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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 OSTI2023

Tech-X contributions to the Center for Tokamak Transients (CTTS) Scientific Discovery through Advanced Computing (SciDAC) project (Final Report)

The Center for Tokamak Transients Simulations (CTTS) consists of computational plasma physicists, computer scientists, and applied mathematicians who are together developing and applying simulation software to improve our understanding of and ability to predict and control transient events in tokamak discharges, particularly those that lead to violent disruptions. We have major simulation activities concerning disruptions that are caused by violating ideal MHD stability criteria, vertical displacement events, resistive wall modes, and tearing modes. We are performing comprehensive modeling of disruption mitigation techniques, particularly by shattered pellet injection (SPI). The Center is built around two mature extended MHD codes: NIMROD and M3D-C1. These codes are being extended in a number of ways as required by the demands of disruption modeling, and are being optimized to work well for larger problem size and modern computer architectures as required to model tokamak plasmas with realistic parameters over the required timescales. The codes will be coupled to the FronTier code for state-of-the-art modeling of SPI. Validation with experimental data on DIII-D, NSTX, and JET is being facilitated by rigorous uncertainty quantification (UQ). The high-level objectives of the center are to: (1) Develop better understanding and improved predictive capability of when crossing a linear stability boundary will likely lead to a disruption, (2) Provide a tool for calculating vessel forces, both axisymmetric and non-axisymmetric, for worst case VDE and other disruptions in tokamaks, (3) Develop increased understanding and improved predictive capability for locked mode disruptions and how best to avoid them, (4) Develop, verify, and validate 3D models for disruption mitigation by shattered pellets that can be used to design and optimize a system for future tokamaks, and (5) Increase the efficiency and scalability of the M3D-C1 and NIMROD codes so that they can model disruptions in ITER scale devices using the most powerful DOE HPC hardware, and (6) Demonstrate code-coupling via FronTier coupling with NIMROD and M3D-C1 and by interfacing these codes within a WDM framework.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2013

LANL CSSE L2: Case Study of In Situ Data Analysis in ASC Integrated Codes [Slides]

The massive, complex datasets generated by scientific simulations on next-generation computer architectures at extreme scale pose new challenges for data management and scientific understanding. A critical element in meeting these new challenges is in situ data analysis where information is reduced and analyzed as close to the point of generation as possible, for example, at run time or as the data stream to longer term storage. This milestone will demonstrate in situ data analysis in xRAGE, an ASC Eulerian Radiation Hydrodynamics code. We will work with the Eulerian Applications Project to identify target problems that will exercise physics of interest to the program, and we will work closely with users to maximize the achieved usability and productivity improvements. We will investigate enhancements to the in situ process that enable and improve techniques of data reduction and data triage in addition to improving in situ performance by using portable acceleration technology. We will report on their viability and performance in xRAGE or another ASC code. These products will provide ASC IC developers with reference codes and tools that will benefit DSW by advancing the technology for predictive science at extreme scales.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2022

Compressed basis GMRES on high-performance graphics processing units

Krylov methods provide a fast and highly parallel numerical tool for the iterative solution of many large-scale sparse linear systems. To a large extent, the performance of practical realizations of these methods is constrained by the communication bandwidth in current computer architectures, motivating the investigation of sophisticated techniques to avoid, reduce, and/or hide the message-passing costs (in distributed platforms) and the memory accesses (in all architectures). This article leverages Ginkgo’s memory accessor in order to integrate a communication-reduction strategy into the (Krylov) GMRES solver that decouples the storage format (i.e., the data representation in memory) of the orthogonal basis from the arithmetic precision that is employed during the operations with that basis. Given that the execution time of the GMRES solver is largely determined by the memory accesses, the cost of the datatype transforms can be mostly hidden, resulting in the acceleration of the iterative step via a decrease in the volume of bits being retrieved from memory. Together with the special properties of the orthonormal basis (whose elements are all bounded by 1), this paves the road toward the aggressive customization of the storage format, which includes some floating-point as well as fixed-point formats with mild impact on the convergence of the iterative process. We develop a high-performance implementation of the “compressed basis GMRES” solver in the Ginkgo sparse linear algebra library using a large set of test problems from the SuiteSparse Matrix Collection. We demonstrate robustness and performance advantages on a modern NVIDIA V100 graphics processing unit (GPU) of up to 50% over the standard GMRES solver that stores all data in IEEE double-precision.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2023

On the use of a multigrid-reduction-in-time algorithm for multiscale convergence of turbulence simulations

Simulations of turbulent flow present challenges in terms of accuracy and affordability on modern highly-parallel computer architectures. A multigrid-reduction-in-time algorithm is used to provide a framework for separately evolving different scales of turbulence and for parallelizing the temporal domain, thereby increasing the concurrency. It is hypothesized that the space–time locality of the small scales of turbulence can be used to circumvent difficulties in applying temporal multigrid to flows dominated by inertial physics. For algorithms that fall well short of spectral accuracy (fourth-order is used in this work) attention must be paid to the accuracy of features on scales transferred between multigrid levels. Numerical experiments were performed using implicit large-eddy simulation. Results from applying the approach to an infinite-Reynolds number Taylor–Green flow and a double-shear flow at a Reynolds number of 11650 provide strong evidence that the approach has merit. The multigrid-reduction-in-time framework can be used to parallelize the temporal domain of a high-Reynolds-number turbulent flow and permit independent convergence of different scales. Establishing this foundation allows for future research in reducing the wall-clock time to solve turbulent flows while retaining the same accuracy as sequential solvers. In conclusion, current performance results from parallelizing the temporal domain are not competitive with those from sequential-in-time methods.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2017

Multigrid Reduction in Time for Nonlinear Parabolic Problems: A Case Study

The need for parallelism in the time dimension is being driven by changes in computer architectures, where performance increases are now provided through greater concurrency, not faster clock speeds. This creates a bottleneck for sequential time marching schemes because they lack parallelism in the time dimension. Multigrid reduction in time (MGRIT) is an iterative procedure that allows for temporal parallelism by utilizing multigrid reduction techniques and a multilevel hierarchy of coarse time grids. MGRIT has been shown to be effective for linear problems, with speedups of up to 50 times. The goal of this work is the efficient solution of nonlinear problems with MGRIT, where efficiency is defined as achieving similar performance when compared to an equivalent linear problem. The benchmark nonlinear problem is the p-Laplacian, where p=4 corresponds to a well-known nonlinear diffusion equation and p=2 corresponds to the standard linear diffusion operator, our benchmark linear problem. The key difficulty encountered is that the nonlinear time-step solver becomes progressively more expensive on coarser time levels as the time-step size increases. To overcome such difficulties, multigrid research has historically targeted an accumulated body of experience regarding how to choose an appropriate solver for a specific problem type. To that end, this paper develops a library of MGRIT optimizations and modifications, most important an alternate initial guess for the nonlinear time-step solver and delayed spatial coarsening, that will allow many nonlinear parabolic problems to be solved with parallel scaling behavior comparable to the corresponding linear problem.

parareal↗
DOE OSTI2022

Applications and Techniques for Fast Machine Learning in Science

In this community review report, we discuss applications and techniques for fast machine learning (ML) in science—the concept of integrating powerful ML methods into the real-time experimental data processing loop to accelerate scientific discovery. The material for the report builds on two workshops held by the Fast ML for Science community and covers three main areas: applications for fast ML across a number of scientific domains; techniques for training and implementing performant and resource-efficient ML algorithms; and computing architectures, platforms, and technologies for deploying these algorithms. We also present overlapping challenges across the multiple scientific domains where common solutions can be found. This community report is intended to give plenty of examples and inspiration for scientific discovery through integrated and accelerated ML solutions. This is followed by a high-level overview and organization of technical advances, including an abundance of pointers to source material, which can enable these breakthroughs.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2016

Multigrid Reduction in Time for Nonlinear Parabolic Problems

The need for parallel-in-time is being driven by changes in computer architectures, where future speed-ups will be available through greater concurrency, but not faster clock speeds, which are stagnant.This leads to a bottleneck for sequential time marching schemes, because they lack parallelism in the time dimension. Multigrid Reduction in Time (MGRIT) is an iterative procedure that allows for temporal parallelism by utilizing multigrid reduction techniques and a multilevel hierarchy of coarse time grids. MGRIT has been shown to be effective for linear problems, with speedups of up to 50 times. The goal of this work is the efficient solution of nonlinear problems with MGRIT, where efficient is defined as achieving similar performance when compared to a corresponding linear problem. As our benchmark, we use the p-Laplacian, where p = 4 corresponds to a well-known nonlinear diffusion equation and p = 2 corresponds to our benchmark linear diffusion problem. When considering linear problems and implicit methods, the use of optimal spatial solvers such as spatial multigrid imply that the cost of one time step evaluation is fixed across temporal levels, which have a large variation in time step sizes. This is not the case for nonlinear problems, where the work required increases dramatically on coarser time grids, where relatively large time steps lead to worse conditioned nonlinear solves and increased nonlinear iteration counts per time step evaluation. This is the key difficulty explored by this paper. We show that by using a variety of strategies, most importantly, spatial coarsening and an alternate initial guess to the nonlinear time-step solver, we can reduce the work per time step evaluation over all temporal levels to a range similar with the corresponding linear problem. This allows for parallel scaling behavior comparable to the corresponding linear problem.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2015

RELAP-7 Development Updates

RELAP-7 is a nuclear systems safety analysis code being developed at the Idaho National Laboratory, and is the next generation tool in the RELAP reactor safety/systems analysis application series. RELAP-7 development began in 2011 to support the Risk Informed Safety Margins Characterization (RISMC) Pathway of the Light Water Reactor Sustainability (LWRS) program. The overall design goal of RELAP-7 is to take advantage of the previous thirty years of advancements in computer architecture, software design, numerical methods, and physical models in order to provide capabilities needed for the RISMC methodology and to support nuclear power safety analysis. The code is being developed based on Idaho National Laboratory’s modern scientific software development framework – MOOSE (the Multi-Physics Object-Oriented Simulation Environment). The initial development goal of the RELAP-7 approach focused primarily on the development of an implicit algorithm capable of strong (nonlinear) coupling of the dependent hydrodynamic variables contained in the 1-D/2-D flow models with the various 0-D system reactor components that compose various boiling water reactor (BWR) and pressurized water reactor nuclear power plants (NPPs). During Fiscal Year (FY) 2015, the RELAP-7 code has been further improved with expanded capability to support boiling water reactor (BWR) and pressurized water reactor NPPs analysis. The accumulator model has been developed. The code has also been coupled with other MOOSE-based applications such as neutronics code RattleSnake and fuel performance code BISON to perform multiphysics analysis. A major design requirement for the implicit algorithm in RELAP-7 is that it is capable of second-order discretization accuracy in both space and time, which eliminates the traditional first-order approximation errors. The second-order temporal is achieved by a second-order backward temporal difference, and the one-dimensional second-order accurate spatial discretization is achieved with the Galerkin approximation of Lagrange finite elements. During FY-2015, we have done numerical verification work to verify that the RELAP-7 code indeed achieves 2nd-order accuracy in both time and space for single phase models at the system level.

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗
DOE OSTI2016

RELAP-7 Pressurizer Component Development Updates

RELAP-7 is a nuclear systems safety analysis code being developed at the Idaho National Laboratory (INL). RELAP-7 development began in 2011 to support the Risk Informed Safety Margins Characterization (RISMC) Pathway of the Light Water Reactor Sustainability (LWRS) program. The overall design goal of RELAP-7 is to take advantage of the previous thirty years of advancements in computer architecture, software design, numerical methods, and physical models in order to provide capabilities needed for the RISMC methodology and to support nuclear power safety analysis. The code is being developed based on Idaho National Laboratory’s modern scientific software development framework – MOOSE (the Multi-Physics Object-Oriented Simulation Environment). The initial development goal of the RELAP-7 approach focused primarily on the development of an implicit algorithm capable of strong (nonlinear) coupling of the dependent hydrodynamic variables contained in the 1-D/2-D flow models with the various 0-D system reactor components that compose various boiling water reactor (BWR) and pressurized water reactor nuclear power plants (NPPs). As part of the efforts to expand the capability for PWR simulation, an equilibrium single-region pressurizer model has been implemented in RELAP-7. The pressurizer component can simulate pressure and water level change through insurge, spray, and heating processes. Two simple tests – one for insurge process and another for outsurge process – have been reported to demonstrate and verify the functions of the pressurizer model. The typical single-phase PWR system model presented in the first RELAP-7 milestone report has been updated, as part of system level test for the new pressurizer model. The updated PWR system model with the pressurizer component can be used for more realistic transient simulations. The addition of the equilibrium single-region pressurizer model represents the first step of developing a suite of pressurizer models with different levels of fidelities. Non-equilibrium two-region two-zone model and non-equilibrium five-region three zone model will be implemented in the near future. Cross comparison and validation will be pursued when higher fidelity pressurizer models are completed.

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗
DOE OSTI2018

A Porphyrin Spin Qubit and Its 2D Framework Nanosheets

Abstract Molecular spin qubits have been shown to reach sufficiently long quantum coherence times to envision their use as hardware in quantum processors. These will however require their implementation in hybrid solid‐state devices for which the controlled localization and homogeneous orientation of the molecular qubits will be necessary. An alternative to isolated molecules that can ensure these key aspects is 2D framework in which the qubit would act as node. In this work, it is demonstrated that the isolated metalloporphyrin [Cu(H 4 TCPP)] molecule is a potential spin qubit, and maintains similar quantum coherence as node in a 2D [{CuTCPP}Zn 2 (H 2 O) 2 ] metal–organic framework. Mono‐ and multilayer deposits of nanosheets of a similar 2D framework are then successfully formed following a modular method based on Langmuir–Schaefer conditions. The orientation of the {CuTCPP} qubit nodes in these nanosheets is homogeneous parallel to the substrate. These nanosheets are also formed with a control over the qubit concentration, i.e., by dilution with the unmetallated porphyrin. Eventually, 2D nanosheets are formed in situ directly on a substrate, through a simple protocol devised to reproduce the Langmuir–Schaefer conditions locally. Altogether these studies show that 2D spin qubit frameworks are ideal components to develop a hybrid quantum computing architecture.

Urtizberea, Ainhoa↗
DOE OSTI2019

Toward Chirality-Encoded Domain Wall Logic

Nonvolatile logic networks based on spintronic and nanomagnetic technologies have the possibility to create high-speed, ultralow power computational architectures. This work investigates the feasibility of “chirality-encoded domain wall logic,” a nanomagnetic logic architecture where data are encoded by the chiral structures of mobile domain walls in networks of ferromagnetic nanowires and processed by the chiral structures' interactions with geometric features of the networks. High-resolution magnetic imaging is used to test two critical functionalities: the inversion of domain wall chirality at tailored artificial defect sites (logical NOT gates) and the chirality-selective output of domain walls from 2-in-1-out nanowire junctions (common operation to AND/NAND/OR/NOR gates). The measurements demonstrate both operations can be performed to a good degree of fidelity even in the presence of complex magnetization dynamics that would normally be expected to destroy chirality-encoded information. Together, these results represent a strong indication of the feasibility of devices where chiral magnetization textures are used to directly carry, rather than merely delineate, data.

36 MATERIALS SCIENCE↗
DOE OSTI2026

Spatiotemporal Thermal Coupling in VO 2 Device Arrays

Correlated oxides such as VO 2 exhibit an electrically driven insulator–metal transition (IMT) that underlies their promise for neuromorphic and memory devices. Yet the IMT is not a uniform bulk process but a spatiotemporal phenomenon in which local heating nucleates filaments, contracts or dissolves them with the electric field, and couples to the environment. In this work, we directly image the VO 2 IMT dynamics by mid-wave infrared, thermography synchronized with electrical transport, resolving device temperature with micrometer spatial and microsecond temporal resolution. At the single-device level, we capture the full cycle of filament nucleation, contraction, and relaxation during current/voltage-driven resistive switching. At the array level, we show that heat propagates across etched gaps with an effective length scale of ∼131 µm, enabling cooperative behaviors among electrically isolated devices. Short-range distanced devices exhibit mutual filament attraction and sequential dissolution, while long-range distanced devices differentiate into distinct roles: drivers that initiate switching, cooperative responders that undergo assisted self-oscillations, and passive reporters that record the thermal field. Furthermore, these results reframe thermal crosstalk, long regarded as parasitic, as an intrinsic coupling channel and design principle for organizing collective switching behaviors, with direct implications for emergent circuit functionality in neuromorphic and unconventional computing architectures.

coupling↗
DOE OSTI2021

Dynamic Symmetry Breaking in Chiral Magnetic Systems

The Dzyaloshinskii–Moriya interaction (DMI) in magnetic systems stabilizes spin textures with preferred chirality, applicable to next-generation memory and computing architectures. In perpendicularly magnetized heavy-metal/ferromagnet films, the interfacial DMI originating from structural inversion asymmetry and strong spin-orbit coupling favors chiral Néel-type domain walls (DWs) whose energetics and mobility remain at issue. Thus, a new effect is characterized in which domains expand unidirectionally in response to a combination of out-of-plane and in-plane magnetic fields, with the growth direction controlled by the in-plane field strength. These growth directionalities and symmetries with applied fields cannot be understood from static treatments alone. The authors theoretically demonstrate that perpendicular field torques stabilize steady-state magnetization profiles highly asymmetric in elastic energy, resulting in a dynamic symmetry breaking consistent with the experimental findings. This phenomenon sheds light on the mechanisms governing the dynamics of Néel-type DWs and expands the utility of field-driven DW motion to probe and control chiral DWs.

36 MATERIALS SCIENCE↗
DOE OSTI2019

Stochastic density functional theory

Linear-scaling implementations of density functional theory (DFT) reach their intended efficiency regime only when applied to systems having a physical size larger than the range of their Kohn–Sham density matrix (DM). This causes a problem since many types of large systems of interest have a rather broad DM range and are therefore not amenable to analysis using DFT methods. For this reason, the recently proposed stochastic DFT (sDFT), avoiding exhaustive DM evaluations, is emerging as an attractive alternative linear-scaling approach. This review develops a general formulation of sDFT in terms of a (non)orthogonal basis representation and offers an analysis of the statistical errors (SEs) involved in the calculation. Using a new Gaussian-type basis-set implementation of sDFT, applied to water clusters and silicon nanocrystals, it demonstrates and explains how the standard deviation and the bias depend on the sampling rate and the system size in various types of calculations. We also develop a basis-set embedded-fragments theory, demonstrating its utility for reducing the SEs for energy, density of states and nuclear force calculations. Finally, we discuss the algorithmic complexity of sDFT, showing it has CPU wall-time linear-scaling. Lastly, the method parallelizes well over distributed processors with good scalability and therefore may find use in the upcoming exascale computing architectures.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2014

Performance Tuning of Fock Matrix and Two-Electron Integral Calculations for NWChem on Leading HPC Platforms

Attaining performance in the evaluation of two-electron repulsion integrals and constructing the Fock matrix is of considerable importance to the computational chemistry community. Due to its numerical complexity improving the performance behavior across a variety of leading supercomputing platforms is an increasing challenge due to the significant diversity in high-performance computing architectures. In this paper, we present our successful tuning methodology for these important numerical methods on the Cray XE6, the Cray XC30, the IBM BG/Q, as well as the Intel Xeon Phi. Our optimization schemes leverage key architectural features including vectorization and simultaneous multithreading, and results in speedups of up to 2.5x compared with the original implementation.

Shan, Hongzhan↗
DOE OSTI2015

On the Design, Development, and Analysis of Optimized Matrix-Vector Multiplication Routines for Coprocessors

The manycore paradigm shift, and the resulting change in modern computer architectures, has made the development of optimal numerical routines extremely challenging. In this work, we target the development of numerical algorithms and implementations for Xeon Phi coprocessor architecture designs. In particular, we examine and optimize the general and symmetric matrix-vector multiplication routines (gemv/symv), which are some of the most heavily used linear algebra kernels in many important engineering and physics applications. We describe a successful approach on how to address the challenges for this problem, starting with our algorithm design, performance analysis and programing model and moving to kernel optimization. Our goal, by targeting low-level and easy to understand fundamental kernels, is to develop new optimization strategies that can be effective elsewhere for use on manycore coprocessors, and to show significant performance improvements compared to existing state-of-the-art implementations. Therefore, in addition to the new optimization strategies, analysis, and optimal performance results, we finally present the significance of using these routines/strategies to accelerate higher-level numerical algorithms for the eigenvalue problem (EVP) and the singular value decomposition (SVD) that by themselves are foundational for many important applications.

Kabir, Khairul↗
DOE OSTI2016

An inertia-free filter line-search algorithm for large-scale nonlinear programming

We present a filter line-search algorithm that does not require inertia information of the linear system. This feature enables the use of a wide range of linear algebra strategies and libraries, which is essential to tackle large-scale problems on modern computing architectures. The proposed approach performs curvature tests along the search step to detect negative curvature and to trigger convexification. We prove that the approach is globally convergent and we implement the approach within a parallel interior-point framework to solve large-scale and highly nonlinear problems. Our numerical tests demonstrate that the inertia-free approach is as efficient as inertia detection via symmetric indefinite factorizations. We also demonstrate that the inertia-free approach can lead to reductions in solution time because it reduces the amount of convexification needed.

Chiang, Nai-Yuan↗
DOE OSTI2022

Dislocation-Limited Thermal Conductivity in LiF: Revisiting Perturbative Models

We revisit models to describe phonon-dislocation interactions and resulting dislocation-limited thermal conductivity (k), particularly as applied to describe the temperature-dependent k behavior of LiF with significant dislocation densities. Coupling semiempirical models of phonon scattering from dislocation strain fields provided by Klemens and Carruthers with density functional theory description of the phonons and input parameters, we find that both models significantly overpredict the measured k of LiF, as found previously. However, more direct application of the quantum perturbation theory description, from which the models were derived, gives significantly stronger phonon-dislocation scattering and strongly underpredicts the measured k data. We revisit the derivation of phonon-dislocation-strain field scattering and provide numerical details regarding its implementation. This work demonstrates that quantum perturbative calculations, now accessible to modern computational architectures, may provide a reasonable description of dislocation-limited k in materials as governed by phonon-strain field interactions provided that questions regarding the relevant strain field range can be resolved.

36 MATERIALS SCIENCE↗