FEDGE - A general-purpose computer program for Finite Element Data Generation. Volume 1 - User's manual
Users manual for /FEDGE/ Finite Element Data Generation computer program - Vol. 1
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Users manual for /FEDGE/ Finite Element Data Generation computer program - Vol. 1
Meteorological data catalog for ATS 3 1 Aug. 1969 - 25 May 1970 and summary of ATS 1 operations
A format developed for Space Transportation System payload data collection and a process for collecting the data are described along with payload volumes and a data deck to be used as input for the Marshall Interactive Planning System. Summary matrices of the data generated are included.
NASA Goddard has been investing in technology demonstrations of a beacon service, now called Next Generation Broadcast Services (NGBS). NGBS is a global, space-based, communications and navigation service for users of Global Navigation Satellite Systems (GNSS) and the Tracking and Data Relay Satellite System (TDRSS). NGBS will provide an S-band beacon messaging source and radio navigation available to users at orbital altitudes 1400 km and below, increasing the autonomy and resiliency of onboard communication and navigation. NGBS will deliver both one-way radiometric (Doppler and pseudorange) and fast forward data transport services to users. Portions of the overall forward data volume will be allocated for fixed message types while the remaining data volume will be left for user forward command data. The NGBS signal will reside within the 2106.43 MHz spectrum currently allocated for the Space Networks multiple access forward (MAF) service and a live service demonstration is currently being planned via the 2nd and 3rd generation TDRS satellites.
Spaceborne sensors like NASA's Hyperion hyperspectral imager generate huge data volumes, and several near-term trends indicate that data volumes will only increase. Next-generation hyperspectral missions, such as NASA's Hyperspectral Infrared Imager (HyspIRI), will operate at higher duty cycles and higher data rates, and their users will expect products to be generated from the data in near real time [1]. Barring a sudden advance in satellite downlink capacity, these trends point to a need to process data and generate products onboard the spacecraft. Rather than downlink an entire hyperspectral image cube, onboard processing enables satellites to downlink partial or completed scientific data products, which are often one to two orders of magnitude smaller than the original image. In addition, a satellite with onboard data processing resources and direct broadcast transmission equipment could send data products directly to first responders, research scientists or other users on the ground. Next-generation space-capable data processors will have a combination of reconfigurable gate arrays, digital signal processors and general-purpose CPUs. Correctly programmed and configured, these resources are sufficient to run sophisticated data analysis programs, including hyperspectral image processing algorithms that commonly run on desktop computers [2]. This paper describes how we implemented one such program, the HSEG hierarchical image segmentation algorithm, software commonly used on desktop and parallel processors, on a hardware platform designed to mimic a next-generation space-capable data processor [3]. We also describe our approach to porting the algorithm to and optimizing it for the new platform, and determine the expected performance gains enabled by our design. This extended abstract will describe the HSEG algorithm and hardware platform in greater detail, provide an analysis of the key function within the algorithm that required hardware acceleration, and describe our implementation of that function in hardware.
Entry heating flight data and wind tunnel data on the side fuselage and payload bay door, Z = 400 and 440 trace aft of X/L=0.2, for the first five flights of the Space Shuttle Orbiter are presented. The heating rate data are reviewed in terms of normalized film heat transfer coefficients as a function of angle of attack, Mach number, and normal shock Reynolds number. The surface heatings rates and temperatures were obtained by the JSC NONLIN/INVERSE computer program. Time history plots of the surface heating rates and temperatures are outlined.
Operations problems and cost drivers were identified for current propulsion systems and design and technology approaches were identified to increase the operational efficiency and to reduce operations costs for future propulsion systems. To provide readily usable data for the ALS program, the results of the OEPSS study were organized into a series of OEPSS Data Books. This volume presents a detailed description of 25 major problems encountered during launch processing of current expendable and reusable launch vehicles. A concise description of each problem and its operational impact on launch processing is presented, along with potential solutions and technology recommendation.
The study was initiated to identify operational problems and cost drivers for current propulsion systems and to identify technology and design approaches to increase the operational efficiency and reduce operations costs for future propulsion systems. To provide readily usable data for the Advanced Launch System (ALS) program, the results of the OEPSS study were organized into a series of OEPSS Data Books. This volume describes operations technologies that will enhance operational efficiency of propulsion systems. A total of 15 operations technologies were identified that will eliminate or mitigate operations problems described in Volume 2. A recommended development plan is presented for eight promising technologies that will simplify the propulsion system and reduce operational requirements.
This study was initiated to identify operations problems and cost drivers for current propulsion systems and to identify technology and design approaches to increase the operational efficiency and reduce operations costs for future propulsion systems. To provide readily usable data for the Advanced Launch System (ALS) program, the results of the OEPSS study have been organized into a series of OEPSS Data Books. This volume describes three propulsion concepts that will simplify the propulsion system design and significantly reduce operational requirements. The concepts include: (1) a fully integrated, booster propulsion module concept for the ALS that avoids the complex system created by using autonomous engines with numerous artificial interfaces; (2) an LOX tank aft concept which avoids potentially dangerous geysering in long LOX propellant lines; and (3) an air augmented, rocket engine nozzle afterburning propulsion concept that will significantly reduce LOX propellant requirements, reduce vehicle size and simplify ground operations and ground support equipment and facilities.
ISEE 3 spacecraft measurements within and near the Earth's magnetic tail is presented. Plots are shown of ISEE 3 magnetic field data. The plots in this volume showing observations from the ISEE 3 vector helium magnetometer experiment were produced from a tape of merged plasma/magnetic field data. The magnetometer produced six vector measurements/sec that were subsequently averaged over one minute intervals before merging with plasma data. Merging was accomplished by associating the nearest 1 minute field average with each plasma sample.
This study was initiated to identify operations problems and cost drivers for current propulsion systems and to identify technology and design approaches to increase the operational efficiency and reduce operations costs for future propulsion systems. To provide readily usable data for the Advanced Launch System (ALS) Program, the results of the Operationally Efficient Propulsion System Study (OEPSS) were organized into a series of OEPSS Data Books. This volume contains the final briefing on the OEPSS first-year effort. This briefing was presented to MSFC as part of an effort to promote greater interaction between the design community and the launch site operator.
Analysis of data systems and computer programs for nuclear rocket shielding methods, modification, updating, and data input preparation - Vol. 1
The Data Assimilation Office (DAO) at Goddard Space Flight Center has produced a multiyear global assimilated data set with version 1 of the Goddard Earth Observing System Data Assimilation System (GEOS-1 DAS). One of the main goals of this project, in addition to benchmarking the GEOS-1 system, was to produce a research quality data set suitable for the study of short-term climate variability. The output, which is global and gridded, includes all prognostic fields and a large number of diagnostic quantities such as precipitation, latent heating, and surface fluxes. Output is provided four times daily with selected quantities available eight times per day. Information about the observations input to the GEOS-1 DAS is provided in terms of maps of spatial coverage, bar graphs of data counts, and tables of all time periods with significant data gaps. The purpose of this document is to serve as a users' guide to NASA's first multiyear assimilated data set and to provide an early look at the quality of the output. Documentation is provided on all the data archives, including sample read programs and methods of data access. Extensive comparisons are made with the corresponding operational European Center for Medium-Range Weather Forecasts analyses, as well as various in situ and satellite observations. This document is also intended to alert users of the data about potential limitations of assimilated data, in general, and the GEOS-1 data, in particular. Results are presented for the period March 1985-February 1990.
Existing and planned space missions to a variety of planetary and satellite surfaces produce an ever increasing volume of spectral data. Understanding the scientific informational content in this large data volume is a daunting task. Fortunately various statistical approaches are available to assess such data sets. Here we discuss an automated classification scheme based on Kohonen Self-organizing maps (SOM) we have developed. The SUM process produces an output layer were spectra having similar properties lie in close proximity to each other. One major effort is partitioning this output layer into appropriate regions. This is prefonned by defining dosed regions based upon the strength of the boundaries between adjacent cells in the SOM output layer. We use the Davies-Bouldin index as a measure of the inter-class similarities and intra-class dissimilarities that determines the optimum partition of the output layer, and hence number of SOM clusters. This allows us to identify the natural number of clusters formed from the spectral data. Mineral spectral libraries prepared at Arizona State University (ASU) and John Hopkins University (JHU) are used to test and evaluate the classification scheme. We label the library sample spectra in a hierarchical scheme with class, subclass, and mineral group names. We use a portion of the spectra to train the SOM, i.e. produce the output layer, while the remaining spectra are used to test the SOM. The test spectra are presented to the SOM output layer and assigned membership to the appropriate cluster. We then evaluate these assignments to assess the scientific meaning and accuracy of the derived SOM classes as they relate to the labels. We demonstrate that unsupervised classification by SOMs can be a useful component in autonomous systems designed to identify mineral species from reflectance and emissivity spectra in the therrnal IR.
The combination of ever-growing scientific datasets and distributed workflow complexity creates I/O performance bottlenecks due to data volume, velocity, and variety. Although the increasing use of descriptive data formats (e.g., HDF5, netCDF) helps organize these datasets, it also creates obscure bottlenecks due to the need to translate high level operations into file addresses and then into low-level I/O operations. To address this challenge, we introduce DaYu, a method and toolset for analyzing (a) semantic relationships between logical datasets and file addresses, (b) how dataset operations translate into I/O, and (c) the combination across entire workflows. DaYu's analysis and visualization enables identification of critical bottlenecks and reasoning about remediation. We describe our methodology and propose optimization guidelines. Evaluation on scientific workflows demonstrates up to 3.7x performance improvements in I/O time for obscure bottlenecks. The time and storage overhead for DaYu's time-ordered data is typically under 0.2% of runtime and 0.25% of data volume, respectively.
In the near future NASA intends to explore Mars in preparation for a sample return mission using robotic devices such as landers, rovers, orbiters, airplanes, and/or balloons. Such platforms will likely carry imaging devices to characterize the surface morphology, and a variety of analytical instruments intended to evaluate the chemical and mineralogical nature of the environment(s) that they encounter. Historically, mission operations have involved the following sequence of activities: (1) return of scientific data from the vehicle; (2) evaluation of the data by space scientists; (3) recommendations of the scientists regarding future mission activity; (4) transmission of commands to the vehicle to achieve this activity; and (5) new activity by the vehicle in response to those commands. This is repeated for the duration of the mission, with command opportunities once or perhaps twice per day. In a rapidly changing environment, such as might be encountered by a rover traversing hundreds of meters a day or an airplane soaring over several hundred of kilometers, this traditional cycle of data evaluation and commands is not amenable to rapid long range traverses, discovery of novelty, or rapid response to any unanticipated situations. In addition, to issues of response time, the nature of imaging and/or spectroscopic devices are such that tremendous data volumes can be acquired, for example during a traverse. These data volumes can rapidly exceed on-board memory capabilities prior to an opportunity to transmit it to Earth.
Volume 7 of the Satellite Power Systems (SPS) Concept Definition Study final report summarizes the basic requirements used as a guide to systems analysis and is a basis for the selection of candidate SPS point design(s). Initially, these collected data reflected the level of definition resulting from the evaluation of a broad spectrum of SPS concepts. As the various concepts matured these requirements were updated to reflect the requirements identified for the projected satellite system/subsystem point design(s). The identified subsystem/systems requirements are defined, and where appropriate, recommendations for alternate approaches which may represent improved design features are presented. A more detailed discussion of the selected point design(s) will be found in Volume 2 of this report.
In the near future NASA intends to explore various regions of our solar system using robotic devices such as rovers, spacecraft, airplanes, and/or balloons. Such platforms will likely carry imaging devices, and a variety of analytical instruments intended to evaluate the chemical and mineralogical nature of the environment(s) that they encounter. Historically, mission operations have involved: (1) return of scientific data from the craft; (2) evaluation of the data by space scientists; (3) recommendations of the scientists regarding future mission activity; (4) commands for achieving these activities being transmitted to the craft; and (5) the activity being undertaken. This cycle is then repeated for the duration of the mission with command opportunities once or perhaps twice per day. In a rapidly changing environment, such as might be encountered by a rover traversing hundreds of meters a day or a spacecraft encountering an asteroid, this historical cycle is not amenable to rapid long range traverses, discovery of novelty, or rapid response to any unexpected situations. In addition to real-time response issues, the nature of imaging and/or spectroscopic devices are such that tremendous data volumes can be acquired, for example during a traverse. However, such data volumes can rapidly exceed on-board memory capabilities prior to the ability to transmit it to Earth. Additionally, the necessary communication band-widths are restrictive enough so that only a small portion of these data can actually be returned to Earth. Such scenarios clearly require the enabling of some crucial decisions to be made on-board by these robotic explorers. These decisions transcend the electromechanical control, health, and navigation issues associated with robotic operations. Instead they focus upon a long term goal of automating scientific discovery based upon data returned by sensors of the robot craft. Such an approach would eventually enable it to understand what is interesting because the data deviates from expectations generated by current theories/models of planetary processes that could have resulted in the observed data. Such interesting data and/or conclusions can then be selectively transmitted to Earth thus reducing memory and communications demands.