Search NASA⌕ Search

SEARCH · Search NASA

Results for “cluster computing”

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.

At least 235 records · Page 13
All sourcesNASA NTRSDOE OSTI
NASA NTRS1986

Head-on binary collisions in globular clusters

Collision probabilities between identical binaries of three different binding energies are computed for binaries in the cores of globular clusters. The more tightly bound a binary is, the smaller the chance is that it suffers a collision. It is found that a given binary in a globular cluster core probably does not suffer more than a very few collisions. If it is not broken up into single stars, it will become so tightly bound that collisions involving it are very rare. Since it is found that head-on collisions are so rare, the collisions which are probably more important in affecting the evolution of the cluster core are the long-range (large impact parameter) encounters.

Hoffer, James B.↗
NASA NTRS1994

Visualization of unsteady computational fluid dynamics

A brief summary of the computer environment used for calculating three dimensional unsteady Computational Fluid Dynamic (CFD) results is presented. This environment requires a super computer as well as massively parallel processors (MPP's) and clusters of workstations acting as a single MPP (by concurrently working on the same task) provide the required computational bandwidth for CFD calculations of transient problems. The cluster of reduced instruction set computers (RISC) is a recent advent based on the low cost and high performance that workstation vendors provide. The cluster, with the proper software can act as a multiple instruction/multiple data (MIMD) machine. A new set of software tools is being designed specifically to address visualizing 3D unsteady CFD results in these environments. Three user's manuals for the parallel version of Visual3, pV3, revision 1.00 make up the bulk of this report.

Haimes, Robert↗
NASA NTRS1981

Evaluation of SLAR and thematic mapper MSS data for forest cover mapping using computer-aided analysis techniques

Supervised and cluster block training statistics were used to analyze the thematic mapper simulation MSS data (both 1979 and 1980 data sets). Cover information classes identified on SAR imagery include: hardwood, pine, mixed pine hardwood, clearcut, pasture, crops, emergent crops, bare soil, urban, and water. Preliminary analysis of the HH and HV polarized SAR data indicate a high variance associated with each information class except for water and bare soil. The large variance for most spectral classes suggests that while the means might be statistically separable, an overlap may exist between the classes which could introduce a significant classification error. The quantitative values of many cover types are much larger on the HV polarization than on the HH, thereby indicating the relative nature of the digitized data values. The mean values of the spectral classes in the areas with larger look angles are greater than the means of the same cover type in other areas having steeper look angles. Difficulty in accurately overlaying the dual polarization of the SAR data was resolved.

Hoffer, R. M.↗
NASA NTRS2010

Device and method to enhance availability of cluster-based processing systems

An electronic computing device including at least one processing unit that implements a specific fault signal upon experiencing an associated fault, a control unit that generates a specific recovery signal upon receiving the fault signal from the at least one processing unit, and at least one input memory unit. The recovery signal initiates specific recovery processes in the at least one processing unit. The input memory buffers input data signals input to the at least one processing unit that experienced the fault during the recovery period.

Lupia, David J.↗
NASA NTRS2004

The Development of Two Science Investigator-led Processing Systems (SIPS) for NASA's Earth Observation System (EOS)

In 2001, NASA Goddard Space Flight Center's Laboratory for Terrestrial Physics started the construction of a science Investigator-led Processing System (SIPS) for processing data from the Ozone Monitoring Instrument (OMI) which will launch on the Aura platform in mid 2004. The Ozone Monitoring Instrument (OMI) is a contribution of the Netherlands Agency for Aerospace Programs (NIVR) in collaboration with the Finnish Meteorological Institute (FMI) to the Earth Observing System (EOS) Aura mission. It will continue the Total Ozone Monitoring System (TOMS) record for total ozone and other atmospheric parameters related to ozone chemistry and climate. OMI measurements will be highly synergistic with the other instruments on the EOS Aura platform. The LTP previously developed the Moderate Resolution Imaging Spectrometer (MODIS) Data Processing System (MODAPS), which has been in full operations since the launches of the Terra and Aqua spacecrafts in December, 1999 and May, 2002 respectively. During that time, it has continually evolved to better support the needs of the MODIS team. We now run multiple instances of the system managing faster than real time reprocessings of the data as well as continuing forward processing. The new OMI Data Processing System (OMIDAPS) was adapted from the MODAPS. It will ingest raw data from the satellite ground station and process it to produce calibrated, geolocated higher level data products. These data products will be transmitted to the Goddard Distributed Active Archive Center (GDAAC) instance of the Earth Observing System (EOS) Data and Information System (EOSDIS) for long term archive and distribution to the public. The OMIDAPS will also provide data distribution to the OMI Science Team for quality assessment, algorithm improvement, calibration, etc. We have taken advantage of lessons learned from the MODIS experience and software already developed for MODIS. We made some changes in the hardware system organization, database and software to adapt the system for OMI. We replaced the fundamental database system, Sybase, with an Open Source RDBMS called PostgreSQL, and based the entire OMIDAPS on a cluster of Linux based commodity computers rather than the large SGI servers that MODAPS uses. Rather than relying on a central I/O server host, the new system distributes its data archive among multiple server hosts in the cluster. OMI is also customizing the graphical user interfaces and reporting structure to more closely meet the needs of the OMI Science Team. Prior to 2003, simulated OMI data and the science algorithms were not ready for production testing. We initially constructed a prototype system and tested using a 25 year dataset of Total Ozone Mapping Spectrometer (TOMS) and Solar Backscatter Ultraviolet Instrument (SBUV) data. This prototype system provided a platform to support the adaptation of the algorithms for OMI, and provided reprocessing of the historical data aiding in its analysis. In a recent reanalysis of the TOMS data, the OMIDAPS processed 108,000 full orbits of data through 4 processing steps per orbit, producing about 800,000 files (400 GiB) of level 2 and greater data files. More recently we have installed two instances of the OMIDAPS for integration and testing of OM1 science processes as they get delivered from the Science Team. A Test instance of the OMIDAPS has also supported a series of "Interface Confidence Tests" (ICTs) and End-to-End Ground System tests to ensure the launch readiness of the system. This paper will discuss the high-level hardware, software, and database organization of the OMIDAPS and how it builds on the MODAPS heritage system. It will also provide an overview of the testing and implementation of the production OMIDAPS.

Tilmes, Curt↗
NASA NTRS1994

X-ray clusters in a cold dark matter + lambda universe: A direct, large-scale, high-resolution, hydrodynamic simulation

A new, three-dimensional, shock-capturing, hydrodynamic code is utilized to determine the distribution of hot gas in a cold dark matter (CDM) + lambda model universe. Periodic boundary conditions are assumed: a box with size 85/h Mpc, having cell size 0.31/h Mpc, is followed in a simulation with 270(exp 3) = 10(exp 7.3) cells. We adopt omega = 0.45, lambda = 0.55, h identically equal to H/100 km/s/Mpc = 0.6, and then, from the cosmic background explorer (COBE) and light element nucleosynthesis, sigma(sub 8) = 0.77, omega(sub b) = 0.043. We identify the X-ray emitting clusters in the simulation box, compute the luminosity function at several wavelength bands, the temperature function and estimated sizes, as well as the evolution of these quantities with redshift. This open model succeeds in matching local observations of clusters in contrast to the standard omega = 1, CDM model, which fails. It predicts an order of magnitude decline in the number density of bright (h nu = 2-10 keV) clusters from z = 0 to z = 2 in contrast to a slight increase in the number density for standard omega = 1, CDM model. This COBE-normalized CDM + lambda model produces approximately the same number of X-ray clusters having L(sub x) greater than 10(exp 43) erg/s as observed. The background radiation field at 1 keV due to clusters is approximately the observed background which, after correction for numerical effects, again indicates that the model is consistent with observations.

Cen, Renyue↗
NASA NTRS2015

Scattering Properties of Heterogeneous Mineral Particles with Absorbing Inclusions

We analyze the results of numerically exact computer modeling of scattering and absorption properties of randomly oriented poly-disperse heterogeneous particles obtained by placing microscopic absorbing grains randomly on the surfaces of much larger spherical mineral hosts or by imbedding them randomly inside the hosts. These computations are paralleled by those for heterogeneous particles obtained by fully encapsulating fractal-like absorbing clusters in the mineral hosts. All computations are performed using the superposition T-matrix method. In the case of randomly distributed inclusions, the results are compared with the outcome of Lorenz-Mie computations for an external mixture of the mineral hosts and absorbing grains. We conclude that internal aggregation can affect strongly both the integral radiometric and differential scattering characteristics of the heterogeneous particle mixtures.

minerals↗
NASA NTRS2014

Experimental and Theoretical Study of Thermodynamics of the Reaction of Titania and Water at High Temperatures

The transpiration method was used to determine the volatility of titanium dioxide (TiO2) in water vapor-containing environments at temperatures between 1473 and 1673 K. Water contents ranged from 0 to 76 mole % in oxygen or argon carrier gases for 20 to 250 hr exposure times. Results indicate that oxygen is not a key contributor to volatilization and the primary reaction for volatilization in this temperature range is: TiO2(s) + H2O(g) = TiO(OH)2(g). Data were analyzed with both the second and third law methods to extract an enthalpy and entropy of formation. The geometry and vibrational frequencies of TiO(OH)2(g) were computed using B3LYP density functional theory, and the enthalpy of formation was computed using the coupled-cluster singles and doubles method with a perturbative correction for connected triple substitutions [CCSD(T)]. Thermal functions are calculated using both a structure with bent and linear hydroxyl groups. Calculated second and third heats show closer agreement with the linear hydroxyl group, suggesting more experimental and computational spectroscopic and structural work is needed on this system.

equilibrium↗
NASA NTRS2015

Assessing the Amazon Cloud Suitability for CLARREO's Computational Needs

In this document we compare the performance of the Amazon Web Services (AWS), also known as Amazon Cloud, with the CLARREO (Climate Absolute Radiance and Refractivity Observatory) cluster and assess its suitability for computational needs of the CLARREO mission. A benchmark executable to process one month and one year of PARASOL (Polarization and Anistropy of Reflectances for Atmospheric Sciences coupled with Observations from a Lidar) data was used. With the optimal AWS configuration, adequate data-processing times, comparable to the CLARREO cluster, were found. The assessment of alternatives to the CLARREO cluster continues and several options, such as a NASA-based cluster, are being considered.

Goldin, Daniel↗
NASA NTRS1983

Radiative accretion of intracluster gas onto dominant galaxies in poor clusters

An analysis of X-ray images of MKW 4, MKW 3, AMW 4, and AMW 7 indicates that the hot gas in poor clusters is cooling and accreting onto the central, dominant galaxies. The deprojection technique of Fabian et al (1980) is applied to deduce the detailed density and temperature profiles for a wide range of assumed parameters. For each cluster, the mass accretion rates computed vary by less than a factor of 2 over the full range of the assumed parameters. Examinations of the gas and light density profiles, and of the effects of contraction of the gravitational potential, lead to the conclusion that the high gas densities giving rise to cooling flows are not primarily the result of dynamical evolution of the cluster, especially the merger of galaxies to form the dominant galaxy. Instead, the general initial condition of high material density favors both mergers and cooling flows.

Stewart, G. C.↗
NASA NTRS1988

Arcs from gravitational lensing

The proposal made by Paczynski (1987) that the arcs of blue light found recently in two cluster cores are gravitationally lensed elongated images of background galaxies is investigated. It is shown that lenses that are circularly symmetric in projection produce pairs of arcs, in conflict with the observations. However, more realistic asymmetric lenses produce single arcs, which can become as elongated as the observed ones whenever the background galaxy is located on or close to a cusp caustic. Detailed computer simulations of lensing by clusters using a reasonable model of the mass distribution are presented. Elongated and curved lensed images longer than 10 arcsec occur in 12 percent of the simulated clusters. It is concluded that the lensing hypothesis must be taken seriously.

Grossman, Scott A.↗
NASA NTRS2010

Using Agent Base Models to Optimize Large Scale Network for Large System Inventories

The aim of this paper is to use Agent Base Models (ABM) to optimize large scale network handling capabilities for large system inventories and to implement strategies for the purpose of reducing capital expenses. The models used in this paper either use computational algorithms or procedure implementations developed by Matlab to simulate agent based models in a principal programming language and mathematical theory using clusters, these clusters work as a high performance computational performance to run the program in parallel computational. In both cases, a model is defined as compilation of a set of structures and processes assumed to underlie the behavior of a network system.

Shameldin, Ramez Ahmed↗
NASA NTRS2007

Monitoring by Use of Clusters of Sensor-Data Vectors

The inductive monitoring system (IMS) is a system of computer hardware and software for automated monitoring of the performance, operational condition, physical integrity, and other aspects of the health of a complex engineering system (e.g., an industrial process line or a spacecraft). The input to the IMS consists of streams of digitized readings from sensors in the monitored system. The IMS determines the type and amount of any deviation of the monitored system from a nominal or normal ( healthy ) condition on the basis of a comparison between (1) vectors constructed from the incoming sensor data and (2) corresponding vectors in a database of nominal or normal behavior. The term inductive reflects the use of a process reminiscent of traditional mathematical induction to learn about normal operation and build the nominal-condition database. The IMS offers two major advantages over prior computational monitoring systems: The computational burden of the IMS is significantly smaller, and there is no need for abnormal-condition sensor data for training the IMS to recognize abnormal conditions. The figure schematically depicts the relationships among the computational processes effected by the IMS. Training sensor data are gathered during normal operation of the monitored system, detailed computational simulation of operation of the monitored system, or both. The training data are formed into vectors that are used to generate the database. The vectors in the database are clustered into regions that represent normal or nominal operation. Once the database has been generated, the IMS compares the vectors of incoming sensor data with vectors representative of the clusters. The monitored system is deemed to be operating normally or abnormally, depending on whether the vector of incoming sensor data is or is not, respectively, sufficiently close to one of the clusters. For this purpose, a distance between two vectors is calculated by a suitable metric (e.g., Euclidean distance) and "sufficiently close" signifies lying at a distance less than a specified threshold value. It must be emphasized that although the IMS is intended to detect off-nominal or abnormal performance or health, it is not necessarily capable of performing a thorough or detailed diagnosis. Limited diagnostic information may be available under some circumstances. For example, the distance of a vector of incoming sensor data from the nearest cluster could serve as an indication of the severity of a malfunction. The identity of the nearest cluster may be a clue as to the identity of the malfunctioning component or subsystem. It is possible to decrease the IMS computation time by use of a combination of cluster-indexing and -retrieval methods. For example, in one method, the distances between each cluster and two or more reference vectors can be used for the purpose of indexing and retrieval. The clusters are sorted into a list according to these distance values, typically in ascending order of distance. When a set of input data arrives and is to be tested, the data are first arranged as an ordered set (that is, a vector). The distances from the input vector to the reference points are computed. The search of clusters from the list can then be limited to those clusters lying within a certain distance range from the input vector; the computation time is reduced by not searching the clusters at a greater distance.

Iverson, David L.↗
NASA NTRS1994

The luminosity functions of embedded stellar clusters. 1: Method of solution and analytic results

We describe a method for computing the history of the luminosity function in a young cluster still forming within a molecular cloud complex. Our method, which utilizes detailed results from stellar evolution theory, assumes that clusters arise from the continuous collapse of dense cloud cores over a protracted period of time. It is also assumed that stars reaching the main sequence are distributed in mass according to a prescribed initial mass function (IMF). We keep track separately of the contributions to the luminosity function from the populations of protostars, pre-main-sequence stars, and main-sequence stars. We derive expressions for the fractional contribution of these populations to both the total number of stars produced and the total cluster luminosity. In our model, the number of protostars rises quickly at first, but then levels off to a nearly constant value, which it maintains until the dispersal of the cloud complex. The number fraction of protostars always decreases with time. Averaged over the life of the parent cloud, this fraction is typically a few percent. The protostar mass distribution can be expressed as an integral over the IMF.

Fletcher, Andre B.↗
NASA NTRS1992

Accurate ab initio quartic force fields for borane and BeH2

The quartic force fields of BH3 and BeH2 have been computed ab initio using an augmented coupled cluster (CCSD(T)) method and basis sets of spdf and spdfg quality. For BH3, the computed spectroscopic constants are in very good agreement with recent experimental data, and definitively confirm misassignments in some older work, in agreement with recent ab initio studies. Using the computed spectroscopic constants, the rovibrational partition function for both molecules has been constructed using a modified direct numerical summation algorithm, and JANAF-style thermochemical tables are presented.

Martin, J. M. L.↗
NASA NTRS1992

A computer search for asteroid families

The improved proper elements of 4100 numbered asteroids have been searched for clusterings in a, e, i space using a computer technique based on the D-criterion. A list of 14 dynamical families each with more than 15 members is presented. Quantitative measurements of the density and dimensions in phase space of each family are presented.

Lindblad, Bertil A.↗
NASA NTRS2000

Numerical Propulsion System Simulation: An Overview

The cost of implementing new technology in aerospace propulsion systems is becoming prohibitively expensive and time consuming. One of the main contributors to the high cost and lengthy time is the need to perform many large-scale hardware tests and the inability to integrate all appropriate subsystems early in the design process. The NASA Glenn Research Center is developing the technologies required to enable simulations of full aerospace propulsion systems in sufficient detail to resolve critical design issues early in the design process before hardware is built. This concept, called the Numerical Propulsion System Simulation (NPSS), is focused on the integration of multiple disciplines such as aerodynamics, structures and heat transfer with computing and communication technologies to capture complex physical processes in a timely and cost-effective manner. The vision for NPSS, as illustrated, is to be a "numerical test cell" that enables full engine simulation overnight on cost-effective computing platforms. There are several key elements within NPSS that are required to achieve this capability: 1) clear data interfaces through the development and/or use of data exchange standards, 2) modular and flexible program construction through the use of object-oriented programming, 3) integrated multiple fidelity analysis (zooming) techniques that capture the appropriate physics at the appropriate fidelity for the engine systems, 4) multidisciplinary coupling techniques and finally 5) high performance parallel and distributed computing. The current state of development in these five area focuses on air breathing gas turbine engines and is reported in this paper. However, many of the technologies are generic and can be readily applied to rocket based systems and combined cycles currently being considered for low-cost access-to-space applications. Recent accomplishments include: (1) the development of an industry-standard engine cycle analysis program and plug 'n play architecture, called NPSS Version 1, (2) A full engine simulation that combines a 3D low-pressure subsystem with a 0D high pressure core simulation. This demonstrates the ability to integrate analyses at different levels of detail and to aerodynamically couple components, the fan/booster and low-pressure turbine, through a 3D computational fluid dynamics simulation. (3) Simulation of all of the turbomachinery in a modern turbofan engine on parallel computing platform for rapid and cost-effective execution. This capability can also be used to generate full compressor map, requiring both design and off-design simulation. (4) Three levels of coupling characterize the multidisciplinary analysis under NPSS: loosely coupled, process coupled and tightly coupled. The loosely coupled and process coupled approaches require a common geometry definition to link CAD to analysis tools. The tightly coupled approach is currently validating the use of arbitrary Lagrangian/Eulerian formulation for rotating turbomachinery. The validation includes both centrifugal and axial compression systems. The results of the validation will be reported in the paper. (5) The demonstration of significant computing cost/performance reduction for turbine engine applications using PC clusters. The NPSS Project is supported under the NASA High Performance Computing and Communications Program.

Lytle, John K.↗
NASA NTRSDate not supplied

Ray Tracing Techniques for the Characterization of Lunar Communication Architectures

This paper provides an overview of the computational techniques used to characterize the viability of different lunar architectures and their ability to provide communication services to the lunar surface. This analysis was done with modern ray tracing techniques that allow for the computations to be done on Graphics Processing Unit (GPU) clusters for a high level of parallelism and severe reduction in computation time. The ray tracing computations were done with the GPU platform Compute Unified Device Architecture (CUDA) provided by NVIDIA which utilizes general-purpose computing on graphics processing units (GPGPU). This new method provides the advantage of being able to characterize a much larger portion of the lunar surface due to its computational efficiency as well as providing a more accurate representation of elevation angle limits instead of the typical and often inaccurate elevation angle mask. The Lunar surface can now be characterized with metrics such as contact time, outage time, and received data rate. With these metrics, different proposed Lunar architectures can be rapidly evaluated. This reduction in computation time not only leads to more accurate results but allows these results to be obtained in a time frame that allows for the complete characterization of the trade space. It is expected that these different architecture comparisons will lead to a conclusive determination of the optimal Lunar architecture and will allow for future Lunar missions to operate as close to real time as possible. In addition, this computation method can be used to recreate visibility figures generated by previous methods but with an increased level of accuracy.

Thomas Montano↗