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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 397 records · Page 22
All sourcesNASA NTRSDOE OSTI
DOE OSTI2013

GYROSURFING ACCELERATION OF IONS IN FRONT OF EARTH's QUASI-PARALLEL BOW SHOCK

It is well known that shocks in space plasmas can accelerate particles to high energies. However, many details of the shock acceleration mechanism are still unknown. A critical element of shock acceleration is the injection problem; i.e., the presence of the so called seed particle population that is needed for the acceleration to work efficiently. In our case study, we present for the first time observational evidence of gyroresonant surfing acceleration in front of Earth's quasi-parallel bow shock resulting in the appearance of the long-suspected seed particle population. For our analysis, we use simultaneous multi-spacecraft measurements provided by the Cluster spacecraft ion (CIS), magnetic (FGM), and electric field and wave instrument (EFW) during a time period of large inter-spacecraft separation distance. The spacecraft were moving toward the bow shock and were situated in the foreshock region. The results show that the gyroresonance surfing acceleration takes place as a consequence of interaction between circularly polarized monochromatic (or quasi-monochromatic) transversal electromagnetic plasma waves and short large amplitude magnetic structures (SLAMSs). The magnetic mirror force of the SLAMS provides the resonant conditions for the ions trapped by the waves and results in the acceleration of ions. Since wave packets with circular polarization and different kinds of magnetic structures are very commonly observed in front of Earth's quasi-parallel bow shock, the gyroresonant surfing acceleration proves to be an important particle injection mechanism. We also show that seed ions are accelerated directly from the solar wind ion population.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2015

Lattice Quantum Chromodynamics with Overlap Fermions on GPUs

Lattice quantum chromodynamics (QCD) calculations were one of the first applications to demonstrate the potential of GPUs in the area of high-performance computing; the nature of lattice QCD calculations matches well with the GPU's computational model. This article discusses ways to effectively use GPUs for lattice calculations using the overlap operator, a discretization that preserves chiral symmetry even at nonzero lattice spacing and makes possible lattice QCD simulations in the parameter region relevant to nuclear physics. The author shows that the large memory footprint of these codes requires the use of multiple GPUs in parallel and discusses methods for implementing this operator efficiently: hybrid CPU/GPU memory use for eigensolvers and MPI/OpenMP/CUDA parallelization strategies required to take full advantage of both GPU and CPU resources. He then compares the performance of codes on a GPU cluster and a CPU cluster with similar interconnects, discussing the strong scaling for problem sizes relevant to current lattice QCD simulations.

Computer Science↗
DOE OSTI2012

Aho-Corasick String Matching on Shared and Distributed Memory Parallel Architectures

String matching is at the core of many critical applications, including network intrusion detection systems, search engines, virus scanners, spam filters, DNA and protein sequencing, and data mining. For all of these applications string matching requires a combination of (sometimes all) the following characteristics: high and/or predictable performance, support for large data sets and flexibility of integration and customization. Many software based implementations targeting conventional cache-based microprocessors fail to achieve high and predictable performance requirements, while Field-Programmable Gate Array (FPGA) implementations and dedicated hardware solutions fail to support large data sets (dictionary sizes) and are difficult to integrate and customize. The advent of multicore, multithreaded, and GPU-based systems is opening the possibility for software based solutions to reach very high performance at a sustained rate. This paper compares several software-based implementations of the Aho-Corasick string searching algorithm for high performance systems. We discuss the implementation of the algorithm on several types of shared-memory high-performance architectures (Niagara 2, large x86 SMPs and Cray XMT), distributed memory with homogeneous processing elements (InfiniBand cluster of x86 multicores) and heterogeneous processing elements (InfiniBand cluster of x86 multicores with NVIDIA Tesla C10 GPUs). We describe in detail how each solution achieves the objectives of supporting large dictionaries, sustaining high performance, and enabling customization and flexibility using various data sets.

99 GENERAL AND MISCELLANEOUS↗
DOE OSTI2025

HARD: A performance portable radiation hydrodynamics code based on FleCSI framework

Hydrodynamics And Radiation Diffusion (HARD) is an open-source application for high-performance simulations of compressible hydrodynamics with radiation-diffusion coupling. Built on the FleCSI (Bergen et al., 2021 [1]) (Flexible Computational Science Infrastructure) framework, HARD expresses its computational units as tasks whose execution can be orchestrated by multiple back-end runtimes, including Legion (Bauer et al., 2012 [2]), MPI (Forum, 1994 [3]), and HPX (Kaiser et al., 2020 [4]). Node-level parallelism is handled through Kokkos (Edwards et al., 2014 [5]), providing a single-source, portable code base that runs efficiently on laptops, small homogeneous clusters, and the largest heterogeneous supercomputers currently available. To ensure scientific reliability, HARD includes a regression test suite that automatically reproduces canonical verification problems such as the Sod and LeBlanc shock tubes, and the Sedov blast wave, comparing numerical solutions against known analytical results. The project is distributed under an OSI-approved license, hosted on GitHub, and accompanied by reproducible build scripts and continuous integration workflows. This combination of performance portability, verification infrastructure, and community-focused development makes HARD a sustainable platform for advancing radiation hydrodynamics research across multiple domains.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2013

THE STABILITY OF WEAKLY COLLISIONAL PLASMAS WITH THERMAL AND COMPOSITION GRADIENTS

Over the last decade, substantial efforts have been devoted to understanding the stability properties, transport phenomena, and long-term evolution of weakly collisional, magnetized plasmas which are stratified in temperature. The insights gained via these studies have led to a significant improvement of our understanding of the processes that determine the physical evolution and observational properties of the intracluster medium (ICM) permeating galaxy clusters. These studies have been carried out under the assumption that the ICM is a homogeneous medium. This, however, might not be a good approximation if heavy elements are able to sediment in the inner region of the galaxy cluster. Motivated by the need to obtain a more complete picture of the dynamical properties of the ICM, we analyze the stability of a weakly collisional, magnetized plane-parallel atmosphere which is stratified in both temperature and composition. This allows us to discuss for the first time the dynamics of weakly collisional environments where heat conduction, momentum transport, and ion-diffusion are anisotropic with respect to the direction of the magnetic field. We show that depending on the relative signs and magnitudes of the gradients in the temperature and the mean molecular weight, the plasma can be subject to a wide variety of unstable modes which include modifications to the magnetothermal instability (MTI), the heat-flux-driven buoyancy instability (HBI), and overstable gravity modes previously studied in homogeneous media. We also find that there are new modes which are driven by heat conduction and particle diffusion. We discuss the astrophysical implications of our findings for a representative galaxy cluster where helium has sedimented. Our findings suggest that the core insulation that results from the magnetic field configurations that arise as a natural consequence of the HBI, which would be MTI stable in a homogeneous medium, could be alleviated if the mean molecular weight gradient is steep enough, i.e., ({nabla}{mu})/{mu} > ({nabla}T)/T. This study constitutes a first step toward understanding the interaction between magnetic turbulence and the diffusion of heavy elements, and its consequences for the long-term evolution and observational signatures of the ICM in galaxy clusters.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2022

Two-Stage Gauss-Seidel Preconditioners and Smoothers for Krylov Solvers on a GPU Cluster: Preprint

Gauss-Seidel (GS) relaxation is often employed as a preconditioner for a Krylov solver or as a smoother for Algebraic Multigrid (AMG). However, the requisite sparse triangular solve is difficult to parallelize on many-core architectures such as graphics processing units (GPUs). In the present study, the performance of the sequential GS relaxation based on a triangular solve is compared with two-stage variants, replacing the direct triangular solve with a fixed number of inner Jacobi-Richardson (JR) iterations. When a small number of inner iterations is sufficient to maintain the Krylov convergence rate, the two-stage GS (GS2) often outperforms the sequential algorithm on many-core architectures. The GS2 algorithm is also compared with JR. When they perform the same number of ops for SpMV (e.g. three JR sweeps compared to two GS sweeps with one inner JR sweep), the GS2 iterations, and the Krylov solver preconditioned with GS2, may converge faster than the JR iterations. Moreover, for some problems (e.g. elasticity), it was found that JR may diverge with a damping factor of one, whereas two-stage GS may improve the convergence with more inner iterations. Finally, to study the performance of the two-stage smoother and preconditioner for a practical problem, these were applied to incompressible uid ow simulations on GPUs.

algebraic multigrid↗
DOE OSTI2022

MPLBM-UT: Multiphase LBM library for permeable media analysis

MPLBM-UT is a specialized lattice-Boltzmann library that makes running single- and two-phase flow simulations in porous media accessible to everyone. We provide a suite of tools to pre-process computational domains for simulation, to set up custom boundary conditions, to run simulations, to post-process simulation outputs, and to visualize simulation results and data. All of these tools are easily accessible to users through the mplbm_utils Python package included in and automatically installed with MPLBM-UT. The high-performance, highly parallel library Palabos is used as the solver backend. MPLBM-UT is easily deployed in a variety of systems, from laptops to supercomputer clusters. MPLBM-UT also features multiple examples and benchmark templates that allow for fast prototyping of different porous media problems. We also provide an interface for reading in different file types and downloading domains from the Digital Rocks Portal to perform simulations.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2019

Properties of the Graph Modularity Matrix and its Applications

We study the popular modularity matrix and respective functional used in connection with graph clustering and derive some properties useful when performing vertex aggregation of the associated graph. These properties are employed in the derivation of a multilevel parallel pairwise aggregation algorithm. Some illustrative examples which include algebraic multigrid (AMG) coarsening that follows strong direction of anisotropy in finite element problems as well as comparative performance results of the studied algorithm are presented.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2023

Enhancing Entanglement: Non-Markovian and Floquet Reservoir Engineering in Many-Qubit Superconducting Quantum Circuits

This is an experimental and theoretical project to leverage dissipation engineering under non-Markovian settings in order to aid in the preparation and stabilization of large, non-trivial, entangled quantum states. This project is a collaborative effort between the Painter group at Caltech and the Clerk group at the University of Chicago. By utilization of superconducting qubits coupled to the metamaterial waveguide described in the proposal, we tackle this goal via two parallel thrusts: (i) non-Markovian dynamics of a superconducting qubit strongly coupled to a slow-light waveguide reservoir and generation of 2D cluster states and (ii) many-qubit waveguide circuit QED for studying quantum many-body physics. In addition to device development and testing, we are also developing theoretical methods for understanding physics in the deep non-Markovian regime and driven-dissipative protocols for preparing and stabilizing the quantum many-body states.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
DOE OSTI2021

PandAna: A Python Analysis Framework for Scalable High Performance Computing in High Energy Physics

Modern experiments in high energy physics analyze millions of events recorded in particle detectors to select the events of interest and make measurements of physics parameters. These data can often be stored as tabular data in files with detector information and reconstructed quantities. Current techniques for event selection in these files lack the scalability needed for high performance computing environments. We describe our work to develop a high energy physics analysis framework suitable for high performance computing. This new framework utilizes modern tools for reading files and implicit data parallelism. Framework users analyze tabular data using standard, easy-to-use data analysis techniques in Python while the framework handles the file manipulations and parallelism without the user needing advanced experience in parallel programming. In future versions, we hope to provide a framework that can be utilized on a personal computer or a high performance computing cluster with little change to the user code.

Groh, Micah↗
DOE OSTI2014

Static electric dipole polarizabilities of An{sup 5+/6+} and AnO{sub 2}{sup +/2+} (An = U, Np, and Pu) ions

The parallel components of static electric dipole polarizabilities have been calculated for the lowest lying spin-orbit states of the penta- and hexavalent oxidation states of the actinides (An) U, Np, and Pu, in both their atomic and molecular diyl ion forms (An{sup 5+/6+} and AnO{sub 2}{sup +/2+}) using the numerical finite-field technique within a four-component relativistic framework. The four-component Dirac-Hartree-Fock method formed the reference for MP2 and CCSD(T) calculations, while multireference Fock space coupled-cluster (FSCC), intermediate Hamiltonian Fock space coupled-cluster (IH-FSCC) and Kramers restricted configuration interaction (KRCI) methods were used to incorporate additional electron correlation. It is observed that electron correlation has significant (∼5 a.u.{sup 3}) impact upon the parallel component of the polarizabilities of the diyls. To the best of our knowledge, these quantities have not been previously reported and they can serve as reference values in the determination of various electronic and response properties (for example intermolecular forces, optical properties, etc.) relevant to the nuclear fuel cycle and material science applications. The highest quality numbers for the parallel components (α{sub zz}) of the polarizability for the lowest Ω levels corresponding to the ground electronic states are (in a.u.{sup 3}) 44.15 and 41.17 for UO{sub 2}{sup +} and UO{sub 2}{sup 2+}, respectively, 45.64 and 41.42 for NpO{sub 2}{sup +} and NpO{sub 2}{sup 2+}, respectively, and 47.15 for the PuO{sub 2}{sup +} ion.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2012

Molecular dynamic studies on anisotropic explosion of laser irradiated Xe cluster

A three dimensional molecular dynamic model is used to investigate the dynamics of Xe clusters of various radii irradiated by laser of moderate intensities ({approx}10{sup 14}-10{sup 16}W/cm{sup 2}). The FWHM pulse duration of the laser is varied from few laser cycles to hundreds of femtosecond. For cluster of radius 50 A irradiated by a laser of 170 fs pulse duration, it is observed that ion yield is more along the direction of laser polarization than perpendicular to it. This trend reverses (more ions are emitted along the direction perpendicular to laser polarization than parallel to it) when laser pulses of few cycles are used. This reversal of anisotropy is explained on the basis of spatial shielding of ions due to the oscillating inner electron cloud along direction of laser electric field. The nature of anisotropy remains same with variations in laser intensity and cluster size.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2016

Enabling parallel simulation of large-scale HPC network systems

Here, with the increasing complexity of today’s high-performance computing (HPC) architectures, simulation has become an indispensable tool for exploring the design space of HPC systems—in particular, networks. In order to make effective design decisions, simulations of these systems must possess the following properties: (1) have high accuracy and fidelity, (2) produce results in a timely manner, and (3) be able to analyze a broad range of network workloads. Most state-of-the-art HPC network simulation frameworks, however, are constrained in one or more of these areas. In this work, we present a simulation framework for modeling two important classes of networks used in today’s IBM and Cray supercomputers: torus and dragonfly networks. We use the Co-Design of Multi-layer Exascale Storage Architecture (CODES) simulation framework to simulate these network topologies at a flit-level detail using the Rensselaer Optimistic Simulation System (ROSS) for parallel discrete-event simulation. Our simulation framework meets all the requirements of a practical network simulation and can assist network designers in design space exploration. First, it uses validated and detailed flit-level network models to provide an accurate and high-fidelity network simulation. Second, instead of relying on serial time-stepped or traditional conservative discrete-event simulations that limit simulation scalability and efficiency, we use the optimistic event-scheduling capability of ROSS to achieve efficient and scalable HPC network simulations on today’s high-performance cluster systems. Third, our models give network designers a choice in simulating a broad range of network workloads, including HPC application workloads using detailed network traces, an ability that is rarely offered in parallel with high-fidelity network simulations

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2021

Pore accessibility and trapping of methane in Marcellus shale

Accessibility of pore space in unconventional reservoirs is an important factor influencing both methane storage capacity and the kinetics of methane desorption. The determination of open (accessible) versus closed (inaccessible) porosity is therefore vital for the prediction of gas production potential. This study investigates accessibility of pores to methane in overmature middle Devonian Marcellus shale samples (cut parallel and perpendicular to bedding) using small and ultra-small neutron scattering (SANS and USANS) with contrast matching (CM), supplemented by other complementary techniques, such as mercury injection capillary pressure (MICP) and low pressure gas (N2 and CO2) adsorption. Our results demonstrate that for the samples studied, only about 6 % of pores with diameter 25-500 nm are accessible to methane. The accessibility fraction for pores larger than 500 nm is 35%. For nanopores smaller than 25 nm, pore accessibility could not be quantitatively determined due to increased methane density and condensation effects in confinement. Our observations indicate that methane penetrates the accessible small mesopores and micropores down to at least 1 nm in diameter, and the density of confined deuterated methane (CD4) is 0.68 g/cm3 for pores of diameter 25 nm and gradually increases with the decreased pore size. Moreover, elevated gas pressure causes formation of additional high-density methane nano-clusters. These clusters have a form of slightly anisotropic polydisperse discs oriented along bedding plane, about 1-12 nm in diameter and with average thickness of 3.6 nm. Utilizing samples cut parallel and perpendicular to the bedding, this study also briefly addresses anisotropy of pores. Based on the iso-size intensity ratio R, our SANS and USANS results demonstrate anisotropy in the out-of-bedding direction and suggest that the degree of anisotropy depends on the pore size. Specifically, for pore diameters ~2.5 to 250 nm, the extent of anisotropy is smaller than for pores ~500 nm to 6 µm in diameter. Finally, comparison of pore size distribution results calculated from SANS/USANS to those obtained using MICP shows good agreement at low pressures, but large difference at pressures above 1000 bar. Here, this discrepancy requires further testing; it is possible that the high mercury pressure used in MICP alters the mesopore and micropore structure of shales.

03 NATURAL GAS↗
DOE OSTI2014

A Structure-Based Distance Metric for High-Dimensional Space Exploration with Multi-Dimensional Scaling

Although the Euclidean distance does well in measuring data distances within high-dimensional clusters, it does poorly when it comes to gauging inter-cluster distances. This significantly impacts the quality of global, low-dimensional space embedding procedures such as the popular multi-dimensional scaling (MDS) where one can often observe non-intuitive layouts. We were inspired by the perceptual processes evoked in the method of parallel coordinates which enables users to visually aggregate the data by the patterns the polylines exhibit across the dimension axes. We call the path of such a polyline its structure and suggest a metric that captures this structure directly in high-dimensional space. This allows us to better gauge the distances of spatially distant data constellations and so achieve data aggregations in MDS plots that are more cognizant of existing high-dimensional structure similarities. Our MDS plots also exhibit similar visual relationships as the method of parallel coordinates which is often used alongside to visualize the high-dimensional data in raw form. We then cast our metric into a bi-scale framework which distinguishes far-distances from near-distances. The coarser scale uses the structural similarity metric to separate data aggregates obtained by prior classification or clustering, while the finer scale employs the appropriate Euclidean distance.

Clustering↗
DOE OSTI2019

Structures of single-layer {beta}-sheet proteins evolved from {beta}-hairpin repeats

Free-standing single-layer beta-sheets are extremely rare in naturally occurring proteins, even though beta-sheet motifs are ubiquitous. Here we report the crystal structures of three homologous, single-layer, anti-parallel beta-sheet proteins, comprised of three or four twisted beta-hairpin repeats. The structures reveal that, in addition to the hydrogen bond network characteristic of beta-sheets, additional hydrophobic interactions mediated by small clusters of residues adjacent to the turns likely play a significant role in the structural stability and compensate for the lack of a compact hydrophobic core. These structures enabled identification of a family of secreted proteins that are broadly distributed in bacteria from the human gut microbiome and are putatively involved in the metabolism of complex carbohydrates. A conserved surface patch, rich in solvent-exposed tyrosine residues, was identified on the concave surface of the beta-sheet. These new modular single-layer beta-sheet proteins may serve as a new model system for studying folding and design of beta-rich proteins.

beta-hairpin repeats↗