NEVADA NATIONAL SECURITY SITE – DEVICE ASSEMBLY FACILITY ENHANCED STAGING AND HANDLING OF RADIOACTIVE MATERIAL PACKAGES: Paper NO. 397
Explore the source record for details and available documents.
SEARCH · Engineering Papers
Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.
Quote a phrase for an exact phrase match. Source license links do not imply unrestricted reuse.
Explore the source record for details and available documents.
The reduction of $121.6 million dollars from NOAA's LANDSAT development program for FY 1982, and the shortened time period for transferring remote sensing technology to the private sector resulted in changes in the Agency's plans for managing the operational system. Proposed legislation for congressional consideration or enactment to establish conditions under which this private sector transfer will occur, and the expected gradual rise in the price of data products are discussed. No money exists for capital investment and none is projected for investing in an operational data handling system for the LANDSAT D satellite. Candidates knowledgeable of various aspects of the needs and uses of remote sensing are urged to consider participation in NOAA's advisory committee.
Robot coordination and control systems for remote teleoperation applications are by necessity implemented on distributed computers. Modeling and performance analysis of these distributed robotic systems is difficult, but important for economic system design. Performance analysis methods originally developed for conventional distributed computer systems are often unsatisfactory for evaluating real-time systems. The paper introduces a formal model of distributed robotic control systems; and a performance analysis method, based on scheduling theory, which can handle concurrent hard-real-time response specifications. Use of the method is illustrated by a case of remote teleoperation which assesses the effect of communication delays and the allocation of robot control functions on control system hardware requirements.
The Instrument Simulator Suite for Atmospheric Remote Sensing (ISSARS) entered its third and final year of development with an overall goal of providing a unified tool to simulate active and passive space borne atmospheric remote sensing instruments. These simulations focus on the atmosphere ranging from UV to microwaves. ISSARS handles all assumptions and uses various models on scattering and microphysics to fill the gaps left unspecified by the atmospheric models to create each instrument's measurements. This will help benefit mission design and reduce mission cost, create efficient implementation of multi-instrument/platform Observing System Simulation Experiments (OSSE), and improve existing models as well as new advanced models in development. In this effort, various aerosol particles are incorporated into the system, and a simulation of input wavelength and spectral refractive indices related to each spherical test particle(s) generate its scattering properties and phase functions. These atmospheric particles being integrated into the system comprise the ones observed by the Multi-angle Imaging SpectroRadiometer(MISR) and by the Multiangle SpectroPolarimetric Imager(MSPI). In addition, a complex scattering database generated by Prof. Ping Yang (Texas A&M) is also incorporated into this aerosol database. Future development with a radiative transfer code will generate a series of results that can be validated with results obtained by the MISR and MSPI instruments; nevertheless, test cases are simulated to determine the validity of various plugin libraries used to determine or gather the scattering properties of particles studied by MISR and MSPI, or within the Single-scattering properties of tri-axial ellipsoidal mineral dust particles database created by Prof. Ping Yang.
The increase in neutron flux at the Oak Ridge National Laboratory (ORNL) Spallation Neutron Source (SNS), currently operating at 2.0 MW proton beam power, has created new opportunities for higher-throughput neutron scattering experiments while also increasing the importance of minimizing background scattering and optimizing sample-environment operations. To address these challenges on the Backscattering Silicon Spectrometer (BA-SIS), several upgrades were developed and evaluated, including boron carbide (B₄C) masking for flat-plate sample containers, multi-cell sample holders used with a vertically translating sample stick, and an automated helium pump and purge (HPP) system for closed-cycle refrigerators. Neutron diffraction measurements demonstrate that B₄C masks reduce background scattering by 49–67%, outperforming both borated aluminum and boron nitride masks while introducing no additional Bragg reflections within the instrument’s accessible Q-range. Commissioning tests of a double-cell flat-plate sample contain-er showed no measurable crosstalk between adjacent sample compartments and con-firmed stable thermal performance, enabling multiple samples to be measured without re-peated temperature cycling. In addition, the automated HPP system provided reproducible sample-space gas handling with approximately ±1 mbar precision while reducing the need for operator intervention and supporting remote operation. Together, these developments improve signal-to-noise performance, increase experimental throughput, and enhance operational efficiency at BASIS, supporting the instrument’s continued operation under higher neutron flux conditions.
The data handling and processing in using synthetic aperture radar as a satellite-borne earth resources remote sensor is considered. The discussion covers the nature of the problem, the theory, both conventional and potential advanced processing techniques, and a complete computer simulation. It is shown that digital processing is a real possibility and suggests some future directions for research.
The NESSUS and NASTRAN computer codes were successfully integrated. The enhanced NESSUS code will use NASTRAN for the structural Analysis and NESSUS for the probabilistic analysis. Any quantities in the NASTRAN bulk data input can be random variables. Any NASTRAN result that is written to the output2 file can be returned to NESSUS as the finite element result. The interfacing between NESSUS and NASTRAN is handled automatically by NESSUS. NESSUS and NASTRAN can be run on different machines using the remote host option.
The rapid increase in digital remote sensing and GIS data raises a critical problem -- how can such an enormous amount of data be handled and analyzed so that useful information can be derived quickly? Efficient handling and analysis of large spatial data sets is central to environmental research, particularly in global change studies that employ time series. Advances in large-scale environmental monitoring and modeling require not only high-quality data, but also reliable tools to analyze the various types of data. A major difficulty facing geographers and environmental scientists in environmental assessment and monitoring is that spatial analytical tools are not easily accessible. Although many spatial techniques have been described recently in the literature, they are typically presented in an analytical form and are difficult to transform to a numerical algorithm. Moreover, these spatial techniques are not necessarily designed for remote sensing and GIS applications, and research must be conducted to examine their applicability and effectiveness in different types of environmental applications. This poses a chicken-and-egg problem: on one hand we need more research to examine the usability of the newer techniques and tools, yet on the other hand, this type of research is difficult to conduct if the tools to be explored are not accessible. Another problem that is fundamental to environmental research are issues related to spatial scale. The scale issue is especially acute in the context of global change studies because of the need to integrate remote-sensing and other spatial data that are collected at different scales and resolutions. Extrapolation of results across broad spatial scales remains the most difficult problem in global environmental research. There is a need for basic characterization of the effects of scale on image data, and the techniques used to measure these effects must be developed and implemented to allow for a multiple scale assessment of the data before any useful process-oriented modeling involving scale-dependent data can be conducted. Through the support of research grants from NASA, we have developed a software module called ICAMS (Image Characterization And Modeling System) to address the need to develop innovative spatial techniques and make them available to the broader scientific communities. ICAMS provides new spatial techniques, such as fractal analysis, geostatistical functions, and multiscale analysis that are not easily available in commercial GIS/image processing software. By bundling newer spatial methods in a user-friendly software module, researchers can begin to test and experiment with the new spatial analysis methods and they can gauge scale effects using a variety of remote sensing imagery. In the following, we describe briefly the development of ICAMS and present application examples.
The University of Utah, Department of Geography has developed a research and instructional program in satellite remote sensing and image processing. The University requested funds for the purchase of software licenses, mass storage for massive hyperspectral imager data sets, upgrades for the central data server to handle the additional storage capacity, a spectroradiometer for field data collection. These purchases have been made. This equipment will support research in one of the newest and most rapidly expanding areas of remote sensing.
Topics include: Ka-Band TWT High-Efficiency Power Combiner for High-Rate Data Transmission; Reusable, Extensible High-Level Data-Distribution Concept; Processing Satellite Imagery To Detect Waste Tire Piles; Monitoring by Use of Clusters of Sensor-Data Vectors; Circuit and Method for Communication Over DC Power Line; Switched Band-Pass Filters for Adaptive Transceivers; Noncoherent DTTLs for Symbol Synchronization; High-Voltage Power Supply With Fast Rise and Fall Times; Waveguide Calibrator for Multi-Element Probe Calibration; Four-Way Ka-Band Power Combiner; Loss-of-Control-Inhibitor Systems for Aircraft; Improved Underwater Excitation-Emission Matrix Fluorometer; Metrology Camera System Using Two-Color Interferometry; Design and Fabrication of High-Efficiency CMOS/CCD Imagers; Foam Core Shielding for Spacecraft CHEM-Based Self-Deploying Planetary Storage Tanks Sequestration of Single-Walled Carbon Nanotubes in a Polymer PPC750 Performance Monitor Application-Program-Installer Builder Using Visual Odometry to Estimate Position and Attitude Design and Data Management System Simple, Script-Based Science Processing Archive Automated Rocket Propulsion Test Management Online Remote Sensing Interface Fusing Image Data for Calculating Position of an Object Implementation of a Point Algorithm for Real-Time Convex Optimization Handling Input and Output for COAMPS Modeling and Grid Generation of Iced Airfoils Automated Identification of Nucleotide Sequences Balloon Design Software Rocket Science 101 Interactive Educational Program Creep Forming of Carbon-Reinforced Ceramic-Matrix Composites Dog-Bone Horns for Piezoelectric Ultrasonic/Sonic Actuators Benchtop Detection of Proteins Recombinant Collagenlike Proteins Remote Sensing of Parasitic Nematodes in Plants Direct Coupling From WGM Resonator Disks to Photodetectors Using Digital Radiography To Image Liquid Nitrogen in Voids Multiple-Parameter, Low-False-Alarm Fire-Detection Systems Mosaic-Detector-Based Fluorescence Spectral Imager Plasmoid Thruster for High Specific-Impulse Propulsion Analysis Method for Quantifying Vehicle Design Goals Improved Tracking of Targets by Cameras on a Mars Rover Sample Caching Subsystem Multistage Passive Cooler for Spaceborne Instruments GVIPS Models and Software Stowable Energy-Absorbing Rocker-Bogie Suspensions
Description of a breadboard configuration of an advanced information management system based on requirements for high data rates and local and centralized computation for subsystems and experiments to be housed on a space station. The system is to contain a 10-megabit-per-second digital data bus, remote terminals with preprocessor capabilities, and a central multiprocessor. A concept definition is presented for the data acquisition and control system breadboard, and a detailed account is given of the operation of the bus control unit, the bus itself, and the remote acquisition and control unit. The data bus control unit is capable of operating under control of both its own test panel and the test processor. In either mode it is capable of both single- and multiple-message operation in that it can accept a block of data requests or update commands for transmission to the remote acquisition and control unit, which in turn is capable of three levels of data-handling complexity.
The Atmosphere Explorer Spacecraft incorporates an orbiting aeronomy laboratory designed to operate in the lower thermosphere. A three-axis stabilized platform capable of operating over a wide range of orbital altitudes, inclinations, solar aspect angles, and spin rates satisfies the science requirements for instrument orientation. An on-board propulsion subsystem allows operations at low-perigee altitudes without severe limitation of orbital lifetime. Programmable high-speed digital command and data handling, together with power supplied by solar cells and batteries, allows the spacecraft to be operated remotely in daylight or darkness. This configuration of spacecraft support subsystems fulfills the requirements for the various phases of the scientific mission.
The objectives, conclusions, and approaches for accomplishing 19 specific design and analysis activities related to the installation of the power extension package (PEP) into the Orbiter cargo bay are described as well as those related to its deployment, extension, and retraction. The proposed cable handling system designed to transmit power from PEP to the Orbiter by way of the shuttle remote manipulator system is described and a preliminary specification for the gimbal assembly, solar array drive is included.
This viewgraph presentation reviews the partnership between NASA and the Caterpillar Corporation. Through the Innovative Partnerships Program (IPP) NASA is providing leveraged technology for projects that are new initiatives that enhance NASA's ability to meet mission technology goals by providing seed funding to initiate cost-shared, joint-development partnerships. This relationship will assist NASA in the development of lunar In Situ resource utilization (ISRU) and surface handling equipment control and hardware requirements and the human-system interaction processes for time delayed remote operations.
Great advances have been made in our understanding of the climate system over the past few decades, and remotely sensed data have played a key role in supporting many of these advances. Improvements in satellites and in computational and data-handling techniques have yielded high quality, readily accessible data. However, rapid increases in data volume have also led to large and complex datasets that pose significant challenges in data analysis (NRC, 2007). Uncertainty characterization is needed for every satellite mission and scientists continue to be challenged by the need to reduce the uncertainty in remotely sensed climate records and projections. The approaches currently used to quantify the uncertainty in remotely sensed data, including statistical methods used to calibrate and validate satellite instruments, lack an overall mathematically based framework.
The constellation of Earth-observing satellites continuously collects measurements of scattered radiance, which must be transformed into geophysical parameters in order to answer fundamental scientific questions about the Earth. Retrieval of these parameters requires highly flexible, accurate, and fast forward and inverse radiative transfer models. Existing forward models used by the remote sensing community are typically accurate and fast, but sacrifice flexibility by assuming the atmosphere or ocean is composed of plane-parallel layers. Monte Carlo forward models can handle more complex scenarios such as 3D spatial heterogeneity, but are relatively slower. We propose looking to the computer graphics community for inspiration to improve the statistical efficiency of Monte Carlo forward models and explore new approaches to inverse models for remote sensing. In Part 2 of this work, we demonstrate that Monte Carlo forward models in computer graphics are capable of sufficient accuracy for remote sensing by extending Mitsuba 3, a forward and inverse modeling framework recently developed in the computer graphics community, to simulate simple atmosphere-ocean systems and show that our framework is capable of achieving error on par with codes currently used by the remote sensing community on benchmark results.
The constellation of Earth-observing satellites continuously collects measurements of scattered radiance, which must be transformed into geophysical parameters in order to answer fundamental scientific questions about the Earth. Retrieval of these parameters requires highly flexible, accurate, and fast forward and inverse radiative transfer models. Existing forward models used by the remote sensing community are typically accurate and fast, but sacrifice flexibility by assuming the atmosphere or ocean is composed of plane-parallel layers. Monte Carlo forward models can handle more complex scenarios such as 3D spatial heterogeneity, but are relatively slower. We propose looking to the computer graphics community for inspiration to improve the statistical efficiency of Monte Carlo forward models and explore new approaches to inverse models for remote sensing. In Part 1 of this work, we examine the evolution of radiative transfer models in computer graphics and highlight recent advancements that have the potential to push forward models in remote sensing beyond their current periphery of realism.
The Gamma Ray Experiment (GRE) is one of the seven instruments on the Solar Maximum Mission. The scientific objective of the GRE is to study solar gamma ray emissions expected during, and, according to some solar models, prior to solar flares. The instrument consists of a detector assembly and a remote electronic assembly. The latter includes redundant low-voltage power supplies and the remaining command, data handling, and ancillary electronic subsystems of the instrument. The electronic systems and subsystems of the instrument are described in some detail.