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The Space Physics Analysis Network (SPAN) is a multi-mission, correlative data comparison network which links science research and data analysis computers in the U.S., Canada, and Europe. The purpose of this document is to provide Astronomy and Astrophysics scientists, currently reachable on SPAN, with basic information and contacts for access to correlative data bases, star catalogs, and other astrophysic facilities accessible over SPAN.
Aging aircraft structures and composite materials are requiring rapid inspection of large areas. Removal from the aircraft for NDE at an inspection facility is not economical as compared to field inspection. Detection and characterization of defects are labor intensive, time consuming and when the process is manual the results are subjected to human error. These limitations of NDE created a need for portable, user friendly inspection systems that can rapidly scan large areas of complex structures and locate all the detrimental material conditions. Addressing this need has been an evolutionary process that followed the technology trend, and unique devices were developed to allow rapid field inspection. This development involves multi-disciplinary approaches to integrate NDE, telerobotics, neural networks, advanced materials science, imbedded computing and automated control. These efforts have led to the development of various portable inspection systems and the current trend is towards fully automatic systems that will operate autonomously.
Since 1988, the Scientific Visualization Studio(SVS) at NASA Goddard Space Flight Center has produced scientific visualizations of NASA s scientific research and remote sensing data for public outreach. These visualizations take the form of images, animations, and end-to-end systems and have been used in many venues: from the network news to science programs such as NOVA, from museum exhibits at the Smithsonian to White House briefings. This presentation will give an overview of the major activities and accomplishments of the SVS, and some of the most interesting projects and systems developed at the SVS will be described. Particular emphasis will be given to the practices and procedures by which the SVS creates visualizations, from the hardware and software used to the structures and collaborations by which products are designed, developed, and delivered to customers. The web-based archival and delivery system for SVS visualizations at svs.gsfc.nasa.gov will also be described.
Many NASA planning problems are over-subscription problems - that is, there are a large number of possible goals of differing value, and the planning system must choose a subset &it car! be accomplished within the limited time and resources available. Examples include planning for telescopes like Hubble, SIRTF, and SOFIA; scheduling for the Deep Space Network; and planning science experiments for a Mars rover. Unfortunately, existing planning systems are not designed to deal with problems like this - they expect a well-defined conjunctive goal and terminate in failure unless the entire goal is achieved. In this paper we develop techniques for over-subscription problems that assist a classical planner in choosing which goals to achieve, and the order in which to achieve them. These techniques use plan graph cost-estimation techniques to construct an orienteering problem, which is then used to provide heuristic advice on the goals and goal order that should considered by a planner.
Pascal is a Mars Climate Network Mission that is being developed for NASA's Mars Scout Program. The mission would establish a network of 18 science weather stations distributed across the entire surface of Mars that operates for 3-10 Mars years (5.6- 18.8 Earth years). Pascal's instrument suite combines entry data from accelerometers and descent cameras, with landed data from pressure, opacity, temperature, wind speed, and water vapor to create a detailed global picture of Martian climate and weather. A panoramic landed camera system acquires images every 30 Sols to monitor changes in the landing environment due to winds. Analysis of data from the science stations, taken as often as once every 15 minutes, will provide a depth of understanding that will vastly increase our knowledge of Mars, and significantly impact site selection for future NASA missions. Pascal is the first mission ever to sample - in situ - the full global diversity of Mars and provide a continuous long-term presence on its surface.
Topics include: A Deep Space Network Portable Radio Science Receiver; Detecting Phase Boundaries in Hard-Sphere Suspensions; Low-Complexity Lossless and Near-Lossless Data Compression Technique for Multispectral Imagery; Very-Long-Distance Remote Hearing and Vibrometry; Using GPS to Detect Imminent Tsunamis; Stream Flow Prediction by Remote Sensing and Genetic Programming; Pilotless Frame Synchronization Using LDPC Code Constraints; Radiometer on a Chip; Measuring Luminescence Lifetime With Help of a DSP; Modulation Based on Probability Density Functions; Ku Telemetry Modulator for Suborbital Vehicles; Photonic Links for High-Performance Arraying of Antennas; Reconfigurable, Bi-Directional Flexfet Level Shifter for Low-Power, Rad-Hard Integration; Hardware-Efficient Monitoring of I/O Signals; Video System for Viewing From a Remote or Windowless Cockpit; Spacesuit Data Display and Management System; IEEE 1394 Hub With Fault Containment; Compact, Miniature MMIC Receiver Modules for an MMIC Array Spectrograph; Waveguide Transition for Submillimeter-Wave MMICs; Magnetic-Field-Tunable Superconducting Rectifier; Bonded Invar Clip Removal Using Foil Heaters; Fabricating Radial Groove Gratings Using Projection Photolithography; Gratings Fabricated on Flat Surfaces and Reproduced on Non-Flat Substrates; Method for Measuring the Volume-Scattering Function of Water; Method of Heating a Foam-Based Catalyst Bed; Small Deflection Energy Analyzer for Energy and Angular Distributions; Polymeric Bladder for Storing Liquid Oxygen; Pyrotechnic Simulator/Stray-Voltage Detector; Inventions Utilizing Microfluidics and Colloidal Particles; RuO2 Thermometer for Ultra-Low Temperatures; Ultra-Compact, High-Resolution LADAR System for 3D Imaging; Dual-Channel Multi-Purpose Telescope; Objective Lens Optimized for Wavefront Delivery, Pupil Imaging, and Pupil Ghosting; CMOS Camera Array With Onboard Memory; Quickly Approximating the Distance Between Two Objects; Processing Images of Craters for Spacecraft Navigation; Adaptive Morphological Feature-Based Object Classifier for a Color Imaging System; Rover Slip Validation and Prediction Algorithm; Safety and Quality Training Simulator; Supply-Chain Optimization Template; Algorithm for Computing Particle/Surface Interactions; Cryogenic Pupil Alignment Test Architecture for Aberrated Pupil Images; and Thermal Transport Model for Heat Sink Design.
The objective of the Mars Environmental Survey (MESUR) Network mission is to establish a global network of small science stations on the surface of Mars to operate concurrently over a minimum of one martian year.
The objective of the Mars Environmental Survey (MESUR) Network Mission is to establish a global network of small science stations on the surface of Mars to operate concurrently over a minimum of one martian year.
Using storytelling to present data has been demonstrated as an effective way to help data users gain deeper insight of information. For this purpose, the “Data in Action” story concept has been adopted by NASA Commercial Smallsat Data Acquisition (CSDA) Program to encourage creating and sharing data information in story form. To aid researchers in exploring similar stories and data in their fields of interest, we created an “Influence Network” within the “Data in Action” framework. The Influence Network is a data visualization system component which gathers information of story relationships using a concept called “influence,” which we define based on the number of visits and keyword similarity between stories. The visualization then provides insights into the influence flows between different stories within the system. The visualization of this “Influence Network” focuses on one story at a time, introducing a time series of neighbor stories that have the most influence to the currently focused story. By focusing on views over time and visualizing influence flows between stories, we aim to assist authors in understanding how their readers perceive their stories as well as advancing their methods for delivering more meaningful stories to expand and lower the barrier to use of CSDA datasets.
The world-class research infrastructure at the US Department of Energy (DOE) Office of Science (SC) provides the research community with premier observational, experimental, computational, and network capabilities. Each user facility is designed to provide unique capabilities to advance the core DOE mission in science and technology for its SC program to stimulate rich scientific discoveries and enhance its innovation ecosystem. Research communities gather and flourish around each user facility, bringing together new and enhanced perspectives. The continual reinvention of the practice of science — as users and staff forge novel approaches expressed in research workflows — unlocks new discoveries and propels scientific progress. Within this research ecosystem, the high-performance computing (HPC) and networking user facilities stewarded by the SC’s Advanced Scientific Computing Research (ASCR) program play a dynamic cross-cutting role, enabling complex workflows demanding high-performance data, networking, and computing solutions. The ASCR facilities enterprise seeks to understand and meet the needs and requirements across SC and DOE domain science programs and priority efforts, highlighted by the formal requirements review methodology. Between July and December 2024, the Energy Sciences Network (ESnet) and the Office of High Energy Physics (HEP) of the DOE-SC organized an ESnet requirements review of HEP-supported program activities. Preparation for these events included identification of key stakeholders: program and facility management, research groups, and technology providers. Each stakeholder group was asked to prepare formal case study documents about its relationship to the HEP program to build a complete understanding of the current, near-term, and long-term status, expectations, and processes that will support the science going forward.
Physics-based models have been mainstream in fluid dynamics for developing predictive models. In recent years, machine learning has offered a renaissance to the fluid community due to the rapid developments in data science, processing units, neural network based technologies, and sensor adaptations. So far in many applications in fluid dynamics, machine learning approaches have been mostly focused on a standard process that requires centralizing the training data on a designated machine or in a data center. In this article, we present a federated machine learning approach that enables localized clients to collaboratively learn an aggregated and shared predictive model while keeping all the training data on each edge device. We demonstrate the feasibility and prospects of such a decentralized learning approach with an effort to forge a deep learning surrogate model for reconstructing spatiotemporal fields. Our results indicate that federated machine learning might be a viable tool for designing highly accurate predictive decentralized digital twins relevant to fluid dynamics.
The Planetary Science Institute (PSI) was funded by SERCulpr to develop a communication network to alert observers of newly discovered near-earth asteroids (NEA's). This network is intended to encourage observers to obtain physical observations of NEA's, which are needed in order to characterize and assess the resource potential of these bodies. This network was declared operational in October 1990 via an announcement to the asteroid observing community. The PSI is also supported to develop the Near-Earth Asteroid Database (NEAD), a comprehensive database of physical and dynamical data on NEA's. In the past year, the database was updated on newly discovered NEA's during 1990, and new data on radar observations and dynamical classifications were added.
In the past decade, an evolving network of Mars relay orbiters has provided telecommunication relay services to the Mars Exploration Rovers, Spirit and Opportunity, and to the Mars Phoenix Lander, enabling high-bandwidth, energy-efficient data transfer and greatly increasing the volume of science data that can be returned from the Martian surface, compared to conventional direct-to-Earth links. The current relay network, consisting of NASA's Odyssey and Mars Reconnaissance Orbiter and augmented by ESA's Mars Express Orbiter, stands ready to support the Mars Science Laboratory, scheduled to arrive at Mars on Aug 6, 2012, with new capabilities enabled by the Electra and Electra-Lite transceivers carried by MRO and MSL, respectively. The MAVEN orbiter, planned for launch in 2013, and the ExoMars/Trace Gas Orbiter, planned for launch in 2016, will replenish the on-orbit relay network as the current orbiter approach their end of life. Currently planned support scenarios for this future relay network include an ESA EDL Demonstrator Module deployed by the 2016 ExoMars/TGO orbiter, and the 2018 NASA/ESA Joint Rover, representing the first step in a multimission Mars Sample Return campaign.
The Lunette mission concept for a network of small, inexpensive lunar landers has evolved over the last three years as the focus of space exploration activities in the US has changed. Originating in a concept for multiple landers launched as a secondary payload capable of regional science and site survey activities, Lunette has recently been developed into a Discovery-class mission concept that offers global lunar coverage enabling network science on a much broader scale. A particular mission concept has been refined by the Lunette team that would result in a low-cost global lunar geophysical network, comprised of two landers widely spaced on the near side of the moon. Each of the two identical landers would carry a suite of instruments that would make continuous measurements of seismic activity, heat flow, and the electromagnetic environment during the full lunar day/night cycle. Each lander would also deploy a next-generation laser retroreflector capable of improving on distance measurement accuracy by an order of magnitude over those emplaced by the previous Apollo and Lunokhod missions. This paper presents a comprehensive overview of the Lunette geophysical network mission concept, including mission and flight system design, as well as the key requirements and constraints that guided them.
In this project, we worked with the University of California at Berkeley/Center for Extreme Ultraviolet Astrophysics and five science museums (the National Air and Space Museum, the Science Museum of Virginia, the Lawrence Hall of Science, the Exploratorium., and the New York Hall of Science) to formulate plans for computer-based laboratories located at these museums. These Science Learning Laboratories would be networked and provided with real Earth and space science observations, as well as appropriate lesson plans, that would allow the general public to directly access and manipulate the actual remote sensing data, much as a scientist would.
Since its founding in 1992, Global Science & Technology, Inc. (GST), of Greenbelt, Maryland, has been developing technologies and providing services in support of NASA scientific research. GST specialties include scientific analysis, science data and information systems, data visualization, communications, networking and Web technologies, computer science, and software system engineering. As a longtime contractor to Goddard Space Flight Center s Earth Science Directorate, GST scientific, engineering, and information technology staff have extensive qualifications with the synthesis of satellite, in situ, and Earth science data for weather- and climate-related projects. GST s experience in this arena is end-to-end, from building satellite ground receiving systems and science data systems, to product generation and research and analysis.
Microwaveguides for spin waves based on yttrium iron garnet films and cross-like structures built on such waveguides are experimentally studied. Additionally, effects of the waveguides geometry, location of the microantennas for excitation and detection of the spin waves, and geometry of the waveguides junctions on the spin wave excitation and propagation efficiency are discussed.
We report the dense populations that inhabit global coastlines have an uncertain future due to increased flooding, storms, and human modification. The channel networks of deltas and marshes that plumb these coastlines present diverse architectures, including well-studied dendritic topologies. However, the quasi-stable loops that exist in nearly all coastal networks have not yet been explained. We present a model for self-organizing networks inspired by vascular biophysics to show that loops emerge when the relative forcings between rivers and tides are comparable, resulting in interplay between hydrodynamic forcings at short time scales relative to network evolution. Using field data and satellite imaging, we confirm this control on 21 field networks. Our comparison provides compelling evidence that hydrodynamic fluctuations are capable of stabilizing loops in geophysical systems.