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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 271 records · Page 15

High-performance implementation of Chebyshev filter diagonalization for interior eigenvalue computations

We study Chebyshev filter diagonalization as a tool for the computation of many interior eigenvalues of very large sparse symmetric matrices. In this technique the subspace projection onto the target space of wanted eigenvectors is approximated with filter polynomials obtained from Chebyshev expansions of window functions. After the discussion of the conceptual foundations of Chebyshev filter diagonalization we analyze the impact of the choice of the damping kernel, search space size, and filter polynomial degree on the computational accuracy and effort, before we describe the necessary steps towards a parallel high-performance implementation. Because Chebyshev filter diagonalization avoids the need for matrix inversion it can deal with matrices and problem sizes that are presently not accessible with rational function methods based on direct or iterative linear solvers. To demonstrate the potential of Chebyshev filter diagonalization for large-scale problems of this kind we include as an example the computation of the 10{sup 2} innermost eigenpairs of a topological insulator matrix with dimension 10{sup 9} derived from quantum physics applications.

97 MATHEMATICS AND COMPUTING↗

Parallel Dynamics Simulation Using a Krylov-Schwarz Linear Solution Scheme

Fast dynamics simulation of large-scale power systems is a computational challenge because of the need to solve a large set of stiff, nonlinear differential-algebraic equations at every time step. The main bottleneck in dynamic simulations is the solution of a linear system during each nonlinear iteration of Newton’s method. In this paper, we present a parallel Krylov- Schwarz linear solution scheme that uses the Krylov subspacebased iterative linear solver GMRES with an overlapping restricted additive Schwarz preconditioner. As a result, performance tests of the proposed Krylov-Schwarz scheme for several large test cases ranging from 2,000 to 20,000 buses, including a real utility network, show good scalability on different computing architectures.

24 POWER TRANSMISSION AND DISTRIBUTION↗

BootCMatch: A Software Package for Bootstrap AMG Based on GraphWeighted Matching

This article has two main objectives: one is to describe some extensions of an adaptive Algebraic Multigrid (AMG) method of the form previously proposed by the first and third authors, and a second one is to present a new software framework, named BootCMatch, which implements all the components needed to build and apply the described adaptive AMG both as a stand-alone solver and as a preconditioner in a Krylov method. The adaptive AMG presented is meant to handle general symmetric and positive definite (SPD) sparse linear systems, without assuming any a priori information of the problem and its origin; the goal of adaptivity is to achieve a method with a prescribed convergence rate. The presented method exploits a general coarsening process based on aggregation of unknowns, obtained by a maximum weight matching in the adjacency graph of the system matrix. More specifically, a maximum product matching is employed to define an effective smoother subspace (complementary to the coarse space), a process referred to as compatible relaxation, at every level of the recursive two-level hierarchical AMG process. Results on a large variety of test cases and comparisons with related work demonstrate the reliability and efficiency of the method and of the software.

97 MATHEMATICS AND COMPUTING↗

Efficient shallow Ritz method for 1D diffusion problems

This paper studies the shallow Ritz method for solving the one-dimensional diffusion problem. It is shown that the shallow Ritz method improves the order of approximation dramatically for non-smooth problems. To realize this optimal or nearly optimal order of the shallow Ritz approximation, we develop a damped block Newton (dBN) method that alternates between updates of the linear and non-linear parameters. Per each iteration, the linear and the non-linear parameters are updated by exact inversion and one step of a modified, damped Newton method applied to a reduced non-linear system, respectively. The computational cost of each dBN iteration is $\mathcal{O}$(n). Starting with the non-linear parameters as a uniform partition of the interval, numerical experiments show that the dBN is capable of efficiently moving mesh points to nearly optimal locations. In conclusion, to improve the efficiency of the dBN further, we propose an adaptive damped block Newton (AdBN) method by combining the dBN with the adaptive neuron enhancement (ANE) method [28].

Diffusion problems↗

Reformulating a Gurson-based dynamic damage model and demonstrating improved predictive power and numerical robustness

The original Tepla (TEnsile PLAsticity) ductile damage model, based on the Gurson yield surface, has long been used to model damage evolution and material failure under dynamic loading. Unfortunately, Tepla suffered from mesh sensitivity, numerical instability, and limited predictive capability. Here, we theoretically reformulate Tepla to address these issues. We especially focus on the prediction of porosity, which is the key state variable used for modeling ductile damage, as compared to more easily measured surface velocities, which are at best an indirect measure of damage. Key model changes include separating the viscosity during volumetric void growth from underlying shear strength behavior and switching to an iterative bisection solver. The new Tepla is then calibrated on incipient spall experiments on half-hard copper and tantalum, which demonstrate its ability to simultaneously fit the model to recovered porosity distributions and measured surface velocities, a stringent test. Improved numerical behavior, such as greatly reduced mesh sensitivity, is also shown in those simulations. Finally, the new Tepla model is applied to several high-explosive loaded, sweeping wave experiments, showing the ability of the model to predict behavior on tests with significantly different loading conditions and histories than the calibration data.

36 MATERIALS SCIENCE↗

An improved iterative HDG approach for partial differential equations

Here we propose and analyze an iterative high-order hybridized discontinuous Galerkin (iHDG) discretization for linear partial differential equations. We improve our previous work [45] in several directions: 1) the improved iHDG approach converges in a finite number of iterations for the scalar transport equation; 2) it is unconditionally convergent for both the linearized shallow water system and the convection–diffusion equation; 3) it has improved stability and convergence rates; 4) we uncover a relationship between the number of iterations and time stepsize, solution order, meshsize and the equation parameters. This allows us to choose the time stepsize such that the number of iterations is approximately independent of the solution order and the meshsize; and 5) we provide both strong and weak scalings of the improved iHDG approach up to 16,384 cores. A connection between iHDG and time integration methods such as parareal and implicit/explicit methods are discussed. Extensive numerical results for linear (and nonlinear) PDEs are presented to verify the theoretical findings.

97 MATHEMATICS AND COMPUTING↗

Modeling the asynchronous Jacobi method without communication delays

Asynchronous iterative methods for solving linear systems are gaining renewed interest due to the high cost of synchronization points in massively parallel codes. Historically, theory on asynchronous iterative methods has focused on asymptotic behavior, while the transient behavior remains poorly understood. In this paper, we study a model of the asynchronous Jacobi method without communication delays, which we call simplified asynchronous Jacobi. Simplified asynchronous Jacobi can be used to model asynchronous Jacobi implemented in shared memory or distributed memory with fast communication networks. Our analysis uses the idea of a propagation matrix, which is similar in concept to an iteration matrix. We show that simplified asynchronous Jacobi can continue to reduce the residual when some processes are slower than other processes. We also show that simplified asynchronous Jacobi can converge when synchronous Jacobi does not. We verify our analysis of simplified asynchronous Jacobi using results from asynchronous Jacobi implemented in shared and distributed memory.

97 MATHEMATICS AND COMPUTING↗

Development of a continuous synthesis process for carbamazepine using validated in-line Raman spectroscopy and kinetic modelling for disturbance simulation

Mitigation of failure modes in the continuous synthesis (CS) of a drug substance (DS) has the potential to widen the adoption of continuous manufacturing (CM) technologies by the pharmaceutical industry. Here, this work demonstrates the development of a robust continuous process for the synthesis of carbamazepine (CBZ), an essential medicine as per the World Health Organization (WHO), facilitated by kinetic modelling and monitored by in-line Raman spectroscopy. Accurate kinetic modelling and the use of validated process analytical technology (PAT) models for quantitative measurement were found to play an important role in developing CS of drug substances. Kinetic data for the formation of CBZ from iminostilbene (ISB) were collected by batch reaction sampling and high-performance liquid chromatography (HPLC) analysis. A non-linear solver and iterative method was applied to determine two sets of Arrhenius parameters simultaneously for the reaction system by minimizing the standard error of the model fit. The start-up and dynamic equilibrium stages for the CS of CBZ using a continuous stirred tank reactor (CSTR) were modelled based on the batch kinetic data and employed to optimize conversion and simulate process disturbances. An in-line Raman spectroscopy method was successfully developed, validated, and integrated to determine the concentrations of CBZ and ISB within the operating range for the CS. The CS kinetic model was evaluated experimentally from startup to dynamic equilibrium over 10 residence times with monitoring by HPLC and in-line Raman spectroscopy. The developed kinetic model in tandem with in-line Raman spectroscopy successfully predicted disturbances due to changes in process variables and can serve as a useful tool in the future design of advanced process control strategies for the continuous synthesis of CBZ.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Predictions for Gyro-phase Drift in MDPX

This work assesses the feasibility of observing the gyro-phase drift in the Auburn Magnetized Dusty Plasma Experiment [MDPX, described by Thomas et al., Plasma Phys. Controlled Fusion 54, 124034 (2012)]. The gyro-phase drift arises when a dust grain does not instantaneously reach the in-situ-equilibrium grain charge during gyro-synchronous grain-charge modulation. Koepke et al. [J. Plasma Phys. 79, 1099 (2013)] first suggested using MDPX to observe the gyro-phase drift, and here we use a single-particle trajectory tracker with an iterative velocity solver, using a fixed timestep for grain motion and an adaptive time step for grain charging, to consider all relevant dust grain forces to assess gyro-phase drift arising from gradual inhomogeneity. Additionally, the semi-analytic theory developed by Walker et al. [J. Plasma Phys. 80, 395 (2014)] predicts dust grain motion in abrupt inhomogeneity for MDPX-relevant conditions. We compare three grain-charging models with each other and with the single-particle trajectory tracker and found to predict distinctly different trajectories depending on the treatment of neutral drag and flowing ions. The measurement thresholds for Particle Tracking Velocimetry permit gyro-phase drift detection in MDPX for the abrupt inhomogeneity, given sufficiently large enough UV photoelectron flux (fuv/[n e v the ] > 0.01) and low enough neutral gas pressure (less than one mTorr). The Orbit-Motion-Limited charge model and the charge models developed by Patacchini et al. [Phys. Plasmas 14, 062111 (2007)] and Gatti and Kortshagen [Phys. Rev. E 78, 046402 (2008)] can, in principle, be distinguished by gyro-phase drift in the abrupt inhomogeneity, but large magnetic fields, large UV photoelectron flux, and low neutral gas pressure are required. Gyro-phase drift for a gradual inhomogeneity in the ratio ne/ni, arising from the presence of a radial electric field, is predicted to be undetectable.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

Fast and scalable quantum Monte Carlo simulations of electron-phonon models

We introduce methodologies for highly scalable quantum Monte Carlo simulations of electron-phonon models, and report benchmark results for the Holstein model on the square lattice. The determinant quantum Monte Carlo (DQMC) method is a widely used tool for simulating simple electron-phonon models at finite temperatures, but incurs a computational cost that scales cubically with system size. Alternatively, near-linear scaling with system size can be achieved with the hybrid Monte Carlo (HMC) method and an integral representation of the Fermion determinant. Here, we introduce a collection of methodologies that make such simulations even faster. To combat "stiffness" arising from the bosonic action, we review how Fourier acceleration can be combined with time-step splitting. To overcome phonon sampling barriers associated with strongly-bound bipolaron formation, we design global Monte Carlo updates that approximately respect particle-hole symmetry. To accelerate the iterative linear solver, we introduce a preconditioner that becomes exact in the adiabatic limit of infinite atomic mass. Finally, we demonstrate how stochastic measurements can be accelerated using fast Fourier transforms. Here, these methods are all complementary and, combined, may produce multiple orders of magnitude speedup, depending on model details.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗

Balancing Power Absorption Against Structural Loads With Viscous Drag and Power-Takeoff Efficiency Considerations

The focus of this paper is to balance power absorption against structural loading for a novel fixed-bottom oscillating surge wave energy converter in both regular and irregular wave environments. The power-to-load ratio will be evaluated using pseudospectral control (PSC) to determine the optimum power-takeoff (PTO) torque based on a multiterm objective function. This paper extends the pseudospectral optimal control problem to not just maximize the time-averaged absorbed power but also include measures for the surge-foundation force and PTO torque in the optimization. The objective function may now potentially include three competing terms that the optimizer must balance. Separate weighting factors are attached to the surge-foundation force and PTO control torque that can be used to tune the optimizer performance to emphasize either power absorption or load shedding. To correct the pitch equation of motion, derived from linear hydrodynamic theory, a quadratic-viscous-drag torque has been included in the system dynamics; however, to continue the use of quadratic programming solvers, an iteratively obtained linearized drag coefficient was utilized that provided good accuracy in the predicted pitch motion. Furthermore, the analysis considers the use of a nonideal PTO unit to more accurately evaluate controller performance. The PTO efficiency is not directly included in the objective function but rather the weighting factors are utilized to limit the PTO torque amplitudes, thereby reducing the losses resulting from the bidirectional energy flow through a nonideal PTO. Furthermore, results from PSC show that shedding a portion of the available wave energy can lead to greater reductions in structural loads, peak-to-average power ratio, and reactive power requirement.

16 TIDAL AND WAVE POWER↗

Spectral Equivalence of Low-Order Discretizations for High-Order H(curl) and H(div) Spaces

In this paper, we present spectral equivalence results for high-order tensor product edge- and face-based finite elements for the H(curl) and H(div) function spaces. Specifically, we show for certain choices of shape functions that the mass and stiffness matrices of the high-order elements are spectrally equivalent to those for an assembly of low-order elements on the associated Gauss--Lobatto--Legendre mesh. Based on this equivalence, efficient preconditioners can be designed with favorable computational complexity. Numerical results are presented which confirm the theory and demonstrate the benefits of the equivalence results for overlapping Schwarz preconditioners.

97 MATHEMATICS AND COMPUTING↗

Boltzmann-Electron Model in Aleph.

We apply the Boltzmann-electron model in the electrostatic, particle-in-cell, finite- element code Aleph to a plasma sheath. By assuming a Boltzmann energy distribution for the electrons, the model eliminates the need to resolve the electron plasma fre- quency, and avoids the numerical "grid instability" that can cause unphysical heating of electrons. This allows much larger timesteps to be used than with kinetic electrons. Ions are treated with the standard PIC algorithm. The Boltzmann-electron model re- quires solution of a nonlinear Poisson equation, for which we use an iterative Newton solver (NOX) from the Trilinos Project. Results for the spatial variation of density and voltage in the plasma sheath agree well with an analytic model

Hughes, Thomas Patrick↗

ForTrilinos Design Document

With the development of a Fortran Interface to Trilinos, ForTrilinos, modelers using modern Fortran will be able to provide their codes the capability to use solvers and other capabilities on exascale machines via a straightforward infrastructure that accesses Trilinos. This document outlines what ForTrilinos does and explains briefly how it works. We show it provides a general access to packages via an entry point and uses an xml file from fortran code. With the first release, ForTrilinos will enable Teuchos to take xml parameter lists from Fortran code and set up data structures. It will provide access to linear solvers and eigen solvers. Several examples are provided to illustrate the capabilities in practice. We explain what the user should have already with their code and what Trilinos provides and returns to the Fortran code. We provide information about the build process for ForTrilinos, with a practical example. In future releases, nonlinear solvers, time iteration, advanced preconditioning techniques, and inversion of control (IoC), to enable callbacks to Fortran routines, will be available.

97 MATHEMATICS AND COMPUTING↗

GCAM Regional Tuning: A framework to tune GCAM parameters

GCAM assumptions typically generate scenarios that are designed to be internally consistent and globally coherent. The gcamdata tool which facilitates the compilation of data sets and user assumptions is not well suited to tailoring to specific country or regional realities, sponsor requirements, or perform harmonization for model intercomparison needs. As described in this report, the GCAM Regional Tuning project develops a computational framework that enables users to adjust GCAM parameters, so model outputs match targeted outcomes at user-defined spatial, temporal, and sectoral resolutions. The framework integrates GCAM, gcamdata, and gcamwrapper with a set of flexible “tuning directives” and an iterative numerical solver. Users can define targets (e.g., technology shares in power generation, BEV uptake, sectoral service demands), select tuners that manipulate relevant GCAM parameters (e.g., share weights, cost adders, elasticities), and export tuned parameters as reusable GCAM XML inputs for future runs. We demonstrate the approach and document usage, diagnostics, and known limitations, and we outline potential future directions.

97 MATHEMATICS AND COMPUTING↗

Methods for design and evaluation of integrated hardware/software systems for concurrent computation

Two testbed programming environments to support the evaluation of a large range of parallel architectures have been implemented under the program Parallel Implementation of Scientific Computing Environments (PISCES). The PISCES 1 environment was applied to two areas of aerospace interest: a sparse matrix iterative equation solver and a dynamic scene analysis system. Currently, the NICE/SPAR testbed system for structural analysis is being modified for parallel operation under PISCES 2; the PISCES 1 applications are also being adapted for PISCES 2. A new formal model of concurrent computation has been developed, based on the mathematical system known as H graph semantics together with a timed Petri net model of the parallel aspects of a system.

Pratt, Terrence W.↗