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At least 379 records · Page 21

SOHO Ultraviolet Coronagraph Spectrometer (UVCS) Mission Operations and Data Analysis

The scientific goal of UVCS is to obtain detailed empirical descriptions of the extended solar corona as it evolves over the solar cycle and to use these descriptions to identify and understand the physical processes responsible for coronal heating, solar wind acceleration, coronal mass ejections (CMEs), and the phenomena that establish the plasma properties of the solar wind as measured by "in situ" solar wind instruments. This report covers the period from 15 February 2003 to 14 April 2004. During that time, UVCS observations have consisted of three types: 1) standard synoptic observations comprising, primarily, the H I Lyalpha line profile and the 0 VI 103.2 and 103.7 nm intensity over a range of heights from 1.5 to about 3.0 solar radii and covering 360 degrees about the Sun, 2) sit and stare observations for major flare watches, and 3) special observations designed by the UVCS Lead Observer of the Week for a specific scientific purpose. The special observations are often coordinated with those of other space-based and ground-based instruments and they often are part of SOHO joint observation programs and campaigns. Lead observers have included UVCS Co-Investigators, scientists from the solar physics community and several graduate and undergraduate level students. UVCS has continued to achieve its purpose of using powerful spectroscopic diagnostic techniques to obtain a much more detailed description of coronal structures and dynamic phenomena than existed before the SOHO mission. The new descriptions of coronal mass ejections (CMEs) and coronal structures from UVCS have inspired a large number of theoretical studies aimed at identifying the physical processes responsible for CMEs and solar wind acceleration in coronal holes and streamers. UVCS has proven to be a very stable instrument. Stellar observations have demonstrated its radiometric stability. UVCS has not required any flight software modifications and all mechanisms are operational. The UVCS 0 VI Channel with its redundant optical path for wavelengths near H I Lyalpha is capable of observing the entire UVCS wavelength range. The regions of the detector currently being used require different grating angles for direct OVI observations and redundant path H I Lyalpha observations, and so those can no longer be observed simultaneously. Since December 1998, the 0 VI Channel has been used for all UVCS observations. Although the H I Lyalpha Channel and detector are still operational, increases in the dark count up to about 5x10(exp 4) counts/sec/pixel and an increase in high voltage current to within a factor of two of the maximum used in the laboratory before flight led to the decision to not use that detector after 1998. The visible light channel functioned nominally during the reporting period. UVCS data, data analysis software, calibration files and the mission log are available from the SOHO archive and SAO. All UVCS data are now available within three months of the observations to scientists and the general public via the SOHO Data Archive and SAO. UVCS has resulted in 33 scientific papers in 2003. There were numerous presentations at scientific meetings. UVCS Education and Public Outreach activities involved nine members of the UVCS team. During the reporting period, there were over a dozen events directed at students and teachers, museum audiences, and public audiences via the mass media, internet and educational literature.

Gurman, Joseph↗

Command decoder unit

The design and testing of laboratory hardware (a command decoder unit) used in evaluating space shuttle instrumentation, data processing, and ground check-out operations is described. The hardware was a modification of another similar instrumentation system. A data bus coupler was designed and tested to interface the equipment to a central bus controller (computer). A serial digital data transfer mechanism was also designed. Redundant power supplies and overhead modules were provided to minimize the probability of a single component failure causing a catastrophic failure. The command decoder unit is packaged in a modular configuration to allow maximum user flexibility in configuring a system. Test procedures and special test equipment for use in testing the hardware are described. Results indicate that the unit will allow NASA to evaluate future software systems for use in space shuttles. The units were delivered to NASA and appear to be adequately performing their intended function. Engineering sketches and photographs of the command decoder unit are included.

Source record↗

Software For A Laser Vibrometer

Vibration Pattern Imager (VPI) system and software designed to control and acquire data from laser vibrometer sensors. Based on personal computer, includes digital signal-processing (DSP) board and analog input/output (I/O) circuit board to control sensors and process data. Originally developed for use with Ometron VPI Sensor, adapted to any commercially available sensor that provides analog output signal and requires analog inputs for control of mirror position. VPI system includes graphical user interface providing for interactive control through keyboard and mouse-selected menu options. Main menu controls all functions for setup, acquisition of data, display, file operations, and leaving program. Two types of data acquired with system: single point or "full field". Written in C language and Texas Instrument' TMS320C30 assembly language.

Rizzi, Stephen A.↗

Lessons Learned in the Livingstone 2 on Earth Observing One Flight Experiment

The Livingstone 2 (L2) model-based diagnosis software is a reusable diagnostic tool for monitoring complex systems. In 2004, L2 was integrated with the JPL Autonomous Sciencecraft Experiment (ASE) and deployed on-board Goddard's Earth Observing One (EO-1) remote sensing satellite, to monitor and diagnose the EO-1 space science instruments and imaging sequence. This paper reports on lessons learned from this flight experiment. The goals for this experiment, including validation of minimum success criteria and of a series of diagnostic scenarios, have all been successfully net. Long-term operations in space are on-going, as a test of the maturity of the system, with L2 performance remaining flawless. L2 has demonstrated the ability to track the state of the system during nominal operations, detect simulated abnormalities in operations and isolate failures to their root cause fault. Specific advances demonstrated include diagnosis of ambiguity groups rather than a single fault candidate; hypothesis revision given new sensor evidence about the state of the system; and the capability to check for faults in a dynamic system without having to wait until the system is quiescent. The major benefits of this advanced health management technology are to increase mission duration and reliability through intelligent fault protection, and robust autonomous operations with reduced dependency on supervisory operations from Earth. The work-load for operators will be reduced by telemetry of processed state-of-health information rather than raw data. The long-term vision is that of making diagnosis available to the onboard planner or executive, allowing autonomy software to re-plan in order to work around known component failures. For a system that is expected to evolve substantially over its lifetime, as for the International Space Station, the model-based approach has definite advantages over rule-based expert systems and limit-checking fault protection systems, as these do not scale well. The model-based approach facilitates reuse of the L2 diagnostic software; only the model of the system to be diagnosed and telemetry monitoring software has to be rebuilt for a new system or expanded for a growing system. The hierarchical L2 model supports modularity and expendability, and as such is suitable solution for integrated system health management as envisioned for systems-of-systems.

Hayden, Sandra C.↗

TRANSLATE - a Monte Carlo simulation of electron transport in liquid argon

Here, the microphysics of electron and photon propagation in liquid argon is a key component of detector design and calibrations needed to construct and perform measurements within a wide range of particle physics experiments. As experiments grow in scale and complexity, and as the precision of their intended measurements increases, the development of tools to investigate important microphysics effects impacting such detectors becomes necessary. In this paper we present a new time-domain Monte Carlo simulation of electron transport in liquid argon. The simulation models the TRANSport in Liquid Argon of near-Thermal Electrons (TRANSLATE) with the aim of providing a multi-purpose software package for the study and optimization of detector environments, with a particular focus on ongoing and next generation liquid argon neutrino experiments utilizing the time projection chamber technology. TRANSLATE builds on previous work of Wojcik and Tachiya, amongst others, introducing additional processes, including ionization, thus modeling the full range of drift electron scattering interactions. The simulation is validated by benchmarking its performance with swarm parameters from data collected in experimental setups operating in gas and liquid.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗

Improved Modeling of Land-Atmosphere Interactions using a Coupled Version of WRF with the Land Information System

The exchange of energy and moisture between the Earth's surface and the atmospheric boundary layer plays a critical role in many hydrometeorological processes. Accurate and high-resolution representations of surface properties such as sea-surface temperature (SST), vegetation, soil temperature and moisture content, and ground fluxes are necessary to better understand the Earth-atmosphere interactions and improve numerical predictions of weather and climate phenomena. The NASA/NWS Short-term Prediction Research and Transition (SPORT) Center is currently investigating the potential benefits of assimilating high-resolution datasets derived from the NASA moderate resolution imaging spectroradiometer (MODIS) instruments using the Weather Research and Forecasting (WRF) model and the Goddard Space Flight Center Land Information System (LIS). The LIS is a software framework that integrates satellite and ground-based observational and modeled data along with multiple land surface models (LSMs) and advanced computing tools to accurately characterize land surface states and fluxes. The LIS can be run uncoupled to provide a high-resolution land surface initial condition, and can also be run in a coupled mode with WRF to integrate surface and soil quantities using any of the LSMs available in LIS. The LIS also includes the ability to optimize the initialization of surface and soil variables by tuning the spin-up time period and atmospheric forcing parameters, which cannot be done in the standard WRF. Among the datasets available from MODIS, a leaf-area index field and composite SST analysis are used to improve the lower boundary and initial conditions to the LIS/WRF coupled model over both land and water. Experiments will be conducted to measure the potential benefits from using the coupled LIS/WRF model over the Florida peninsula during May 2004. This month experienced relatively benign weather conditions, which will allow the experiments to focus on the local and mesoscale impacts of the high-resolution MODIS datasets and optimized soil and surface initial conditions. Follow-on experiments will examine the utility of such an optimized WRF configuration for more complex weather scenarios such as convective initiation. This paper will provide an overview of the experiment design and present preliminary results from selected cases in May 2004.

Case, Jonathan L.↗

Science of the Van Allen Probes Science Operations Centers

The Van Allen Probes mission operations materialized through a distributed model in which operational responsibility was divided between the Mission Operations Center (MOC) and separate instrument specific SOCs. The sole MOC handled all aspects of telemetering and receiving tasks as well as certain scientifically relevant ancillary tasks. Each instrument science team developed individual instrument specific SOCs proficient in unique capabilities in support of science data acquisition, data processing, instrument performance, and tools for the instrument team scientists. In parallel activities, project scientists took on the task of providing a significant modeling tool base usable by the instrument science teams and the larger scientific community. With a mission as complex as Van Allen Probes, scientific inquiry occurred due to constant and significant collaboration between the SOCs and in concert with the project science team. Planned cross-instrument coordinated observations resulted in critical discoveries during the seven-year mission. Instrument cross-calibration activities elucidated a more seamless set of data products. Specific topics include post-launch changes and enhancements to the SOCs, discussion of coordination activities between the SOCs, SOC specific analysis software, modeling software provided by the Van Allen Probes project, and a section on lessons learned. One of the most significant lessons learned was the importance of the original decision to implement individual team SOCs providing timely and well-documented instrument data for the NASA Van Allen Probes Mission scientists and the larger magnetospheric and radiation belt scientific community.

47 OTHER INSTRUMENTATION↗

Hindsight logging for model training

In modern Machine Learning, model training is an iterative, experimental process that can consume enormous computation resources and developer time. To aid in that process, experienced model developers log and visualize program variables during training runs. Exhaustive logging of all variables is infeasible, so developers are left to choose between slowing down training via extensive conservative logging, or letting training run fast via minimalist optimistic logging that may omit key information. As a compromise, optimistic logging can be accompanied by program checkpoints; this allows developers to add log statements post-hoc, and "replay" desired log statements from checkpoint---a process we refer to as hindsight logging. Unfortunately, hindsight logging raises tricky problems in data management and software engineering. Done poorly, hindsight logging can waste resources and generate technical debt embodied in multiple variants of training code. In this paper, we present methodologies for efficient and effective logging practices for model training, with a focus on techniques for hindsight logging. Our goal is for experienced model developers to learn and adopt these practices. To make this easier, we provide an open-source suite of tools for Fast Low-Overhead Recovery (flor) that embodies our design across three tasks: (i) efficient background logging in Python, (ii) adaptive periodic checkpointing, and (iii) an instrumentation library that codifies hindsight logging for efficient and automatic record-replay of model-training. Model developers can use each flor tool separately as they see fit, or they can use flor in hands-free mode, entrusting it to instrument their code end-to-end for efficient record-replay. Our solutions leverage techniques from physiological transaction logs and recovery in database systems. Evaluations on modern ML benchmarks demonstrate that flor can produce fast checkpointing with small user-specifiable overheads (e.g. 7%), and still provide hindsight log replay times orders of magnitude faster than restarting training from scratch.

Computer Science↗

Biomechanical Modeling Analysis of Loads Configuration for Squat Exercise

INTRODUCTION: Long duration space travel will expose astronauts to extended periods of reduced gravity. Since gravity is not present to assist loading, astronauts will use resistive and aerobic exercise regimes for the duration of the space flight to minimize loss of bone density, muscle mass and aerobic capacity that occurs during exposure to a reduced gravity environment. Unlike the International Space Station (ISS), the area available for an exercise device in the next generation of spacecraft for travel to the Moon or to Mars is limited and therefore compact resistance exercise device prototypes are being developed. The Advanced Resistive Exercise Device (ARED) currently on the ISS is being used as a benchmark for the functional performance of these new devices. Biomechanical data collection and computational modeling aid the device design process by quantifying the joint torques and the musculoskeletal forces that occur during exercises performed on the prototype devices. METHODS The computational models currently under development utilize the OpenSim [1] software platform, consisting of open source code for musculoskeletal modeling, using biomechanical input data from test subjects for estimation of muscle and joint loads. The OpenSim Full Body Model [2] is used for all analyses. The model incorporates simplified wrap surfaces, a new knee model and updated lower body muscle parameters derived from cadaver measurements and magnetic resonance imaging of young adults. The upper body uses torque actuators at the lumbar and extremity joints. The test subjects who volunteer for this study are instrumented with reflective markers for motion capture data collection while performing squat exercising on the Hybrid Ultimate Lifting Kit (HULK) prototype device (ZIN Technologies, Middleburg Heights, OH). Ground reaction force data is collected with force plates under the feet, and device loading is recorded through load cells internal to the HULK. Test variables include the applied device load and the dual cable long bar or single cable T-bar interface between the test subject and the device. Data is also obtained using free weights with the identical loading for a comparison to the resistively loaded exercise device trials. The data drives the OpenSim biomechanical model, which has been scaled to match the anthropometrics of the test subject, to calculate the body loads. RESULTS Lower body kinematics, joint moments, joint forces and muscle forces are obtained from the OpenSim biomechanical analysis of the squat exercises under different loading conditions. Preliminary results from the model for the loading conditions will be presented as will hypotheses developed for follow on work.

Human Factors Engineering↗

Spatially Resolved Raman Spectroscopic Investigation of Uranyl Fluoride: A Case Study in the Importance of Instrument Optimization

Raman spectroscopy is an emerging technique for rapid and nondestructive analysis of nuclear materials for forensic and nonproliferation applications as it is a powerful tool for distinguishing multiple chemical forms of materials with similar stoichiometries. Recent developments in spectroscopic software have enabled rapid data collection with high-speed Raman spectroscopic mapping capabilities. However, some uranium-rich materials are susceptible to degradation in humid air and/or laser-induced phase transformations. To mitigate environmental or measurement-related sample degradation of potential samples of interest, we have taken a systematic approach to define optimized data collection parameters for high-throughput measurements of uranyl fluoride (UO 2 F 2 ), which is an important intermediate material in the nuclear fuel cycle. First, we systematically describe the influence of optical magnification (5× to 100×), laser power, and exposure time on obtained signal for identical particles of UO 2 F 2 and find that at low laser power and exposure times, comparable signal is obtained regardless of optical magnification. Second, we ensure sample integrity during data collection, and third, collect spectroscopic maps that employ optimized parameters to reduce the time required to obtain spatially resolved spectroscopic information. Reductions of 90% and 99% in measurement times are discussed as they relate to differences in resolving spectroscopic features of particles in identical mapping areas. Finally, during this work, we found that additional data processing options were needed and thus developed a customized Python script for importing, processing, analyzing, and visualizing Raman spectroscopic map data.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗

Do it yourself remote sensing: Generating an inexpensive, high tech, real science lake mapping project for the classroom

The utilization of modest equipment and software revealed bottom contours and water column conditions of a dynamic water body. Classroom discussions of field techniques and equipment capabilities followed by exercises with the data sets in cause-and-effect analysis all contributed to participatory education in the process of science. This project is presented as a case study of the value of engaging secondary and collegiate level students in planning, executing and appraising a real world investigation which they can directly relate to. A 1 km wide bay, experiencing marsh inflow, along an 8 km long lake situated 120 km north of Ottawa, Canada, on the glaciated Canadian Precambrian Shield was mapped in midsummer for submerged topography, bottom composition, temperature profile, turbudity, dissolved oxygen and biota distribution. Low level aerial photographs scanned into image processing software are permitting spatial classification of bottom variations in biology and geology. Instrumentation consisted of a portable sport fishing SONAR depth finder, an electronic lead line multiprobe with photocell, thermistor and dissolved oxygen sensors, a selective depth water sampler, portable pH meter, an underwater camera mounted on a home-made platform with a bottom-contact trigger and a disposable underwater camera for shallow survey work. Sampling transects were referenced using a Brunton hand transit triangulating several shore markers.

Metzger, Stephen M.↗

The Automated Instrumentation and Monitoring System (AIMS): Design and Architecture

Whether a researcher is designing the 'next parallel programming paradigm', another 'scalable multiprocessor' or investigating resource allocation algorithms for multiprocessors, a facility that enables parallel program execution to be captured and displayed is invaluable. Careful analysis of such information can help computer and software architects to capture, and therefore, exploit behavioral variations among/within various parallel programs to take advantage of specific hardware characteristics. A software tool-set that facilitates performance evaluation of parallel applications on multiprocessors has been put together at NASA Ames Research Center under the sponsorship of NASA's High Performance Computing and Communications Program over the past five years. The Automated Instrumentation and Monitoring Systematic has three major software components: a source code instrumentor which automatically inserts active event recorders into program source code before compilation; a run-time performance monitoring library which collects performance data; and a visualization tool-set which reconstructs program execution based on the data collected. Besides being used as a prototype for developing new techniques for instrumenting, monitoring and presenting parallel program execution, AIMS is also being incorporated into the run-time environments of various hardware testbeds to evaluate their impact on user productivity. Currently, the execution of FORTRAN and C programs on the Intel Paragon and PALM workstations can be automatically instrumented and monitored. Performance data thus collected can be displayed graphically on various workstations. The process of performance tuning with AIMS will be illustrated using various NAB Parallel Benchmarks. This report includes a description of the internal architecture of AIMS and a listing of the source code.

Yan, Jerry C.↗

PYSAT: Python Satellite Data Analysis Toolkit

A common problem in space science data analysis is combining complementary data sources that are provided and analyzed in different formats and programming languages. The Python Satellite Data Analysis Toolkit (pysat) addresses this issue by providing an open source toolkit that implements the general process of space science data analysis, from beginning to end, in an instrumentindependent manner. This toolkit uses an Instrument object that enables systematic analysis of science data from a variety of platforms within a single interface. Basic functions such as downloading, loading, and cleaning are included for all supported instruments. Common analysis routines are also included, which are instrument and data source independent. A nanokernel is used to provide instrument independence, it is attached to the Instrument object and mediates the systematic and arbitrary modification of loaded data. Pysat uses the nanokernel to improve the rigor of time series analysis, support onthefly orbit determination, and cleanly span file breaks. Pysat's functions and higherlevel scientific analysis features are validated through the use of unit testing. Further adoption by the community provides a set of scientific results produced by a common core, constituting a distributed heritage that supports the validity of the underlying processing and scientific output. These features are used to demonstrate consistency between derived electron density profiles and measured ion drifts, particularly downward ion drifts in the afternoon hours during extreme solar minimum. Pysat builds upon open source Python software that is freely available and encourages communitydriven development.

Stoneback, R.A.↗

Characterization of Infrared Diode Laser Beams and Atmospheric CO Imaging Instrument

During June-August 1997 Dr. Jonathan Miles participated in the ASEE-sponsored summer faculty research program at NASA Langley Research Center (LaRC). The Aerospace Electronic Systems Division (AESD), Sensor Systems Branch (SSB), at NASA LARC had proposed a new mission, GEOstationary TROpospheric Pollution SATellite (GEO TROPSAT), to address critical science questions of tropospheric chemistry. The troposphere is a complex system, comprising "point" and distributed sources of natural and anthropogenic origin; complicated transport processes, both lateral and vertical; and photochemistry driven by UV flux, temperature, atmospheric composition, and other variables. GEO TROPSAT would be implemented about a geostationary Earth orbital (GEO) position at the equator between 600 and 80" West longitude to observe the Americas and large portions of the oceans of either coast. This mission would advance our knowledge of the atmosphere by capturing the wide temporal and spatial variability of tropospheric phenomena which is undetectable from low Earth orbit. A pre-prototype imaging carbon monoxide (CO) imaging system operating within a narrow waveband about 4.7 [Lm was built, demonstrated, and evaluated. This system applies the gas-filter correlation radiometry (GFCR) technique and produces digitized images comprising 4096 pixels, each representing a single CO mixing ratio measurement inferred from radiometric data. Associated tasks accomplished included specification for the next-generation prototype system to operate in the 2.3-@tm waveband; characterization of a 64x64, InSb focal-plane-array (FPA) imager; design, fabrication, and assembly of a filter wheel; and software development. Laboratory evaluation of this system involved imaging of a test cell placed in the path of radiant flux emanating from a blackbody source used to simulate the radiant energy reflected by Earth in real application. The cell was evacuated for system balancing and then charged with measured quantities of CO to provide a means for system characterization. Two related research efforts were undertaken during the term of the study reported here - continued development of an atmospheric CO imaging instrument and characterization of diode-laser beams. Both efforts were successful and are described within the body of this report. A second objective was to provide a means for undergraduate ISAT majors to become involved with the research described, to be afforded the opportunity to learn the technologies associated with the work performed. Two ISAT students gained a comprehensive understanding and interest in missions supported by NASA through direct involvement in this project. Many more students were exposed to these technologies through demonstrations, laboratory tours, and explanations provided in lectures.

Miles, Jonathan J.↗

Kepler Mission's Focal Plane Characterization Models Implementation

The Kepler Mission photometer is an unusually complex array of CCDs. A large number of time-varying instrumental and systemic effects must be modeled and removed from the Kepler pixel data to produce light curves of sufficiently high quality for the mission to be successful in its planet-finding objective. After the launch of the spacecraft, many of these effects are difficult to remeasure frequently, and various interpolations over a small number of sample measurements must be used to determine the correct value of a given effect at different points in time. A library of software modules, called Focal Plane Characterization (FC) Models, is the element of the Kepler Science Data Pipeline (hereafter "pipeline") that handles this. FC, or products generated by FC, are used by nearly every element of the SOC processing chain. FC includes Java components: database persistence classes, operations classes, model classes, and data importers; and MATLAB code: model classes, interpolation methods, and wrapper functions. These classes, their interactions, and the database tables they represent, are discussed. This paper describes how these data and the FC software work together to provide the pipeline with the correct values to remove non-photometric effects caused by the photometer and its electronics from the Kepler light curves. The interpolation mathematics is reviewed, as well as the special case of the sky-to-pixel,pixel-to-sky coordinate transformation code, which incorporates a compound model that is unique in the SOC software.

mission↗

Modeling of Vertical Motor-driven Pump for Simulation of a Fault Signature \\ for Condition Monitoring

As part of the ongoing effort to transition from preventive maintenance strategies to condition-based maintenance strategies in nuclear power plants, there is significant reliance on using machine learning techniques. To develop a robust machine learning model that can diagnose all the fault modes of a vertical motor-driven pump, data capturing the unique signature of each fault mode is required. In practice, it is difficult to collect or capture data that captures all the fault modes from a single plant site. So to address this situation, a computational model of a vertical motor-driven pump is developed using the multipurpose finite element software COMSOL Multiphysics. The developed model is used to generate simulated data under normal operation and is compared with the vibration data collected using vibration sensors. Once the simulation model is verified under normal operating condition, simulated data for the fault mode for which minimal or no evidence is available in historical plant process data is developed. This simulated data is used to develop fault signatures to achieve robust predictive models. This paper presents modeling details and verification of the model that can used to generate data for fault modes that are not available at a plant site for condition monitoring purpose.

46 - INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AN↗

A new systems engineering approach to streamlined science and mission operations for the Far Ultraviolet Spectroscopic Explorer (FUSE)

The Mission Operations and Data Systems Directorate (MO&DSD, Code 500), the Space Sciences Directorate (Code 600), and the Flight Projects Directorate (Code 400) have developed a new approach to combine the science and mission operations for the FUSE mission. FUSE, the last of the Delta-class Explorer missions, will obtain high resolution far ultraviolet spectra (910 - 1220 A) of stellar and extragalactic sources to study the evolution of galaxies and conditions in the early universe. FUSE will be launched in 2000 into a 24-hour highly eccentric orbit. Science operations will be conducted in real time for 16-18 hours per day, in a manner similar to the operations performed today for the International Ultraviolet Explorer. In a radical departure from previous missions, the operations concept combines spacecraft and science operations and data processing functions in a single facility to be housed in the Laboratory for Astronomy and Solar Physics (Code 680). A small missions operations team will provide the spacecraft control, telescope operations and data handling functions in a facility designated as the Science and Mission Operations Center (SMOC). This approach will utilize the Transportable Payload Operations Control Center (TPOCC) architecture for both spacecraft and instrument commanding. Other concepts of integrated operations being developed by the Code 500 Renaissance Project will also be employed for the FUSE SMOC. The primary objective of this approach is to reduce development and mission operations costs. The operations concept, integration of mission and science operations, and extensive use of existing hardware and software tools will decrease both development and operations costs extensively. This paper describes the FUSE operations concept, discusses the systems engineering approach used for its development, and the software, hardware and management tools that will make its implementation feasible.

Butler, Madeline J.↗

FPGA Coprocessor for Accelerated Classification of Images

An effort related to that described in the preceding article focuses on developing a spaceborne processing platform for fast and accurate onboard classification of image data, a critical part of modern satellite image processing. The approach again has been to exploit the versatility of recently developed hybrid Virtex-4FX field-programmable gate array (FPGA) to run diverse science applications on embedded processors while taking advantage of the reconfigurable hardware resources of the FPGAs. In this case, the FPGA serves as a coprocessor that implements legacy C-language support-vector-machine (SVM) image-classification algorithms to detect and identify natural phenomena such as flooding, volcanic eruptions, and sea-ice break-up. The FPGA provides hardware acceleration for increased onboard processing capability than previously demonstrated in software. The original C-language program demonstrated on an imaging instrument aboard the Earth Observing-1 (EO-1) satellite implements a linear-kernel SVM algorithm for classifying parts of the images as snow, water, ice, land, or cloud or unclassified. Current onboard processors, such as on EO-1, have limited computing power, extremely limited active storage capability and are no longer considered state-of-the-art. Using commercially available software that translates C-language programs into hardware description language (HDL) files, the legacy C-language program, and two newly formulated programs for a more capable expanded-linear-kernel and a more accurate polynomial-kernel SVM algorithm, have been implemented in the Virtex-4FX FPGA. In tests, the FPGA implementations have exhibited significant speedups over conventional software implementations running on general-purpose hardware.

Pingree, Paula J.↗