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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 973 records · Page 54
All sourcesNASA NTRSDOE OSTI
DOE OSTI2023

System and method for testing missile components

A testing system for testing a missile component having a sense axis includes a centrifuge, a support arm, an orientation assembly, and a controller. The centrifuge rotates the orientation assembly about a vertical axis in a substantially horizontal plane. The orientation assembly includes a first motor, a first gimbal, and a gimballed support. The first motor has a first rotatable shaft defining a first gimbal axis. The first gimbal is coupled with the first rotatable shaft to rotate about the first gimbal axis while the centrifuge rotates the orientation assembly about the vertical axis such that missile component is simultaneously rotated about both the vertical axis and the first gimbal axis to simulate a missile launch of the missile component. The gimballed support is coupled with the first gimbal for supporting the missile component such that the sense axis of the missile component is not parallel to the substantially horizontal plane. The orientation assembly may also include a second gimbal that is rotated about a second gimbals axis by a second motor.

Prewitt, Steven Forrest↗
DOE OSTI2024

Impact of Reordering on the LU Factorization Performance of Bordered Block-Diagonal Sparse Matrix

Power engineers rely on computer-based simulation tools to assess grid performance and ensure security. At the core of these tools are solvers for sparse linear equations. When transformed into a bordered block-diagonal (BBD) structure, part of the sparse linear equation solving can be parallelized. This work focuses on using the Schur-complement-based method for LU factorization on BBD matrices, specifically, Jacobian matrices from large-scale systems. Our findings show that the natural ordering method outperforms the default ordering method in computational performance for each block of the BBD matrix. This observation is validated using synthetic 25k-bus and 70k-bus cases, showing a speedup of up to 38% when using natural ordering without permutation. Additionally, the impact of the number of partitions is studied, and the result shows that computational performance improves with more, smaller partitions in the BBD matrices.

BBD matrix↗
DOE OSTI2022

Three-dimensional inhomogeneity of electron-temperature-gradient turbulence in the edge of tokamak plasmas

Nonlinear multiscale gyrokinetic simulations of a Joint European Torus edge pedestal are used to show that electron-temperature-gradient (ETG) turbulence has a rich three-dimensional structure, varying strongly according to the local magnetic-field configuration. In the plane normal to the magnetic field, the steep pedestal electron temperature gradient gives rise to anisotropic turbulence with a radial (normal) wavelength much shorter than in the binormal direction. In the parallel direction, the location and parallel extent of the turbulence are determined by the variation in the magnetic drifts and finite-Larmor-radius (FLR) effects. The magnetic drift and FLR topographies have a perpendicular-wavelength dependence, which permits turbulence intensity maxima near the flux-surface top and bottom at longer binormal scales, but constrains turbulence to the outboard midplane at shorter electron-gyroradius binormal scales. Here our simulations show that long-wavelength ETG turbulence does not transport heat efficiently, and significantly decreases overall ETG transport—in our case by ~40%—through multiscale interactions.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2020

Programmable topotaxis of magnetic rollers in time-varying fields

We discuss how spatially uniform, time-periodic magnetic fields can be designed to power and direct the migration of ferromagnetic spheres up (or down) local gradients in the topography of a solid substrate. Our results are based on a dynamical model that considers the time-varying magnetic torques on the particle and its motion through the fluid at low Reynolds number. We use both analytical theory and numerical simulation to design magnetic fields that maximize the migration velocity up (or down) an inclined plane. We show how “topotaxis” of spherical particles relies on differences in the hydrodynamic resistance to rotation about axes parallel and perpendicular to the plane. Importantly, the designed fields can drive multiple independent particles to move simultaneously in different directions as determined by gradients in their respective environments. Experiments on ferromagnetic spheres provide evidence for topotactic motions up inclined substrates. The ability to program the autonomous navigation of driven particles within anisotropic environments is relevant to the design of colloidal robots.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2020

Concurrent Relaxation through Accelerated Deep Learning

CRADL captures performance metrics of machine learning algorithms operating on mesh data from multiphysics codes This proxy application is a tool to explore scalability of inference on HPC platforms, and also gather performance metrics for inference on new machine learning specific hardware. CRADL is designed to give users as fine a control as possible over an inference simulation. Users may select the number of cycles, amount of data, and batch size to pass to the accelerator of choice. Additionally the user may select a number of performance optimization libraries and flags. CRADL comes packaged with a repository of anonymized multi-physics simulation data, as well as a pretrained model for inference. The code allows a user to load their own pre-trained model and data if they wish. The code can operate in multiple parallelization schemes, with performance enhancing options such as half-precision libraries, PyTorch benchmarking, and pinned memory with non-blocking data transfers.

Zieb, KristoferJ.↗
DOE OSTI2020

TChem 2.0

The TChem toolkit is an object-oriented C++ software library that enables numerical simulations using complex chemistry and facilitates the analysis of detailed kinetic models. The toolkit provides capabilities for thermodynamic properties and gas-phase and surface chemistry. The computations rely on the Kokkos framework for parallel execution on many-core and GPU-based platforms. Sandia National Laboratories is a multimission laboratory managed and operated by National Technology & Engineering Solutions of Sandia, LLC, a wholly owned subsidiary of Honeywell International Inc., for the U.S. Department of Energy's National Nuclear Security Administration under contract DE-NA0003525. SAND2021-2752 O

Kim, Kyungjoo↗
DOE OSTI2024

Unraveling the Physics Associated with the Production of Extremely Dense Plasma States of Microscale Nanosecond-pulsed Discharges

The research carried out on this grant aimed to study the properties of anomalously dense plasmas formed in so-called ”fast” discharges, such as high pressure narrow-gap nanosecond pulsed discharges and short pulse (nanosecond-scale) laser driven discharges. These fast discharges are receiving much attention as they now enable new applications in aerodynamics, combustion, biology, and medicine. The mechanisms that generate these high electron densities (ne > 10 19 cm −3 ) that encroach on warm dense matter regimes are not well understood. Such densities are orders of magnitude higher than those (≈ 10 15 cm −3 ) routinely seen in classical high-pressures (streamer) discharges. Furthermore, the dense plasmas are reported to be highly nonequilibrium, with T gas <<, T i << T e . These properties would place these discharges in a regime of near full ionization (Z ≥ 1) where there is inadequate electron screening and therefore strong ion coupling - physics that is not generally accounted for in simulations. In this project work, we seek to study these fast discharges, validate simulations with experiments at pressures as high as 10-50 bar, and augment plasma production to even higher levels of n e (> 10 20 cm −3 ) with second-stage picosecond laser heating. In parallel, we have studied the use of these fast discharges in reactive gases, unraveling mechanisms related to the fast discharge dissociation of CO 2 .

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2020

Dynamic Equivalence of Large-Scale Power Systems Based on Boundary Measurements

Parallel computing helped speed up many tasks that can be done independently. The advance in gaming industry did not produce a technology that helps the power industry to reduce the computation time for dynamic simulation in individual cases. To perform faster than real-time simulation for the purpose of predicting power system dynamic trajectory, power industry continues to struggle to reduce the system size and simulation time of large-scale power systems while keeping its dynamic behavior under various disturbances. There is also an acute need for real-time dynamic model reduction as more renewables enter the generation mix with dramatic changes in the generation outputs. All existing model reduction solutions are based on having access to a detailed dynamic model of the system. The system changes by the minutes, dynamic models are only updated annually. To solve this problem, wide-area measurements obtained by the phasor measurement unit (PMU) at the boundaries between the reduced system and the study system is used to represent the external area. An artificial neuro-fuzzy inference system (ANFIS) is established to perform the mapping of the measurement to the external equivalent model. Here the external area is regarded as a black-box. Model reduction studies are conducted on the Northeast Power Coordinating Council (NPCC) under various types of contingencies, by using a co-simulation approach between PSS/E and MATLAB. The results look very promising and will be discussed in this paper.

Tong, Ning↗
DOE OSTI2025

LuGo: An enhanced quantum phase estimation implementation

Quantum Phase Estimation (QPE) is a cardinal algorithm in quantum computing that plays a crucial role in various applications, including cryptography, molecular simulation, and solving systems of linear equations. However, the standard implementation of QPE faces challenges related to time complexity and circuit depth, which limit its practicality for large-scale computations. We introduce LuGo, a novel framework designed to enhance the performance of QPE by reducing circuit duplication, as well as using parallelization techniques to achieve faster generation of the QPE circuit and gate reduction. We validate the effectiveness of our framework by generating quantum linear solver circuits, which require both QPE and inverse QPE, to solve linear systems of equations. LuGo achieves significant improvements in both computational efficiency and hardware requirements without compromising on accuracy. Compared to a standard QPE implementation, LuGo reduces time consumption to generate a circuit that solves a 2 6 × 2 6 system matrix by a factor of 50.68 and over 31× reduction of quantum gates and circuit depth, with no fidelity loss on an ideal quantum simulator. Furthermore, we demonstrated the versatility and scalability of LuGo enabled HHL algorithm by simulating a canonical Hele-Shaw fluid problem using a quantum simulator. With these advantages, LuGo paves the way for more efficient implementations of QPE, enabling broader applications across several quantum computing domains.

Quantum algorithm↗
DOE OSTI2020

On Simulating the Formation of Structured, Crystalline Systems via Non-classical Pathways

Observations in crystal growth and assembly from recent in situ methods suggest alternative, non-classical crystallization pathways play an important role in the determination of the micro- and meso- structures in crystalline systems. These processes display parallels that cross-cut multiple disciplines investigating crystallization across four orders of magnitude in size scales and widely differing environments, hinting that alternative crystal growth pathways may be a fundamental scheme in natural crystal formation. Using a system of short-range attractive microbeads, we demonstrate that the addition of a small concentration of sub-species incommensurate with the lattice spacing of the dominant species results in a stark change in crystal size and morphology. These changes are attributed to the presence of fleeting, amorphous-like configurations of beads that ultimately change the melting and growth dynamics in preferred directions. From these real-time observations, we hypothesize the amorphous mineral precursors present in biological mineralized tissues undergo similar non-classical crystallization processes resulting in the complex structures found in biomineralization.

36 MATERIALS SCIENCE↗
DOE OSTI2021

Asynchronous and Load-Balanced Union-Find for Distributed and Parallel Scientific Data Visualization and Analysis

We present a novel distributed union-find algorithm that features asynchronous parallelism and k-d tree based load balancing for scalable visualization and analysis of scientific data. Applications of union-find include level set extraction and critical point tracking, but distributed union-find can suffer from high synchronization costs and imbalanced workloads across parallel processes. In this study, we prove that global synchronizations in existing distributed union-find can be eliminated without changing final results, allowing overlapped communications and computations for scalable processing. We also use a k-d tree decomposition to redistribute inputs, in order to improve workload balancing. We benchmark the scalability of our algorithm with up to 1,024 processes using both synthetic and application data. Here, we demonstrate the use of our algorithm in critical point tracking and super-level set extraction with high-speed imaging experiments and fusion plasma simulations, respectively.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2020

Mind the Gap: Building Simulation in the Architectural Design Studio

Building modelling and simulation approaches are increasingly being utilized in architectural design studios to guide and inform the design process and offer evidence-based feedback on proposed building performance. The development of intuitive and simplified simulation interfaces has greatly contributed to achieving this integration. One aspect that is often overlooked is the workflow that governs and regulates integrated design, which can have significant impacts on final design outcomes. Currently there are numerous software packages available for building performance simulations. This makes it challenging to select an appropriate tool that provides accurate results yet allows a designer to make informed architectural decisions with a designer-friendly interface. Furthermore, workflows to incorporate simulations into the design process proved to highly impact student’s project design integration. Yet, it is not clear what type of workflows are successful to achieve this goal, under what conditions, and/or for which building and site typologies. This paper addresses these issues by first reviewing three different workflows for integrating building performance simulation processes and highlighting their strengths and weaknesses. Second, a comparative case study approach was employed to test three of the most common workflows in three different integrated design architectural studios at the senior and vertical studio levels as well as in two courses that run parallel and complementary to the design studios. The workflows, processes, and the resultant student projects were further analyzed based on criteria for better integrated design and architectural excellence as outlined in the American Institute of Architects Committee on the Environment (AIA COTE) Top 10 Student’s Competition. Third, to situate the pedagogical case studies’ results within a larger context, a survey of the AIA COTE Top 10 student competition award recipients over the last five years was conducted. The results are summarized in a pedagogical framework that outlines best strategies of the type of workflows, software, design process used, methods to achieve desired interaction between design process and analytical feedback, and metrics for educators to evaluate the success of this integration and their learning outcomes in the design studio. The goal is to help bridge the gap between the building design and simulation within the design studio’s creative process for more integrated design outcomes.

Elzeyadi, Ihab↗
DOE OSTI2021

DART-PFLOTRAN: An ensemble-based data assimilation system for estimating subsurface flow and transport model parameters

Ensemble-based Data Assimilation (EDA), based on the Monte Carlo approach, has been effectively applied to estimate model parameters through inverse modeling in subsurface flow and transport problems. However, implementation of EDA approach involves a complicated workflow that include setting up and executing ensemble forward model simulations, processing observations and model simulation results for parameter updates, and repeat for sequential or iterative EDA. To facilitate the management of such workflow and lower the barriers for adopting EDA-based parameter estimation in subsurface science, we develop a generic software frame-work linking the Data Assimilation Research Testbed (DART) with a massively parallel subsurface FLOw and TRANsport code PFLOTRAN. The new DART-PFLOTRAN leverages both the core data assimilation engines in DART and the computational power afforded by PFLOTRAN. In addition to the standard smoother and filtering options, DART-PFLOTRAN enables an iterative EDA workflow based on the Ensemble Smoother for Multiple Data Assimilation method (ES-MDA) to improve estimation accuracy for nonlinear forward problems. Here, we verify the implementation of ES-MDA in DART-PFLOTRAN using two synthetic cases designed to estimate static permeability and dynamic exchange fluxes across the riverbed, respectively, from continuous temperature measurements made across a depth profile. One-dimensional hydro-thermal simulations are performed in both cases to relate temperature responses with the parameters of interest. In the case of estimating dynamic parameters, we demonstrate the flexibility of DART-PFLOTRAN in automating sequential ES-MDA workflow, which will significantly reduce the time researchers spend on managing complex workflows in similar applications. Both studies yield accurate estimations of the parameters compared to their synthetic truth, while ES-MDA leads to more accurate estimation when a high level of nonlinearity exist between observed responses and unknown parameters. With a code base in Python and Fortran, DART-PFLOTRAN paves the way for applications in large-scale subsurface inverse modeling by automating the complex workflow of sequential ES-MDA that can be executed on various computing platforms.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2024

A High-Performance Discrete-Element Framework for Simulating Flow and Jamming of Moisture Bearing Biomass Feedstocks

We developed and verified a high-performance open-source discrete element method (DEM) solver with simultaneously-supported feedstock-specific interaction models, including bonded-sphere, liquid bridge, cohesion, and non-linear contact models. Our solver uses parallel data structures on hybrid central and graphics processing unit (CPU/GPU) architectures, with favorable strong scaling performance observed for large problem sizes comprised of (100 M particles), and 4X single-node GPU speedup. The particles for corn stover feedstock were conceptualized and calibrated based on experimental measurements and results. Sensitivity analyses demonstrate that the mass flow rate from a wedge hopper is governed primarily by moisture content, friction coefficient, and cohesion energy density. The model is used to reproduce experimentally observed hopper jamming results, highlighting that the experimental no-flow trends can only be achieved by using non-spherical particles, liquid bridge and cohesion models, highlighting the importance of using concurrent feedstock specialized models for the effective representation of biomass material handling problems.

bioenergy↗
DOE OSTI2023

Non-thermal electron acceleration from magnetically driven reconnection in a laboratory plasma

Magnetic reconnection rapidly converts magnetic energy into some combination of plasma flow energy, thermal energy and non-thermal energetic particles. Various reconnection acceleration mechanisms have been theoretically proposed and numerically studied in different collisionless and low-β environments, where β refers to the plasma-to-magnetic pressure ratio. These mechanisms include Fermi acceleration, betatron acceleration, parallel electric field acceleration along magnetic fields and direct acceleration by the reconnection electric field. However, none of them have been experimentally confirmed, as the direct observation of non-thermal particle acceleration in laboratory experiments has been difficult due to short Debye lengths for in situ measurements and short mean free paths for ex situ measurements. Here we report the direct measurement of accelerated non-thermal electrons from magnetically driven reconnection at low β in experiments using a laser-powered capacitor coil platform. We use kilojoule lasers to drive parallel currents to reconnect megagauss-level magnetic fields in a quasi-axisymmetric geometry. The angular dependence of the measured electron energy spectrum and the resulting accelerated energies, supported by particle-in-cell simulations, indicate that the mechanism of direct electric field acceleration by the out-of-plane reconnection electric field is at work. Scaled energies using this mechanism show direct relevance to astrophysical observations.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2024

Frequency-domain computing using nonlinear acoustic-wave device on lithium niobate

Abstract Multiply-accumulation are crucial computing operations in signal processing, numerical simulations, and machine learning. In recent years, optical analog approaches have demonstrated higher computing performance and better power efficiency than their digital counterparts. However, analog computing chips usually need large areas and complex structures for parallel computing, as a single device element only executes one computing operation at a single time. Here, we demonstrate frequency-domain computing using the nonlinear acoustic-wave devices on lithium niobate, featuring a normalized external second-harmonic generation conversion efficiency of ~ 5.7 × 10-4 W-1. The second-order sum-frequency nonlinear process of lithium niobate enables multiplication of inputs encoded in the frequency domain. Compared to the analog schemes, our device features a notably simpler design, and nanofabrication requires only one lift-off. Using a single acoustic-wave device within an area of 0.03 mm2, we can simultaneously conduct over 130,000 multiply-accumulation operations. Our acoustic-wave device shows applications in real and complex vector convolutions and image processing. This demonstration sets the stage for experimental realizations into frequency-domain integrated nonlinear acoustic computing systems, potentially shaping future developments in acoustic neural networks and quantum computing.&#xD;

chai, mingzhao (ORCID:0009000466226341)↗
DOE OSTI2025

I/O in Machine Learning Applications on HPC Systems: A 360-degree Survey

Growing interest in Artificial Intelligence (AI) has resulted in a surge in demand for faster methods of Machine Learning (ML) model training and inference. This demand for speed has prompted the use of high performance computing (HPC) systems that excel in managing distributed workloads. Because data is the main fuel for AI applications, the performance of the storage and I/O subsystem of HPC systems is critical. In the past, HPC applications accessed large portions of data written by simulations or experiments or ingested data for visualizations or analysis tasks. ML workloads perform small reads spread across a large number of random files. This shift of I/O access patterns poses several challenges to modern parallel storage systems. In this paper, we survey I/O in ML applications on HPC systems, and target literature within a 6-year time window from 2019 to 2024. We define the scope of the survey, provide an overview of the common phases of ML, review available profilers and benchmarks, examine the I/O patterns encountered during offline data preparation, training, and inference, and explore I/O optimizations utilized in modern ML frameworks and proposed in recent literature. Lastly, we seek to expose research gaps that could spawn further R&D.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2021

USING ER@CEBAF TO SHOW THAT A MULTIPASS ERL CAN DRIVE AN XFEL

A multi-pass recirculating superconducting CW linac offers a cost effective path to a multi-user facility with unprecedented scientific and industrial reach over a wide range of disciplines. We propose such a facility as an option for a potential UK-XFEL. Energy Recovery enables multi-MHz FEL sources, for example, an X-ray FEL oscillator or regenerative amplifier FEL. Additionally, combining with external lasers and/or self-interaction would provide access to MeV and GeV gamma-rays via inverse Compton scattering at high average power for nuclear and particle physics applications. An opportunity exists to demonstrate the necessary point-to-parallel longitudinal matches to drive an XFEL and successfully energy recover at the upcoming 5-pass up, 5-pass down Energy Recovery experiment on CEBAF at JLab termed ER@CEBAF. We show candidate matches and simulations supporting the minimal necessary modifications to CEBAF this will require. This includes linearisation of the longitudinal phase space in the injector and a reduction in the dispersion of the arcs, both of which increase the energy acceptance of CEBAF. We expect to commence initial tests of these adaptations on CEBAF during 2021.

Perez-Segurana, G.↗