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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 1,243 records · Page 69
All sourcesNASA NTRSDOE OSTI
DOE OSTI2019

Scalable Bayesian Nonparametric Clustering and Classification

We develop a scalable multi-step Monte Carlo algorithm for inference under a large class of nonparametric Bayesian models for clustering and classification. Each step is “embarrassingly parallel” and can be implemented using the same Markov chain Monte Carlo sampler. The simplicity and generality of our approach makes inference for a wide range of Bayesian nonparametric mixture models applicable to large datasets. Specifically, we apply the approach to inference under a product partition model with regression on covariates. We show results for inference with two motivating data sets: a large set of electronic health records (EHR) and a bank telemarketing dataset. We find interesting clusters and competitive classification performance relative to other widely used competing classifiers. Supplementary materials for this article are available online.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2020

2020 IEEE PES Innovative Smart Grid Technologies Europe (ISGT-Europe)

Recent proliferation of distributed energy sources in distribution or sub-transmission systems necessitates close monitoring of these three-phase power grids which typically operate under unbalanced loading conditions. Unlike the transmission systems where the network equations are commonly based on the positive sequence component models, a detailed three phase model will have to be used in implementing network applications for these systems. In the specific case of the state estimator, where measurement and parameter errors may bias the solution, bad data and parameter error detection algorithms should also be incorporated. Implementing the state estimator and error detection algorithms for three-phase systems impose additional computational burden and modifications to the state estimation code. This paper proposes a practical solution to avoid these issues by using synchronized phasor measurements and modal decoupling. The previously developed parameter error detection algorithm based on the normalized Lagrange multipliers (NLM) test is applied to the measurements independently in each mode in parallel, not only saving CPU time but also avoiding new code development for a three-phase estimator. Different parameter error scenarios are created and tested to verify the effectiveness of the proposed error detection approach.

Khalili, Ramtin↗
DOE OSTI2021

Restoration Strategy for Active Distribution Systems Considering Endogenous Uncertainty in Cold Load Pickup

Cold load pickup (CLPU) phenomenon is identified as the persistent power inrush upon a sudden load pickup after an outage. Under the active distribution system (ADS) paradigm, where distributed energy resources (DERs) are extensively installed, the decreased outage duration can induce a strong interdependence between CLPU pattern and load pickup decisions. In this paper, we propose a novel modelling technique to tractably capture the decision-dependent uncertainty (DDU) inherent in the CLPU process. Subsequently, a two-stage stochastic decision-dependent service restoration (SDDSR) model is constructed, where first stage searches for the optimal switching sequences to decide step-wise network topology, and the second stage optimizes the detailed generation schedule of DERs as well as the energization of switchable loads. Further, to tackle the computational burdens introduced by mixed-integer recourse, the progressive hedging algorithm (PHA) is utilized to decompose the original model into scenario-wise subproblems that can be solved in parallel. The numerical test on modified IEEE 123-node test feeders has verified the efficiency of our proposed SDDSR model and provided fresh insights into the monetary and secure values of DDU quantification.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2016

Fast multipurpose Monte Carlo simulation for proton therapy using multi- and many-core CPU architectures

Purpose: Accuracy in proton therapy treatment planning can be improved using Monte Carlo (MC) simulations. However the long computation time of such methods hinders their use in clinical routine. This work aims to develop a fast multipurpose Monte Carlo simulation tool for proton therapy using massively parallel central processing unit (CPU) architectures. Methods: A new Monte Carlo, called MCsquare (many-core Monte Carlo), has been designed and optimized for the last generation of Intel Xeon processors and Intel Xeon Phi coprocessors. These massively parallel architectures offer the flexibility and the computational power suitable to MC methods. The class-II condensed history algorithm of MCsquare provides a fast and yet accurate method of simulating heavy charged particles such as protons, deuterons, and alphas inside voxelized geometries. Hard ionizations, with energy losses above a user-specified threshold, are simulated individually while soft events are regrouped in a multiple scattering theory. Elastic and inelastic nuclear interactions are sampled from ICRU 63 differential cross sections, thereby allowing for the computation of prompt gamma emission profiles. MCsquare has been benchmarked with the GATE/GEANT4 Monte Carlo application for homogeneous and heterogeneous geometries. Results: Comparisons with GATE/GEANT4 for various geometries show deviations within 2%–1 mm. In spite of the limited memory bandwidth of the coprocessor simulation time is below 25 s for 10{sup 7} primary 200 MeV protons in average soft tissues using all Xeon Phi and CPU resources embedded in a single desktop unit. Conclusions: MCsquare exploits the flexibility of CPU architectures to provide a multipurpose MC simulation tool. Optimized code enables the use of accurate MC calculation within a reasonable computation time, adequate for clinical practice. MCsquare also simulates prompt gamma emission and can thus be used also for in vivo range verification.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2016

Smoothed Particle Hydrodynamic Simulator

This code is a highly modular framework for developing smoothed particle hydrodynamic (SPH) simulations running on parallel platforms. The compartmentalization of the code allows for rapid development of new SPH applications and modifications of existing algorithms. The compartmentalization also allows changes in one part of the code used by many applications to instantly be made available to all applications.

Source record↗
DOE OSTI2024

Evolution of the SLATE linear algebra library

SLATE (Software for Linear Algebra Targeting Exascale) is a distributed, dense linear algebra library targeting both CPU-only and GPU-accelerated systems, developed over the course of the Exascale Computing Project (ECP). While it began with several documents setting out its initial design, significant design changes occurred throughout its development. In some cases, these were anticipated: an early version used a simple consistency flag that was later replaced with a full-featured consistency protocol. In other cases, performance limitations and software and hardware changes prompted a redesign. Sequential communication tasks were parallelized; host-to-host MPI calls were replaced with GPU device-to-device MPI calls; more advanced algorithms such as Communication Avoiding LU and the Random Butterfly Transform (RBT) were introduced. Early choices that turned out to be cumbersome, error prone, or inflexible have been replaced with simpler, more intuitive, or more flexible designs. Applications have been a driving force, prompting a lighter weight queue class, nonuniform tile sizes, and more flexible MPI process grids. Of paramount importance has been building a portable library that works across several different GPU architectures – AMD, Intel, and NVIDIA – while keeping a clean and maintainable codebase. Here we explore the evolving design choices and their effects, both in terms of performance and software sustainability.

Gates, Mark↗
DOE OSTI2016

Introduction to Numerical Methods [Slides]

These are slides for a lecture for the Parallel Computing Summer Research Internship at the National Security Education Center. This gives an introduction to numerical methods. Repetitive algorithms are used to obtain approximate solutions to mathematical problems, using sorting, searching, root finding, optimization, interpolation, extrapolation, least squares regression, Eigenvalue problems, ordinary differential equations, and partial differential equations. Many equations are shown. Discretizations allow us to approximate solutions to mathematical models of physical systems using a repetitive algorithm and introduce errors that can lead to numerical instabilities if we are not careful.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2020

Broadband Characterization and Circuit Model Development of Transmission-Scale Transformers

This report describes broadband measurements of transmission-scale transformers typical in the electric power grid. This work was performed as part of the EMP Resilient Grid LDRD project at Sandia National Laboratories to generate circuit models that can be used for high-altitude electromagnetic pulse (HEMP) coupling simulations and response predictions. The objective of the work was to obtain characterization data of substation yard equipment across a frequency range relevant to HEMP. Vector network analyzer measurements up to 100 MHz were performed on two power transformers at ABB-Hitachi and a single ITEC potential transformer. Custom cable breakouts were designed to interface with the transformer terminals and provide ground connections to the chassis at the base of the transformer bushings. The three-phase terminals of the power transformers were measured as a common mode impedance using a parallel resistive splitter, and the single-phase terminals of the potential transformer were measured directly. A vector fitting algorithm was used to empirically fit circuit models to the resulting two-port networks and input impedances of the measured objects. Simplified circuit representations of the input impedances were also generated to assess the degree of precision needed for high-altitude electromagnetic pulse response predictions, which were performed in Sandia's XYCE circuit simulator platform. HEMP coupling simulations using the transformer models showed significant reduction in the voltage peak and broadening in the pulse width seen at the power transformer compared to the traveling wave voltage. This indicated the importance of the load condition when defining the coupled insult in an electric power substation. Simplified circuit models showed a similar voltage at the transformer with a smoothed waveform. The presence of potential transformers in the simulation did not significantly change the simulated voltage at the power transformer. Single-port input impedance models were also developed to define load conditions when transfer characteristics were not necessary.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2018

The Future of Software and Computing for HEP: Pushing the Boundaries of the Possible

The nature of computing is changing. Driven by the solid state physics of CPU technology, industry is moving to multi-core systems with less memory, power, and memory bandwidth per core. The result is that the pleasantly parallel HEP event processing paradigm has to adjust to this new reality. New techniques such as machine learning and algorithms capable of exploiting vector processors, will be needed. Advances in instrumentation enabling fine-granularity high-precision measurements, have driven a data revolution. In this paper I will capture the needs, and where we are in addressing these data and compute challenges.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2019

Control of Hybrid Power Unit with a Mechanical Transmission in High-Speed Caterpillar Vehicles

Abstract—: The properties of a hybrid power unit in which a mechanical transmission rigidly connects the internal combustion engine to the driving wheels are considered. In this transmission, the torque created by the parallel electric field is summed with the torque generated by the engine in the event of overloading. The control algorithms developed for the electric power prevent its opposition to the mechanical power under any circumstances.

42 ENGINEERING↗
DOE OSTI2016

Models of TCP in high-BDP environments and their experimental validation

In recent years, the computer networking community has seen a steady growth in bandwidth-delay products (BDPs). Several TCP variants were created to combat the shortcomings of legacy TCP when it comes to operation in high-BDP environments. These variants, among which are CUBIC, STCP, and H-TCP, have been extensively studied in some empirical contexts, and some analytical models exist for CUBIC and STCP. However, since these studies have been conducted, BDPs have risen even more, and new bulk data transfer tools have emerged that utilize multiple parallel TCP streams. In view of these new developments, it is imperative to revisit the question: Which congestion control algorithms are best adapted to current networking environments? In order to help resolve this question, we contribute the following: (i) using first principles, we develop a general throughput-prediction framework that takes into account buffer sizes and maximum window constraints; (ii) we validate the models using measurements and achieve low prediction errors; (iii) we note differences in TCP dynamics between two experimental configurations and find one of them to be significantly more deterministic than the other; we also find that CUBIC and H-TCP outperform STCP, especially when multiple streams are used; and (iv) we present preliminary results for modelling multiple TCP streams for CUBIC and STCP.

Vardoyan, G.↗
DOE OSTI2016

Progress In Developing An In-Pile Acoustically Telemetered Sensor Infrastructure

A salient grand challenge for a number of Department of Energy programs such as Fuels Cycle Research and Development ( includes Accident Tolerant Fuel research and the Transient Reactor Test Facility Restart experiments), Light Water Sustainability, and Advanced Reactor Technologies is to enhance our fundamental understanding of fuel and materials behavior under irradiation. Robust and accurate in-pile measurements will be instrumental to develop and validate a computationally predictive multi-scale understanding of nuclear fuel and materials. This sensing technology will enable the linking of fundamental micro-structural evolution mechanisms to the macroscopic degradation of fuels and materials. The in situ sensors and measurement systems will monitor local environmental parameters as well as characterize microstructure evolution during irradiation. One of the major road blocks in developing practical robust, and cost effective in-pile sensor systems, are instrument leads. If a wireless telemetry infrastructure can be developed for in-pile use, in-core measurements would become more attractive and effective. Thus to be successful in accomplishing effective in-pile sensing and microstructure characterization an interdisciplinary measurement infrastructure needs to be developed in parallel with key sensing technology. For the discussion in this research, infrastructure is defined as systems, technology, techniques, and algorithms that may be necessary in the delivery of beneficial and robust data from in-pile devices. The architecture of a system’s infrastructure determines how well it operates and how flexible it is to meet future requirements. The limiting path for the effective deployment of the salient sensing technology will not be the sensors themselves but the infrastructure that is necessary to communicate data from in-pile to the outside world in a non-intrusive and reliable manner. This article gives a high level overview of a promising telemetry infrastructure based on acoustic wireless transmission of data that is being developed and tested by the INL, Penn State and Westinghouse.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2016

ecode - Electron Transport Algorithm Testing v. 1.0

ecode is a Monte Carlo code used for testing algorithms related to electron transport. The code can read basic physics parameters, such as energy-dependent stopping powers and screening parameters. The code permits simple planar geometries of slabs or cubes. Parallelization consists of domain replication, with work distributed at the start of the calculation and statistical results gathered at the end of the calculation. Some basic routines (such as input parsing, random number generation, and statistics processing) are shared with the Integrated Tiger Series codes. A variety of algorithms for uncertainty propagation are incorporated based on the stochastic collocation and stochastic Galerkin methods. These permit uncertainty only in the total and angular scattering cross sections. The code contains algorithms for simulating stochastic mixtures of two materials. The physics is approximate, ranging from mono-energetic and isotropic scattering to screened Rutherford angular scattering and Rutherford energy-loss scattering (simple electron transport models). No production of secondary particles is implemented, and no photon physics is implemented.

Franke, Brian C.↗
DOE OSTI2015

A high-order time-parallel scheme for solving wave propagation problems via the direct construction of an approximate time-evolution operator

Our manuscript demonstrates a technique for efficiently solving the classical wave equation, the shallow water equations, and, more generally, equations of the form ∂u/∂t=Lu∂u/∂t=Lu, where LL is a skew-Hermitian differential operator. The idea is to explicitly construct an approximation to the time-evolution operator exp(τL)exp(τL) for a relatively large time-step ττ. Recently developed techniques for approximating oscillatory scalar functions by rational functions, and accelerated algorithms for computing functions of discretized differential operators are exploited. Principal advantages of the proposed method include: stability even for large time-steps, the possibility to parallelize in time over many characteristic wavelengths and large speed-ups over existing methods in situations where simulation over long times are required. Numerical examples involving the 2D rotating shallow water equations and the 2D wave equation in an inhomogenous medium are presented, and the method is compared to the 4th order Runge–Kutta (RK4) method and to the use of Chebyshev polynomials. The new method achieved high accuracy over long-time intervals, and with speeds that are orders of magnitude faster than both RK4 and the use of Chebyshev polynomials.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2016

A Well-Posed Two Phase Flow Model and its Numerical Solutions for Reactor Thermal-Fluids Analysis

A 7-equation two-phase flow model and its numerical implementation is presented for reactor thermal-fluids applications. The equation system is well-posed and treats both phases as compressible flows. The numerical discretization of the equation system is based on the finite element formalism. The numerical algorithm is implemented in the next generation RELAP-7 code (Idaho National Laboratory (INL)’s thermal-fluids code) built on top of an other INL’s product, the massively parallel multi-implicit multi-physics object oriented code environment (MOOSE). Some preliminary thermal-fluids computations are presented.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗
DOE OSTI2022

Cabana: A Performance Portable Library for Particle-Based Simulations

Particle-based simulations are ubiquitous throughout many fields of computational science and engineering, spanning the atomistic level with molecular dynamics (MD), to mesoscale particle-in-cell (PIC) simulations for solid mechanics, device-scale modeling with PIC methods for plasma physics, and massive N-body cosmology simulations of galaxy structures, with many other methods in between (Hockney & Eastwood, 1989). While these methods use particles to represent significantly different entities with completely different physical models, many low-level details are shared including performant algorithms for short- and/or long-range particle interactions, multi-node particle communication patterns, and other data management tasks such as particle sorting and neighbor list construction. Cabana is a performance portable library for particle-based simulations, developed as part of the Co-Design Center for Particle Applications (CoPA) within the Exascale Computing Project (ECP) (Alexander et al., 2020). The CoPA project and its full development scope, including ECP partner applications, algorithm development, and similar software libraries for quantum MD, is described in (Mniszewski et al., 2021). Cabana uses the Kokkos library for on-node parallelism (Edwards et al., 2014; Trott et al., 2022), enabling simulation on multi-core CPU and GPU architectures, and MPI for GPU-aware, multi-node communication. Cabana provides particle simulation capabilities on almost all current Kokkos backends, including serial execution, OpenMP (including OpenMP-Target for GPUs), CUDA (NVIDIA GPUs), HIP (AMD GPUs), and SYCL (Intel GPUs), providing a clear path for the coming generation of accelerator-based exascale hardware. Cabana builds on Kokkos by providing new particle data structures and particle algorithms resulting in a similar execution policy-based, node-level programming model that is intended to be used in addition to the core Kokkos library within an application. Cabana is designed as an application and physics agnostic, but particle-specific toolkit which can either be used to generate a new application, or to be used as needed in existing applications at various levels of invasiveness including through interfaces that wrap user memory in existing data structures.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2016

A Posteriori Error Analysis of Two-Stage Computation Methods with Application to Efficient Discretization and the Parareal Algorithm

We consider numerical methods for initial value problems that employ a two stage approach consisting of solution on a relatively coarse discretization followed by solution on a relatively fine discretization. Examples include adaptive error control, parallel-in-time solution schemes, and efficient solution of adjoint problems for computing a posteriori error estimates. We describe a general formulation of two stage computations then perform a general a posteriori error analysis based on computable residuals and solution of an adjoint problem. The analysis accommodates various variations in the two stage computation and in formulation of the adjoint problems. We apply the analysis to compute “dual-weighted” a posteriori error estimates, to develop novel algorithms for efficient solution that take into account cancellation of error, and to the Parareal Algorithm. We test the various results using several numerical examples.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2018

Distributed X-ray photon correlation spectroscopy data reduction using Hadoop MapReduce

Multi-speckle X-ray photon correlation spectroscopy (XPCS) is a powerful technique for characterizing the dynamic nature of complex materials over a range of time scales. XPCS has been successfully applied to study a wide range of systems. Recent developments in higher-frame-rate detectors, while aiding in the study of faster dynamical processes, creates large amounts of data that require parallel computational techniques to process in near real-time. Here, an implementation of the multi-tau and two-time autocorrelation algorithms using the Hadoop MapReduce framework for distributed computing is presented. In conclusion, the system scales well with regard to the increase in the data size, and has been serving the users of beamline 8-ID-I at the Advanced Photon Source for near real-time autocorrelations for the past five years.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗