SEARCH · Engineering Papers
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.
Quote a phrase for an exact phrase match. Source license links do not imply unrestricted reuse.
Doppler shift measurements derived from closed-loop radio tracking of distant spacecraft by ground stations of the Deep Space Network (DSN) are one of the principal means used for interplanetary navigation.
Delay/Disruption Tolerant Networking (DTN) promises solutions in solving space communications challenges arising from disconnections as orbiters lose line-of-sight with landers, long propagation delays over interplanetary links, and other phenomena. DTN has been identified as the basis for the future NASA space communications network backbone, and international standardization is progressing through both the Consultative Committee for Space Data Systems (CCSDS) and the Internet Engineering Task Force (IETF). JPL has developed an implementation of the DTN architecture, called the Interplanetary Overlay Network (ION). ION is specifically implemented for space use, including design for use in a real-time operating system environment and high processing efficiency. In order to raise the Technology Readiness Level of ION, the first deep space flight demonstration of DTN is underway, using the Deep Impact (DI) spacecraft. Called the Deep Impact Network (DINET), operations are planned for Fall 2008. An essential component of the DINET project is the Experiment Operations Center (EOC), which will generate and receive the test communications traffic as well as "out-of-DTN band" command and control of the DTN experiment, store DTN flight test information in a database, provide display systems for monitoring DTN operations status and statistics (e.g., bundle throughput), and support query and analyses of the data collected. This paper describes the DINET EOC and its value in the DTN flight experiment and potential for further DTN testing.
We describe the first use from space of the Bundle Protocol for Delay-Tolerant Networking (DTN) and lessons learned from experiments made and experience gained with this protocol. The Disaster Monitoring Constellation (DMC), constructed by Surrey Satellite Technology Ltd (SSTL), is a multiple-satellite Earth-imaging low-Earth-orbit sensor network in which recorded image swaths are stored onboard each satellite and later downloaded from the satellite payloads to a ground station. Store-and-forward of images with capture and later download gives each satellite the characteristics of a node in a disruption-tolerant network. Originally developed for the Interplanetary Internet, DTNs are now under investigation in an Internet Research Task Force (IRTF) DTN research group (RG), which has developed a bundle architecture and protocol. The DMC is technically advanced in its adoption of the Internet Protocol (IP) for its imaging payloads and for satellite command and control, based around reuse of commercial networking and link protocols. These satellites use of IP has enabled earlier experiments with the Cisco router in Low Earth Orbit (CLEO) onboard the constellation s UK-DMC satellite. Earth images are downloaded from the satellites using a custom IP-based high-speed transfer protocol developed by SSTL, Saratoga, which tolerates unusual link environments. Saratoga has been documented in the Internet Engineering Task Force (IETF) for wider adoption. We experiment with the use of DTNRG bundle concepts onboard the UK-DMC satellite, by examining how Saratoga can be used as a DTN convergence layer to carry the DTNRG Bundle Protocol, so that sensor images can be delivered to ground stations and beyond as bundles. Our practical experience with the first successful use of the DTNRG Bundle Protocol in a space environment gives us insights into the design of the Bundle Protocol and enables us to identify issues that must be addressed before wider deployment of the Bundle Protocol. Published in 2010 by John Wiley & Sons, Ltd. KEY WORDS: Internet; UK-DMC; satellite; Delay-Tolerant Networking (DTN); Bundle Protocol
The Deep Space Network (DSN) is an international network of antennas that supports interplanetary spacecraft missions and radio and radar astronomy observations for the exploration of the solar system and the universe. DSN provides the vital two-way communications link that guides and controls planetary explorers, and brings back the images and new scientific information they collect. In an attempt to streamline operations and improve overall services provided by the Deep Space Network a DSN-wide portal is under development. The project is one step in a larger effort to centralize the data collected from current missions including user input parameters for spacecraft to be tracked. This information will be placed into a principal repository where all operations related to the DSN are stored. Furthermore, providing statistical characterization of data volumes will help identify technically feasible tracking opportunities and more precise mission planning by providing upfront scheduling proposals. Business intelligence tools are to be incorporated in the output to deliver data visualization.
Abstract Mercury's small magnetosphere is embedded in the dynamic and intense solar wind environment characteristic of the inner heliosphere. Both the magnitude and orientation of the interplanetary magnetic field (IMF) significantly influence the solar wind‐magnetospheric interaction at Mercury, driving phenomena such as magnetic reconnection. The MErcury Surface, Space Environment, Geochemistry and Ranging (MESSENGER) spacecraft provided in‐situ magnetic field measurements of the solar wind, the magnetosheath, and the magnetosphere along each orbit. However, it is a challenge to directly assess the IMF's impact on Mercury's plasma environment due to the temporal separation between observations within the solar wind and the magnetosphere, especially in the absence of an upstream monitor. Here, we present a feedforward neural network (FNN) trained on a subset of magnetosheath observations to estimate the strength and orientation of the IMF upstream of the bow shock. Utilizing magnetosheath magnetic field, cylindrical spatial coordinates, and heliocentric distance measurements, the FNN predicts upstream IMF conditions with an score of 0.70 and mean averaged error of 5.3 nT, thereby greatly decreasing the temporal separation between IMF estimates and magnetospheric measurements throughout the MESSENGER mission. This approach yields IMF estimates for all magnetosheath data measured by MESSENGER, providing a useful tool for future investigations of the IMF impact on Mercury's magnetosphere. This method will be integrable with the dual‐spacecraft BepiColombo magnetosheath measurements, providing useful estimates of upstream IMF conditions particularly during the extended periods in which neither spacecraft sample the solar wind. Our results demonstrate the utility of machine learning techniques on advancing space science research.
During cosmic ray propagation in interplanetary space there appear characteristic cosmic-ray intensity scintillations which are due to charged particle scattering on random inhomogeneities of the interplanetary magnetic field. The power spectra of cosmic ray scintillations on the Earth during some intervals from 1977 to 1982 (for quiet periods, for solar flares and Forbush decreases due to power shock waves) have been calculated from five-minute, one and two-hour values of the cosmic-ray intensity measured by the scintillator supertelescope IZMIRAN. The spectra were estimated by the methods of spectral analysis and by autoregressive methods which mutually control each other and make it possible not only to analyze scintillation powers at distinguished frequencies, but also to determine the behavior of spectrum slopes in some frequency ranges.
The transient gamma-ray burst observed on March 5, 1979 by the nine spacecraft forming the interplanetary gamma-ray burst network is discussed. Measurements reveal the event to be unlike any previously observed gamma-ray burst or X-ray burster, with a maximum intensity greater than several thousandths erg/sq cm per sec, a rise time of less than 200 microsec, a narrow and featureless initial spike and a regular 8-sec oscillation with a compound pulse shape. The source of the transient has been localized to a region including the supernova remnant N 49 in the Large Magellanic Cloud, at a distance of 55 pc, and a ratio of X-ray point-source steady state to transient emission of less than 10 to the -9th was obtained. The identification of the burst source with the supernova remnant at that distance would require an enormous source output if it was radiated isotropically, and substantially less if beaming is present. Alternatively, the event could be explained by a nearby, invisible neutron star.
The Goddard program of gamma-ray burst studies is briefly reviewed. The past results, present status and future expectations are outlined regarding our endeavors using experiments on balloons. IMP-6 and IMP-7, OGO-3, ISEE-1 and ISEE-3, Helios-2, Solar Maximum Mission, the Einstein Observatory, Solar Polar and the Gamma Ray Observatory, and with the interplanetary gamma-ray burst networks, to which some of these spacecraft sensors contribute. Additional emphasis is given to the recent discovery of a new type of gamma-ray transient, detected on 5 March, 1979.
The celestial source location of the November 19, 1978, intense gamma ray burst has been determined from data obtained with the interplanetary gamma-ray sensor network by means of long-baseline wave front timing instruments. Each of the instruments was designed for studying events with observable spectra of approximately greater than 100 keV, and each provides accurate event profile timing in the several millisecond range. The data analysis includes the following: the triangulated region is centered at (gamma, delta) 1950 = (1h16m32s, -28 deg 53 arcmin), at -84 deg galactic latitude, where the star density is very low and the obscuration negligible. The gamma-ray burst source region, consistent with that of a highly polarized radio source described by Hjellming and Ewald (1981), may assist in the source modeling and may facilitate the understanding of the source process. A marginally identifiable X-ray source was also found by an Einstein Observatory investigation. It is concluded that the burst contains redshifted positron annihilation and nuclear first-excited iron lines, which is consistent with a neutron star origin.
The source location data analyzed by the first and second interplanetary gamma ray burst spacecraft networks are reviewed. The possibilities of additional networks and of related studies in other disciplines, and the prospects for real time optical transient observations and for the definition of gamma ray burst sources by optical transient astronomy are also reviewed.
The source location data analyzed by the first and second interplanetary gamma ray burst spacecraft networks are reviewed. The possibilities of additional networks and of related studies in other disciplines, and the prospects for real time optical transient observations and for the definition of gamma ray burst sources by optical transient astronomy are also reviewed. Previously announced in STAR as N82-31290
Moon Burst Energetics All-sky Monitor (MoonBEAM) is a CubeSat concept of deploying gamma-ray detectors in cislunar space to increase gamma-ray burst detections and improve localization precision with the timing triangulation technique. A gamma-ray instrument in cislunar orbit will have greatly reduced sky blockage compared to instruments in low Earth orbit. Working in conjunction with another instrument in low Earth orbit, MoonBEAM can also help constrain the arrival direction of the wavefront to an annulus on the sky by utilizing the light arrival times between the different orbits. This method has been demonstrated by the Interplanetary Gamma- Ray Burst Timing Network. However, delays in data downlink for instruments outside the Tracking and Data Relay Satellite network prevent rapid follow-up observations. We present here a gamma-ray CubeSat concept in Earth-Moon L3 halo orbit that is capable of faster response and provide a timing baseline for localization improvement. Such an instrument would aid in the gravitational wave follow-up observations in other wavelengths to identify the gamma-ray burst afterglow and kilonova emission. Reducing the region of interest makes identifying afterglows much faster, allowing for rapid on-source observations and monitoring of the rise and decay times. It will also prevent source confusion between two transients and enable robust association. A gamma-ray detection could also increase the confidence of a simultaneous but marginal gravitational wave signal, extending the detection horizon. MoonBEAM is a 12U CubeSat concept of deploying gamma-ray detectors in cislunar space to increase gamma-ray burst detections and improve localization precision with the timing triangulation technique. Such an instrument would probe the extreme processes in cosmic collision of compact objects and facilitate multi-messenger time-domain astronomy to explore the end of stellar life cycles and black hole formations.
An autonomous/adaptive interplanetary navigation architecture employing neural networks and genetic algorithms is being developed that will alert navigators when a shift from optimal to suboptimal filtering occurs and assist in modifying the filter parameters to resume optical tracking.
The Disaster Monitoring Constellation (DMC), constructed by Survey Satellite Technology Ltd (SSTL), is a multisatellite Earth-imaging low-Earth-orbit sensor network where captured image swaths are stored onboard each satellite and later downloaded from the satellite payloads to a ground station. Store-and-forward of images with capture and later download gives each satellite the characteristics of a node in a Delay/Disruption Tolerant Network (DTN). Originally developed for the Interplanetary Internet, DTNs are now under investigation in an Internet Research Task Force (IRTF) DTN research group (RG), which has developed a bundle architecture and protocol. The DMC is currently unique in its adoption of the Internet Protocol (IP) for its imaging payloads and for satellite command and control, based around reuse of commercial networking and link protocols. These satellites use of IP has enabled earlier experiments with the Cisco router in Low Earth Orbit (CLEO) onboard the constellation's UK-DMC satellite. Earth images are downloaded from the satellites using a custom IPbased high-speed transfer protocol developed by SSTL, Saratoga, which tolerates unusual link environments. Saratoga has been documented in the Internet Engineering Task Force (IETF) for wider adoption. We experiment with use of DTNRG bundle concepts onboard the UKDMC satellite, by examining how Saratoga can be used as a DTN convergence layer to carry the DTNRG Bundle Protocol, so that sensor images can be delivered to ground stations and beyond as bundles. This is the first successful use of the DTNRG Bundle Protocol in a space environment. We use our practical experience to examine the strengths and weaknesses of the Bundle Protocol for DTN use, paying attention to fragmentation, custody transfer, and reliability issues.
During periods of rapidly changing geomagnetic conditions electric fields form within the Earth’s surface and induce currents known as geomagnetically induced currents(GICs), which interact with unprotected electrical systems our society relies on. In this study, we train multi-variate Long-Short Term Memory neural networks to predict magnitude of north-south component of the geomagnetic field (|BN|) at multiple ground magnetometer stations across Alaska provided by the SuperMAG database with a future goal of predicting geomagnetic field disturbances. Each neural network is driven by solar wind and interplanetary magnetic field inputs from the NASA OMNI database spanning from 2000–2015 and is fine tuned for each station to maximize the effectiveness in predicting |BN|. The neural networks are then compared against multivariate linear regression models driven with the same inputs at each station using Heidke skill scores with thresholds at the 50, 75, 85, and 99 percentiles for |BN|. The neural network models show significant increases over the linear regression models for |BN| thresholds. We also calculate the Heidke skill scores for d|BN|/dt by deriving d|BN|/dt from |BN| predictions. However, neural network models do not show clear outperformance compared to the linear regression models. To retain the sign information and thus predict BN instead of |BN|, a secondary so-called polarity model is utilized. The polarity model is run in tandem with the neural networks predicting geomagnetic field in a coupled model approach and results in a high correlation between predicted and observed values for all stations. We find this model a promising starting point for a machine learned geomagnetic field model to be expanded upon through increased output time history and fast turnaround times.
An extremely intense burst of hard X-rays and gamma-rays that was recorded by the nine interplanetary spacecraft of the burst sensor network and localized by time-of-flight determinations to a position coincident with the supernova remnant N49 in the Large Magellanic Cloud is analyzed. The region of the sky was observed both before and after the gamma-ray event with the soft X-ray imaging instruments aboard the Einstein Observatory. Coupled with the optical plate material, the soft X-ray data is used to place severe constraints on models for the origin of the transient phenomena.
Radio astronomy and radio interferometry at microwave frequencies are discussed. Other topics concerning the Deep Space Network include program planning, planetary and interplanetary mission support, tracking and ground based navigation, communications, and station control and system technology.
The heliosphere is pervaded by interplanetary energetic particles, traditionally also called cosmic rays, from solar, internal heliospheric, and galactic sources. The particles species of interest to heliophysics extend from plasma energies to the GeV energies of galactic cosmic rays still measurably affected by heliospheric modulation and the still higher energies contributing to atmospheric ionization. The NASA and international Heliospheric Network of operational and legacy spacecraft measures interplanetary fluxes of these particles. Spatial coverage extends from the inner heliosphere and geospace to the heliosheath boundary region now being traversed by Voyager 1 and soon by Voyager 2. Science objectives include investigation of solar flare and coronal mass ejection events, acceleration and transport of interplanetary particles within the inner heliosphere, cosmic ray interactions with planetary surfaces and atmospheres, sources of suprathermal and anomalous cosmic ray ions in the outer heliosphere, and solar cycle modulation of galactic cosmic rays. The Virtual Energetic Particle Observatory (VEPO) will improve access and usability of selected spacecraft and sub-orbital NASA heliospheric energetic particle data sets as a newly approved effort within the evolving heliophysics virtual observatory environment. In this presentation, we will describe current VEPO science requirements, our initial priorities and an overview of our strategy to implement VEPO rapidly and at minimal cost by working within the high-level framework of the Virtual Heliospheric Observatory (VHO). VEPO will also leverage existing data services of NASA's Space Physics Data Facility and other existing capabilities of the U.S. and international heliospheric research communities.