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At least 1,153 records · Page 64

Implementation of Parallel Computing Technology to Vortex Flow

Mainframe supercomputers such as the Cray C90 was invaluable in obtaining large scale computations using several millions of grid points to resolve salient features of a tip vortex flow over a lifting wing. However, real flight configurations require tracking not only of the flow over several lifting wings but its growth and decay in the near- and intermediate- wake regions, not to mention the interaction of these vortices with each other. Resolving and tracking the evolution and interaction of these vortices shed from complex bodies is computationally intensive. Parallel computing technology is an attractive option in solving these flows. In planetary science vortical flows are also important in studying how planets and protoplanets form when cosmic dust and gases become gravitationally unstable and eventually form planets or protoplanets. The current paradigm for the formation of planetary systems maintains that the planets accreted from the nebula of gas and dust left over from the formation of the Sun. Traditional theory also indicate that such a preplanetary nebula took the form of flattened disk. The coagulation of dust led to the settling of aggregates toward the midplane of the disk, where they grew further into asteroid-like planetesimals. Some of the issues still remaining in this process are the onset of gravitational instability, the role of turbulence in the damping of particles and radial effects. In this study the focus will be with the role of turbulence and the radial effects.

Dacles-Mariani, Jennifer↗

Technology for a NASA Space-Based Science Operations Grid

This viewgraph representation presents an overview of a proposal to develop a space-based operations grid in support of space-based science experiments. The development of such a grid would provide a dynamic, secure and scalable architecture based on standards and next-generation reusable software and would enable greater science collaboration and productivity through the use of shared resources and distributed computing. The authors propose developing this concept for use on payload experiments carried aboard the International Space Station. Topics covered include: grid definitions, portals, grid development and coordination, grid technology and potential uses of such a grid.

Bradford, Robert N.↗

The Application of Jason-1 Measurements to Estimate the Global Near Surface Ocean Circulation for Climate Research

The scientific objective of this research program was to utilize drifter, Jason-1 altimeter data and a variety of wind data for the determination of time mean and time variable wind driven surface currents of the global ocean. To accomplish this task has required the interpolation of 6-hourly winds on drifter tracks and the computation of the wind coherent motions of the drifters. These calculations showed that the Ekman current model proposed by Ralph and Niiler for the tropical Pacific was valid for all the oceans south of 40N latitude. Improvements to RN99 model were computed and poster presentations of the results were given in several ocean science venues, including the November 2004 GODAY meeting in St. Petersburg, FL.

Niiler, Peran P.↗

NASA Center for Climate Simulation (NCCS) Presentation

The NASA Center for Climate Simulation (NCCS) offers integrated supercomputing, visualization, and data interaction technologies to enhance NASA's weather and climate prediction capabilities. It serves hundreds of users at NASA Goddard Space Flight Center, as well as other NASA centers, laboratories, and universities across the US. Over the past year, NCCS has continued expanding its data-centric computing environment to meet the increasingly data-intensive challenges of climate science. We doubled our Discover supercomputer's peak performance to more than 800 teraflops by adding 7,680 Intel Xeon Sandy Bridge processor-cores and most recently 240 Intel Xeon Phi Many Integrated Core (MIG) co-processors. A supercomputing-class analysis system named Dali gives users rapid access to their data on Discover and high-performance software including the Ultra-scale Visualization Climate Data Analysis Tools (UV-CDAT), with interfaces from user desktops and a 17- by 6-foot visualization wall. NCCS also is exploring highly efficient climate data services and management with a new MapReduce/Hadoop cluster while augmenting its data distribution to the science community. Using NCCS resources, NASA completed its modeling contributions to the Intergovernmental Panel on Climate Change (IPCG) Fifth Assessment Report this summer as part of the ongoing Coupled Modellntercomparison Project Phase 5 (CMIP5). Ensembles of simulations run on Discover reached back to the year 1000 to test model accuracy and projected climate change through the year 2300 based on four different scenarios of greenhouse gases, aerosols, and land use. The data resulting from several thousand IPCC/CMIP5 simulations, as well as a variety of other simulation, reanalysis, and observationdatasets, are available to scientists and decision makers through an enhanced NCCS Earth System Grid Federation Gateway. Worldwide downloads have totaled over 110 terabytes of data.

Webster, William P.↗

The Kepler Data Processing Handbook: A Field Guide to Prospecting for Habitable Worlds

The Kepler telescope hurtled into orbit in March 2009, initiating NASA's first mission to discover Earth-size planets orbiting Sun-like stars. Kepler simultaneously collected data for approximately 165,000 target stars at a time over its four-year mission, identifying over 4700 planet candidates, over 2300 confirmed or validated planets, and over 2100 eclipsing binaries. While Kepler was designed to discover exoplanets, the long-term, ultrahigh photometric precision measurements it achieved made it a premier observational facility for stellar astrophysics, especially in the field of asteroseismology, and for variable stars, such as RR Lyrae. The Kepler Science Operations Center (SOC) was developed at NASA Ames Research Center to process the data acquired by Kepler from pixel-level calibrations all the way to identifying transiting planet signatures and subjecting them to a suite of diagnostic tests to establish or break confidence in their planetary nature. Detecting small, rocky planets transiting Sun-like stars presents a variety of daunting challenges, including achieving an unprecedented photometric precision of ~20 ppm on 6.5-hour timescales, and supporting the science operations, management, processing, and repeated reprocessing of the accumulating data stream. A newly revised and expanded version of the Kepler Data Processing Handbook (KDPH) has been released to support the legacy archival products. The KDPH details the theory, design and performance of the algorithms supporting each data processing step. This paper presents an overview of the KDPH and features illustrations of several key algorithms in the Kepler Science Data Processing Pipeline. Kepler was selected as the 10th mission of the Discovery Program. Funding for this mission is provided by NASA, Science Mission Directorate.

high performance computing↗

Predictive Modeling of Carbon Ablators Using Micro and Macro-Scale Modeling

Efforts to build a Predictive Material Modeling (PMM) framework from the micro-scale to the macro-scale are presented in this abstract. To reduce the need for extensive testing, accelerate the design cycle process, and reduce uncertainty margins applied to final designs, NASA is developing simulation and modeling tools that enable characterization of material properties and response to high-enthalpy environments. The Porous Microstructure Analysis (PuMA) code has been developed for computing macroscale (volume averaged) properties of porous materials using microscale images from micro-computed tomography (micro-CT). Microscale modeling requires a realistic representation of a material microstructure; these are obtained either synthetically during the design of the material or through X-ray micro-CT. Volume averaged properties are then used to inform macroscale material response models, such as those implemented in the Porous-material Analysis Toolbox based on OpenFOAM (PATO) software, also actively developed by NASA. The computational model in PATO is a generic heat and mass transfer model for porous reactive materials containing several solid phases and a single gas phase. The detailed chemical interactions occurring between the solid phases and the gas phase are modeled at the pore scale assuming local thermal equilibrium. These tools were developed to efficiently interface with other pre-existing codes such as SPARTA (direct simulation Monte Carlo), DPLR (hypersonic CFD), NEQAIR (radiative transport) and DAKOTA (uncertainty quantification and optimization). Detailed flight data (Mars Science Laboratory [MSL] Entry Descent and Landing Instrument [MEDLI]) is critical for validating these computational tools for NASA applications. Examples of modeling ablative material response using these codes will be presented including 3D simulations of the full-scale heatshield of the MSL capsule. The simulations demonstrate the ability of the modern material response code, PATO, to handle the material response of geometrically complex and large domains, through the use of massively parallel computations.

Thermal Protection Systems↗

Enabling Space Biological Knowledge Discovery Through Image and Video Data Sharing

Increased biomedical risks and challenges associated with deep space missions and experiments (cis-Lunar, Mars transit/surface) require new knowledge discovery and development of novel ecosystems. Supporting distant and long-duration missions and experiments requires biological data (from yeast, microbes, fruit flies, C. elegans, plants, crops, rodents, humans) be findable, accessible, interoperable, reusable (FAIR), and maximally open-access. As data-intensive, bioinformatic, meta-analytical, and computer-assisted approaches continue to be a centerpiece of modern research, the NASA Biological and Physical Sciences division is expanding its Open Science capabilities beyond NASA GeneLab. The NASA Ames Life Sciences Data Archive (ALSDA) is a repository which is responsible for collecting and access to space biological imagery and video, alongside tabular and environmental data. In this presentation, we will discuss strategies dealing with archiving, curating, and accessibility of images from very distinct imaging modalities (e.g., micro-computed tomography, magnetic resonance imaging, photographic images of plants, fluorescence microscopy, behavioral videos, etc.). There are two main challenges: 1. Open-source data storage and 2. Metadata related to the imagery-video. Both have been solved by leveraging two existing open-source systems. For data storage, ALSDA is utilizing components through the Open Microscopy Environment (OME), which can read most imaging proprietary formats and display on a web interface complex multidimensional images (Z stack, multi-channel, temporal, spectral). Most technical metadata from imaging modalities are captured seamlessly. For metadata capturing experimental details, ALSDA (like GeneLab) uses the ISA-Tab specification which relies on the ISA data model to order and classify metadata. The ISA data model uses a tree structure with three files to capture the metadata: The top layer is the Investigations file, the second layer is the Study file(s), and the last layer is the Assay file(s). We believe such an approach may be useful for other types of image research data from other investigators in the AGU community.

imaging↗

Experimental and Computational Analysis of Unidirectional Flow Through Stirling Engine Heater Head

A high efficiency Stirling Radioisotope Generator (SRG) is being developed for possible use in long-duration space science missions. NASA s advanced technology goals for next generation Stirling convertors include increasing the Carnot efficiency and percent of Carnot efficiency. To help achieve these goals, a multi-dimensional Computational Fluid Dynamics (CFD) code is being developed to numerically model unsteady fluid flow and heat transfer phenomena of the oscillating working gas inside Stirling convertors. In the absence of transient pressure drop data for the zero mean oscillating multi-dimensional flows present in the Technology Demonstration Convertors on test at NASA Glenn Research Center, unidirectional flow pressure drop test data is used to compare against 2D and 3D computational solutions. This study focuses on tracking pressure drop and mass flow rate data for unidirectional flow though a Stirling heater head using a commercial CFD code (CFD-ACE). The commercial CFD code uses a porous-media model which is dependent on permeability and the inertial coefficient present in the linear and nonlinear terms of the Darcy-Forchheimer equation. Permeability and inertial coefficient were calculated from unidirectional flow test data. CFD simulations of the unidirectional flow test were validated using the porous-media model input parameters which increased simulation accuracy by 14 percent on average.

Wilson, Scott D.↗

Telescience Testbed Program: A study of software for SIRTF instrument control

As a continued element in the Telescience Testbed Program (TTP), the University of Arizona Steward Observatory and the Electrical and Computer Engineering Department (ECE) jointly developed a testbed to evaluate the Operations and Science Instrument System (OASIS) software package for remote control of an instrument for the Space Infrared Telescope Facility (SIRTF). SIRTF is a cryogenically-cooled telescope with three focal plane instruments that will be the infrared element of NASA's Great Observatory series. The anticipated launch date for SIRTF is currently 2001. Because of the complexity of the SIRTF mission, it was not expected that the OASIS package would be suitable for instrument control in the flight situation, however, its possible use as a common interface during the early development and ground test phases of the project was considered. The OASIS package, developed at the University of Colorado for control of the Solar Mesosphere Explorer (SME) satellite, serves as an interface between the operator and the remote instrument which is connected via a network. OASIS provides a rudimentary windowing system as well as support for standard spacecraft communications protocols. The experiment performed all of the functions required of the MIPS simulation program. Remote control of the instrument was demonstrated but found to be inappropriate for SIRTF at this time for the following reasons: (1) programming interface is too difficult; (2) significant computer resources were required to run OASIS; (3) the communications interface is too complicated; (4) response time was slow; and (5) quicklook of image data was not possible.

Young, Erick T.↗

Polyphony: A Workflow Orchestration Framework for Cloud Computing

Cloud Computing has delivered unprecedented compute capacity to NASA missions at affordable rates. Missions like the Mars Exploration Rovers (MER) and Mars Science Lab (MSL) are enjoying the elasticity that enables them to leverage hundreds, if not thousands, or machines for short durations without making any hardware procurements. In this paper, we describe Polyphony, a resilient, scalable, and modular framework that efficiently leverages a large set of computing resources to perform parallel computations. Polyphony can employ resources on the cloud, excess capacity on local machines, as well as spare resources on the supercomputing center, and it enables these resources to work in concert to accomplish a common goal. Polyphony is resilient to node failures, even if they occur in the middle of a transaction. We will conclude with an evaluation of a production-ready application built on top of Polyphony to perform image-processing operations of images from around the solar system, including Mars, Saturn, and Titan.

Space Exploration,↗

Atomistic Method Applied to Computational Modeling of Surface Alloys

The formation of surface alloys is a growing research field that, in terms of the surface structure of multicomponent systems, defines the frontier both for experimental and theoretical techniques. Because of the impact that the formation of surface alloys has on surface properties, researchers need reliable methods to predict new surface alloys and to help interpret unknown structures. The structure of surface alloys and when, and even if, they form are largely unpredictable from the known properties of the participating elements. No unified theory or model to date can infer surface alloy structures from the constituents properties or their bulk alloy characteristics. In spite of these severe limitations, a growing catalogue of such systems has been developed during the last decade, and only recently are global theories being advanced to fully understand the phenomenon. None of the methods used in other areas of surface science can properly model even the already known cases. Aware of these limitations, the Computational Materials Group at the NASA Glenn Research Center at Lewis Field has developed a useful, computationally economical, and physically sound methodology to enable the systematic study of surface alloy formation in metals. This tool has been tested successfully on several known systems for which hard experimental evidence exists and has been used to predict ternary surface alloy formation (results to be published: Garces, J.E.; Bozzolo, G.; and Mosca, H.: Atomistic Modeling of Pd/Cu(100) Surface Alloy Formation. Surf. Sci., 2000 (in press); Mosca, H.; Garces J.E.; and Bozzolo, G.: Surface Ternary Alloys of (Cu,Au)/Ni(110). (Accepted for publication in Surf. Sci., 2000.); and Garces, J.E.; Bozzolo, G.; Mosca, H.; and Abel, P.: A New Approach for Atomistic Modeling of Pd/Cu(110) Surface Alloy Formation. (Submitted to Appl. Surf. Sci.)). Ternary alloy formation is a field yet to be fully explored experimentally. The computational tool, which is based on the BFS (Bozzolo, Ferrante, and Smith) method for the calculation of the energetics, consists of a small number of simple PCbased computer codes that deal with the different aspects of surface alloy formation. Two analysis modes are available within this package. The first mode provides an atom-by-atom description of real and virtual stages 1. during the process of surface alloying, based on the construction of catalogues of configurations where each configuration describes one possible atomic distribution. BFS analysis of this catalogue provides information on accessible states, possible ordering patterns, and details of island formation or film growth. More importantly, it provides insight into the evolution of the system. Software developed by the Computational Materials Group allows for the study of an arbitrary number of elements forming surface alloys, including an arbitrary number of surface atomic layers. The second mode involves large-scale temperature-dependent computer 2. simulations that use the BFS method for the energetics and provide information on the dynamic processes during surface alloying. These simulations require the implementation of Monte-Carlo-based codes with high efficiency within current workstation environments. This methodology capitalizes on the advantages of the BFS method: there are no restrictions on the number or type of elements or on the type of crystallographic structure considered. This removes any restrictions in the definition of the configuration catalogues used in the analytical calculations, thus allowing for the study of arbitrary ordering patterns, ultimately leading to the actual surface alloy structure. Moreover, the Monte Carlo numerical technique used for the large-scale simulations allows for a detailed visualization of the simulated process, the main advantage of this type of analysis being the ability to understand the underlying features that drive these processes. Because of the simplicity of the BFS method for e energetics used in these calculations, a detailed atom-by-atom analysis can be performed at any point in the simulation, providing necessary insight on the details of the process. The main objective of this research program is to develop a tool to guide experimenters in understanding and interpreting often unexpected results in alloy formation experiments. By reducing the computational effort without losing physical accuracy, we expect that powerful simulation tools will be developed in the immediate future, which will allow material scientists to easily visualize and analyze processes at a level not achievable experimentally.

Bozzolo, Guillermo H.↗

Comparison of remotely sensed continental-shelf wave spectra with spectra computed by using a wave refraction computer model

An initial attempt was made to verify the Langley Research Center and Virginia Institute of Marine Science mid-Atlantic continental-shelf wave refraction model. The model was used to simulate refraction occurring during a continental-shelf remote sensing experiment conducted on August 17, 1973. Simulated wave spectra compared favorably, in a qualitative sense, with the experimental spectra. However, it was observed that most of the wave energy resided at frequencies higher than those for which refraction and shoaling effects were predicted, In addition, variations among the experimental spectra were so small that they were not considered statistically significant. In order to verify the refraction model, simulation must be performed in conjunction with a set of significantly varying spectra in which a considerable portion of the total energy resides at frequencies for which refraction and shoaling effects are likely.

Poole, L. R.↗

Building a Transdisciplinary, Exascale-Capable Workforce for Geospace Science

Key Points: ●First-principles, self-consistent geospace modeling will require at least exascale-level computing capabilities; however, the technical skills necessary to develop such simulation codes are not taught as part of Heliophysics training/PhD programs. ●Developing exascale Heliophysics codes will require transdisciplinary collaborations between physicists, computer scientists, software engineers, data scientists, and applied mathematics. Such teams must be persistent and formed around specific skills, not specific problems. ●We must have stable, positive long-term career outcomes for Heliophysics scientific developers in order to retain knowledge of and promote future innovation in scientific algorithm development and advanced computing techniques. One such way to do this is by funding long-term scientific programming groups, akin to Heliophysics DRIVE Centers. ●We must have a balance between promoting innovation via funding short-term closed-source development and allowing the open-source community to benefit from and build on the newest scientific modeling techniques.

C Bard↗

High Resolution Nature Runs and the Big Data Challenge

NASA's Global Modeling and Assimilation Office at Goddard Space Flight Center is undertaking a series of very computationally intensive Nature Runs and a downscaled reanalysis. The nature runs use the GEOS-5 as an Atmospheric General Circulation Model (AGCM) while the reanalysis uses the GEOS-5 in Data Assimilation mode. This paper will present computational challenges from three runs, two of which are AGCM and one is downscaled reanalysis using the full DAS. The nature runs will be completed at two surface grid resolutions, 7 and 3 kilometers and 72 vertical levels. The 7 km run spanned 2 years (2005-2006) and produced 4 PB of data while the 3 km run will span one year and generate 4 BP of data. The downscaled reanalysis (MERRA-II Modern-Era Reanalysis for Research and Applications) will cover 15 years and generate 1 PB of data. Our efforts to address the big data challenges of climate science, we are moving toward a notion of Climate Analytics-as-a-Service (CAaaS), a specialization of the concept of business process-as-a-service that is an evolving extension of IaaS, PaaS, and SaaS enabled by cloud computing. In this presentation, we will describe two projects that demonstrate this shift. MERRA Analytic Services (MERRA/AS) is an example of cloud-enabled CAaaS. MERRA/AS enables MapReduce analytics over MERRA reanalysis data collection by bringing together the high-performance computing, scalable data management, and a domain-specific climate data services API. NASA's High-Performance Science Cloud (HPSC) is an example of the type of compute-storage fabric required to support CAaaS. The HPSC comprises a high speed Infinib and network, high performance file systems and object storage, and a virtual system environments specific for data intensive, science applications. These technologies are providing a new tier in the data and analytic services stack that helps connect earthbound, enterprise-level data and computational resources to new customers and new mobility-driven applications and modes of work. In our experience, CAaaS lowers the barriers and risk to organizational change, fosters innovation and experimentation, and provides the agility required to meet our customers' increasing and changing needs

big data analysis↗

The ISES: A non-intrusive medium for in-space experiments in on-board information extraction

The Information Science Experiment System (ISES) represents a new approach in applying advanced systems technology and techniques to on-board information extraction in the space environment. Basically, what is proposed is a 'black box' attached to the spacecraft data bus or local area network. To the spacecraft the 'black box' appears to be just another payload requiring power, heat rejection, interfaces, adding weight, and requiring time on the data management and communication system. In reality, the 'black box' is a programmable computational resource which eavesdrops on the data network, taking and producing selectable, real-time science data back on the network. This paper will present a brief overview of the ISES Concept and will discuss issues related to applying the ISES to the polar platform and Space Station Freedom. Critical to the operation of ISES is the viability of a payload-like interface to the spacecraft data bus or local area network. Study results that address this question will be reviewed vis-a-vis the solar platform and the core space station. Also, initial results of processing science and other requirements for onboard, real-time information extraction will be presented with particular emphasis on the polar platform. Opportunities for a broader range of applications on the core space station will also be discussed.

Murray, Nicholas D.↗

Feeding People's Curiosity: Leveraging the Cloud for Automatic Dissemination of Mars Images

Smartphones and tablets have made wireless computing ubiquitous, and users expect instant, on-demand access to information. The Mars Science Laboratory (MSL) operations software suite, MSL InterfaCE (MSLICE), employs a different back-end image processing architecture compared to that of the Mars Exploration Rovers (MER) in order to better satisfy modern consumer-driven usage patterns and to offer greater server-side flexibility. Cloud services are a centerpiece of the server-side architecture that allows new image data to be delivered automatically to both scientists using MSLICE and the general public through the MSL website (http://mars.jpl.nasa.gov/msl/).

Cloud Computing↗

Center for Advanced Computational Technology

The Center for Advanced Computational Technology (ACT) was established to serve as a focal point for diverse research activities pertaining to application of advanced computational technology to future aerospace systems. These activities include the use of numerical simulations, artificial intelligence methods, multimedia and synthetic environments, and computational intelligence, in the modeling, analysis, sensitivity studies, optimization, design and operation of future aerospace systems. The Center is located at NASA Langley and is an integral part of the School of Engineering and Applied Science of the University of Virginia. The Center has four specific objectives: 1) conduct innovative research on applications of advanced computational technology to aerospace systems; 2) act as pathfinder by demonstrating to the research community what can be done (high-potential, high-risk research); 3) help in identifying future directions of research in support of the aeronautical and space missions of the twenty-first century; and 4) help in the rapid transfer of research results to industry and in broadening awareness among researchers and engineers of the state-of-the-art in applications of advanced computational technology to the analysis, design prototyping and operations of aerospace and other high-performance engineering systems. In addition to research, Center activities include helping in the planning and coordination of the activities of a multi-center team of NASA and JPL researchers who are developing an intelligent synthesis environment for future aerospace systems; organizing workshops and national symposia; as well as writing state-of-the-art monographs and NASA special publications on timely topics.

Noor, Ahmed K.↗