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DebriSat Fragment Characterization System and Processing Status
The DebriSat project is a continuing effort sponsored by NASA and DoD to update existing break-up models using data obtained from hypervelocity impact tests performed to simulate on-orbit collisions. After the impact tests, a team at the University of Florida has been working to characterize the fragments in terms of their mass, size, shape, color and material content. The focus of the post-impact effort has been the collection of 2 mm and larger fragments resulting from the hypervelocity impact test. To date, in excess of 125K fragments have been recovered which is approximately 40K more than the 85K fragments predicted by the existing models. While the fragment collection activities continue, there has been a transition to the characterization of the recovered fragments. Since the start of the characterization effort, the focus has been on the use of automation to (i) expedite the fragment characterization process and (ii) minimize the effects of human subjectivity on the results; e.g., automated data entry processes were developed and implemented to minimize errors during transcription of the measurement data. At all steps of the process, however, there is human oversight to ensure the integrity of the data. Additionally, repeatability and reproducibility tests have been developed and implemented to ensure that the instrumentations used in the characterization process are accurate and properly calibrated.
Preliminary Test Results on a Closed-Loop Contaminant Removal System for Processing of Metallic Melts
Processing of metallic melts in microgravity containerless experiments requires control of contaminants like oxygen and water vapor to below parts-per-billion (ppb) levels.
The Earth Science Data and Information System Project (ESDIS)
Earth Science Data and Information Systems Overview at the Open Source Science for the Earth System Observatory Science Data Processing System Workshop.
Introduction of an Agile Systems Engineering Process to the NASA Armstrong Flight Research Center
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Autonomous Frequency-Domain Indentification
Test and data-processing system determines plant models and uncertainties. Integrated system of methods, digital signal-processing, and algorithms identifies parametric model of large, flexible structures. Experiments in development of system conducted on laboratory model intended to represent large space antenna or flexible spacecraft. Also applicable to many terrestrial systems, robust control of dynamic plants and processes, robust control of systems about which knowledge uncertain or incomplete, decentralized control, and knowledge-based control systems.
Processing Spacecraft Data Without Confusion
Producing multiple versions of the same data product for the same time frame with the same remotely sensed inputs can be a recipe for disaster. Yet, amidst the commotion of satellite launch and early operations (LEO), such data processing is needed. After LEO, the situation gets worse. Processing newly arriving data ("forward processing") is augmented with reprocessing and algorithm development, comparison, evaluation, and testing -- often happening all at the same time. The problem can be analyzed in three main parts -- maintaining multiple versions of algorithms and data so that end-product users are not overwhelmed,allocating computer resources efficiently, and simplifying production operations so that va st amounts of data can be processed with minimal staff and fewer errors. OMIDAPS provides a framework for execution of algorithms that transform lower level data acquired by OMI on NASA's Aura satellite into higher level science data products. In contrast to traditional science data processing systems, we address all parts of the problem with an innovative approach allowing multiple data processing to run within a single physical system. The data products, imports, exports, and execution planning are all segregated into distinct "ArchiveSets." This paper describes reasons for multiple concurrent productions on a typical satellite data processing project using OMI as an example. It describes the virtual data processing system concept and its advantages over separate physical processing strings. It explores the specific implementation of the virtual systems within OMIDAPS and discusses some of the implications of our approach and describes how virtual processing is used to accomplish the overall mission of OMI data processing.
Three-Dimensional Robotic Vision System
Stereoscopy and motion provide clues to outlines of objects. Digital image-processing system acts as "intelligent" automatic machine-vision system by processing views from stereoscopic television cameras into three-dimensional coordinates of moving object in view. Epipolar-line technique used to find corresponding points in stereoscopic views. Robotic vision system analyzes views from two television cameras to detect rigid three-dimensional objects and reconstruct numerically in terms of coordinates of corner points. Stereoscopy and effects of motion on two images complement each other in providing image-analyzing subsystem with clues to natures and locations of principal features.
Medical Information Management System
On-line interactive information processing system easily and rapidly handles all aspects of data management related to patient care. General purpose system is flexible enough to be applied to other data management situations found in areas such as occupational safety data, judicial information, or personnel records.
LACIE/ERIPS software system summary
The Earth resources interactive processing system (ERIPS) supports LACIE by classifying LANDSAT sensed data on the basis of the statistical similarity to those portions which were identified by analysts. The development and capabilities of the ERIPS software system are described with emphasis on (1) system requirements; (2) LACIE/ERIPS hardware; (3) system functions; (4) pattern recognition concept; and (5) LACIE/ERIPS data bases. Algorithms used in LACIE/ERIPS for statistics, divergence, feature selection, classification, registration, adaptive clustering, iterative clustering, clustering report functions, Sun angle correction, mean level adjustment, and bias correction are appended.
Reduce fluid experiment system flight data from IML-1
Processing and data reduction of holographic images from Spacelab presents some interesting challenges in determining the effects of microgravity on crystal growth processes. Evaluation of several processing techniques, including the Computerized Holographic Image Processing System and the Software Development Package (SDP151) will provide fundamental information for holographic and schlieren analysis of the space flight data.
Medical Imaging System
The MD Image System, a true-color image processing system that serves as a diagnostic aid and tool for storage and distribution of images, was developed by Medical Image Management Systems, Huntsville, AL, as a "spinoff from a spinoff." The original spinoff, Geostar 8800, developed by Crystal Image Technologies, Huntsville, incorporates advanced UNIX versions of ELAS (developed by NASA's Earth Resources Laboratory for analysis of Landsat images) for general purpose image processing. The MD Image System is an application of this technology to a medical system that aids in the diagnosis of cancer, and can accept, store and analyze images from other sources such as Magnetic Resonance Imaging.
Oversimplification of Systems Engineering Goals, Processes, and Criteria in NASA Space Life Support
This paper investigates the oversimplification of the inherently complex systems engineering process in space life support. The standard systems engineering process steps are described. The International Space Station (ISS) life support system is explained with its goals and performance criteria. Although it is not usually emphasized, the essential function of developing a hierarchy of systems and subsystems is to simplify the design process. The System Complexity Metric (SCM) shows how this di-vide-and-conquer approach also reduces the system complexity. The complete systems engineering process has many detailed steps. It is often simplified because of the effort required and the human limitations on working memory and decision span. Systems analysis demands slow, logical, and fo-cused thinking but is often bypassed in favor of quick, intuitive, subconscious “gut feel.” A study of 100 system designs found examples of 12 specific mental mistakes, such as ignoring stakeholder needs, and these mistakes are essentially oversimplifications of the systems engineering process. An analysis of space life support goals, options, criteria, and processes found 11 examples of oversimplifications in systems engineering, such as neglecting safety and cost. All these 11 oversimplifications could be traced to one or more of the 12 previously identified mental mistakes or other well-known ones, such as ig-noring sunk costs. Oversimplification of the systems engineering process is rarely noticed but is a common and harmful problem. A study of failures in 50 different space systems found that problems in systems engineering caused failures and often led to errors in design, development, and test that further contributed to failure. It seems that more diligent systems engineering could prevent many project problems and failures, but projects seem to be more guided by “gut feel” based on tradition, authority, and consensus than on the logical, rational systems engineering approach.
Seasat synthetic-aperture radar data reduction using parallel programmable array processors
This paper presents a digital processing system that produces the Seasat synthetic-aperture radar (SAR) imagery. The system consists of a SEL 32/77 host minicomputer and three AP-120B array processors. The partitioning of the SAR processing functions and the design of software modules is described. The rationale for selecting the parallel array processor architecture and the methodology for developing the parallel processing scheme on this system is described. This system attains a Seasat SAR data reduction speed of 2.5 h per 25-m resolution 4-look and 100 km x 100 km image frame. A preliminary performance evaluation of this parallel processing system and potential future applications for remote sensing data reduction are described.
Microchemical and Thermal Systems for In-Situ Resource Utilization
Process Intensification and Process Miniaturization can simultaneously be achieved through the application of microfabricated chemical process systems, based on the rapid heat and mass transport in engineered microchannels. Researchers at NASA's Johnson Space Center (JSC) and the Department of Energy's Pacific Northwest National Laboratory (PNNL) are collaboratively developing micro thermal and chemical systems for NASA's Mission to Mars program. Preliminary results show that many standard chemical process components (e.g., heat exchangers, chemical reactors and chemical separations units) can be reduced in hardware volume without a corresponding reduction in chemical production rates. Low pressure drops and improved thermal integration are also accomplished when appropriate scaling rules are applied and when individual microchemical components are packaged together into integral systems.
Microchemical and Thermal Systems for In-Situ Resource Utilization
Process Intensification and Process Miniaturization can simultaneously be achieved through the application of microfabricated chemical process systems, based on the rapid heat and mass transport in engineered microchannels. Researchers at NASA's Johnson Space Center (JSC) and the Department of Energy's Pacific Northwest National Laboratory (PNNL) are collaboratively developing micro thermal and chemical systems for NASA's Mission to Mars program. Preliminary results show that many standard chemical process components (e.g., heat exchangers, chemical reactors and chemical separations units) can be reduced in hardware volume without a corresponding reduction in chemical production rates. Low pressure drops and improved thermal integration are also accomplished when appropriate scaling rules are applied and when individual microchemical components are packaged together into integral systems.
Architectures Toward Reusable Science Data Systems
Science Data Systems (SDS) comprise an important class of data processing systems that support product generation from remote sensors and in-situ observations. These systems enable research into new science data products, replication of experiments and verification of results. NASA has been building systems for satellite data processing since the first Earth observing satellites launched and is continuing development of systems to support NASA science research and NOAA's Earth observing satellite operations. The basic data processing workflows and scenarios continue to be valid for remote sensor observations research as well as for the complex multi-instrument operational satellite data systems being built today.
Basic principles of flight test instrumentation engineering, volume 1, issue 2
Volume 1 of the AG 300 series on ´Flight Test Instrumentation´ gives a general introduction to the basic principles of flight test instrumentation. The other volumes in the series provide more detailed treatments of selected topics on flight test instrumentation. Volume 1, first published in 1974, has been used extensively as an introduction for instrumentation courses and symposia, as well as being a reference work on the desk of most flight test and instrumentation engineers. It is hoped that this second edition, fully revised, will be used with as much enthusiasm as the first edition. In this edition a flight test system is considered to include both the data collection and data processing systems. In order to obtain an optimal data flow, the overall design of these two subsystems must be carefully matched; the detail development and the operation may have to be done by separate groups of specialists. The main emphasis is on the large automated instrumentation systems used for the initial flight testing of modern military and civil aircraft. This is done because there, many of the problems, which are discussed here, are more critical. It does not imply, however, that smaller systems with manual data processing are no longer used. In general, the systems should be designed to provide the required results at the lowest possible cost. For many tests which require only a few parameters, relatively simple systems are justified, especially if no complex equipment is available to the user. Although many of the aspects discussed in this volume apply to both small and large systems, aspects of the smaller systems are mentioned only when they are of special interest. The volume has been divided into three main parts. Part 1 defines the main starting points for the design of a flight test instrumentation system, as seen from the points of view of the flight test engineer and the instrumentation engineer. In Part 2 the discussion is concentrated on those aspects which apply to each individual measuring channel, and in Part 3 the main emphasis is on the integration of the individual data channels into one data collection system and on those aspects of the data processing which apply to the complete system.