models. Building on the success and learning experiences of its predecessor, Nucleus , this enhanced tool introduces improved functionality and compatibility. With its user-friendly interface, Nucleus++ was designed as a valuable tool for scholars and practitioners in the field of nuclear science. Finally, this article offers an in-depth description of Nucleus++ , highlighting its main features and anticipated impacts on nuclear science research.

AME↗
NASA NTRS2008

The Telesupervised Adaptive Ocean Sensor Fleet (TAOSF) Architecture: Coordination of Multiple Oceanic Robot Boats

Earth science research must bridge the gap between the atmosphere and the ocean to foster understanding of Earth s climate and ecology. Ocean sensing is typically done with satellites, buoys, and crewed research ships. The limitations of these systems include the fact that satellites are often blocked by cloud cover, and buoys and ships have spatial coverage limitations. This paper describes a multi-robot science exploration software architecture and system called the Telesupervised Adaptive Ocean Sensor Fleet (TAOSF). TAOSF supervises and coordinates a group of robotic boats, the OASIS platforms, to enable in-situ study of phenomena in the ocean/atmosphere interface, as well as on the ocean surface and sub-surface. The OASIS platforms are extended deployment autonomous ocean surface vehicles, whose development is funded separately by the National Oceanic and Atmospheric Administration (NOAA). TAOSF allows a human operator to effectively supervise and coordinate multiple robotic assets using a sliding autonomy control architecture, where the operating mode of the vessels ranges from autonomous control to teleoperated human control. TAOSF increases data-gathering effectiveness and science return while reducing demands on scientists for robotic asset tasking, control, and monitoring. The first field application chosen for TAOSF is the characterization of Harmful Algal Blooms (HABs). We discuss the overall TAOSF architecture, describe field tests conducted under controlled conditions using rhodamine dye as a HAB simulant, present initial results from these tests, and outline the next steps in the development of TAOSF.

sensor web↗
NASA NTRS2004

DEMO: the Autonomous Sciencecraft Experiment onboard the EO-1 spacecraft

The Autonomous Sciencececraft Experiment (ASE), currently flying onboard the Earth Observing-1 (EO-1) spacecraft, integrates several autnomoy software technologies enabling autnomous science analysis and mission planning. The experiment demonstrates the potential for future space missions to use onboard decision-making to respond autonomously to capture short-lived science phenomena. The AAAI software demonstration will consist of two sections: a real-time display of an ASE-commanded ground contact from the EO-1 spacecraft, and a simulation of the full ASE autonomous science-response scenario.

EO-1 spacecraft↗
NASA NTRS2004

The autonomous sciencecraft experiment onboard the EO-1 spacecraft

The Autonomous Sciencecraft Experiment (ASE), currently flying onboard the Earth Observing-1 (EO-I) spacecraft, integrates several autonomy software technologies enabling autonomous science analysis and mission planning. The experiment demonstrates the potential for future space missions to use onboard decision-making to respond autonomously to capture short-lived science phenomena. The AAAI software demonstration will consist of two sections: a real-time display of an ASE-commanded ground contact from the EO-1 spacecraft, and a simulation of the full ASE autonomous science-response scenario.

Earth Observatory (EO)↗
DOE OSTI2024

RNA-Puzzles Round V: blind predictions of 23 RNA structures

RNA-Puzzles is a collective endeavor dedicated to the advancement and improvement of RNA three-dimensional structure prediction. With agreement from structural biologists, RNA structures are predicted by modeling groups before publication of the experimental structures. We report a large-scale set of predictions by 18 groups for 23 RNA-Puzzles: 4 RNA elements, 2 Aptamers, 4 Viral elements, 5 Ribozymes and 8 Riboswitches. We describe automatic assessment protocols for comparisons between prediction and experiment. Our analyses reveal some critical steps to be overcome to achieve good accuracy in modeling RNA structures: identification of helix-forming pairs and of non-Watson–Crick modules, correct coaxial stacking between helices and avoidance of entanglements. Three of the top four modeling groups in this round also ranked among the top four in the CASP15 contest.

59 BASIC BIOLOGICAL SCIENCES↗
NASA NTRS1976

Caltech/JPL Conference on Image Processing Technology, Data Sources and Software for Commercial and Scientific Applications

Recent advances in image processing and new applications are presented to the user community to stimulate the development and transfer of this technology to industrial and commercial applications. The Proceedings contains 37 papers and abstracts, including many illustrations (some in color) and provides a single reference source for the user community regarding the ordering and obtaining of NASA-developed image-processing software and science data.

Redmann, G. H.↗
NASA NTRS1977

NASCAP, a three-dimensional Charging Analyzer Program for complex spacecraft

A computer code, NASCAP (NASA Charging Analyzer Program), has been developed by Systems, Science and Software under contract to NASA-LeRC to simulate the charging of a complex spacecraft in geosynchronous orbit. The capabilities of the NASCAP code include a fully three-dimensional solution of Poisson's equation about an object having considerable geometrical and material complexity, particle tracking, shadowing in sunlight, calculation of secondary emission, backscatter and photoemission, and graphical output. A model calculation shows how the NASCAP code may be used to improve our understanding of the spacecraft-plasma interaction.

Katz, I.↗
NASA NTRS1982

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

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

Moore, J. W.↗
NASA NTRS1995

Research and technology 1995 annual report

As the NASA Center responsible for assembly, checkout, servicing, launch, recovery, and operational support of Space Transportation System elements and payloads, the John F. Kennedy Space Center is placing increasing emphasis on its advanced technology development program. This program encompasses the efforts of the Engineering Development Directorate laboratories, most of the KSC operations contractors, academia, and selected commercial industries - all working in a team effort within their own areas of expertise. This edition of the Kennedy Space Center Research and Technology 1995 Annual Report covers efforts of all these contributors to the KSC advanced technology development program, as well as technology transfer activities. Major areas of research include environmental engineering, automation, robotics, advanced software, materials science, life sciences, mechanical engineering, nondestructive evaluation, and industrial engineering.

Source record↗
NASA NTRS2000

Photochemical Phenomenology Model for the New Millenium

This project tackles the problem of conversion of validated a priori physics-based modeling capabilities, specifically those relevant to the analysis and interpretation of planetary atmosphere observations, to application-oriented software for use in science and science-support activities. The software package under development, named the Photochemical Phenomenology Modeling Tool (PPMT), has particular focus on the atmospheric remote sensing data to be acquired by the CIRS instrument during the CASSINI Jupiter flyby and orbital tour of the Saturnian system. Overall, the project has followed the development outline given in the original proposal, and the Year 1 design and architecture goals have been met. Specific accomplishments and the difficulties encountered are summarized in this report. Most of the effort has gone into complete definition of the PPMT interfaces within the context of today's IT arena: adoption and adherence to the CORBA Component Model (CCM) has yielded a solid architecture basis, and CORBA-related issues (services, specification options, development plans, etc.) have been largely resolved. Implementation goals have been redirected somewhat so as to be more relevant to the upcoming CASSINI flyby of Jupiter, with focus now being more on data analysis and remote sensing retrieval applications.

Bishop, James↗
NASA NTRS2001

Live from Space Station Learning Technologies Project

This is the Final Report for the Live From Space Station (LFSS) project under the Learning Technologies Project FY 2001 of the MSFC Education Programs Department. AZ Technology, Inc. (AZTek) has developed and implemented science education software tools to support tasks under the LTP program. Initial audience consisted of 26 TreK in the Classroom schools and thousands of museum visitors to the International Space Station: The Earth Tour exhibit sponsored by Discovery Place museum.

Source record↗
NASA NTRS2005

Monitoring Floods with NASA's ST6 Autonomous Sciencecraft Experiment: Implications on Planetary Exploration

NASA's New Millennium Program (NMP) Autonomous Sciencecraft Experiment (ASE) [1-3] has been successfully demonstrated in Earth-orbit. NASA has identified the development of an autonomously operating spacecraft as a necessity for an expanded program of missions exploring the Solar System. The versatile ASE spacecraft command and control, image formation, and science processing software was uploaded to the Earth Observer 1 (EO-1) spacecraft in early 2004 and has been undergoing onboard testing since May 2004 for the near real-time detection of surface modification related to transient geological and hydrological processes such as volcanism [4], ice formation and retreat [5], and flooding [6]. Space autonomy technology developed as part of ASE creates the new capability to autonomously detect, assess, react to, and monitor dynamic events such as flooding. Part of the challenge has been the difficulty to observe flooding in real time at sufficient temporal resolutions; more importantly, it is the large spatial extent of most drainage networks coupled with the size of the data sets necessary to be downlinked from satellites that make it difficult to monitor flooding from space. Below is a description of the algorithms (referred to as ASE Flood water Classifiers) used in tandem with the Hyperion spectrometer instrument on EO-1 to identify flooding and some of the test results.

Ip, Felipe↗