Engineering Papers⌕ Search

SEARCH · Engineering Papers

Results for “Network data”

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.

At least 1,297 records · Page 72

Determination of Position of Jupiter From Very-Long Baseline Interferometry Observations of Ulysses

Very-long baseline interferometry (VLBI) observations of the Ulysses spacecraft near its encounter with Jupiter on 1992 February 8 were made to determine the angular position of Jupiter with respect to well known extragalactic radio sources. Spacecraft range and Doppler data were used to determine the position of the spacecraft with respect to Jupiter. Thirty-one VLBI observations of the spacecraft were made within 30 days of Ulysses closest approach to Jupiter, using the California-Spain and California-Australia baselines of NASA's Deep Space Network. When combined, these data determine the position of Jupiter at the time of encounter with an accuracy of 0.003 min in right ascension and 0.005 sec in declination. In addition, the Earth-Jupiter distance was determined with 20 m accuracy.

Folkner, W. M.↗

Comparison of Satellite Rainfall Estimates and Rain Gauge Measurements in Italy, and Impact on Landslide Modeling

Landslides can be triggered by intense or prolonged rainfall. Rain gauge measurements are commonly used to predict landslides even if satellite rainfall estimates are available. Recent research focuses on the comparison of satellite estimates and gauge measurements. The rain gauge data from the Italian network (collected in the system database Verifica Rischio Frana" (VRF)) are compared with the National Aeronautics and Space Administration (NASA) Tropical Rainfall Measuring Mission (TRMM) products. For the purpose, we couple point gauge and satellite rainfall estimates at individual grid cells, evaluating the correlation between gauge and satellite data in different morpho-climatological conditions. We then analyze the statistical distributions of both rainfall data types and the rainfall events derived from them. Results show that satellite data underestimates ground data, with the largest differences in mountainous areas. Power-law models, are more appropriate to correlate gauge and satellite data. The gauge and satellite-based products exhibit different statistical distributions and the rainfall events derived from them differ. In conclusion, satellite rainfall cannot be directly compared with ground data, requiring local investigation to account for specific morpho-climatological settings. Results suggest that satellite data can be used for forecasting landslides, only performing a local scaling between satellite and ground data.

landslide; satellite rainfall; TRMM; rain gauges; ↗

Method for neural network control of motion using real-time environmental feedback

A method of motion control for robotics and other automatically controlled machinery using a neural network controller with real-time environmental feedback. The method is illustrated with a two-finger robotic hand having proximity sensors and force sensors that provide environmental feedback signals. The neural network controller is taught to control the robotic hand through training sets using back- propagation methods. The training sets are created by recording the control signals and the feedback signal as the robotic hand or a simulation of the robotic hand is moved through a representative grasping motion. The data recorded is divided into discrete increments of time and the feedback data is shifted out of phase with the control signal data so that the feedback signal data lag one time increment behind the control signal data. The modified data is presented to the neural network controller as a training set. The time lag introduced into the data allows the neural network controller to account for the temporal component of the robotic motion. Thus trained, the neural network controlled robotic hand is able to grasp a wide variety of different objects by generalizing from the training sets.

Buckley, Theresa M.↗

Inter-Comparison of CHARM Data and WSR-88D Storm Integrated Rainfall

A localized precipitation network has been established over a 4000 sq km region of northern Alabama in support of local weather and climate research at the Global Hydrology and Climate Center (GHCC) in Huntsville. This Cooperative Huntsville-Area Rainfall Measurement (CHARM) network is comprised of over 80 volunteers who manually take daily rainfall measurements from 85 sites. The network also incorporates 20 automated gauges that report data at 1-5 minute intervals on a 24 h a day basis. The average spacing of the gauges in the network is about 6 kin, however coverage in some regions benefit from gauges every 1-2 km. The 24 h rainfall totals from the CHARM network have been used to validate Stage III rainfall estimates of daily and storm totals derived from the WSR-88D radars that cover northern Alabama. The Stage III rainfall product is produced by the Lower Mississippi River Forecast Center (LMRFC) in support of their daily forecast operations. The intercomparisons between the local rain gauge and the radar estimates have been useful to understand the accuracy and utility of the Stage III data. Recently, the Stage III and CHARM rainfall measurements have been combined to produce an hourly rainfall dataset at each CHARM observation site. The procedure matches each CHARM site with a time sequence of Stage III radar estimates of precipitation. Hourly stage III rainfall estimates were used to partition the rain gauge values to the time interval over which they occurred. The new hourly rain gauge dataset is validated at selected points where 1-5 minute rainfall measurements have been made. This procedure greatly enhances the utility of the CHARM data for local weather and hydrologic modeling studies. The conference paper will present highlights of the Stage III intercomparison and some examples of the combined radar / rain gauge product demonstrating its accuracy and utility in deriving an hourly rainfall product from the 24 h CHARM totals.

Jedlovec, Gary J.↗

Dual Purpose Simulation: New Data Link Test and Comparison With VDL-2

While the results of this paper are similar to those of previous research, in this paper technical difficulties present there are eliminated, producing better results, enabling one to more readily see the benefits of Prioritized CSMA (PCSMA). A new analysis section also helps to generalize this research so that it is not limited to exploration of the new concept of PCSMA. Commercially available network simulation software, OPNET version 7.0, simulations are presented involving an important application of the Aeronautical Telecommunications Network (ATN), Controller Pilot Data Link Communications (CPDLC) over the Very High Frequency Data Link Mode 2 (VDL-2). Communication is modeled for essentially all incoming and outgoing nonstop air traffic for just three United States cities: Cleveland, Cincinnati, and Detroit. The simulation involves 111 Air Traffic Control (ATC) ground stations, 32 airports distributed throughout the U.S., which are either sources or destinations for the air traffic landing or departing from the three cities, and also 1,235 equally equipped aircraft taking off, flying realistic free-flight trajectories, and landing in a 24-hr period. Collision-less PCSMA is successfully tested and compared with the traditional CSMA typically associated with VDL- 2. The performance measures include latency, throughput, and packet loss. As expected, PCSMA is much quicker and more efficient than traditional CSMA. These simulation results show the potency of PCSMA for implementing low latency, high throughput and efficient connectivity. Moreover, since PCSMA outperforms traditional CSMA, by simulating with it, we can determine the limits of performance beyond which traditional CSMA may not pass. We are testing a new and better data link that could replace CSMA with relative ease. Work is underway to drastically expand the number of flights to make the simulation more representative of the National Aerospace System.

Robinson, Daryl C.↗

Estimating the urban bias of surface shelter temperatures using upper-air and satellite data. Part 2: Estimation of the urban bias

A methodology is presented for estimating the urban bias of surface shelter temperatures due to the effect of the urban heat island. Multiple regression techniques were used to predict surface shelter temperatures based on the time period 1986-89 using upper-air data from the European Centre for Medium-Range Weather Forecasts (ECMWF) to represent the background climate, site-specific data to represent the local landscape, and satellite-derived data -- the normalized difference vegetation index (NDVI) and the Defense Meteorological Satellite Program (DMSP) nighttime brightness data -- to represent the urban and rural landscape. Local NDVI and DMSP values were calculated for each station using the mean NDVI and DMSP values from a 3 km x 3 km area centered over the given station. Regional NDVI and DMSP values were calculated to represent a typical rural value for each station using the mean NDVI and DMSP values from a 1 deg x 1 deg latitude-longitude area in which the given station was located. Models for the United States were then developed for monthly maximum, mean, and minimum temperatures using data from over 1000 stations in the U.S. Cooperative (COOP) Network and for monthly mean temperatures with data from over 1150 stations in the Global Historical Climate Network (GHCN). Local biases, or the differences between the model predictions using the observed NDVI and DMSP values, and the predictions using the background regional values were calculated and compared with the results of other research. The local or urban bias of U.S. temperatures, as derived from all U.S. stations (urban and rural) used in the models, averaged near 0.40 C for monthly minimum temperatures, near 0.25 C for monthly mean temperatures, and near 0.10 C for monthly maximum temperatures. The biases of monthly minimum temperatures for individual stations ranged from near -1.1 C for rural stations to 2.4 C for stations from the largest urban areas. The results of this study indicate minimal problems for global application once global NDVI and DMSP data become available.

Epperson, David L.↗

An executable specification for the message processor in a simple combining network

While the primary function of the network in a parallel computer is to communicate data between processors, it is often useful if the network can also perform rudimentary calculations. That is, some simple processing ability in the network itself, particularly for performing parallel prefix computations, can reduce both the volume of data being communicated and the computational load on the processors proper. Unfortunately, typical implementations of such networks require a large fraction of the hardware budget, and so combining networks are viewed as being impractical. The FFP Machine has such a combining network, and various characteristics of the machine allow a good deal of simplification in the network design. Despite being simple in construction however, the network relies on many subtle details to work correctly. This paper describes an executable model of the network which will serve several purposes. It provides a complete and detailed description of the network which can substantiate its ability to support necessary functions. It provides an environment in which algorithms to be run on the network can be designed and debugged more easily than they would on physical hardware. Finally, it provides the foundation for exploring the design of the message receiving facility which connects the network to the individual processors.

Middleton, David↗

The Use of HDTV Format and the Electronic Theater in Presenting Earth Science

In order to maximize the public's awareness of earth science observations, earth science data must be available in multiple media formats. This talk will focus on the use High Definition TV format in presenting earth science data, The Television (HDTV) networks are mandated to completely switch over from the current TV standard (NTSC) to HDTV in the next seven years. Museums are also beginning to use HDTV format in their displays. The Visualization Analysis Laboratory at Goddard Space Flight Center has been experimenting with the use of HDTV to present earth science data. The experimental package we have developed is called the Electronic Theater (e-theater). The e-theater is a mobile presentation system used for displaying and teaching groups about earth science and the delicate interdependence between the various earth systems. The e-theater takes advantage of a double-wide screen to show the audiences high resolution data displays. The unique architecture used in this exhibit allows several data sets to be displayed at one time, demonstrating the connections between different earth systems. The data animations are manipulated in real-time during the presentation and can be paused, moved forward, backward, looped, or zoomed into, to maximize the flexibility of the presentation. Because HDTV format is used within the e-theater, the materials generated for the e-theater are made available to the news media and museums.

Summey, Barbara↗

Processes and Methods used for NASA Communications Services Project Conceptualization and Formulation

The U.S. National Aeronautics and Space Administration (NASA) is partnering with the commercial SATCOM industry to demonstrate the industry’s capabilities to provide services to NASA’s near-Earth missions. Leveraging commercial capabilities will become increasingly necessary for NASA, as its incumbent Government-owned-and-operated near-Earth satellite network, the Tracking and Data Relay Satellite System (TDRSS), will approach retirement towards the end of the current decade. NASA is actively taking the first steps to making the vision of using commercial SATCOM a reality. For more than two years, NASA’s Communication Services Project (CSP) has been evaluating the feasibility of employing commercial satellite communication (SATCOM) networks for near-Earth operations. This past April, CSP awarded US$278.5 million in Funded Space Act Agreements to select commercial SATCOM providers, so they may begin developing and demonstrating their specific near-Earth space communication services that may support future agency missions. Each company will match or exceed agency contributions during the five-year development and demonstration period, totaling more than $1.5 billion of cost-share investment. The companies will complete technology development and in-space demonstrations by 2025, after which NASA intends to seek multiple long-term contracts to acquire these kinds of services. The six companies (Inmarsat Government Inc., Kuiper Government Solutions (KGS), SES Government Solutions, Space Exploration Technologies (SpaceX), Telesat U.S. Services and Viasat Inc.) will shortly begin developing and demonstrating their capabilities to provide services, ranging from launch to standard on-orbit operations. The demonstrations will be across multiple spectrum regimes from L-Band to optical, and will utilize Geostationary Orbit (GEO), Medium-Earth Orbit (MEO) and Low-Earth Orbit (LEO) constellations. This paper discusses methodologies and processes used over the past two years to reach the point of entering into these partnerships. It also includes CSP’s goals and objectives going forward, following the award of six Funded Space Act Agreements to commercial SATCOM providers to develop and demonstrate these capabilities.

Communications Services Project↗

Processes and Methods used for Nasa Communications Services Project Conceptualization and Formulation

The U.S. National Aeronautics and Space Administration (NASA) is partnering with the commercial SATCOM industry to demonstrate the industry’s capabilities to provide services to NASA’s near-Earth missions. Leveraging commercial capabilities will become increasingly necessary for NASA, as its incumbent Government-owned-and-operated near-Earth satellite network, the Tracking and Data Relay Satellite System (TDRSS), will approach retirement towards the end of the current decade. NASA is actively taking the first steps to making the vision of using commercial SATCOM a reality. For more than two years, NASA’s Communication Services Project (CSP) has been evaluating the feasibility of employing commercial satellite communication (SATCOM) networks for near-Earth operations. This past April, CSP awarded US$278.5 million in Funded Space Act Agreements to select commercial SATCOM providers, so they may begin developing and demonstrating their specific near-Earth space communication services that may support future agency missions. Each company will match or exceed agency contributions during the five-year development and demonstration period, totaling more than $1.5 billion of cost-share investment. The companies will complete technology development and in-space demonstrations by 2025, after which NASA intends to seek multiple long-term contracts to acquire these kinds of services. The six companies (Inmarsat Government Inc., Kuiper Government Solutions (KGS), SES Government Solutions, Space Exploration Technologies (SpaceX), Telesat U.S. Services and Viasat Inc.) will shortly begin developing and demonstrating their capabilities to provide services, ranging from launch to standard on-orbit operations. The demonstrations will be across multiple spectrum regimes from L-Band to optical, and will utilize Geostationary Orbit (GEO), Medium-Earth Orbit (MEO) and Low-Earth Orbit (LEO) constellations. This paper discusses methodologies and processes used over the past two years to reach the point of entering into these partnerships. It also includes CSP’s goals and objectives going forward, following the award of six Funded Space Act Agreements to commercial SATCOM providers to develop and demonstrate these capabilities.

Communications Services Project↗

Flood Mapping Using UAVSAR and Convolutional Neural Networks

We have mapped flooded areas in data collected by the NASA/JPL Uninhabited Aerial Vehicle Synthetic Aperture Radar (UAVSAR) using two convolutional neural network (CNN) image classifier architectures: U-Net and SegNet. Our study area was a region around Houston, TX, USA affected by widespread flooding in 2017 due to Hurricane Harvey. To train and test the classifiers, we manually labelled over 10000 image segments in two flight lines. Both U-Net and SegNet yielded higher accuracy than a previous non-machine learning classifier we used as a baseline. U-Net had slightly higher accuracy than SegNet. The classifiers performed better in areas with more homogeneous land cover. To independently validate the classifier accuracy we used NOAA aerial imagery, with overall accuracy around 80%. Future work includes assessing the classifier robustness in other study areas, assessing the classifier dependence on UAVSAR incidence angle, particularly for open water and bare ground, and collecting more training data, particularly in urban areas. This study demonstrates the potential of CNN image classifiers for mapping flooded areas in airborne polarimetric SAR imagery, and for land cover classification of polarimetric SAR imagery more generally.

Denbina, Michael W↗

Data Mining Methods Applied to Flight Operations Quality Assurance Data: A Comparison to Standard Statistical Methods

In a previous study, multiple regression techniques were applied to Flight Operations Quality Assurance-derived data to develop parsimonious model(s) for fuel consumption on the Boeing 757 airplane. The present study examined several data mining algorithms, including neural networks, on the fuel consumption problem and compared them to the multiple regression results obtained earlier. Using regression methods, parsimonious models were obtained that explained approximately 85% of the variation in fuel flow. In general data mining methods were more effective in predicting fuel consumption. Classification and Regression Tree methods reported correlation coefficients of .91 to .92, and General Linear Models and Multilayer Perceptron neural networks reported correlation coefficients of about .99. These data mining models show great promise for use in further examining large FOQA databases for operational and safety improvements.

Stolzer, Alan J.↗

An overview of the Hubble Space Telescope command and data management system

The Hubble Space Telescope (HST) will be an orbiting observatory which will extend the capability of large earth-based observatories to view the universe by approximately 350 times in volume and approximately seven times in distance. The HST program, which includes the Orbiting Observatory, the Space Telescope Science Institute, and the Space Telescope Operations Control Center, is supported by the Space Shuttle, the Tracking and Data Relay Satellite System, and the NASA Communications Network. This paper describes the Command and Data Management System for the HST spacecraft, including flexibility, operation modes, and end-to-end data flow paths used to meet stringent synchronization and data quality requirements. The results of system tests indicate that the use of concatenated coding techiques consisting of both block and convolutional codes as a protection against random and burst errors has been successful. Diagrams of the HST data system are included.

Clubb, Jerry↗

ISS Solar Array Management

The International Space Station (ISS) Solar Array Management (SAM) software toolset provides the capabilities necessary to operate a spacecraft with complex solar array constraints. It monitors spacecraft telemetry and provides interpretations of solar array constraint data in an intuitive manner. The toolset provides extensive situational awareness to ensure mission success by analyzing power generation needs, array motion constraints, and structural loading situations. The software suite consists of several components including samCS (constraint set selector), samShadyTimers (array shadowing timers), samWin (visualization GUI), samLock (array motion constraint computation), and samJet (attitude control system configuration selector). It provides high availability and uptime for extended and continuous mission support. It is able to support two-degrees-of-freedom (DOF) array positioning and supports up to ten simultaneous constraints with intuitive 1D and 2D decision support visualizations of constraint data. Display synchronization is enabled across a networked control center and multiple methods for constraint data interpolation are supported. Use of this software toolset increases flight safety, reduces mission support effort, optimizes solar array operation for achieving mission goals, and has run for weeks at a time without issues. The SAM toolset is currently used in ISS real-time mission operations.

Williams, James P.↗

Working Toward A National Coordinated Soil Moisture Monitoring Network: Vision, Progress, and Future Directions

Soil moisture is a critical land surface variable, impacting the water, energy, and carbon cycles. While in situ soil moisture monitoring networks are still developing, there is no cohesive strategy or framework to coordinate, integrate, or disseminate these diverse data sources in a synergistic way that can improve our ability to understand climate variability at the national, state, and local levels. Thus, a national strategy is needed to guide network deployment, sustainable network operation, data integration and dissemination, and user-focused product development. The National Coordinated Soil Moisture Monitoring Network (NCSMMN) is a federally led, multi-institution effort that aims to address these needs by capitalizing on existing wide-ranging soil moisture monitoring activities, increasing the utility of observational data, and supporting their strategic application to the full range of decision-making needs. The goals of the NCSMMN are to 1) establish a national “network of networks” that effectively demonstrates data integration and operational coordination of diverse in situ networks; 2) build a community of practice around soil moisture measurement, interpretation, and application—a “network of people” that links data providers, researchers, and the public; and 3) support research and development (R&D) on techniques to merge in situ soil moisture data with remotely sensed and modeled hydrologic data to create user-friendly soil moisture maps and associated tools. The overarching mission of the NCSMMN is to provide coordinated high-quality, nationwide soil moisture information for the public good by supporting applications like drought and flood monitoring, water resource management, agricultural and forestry planning, and fire danger ratings.

C. Bruce Baker↗