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Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

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At least 145 records · Page 8

Near-Earth asteroids: Observer alert network and database analysis

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.

Davis, Donald R.↗

Relay Support for the Mars Science Laboratory and the Coming Decade of Mars Relay Network Evolution

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.

MAVEN↗

A Discovery-Class Lunette Mission Concept for a Lunar Geophysical Network

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.

Elliott, John↗

A Science Information Infrastructure for Access to Earth and Space Science Data through the Nation's Science Museums

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.

Murray, S.↗

Supporting Weather Data

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.

Source record↗

Future Evolution of NASA's SLR and VLBI Networks

Over the first half of this decade the NASA Space Geodesy Program is planning a major transformation of its existing (Satellite Laser Ranging) SLR network of stations and also further evolutionary changes to its network of (Very Long Base Interferometry) VLBI stations. These network changes will be made to meet the ever more demanding requirements of the earth and space science programs that these networks support while seeking through automation and electronic data communications to increase efficiency and decrease cost of operations and maintenance. The major aspects of the NASA plan will be outlined and the benefits to the scientific community will be addressed.

Bosworth, John M.↗

DSMS science operations concept

The Deep Space Mission System (DSMS) Science Operations Concept describes the vision for enabling the use of the DSMS, particularly the Deep Space Network (DSN) for direct science observations in the areas of radio astronomy, planetary radar, radio science and VLBI.

deep space science↗

The Plant Phenology Monitoring Design for the National Ecological Observatory Network

Phenology is an integrative science that comprises the study of recurring biological activities or events. In an era of rapidly changing climate, the relationship between the timing of those events and environmental cues such as temperature, snowmelt, water availability, or day length are of particular interest. This article provides an overview of the observer-based plant phenology sampling conducted by the U.S. National Ecological Observatory Network (NEON), the resulting data, and the rationale behind the design. Trained technicians will conduct regular in situ observations of plant phenology at all terrestrial NEON sites for the 30-yr life of the observatory. Standardized and coordinated data across the network of sites can be used to quantify the direction and magnitude of the relationships between phenology and environmental forcings, as well as the degree to which these relationships vary among sites, among species, among phenophases, and through time. Vegetation at NEON sites will also be monitored with tower-based cameras, satellite remote sensing, and annual high-resolution airborne remote sensing. Ground-based measurements can be used to calibrate and improve satellite-derived phenometrics. NEON's phenology monitoring design is complementary to existing phenology research efforts and citizen science initiatives throughout the world and will produce interoperable data. By collocating plant phenology observations with a suite of additional meteorological, biophysical, and ecological measurements (e.g., climate, carbon flux, plant productivity, population dynamics of consumers) at 47 terrestrial sites, the NEON design will enable continental-scale inference about the status, trends, causes, and ecological consequences of phenological change.

phenology↗

Implementing Delay/Disruption Tolerant Networking for NASA’s Plankton, Aerosol, Clouds, ocean Ecosystem (PACE) Mission

NASA’s Plankton, Aerosol, Clouds, ocean Ecosystem (PACE) mission will be the first NASA science mission to use Delay/Disruption Tolerant Networking (DTN) for routine operations. The DTN Bundle Protocol (BP) is being integrated into the core Flight Software (cFS) for the transfer of house-keeping files. DTN nodes will also be integrated into the Near Space Network (NSN) ground stations and the PACE Mission Operations Center. This paper will describe the DTN implementations, the PACE DTN operations concept and how this mission is a significant step towards the Solar System Internet.

dtn↗

(abstract) The Role of the Deep Space Network for Cassini

Cassini radio science experiments have several categories of requirements for DSN tracking services. The three main areas for upgrade are in Ka-band, long-term frequence stability, and short-term frequency stability/phase noise level.

Cassini Deep Space Network telecommunications Grav↗

High-Rate Wireless Airborne Network Demonstration (HiWAND) Flight Test Results

An increasing number of flight research and airborne science experiments now contain network-ready systems that could benefit from a high-rate bidirectional air-to-ground network link. A prototype system, the High-Rate Wireless Airborne Network Demonstration, was developed from commercial off-the-shelf components while leveraging the existing telemetry infrastructure on the Western Aeronautical Test Range. This approach resulted in a cost-effective, long-range, line-of-sight network link over the S and the L frequency bands using both frequency modulation and shaped-offset quadrature phase-shift keying modulation. This paper discusses system configuration and the flight test results.

Franz, Russell↗

High-Rate Wireless Airborne Network Demonstration (HiWAND) Flight Test Results

An increasing number of flight research and airborne science experiments now contain network-ready systems that could benefit from a high-rate bidirectional air-to-ground network link. A prototype system, the High-Rate Wireless Airborne Network Demonstration, was developed from commercial off-the-shelf components while leveraging the existing telemetry infrastructure on the Western Aeronautical Test Range. This approach resulted in a cost-effective, long-range, line-of-sight network link over the S and the L frequency bands using both frequency modulation and shaped-offset quadrature phase-shift keying modulation. This report discusses system configuration and the flight test results.

Franz, Russell↗

Understanding Machine Learning in Earth Science: A Natural Language Processing Approach

Machine learning (ML) is being increasingly utilized in Earth science research. Benefits of ML include efficiency, reduction of human error, and ability to extract hidden patterns within data. However, the mutual lack of each other’s domain knowledge by ML and Earth science stands as a barrier to timely and effective implementation. Earth science, in particular, faces challenges in generating sample data, compared to those of traditional ML problems such as face recognition or stock predictions, where data is abundant and not lacking in ground truth, which is necessary for labeling. Earth science data are more varying in formats, such as HDF5 and image resolutions, and are not standardized across instruments, even within a given Earth science discipline. Previous studies have been done to outline the specific challenges that Earth science faces with ML, while others have focused on using existing publications to mine information efficiently. Other resources such as Scikit-Learn have developed decision trees for choosing appropriate machine learning algorithms, but application within Earth science subjects becomes much more complex. For the current study, we propose a methodology and tool that aids in implementation of ML in Earth science using natural language processing (NLP). Our work comprises three main parts: (1) analyzing existing publications related to ML and Earth science, using natural language processing: (2) extracting from the publications information on ML models subjects in Earth Science: and (3) visualizing the extracted relationships as a network graph. The resulting network graph should aid the Earth science communities in applying optimal ML algorithms and guiding data preparation through visualization of similar studies. The network graph and analysis of document similarity will be the basis of our next step, which is to develop a decision tree for selecting optimal machine learning methodologies for specified Earth science applications.

Zheng, Laura↗

Neural Network Machine Learning and Dimension Reduction for Data Visualization

Neural network machine learning in computer science is a continuously developing field of study. Although neural network models have been developed which can accurately predict a numeric value or nominal classification, a general purpose method for constructing neural network architecture has yet to be developed. Computer scientists are often forced to rely on a trial-and-error process of developing and improving accurate neural network models. In many cases, models are constructed from a large number of input parameters. Understanding which input parameters have the greatest impact on the prediction of the model is often difficult to surmise, especially when the number of input variables is very high. This challenge is often labeled the "curse of dimensionality" in scientific fields. However, techniques exist for reducing the dimensionality of problems to just two dimensions. Once a problem's dimensions have been mapped to two dimensions, it can be easily plotted and understood by humans. The ability to visualize a multi-dimensional dataset can provide a means of identifying which input variables have the highest effect on determining a nominal or numeric output. Identifying these variables can provide a better means of training neural network models; models can be more easily and quickly trained using only input variables which appear to affect the outcome variable. The purpose of this project is to explore varying means of training neural networks and to utilize dimensional reduction for visualizing and understanding complex datasets.

Liles, Charles A.↗

CLAIRE: Enabling Heterogeneous Communication Network Optimization for Robust and Resilient Operations

In this paper, we present the capabilities of the CLAIRE System which provides resilient communications for NASA in presence of interference and congestion for a heterogeneous multi-vendor network. CLAIRE increases mission science data return to improve resource efficiencies and ensures resilience in the unpredictable space environment for NASA missions and communication networks. CLAIRE provides technology / waveform agnostic cognitive control plane that is instantiated at the Application Layer (APP) so that it can ride on NASA’s HDTN bundle protocol or any other protocol stack that is used by the network. The cognitive control plane is instantiated using Heartbeats (HTBTs). CLAIRE is assisted by Wideband UHF-Ka Band RF Sensing that leverages advances in the Direct Digital Transceiver (DDTRX) technology. The Wideband RF Sensing is driven by statistical signal processing and machine learning algorithms. Interference is mitigated using Dynamic Spectrum Access (DSA). Finally, CLAIRE addresses congestion using spectrum aware packet forwarding algorithm. CLAIRE provides an extensible protocol that allows passing of RF spectrum situational awareness, cross-layer sensing, delay tolerant networking and dynamic spectrum access information that can help with network optimization. Cross-Layer Sensing (CLS) and CLAIRE Decision Engine (CDE) enable spectrum and delay aware packet forwarding and Dynamic Spectrum Access during cases of severe interference.

cognitive communications↗

Innovations in Delta Differential One-Way Range: from Viking to Mars Science Laboratory

The Deep Space Network has provided the capability for very-long-baseline interferometry measurements in support of spacecraft navigation since the late 1970s. Both system implementation and the importance of such measurements to flight projects have evolved significantly over the past three decades. Innovations introduced through research and development programs have led to much better performance. This paper provides an overview of the development and use of interferometric tracking techniques in the DSN starting with the Viking era and continuing with a description of the current system and its planned use to support Mars Science Laboratory.

VLBI Spacecraft Navigation↗

Digital signal processing in the radio science stability analyzer

The Telecommunications Division has built a stability analyzer for testing Deep Space Network installations during flight radio science experiments. The low-frequency part of the analyzer operates by digitizing wave signals with bandwidths between 80 Hz and 45 kHz. Processed outputs include spectra of signal, phase, amplitude, and differential phase; time series of the same quantities; and Allan deviation of phase and differential phase. This article documents the digital signal-processing methods programmed into the analyzer.

Greenhall, C. A.↗

Enabling Communication and Navigation Technologies for Future Near Earth Science Missions

In 2015, the Earth Regimes Network Evolution Study (ERNESt) proposed an architectural concept and technologies that evolve to enable space science and exploration missions out to the 2040 timeframe. The architectural concept evolves the current instantiations of the Near Earth Network and Space Network with new technologies to provide a global communication and navigation network that provides communication and navigation services to a wide range of space users in the near Earth domain. The technologies included High Rate Optical Communications, Optical Multiple Access (OMA), Delay Tolerant Networking (DTN), User Initiated Services (UIS), and advanced Position, Navigation, and Timing technology. This paper describes the key technologies and their current technology readiness levels. Examples of science missions that could be enabled by the technologies and the projected operational benefits of the architecture concept to missions are also described.

Laser↗