Engineering Papers⌕ Search

SEARCH · Engineering Papers

Results for “cluster computer”

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 1,801 records · Page 100
All sourcesNASA NTRSDOE OSTI
NASA NTRS1993

The three-dimensional Multi-Block Advanced Grid Generation System (3DMAGGS)

As the size and complexity of three dimensional volume grids increases, there is a growing need for fast and efficient 3D volumetric elliptic grid solvers. Present day solvers are limited by computational speed and do not have all the capabilities such as interior volume grid clustering control, viscous grid clustering at the wall of a configuration, truncation error limiters, and convergence optimization residing in one code. A new volume grid generator, 3DMAGGS (Three-Dimensional Multi-Block Advanced Grid Generation System), which is based on the 3DGRAPE code, has evolved to meet these needs. This is a manual for the usage of 3DMAGGS and contains five sections, including the motivations and usage, a GRIDGEN interface, a grid quality analysis tool, a sample case for verifying correct operation of the code, and a comparison to both 3DGRAPE and GRIDGEN3D. Since it was derived from 3DGRAPE, this technical memorandum should be used in conjunction with the 3DGRAPE manual (NASA TM-102224).

Alter, Stephen J.↗
NASA NTRS1999

Development of a Three-Dimensional PSE Code for Compressible Flows: Stability of Three-Dimensional Compressible Boundary Layers

A program is developed to investigate the linear stability of three-dimensional compressible boundary layer flows over bodies of revolutions. The problem is formulated as a two dimensional (2D) eigenvalue problem incorporating the meanflow variations in the normal and azimuthal directions. Normal mode solutions are sought in the whole plane rather than in a line normal to the wall as is done in the classical one dimensional (1D) stability theory. The stability characteristics of a supersonic boundary layer over a sharp cone with 50 half-angle at 2 degrees angle of attack is investigated. The 1D eigenvalue computations showed that the most amplified disturbances occur around x(sub 2) = 90 degrees and the azimuthal mode number for the most amplified disturbances range between m = -30 to -40. The frequencies of the most amplified waves are smaller in the middle region where the crossflow dominates the instability than the most amplified frequencies near the windward and leeward planes. The 2D eigenvalue computations showed that due to the variations in the azimuthal direction, the eigenmodes are clustered into isolated confined regions. For some eigenvalues, the eigenfunctions are clustered in two regions. Due to the nonparallel effect in the azimuthal direction, the eigenmodes are clustered into isolated confined regions. For some eigenvalues, the eigenfunctions are clustered in two regions. Due to the nonparallel effect in the azimuthal direction, the most amplified disturbances are shifted to 120 degrees compared to 90 degrees for the parallel theory. It is also observed that the nonparallel amplification rates are smaller than that is obtained from the parallel theory.

Balakumar, P.↗
NASA NTRS2004

Research on Spectroscopy, Opacity, and Atmospheres

I propose to continue providing observers with basic data for interpreting spectra from stars, novas, supernovas, clusters, and galaxies. These data will include allowed forbidden line lists both laboratory and computed, for the first five to ten ions of all atoms and for all relevant diatomic molecules. I will eventually expend to all ions of the first thirty elements to treat far UV end X-ray spectra, and for envelope opacities. I also include triatomic molecules providing by other researchers. I have made CDs with Partridge and Schwanke's water data for work on M stars.The luna data also serve as input to my model atmosphere and synthesis programs that generated energy distributions, photometry, limb darkening, and spectra that can be used for planning observations and for fitting observed spectra. The spectrum synthesis programs produce detailed plots with the line identified. Grids of stellar spectra can be used for radial velocity-, rotation-, or abundance templates and for population synthesis. I am fitting spectra of bright stars to test the data and to produce atlases to guide observer. For each star the whole spectrum is computed from the UV to the far IR. The line data, opacities, models, spectra, and programs are freely distributed on CDs and on my web site and represent a unique resource for many NASA programs.

Oliversen, Ronald↗
NASA NTRS2008

Benchmark Comparison of Dual- and Quad-Core Processor Linux Clusters with Two Global Climate Modeling Workloads

This viewgraph presentation details the science and systems environments that NASA High End computing program serves. Included is a discussion of the workload that is involved in the processing for the Global Climate Modeling. The Goddard Earth Observing System Model, Version 5 (GEOS-5) is a system of models integrated using the Earth System Modeling Framework (ESMF). The GEOS-5 system was used for the Benchmark tests, and the results of the tests are shown and discussed. Tests were also run for the Cubed Sphere system, results for these test are also shown.

McGalliard, James↗
DOE OSTI2012

Verification of a neutronic code for transient analysis in reactors with Hex-z geometry

Due to the geometry of the fuel bundles, to simulate reactors such as VVER reactors it is necessary to develop methods that can deal with hexagonal prisms as basic elements of the spatial discretization. The main features of a code based on a high order finite element method for the spatial discretization of the neutron diffusion equation and an implicit difference method for the time discretization of this equation are presented and the performance of the code is tested solving the first exercise of the AER transient benchmark. The obtained results are compared with the reference results of the benchmark and with the results provided by PARCS code. (authors)

22 GENERAL STUDIES OF NUCLEAR REACTORS↗
DOE OSTI2016

Modeling of Two-Phase Flow around Spacers with Mixing Vanes in Reactor Rod-Bundles

Reactor fuel rod bundles experience complex two-phase flow patterns that are governed by multiple interacting phenomena. Proper understand of the underlying flow hydrodynamics can point to potential hotspots within nuclear reactors. The structural supports, called spacer grids, have mixing vanes fixed to the trailing edges to enhance mixing and swirl within the flow. This is an added phenomenon that makes the flows even more complicated to model. As reactors can experience boiling conditions, it is important to understand how the spacer geometry affects local velocity and phase distributions in these geometries. This work represents a continuation of a study that has been focused on developing, testing, and validation of a consistent multidimensional model of dispersed bubbly flow along PWR coolant channels,. The proposed model has been implemented in the NPHASE-CMFD code the results of computer simulations have been compared to experimental results of Yloenen. One of the objectives of the current study has been to examine the effects of selected recent modeling improvements at RPI in NPHASE-CMFD as a part of the continuing model development and validation efforts. (authors)

22 GENERAL STUDIES OF NUCLEAR REACTORS↗
DOE OSTI2024

Monte Carlo Explicitly Correlated Second-Order Many-Body Green’s Function Calculations of Semiconductor Band Gaps

A systematically converging series of ab initio, post-density-functional, size-consistent, electron-correlated approximations is desired for predictive computing of felectronic band structures of insulating, semiconducting, and metallic solids. A series that meets all of these desiderata (except the applicability to metals) is ab initio many-body Green's function theory based on Gaussian-type-orbital (GTO) basis sets. Here, its leading-order approximation, the second-order Green's function (GF2) method in the diagonal and frequency-independent approximations with the aug-cc-pVDZ basis set, is applied to the fundamental band gaps of three semiconductors (diamond, silicon, and silicon carbide in the zincblende structure) using cluster models. Corrections are made to the basis-set-incompleteness errors by the explicit-correlation (F12) ansatz (GF2-F12) for the valence band edges. The crystals are modeled as surface-passivated clusters of increasing sizes, whose wave functions are expanded by up to 2709 GTO basis functions. Immense computational costs of these calculations are overcome by the highly scalable stochastic algorithm of the Monte Carlo GF2-F12 method, whose operation cost per state increases only as a cubic power of system size, which has a tiny memory footprint and easily achieves near-perfect parallel efficiency on thousands of CPUs or on hundreds of GPUs. The correlated, F12-corrected highest-occupied and lowest-unoccupied molecular-orbital energy (HOMO-LUMO) gap is 5.78 ± 0.07 eV for C 87 H 76 as compared with the experimental value of the fundamental (indirect) band gap of bulk diamond at 5.48 eV. The correlated, F12-corrected HOMO-LUMO gaps for Si 75 H 76 and Si 32 C 43 H 76 are 2.56 ± 0.15 eV and 3.50 ± 0.12 eV, respectively, which are expected to decrease further with increasing cluster sizes. As a result, the experimental fundamental (indirect) band gaps of bulk silicon and silicon carbide are 1.17 eV and 2.42 eV, respectively.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
DOE OSTI2017

Exploiting analytics techniques in CMS computing monitoring

The CMS experiment has collected an enormous volume of metadata about its computing operations in its monitoring systems, describing its experience in operating all of the CMS workflows on all of the Worldwide LHC Computing Grid Tiers. Data mining efforts into all these information have rarely been done, but are of crucial importance for a better understanding of how CMS did successful operations, and to reach an adequate and adaptive modelling of the CMS operations, in order to allow detailed optimizations and eventually a prediction of system behaviours. These data are now streamed into the CERN Hadoop data cluster for further analysis. Specific sets of information (e.g. data on how many replicas of datasets CMS wrote on disks at WLCG Tiers, data on which datasets were primarily requested for analysis, etc) were collected on Hadoop and processed with MapReduce applications profiting of the parallelization on the Hadoop cluster. We present the implementation of new monitoring applications on Hadoop, and discuss the new possibilities in CMS computing monitoring introduced with the ability to quickly process big data sets from mulltiple sources, looking forward to a predictive modeling of the system.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2026

Stochastic tensor contraction for quantum chemistry

Many computational methods in ab initio quantum chemistry are formulated in terms of high-order tensor contractions, whose cost determines the size of system that can be studied. We introduce stochastic tensor contraction to perform such operations with greatly reduced cost, and present its application to the gold-standard quantum chemistry method, coupled cluster theory with up to perturbative triples. For total energy errors more stringent than chemical accuracy, we reduce the computational scaling to that of mean-field theory, while starting to approach the mean-field absolute cost, thereby challenging the existing cost-to-accuracy landscape. Benchmarks against state-of-the-art local correlation approximations further show that we achieve an order-of-magnitude improvement in both total computation time and error, with significantly reduced sensitivity to system dimensionality and electron delocalization. We conclude that stochastic tensor contraction is a powerful computational primitive to accelerate a wide range of quantum chemistry.

Chemical Physics (physics.chem-ph)↗
DOE OSTI2022

Hybrid quantum-classical approach for coupled-cluster Green's function theory

The three key elements of a quantum simulation are state preparation, time evolution, and measurement. While the complexity scaling of time evolution and measurements are well known, many state preparation methods are strongly system-dependent and require prior knowledge of the system's eigenvalue spectrum. Here, we report on a quantum-classical implementation of the coupled-cluster Green's function (CCGF) method, which replaces explicit ground state preparation with the task of applying unitary operators to a simple product state. While our approach is broadly applicable to many models, we demonstrate it here for the Anderson impurity model (AIM). The method requires a number of T gates that grows as O ( N 5 ) per time step to calculate the impurity Green's function in the time domain, where N is the total number of energy levels in the AIM. Since the number of T gates is analogous to the computational time complexity of a classical simulation, we achieve an order of magnitude improvement over a classical CCGF calculation of the same order, which requires O ( N 6 ) computational resources per time step.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
NASA NTRS1993

Optical and near infrared photometry of Butcher-Oemler clusters

Rich clusters of galaxies at moderate redshifts (z approx. .3) have a larger proportion of optically blue galaxies than their low redshift counterparts. Spectroscopic examination of the blue galaxies by various authors has shown that the blue galaxies are generally Seyferts, show evidence for recent star formation, or are foreground objects. Unfortunately, spectroscopy is too time consuming to be used on large samples. Thus, we have looked for a way to separate Seyferts, starbursts, ellipticals and nonmembers using photometry alone. Five moderate redshift clusters, Abell numbers 777, 963, 1758, 1961 and 2218, have been observed in the V, R and K bands. We model the spectral energy distributions of various kinds of galaxies found in clusters and derive observed colors. We have modeled the spectral energy distributions (SED) of several kinds of galaxies and compute their colors as a function of redshift. We expect to see ellipticals, spirals, starbursts, post-starburst and Seyfert galaxies. The SED of elliptical and Sbc galaxies was observed by Rieke and Rieke. The SEDs for the starburst galaxies was created by adding a reddened 10(exp 8) year old burst to a spiral galaxy SED. The post-starburst (E+A) galaxy SEDs are composed of a slightly reddened 10(exp 9) year old burst and elliptical galaxy SED. SEDs for the Seyferts were created by adding a v(exp -1.1) power law, and a hot dust thermal spectrum to the Sbc. From the SEDs the colors of galaxies at various redshifts with assorted filters were computed. Lilly & Gunn (1985) have optical and infrared photometry for a sample of galaxies in CL0024+1654 observed spectroscopically by Dressler, Gunn and Schneider (1985). We have used this data to choose the most appropriate SEDs for our starburst and post-starburst models. The most likely explanation for the optically blue colors in most cluster galaxies is star formation. Very few galaxies lie in the Seyfert locus. Abel 1758 has more Seyfert candidates than the other clusters, we observed. It seems possible to roughly sort types of galaxies in clusters by color alone. The cluster population seems to vary considerably between clusters, but our K selected sample has few Seyferts in any cluster.

Shier, Lisa M.↗
DOE OSTI2019

Implementation of analytic gradients for CCSD and EOM-CCSD using Cholesky decomposition of the electron-repulsion integrals and their derivatives: Theory and benchmarks

We present a general formulation of analytic nuclear gradients for the coupled-cluster with single and double substitution (CCSD) and equation-of-motion (EOM) CCSD energies computed using Cholesky decomposition (CD) representations of the electron repulsion integrals. By rewriting the correlated energy and response equations such that the storage of the largest four-index intermediates is eliminated, CD leads to a significant reduction in disk storage requirements, reduced I/O penalties, and an improved parallel performance. CD thus extends the scope of the systems that can be treated by (EOM-)CCSD methods, although analytic gradients in the framework of CD are needed to extend the applicability of (EOM-)CCSD methods in the context of geometry optimizations. This paper presents a formulation of analytic (EOM-)CCSD gradient within the CD framework and reports on the salient details of the corresponding implementation. The accuracy and the capabilities of analytic CD-based (EOM-)CCSD gradients are illustrated by benchmark calculations and several illustrative examples.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2021

Electromagnetic Transient Simulation Algorithms for Evaluation of Large-Scale Extreme Fast Charging Systems (Distribution Grid Models)

The distribution and transmission grids are observing an increased penetration of power electronics in loads and generations. For example, there is increasing interest in integrating in extreme fast charging (XFC) systems for fast charging of electrical vehicles. As these systems are integrated, developing high-fidelity electromagnetic transient model of XFC systems in distribution grids and evaluating their interactions with the power grid would be of significant interest. This model will be utilized for design of XFC systems, to identify upgrades in distribution and/or transmission grids, for planning purposes by transmission planners or operators or owners, among others. It can also be utilized in operations for improved reliable performance of the grid and/or XFC station. The challenge with simulating these models is the high computational complexity introduced by the large number of states present in the system and the time-step needed to simulate the system. In this paper, advanced simulations algorithms are applied to reduce the computational complexity of simulating large-scale XFC systems. The algorithms include numerical stiffness-based segregation, time constant-based segregation, clustering and aggregation on differential algebraic equations (DAEs), and multi-order integration approaches. While the first three algorithms split the matrix that needs to be inverted from a large matrix to much smaller matrices, the final algorithm reduces the computational burden of applying higher-order integration approaches in the complete system. The comparison made in the previous sentence is with respect to use of homogeneous integration approaches used in conventional electromagnetic transient simulators like power systems computer aided design (PSCAD). The approaches mentioned here have resulted in speed-up of 36x in the simulation of a single distribution system with 15 XFCs.

Debnath, Suman↗
DOE OSTI2019

IMG-ABC v.5.0: an update to the IMG/Atlas of Biosynthetic Gene Clusters Knowledgebase

Microbial secondary metabolism is a reservoir of bioactive compounds of immense biotechnological and biomedical potential. The biosynthetic machinery responsible for the production of these secondary metabolites (SMs) (also called natural products) is often encoded by collocated groups of genes called biosynthetic gene clusters (BGCs). Here, high-throughput genome sequencing of both isolates and metagenomic samples combined with the development of specialized computational workflows is enabling systematic identification of BGCs and the discovery of novel SMs. In order to advance exploration of microbial secondary metabolism and its diversity, we developed the largest publicly available database of predicted BGCs combined with experimentally verified BGCs, the Integrated Microbial Genomes Atlas of Biosynthetic gene Clusters (IMG-ABC) (https://img.jgi.doe.gov/abc-public). Here we describe the first major content update of the IMG-ABC knowledgebase, since its initial release in 2015, refreshing the BGC prediction pipeline with the latest version of antiSMASH (v5) as well as presenting the data in the context of underlying environmental metadata sourced from GOLD (https://gold.jgi.doe.gov/). This update has greatly improved the quality and expanded the types of predicted BGCs compared to the previous version.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2012

Scalable Node Monitoring

Project description is: (1) Build a high performance computer; and (2) Create a tool to monitor node applications in Component Based Tool Framework (CBTF) using code from Lightweight Data Metric Service (LDMS). The importance of this project is that: (1) there is a need a scalable, parallel tool to monitor nodes on clusters; and (2) New LDMS plugins need to be able to be easily added to tool. CBTF stands for Component Based Tool Framework. It's scalable and adjusts to different topologies automatically. It uses MRNet (Multicast/Reduction Network) mechanism for information transport. CBTF is flexible and general enough to be used for any tool that needs to do a task on many nodes. Its components are reusable and 'EASILY' added to a new tool. There are three levels of CBTF: (1) frontend node - interacts with users; (2) filter nodes - filters or concatenates information from backend nodes; and (3) backend nodes - where the actual work of the tool is done. LDMS stands for lightweight data metric servies. It's a tool used for monitoring nodes. Ltool is the name of the tool we derived from LDMS. It's dynamically linked and includes the following components: Vmstat, Meminfo, Procinterrupts and more. It works by: Ltool command is run on the frontend node; Ltool collects information from the backend nodes; backend nodes send information to the filter nodes; and filter nodes concatenate information and send to a database on the front end node. Ltool is a useful tool when it comes to monitoring nodes on a cluster because the overhead involved with running the tool is not particularly high and it will automatically scale to any size cluster.

99 GENERAL AND MISCELLANEOUS↗
DOE OSTI2020

Domain Separated Density Functional Theory for Reaction Energy Barriers and Optical Excitations

We recently proposed Domain Separated Density Functional Theory (DS-DFT), a framework that allows for the combination of different levels of theory for the computation of the electronic structure of molecules. Here, this work discusses the application of DS-DFT to the computation of transition-state energy barriers and optical absorption spectra. We considered several hydrogen abstraction reactions and optical spectra of molecule/metal cluster systems, including the absorption of individual species such as carbon monoxide, methane, and molecular hydrogen to a Li6 cluster. We present and discuss two domain-separated methods: i), the screened-density approximation (SDA), and, ii), linearly weighted exchange (LWE). We find that SDA, which is applied as a hybridization based on atomic domains, could be useful to computing energy barriers, whereas LWE is suited for the analysis of electronic properties such as ground-state gaps, excitation energies, and oscillator strengths.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2026

A GPU-based compressible combustion solver for applications exhibiting disparate space and time scales

High-speed chemically active flows pose significant computational challenges due to their disparate space and time scales, with stiff chemistry often dominating simulation time. While modern scientific computing programs achieve exascale performance by leveraging graphics processing units (GPUs), existing GPU-based compressible combustion solvers face critical limitations in memory management, load balancing, and handling the highly localized nature of chemical reactions. To this end, we present a high-performance compressible reacting flow solver built on the AMReX framework and optimized for multi-GPU settings. Here, our approach addresses three GPU performance bottlenecks: memory access patterns through column-major storage optimization, computational workload variability via a bulk-sparse integration strategy for chemical kinetics, and multi-GPU load distribution for adaptive mesh refinement applications. The solver adapts existing matrix-based chemical kinetics formulations to multi-grid contexts. Using representative combustion applications, including 2D and 3D detonations and a 3D jet-in-crossflow configuration, we demonstrate 1.4–5× performance improvements over initial implementations on an in-house cluster of NVIDIA H100 GPUs, and near-ideal weak scaling on the Frontier supercomputer (Oak Ridge Leadership Computing Facility) with up to 1024 AMD Instinct MI250X GPUs. Roofline analysis reveals substantial improvements in arithmetic intensity for both convection (∼ 10 ×) and chemistry (∼ 4 ×) routines, confirming efficient utilization of GPU memory bandwidth and computational resources.

42 ENGINEERING↗
DOE OSTI2024

Cu site differentiation in tetracopper(I) sulfide clusters enables biomimetic N 2 O reduction

Copper clusters feature prominently in both metalloenzymes and synthetic nanoclusters that mediate catalytic redox transformations of gaseous small molecules. Such reactions are critical to biological energy conversion and are expected to be crucial parts of renewable energy economies. However, the precise roles of individual metal atoms within clusters are difficult to elucidate, particularly for cluster systems that are dynamic under operating conditions. Here, we present a metal site-specific analysis of synthetic Cu 4 (μ 4 -S) clusters that mimic the Cu Z active site of the nitrous oxide reductase enzyme. Leveraging the ability to obtain structural snapshots of both inactive and active forms of the synthetic model system, we analyzed both states using resonant X-ray diffraction anomalous fine structure (DAFS), a technique that enables X-ray absorption profiles of individual metal sites within a cluster to be extracted independently. Using DAFS, we found that a change in cluster geometry between the inactive and active states is correlated to Cu site differentiation that is presumably required for efficient activation of N 2 O gas. More precisely, we hypothesize that the Cu δ+ ∙∙∙Cu δ- pairs produced upon site differentiation are poised for N 2 O activation, as supported by computational modeling. These results provide an unprecedented level of detail on the roles of individual metal sites within the synthetic cluster system and how those roles interplay with cluster geometry to impact the reactivity function. We expect this fundamental knowledge to inform understanding of metal clusters in settings ranging from (bio)molecular to nanocluster to extended solid systems involved in energy conversion.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Refine your search to explore more results.