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Forward Cleaner PCS Pre-refurb AHJ Eval Notes and EXAMPLE IO List REV 0
The color ORANGE shall be used to identify ungrounded conductors that remain energized when the main supply circuit disconnecting means is in the off position. This color identification shall be strictly reserved for this application only.
Design review of PCS-G condenser, P/N 268340-1, redesigned from P/N 093043
Mercury and NaK inlet and outlet port, condenser, and attachment design modifications of power conversion system for SNAP 8
PCS-G systems analysis
Digital computer simulation of SNAP 8 power conversion system G startup and shutdown for systems analysis
Design review of the Bare Refractory Double-Containment (BRDC) boiler number 5 for PCS, SNAP-8
Bare refractory double containment boiler for SNAP 8 power conversion system utilizing mercury, tantalum, zirconium, and type 300 stainless steel materials
Mechanical evaluation of TAA 5/4 after 10,823 hours of operation in PCS-1
Evaluation of SNAP 8 turbine alternator assembly after 19,283 hours of operation
PCS-1 testing, March - May 1970
Development, characteristics, and performance tests of turbine alternator assembly system and component parts
PCIPS 2.0: Powerful multiprofile image processing implemented on PCs
Over the years, the processing power of personal computers has steadily increased. Now, 386- and 486-based PC's are fast enough for many image processing applications, and inexpensive enough even for amateur astronomers. PCIPS is an image processing system based on these platforms that was designed to satisfy a broad range of data analysis needs, while requiring minimum hardware and providing maximum expandability. It will run (albeit at a slow pace) even on a 80286 with 640K memory, but will take full advantage of bigger memory and faster CPU's. Because the actual image processing is performed by external modules, the system can be easily upgraded by the user for all sorts of scientific data analysis. PCIPS supports large format lD and 2D images in any numeric type from 8-bit integer to 64-bit floating point. The images can be displayed, overlaid, printed and any part of the data examined via an intuitive graphical user interface that employs buttons, pop-up menus, and a mouse. PCIPS automatically converts images between different types and sizes to satisfy the requirements of various applications. PCIPS features an API that lets users develop custom applications in C or FORTRAN. While doing so, a programmer can concentrate on the actual data processing, because PCIPS assumes responsibility for accessing images and interacting with the user. This also ensures that all applications, even custom ones, have a consistent and user-friendly interface. The API is compatible with factory programming, a metaphor for constructing image processing procedures that will be implemented in future versions of the system. Several application packages were created under PCIPS. The basic package includes elementary arithmetics and statistics, geometric transformations and import/export in various formats (FITS, binary, ASCII, and GIF). The CCD processing package and the spectral analysis package were successfully used to reduce spectra from the Nordic Telescope at La Palma. A photometry package is also available, and other packages are being developed. A multitasking version of PCIPS that utilizes the factory programming concept is currently under development. This version will remain compatible (on the source code level) with existing application packages and custom applications.
Optically derived elevation angle dependence of fading for satellite PCS
Images of urban Japan taken vertically through a 180 deg fisheye lens were analyzed to derive, as a function of elevation the fraction of sky that is clear, shadowed by trees, or blocked by buildings. At 32 deg elevation, results match those derived from satellite measurements fit to a 3-state fade model. Using the same model, for the first time the elevation angle dependence of mobile satellite fading is predicted.
Into building fading at L- and S-band for satellite PCS
Selected results from L- and S-Band slant-path fade measurements into six different buildings employing a tower-mounted transmitter and dual-frequency receiver are presented. The objective of the measurements was to provide information for personal communications satellite design on the correlation of fading inside buildings between frequencies near 1620 and 2500 MHz. Fades were measured along horizontal directions with 5 cm spacing. Fade differences between L- and S-Band exhibited a normal distribution with means usually near 0 dB and standard deviations from 7.2 to 8.2 dB. After spatial averaging over a few wavelengths, the correlation between L- and S-Band was significantly improved. Simultaneous swept measurements over 160 MHz spans showed that the standard deviation of the power levels as function of frequency increased linearly with average fade depth from a minimum of about 1.3 dB and increased by .2 dB per 1 dB of fade. Fade slopes were also a function of fade level, with LMSS-Band averages in the range of 1 to 2 dB/MHz for 10 dB fades and increasing to about 3 to 4 dB/MHz at a 30 dB fade.
Measurement of satellite PCS fading using GPS
A six-channel commercial GPS receiver with a custom-made 40 deg tilted, rotating antenna has been assembled to make fade measurements for personal satellite communications. The system can measure up to two times per minute fades of up to 15 dB in the direction of each tracked satellite from 10 to 90 deg elevation. Photographic fisheye lens images were used to categorize the fade data obtained in several test locations according to fade states of clear, shadowed, or blocked. Multipath effects in the form of annular rings can be observed when most of the sky is clear. Tree fading by a Pecan exceeding 3.5 dB and 12 dB at 50 to 10 percent probability, respectively, compared with median fades of 7.5 dB measured earlier and the discrepancy is attributed to the change in ratio when measuring over an area as opposed to along a line. Data acquired inside buildings revealed 'rf-leaky' ceilings. Satellite diversity gain in a shadowed environment exceeded 6 dB at the 10 percent probability.
Physics of Colloids in Space (PCS) Flight Hardware Developed
investigation that will be located in an Expedite the Process of Experiments to Space Station (EXPRESS) Rack. The investigation will be conducted in the International Space Station U.S. laboratory, Destiny, over a period of approximately 10 months during the station assembly period from flight 6A through flight UF-2. This experiment will gather data on the basic physical properties of colloids by studying three different colloid systems with the objective of understanding how they grow and what structures they form. A colloidal suspension consists of fine particles (micrometer to submicrometer) suspended in a fluid for example, paints, milk, salad dressings, and aerosols. The long-term goal of this investigation is to learn how to steer the growth of colloidal suspensions to create new materials and new structures. This experiment is part of a two-stage investigation conceived by Professor David Weitz of Harvard University along with Professor Peter Pusey of the University of Edinburgh. The experiment hardware was developed by the NASA Glenn Research Center through contracts with Dynacs, Inc., and ZIN Technologies.
Physics of Colloids in Space (PCS): Microgravity Experiment Completed Operations on the International Space Station
Immediately after mixing, the two-phase-like colloid-polymer critical point sample begins to phase separate, or de-mix, into two phases-one that resembles a gas and one that resembles a liquid, except that the particles are colloids and not atoms. The colloid-poor black regions (colloidal gas) grow bigger, and the colloid-rich white regions (colloidal liquid) become whiter as the domains further coarsen. Finally, complete phase separation is achieved, that is, just one region of each colloid-rich (white) and colloid-poor (black) phase. This process was studied over four decades of length scale, from 1 micrometer to 1 centimeter.
Addings PCs to SLC Control System
Explore the source record for details and available documents.
Framework for Integrating Science Data Processing Algorithms Into Process Control Systems
A software framework called PCS Task Wrapper is responsible for standardizing the setup, process initiation, execution, and file management tasks surrounding the execution of science data algorithms, which are referred to by NASA as Product Generation Executives (PGEs). PGEs codify a scientific algorithm, some step in the overall scientific process involved in a mission science workflow. The PCS Task Wrapper provides a stable operating environment to the underlying PGE during its execution lifecycle. If the PGE requires a file, or metadata regarding the file, the PCS Task Wrapper is responsible for delivering that information to the PGE in a manner that meets its requirements. If the PGE requires knowledge of upstream or downstream PGEs in a sequence of executions, that information is also made available. Finally, if information regarding disk space, or node information such as CPU availability, etc., is required, the PCS Task Wrapper provides this information to the underlying PGE. After this information is collected, the PGE is executed, and its output Product file and Metadata generation is managed via the PCS Task Wrapper framework. The innovation is responsible for marshalling output Products and Metadata back to a PCS File Management component for use in downstream data processing and pedigree. In support of this, the PCS Task Wrapper leverages the PCS Crawler Framework to ingest (during pipeline processing) the output Product files and Metadata produced by the PGE. The architectural components of the PCS Task Wrapper framework include PGE Task Instance, PGE Config File Builder, Config File Property Adder, Science PGE Config File Writer, and PCS Met file Writer. This innovative framework is really the unifying bridge between the execution of a step in the overall processing pipeline, and the available PCS component services as well as the information that they collectively manage.
Assimilation of Reconstructed Radiances from IASI Principal Component Scores into the GEOS-ADAS
Hyperspectral Infrared sounders such as IASI, AIRS, and CrIS have long been an integral part of radiance assimilation in numerical weather prediction (NWP), providing vertical profiles of water vapor and temperature information. Principal Component Scores (PCS) are a lossy form of compression that retains most information, such as temperature and moisture, by using a large training set of atmospheric profiles. However, PCS may not well represent profiles which are rare events, such as volcanic eruptions, and drops some sources of random noise. There has been an increased interest in the use of PCS as EUMETSAT plans to distribute future geostationary sounder radiances from MTG-IRS via PCS only. NWP centers use two approaches to deal with PCS: direct assimilation of the PCS by modifying the radiative transfer model to produce PCS and the associated Jacobians, or a simpler approach of decompressing the PCS and reconstructing the radiances back into channel space to allow assimilating radiances without modifications to the data assimilation system. EUMETSAT has developed a PCS product for IASI that has been operational since 2011. We utilize this product opting for the simpler approach, decompressing IASI PCS into channel space, and assimilating those radiances using the GEOS-ADAS. We then compare this with a control using the standard IASI radiance product. Resulting differences in global forecast statistics, differences in Forecast Sensitivity to Observation Impact, along with implications for implementation and quality control are discussed.
Enabling co-simulation of tokamak plant models and plasma control systems
A system for connecting the Plasma Control System and a model of the tokamak Plant in closed loop co-simulation for plasma control development has been in routine use at DIII-D for more than 20 years and at other fusion labs that use variants of the DIII-D PCS for approximately the last decade. Here, co-simulation refers to the simultaneous execution of two independent codes with the exchange of data - Plant actuator commands and tokamak diagnostic data - between them during execution. Interest in this type of PCS-Plant simulation technology has also been growing recently at other fusion facilities. In fact, use of such closed loop control simulations is assumed to play an even larger role in the development of both the ITER Plasma Control System (PCS) and the experimental operation of the ITER device, where they will be used to support verification/validation of the PCS and also for ITER pulse schedule development and validation. We describe the key use cases that motivate the co-simulation capability and the features that must be provided by the Plasma Control System to support it. These features could be provided by the PCS itself or by a model of the PCS. If the PCS itself is chosen to provide them, there are requirements imposed on its architecture. If a PCS model is chosen, there are requirements imposed on the initial implementation of this simulation as well as long-term consequences for its continued development and maintenance. We describe these issues for each use case and discuss the relative merits of the two choices. Several examples are given illustrating uses of the co-simulation method to address problems of plasma control during the operation of DIII-D and of other devices that use the DIII-D PCS.
Veridical data science
Building and expanding on principles of statistics, machine learning, and scientific inquiry, we propose the predictability, computability, and stability (PCS) framework for veridical data science. Our framework, composed of both a workflow and documentation, aims to provide responsible, reliable, reproducible, and transparent results across the data science life cycle. The PCS workflow uses predictability as a reality check and considers the importance of computation in data collection/storage and algorithm design. It augments predictability and computability with an overarching stability principle. Stability expands on statistical uncertainty considerations to assess how human judgment calls impact data results through data and model/algorithm perturbations. As part of the PCS workflow, we develop PCS inference procedures, namely PCS perturbation intervals and PCS hypothesis testing, to investigate the stability of data results relative to problem formulation, data cleaning, modeling decisions, and interpretations. We illustrate PCS inference through neuroscience and genomics projects of our own and others. Moreover, we demonstrate its favorable performance over existing methods in terms of receiver operating characteristic (ROC) curves in high-dimensional, sparse linear model simulations, including a wide range of misspecified models. Finally, we propose PCS documentation based on R Markdown or Jupyter Notebook, with publicly available, reproducible codes and narratives to back up human choices made throughout an analysis. The PCS workflow and documentation are demonstrated in a genomics case study available on Zenodo.