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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.

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At least 379 records · Page 21

Emission Line Galaxies in the STIS Parallel Survey II: Star Formation Density

We present the luminosity function of [OII]-emitting galaxies at a median redshift of z = 0.9, as measured in the deep spectroscopic data in the STIS Parallel Survey (SPS). The luminosity function shows strong evolution from the local value, as expected. By using random lines of sight, the SPS measurement complements previous deep single field studies. We calculate the density of inferred star formation at this redshift by converting from [OII] to H(alpha) line flux as a function of absolute magnitude and find rho = 0.052 +/- 0.017 Solar mass/yr Mpc(sup -3) at a median redshift z approx. 0.9 within the range 0.46 less than z less than 1.415 (H(sub 0) = 50 km/s Mpc(sup -l), Omega(sub M) = 1.0, Omega(sub lambda) = 0.0). This density is consistent with a (1 + z)(sup )4 evolution in global star formation since z approx. 1. To reconcile the density with similar measurements made by surveys targeting H(alpha) may require substantial extinction correction.

Teplitz, Harry I.↗

Experimental Studies of the Interaction Between a Parallel Shear Flow and a Directionally-Solidifying Front

It has long been recognized that flow in the melt can have a profound influence on the dynamics of a solidifying interface and hence the quality of the solid material. In particular, flow affects the heat and mass transfer, and causes spatial and temporal variations in the flow and melt composition. This results in a crystal with nonuniform physical properties. Flow can be generated by buoyancy, expansion or contraction upon phase change, and thermo-soluto capillary effects. In general, these flows can not be avoided and can have an adverse effect on the stability of the crystal structures. This motivates crystal growth experiments in a microgravity environment, where buoyancy-driven convection is significantly suppressed. However, transient accelerations (g-jitter) caused by the acceleration of the spacecraft can affect the melt, while convection generated from the effects other than buoyancy remain important. Rather than bemoan the presence of convection as a source of interfacial instability, Hurle in the 1960s suggested that flow in the melt, either forced or natural convection, might be used to stabilize the interface. Delves considered the imposition of both a parabolic velocity profile and a Blasius boundary layer flow over the interface. He concluded that fast stirring could stabilize the interface to perturbations whose wave vector is in the direction of the fluid velocity. Forth and Wheeler considered the effect of the asymptotic suction boundary layer profile. They showed that the effect of the shear flow was to generate travelling waves parallel to the flow with a speed proportional to the Reynolds number. There have been few quantitative, experimental works reporting on the coupling effect of fluid flow and morphological instabilities. Huang studied plane Couette flow over cells and dendrites. It was found that this flow could greatly enhance the planar stability and even induce the cell-planar transition. A rotating impeller was buried inside the sample cell, driven by an outside rotating magnet, in order to generate the flow. However, it appears that this was not a well-controlled flow and may also have been unsteady. In the present experimental study, we want to study how a forced parallel shear flow in a Hele-Shaw cell interacts with the directionally solidifying crystal interface. The comparison of experimental data show that the parallel shear flow in a Hele-Shaw cell has a strong stabilizing effect on the planar interface by damping the existing initial perturbations. The flow also shows a stabilizing effect on the cellular interface by slightly reducing the exponential growth rate of cells. The left-right symmetry of cells is broken by the flow with cells tilting toward the incoming flow direction. The tilting angle increases with the velocity ratio. The experimental results are explained through the parallel flow effect on lateral solute transport. The phenomenon of cells tilting against the flow is consistent with the numerical result of Dantzig and Chao.

Zhang, Meng↗

GeneLab: A Systems Biology Platform for Spaceflight Omics Data

NASA's mission includes expanding our understanding of biological systems to improve life on Earth and to enable long-duration human exploration of space. Resources to support large numbers of spaceflight investigations are limited. NASA's GeneLab project is maximizing the science output from these experiments by: (1) developing a unique public bioinformatics database that includes space bioscience relevant "omics" data (genomics, transcriptomics, proteomics, and metabolomics) and experimental metadata; (2) partnering with NASA-funded flight experiments through bio-sample sharing or sample augmentation to expedite omics data input to the GeneLab database; and (3) developing community-driven reference flight experiments. The first database, GeneLab Data System Version 1.0, went online in April 2015. V1.0 contains numerous flight datasets and has search and download capabilities. Version 2.0 will be released in 2016 and will link to analytic tools. In 2015 Genelab partnered with two Biological Research in Canisters experiments (BBRIC-19 and BRIC-20) which examine responses of Arabidopsis thaliana to spaceflight. GeneLab also partnered with Rodent Research-1 (RR1), the maiden flight to test the newly developed rodent habitat. GeneLab developed protocols for maxiumum yield of RNA, DNA and protein from precious RR-1 tissues harvested and preserved during the SpaceX-4 mission, as well as from tissues from mice that were frozen intact during spaceflight and later dissected. GeneLab is establishing partnerships with at least three planned flights for 2016. Organism-specific nationwide Science Definition Teams (SDTs) will define future GeneLab dedicated missions and ensure the broader scientific impact of the GeneLab missions. GeneLab ensures prompt release and open access to all high-throughput omics data from spaceflight and ground-based simulations of microgravity and radiation. Overall, GeneLab will facilitate the generation and query of parallel multi-omics data, and deep curation of metadata for integrative analysis, allowing researchers to uncover cellular networks as observed in systems biology platforms. Consequently, the scientific community will have access to a more complete picture of functional and regulatory networks responsive to the spaceflight environment.. Analysis of GeneLab data will contribute fundamental knowledge of how the space environment affects biological systems, and enable emerging terrestrial benefits resulting from mitigation strategies to prevent effects observed during exposure to space. As a result, open access to the data will foster new hypothesis-driven research for future spaceflight studies spanning basic science to translational science.

proteomics↗

The PARTY parallel runtime system

In the present automated system for the organization of the data and computational operations entailed by parallel problems, in ways that optimize multiprocessor performance, general heuristics for partitioning program data and control are implemented by capturing and manipulating representations of a computation at run time. These heuristics are directed toward the dynamic identification and allocation of concurrent work in computations with irregular computational patterns. An optimized static-workload partitioning is computed for such repetitive-computation pattern problems as the iterative ones employed in scientific computation.

Saltz, J. H.↗

Toward NASA/GMAO Coupled Data Assimilation Using JEDI

NASA’s Global Modeling and Assimilation Office (GMAO) is establishing coupled Earth system capabilities using the Joint Effort for Data Assimilation Integration (JEDI) framework, developed in collaboration with the Joint Center for Satellite Data Assimilation(JCSDA). Marine and atmospheric components will utilize a weakly-coupled data assimilation approach. The implementation of the sea-ice, ocean, and coupled analysis (SOCA) component of JEDI is highlighted here, while parallel work on atmospheric data assimilation is also in progress. Improvements to the ocean data assimilation system (ODAS) include: 1) adopting the JEDI framework, 2) a new coupled GCM, and 3) incorporation of new observation sources.

Dorukhan Ardağ↗

Mechanism of parallel electric fields inferred from observations

Data from various experiments of the Atmosphere Explorer satellites are analyzed to test their consistency with the model of single-particle linear acceleration through a static parallel potential drop. Theoretical current/voltage and energy flux/voltage relations are applied to the data to predict the densities of source current carriers above the acceleration region for upward Birkeland currents. Comparison of these model predictions with simultaneous electron data indicates that the observed field-aligned potential drops are consistent with direct acceleration in the absence of anomalous resistivity.

Yeh, H.-C.↗

Multiwavelength monolithic integrated fiber-optic terminal

The paper presents the Multiwavelength Monolithic Integrated Fiber Optic Terminal (MMIFOT) developed under NASA sponsorship. The program aims to utilize the advantage of optical fiber and integrated optical device technology to achieve parallel transmission of many data channels over the same optical fiber link, and to develop an eight channel wavelength multiplexed fiber optic link that transmits eight bit words in a parallel format at a nominal rate of 20 Mw/s; in the second phase of the program a transmitter/multiplexer chip will be developed. The MMIFOT configuration, the receiver/demultiplexer development, and the waveguide detector development are discussed, concluding that the first phase of the MMIFOT program will culminate in the demonstration of an eight channel receiver/demultiplexer chip with a four channel breadboard multiplexer with the data rate of 20 Mbps per channel with a dynamic range of minimum 20 dB.

Rice, R. R.↗

Mentat: An object-oriented macro data flow system

Mentat, an object-oriented macro data flow system designed to facilitate parallelism in distributed systems, is presented. The macro data flow model is a model of computation similar to the data flow model with two principal differences: the computational complexity of the actors is much greater than in traditional data flow systems, and there are persistent actors that maintain state information between executions. Mentat is a system that combines the object-oriented programming paradigm and the macro data flow model of computation. Mentat programs use a dynamic structure called a future list to represent the future of computations.

Grimshaw, Andrew S.↗

Computer-Aided Engineering Of Cabling

Program generates data sheets, drawings, and other information on electrical connections. DFACS program, centered around single data base, has built-in menus providing easy input of, and access to, data for all personnel involved in system, subsystem, and cabling. Enables parallel design of circuit-data sheets and drawings of harnesses. Also recombines raw information to generate automatically various project documents and drawings, including index of circuit-data sheets, list of electrical-interface circuits, lists of assemblies and equipment, cabling trees, and drawings of cabling electrical interfaces and harnesses. Purpose of program to provide engineering community with centralized data base for putting in, and gaining access to, functional definition of system as specified in terms of details of pin connections of end circuits of subsystems and instruments and data on harnessing. Primary objective to provide instantaneous single point of interchange of information, thus avoiding

Billitti, Joseph W.↗

GOES-R Geostationary Lightning Mapper Performance Specifications and Algorithms

The Geostationary Lightning Mapper (GLM) is a single channel, near-IR imager/optical transient event detector, used to detect, locate and measure total lightning activity over the full-disk. The next generation NOAA Geostationary Operational Environmental Satellite (GOES-R) series will carry a GLM that will provide continuous day and night observations of lightning. The mission objectives for the GLM are to: (1) Provide continuous, full-disk lightning measurements for storm warning and nowcasting, (2) Provide early warning of tornadic activity, and (2) Accumulate a long-term database to track decadal changes of lightning. The GLM owes its heritage to the NASA Lightning Imaging Sensor (1997- present) and the Optical Transient Detector (1995-2000), which were developed for the Earth Observing System and have produced a combined 13 year data record of global lightning activity. GOES-R Risk Reduction Team and Algorithm Working Group Lightning Applications Team have begun to develop the Level 2 algorithms and applications. The science data will consist of lightning "events", "groups", and "flashes". The algorithm is being designed to be an efficient user of the computational resources. This may include parallelization of the code and the concept of sub-dividing the GLM FOV into regions to be processed in parallel. Proxy total lightning data from the NASA Lightning Imaging Sensor on the Tropical Rainfall Measuring Mission (TRMM) satellite and regional test beds (e.g., Lightning Mapping Arrays in North Alabama, Oklahoma, Central Florida, and the Washington DC Metropolitan area) are being used to develop the prelaunch algorithms and applications, and also improve our knowledge of thunderstorm initiation and evolution.

Mach, Douglas M.↗

Multimission modular spacecraft parallel battery tests

Acceptance test data included: voltage profiles; pressure increase or decrease; and response of the third electrode cell. A softening of the voltage profile was revealed, as well as a lowering of the discharge profile and a 10 percent loss of capacity over a 0 to 20 C temperature range.

Tasevoli, M.↗

Semi-automatic process partitioning for parallel computation

On current multiprocessor architectures one must carefully distribute data in memory in order to achieve high performance. Process partitioning is the operation of rewriting an algorithm as a collection of tasks, each operating primarily on its own portion of the data, to carry out the computation in parallel. A semi-automatic approach to process partitioning is considered in which the compiler, guided by advice from the user, automatically transforms programs into such an interacting task system. This approach is illustrated with a picture processing example written in BLAZE, which is transformed into a task system maximizing locality of memory reference.

Koelbel, Charles↗

MERRA/AS: The MERRA Analytic Services Project Interim Report

MERRA AS is a cyberinfrastructure resource that will combine iRODS-based Climate Data Server (CDS) capabilities with Coudera MapReduce to serve MERRA analytic products, store the MERRA reanalysis data collection in an HDFS to enable parallel, high-performance, storage-side data reductions, manage storage-side driver, mapper, reducer code sets and realized objects for users, and provide a library of commonly used spatiotemporal operations that can be composed to enable higher-order analyses.

MapReduce↗

The question of the possibility of using Associative Computer Devices (ACD) for parallel adaptive discretization of multichannel telemetry information

The method of parallel adaptive discretization of data is considered the most promising and allows the effective compression algorithms to be used for high information-capacity radio telemetry systems. An associative computer device (ACD), i.e., parallel computers based on associative memory units (AMU), are recommended for realization of this method. A detailed discussion of the problems of application of AMU is followed by description of a particular ACD and its recommended use.

Kantor, A. V.↗

The ParaScope parallel programming environment

The ParaScope parallel programming environment, developed to support scientific programming of shared-memory multiprocessors, includes a collection of tools that use global program analysis to help users develop and debug parallel programs. This paper focuses on ParaScope's compilation system, its parallel program editor, and its parallel debugging system. The compilation system extends the traditional single-procedure compiler by providing a mechanism for managing the compilation of complete programs. Thus, ParaScope can support both traditional single-procedure optimization and optimization across procedure boundaries. The ParaScope editor brings both compiler analysis and user expertise to bear on program parallelization. It assists the knowledgeable user by displaying and managing analysis and by providing a variety of interactive program transformations that are effective in exposing parallelism. The debugging system detects and reports timing-dependent errors, called data races, in execution of parallel programs. The system combines static analysis, program instrumentation, and run-time reporting to provide a mechanical system for isolating errors in parallel program executions. Finally, we describe a new project to extend ParaScope to support programming in FORTRAN D, a machine-independent parallel programming language intended for use with both distributed-memory and shared-memory parallel computers.

Cooper, Keith D.↗

A high speed buffer for LV data acquisition

The laser velocimeter (autocovariance) buffer interface is a data acquisition subsystem designed specifically for the acquisition of data from a laser velocimeter. The subsystem acquires data from up to six laser velocimeter components in parallel, measures the times between successive data points for each of the components, establishes and maintains a coincident condition between any two or three components, and acquires data from other instrumentation systems simultaneously with the laser velocimeter data points. The subsystem is designed to control the entire data acquisition process based on initial setup parameters obtained from a host computer and to be independent of the computer during the acquisition. On completion of the acquisition cycle, the interface transfers the contents of its memory to the host under direction of the host via a single 16-bit parallel DMA channel.

Cavone, Angelo A.↗

GMI-IPS: Python Processing Software for Aircraft Campaigns

NASA's Atmospheric Tomography Mission (ATom) seeks to understand the impact of anthropogenic air pollution on gases in the Earth's atmosphere. Four flight campaigns are being deployed on a seasonal basis to establish a continuous global-scale data set intended to improve the representation of chemically reactive gases in global atmospheric chemistry models. The Global Modeling Initiative (GMI), is creating chemical transport simulations on a global scale for each of the ATom flight campaigns. To meet the computational demands required to translate the GMI simulation data to grids associated with the flights from the ATom campaigns, the GMI ICARTT Processing Software (GMI-IPS) has been developed and is providing key functionality for data processing and analysis in this ongoing effort. The GMI-IPS is written in Python and provides computational kernels for data interpolation and visualization tasks on GMI simulation data. A key feature of the GMI-IPS, is its ability to read ICARTT files, a text-based file format for airborne instrument data, and extract the required flight information that defines regional and temporal grid parameters associated with an ATom flight. Perhaps most importantly, the GMI-IPS creates ICARTT files containing GMI simulated data, which are used in collaboration with ATom instrument teams and other modeling groups. The initial main task of the GMI-IPS is to interpolate GMI model data to the finer temporal resolution (1-10 seconds) of a given flight. The model data includes basic fields such as temperature and pressure, but the main focus of this effort is to provide species concentrations of chemical gases for ATom flights. The software, which uses parallel computation techniques for data intensive tasks, linearly interpolates each of the model fields to the time resolution of the flight. The temporally interpolated data is then saved to disk, and is used to create additional derived quantities. In order to translate the GMI model data to the spatial grid of the flight path as defined by the pressure, latitude, and longitude points at each flight time record, a weighted average is then calculated from the nearest neighbors in two dimensions (latitude, longitude). Using SciPya's Regular Grid Interpolator, interpolation functions are generated for the GMI model grid and the calculated weighted averages. The flight path points are then extracted from the ATom ICARTT instrument file, and are sent to the multi-dimensional interpolating functions to generate GMI field quantities along the spatial path of the flight. The interpolated field quantities are then written to a ICARTT data file, which is stored for further manipulation. The GMI-IPS is aware of a generic ATom ICARTT header format, containing basic information for all flight campaigns. The GMI-IPS includes logic to edit metadata for the derived field quantities, as well as modify the generic header data such as processing dates and associated instrument files. The ICARTT interpolated data is then appended to the modified header data, and the ICARTT processing is complete for the given flight and ready for collaboration. The output ICARTT data adheres to the ICARTT file format standards V1.1. The visualization component of the GMI-IPS uses Matplotlib extensively and has several functions ranging in complexity. First, it creates a model background curtain for the flight (time versus model eta levels) with the interpolated flight data superimposed on the curtain. Secondly, it creates a time-series plot of the interpolated flight data. Lastly, the visualization component creates averaged 2D model slices (longitude versus latitude) with overlaid flight track circles at key pressure levels. The GMI-IPS consists of a handful of classes and supporting functionality that have been generalized to be compatible with any ICARTT file that adheres to the base class definition. The base class represents a generic ICARTT entry, only defining a single time entry and 3D spatial positioning parameters. Other classes inherit from this base class; several classes for input ICARTT instrument files, which contain the necessary flight positioning information as a basis for data processing, as well as other classes for output ICARTT files, which contain the interpolated model data. Utility classes provide functionality for routine procedures such as: comparing field names among ICARTT files, reading ICARTT entries from a data file and storing them in data structures, and returning a reduced spatial grid based on a collection of ICARTT entries. Although the GMI-IPS is compatible with GMI model data, it can be adapted with reasonable effort for any simulation that creates Hierarchical Data Format (HDF) files. The same can be said of its adaptability to ICARTT files outside of the context of the ATom mission. The GMI-IPS contains just under 30,000 lines of code, eight classes, and a dozen drivers and utility programs. It is maintained with GIT source code management and has been used to deliver processed GMI model data for the ATom campaigns that have taken place to date.

Damon, M. R.↗