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Results for “high performance and distributed computing”

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 1,081 records · Page 60
All sourcesNASA NTRSDOE OSTI
NASA NTRS1957

Surge-Inception Study in a Two-Spool Turbojet Engine

A two-spool turbojet engine was operated in the Lewis altitude wind tunnel to study the inception of compressor surge. In addition to the usual steady-state pressure and temperature measurements, the compressors were extensively instrumented with fast-response interstage pressure transducers. Thus it was possible to obtain maps for both compressors, pressure oscillations during rotating stall, effects of stall on efficiency, and stage-loading curves. In addition, with the transient measurements, it was possible to record interstage pressures and then compute stage performance during accelerations to the stall limit. Rotating stall was found to exist at low speeds in the outer spool. Although the stall arose from poor flow conditions at the inlet-stage blade tips, the low-energy air moved through the machine from the tip at the inlet to the outer spool to the hub at the inlet to the inner spool. This tip stall ultimately resulted in compressor surge in the mid-speed region, and necessitated inter-compressor air bleed. Interstage pressure measurements during acceleration to the compressor stall limit indicated that rotating stall was not a necessary condition for compressor surge and that, at the critical stall point, the circumferential interstage pressure distribution was uniform. The exit-stage group of the inner spool was first t o stall; then, the stages upstream stalled in succession until the inlet stage of the outer spool was stalled. With a sufficiently high fuel rate, the process repeated with a cycle time of about 0.1 second. It was possible to construct reproducible stage stall lines as a function of compressor speed from the stage stall points of several such compressor surges. This transient stall line was checked by computing the stall line from a steady-state stage-loading curve. Good agreement between the stage stall lines was obtained by these two methods.

Wallner, Lewis E.↗
DOE OSTI2016

Exploiting Thread Parallelism for Ocean Modeling on Cray XC Supercomputers

The incorporation of increasing core counts in modern processors used to build state-of-the-art supercomputers is driving application development towards exploitation of thread parallelism, in addition to distributed memory parallelism, with the goal of delivering efficient high-performance codes. In this work we describe the exploitation of threading and our experiences with it with respect to a real-world ocean modeling application code, MPAS-Ocean. We present detailed performance analysis and comparisons of various approaches and configurations for threading on the Cray XC series supercomputers.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2018

Planning of distributed data production for High Energy and Nuclear Physics

Modern experiments in High Energy and Nuclear Physics heavily rely on distributed computations using multiple computational facilities across the world. One of the essential types of the computations is a distributed data production where petabytes of raw files from a single source has to be processed once (per production campaign) using thousands of CPUs at distant locations and the output has to be transferred back to that source. The data distribution over a large system does not necessary match the distribution of storage, network and CPU capacity. Therefore, bottlenecks may appear and lead to increased latency and degraded performance. In this paper we propose a new scheduling approach for distributed data production which is based on the network flow maximization model. In our approach a central planner defines how much input and output data should be transferred over each network link in order to maximize the computational throughput. Such plans are created periodically for a fixed planning time interval using up-to-date information on network, storage and CPU resources. The centrally created plans are executed in a distributed manner by dedicated services running at participating sites. In conclusion, our simulations based on the log records from the data production framework of the experiment STAR (Solenoid Tracker at RHIC) have shown that the proposed model systematically provides a better performance compared to the simulated traditional techniques.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2018

Asymmetric Cracking in Mar-M247 Alloy Builds During Electron Beam Powder Bed Fusion Additive Manufacturing

In the electron beam powder bed fusion (EB-PBF) process, a substantial number of high-gamma prime Ni-based superalloys are considered as non-printable due to a high propensity to form cracks. In this research, we focused on computational modeling framework to predict solidification-related cracking phenomena in EB-PBF processes. The cracking analysis was performed on cylindrical overhang structures where the cracks are observed only on one side of the part. Comprehensive microstructural characterization correlated the cracking tendency to low-melting point liquid-film formation along columnar grain boundaries with high misorientation angles due to partitioning of alloying elements. Uncoupled numerical thermal and mechanical models were used to rationalize the relationship between process parameters, build geometry, and cracking. The simulations showed asymmetric temperature distributions and associated asymmetric tensile thermal stresses over a cross section due to differences in section modulus and periodic changes in beam scanning directions. Here, the results provide a potential pathway based on spatially varying beam scanning strategies to reduce the cracking tendency during additive manufacturing of complex geometries on the overhang structure in high-gamma prime nickel-based superalloys.

36 MATERIALS SCIENCE↗
DOE OSTI2024

A variance deconvolution estimator for efficient uncertainty quantification in Monte Carlo radiation transport applications

Monte Carlo simulations are at the heart of many high-fidelity simulations and analyses for radiation transport systems. As is the case with any complex computational model, it is important to propagate sources of input uncertainty and characterize how they affect model output. Unfortunately, uncertainty quantification (UQ) is made difficult by the stochastic variability that Monte Carlo transport solvers introduce. The standard method to avoid corrupting the UQ statistics with the transport solver noise is to increase the number of particle histories, resulting in very high computational costs. In this contribution, we propose and analyze a sampling estimator based on the law of total variance to compute UQ variance even in the presence of residual noise from Monte Carlo transport calculations. Here, we rigorously derive the statistical properties of the new variance estimator, compare its performance to that of the standard method, and demonstrate its use on neutral particle transport model problems involving both attenuation and scattering physics. We illustrate, both analytically and numerically, the estimator’s statistical performance as a function of available computational budget and the distribution of that budget between UQ samples and particle histories. We show analytically and corroborate numerically that the new estimator is unbiased, unlike the standard approach, and is more accurate and precise than the standard estimator for the same computational budget.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2025

PHASE: Personalized Head-based Automatic Simulation for Electromagnetic properties in 7T MRI

Accurate and individualized human head models are becoming increasingly important for electromagnetic (EM) simulations. These simulations depend on precise anatomical representations to realistically model electric and magnetic field distributions, particularly when evaluating Specific Absorption Rate (SAR) within safety guidelines. State of the art simulations use the Virtual Population due to limited public resources and the impracticality of manually annotating patient data at scale. Here, this paper introduces Personalized Head-based Automatic Simulation for EM properties (PHASE), an automated open-source toolbox that generates high-resolution, patient-specific head models for EM simulations using paired T1-weighted (T1w) magnetic resonance imaging (MRI) and computed tomography (CT) scans with 14 tissue labels. To evaluate the performance of PHASE models, we conduct semi-automated segmentation and EM simulations on 15 real human patients, serving as the gold standard reference. The PHASE model achieved comparable global SAR and localized SAR averaged over 10 grams of tissue (SAR-10g), demonstrating its potential as a promising tool for generating large-scale human model datasets in the future. The code and models of PHASE toolbox have been made publicly available: https://github.com/hrlblab/PHASE.

Deep learning↗
DOE OSTI2025

Portable Software Environment for Ultrahigh-Resolution ELM Development on GPUs

This paper presents our endeavors in developing the large-scale, ultra-high-resolution E3SM Land Model (uELM), specifically designed for exascale computers furnished with accelerators such as Nvidia GPUs. The uELM is a sophisticated code that substantially relies on High-Performance Computing (HPC) environments, necessitating particular machine and software configurations. To facilitate community-based uELM developments employing GPUs, we have created a portable, standalone software environment preconfigured with uELM input datasets, simulation cases, and source code. This environment, utilizing Docker, encompasses all essential code, libraries, and system software for uELM development on GPUs. It also features a functional unit test framework and an offline model testbed for comprehensive numerical experiments. From a technical perspective, the paper discusses GPU-ready container generations, uELM code management, and input data distribution across computational platforms. Lastly, the paper demonstrates the use of environment for functional unit testing, end-to-end simulation on CPUs and GPUs, and collaborative code development.

E3SM Land Model↗
NASA NTRS2000

Non-Intrusive, Laser-Based Imaging of Jet-A Fuel Injection and Combustion Species in High Pressure, Subsonic Flows

The emphasis of combustion research efforts at NASA Glenn Research Center (GRC) is on collaborating with industry to design and test gas-turbine combustors and subcomponents for both sub- and supersonic applications. These next-generation aircraft combustors are required to meet strict international environmental restrictions limiting emissions. To meet these goals, innovative combustor concepts require operation at temperatures and pressures far exceeding those of current designs. New and innovative diagnostic tools are necessary to characterize these flow streams since existing methods are inadequate. The combustion diagnostics team at GRC has implemented a suite of highly sensitive, nonintrusive optical imaging methods to diagnose the flowfields of these new engine concepts. By using optically accessible combustors and flame-tubes, imaging of fuel and intermediate combustion species via planar laser-induced fluorescence (PLIF) at realistic pressures are now possible. Direct imaging of the fuel injection process through both planar Mie scattering and PLIF methods is also performed. Additionally, a novel combination of planar fuel fluorescence imaging and computational analysis allows a 3-D examination of the flowfield, resulting in spatially and temporally resolved fuel/air volume distribution maps. These maps provide detailed insight into the fuel injection process at actual conditions, thereby greatly enhancing the evaluation of fuel injector performance and other combustion phenomena. Stable species such as CO2, O2, N2, H2O, and hydrocarbons are also investigated by a newly demonstrated 1-D, spontaneous Raman spectroscopic method. This visible wavelength Raman technique allows the acquisition of quantitative, stable species concentration measurements from the flow.

Locke, R. J.↗
NASA NTRS2009

Bio-Inspired Neural Model for Learning Dynamic Models

A neural-network mathematical model that, relative to prior such models, places greater emphasis on some of the temporal aspects of real neural physical processes, has been proposed as a basis for massively parallel, distributed algorithms that learn dynamic models of possibly complex external processes by means of learning rules that are local in space and time. The algorithms could be made to perform such functions as recognition and prediction of words in speech and of objects depicted in video images. The approach embodied in this model is said to be "hardware-friendly" in the following sense: The algorithms would be amenable to execution by special-purpose computers implemented as very-large-scale integrated (VLSI) circuits that would operate at relatively high speeds and low power demands.

Duong, Tuan↗
NASA NTRS2021

LUVOIR-ECLIPS Closed-Loop Adaptive Optics Performance and Contrast Predictions

One of the primary science goals of the Large UV/Optical/Infrared Surveyor (LUVOIR) mission concept is to detect and characterize Earth-like exoplanets orbiting nearby stars with direct imaging. The success of its coronagraph instrument ECLIPS (Extreme Coronagraph for Living Planetary Systems) depends on the ability to stabilize the wavefront from a large segmented mirror such that optical path differences are limited to tens of picometers RMS during an exposure time of a few hours. In order to relax the constraints on the mechanical stability, ECLIPS will be equipped with a wavefront sensing and control (WS\&C) architecture to correct wavefront errors up to temporal frequencies $\gtrsim$1 Hz. These errors may be dominated by spacecraft structural dynamics exciting vibrations at the segmented primary mirror. In this work, we present detailed simulations of the WS\&C system within the ECLIPS instrument and the resulting contrast performance. This study assumes wavefront aberrations based on a finite element model of a simulated telescope with spacecraft structural dynamics. Wavefront residuals are then computed according to a model of the adaptive optics system that includes numerical propagation to simulate a realistic wavefront sensor and an analytical model of the temporal performance. An end-to-end numerical propagation model of ECLIPS is then used to estimate the residual starlight intensity distribution at the science detector. We show that the contrast performance depends strongly on the target star magnitude and the spatio-temporal distribution of wavefront errors from the telescope. In cases with significant vibration, we advocate for the use of laser metrology to mitigate high temporal frequency wavefront errors and increase the mission yield.

Sirbu, Dan↗
DOE OSTI2017

Current Capabilities at SNL for the Integration of Small Modular Reactors onto Smart Microgrids Using Sandia's Smart Microgrid Technology High Performance Computing and Advanced Manufacturing.

Smart grids are a crucial component for enabling the nation’s future energy needs, as part of a modernization effort led by the Department of Energy. Smart grids and smart microgrids are being considered in niche applications, and as part of a comprehensive energy strategy to help manage the nation’s growing energy demands, for critical infrastructures, military installations, small rural communities, and large populations with limited water supplies. As part of a far-reaching strategic initiative, Sandia National Laboratories (SNL) presents herein a unique, three-pronged approach to integrate small modular reactors (SMRs) into microgrids, with the goal of providing economically-competitive, reliable, and secure energy to meet the nation’s needs. SNL’s triad methodology involves an innovative blend of smart microgrid technology, high performance computing (HPC), and advanced manufacturing (AM). In this report, Sandia’s current capabilities in those areas are summarized, as well as paths forward that will enable DOE to achieve its energy goals. In the area of smart grid/microgrid technology, Sandia’s current computational capabilities can model the entire grid, including temporal aspects and cyber security issues. Our tools include system development, integration, testing and evaluation, monitoring, and sustainment.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2019

First principle study of magnetism and vacancy energetics in a near equimolar NiFeMnCr high entropy alloy

We report the results of ab initio calculations of a novel NiFeMnCr high entropy alloy (HEA) with potential applications as a high performance structural material. The bulk and defect property variations due to chemical disordering and magnetic frustration have been studied using both supercell and coherent potential approximation-based techniques. While magnetic frustration due to the presence of multiple 3d transition metals can severely affect the accuracy of vacancy formation energy in first-principles calculations, this effect should be suppressed at intermediate and high temperatures. An efficient approach to evaluate the chemical potential in HEA is constructed and implemented. Vacancy formation energies are computed based on the chemical potential. The statistical distribution of formation energies is weakly dependent upon the chemical identity of the vacancy. On the other hand, the calculated vacancy migration energies show that Fe is more likely to have a large migration barrier than Cr, Mn, or Ni. Finally, atomic-level stresses are computed. A qualitative model to explain the elemental segregation trend in HEA is built upon the atomic-level stress calculation results and provides a reasonable qualitative agreement with ion irradiation experimental data of a NiFeMnCr HEA.

36 MATERIALS SCIENCE↗
DOE OSTI2024

Privacy-Preserving Federated Learning for Science: Challenges and Research Directions

This paper discusses the key challenges and future research directions for privacy-preserving federated learning (PPFL), with a focus on its application to large-scale scientific AI models, in particular, foundation models~(FMs). PPFL enables collaborative model training across distributed datasets while preserving privacy-- an important collaborative approach for science. We discuss the need for efficient and scalable algorithms to address the increasing complexity of FMs, particularly when dealing with heterogeneous clients. In addition, we underscore the need for developing advance privacy-preserving techniques, such as differential privacy, to balance privacy and utility in large FMs emphasizing fairness and incentive mechanisms to ensure equitable participation among heterogeneous clients. Finally, we emphasize the need for a robust software stack supporting scalable and secure PPFL deployments across multiple high-performance computing facilities. We envision that PPFL would play a crucial role to advance scientific discovery and enable large-scale, privacy-aware collaborations across science domains.

Kim, Kibaek [Argonne National Laboratory (ANL)]↗
DOE OSTI2022

Traveler: Navigating Task Parallel Traces for Performance Analysis

Understanding the behavior of software in execution is a key step in identifying and fixing performance issues. This is especially important in high performance computing contexts where even minor performance tweaks can translate into large savings in terms of computational resource use. To aid performance analysis, developers may collect an execution trace —a chronological log of program activity during execution. As traces represent the full history, developers can discover a wide array of possibly previously unknown performance issues, making them an important artifact for exploratory performance analysis. However, interactive trace visualization is difficult due to issues of data size and complexity of meaning. Traces represent nanosecond-level events across many parallel processes, meaning the collected data is often large and difficult to explore. The rise of asynchronous task parallel programming paradigms complicates the relation between events and their probable cause. Here, to address these challenges, we conduct a continuing design study in collaboration with high performance computing researchers. We develop diverse and hierarchical ways to navigate and represent execution trace data in support of their trace analysis tasks. Through an iterative design process, we developed Traveler , an integrated visualization platform for task parallel traces. Traveler provides multiple linked interfaces to help navigate trace data from multiple contexts. We evaluate the utility of Traveler through feedback from users and a case study, finding that integrating multiple modes of navigation in our design supported performance analysis tasks and led to the discovery of previously unknown behavior in a distributed array library.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2017

Optimizing Discharge Capacity of Li-O 2 Batteries by Design of Air-Electrode Porous Structure: Multifidelity Modeling and Optimization

We develop a new mathematical framework to study the optimal design of air electrode microstructures for lithium-oxygen (Li-O2) batteries. It can eectively reduce the number of expensive experiments for testing dierent air-electrodes, thereby minimizing the cost in the design of Li-O2 batteries. The design parameters to characterize an air-electrode microstructure include the porosity, surface-to-volume ratio, and parameters associated with the pore-size distribution. A surrogate model (also known as response surface) for discharge capacity is rst constructed as a function of these design parameters. The surrogate model is accurate and easy to evaluate such that an optimization can be performed based on it. In particular, a Gaussian process regression method, co-kriging, is employed due to its accuracy and eciency in predicting high-dimensional responses from a combination of multidelity data. Specically, a small amount of data from high-delity simulations are combined with a large number of data obtained from computationally ecient low-delity simulations. The high-delity simulation is based on a multiscale modeling approach that couples the microscale (pore-scale) and macroscale (device-scale) models. Whereas, the low-delity simulation is based on an empirical macroscale model. The constructed response surface provides quantitative understanding and prediction about how air electrode microstructures aect the discharge performance of Li-O2 batteries. The succeeding sensitivity analysis via Sobol indices and optimization via genetic algorithm ultimately oer a reliable guidance on the optimal design of air electrode microstructures. The proposed mathematical framework can be generalized to investigate other new energy storage techniques and materials.

25 ENERGY STORAGE↗
DOE OSTI2021

Emu v1.1

Emu is a particle-in-cell code for solving the neutrino quantum kinetic equations in 1, 2, or 3 spatial dimensions with arbitrary angular resolution in order to simulate neutrino flavor transformation in neutron star merger and core collapse supernova environments. Emu represents the neutrino distribution function as a set of particles, each of which represent a collection of neutrinos and antineutrinos with unique position and momentum. Each particle carries two density matrices to define the flavor state of the neutrinos and antineutrinos it represents. Emu includes the vacuum, matter, and neutrino self-interaction potentials. Emu calculates the self-interaction potential using PIC deposition and interpolation algorithms that efficiently compute the local number density and flux at particle locations. Emu is implemented in C++ and is based on the AMReX library for high-performance, block-structured adaptive mesh refinement. Emu is parallelized with MPI + OpenMP for CPUs and MPI + CUDA for GPUs.

Willcox, Donald↗
DOE OSTI2023

Thermal Spectrum Molten Salt-Fueled Reactor Reference Plant Model

This report details a fully coupled neutronics thermal hydraulics reference plant model for a thermal spectrum molten salt-fueled reactor. The Multiphysics model is developed on the Nuclear Regulatory Commission's Comprehensive Reactor Analysis Bundle available on the Idaho National Laboratory high-performance computer, which natively and seamlessly couples Griffin and Sam codes of the Multiphysics Object-Oriented Simulation Environment (MOOSE) based applications. Griffin provides the reactor physics capabilities, k-eigenvalue, delayed neutron precursor concentrations, and transient solutions for stationary and flowing fuels. Sam provides the solution of mass, momentum, and energy conservation equations of the whole system with a set of system components for one-dimensional single-phase flow. The neutronics feedback model relies primarily on fuel and moderator temperatures, fuel salt density, and delayed neutron precursors distributions. This report presents our results for the coupled steady state core and an unprotected loss of flow event. Although this model is prototypical regarding capabilities in the Comprehensive Reactor Analysis Bundle, its results are consistent with experimental data of the pump transient tests that were performed at zero power of the Molten Salt Reactor Experiment (MSRE).

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
NASA NTRS1987

Thermal stress analysis of space shuttle orbiter subjected to reentry aerodynamic heating

A structural performance and resizing (SPAR) finite-element computer program and NASA structural analysis (NASTRAN) finite-element computer programs were used in the thermal stress analysis of the space shuttle orbiter subjected to reentry aerodynamic heating. A SPAR structural model was set up for the entire left wing of the orbiter, and NASTRAN structural models were set up for: (1) a wing segment located at midspan of the orbiter left wing, and (2) a fuselage segment located at midfuselage. The thermal stress distributions in the orbiter structure were obtained and the critical high thermal stress regions were identified. It was found that the thermal stresses induced in the orbiter structure during reentry were relatively low. The thermal stress predictions from the whole wing model were considered to be more accurate than those from the wing segment model because the former accounts for temperature and stress effects throughout the entire wing.

Ko, William L.↗