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At least 685 records · Page 38

An algorithm for continuum modeling of rocks with multiple embedded nonlinearly-compliant joints [Continuum modeling of elasto-plastic media with multiple embedded nonlinearly-compliant joints]

Here, we present a numerical method for modeling the mechanical effects of nonlinearly-compliant joints in elasto-plastic media. The method uses a series of strain-rate and stress update algorithms to determine joint closure, slip, and solid stress within computational cells containing multiple “embedded” joints. This work facilitates efficient modeling of nonlinear wave propagation in large spatial domains containing a large number of joints that affect bulk mechanical properties. We implement the method within the massively parallel Lagrangian code GEODYN-L and provide verification and examples. We highlight the ability of our algorithms to capture joint interactions and multiple weakness planes within individual computational cells, as well as its computational efficiency. We also discuss the motivation for developing the proposed technique: to simulate large-scale wave propagation during the Source Physics Experiments (SPE), a series of underground explosions conducted at the Nevada National Security Site (NNSS).

42 ENGINEERING↗

Analysis of Plane-Parallel Electron Beam Propagation in Different Media by Numerical Simulation Methods

Simulation by the Monte Carlo method is widely used to calculate the character of ionizing radiation interaction with substance. A wide variety of programs based on the given method allows users to choose the most suitable package for solving computational problems. In turn, it is important to know exactly restrictions of numerical systems to avoid gross errors. Results of estimation of the feasibility of application of the program PCLab (Computer Laboratory, version 9.9) for numerical simulation of the electron energy distribution absorbed in beryllium, aluminum, gold, and water for industrial, research, and clinical beams are presented. The data obtained using programs ITS and Geant4 being the most popular software packages for solving the given problems and the program PCLab are presented in the graphic form. A comparison and an analysis of the results obtained demonstrate the feasibility of application of the program PCLab for simulation of the absorbed energy distribution and dose of electrons in various materials for energies in the range 1–20 MeV.

61 RADIATION PROTECTION AND DOSIMETRY↗

ZERNIPAX: A fast and accurate Zernike polynomial calculator in Python

Zernike polynomials serve as an orthogonal basis on the unit disc, and have proven to be effective in optics simulations, astrophysics, and more recently in plasma simulations. Unlike Bessel functions, Zernike polynomials are inherently finite and smooth at the disc center (r=0), ensuring continuous differentiability along the axis. This property makes them particularly suitable for simulations, requiring no additional handling at the origin. We developed ZERNIPAX, an open-source Python package capable of utilizing CPU/GPUs, leveraging Google's JAX package and available on GitHub as well as the Python software repository PyPI. Furthermore, our implementation of the recursion relation between Jacobi polynomials significantly improves computation time compared to alternative methods by use of parallel computing while still performing more accurately for high-mode numbers.

Astrophysics↗

Component-wise reduced order model lattice-type structure design

Lattice-type structures can provide a combination of stiffness with light weight that is desirable in a variety of applications. Design optimization of these structures must rely on approximations of the governing physics to render solution of a mathematical model feasible. In this paper, we propose a topology optimization (TO) formulation that approximates the governing physics using component-wise reduced order modeling as introduced in Huynh et al. (2013); Eftang and Patera (2013), which can reduce solution time by multiple orders of magnitude over a full-order finite element model while providing a relative error in the solution of 1%. In addition, the offline training data set from such component-wise models is reusable, allowing its application to many design problems for only the cost of a single offline training phase, and the component-wise method is nearly embarrassingly parallel. We also show how the parameterization chosen in our optimization allows a simplification of the component-wise reduced order model (CWROM) not noted in previous literature, for further speedup of the optimization process. Furthermore, the sensitivity of the compliance with respect to the particular parameterization is derived solely at the component level. In numerical examples, we demonstrate a 1000x speedup over a full-order FEM model with relative error of 1% and show minimum compliance designs for two different cantilever beam examples, one smaller and one larger. Finally, error bounds for the displacement field, compliance, and compliance sensitivity of the CWROM are derived.

97 MATHEMATICS AND COMPUTING↗

PUMIPic: A mesh-based approach to unstructured mesh Particle-In-Cell on GPUs

Unstructured mesh particle-in-cell, PIC, simulations executing on the current and next generation of massively parallel systems require new methods for both the mesh and particles to achieve performance and scalability on GPUs. The traditional approach to implementing PIC simulations defines data structures and algorithms in terms of particles with a full copy of the unstructured mesh on every process. To effectively scale the unstructured mesh and particles, mesh-based PIC uses the unstructured mesh as the predominant data structure with the particles stored in terms of the mesh entities. Here, this paper details the PUMIPic library, a framework for developing efficient and performance-portable mesh-based PIC simulations on GPU systems. A pseudo physics simulation based on a five-dimensional gyro-kinetic code for modeling plasma physics is used to examine the performance of PUMIPic. Scaling studies of the unstructured mesh partition and number of particles are performed up to 4096 nodes of the Summit system at Oak Ridge National Laboratory. The studies show that mesh-based PIC can utilize a partitioned mesh and maintain scaling up to system limitations.

97 MATHEMATICS AND COMPUTING↗

Laser Ablation-Aerosol Mass Spectrometry-Chemical Ionization Mass Spectrometry for Ambient Surface Imaging

Mass spectrometry imaging is becoming an increasingly common analytical technique due to its ability to provide spatially resolved chemical information. In this paper, we report a novel imaging approach combining laser ablation with two mass spectrometric techniques, aerosol mass spectrometry and chemical ionization mass spectrometry, separately and in parallel. Both mass spectrometric methods provide the fast response, rapid data acquisition, low detection limits, and high-resolution peak separation desirable for imaging complex samples. Additionally, the two techniques provide complementary information with aerosol mass spectrometry providing near universal detection of all aerosol molecules and chemical ionization mass spectrometry with a heated inlet providing molecular-level detail of both gases and aerosols. The two techniques operate with atmospheric pressure interfaces and require no matrix addition for ionization, allowing for samples to be investigated in their native state under ambient pressure conditions. We demonstrate the ability of laser ablation-aerosol mass spectrometry-chemical ionization mass spectrometry (LA-AMS-CIMS) to create 2D images of both standard compounds and complex mixtures. Finally, the results suggest that LA-AMS-CIMS, particularly when combined with advanced data analysis methods, could have broad applications in mass spectrometry imaging applications.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Quantum Electrodynamics Coupled-Cluster at Scale: High-Performance Implementation for Complex Systems

Coupled-cluster theory (CC) is a highly accurate and versatile method for simulating complex interactions within quantum systems. The extension of CC theory to model mixed electron-photon processes with quantum electrodynamics (QED) has improved our capability to predict cavity-modified chemistry, a field where photons are used as cost-effective and eco-friendly alternatives to catalyze/inhibit chemical reactions. However, calculations with CC methods, even without incorporating QED effects, are often prohibitively expensive. Simulations of larger systems require scalable infrastructures that exist for traditional CC methods but not for QED-CC methods. As such, we present a GPU-enabled, high-performance, open-source implementation of the quantum electrodynamics coupled-cluster method with single and double excitations (QED-CCSD) within the ExaChem quantum chemistry software package. ExaChem relies on the Tensor Algebra for Many-body Methods (TAMM) infrastructure: a parallel heterogeneous tensor library designed to achieve scalable performance on modern heterogeneous supercomputing platforms. Furthermore, we discuss theoretical foundations, algorithmic details, and numerical benchmarks to showcase the larger systems that ExaChem can simulate and how the integration of photonic degrees-of-freedom alters their ground-state properties.

Basis sets↗

Vertically oriented arrays of ReS 2 nanosheets for electrochemical energy storage and electrocatalysis

Here, transition-metal dichalcogenide (TMD) nanolayers show potential as high-performance catalysts in energy conversion and storage devices. Synthetic TMDs produced by chemical-vapor deposition (CVD) methods tend to grow parallel to the growth substrate. Here, we show that with the right precursors and appropriate tuning of the CVD growth conditions, ReS 2 nanosheets can be made to orient perpendicular to the growth substrate. This accomplishes two important objectives; first, it drastically increases the wetted or exposed surface area of the ReS 2 sheets, and second, it exposes the sharp edges and corners of the ReS 2 sheets. We show that these structural features of the vertically grown ReS 2 sheets can be exploited to significantly improve their performance as polysulfide immobilizers and electrochemical catalysts in lithium–sulfur (Li–S) batteries and in hydrogen evolution reactions (HER). After 300 cycles, the specific capacity of the Li–S battery with vertical ReS 2 catalyst is retained above 750 mA h g –1 , with only ~0.063% capacity decay per cycle, much better than the baseline battery (without ReS 2 ), which shows ~0.184% capacity decay per cycle under the same test conditions. As a HER catalyst, the vertical ReS 2 provides very small onset overpotential (<100 mV) and an exceptional exchange-current density (~67.6 μA/cm 2 ), which is vastly superior to the baseline electrode without ReS 2 .

2D materials↗

Quantum annealing algorithms for Boolean tensor networks

Abstract Quantum annealers manufactured by D-Wave Systems, Inc., are computational devices capable of finding high-quality heuristic solutions of NP-hard problems. In this contribution, we explore the potential and effectiveness of such quantum annealers for computing Boolean tensor networks. Tensors offer a natural way to model high-dimensional data commonplace in many scientific fields, and representing a binary tensor as a Boolean tensor network is the task of expressing a tensor containing categorical (i.e., $$\{0, 1\}$$ { 0 , 1 } ) values as a product of low dimensional binary tensors. A Boolean tensor network is computed by Boolean tensor decomposition, and it is usually not exact. The aim of such decomposition is to minimize the given distance measure between the high-dimensional input tensor and the product of lower-dimensional (usually three-dimensional) tensors and matrices representing the tensor network. In this paper, we introduce and analyze three general algorithms for Boolean tensor networks: Tucker, Tensor Train, and Hierarchical Tucker networks. The computation of a Boolean tensor network is reduced to a sequence of Boolean matrix factorizations, which we show can be expressed as a quadratic unconstrained binary optimization problem suitable for solving on a quantum annealer. By using a novel method we introduce called parallel quantum annealing, we demonstrate that Boolean tensor’s with up to millions of elements can be decomposed efficiently using a DWave 2000Q quantum annealer.

97 MATHEMATICS AND COMPUTING↗

Accurate modeling and inversion of electrical resistivity data in the presence of metallic infrastructure with known location and dimension

Electrical resistivity tomography (ERT) has been widely used in environmental applications to study processes associated with subsurface contaminants and contaminant remediation. Anthropogenic alterations in subsurface electrical conductivity associated with contamination often originate from highly industrialized areas with significant amounts of buried metallic infrastructure. The deleterious influence of such infrastructure on imaging results generally limits the utility of ERT where it might otherwise prove useful for subsurface investigation and monitoring. In this manuscript we present a method of accurately modeling the effects of buried conductive infrastructure within the forward modeling algorithm, thereby removing them from the inversion results. The method is implemented in parallel using immersed interface boundary conditions, whereby the global solution is reconstructed from a series of well-conditioned partial solutions. Forward modeling accuracy is demonstrated by comparison with analytic solutions. Synthetic imaging examples are used to investigate imaging capabilities within a subsurface containing electrically conductive buried tanks, transfer piping, and well casing, using both well casings and vertical electrode arrays as current sources and potential measurement electrodes. Results show that, although accurate infrastructure modeling removes the dominating influence of buried metallic features, the presence of metallic infrastructure degrades imaging resolution compared to standard ERT imaging. However, accurate imaging results may be obtained if electrodes are appropriately located.

imaging↗

Multilevel Parareal Algorithm with Averaging for Oscillatory Problems

The present study is an extension of the work done by Peddle, Haut, and Wingate and Haut and Wingate, where a two-level Parareal method with mapping and averaging is examined. The method proposed in this paper is a multilevel Parareal method with arbitrarily many levels, which is not restricted to the two-level case. We give an asymptotic error estimate which reduces to the two-level estimate for the case when only two levels are considered. Introducing more than two levels has important consequences for the averaging procedure, as we choose separate averaging windows for each of the different levels, which is an additional new feature of the present study. The different averaging windows make the proposed method especially appropriate for nonlinear multiscale problems, because we can introduce a level for each intrinsic scale of the problem and adapt the averaging procedure such that we reproduce the behavior of the model on the particular scale resolved by the level. The method is applied to nonlinear differential equations. The nonlinearities can generate a range of frequencies in the problem. The computational cost of the new method is investigated and studied on several examples.

97 MATHEMATICS AND COMPUTING↗

Parallel implementation and performance optimization of the configuration-interaction method

The configuration-interaction (CI) method, long a popular approach to describe quantum many-body systems, is cast as a very large sparse matrix eigenpair problem with matrices whose dimension can exceed one billion. Such formulations place high demands on memory capacity and memory bandwidth - - two quantities at a premium today. In this paper, we describe an efficient, scalable implementation, BIGSTICK, which, by factorizing both the basis and the interaction into two levels, can reconstruct the nonzero matrix elements on the fly, reduce the memory requirements by one or two orders of magnitude, and enable researchers to trade reduced resources for increased computational time. We optimize BIGSTICK on two leading HPC platforms - - the Cray XC30 and the IBM Blue Gene/Q. Specifically, we not only develop an empirically-driven load balancing strategy that can evenly distribute the matrix-vector multiplication across 256K threads, we also developed techniques that improve the performance of the Lanczos reorthogonalization. Combined, these optimizations improved performance by 1.3-8× depending on platform and configuration.

97 MATHEMATICS AND COMPUTING↗

Numerical eigen-spectrum slicing, accurate orthogonal eigen-basis, and mixed-precision eigenvalue refinement using OpenMP data-dependent tasks and accelerator offload

Performing a variety of numerical computations efficiently and, at the same time, in a portable fashion requires both an overarching design followed by a number of implementation strategies. All of these are exemplified below as we present transitioning the PLASMA numerical library from relying on dependence-driven large tasks to achieving utilization of fine grain tasking and offload to hardware accelerators while keeping its core dependence sets: OpenMP source code pragmas and runtime for most system-level functionality and basic low-level numerical kernels provided directly by hardware vendors or open source projects with vendor contributions. We also present new algorithmic methods and their efficient parallel implementations including fine grained tasking for eigen-spectrum slicing and offload for mixed-precision eigenvalue refinement. We provide performance, scaling, and numerical results showing sizable gains over the available solutions from either the open source and vendor-provided packages.

Luszczek, Piotr↗

High-Throughput Discovery of Robust Metal-Organic Frameworks for CO 2 Capture (Final Report)

The goal of the project is to develop and utilize high-throughput instrumentation for the discovery of robust, cost-effective metal-organic frameworks for the efficient capture of CO 2 from power plant flue gas. To this end, we have used highly-parallel and automated synthesize methods to accelerate the discovery of new MOF structures and their optimized synthesis and activation routes. To be able to rapidly screen these new materials for their potential CO 2 capture performance, we have developed high-throughput structural characterization instruments and gas adsorption instruments. To guide the materials choice and design, we have also developed computational tools to analyze the life cycle and sorbent performance of existing and hypothetical materials.

36 MATERIALS SCIENCE↗

Predictive Modeling of Aging and Degradation of Materials in Extreme Environments.

In order to accurately describe defect accumulation in heterogeneous microstructures and under complex irradiation conditions, simulation methods are needed that can explicitly account for the effect of nonhomogeneous microstructures on damage accumulation. In this project, an advanced simulation tool called spatially resolved stochastic cluster dynamics (SRSCD) is developed for this purpose. The proposed approach relies on solving spatially resolved coupled rate equations of standard cluster dynamics methods in a kinetic Monte Carlo scheme. Large-scale simulations of radiation damage in polycrystalline materials are enabled through several improvements made to this method, including a pseudo-adaptive meshing scheme for cascade implantation and implementation of this method in a synchronous parallel kinetic Monte Carlo framework.

36 MATERIALS SCIENCE↗

Conduct of the International Multigrid Conference

The 1983 International Multigrid Conference was held at Colorado's Copper Mountain Ski Resort, April 5-8. It was organized jointly by the Institute for Computational Studies at Colorado State University, U.S.A., and the Gasellschaft fur Mathematik und Datenverarbeitung Bonn, F.R. Germany, and was sponsored by the Air Force Office of Sponsored Research and National Aeronautics and Space Administration Headquarters. The conference was attended by 80 scientists, divided by institution almost equally into private industry, research laboratories, and academia. Fifteen attendees came from countries other than the U.S.A. In addition to the fruitful discussions, the most significant factor of the conference was of course the lectures. The lecturers include most of the leaders in the field of multigrid research. The program offered a nice integrated blend of theory, numerical studies, basic research, and applications. Some of the new areas of research that have surfaced since the Koln-Porz conference include: the algebraic multigrid approach; multigrid treatment of Euler equations for inviscid fluid flow problems; 3-D problems; and the application of MG methods on vector and parallel computers.

Mccormick, S.↗

A system for routing arbitrary directed graphs on SIMD architectures

There are many problems which can be described in terms of directed graphs that contain a large number of vertices where simple computations occur using data from connecting vertices. A method is given for parallelizing such problems on an SIMD machine model that is bit-serial and uses only nearest neighbor connections for communication. Each vertex of the graph will be assigned to a processor in the machine. Algorithms are given that will be used to implement movement of data along the arcs of the graph. This architecture and algorithms define a system that is relatively simple to build and can do graph processing. All arcs can be transversed in parallel in time O(T), where T is empirically proportional to the diameter of the interconnection network times the average degree of the graph. Modifying or adding a new arc takes the same time as parallel traversal.

Tomboulian, Sherryl↗