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At least 325 records · Page 18

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NASA NTRS1990

Ionospheric refraction effects on orbit determination using the orbit determination error analysis system

The influence of ionospheric refraction on orbit determination was studied through the use of the Orbit Determination Error Analysis System (ODEAS). The results of a study of the orbital state estimate errors due to the ionospheric refraction corrections, particularly for measurements involving spacecraft-to-spacecraft tracking links, are presented. In current operational practice at the Goddard Space Flight Center (GSFC) Flight Dynamics Facility (FDF), the ionospheric refraction effects on the tracking measurements are modeled in the Goddard Trajectory Determination System (GTDS) using the Bent ionospheric model. While GTDS has the capability of incorporating the ionospheric refraction effects for measurements involving ground-to-spacecraft tracking links, such as those generated by the Ground Spaceflight Tracking and Data Network (GSTDN), it does not have the capability to incorporate the refraction effects for spacecraft-to-spacecraft tracking links for measurements generated by the Tracking and Data Relay Satellite System (TDRSS). The lack of this particular capability in GTDS raised some concern about the achievable accuracy of the estimated orbit for certain classes of spacecraft missions that require high-precision orbits. Using an enhanced research version of GTDS, some efforts have already been made to assess the importance of the spacecraft-to-spacecraft ionospheric refraction corrections in an orbit determination process. While these studies were performed using simulated data or real tracking data in definitive orbit determination modes, the study results presented here were obtained by means of covariance analysis simulating the weighted least-squares method used in orbit determination.

Yee, C. P.↗

NASA NTRS2011

Passage of Bolides Through the Atmosphere

Different fragmentation models are applied to a number of events, including the entry of TC3 2008 asteroid in order to reproduce existing observational data. Keywords meteoroid entry fragmentation modeling 1 Introduction Fragmentation is a very important phenomenon which occurs during the meteoroid entry into the atmosphere and adds more drastic effects than mere deceleration and ablation. Modeling of bolide fragmentation (100 106 kg in mass) may be divided into several approaches. Detail fitting of observational data (deceleration and/or light curves) allows the determination of some meteoroid parameters (ablation and shape-density coefficients, fragmentation points, amount of mass loss) (Ceplecha et al. 1993; Ceplecha and ReVelle 2005). Observational data with high accuracy are needed for the gross-fragmentation model (Ceplecha et al. 1993), which is used for the analysis of European and Desert bolide networks data. Hydrodynamical models, which describe the entry of the meteoroid including evolution of its material, are applied mainly for large bodies (>106 kg) (Boslough et al. 1994; Svetsov et al. 1995; Shuvalov and Artemieva 2002, and others). Numerous papers were devoted to the application of standard equations for large meteoroid entry in the attempts to reproduce dynamics and/or radiation for different bolides and to predict meteorite falls. These modeling efforts are often supplemented by different fragmentation models (Baldwin and Sheaffer, 1971; Borovi.ka et al. 1998; Artemieva and Shuvalov, 2001; Bland and Artemieva, 2006, and others). The fragmentation may occur in different ways. For example, few large fragments are formed. These pieces initially interact through their shock waves and then continue their flight independently. The progressive fragmentation model suggests that meteoroids are disrupted into fragments, which continue their flight as independent bodies and may be disrupted further. Similar models were suggested in numerous papers, beginning with Levin (1956) and initial interaction of fragments started to be taken into account after the paper by Passey and Melosh (1980). The progressive fragmentation model with lateral spreading of formed fragments is widely used (Artemieva and Shuvalov, 1996; Nemtchinov and Popova, 1997; Borovi.ka et al. 1998; Bland and Artemieva, 2006).

Popova, O.↗

NASA NTRS2003

Modeling Aircraft Wing Loads from Flight Data Using Neural Networks

Neural networks were used to model wing bending-moment loads, torsion loads, and control surface hinge-moments of the Active Aeroelastic Wing (AAW) aircraft. Accurate loads models are required for the development of control laws designed to increase roll performance through wing twist while not exceeding load limits. Inputs to the model include aircraft rates, accelerations, and control surface positions. Neural networks were chosen to model aircraft loads because they can account for uncharacterized nonlinear effects while retaining the capability to generalize. The accuracy of the neural network models was improved by first developing linear loads models to use as starting points for network training. Neural networks were then trained with flight data for rolls, loaded reversals, wind-up-turns, and individual control surface doublets for load excitation. Generalization was improved by using gain weighting and early stopping. Results are presented for neural network loads models of four wing loads and four control surface hinge moments at Mach 0.90 and an altitude of 15,000 ft. An average model prediction error reduction of 18.6 percent was calculated for the neural network models when compared to the linear models. This paper documents the input data conditioning, input parameter selection, structure, training, and validation of the neural network models.

Allen, Michael J.↗

NASA NTRS1978

STDN in the TDRSS and Shuttle Era

NASA presently maintains a worldwide system of ground tracking stations to provide communication support (tracking, telemetry and command) to all authorized user spacecraft missions. The set of ground stations supporting earth orbiting missions, and their supporting communication links (called NASCOM) to various NASA centers, is designated as the Spaceflight Tracking and Data Network (STDN). Major users of the STDN in the 1980's include LANDSAT-D, SEASAT-B and the Shuttle, all of which are capable of generating data at rates that cannot be handled by the present STDN ground stations. The expanded capabilities of the STDN in the 1980's to provide support to these missions and other users is addressed. The newest asset of the STDN, the Tracking and Data Relay Satellite System (TDRSS) is described, as are the remaining STDN ground stations (called the GSTDN). The Shuttle communications support is not only for the Shuttle itself, but also for the Spacelab, attached payloads (within the Shuttle bay), and detached payloads being either deployed or retrieved by Shuttle. The specific communications support being provided by STDN (both by TDRSS and by the GSTDN) to the Shuttle is also described.

Schwartz, J. J.↗

NASA NTRS1990

Communication protocol standards for space data systems

The main elements and requirements of advanced space data networks are identified. The communication protocol standards for use on space missions during the coming decades are described. In particular, the blending of high-performance space-unique data transmission techniques with off-the-shelf open systems interconnection (OSI) protocols is described.

Hooke, Adrian J.↗

NASA NTRS1999

A Search for Simultaneous Optical Counterparts of Gamma-Ray Bursts (LOTIS: Livermore Optical Transient Imaging System)

Under this grant the UC Berkeley PI, K. Hurley, joined the LOTIS collaboration. His task was to provide precise localization data on cosmic gamma-ray bursts, so that the LOTIS automated camera data could be searched more efficiently for evidence of optical emission from gamma-ray burst sources. This was accomplished. A program is now in place which automatically sends Interplanetary Network data on bursts via e-mail to H.S. Park, for every burst detected by the GRB experiment aboard the Ulysses spacecraft (for which K. Hurley is the P.I.). The data consist either of triangulation annuli (obtained when just two spacecraft observe the burst) or error boxes (when three widely separated spacecraft observe it). These define a locus of possible burst positions. The annuli intersect the large error circles of the CGRO-BATSE experiment, and reduce their areas by a factor of approximately 25 or more. The error boxes reduce the areas by factors of several hundred. This in turn reduces the area which must be searched for an optical counterpart. No such counterparts have been observed to date by the LOTIS experiment, but several interesting upper limits have been obtained.

Park, H.-S.↗

NASA NTRS1996

Gigabit Satellite Network for NASA's Advanced Communication Technology Satellite (ACTS)

The advanced communication technology satellite (ACTS) gigabit satellite network provides long-haul point-to-point and point-to-multipoint full-duplex SONET services over NASA's ACTS. at rates up to 622 Mbit/s (SONET OC-12), with signal quality comparable to that obtained with terrestrial fiber networks. Data multiplexing over the satellite is accomplished using time-division multiple access (TDMA) techniques coordinated with the switching and beam hopping facilities provided by ACTS. Transmissions through the satellite are protected with Reed-Solomon encoding. providing virtually error-free transmission under most weather conditions. Unique to the system are a TDMA frame structure and satellite synchronization mechanism that allow: (a) very efficient utilization of the satellite capacity: (b) over-the-satellite dosed-loop synchronization of the network in configurations with up to 64 ground stations: and (c) ground station initial acquisition without collisions with existing signalling or data traffic. The user interfaces are compatible with SONET standards, performing the function of conventional SONET multiplexers and. as such. can be: readily integrated with standard SONET fiber-based terrestrial networks. Management of the network is based upon the simple network management protocol (SNMP). and includes an over-the-satellite signalling network and backup terrestrial internet (IP-based) connectivity. A description of the ground stations is also included.

Hoder, Douglas↗

NASA NTRS2011

Multi-Decadal Change of Atmospheric Aerosols and their Effect on Surface Radiation

We present an investigation on multi-decadal changes of atmospheric aerosols and their effects on surface radiation using a global chemistry transport model, GOCART, along with the near-term to long-term data records. We focus on a 28-year time period of satellite era from 1980 to 2007 during which a suite of aerosol data from satellite observations, ground-based measurements, and intensive field experiments have become available. Particularly: (1) We compare the model calculated clear sky downward radiation at the surface with surface network data from BSRN and CMA (2) We compare the model and surface data with satellite derived downward radiation products from ISCCP and SRS (3) We analyze the long-term global and regional aerosol trends in major anthropogenic source regions (North America, Europe, Asia) that have been experiencing considerable changes of emissions during the three decades, dust and biomass burning regions that have large interannual variability, downwind regions that are directly affected by the changes in the source area, and remote regions that are considered to representing "background" conditions. The comparisons and methods from this study can be applied to multiple model analysis in the AeroCom framework.

Chin, Mian↗

NASA NTRS2016

Marshall Space Flight Center Ground Systems Development and Integration

Ground Systems Development and Integration performs a variety of tasks in support of the Mission Operations Laboratory (MOL) and other Center and Agency projects. These tasks include various systems engineering processes such as performing system requirements development, system architecture design, integration, verification and validation, software development, and sustaining engineering of mission operations systems that has evolved the Huntsville Operations Support Center (HOSC) into a leader in remote operations for current and future NASA space projects. The group is also responsible for developing and managing telemetry and command configuration and calibration databases. Personnel are responsible for maintaining and enhancing their disciplinary skills in the areas of project management, software engineering, software development, software process improvement, telecommunications, networking, and systems management. Domain expertise in the ground systems area is also maintained and includes detailed proficiency in the areas of real-time telemetry systems, command systems, voice, video, data networks, and mission planning systems.

Wade, Gina↗

NASA NTRS1987

Spacelab Data Processing Facility (SLDPF) quality assurance expert systems development

The Spacelab Data Processing Facility (SLDPF) is an integral part of the Space Shuttle data network for missions that involve attached scientific payloads. Expert system prototypes were developed to aid in the performance of the quality assurance function of the Spacelab and/or Attached Shuttle Payloads processed telemetry data. The Spacelab Input Processing System (SIPS) and the Spacelab Output Processing System (SOPS), two expert systems, were developed to determine their feasibility and potential in the quality assurance of processed telemetry data. The capabilities and performance of these systems are discussed.

Basile, Lisa R.↗

NASA NTRS2017

NASA's Big Earth Data Initiative Accomplishments

The goal of NASA's effort for BEDI is to improve the usability, discoverability, and accessibility of Earth Observation data in support of societal benefit areas. Accomplishments: In support of BEDI goals, datasets have been entered into Common Metadata Repository(CMR), made available via the Open-source Project for a Network Data Access Protocol (OPeNDAP), have a Digital Object Identifier (DOI) registered for the dataset, and to support fast visualization many layers have been added in to the Global Imagery Browse Services (GIBS).

CMR↗

NASA NTRS2019

NASA EOSDIS Data Usage Metrics- Insight and Assessment

NASA's Earth Science Data and Information System (ESDIS) Project collects Earth science data usage metrics on a daily basis through the ESDIS Metrics System (EMS). This includes metrics on distribution of data products, users, data volumes, and number of files, which are key parameters in evaluating system-level performance of any of the Distributed Active Archive Centers (DAACs) encompassed by NASA's Earth Observing System (EOS) Data and Information System (EOSDIS). EOSDIS data usage metrics illustrate the benefits of making NASA data openly available to the public and show a rapid growth in data distribution to a worldwide user community. In fact, each year since 2014 the EOSDIS has distributed over one billion data files of products from EOS satellite, airborne, and in situ observations. An assessment of the long-term trends of data usage metrics and user characterization provides insights into data usability.This study will focus on describing the EMS as a metrics collection tool and will provide a comprehensive analysis of EOSDIS data usage metrics over the last 10 years. This study will also characterize the product distribution metrics by various tools and services, such as Giovanni, the Open-source Project for a Network Data Access Protocol (OPeNDAP), and subsets, to address how these tools/services have extended the usage of data in the EOSDIS collection. Data usage patterns based on discipline and study area will further assist in understanding how EOSDIS data user needs have evolved over time. Results from this study will provide useful information for the DAACs that can help them improve the functionality of their tools and services as well as more efficiently allocate the resources necessary for enhanced access and availability of their data products. Knowledge of these metrics may also benefit user discovery of data in the EOSDIS collection, promote research collaboration, and stimulate new ideas from work and research conducted using specific datasets and data collections.

Kafle, Durga N.↗

NASA NTRS2019

VIIRS Deep Blue Aerosol Products Over Land: Extending the EOS Long‐Term Aerosol Data Records

A primary goal of the Deep Blue (DB) project is to create consistent long‐term aerosol data records, suitable for climate studies, using multiple satellite instruments. In order to continue Earth Observing System (EOS)‐era aerosol products into the Joint Polar Satellite System era, we have successfully ported the DB algorithm to process data from the Visible Infrared Imaging Radiometer Suite (VIIRS). Although the basic structure of the VIIRS algorithm is similar to that for the Moderate Resolution Imaging Spectroradiometer (MODIS), many enhancements have been made compared to the MODIS collection 6 (C6) version. Most have also been implemented in the latest MODIS Collection 6.1 (C6.1). For example, a new smoke mask was developed based on the spectral curvature of measured reflectance to distinguish biomass burning smoke from weakly absorbing urban/industrial aerosols. Consequently, a new aerosol‐type flag was added into the VIIRS DB data set. In addition, new dust models have been developed to account for the nonsphericity of mineral dust. As a result, a discontinuity in the retrieved aerosol optical depth (AOD) of Saharan dust plumes seen in MODIS C6 products near the boundary between North Africa and the Atlantic has been much reduced. We have also evaluated the VIIRS and MODIS Terra/Aqua C6.1 AOD against Aerosol Robotic Network data. VIIRS and MODIS retrievals show similar performance; around 80% of matchups agree with Aerosol Robotic Network within the expected error of ±(0.05 + 20)%, indicating that DB can provide consistent AOD through the historical EOS and present Joint Polar Satellite System eras.

aerosols↗

NASA NTRS1978

On the time-varying properties of the lunar seismic meteoroid population

Strong short-term fluctuations of meteroid impact rates are evident in a list of 1557 events derived from Apollo lunar seismic data. Times of fall and seismic signal amplitudes are considered in relation to the possible orbits and identification of the impacting objects. The entire lunar surface is the effective collector and the Apollo network data, gathered between 1970 and 1977, reflect the recognized abundance of large meteorite falls from early April through July. There is also some indication that briefly increased counts represent fragments of about 100 g or greater belonging to several meteor streams: Quadrantids, Aquarids, Perseids, Orionids, Leonids, Geminids, and possibly others as well.

Dorman, J.↗

DOE OSTI2022

Data reduction through optimized scalar quantization for more compact neural networks

Raw data generation for several existing and planned large physics experiments now exceeds TB/s rates, generating untenable data sets in very little time. Those data often demonstrate high dimensionality while containing limited information. Meanwhile, Machine Learning algorithms are now becoming an essential part of data processing and data analysis. Those algorithms can be used offline for post processing and post data analysis, or they can be used online for real time processing providing ultra low latency experiment monitoring. Both use cases would benefit from data throughput reduction while preserving relevant information: one by reducing the offline storage requirements by several orders of magnitude and the other by allowing ultra fast online inferencing with low complexity Machine Learning models. Moreover, reducing the data source throughput also reduces material cost, power and data management requirements. In this work we demonstrate optimized nonuniform scalar quantization for data source reduction. This data reduction allows lower dimensional representations while preserving the relevant information of the data, thus enabling high accuracy Tiny Machine Learning classifier models for online fast inferences. We demonstrate this approach with an initial proof of concept targeting the CookieBox, an array of electron spectrometers used for angular streaking, that was developed for LCLS-II as an online beam diagnostic tool. We used the Lloyd-Max algorithm with the CookieBox dataset to design an optimized nonuniform scalar quantizer. Optimized quantization lets us reduce input data volume by 69% with no significant impact on inference accuracy. When we tolerate a 2% loss on inference accuracy, we achieved 81% of input data reduction. Finally, the change from a 7-bit to a 3-bit input data quantization reduces our neural network size by 38%.

97 MATHEMATICS AND COMPUTING↗

NASA NTRS1994

Automated mainframe data collection in a network environment

The progress and direction of the computer industry have resulted in widespread use of dissimilar and incompatible mainframe data systems. Data collection from these multiple systems is a labor intensive task. In the past, data collection had been restricted to the efforts of personnel specially trained on each system. Information is one of the most important resources an organizations has. Any improvement in an organization's ability to access and manage that information provides a competitive advantage. This problem of data collection is compounded at NASA sites by multi-center and contractor operations. The Centralized Automated Data Retrieval System (CADRS) is designed to provide a common interface that would permit data access, query, and retrieval from multiple contractor and NASA systems. The methods developed for CADRS have a strong commercial potential in that they would be applicable for any industry that needs inter-department, inter-company, or inter-agency data communications. The widespread use of multi-system data networks, that combine older legacy systems with newer decentralized networks, has made data retrieval a critical problem for information dependent industries. Implementing the technology discussed in this paper would reduce operational expense and improve data collection on these composite data systems.

Gross, David L.↗

DOE OSTI2023

Radar Wind Profiler at McKinleyville, CA

These data are collected as part of an observational database developed to support the floating offshore wind energy research under the ORACLE project funded by DOE Wind Energy Technologies Office (WETO). The radar wind profiler network data are collected by NOAA (https://psl.noaa.gov/data/obs/datadisplay), and only data within the state of California are part of the database.

17 WIND ENERGY↗

DOE OSTI2023

Radar Wind Profiler at Bodega Bay

17 WIND ENERGY↗