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We propose to develop and enhance a workstation based grid analysis and display software system for Earth science data set browsing, sampling and manipulation. The system will be coupled to a super computer in a distributed computing environment for near real-time interaction between scientists and computational results.
The analysis program (AN) is specifically designed to produce graphic and tabular information to aid in the design and checkout of the Center TRACON Automation System (CTAS). To best reveal CTAS operation and possible problems, data are plotted in many different ways both in detail and summary form. AN has been designed to analyze both radar surveillance data and output data from CTAS. AN has been extensively used to debug and refine CTAS. It is also being used in the field to monitor and assess CTAS performance. AN is continuously refined to keep up with changing needs. The present version of AN grew out of analysis of Denver Center data. However, the AN software has been written to be adaptable to any other facility Center or TRACON. Presently, one can select Denver Stapleton, Denver International, Dallas/Fort Worth International Airport, and Dallas Love Field.
The X-33 program requires the use of multiple telemetry ground stations to cover the launch, ascent, transition, descent, and approach phases for the flights from Edwards AFB to landings at Dugway Proving Grounds, UT and Malmstrom AFB, MT. This paper will discuss the X-33 telemetry requirements and design, including information on fixed and mobile telemetry systems, best source selection, and support for Range Safety Officers. A best source selection system will be utilized to automatically determine the best source based on the frame synchronization status of the incoming telemetry streams. These systems will be used to select the best source at the landing sites and at NASA Dryden Flight Research Center to determine the overall best source between the launch site, intermediate sites, and landing site sources. The best source at the landing sites will be decommutated to display critical flight safety parameters for the Range Safety Officers. The overall best source will be sent to the Lockheed Martin's Operational Control Center at Edwards AFB for performance monitoring by X-33 program personnel and for monitoring of critical flight safety parameters by the primary Range Safety Officer. The real-time telemetry data (received signal strength, etc.) from each of the primary ground stations will also be compared during each nu'ssion with simulation data generated using the Dynamic Ground Station Analysis software program. An overall assessment of the accuracy of the model will occur after each mission. Acknowledgment: The work described in this paper was NASA supported through cooperative agreement NCC8-115 with Lockheed Martin Skunk Works.
Design of large precision optical systems requires multi-disciplinary analysis, modeling, and design. Thermal, structural and optical characteristics of the hardware must be accurately understood in order to design a system capable of accomplishing the performance requirements. The interactions between each of the disciplines become stronger as systems are designed lighter weight for space applications. This coupling dictates a concurrent engineering design approach. In the past, integrated modeling tools have been developed that attempt to integrate all of the complex analysis within the framework of a single model. This often results in modeling simplifications and it requires engineering specialist to learn new applications. The software described in this presentation addresses the concurrent engineering task using a different approach. The software tool, Integrated Optical Design Analysis (IODA), uses data fusion technology to enable a cross discipline team of engineering experts to concurrently design an optical system using their standard validated engineering design tools.
The Infrared Multi-Object Spectrograph (IRMOS) is a facility instrument for the Kitt Peak National Observatory Mayall Telescope (3.8 meter). IRMOS is a near-IR (0.8 - 2.5 micron) spectrograph with low to mid resolution (R=lambda/delta, lambda = 300 - 3800). The IRMOS spectrograph produces simultaneous spectra of - 100 objects in its 2.8 x 2.0 arc-min field of view using a commercial MEMS multi-mirror array device (MMA). The IRMOS optical design consists of two imaging systems, or "stages." The focal reducer, stage one, images the focal plane of the telescope onto the MMA. The spectrograph, stage two, images the MMA onto the detector. We describe the breadboard alignment method and imaging and scattered light performance for both the focal reducer and spectrograph. This testing provides verification of the optomechanical alignment method, and a measurement of the contribution of scattered light in the system due to mirror small scale surface error. After the stage I and 2 optics are integrated with the instrument, our test results will make it possible to distinguish between scattered light from the mirrors and the MMA. Image testing will be done at four wavelengths in the visible and near-IR. A mercury-argon pencil lamp will provide spectral lines at 546.1 and 1012 nm, and a blackbody radiation source lines at 1600 and 2200 nm. A CCD camera will be used as a detector for the visible wavelengths, and an IR photodiode will be used for the IR wavelengths. We compare our data with a theoretical analysis using a commercial software package. Mirror surface error is modeled by treating each surface as a superposition of various gratings (e.g., diamond turning tool marks, features due to the impurities of Al 6061, and periodic mid-frequency errors due to drift during machining).
This report presents the activities of the GSFC VLBI Analysis Center during 2004. The GSFC Analysis Center analyzes all IVS sessions, makes regular IVS submissions of data and analysis products, and performs research and software development activities aimed at improving the VLBI technique.
This geologic mapping project supports a topical study of structures in east Thaumasia associated with the Coprates rise. The study examines cuesta-like features on the east flank of the Coprates rise first identified by Saunders et al. [1]. Mapping combines detailed local stratigraphy, structural geology and topography. Hogbacks and cuestas indicate erosion of tilted rock units. The extent of the erosion will be determined in the course of the mapping. The region of interest lies along the eastern margin of Thaumasia bounded by latitudes -15 and -35 and longitudes 50 to 70 W (Figure 1). Three MTM geologic quadrangles are being compiled for publication by the USGS (-20057, -25057, -30057). All existing data sources are used including THEMIS, MOC, CTX, HiRISE, MOLA and gravity, as well as higher level data available through the PDS data nodes at ASU, UA and Washington University. The extremely valuable ASU JMARS tools are used for analysis of many of the data sets. ArcGIS software has been obtained and is being learned for the map compilation.
Astronauts experience changes in multiple physiological systems due to exposure to the microgravity conditions of space flight. To understand how changes in physiological function influence functional performance, a testing procedure has been developed that evaluates both astronaut postflight functional performance and related physiological changes. Astronauts complete seven functional and physiological tests. The objective of this project is to use motion tracking and digitizing software to visually display the postflight decrement in the functional performance of the astronauts. The motion analysis software will be used to digitize astronaut data videos into stick figure videos to represent the astronauts as they perform the Functional Tasks Tests. This project will benefit NASA by allowing NASA scientists to present data of their neurological studies without revealing the identities of the astronauts.
Flight Operations Analysis Tool (FLOAT) is a computer program that partly automates the process of assessing the benefits of planning spacecraft missions to incorporate various combinations of launch vehicles and payloads. Designed primarily for use by an experienced systems engineer, FLOAT makes it possible to perform a preliminary analysis of trade-offs and costs of a proposed mission in days, whereas previously, such an analysis typically lasted months. FLOAT surveys a variety of prior missions by querying data from authoritative NASA sources pertaining to 20 to 30 mission and interface parameters that define space missions. FLOAT provides automated, flexible means for comparing the parameters to determine compatibility or the lack thereof among payloads, spacecraft, and launch vehicles, and for displaying the results of such comparisons. Sparseness, typical of the data available for analysis, does not confound this software. FLOAT effects an iterative process that identifies modifications of parameters that could render compatible an otherwise incompatible mission set.
Satellite-based laser technology has been developed for topographical measurements of the Earth and of other planets. Lasers for such missions must be highly efficient and stable over long periods in the temperature variations of orbit. In this innovation, LabVIEW is used on an Apple Macintosh to acquire and analyze images of the laser beam as it exits the laser cavity to evaluate the laser s performance over time, and to monitor and control the environmental conditions under which the laser is tested. One computer attached to multiple cameras and instruments running LabVIEW-based software replaces a conglomeration of computers and software packages, saving hours in maintenance and data analysis, and making very longterm tests possible. This all-in-one system was written primarily using LabVIEW for Mac OS X, which allows the combining of data from multiple RS-232, USB, and Ethernet instruments for comprehensive laser analysis and control. The system acquires data from CCDs (charge coupled devices), power meters, thermistors, and oscilloscopes over a controllable period of time. This data is saved to an html file that can be accessed later from a variety of data analysis programs. Also, through the LabVIEW interface, engineers can easily control laser input parameters such as current, pulse width, chiller temperature, and repetition rates. All of these parameters can be adapted and cycled over a period of time.
This report presents the activities of the GSFC VLBI Analysis Center during 2012. The GSFC VLBI Analysis Center analyzes all IVS sessions, makes regular IVS submissions of data and analysis products, and performs research and software development aimed at improving the VLBI technique.
Asian elephants (Elephas maximus) are a flagship species essential for the functioning of forest ecosystems, and they also have cultural significance in Bhutan. Elephants receive the highest legal protection as listed under Schedule I of the Bhutan Forests and Nature Conservation Act, 1995. Yet, they face threats of extinction due to poaching for ivory as well as the loss and fragmentation of their habitat. Due to the recent clearing of forests and the growing populations in these areas, there has been an increase in incidents of human-elephant conflict. These conflicts have been detrimental to farmer’s annual harvests and livelihoods and have led to retaliatory killing and injury of elephants in southern Bhutan. The DEVELOP Southern Bhutan Ecological Forecasting team partnered with the Bhutan Foundation and Bhutan Tiger Center to help address this problem. The team integrated NASA Earth observations, including Landsat 5 Thematic Mapper (TM), Landsat 8 Operational Land Imager (OLI), Terra Moderate Resolution Imaging Spectroradiometer (MODIS), and the Shuttle Radar Topography Mission (SRTM) to acquire information on land cover change and elephant habitat suitability along the southern border of Bhutan. The team utilized Esri ArcGIS Pro and Software for Assisted Habitat Modeling (SAHM) for data analysis, modeling, and visualization. The team used elephant occurrence data and environmental variables to model current habitat suitability for migrating elephant populations. This analysis provided partners with maps to inform decisions about the placement and conservation of elephant corridors and helped build their capacity to use satellite data for future studies and project planning.
Asian elephants (Elephas maximus) are a flagship species essential for the functioning of forest ecosystems, and they also have cultural significance in Bhutan. Elephants receive the highest legal protection as listed under Schedule I of the Bhutan Forests and Nature Conservation Act, 1995. Yet, they face threats of extinction due to poaching for ivory as well as the loss and fragmentation of their habitat. Due to the recent clearing of forests and the growing populations in these areas, there has been an increase in incidents of human-elephant conflict. These conflicts have been detrimental to farmer’s annual harvests and livelihoods and have led to retaliatory killing and injury of elephants in southern Bhutan. The DEVELOP Southern Bhutan Ecological Forecasting team partnered with the Bhutan Foundation and Bhutan Tiger Center to help address this problem. The team integrated NASA Earth observations, including Landsat 5 Thematic Mapper (TM), Landsat 8 Operational Land Imager (OLI), Terra Moderate Resolution Imaging Spectroradiometer (MODIS), and the Shuttle Radar Topography Mission (SRTM) to acquire information on land cover change and elephant habitat suitability along the southern border of Bhutan. The team utilized Esri ArcGIS Pro and Software for Assisted Habitat Modeling (SAHM) for data analysis, modeling, and visualization. The team used elephant occurrence data and environmental variables to model current habitat suitability for migrating elephant populations. This analysis provided partners with maps to inform decisions about the placement and conservation of elephant corridors and helped build their capacity to use satellite data for future studies and project planning.
The data analysis tool of choice for many Sun-Earth Connection missions is the Interactive Data Language (IDL) by ITT VIS. The increasing amount of data produced by these missions and the increasing complexity of image processing algorithms requires access to higher computing power. Parallel computing is a cost-effective way to increase the speed of computation, but algorithms oftentimes have to be modified to take advantage of parallel systems. Enhancing IDL to work on clusters gives scientists access to increased performance in a familiar programming environment. The goal of this project was to enable IDL applications to benefit from both computing clusters as well as graphics processing units (GPUs) for accelerating data analysis tasks. The tool suite developed in this project enables scientists now to solve demanding data analysis problems in IDL that previously required specialized software, and it allows them to be solved orders of magnitude faster than on conventional PCs. The tool suite consists of three components: (1) TaskDL, a software tool that simplifies the creation and management of task farms, collections of tasks that can be processed independently and require only small amounts of data communication; (2) mpiDL, a tool that allows IDL developers to use the Message Passing Interface (MPI) inside IDL for problems that require large amounts of data to be exchanged among multiple processors; and (3) GPULib, a tool that simplifies the use of GPUs as mathematical coprocessors from within IDL. mpiDL is unique in its support for the full MPI standard and its support of a broad range of MPI implementations. GPULib is unique in enabling users to take advantage of an inexpensive piece of hardware, possibly already installed in their computer, and achieve orders of magnitude faster execution time for numerically complex algorithms. TaskDL enables the simple setup and management of task farms on compute clusters. The products developed in this project have the potential to interact, so one can build a cluster of PCs, each equipped with a GPU, and use mpiDL to communicate between the nodes and GPULib to accelerate the computations on each node.
ABSTRACT We introduce a new software package for modelling the point spread function (PSF) of astronomical images, called piff (PSFs In the Full FOV), which we apply to the first three years (known as Y3) of the Dark Energy Survey (DES) data. We describe the relevant details about the algorithms used by piff to model the PSF, including how the PSF model varies across the field of view (FOV). Diagnostic results show that the systematic errors from the PSF modelling are very small over the range of scales that are important for the DES Y3 weak lensing analysis. In particular, the systematic errors from the PSF modelling are significantly smaller than the corresponding results from the DES year one (Y1) analysis. We also briefly describe some planned improvements to piff that we expect to further reduce the modelling errors in future analyses.
The Used Nuclear Fuel-Storage, Transportation & Disposal Analysis Resource and Data System (UNF-ST&DARDS) is a software tool that integrates a used nuclear fuel (UNF) or spent nuclear fuel (SNF) relational database and key analysis capabilities to simplify and automate numerous UNF management and fuel cycle–related activities. UNF-ST&DARDS is being developed for the US Department of Energy’s Office of Nuclear Energy Spent Fuel and Waste Disposition program. UNF-ST&DARDS provides an integrated framework that uses advanced modeling and simulation to predict the behavior of SNF over the timescales associated with permanent disposal in a geologic repository. After leaving the spent fuel pool, SNF is transferred to dry storage in a dual-purpose canister (DPC). DPCs are considered “dual purpose” because they are designed for both storage and transportation, removing the need to transfer the fuel to a separate transportation cask. However, much research has been conducted investigating the feasibility of directly disposing of DPCs in geologic repositories. Direct disposal of DPCs could reduce worker exposure during repackaging, reducing the amount of low-level waste from the discarded DPCs and potentially saving billions of dollars. Therefore, direct disposal of as-loaded DPCs is desirable if it can be done safely.
During the analysis of flight data and safety reports done in ASAP and FOQA programs, airline personnel are not able to access relevant aviation data for a variety of reasons. We have developed the Aviation Data Integration System (ADIS), a software system that provides integrated heterogeneous data to support safety analysis. Types of data available in ADIS include weather, D-ATIS, RVR, radar data, and Jeppesen charts, and flight data. We developed three versions of ADIS to support airlines. The first version has been developed to support ASAP teams. A second version supports FOQA teams, and it integrates aviation data with flight data while keeping identification information inaccessible. Finally, we developed a prototype that demonstrates the integration of aviation data into flight data analysis programs. The initial feedback from airlines is that ADIS is very useful in FOQA and ASAP analysis.
The analysis of large and complex parameterized software systems, e.g., systems simulation in aerospace, is very complicated and time-consuming due to the large parameter space, and the complex, highly coupled nonlinear nature of the different system components. Thus, such systems are generally validated only in regions local to anticipated operating points rather than through characterization of the entire feasible operational envelope of the system. We have addressed the factors deterring such an analysis with a tool to support envelope assessment: we utilize a combination of advanced Monte Carlo generation with n-factor combinatorial parameter variations to limit the number of cases, but still explore important interactions in the parameter space in a systematic fashion. Additional test-cases, automatically generated from models (e.g., UML, Simulink, Stateflow) improve the coverage. The distributed test runs of the software system produce vast amounts of data, making manual analysis impossible. Our tool automatically analyzes the generated data through a combination of unsupervised Bayesian clustering techniques (AutoBayes) and supervised learning of critical parameter ranges using the treatment learner TAR3. The tool has been developed around the Trick simulation environment, which is widely used within NASA. We will present this tool with a GN&C (Guidance, Navigation and Control) simulation of a small satellite system.