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The status of the technologies for phased-array-fed dual reflector systems is reviewed. The different aspects of these technologies, including optical performances, phased array systems, problems encountered in phased array design, beamforming networks, MMIC design and its incorporation into waveguide systems, reflector antenna structures, and reflector deployment mechanisms are addressed.
The time history, energy spectra, and precise localization of the intense January 13, 1979 gamma-ray burst, observed by five spacecraft in the interplanetary network, are presented. The time history displays a pulse-afterpulse structure suggestive of periodicity. Fine time resolution spectral analysis shows that a wide variety of models can be used to fit individual spectra, while spectra integrated over longer periods are well fitted by a thermal synchrotron law, making it difficult to identify any specific emission mechanism. The precise localization may be consistent with an archival optical transient having no quiescent counterpart down to 22d mag on recent plates.
NASA's Office of Space Science and Applications has formulated an operational concept, 'telescience', for Space Station-related missions; telescience encompasses teledesign, teleoperations, teleanalysis, and an overall integrating structure that defines and delineates the system's architectural infrastructure and networking for implementation. Attention is here given to the development status of data interchange standards, interoperable networks, automated data-ingest mechanisms and access directories, means to the accessing of heterogeneous data bases, and user-support environments.
The components necessary for the success of the commercialization of an Ada Technology Transition Network are reported in detail. The organizational plan presents the planned structure for services development and technical transition of AdaNET services to potential user communities. The Business Plan is the operational plan for the AdaNET service as a commercial venture. The Technical Plan is the plan from which the AdaNET can be designed including detailed requirements analysis. Also contained is an analysis of user fees and charges, and a proposed user fee schedule.
Variations in solar and stellar irradiances have long been of interest. An International Astronomical Union (IAU) colloquium reviewed such relevant subjects as observations, theoretical interpretations, and empirical and physical models, with a special emphasis on climatic impact of solar irradiance variability. Specific topics discussed included: (1) General Reviews on Observations of Solar and Stellar Irradiance Variability; (2) Observational Programs for Solar and Stellar Irradiance Variability; (3) Variability of Solar and Stellar Irradiance Related to the Network, Active Regions (Sunspots and Plages), and Large-Scale Magnetic Structures; (4) Empirical Models of Solar Total and Spectral Irradiance Variability; (5) Solar and Stellar Oscillations, Irradiance Variations and their Interpretations; and (6) The Response of the Earth's Atmosphere to Solar Irradiance Variations and Sun-Climate Connections.
The 3-dimensional model for a segmented reflector telescope is developed using finite element techniques. The structure is decomposed into six subsystems. System control design using neural networks is performed. Performance evaluation is demonstrated via simulation using PRO-MATLAB and SIMULINK.
Ulysses observations have shown that pressure balance structures (PBSs) are a common feature in high-latitude, fast solar wind near solar minimum. Previous studies of Ulysses/SWOOPS plasma data suggest these PBSs may be remnants of coronal polar plumes. Here we find support for this suggestion in an analysis of PBS magnetic structure. We used Ulysses magnetometer data and applied a minimum variance analysis to discontinuities. We found that PBSs preferentially contain tangential discontinuities, as opposed to rotational discontinuities and to non-PBS regions in the solar wind. This suggests that PBSs contain structures like current sheets or plasmoids that may be associated with network activity at the base of plumes.
Predictive models for tides, hydrodynamics, and bio-optical properties affecting the visibility and buoyancy of coastal waters are needed to evaluate the safety of personnel and equipment engaged in maritime operations under potentially hazardous conditions. Predicted currents can be markedly different for two-layer systems affected by terrestrial runoff than for well-mixed conditions because the layering decouples the surface and bottom Ekman layers and rectifies the current response to oscillatory upwelling-and downwelling-favorable winds. Standard ocean models (e.g. Princeton Ocean Model) require initial-and boundary data on the physical and optical properties of the multilayered water column to provide accurate simulations of heat budgets and circulation. Two observational systems are designed to measure vertically structured conditions on the West Florida Shelf (WFS): a tethered buoy network and an autonomous underwater vehicle (AUV) observational system. The AUV system is described with a focus on the observational systems that challenge or limit the communications command and control network for various types of measurement programs. These include vertical oscillatory missions on shelf transects to observe the optical and hydrographic properties of the water column, and bottom-following missions for measuring the bottom albedo. Models of light propagation, absorption, and conversion to heat as well as determination of the buoyancy terms for physical models require these measurements. High data rates associated with video bottom imagery are the most challenging for the real-time, command and control communications system, but they are met through a combination of loss-less and lossy data-compression methods, depending upon the data-rate of the radio links.
Ulysses observations have shown that pressure balance structures (PBSs) are a common feature in high-latitude, fast solar wind near solar minimum. Previous studies of Ulysses/SWOOPS plasma data suggest these PBSs may be remnants of coronal polar plumes. Here we find support for this suggestion in an analysis of PBS magnetic structure. We used Ulysses magnetometer data and applied a minimum variance analysis to magnetic discontinuities in PBSs. We found that PBSs preferentially contain tangential discontinuities, as opposed to rotational discontinuities and to non-PBS regions in the solar wind. This suggests that PBSs contain structures like current sheets or plasmoids that may be associated with network activity at the base of plumes.
The titles in this section include: 1) Analysis of Orientation Dependence of Martian Gullies; 2) A Preliminary Relationship between the Depth of Martian Gullies and the Abundance of Hydrogen on Near-Surface Mars; 3) Water Indicators in Sirenum Terra and around the Argyre Impact Basin, Mars; 4) The Distribution of Gullies and Tounge-shaped Ridges and Their Role in the Degradation of Martian Craters; 5) A Critical Evaluation of Crater Lake Systems in Memnonia Quadrangle, Mars; 6) Impact-generated Hydrothermal Activity at Gusev Crater: Implications for the Spirit Mission; 7) Characterization of the Distributary Fan in Holden NE Crater using Stereo Analysis; 8) Computational Analysis of Drainage Basins on Mars: Appraising the Drainage Density; 9) Hypsometric Analyses of Martian Basins: A Comparison to Terrestrial, Lunar, and Venusian Hypsometry; 10) Morphologic Development of Harmakhis Vallis, Mars; 11) Mangala Valles, Mars: Investigations of the source of Flood Water and Early Stages of Flooding; 12) The Formation of Aromatum Chaos and the Water Discharge Rate at Ravi Vallis; 13) Inferring Hydraulics from Geomorphology for Athabasca Valles, Mars; 14) The Origin and Evolution of Dao Vallis: Formation and Modification of Martian Channels by Structural Collapse and Glaciation; 15) Snowmelt and the Formation of Valley Networks on Martian Volcanoes; 16) Extent of Floating Ice in an Ancient Echus Chasma/Kasei Valley System, Mars.
This paper presents work on the development and implementation of a novel approach to robotic navigation. In this system, map-building and localization for obstacle avoidance are discarded in favor of moment-by-moment behavioral processing of the sonar sensor data. To accomplish this, we developed a network of behaviors that communicate through the passing of rings, data structures that are similar in form to the sonar data itself and express the decisions of each behavior. Through the use of these rings, behaviors can moderate each other, conflicting impulses can be mediated, and designers can easily connect modules to create complex emergent navigational techniques. We discuss the development of a number of these modules and their successful use as a navigation system in the Trinity omnidirectional robot.
The lessons learned from the Great Tohoku EQ (Japan, 2011) will affect our future observations and an analysis is the main focus of this presentation. Multi-sensors observations and multidisciplinary research is presented in our study of the phenomena preceding major earthquakes Our approach is based on a systematic analysis of several physical and environmental parameters, which been reported by others in connections with earthquake processes: thermal infrared radiation; temperature; concentration of electrons in the ionosphere; radon/ion activities; and atmospheric temperature/humidity [Ouzounov et al, 2011]. We used the Lithosphere-Atmosphere-Ionosphere Coupling (LAIC) model, one of several possible paradigms [Pulinets and Ouzounov, 2011] to interpret our observations. We retrospectively analyzed the temporal and spatial variations of three different physical parameters characterizing the state of the atmosphere, ionosphere the ground surface several days before the March 11, 2011 M9 Tohoku earthquake Namely: (i) Outgoing Long wave Radiation (OLR) measured at the top of the atmosphere; (ii) Anomalous variations of ionospheric parameters revealed by multi-sensors observations; and (iii) The change in the foreshock sequence (rate, space and time); Our results show that on March 8th, 2011 a rapid increase of emitted infrared radiation was observed and an anomaly developed near the epicenter with largest value occurring on March 11 at 07.30 LT. The GPS/TEC data indicate an increase and variation in electron density reaching a maximum value on March 8. Starting from this day in the lower ionosphere there was also observed an abnormal TEC variation over the epicenter. From March 3 to 11 a large increase in electron concentration was recorded at all four Japanese ground-based ionosondes, which returned to normal after the main earthquake. We use the Japanese GPS network stations and method of Radio Tomography to study the spatiotemporal structure of ionospheric perturbations, and to distinguish ionospheric responses to processes of EQ preparation against the effects of other factors. The 2-D snapshots of the electron density over Japan showed abnormal increase over the maximum stress during the night, a few hours before the main shock. Our results from recording atmospheric and ionospheric conditions during the earthquake indicate the presence of anomalies in the atmosphere and ionospheres occurring consistently over regions of maximum stress near the epicenter. Due to their long duration (hours and days) and spatial appearance (only over the Sendai region) these results do not appear to be caused by meteorological or magnetic activity. They reveal the existence of atmospheric and ionospheric phenomena occurring prior to the earthquake, which indicates new evidence of a distinct coupling between the lithosphere and atmosphere/ionosphere. Similar results have been reported before the catastrophic events in Chile (M8.8, 2010), Italy (M6.3, 2009) and Sumatra (M9.3, 2004).
Astronauts experience sensorimotor disturbances during the initial exposure to microgravity and during the readapation phase following a return to a gravitational environment. These alterations may lead to disruption in the ability to perform mission critical functional tasks during and after these gravitational transitions. Astronauts show significant inter-subject variation in adaptive capability following gravitational transitions. The ability to predict the manner and degree to which each individual astronaut will be affected would improve the effectiveness of a countermeasure comprised of a training program designed to enhance sensorimotor adaptability. Due to this inherent individual variability we need to develop predictive measures of sensorimotor adaptability that will allow us to predict, before actual space flight, which crewmember will experience challenges in adaptive capacity. Thus, obtaining this information will allow us to design and implement better sensorimotor adaptability training countermeasures that will be customized for each crewmember's unique adaptive capabilities. Therefore the goals of this project are to: 1) develop a set of predictive measures capable of identifying individual differences in sensorimotor adaptability, and 2) use this information to design sensorimotor adaptability training countermeasures that are customized for each crewmember's individual sensorimotor adaptive characteristics. To achieve these goals we are currently pursuing the following specific aims: Aim 1: Determine whether behavioral metrics of individual sensory bias predict sensorimotor adaptability. For this aim, subjects perform tests that delineate individual sensory biases in tests of visual, vestibular, and proprioceptive function. Aim 2: Determine if individual capability for strategic and plastic-adaptive responses predicts sensorimotor adaptability. For this aim, each subject's strategic and plastic-adaptive motor learning abilities are assessed using a test of locomotor function designed specifically to delineate both mechanisms. Aim 3: Develop predictors of sensorimotor adaptability using brain structural and functional metrics. We will measure individual differences in regional brain volumes (structural MRI), white matter integrity (diffusion tensor imaging, or DTI), functional network integrity (resting state functional connectivity MRI), and sensorimotor adaptation task-related functional brain activation (functional MRI). We decided to complete the data collection for Specific Aims 1, 2 and 3 simultaneously on the same subjects to increase data capture. By having the same subjects perform all three specific aims we can enhance our ability to detect how a wider range of factors can predict adaptability in a specific individual. This provides a much richer database and potentially a better understanding of the predictive power of the selected factors. In this presentation I will discuss preliminary data obtained to date.
Earlier studies show that future human explorations missions are composed of multi-vehicle assemblies with interconnected electric power systems. Some vehicles are often intended to serve as flexible multi-purpose or multi-mission platforms. This drives the need for power architectures that can be reconfigured to support this level of flexibility. Power system developmental costs can be reduced, program wide, by utilizing a common set of modular building blocks. Further, there are mission operational and logistics cost benefits of using a common set of modular spares. These benefits are the goals of the Advanced Exploration Systems (AES) Modular Power System (AMPS) project. A common set of modular blocks requires a substantial level of standardization in terms of the Electrical, Data System, and Mechanical interfaces. The AMPS project is developing a set of proposed interface standards that will provide useful guidance for modular hardware developers but not needlessly constrain technology options, or limit future growth in capability. In 2015 the AMPS project focused on standardizing the interfaces between the elements of spacecraft power distribution and energy storage. The development of the modular power standard starts with establishing mission assumptions and ground rules to define design application space. The standards are defined in terms of AMPS objectives including Commonality, Reliability-Availability, Flexibility-Configurability and Supportability-Reusability. The proposed standards are aimed at assembly and sub-assembly level building blocks. AMPS plans to adopt existing standards for spacecraft command and data, software, network interfaces, and electrical power interfaces where applicable. Other standards including structural encapsulation, heat transfer, and fluid transfer, are governed by launch and spacecraft environments and bound by practical limitations of weight and volume. Developing these mechanical interface standards is more difficult but an essential part of defining physical building blocks of modular power. This presentation describes the AMPS projects progress towards standardized modular power interfaces.
The land surface is a critical part of the earth system as processes related to water, carbon, energy and nitrogen cycling have important implications for climate forcing, air quality, water availability and seasonal atmospheric forecasting. Despite advances in land surface modeling, land surface model performance is often limited because of errors related to initial and boundary conditions, model structure, and parameters. Data assimilation (DA) techniques combined with an expanding network of earth system observations present an opportunity to reduce these errors and improve simulations. Here we apply an Ensemble Kalman Filter DA system as part of the Data Assimilation Research Testbed to a variety of land surface simulations. First, we describe the use of remotely sensed biomass observations to provide improved simulations of plant phenology, carbon and water cycling for regions highly sensitive to climate change (Western US, China, and Arctic). We discuss approaches to account for systemic biases between models and observations, including the use of spatially-varying adaptive ensemble inflation as an alternative approach to re-scaling soil moisture observations. Finally, we discuss a strategy to incorporate complementary observations (snow water equivalent, solar-induced fluorescence) to better constrain the representation of carbon and water cycling across complex terrain.
The land surface is a critical part of the earth system as processes related to water, carbon, energy and nitrogen cycling have important implications for climate forcing, air quality, water availability and seasonal atmospheric forecasting. Despite advances in land surface modeling, land surface model performance is often limited because of errors related to initial and boundary conditions, model structure, and parameters. Data assimilation (DA) techniques combined with an expanding network of earth system observations present an opportunity to reduce these errors and improve simulations. Here, we emphasize the implementation of tools and approaches to overcome challenges related to land DA to constrain carbon and water cycling. In particular, we discuss the implementation of adaptive inflation to modify ensemble spread in response to time-varying networks of gridded observations. We also discuss methods to generate ensemble spread through boundary condition (meteorology) forcing that can be applied to site-level applications. Next, we describe the application of vertical localization upon surface soil moisture observations, and forward operators specifically designed for the assimilation of snow and solar-induced fluorescence observations. Finally, we discuss the potential benefit of a quantile conserving filter used to update bounded quantities (state or parameter values).
Machine learning (ML) models are increasingly being used in many engineering fields due to the advancements in ML algorithms and availability of high-speed computing power. One of the most popular ML class of models is artificial neural networks (ANN). ML is increasingly being used in the design and analysis of composite materials and structures, specifically in the constitutive modeling of composite materials with the focus on greatly accelerating multiscale analyses of composite materials and structures through development of surrogate models. Towards that end, Python-based neural nets have been developed to predict initial stiffness and fatigue life of an eight-ply symmetric polymer matrix composite laminate. Two types of neural networks, a Multilayer Perceptron (MLP) and a Recurrent Neural Network (RNN), have been established. Results show that both neural net type algorithms can provide an excellent estimate of initial laminate stiffness as well as fatigue life of eight-ply symmetric polymer matrix composite laminates (PMCs). RNNs are better able to capture the shape of the fatigue curve of a laminate. The resulting tool and GUI can be very useful for system level studies to obtain an estimate of desired properties and life of PMC composite laminates. Further, the associated surrogate models can also be used in composite multiscale analyses to replace the actual physics-based calculations at lower scales and thereby significantly increase the computational efficiency of such analyses and thus make micromechanics-based multiscale analyses a viable industrial tool for large scale structural problems.
Machine learning (ML) models are increasingly being used in many engineering fields due to the advancements in ML algorithms and availability of high-speed computing power. One of the most popular ML class of models is artificial neural networks (ANN). ML is increasingly being used in the design and analysis of composite materials and structures, specifically in the constitutive modeling of composite materials with the focus on greatly accelerating multiscale analyses of composite materials and structures through development of surrogate models. Towards that end, Python-based neural nets have been developed to predict initial stiffness and fatigue life of an eight-ply symmetric polymer matrix composite laminate. Two types of neural networks, a Multilayer Perceptron (MLP) and a Recurrent Neural Network (RNN), have been established. Results show that both neural net type algorithms can provide an excellent estimate of initial laminate stiffness as well as fatigue life of eight-ply symmetric polymer matrix composite laminates (PMCs). RNNs are better able to capture the shape of the fatigue curve of a laminate. The resulting tool and GUI can be very useful for system level studies to obtain an estimate of desired properties and life of PMC composite laminates. Further, the associated surrogate models can also be used in composite multiscale analyses to replace the actual physics-based calculations at lower scales and thereby significantly increase the computational efficiency of such analyses and thus make micromechanics-based multiscale analyses a viable industrial tool for large scale structural problems.