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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

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DOE OSTI2021

Characterizing the acceleration time of laser-driven ion acceleration with data-informed neural networks

Peak ion energy is an important figure-of-merit in short-pulse, laser-driven ion acceleration and is dependent on an associated acceleration time. Standard metrics for these quantities depend on analytical results such as the self-similar fluid model or empirical models based on relatively small experimental and simulation datasets. In this work we attempt to use a data-informed neural network (NN) as a surrogate model for a large ensemble of PIC simulations to investigate an effective acceleration time. We explore the application of a stacked convolutional and recurrent NN architecture for improved regression by incorporating the time dependencies of the data into the training process. Of particular note is how pretraining a network on lower fidelity data, e.g. 1D analytical results, greatly improves the network's ability to learn more complex, higher fidelity data. Finally, the dependency of the acceleration time on various laser and plasma parameters is explored.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

NASA NTRS1993

The role of magnetic loops in particle acceleration at nearly perpendicular shocks

The acceleration of superthermal ions is investigated when a planar shock that is on average nearly perpendicular propagates through a plasma in which the magnetic field is the superposition of a constant uniform component plus a random field of transverse hydromagnetic fluctuations. The importance of the broadband nature of the transverse magnetic fluctuations in mediating ion acceleration at nearly perpendicular shocks is pointed out. Specifically, the fluctuations are composed of short-wavelength components which scatter ions in pitch angle and long-wavelength components which are responsible for a spatial meandering of field lines about the mean field. At nearly perpendicular shocks the field line meandering produces a distribution of transient loops along the shock. As an application of this model, the acceleration of a superthermal monoenergetic population of seed protons at a perpendicular shock is investigated by integrating along the exact phase-space orbits.

Decker, R. B.↗

DOE OSTI2016

Influence of spraying on the early hydration of accelerated cement pastes

In practice, most of the studies about the interaction between cement and accelerators is performed with hand-mixed pastes. However, in many applications mixing occurs through spraying, which may affect accelerators reactivity and the microstructure of the hardened paste. The objective of this study is to analyze how the mixing process influences the early hydration of accelerated cement pastes. Isothermal calorimetry, X-ray diffraction, thermogravimetry and SEM imaging were performed on cement pastes produced by hand-mixing and by spraying, using equivalent doses of an alkali-free and an alkaline accelerator and two types of cement. Results showed a great influence of the spraying process on the reactivity of accelerators and on the morphology of the precipitated hydrates. Variations in hydration kinetics caused by the mixing method are explained and the results obtained might have a significant repercussion on how future research on the behavior of accelerated mixes will be performed.

36 MATERIALS SCIENCE↗

DOE OSTI2014

Doubling Beam Intensity Unlocks Rare Opportunities for Discovery at Fermi National Accelerator Laboratory

Particle accelerators such as the Booster synchrotron at the Fermi National Accelerator Laboratory (FNAL) produce high-intensity proton beams for particle physics experiments that can ultimately reveal the secrets of the universe. High-intensity proton beams are required by experiments at the “intensity frontier” of particle physics research, where the availability of more particles improves the chances of observing extremely rare physical processes. In addition to their central role in particle physics experiments, particle accelerators have found widespread use in industrial, nuclear, environmental, and medical applications. RF cavities are essential components of particle accelerators that, depending on the design, can perform multiple functions, including bunching, focusing, decelerating, and accelerating a beam of charged particles. Engineers are working to model the RF cavities required for upgrading the 40-year old Booster synchrotron. It is a rather complicated process to refurbish, test, and qualify the upgraded RF cavities to sustain an increased repetition rate of the RF field required to produce proton beams at double the current intensity. Both multiphysics simulation and physical measurements are used to evaluate the RF, thermal, and mechanical properties of the Booster RF cavities.

43 PARTICLE ACCELERATORS↗

DOE OSTI2019

Report of the Workshop on Advanced Fusion with Machine Learning, April 30-May 2, 2019

The pursuit of fusion energy has led to extensive activities in both experimental and theoretical science. The central goal of all these activities has been to develop the knowledge necessary for the design of successful fusion power plants. Even today, following decades of research in many key areas including plasma physics and material science, much remains to be learned in order to achieve optimization of the tokamak or other paths to fusion energy. Data science methods from the fields of machine learning and artificial intelligence (ML/AI) offer opportunities for enabling or accelerating progress toward the realization of fusion energy by maximizing the amount and usefulness of information extracted from experimental and simulation output data. From April 30 to May 2 of 2019, a workshop on “Advancing Fusion with Machine Learning Research Needs” was held in Gaithersburg, MD, with joint support from the Fusion Energy Science (FES) and Advanced Scientific Computing Research (ASCR) Programs. The workshop brought together ~ 60 experts in fields spanning fusion science, data science, statistical inference and mathematics, machine learning, and artificial intelligence, along with DOE program managers and technical experts, with the goal of identifying Priority Research Opportunities (PROs) for the application of ML/AI methods to accelerating progress on solving fusion problems. During the workshop, seven key PROs were identified. The description of each PRO includes relevant fusion problems, potentially useful ML/AI approaches, known gaps currently preventing the use of such approaches, and research guidelines to maximize the effective application of ML/AI methods to the PRO. The report containing the full description of the workshop outcomes is available at https://science.osti.gov/-/media/fes/pdf/workshopreports/FES_ASCR_Machine_Learning_Report.pdf

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

DOE OSTI2018

Porting DMRG++ Scientific Application to OpenPOWER

With the rapidly changing microprocessor designs and architectural diversity (multi-cores, many-cores, accelerators) for the next generation HPC systems, scientific applications must adapt to the hardware, to exploit the different types of parallelism and resources available in the architecture. To get the benefit of all the in-node hardware threads, it is important to use a single programming model to map and coordinate the available work to the different heterogeneous execution units in the node (e.g., multi-core hardware threads (latency optimized), accelerators (bandwidth optimized), etc.).Our goal is to show that we can manage the node complexity of these systems by using OpenMP for in-node parallelization by exploiting different “programming styles” supported by OpenMP 4.5 to program CPU cores and accelerators. Finding out the suitable programming-style (e.g., SPMD style, multi-level tasks, accelerator programming, nested parallelism, or a combination of these) using the latest features of OpenMP to maximize performance and achieve performance portability across heterogeneous and homogeneous systems is still an open research problem.We developed a mini-application, Kronecker Product (KP), from the original DMRG++ application (sparse matrix algebra) computational motif to experiment with different OpenMP programming styles on an OpenPOWER architecture and present their results in this paper.

Chatterjee, Ronnie↗

DOE OSTI2024

Producing circular field harmonics inside elliptic magnet apertures with superconducting canted-cosine-theta coils

Superconducting magnets with noncircular aperture are desired for accelerators and many other high-field applications. This paper presents new methods for the analytic design of elliptic bore superconducting accelerator magnets. Part 1 of this work shares the derivation of current to field relations between a sheet current density on an elliptic cylinder and the magnetic field harmonics inside the aperture. This result is explored in the general context of elliptic bore magnet design with relevant scaling laws compared between elliptic and circular bore magnets. In part 2, this approach is applied to the specific geometry of canted-cosine-theta (CCT) accelerator magnets, enabling analytic winding design for single or mixed circular harmonics within elliptic aperture CCT magnets. Published by the American Physical Society 2024

43 PARTICLE ACCELERATORS↗

NASA NTRS1978

A new experimental method for the accelerated characterization of composite materials

The use of composite materials for a variety of practical structural applications is presented and the need for an accelerated characterization procedure is assessed. A new experimental and analytical method is presented which allows the prediction of long term properties from short term tests. Some preliminary experimental results are presented.

Yeow, Y. T.↗

DOE OSTI2020

Shaped Beams from Diamond Field-Emitter Array Cathodes

Diamond field-emitter arrays (DFEAs) are arrays of diamond pyramids with exquisitely sharp tips and micrometer-scale bases that produce high current densities. These arrays can be fabricated in arbitrary shapes, ranging from single tips to many millions of tips, so that they produce an inherently shaped electron beam. Each tip emits a modest current, but the large dense array can produce many Amps. We are investigating these cathodes for use in dielectric wakefield accelerators; however, they may also be applicable to vacuum microwave tubes. Recently, shaped beam production and transport have been demonstrated in the 1.3-GHz RF gun at the Argonne Cathode Test Stand at the Argonne National Laboratory. The charge was measured on a Faraday cup and the beam imaged on a YAG screen with peak electric field gradients on the cathode ranging from 12 to 35 MV/m. Three cathode geometries were tested: one 1-mm equilateral triangle with 7-mu m base pyramids and 10-mu m pitch, one 1-mm equilateral triangle with 10-mu m base and 25-mu m pitch, and one sparse 5 x 5 square array with 20-mu m base and 400-mu m pitch. The two triangular arrays emitted 35 nC in an RF macropulse at 35 MV/m and 13-nC charge at 27 MV/m, respectively, while the sparse array emitted 0.060-nC charge at 15 MV/m. This article presents the results of the triangular array experiments, including damage due to breakdown in the RF gun and initial models of tip-to-tip shielding.

Cathodes↗

DOE OSTI2017

Application of NSUF Capabilities Towards Understanding the Emulation of High Dose Neutron Irradiations with Ion Beams

Development of new materials for current nuclear power plants (NPPs) or materials for new NPPs requires extensive research, development, and deployment programs. Central to these efforts, particularly for core internals, are studies on the microstructural and mechanical changes due to neutron irradiation. These radiation effects studies are typically completed using materials test reactors followed by expensive and time-consuming post-irradiation examinations (PIE). This sluggish approach has severely limited the nuclear materials field to develop new materials or verify materials for new reactor design use. It is also very difficult to achieve the high levels of damage proposed for future reactors. A logical approach to accelerating the field is the application of ion beams to simulate neutron damage, especially for high dose applications. Ion beams have been used for decades to study radiation effects but not to emulate high dose reactor irradiations. In this regard, new (or renewed) methods for ion beam irradiations, new developments in materials characterization, and greater understanding on the governing mechanisms controlling observed radiation effects have led to a need for further studies to refine the technique. A primary challenge is the ability to determine the ion irradiation conditions that produce microstructures and mechanical properties relevant to in-core neutron irradiation conditions. A large, multi-disciplinary, multi-laboratory program deemed the High Fidelity Ion Beam Simulation of High Dose Neutron Irradiation has been formed to assess and overcome the challenges associated with emulating high dose neutron irradiations using ion beams. Central to this program is the use of dual-beam ion irradiations and corresponding neutron irradiations within the BOR-60 fast reactor. These irradiations have produced hundreds of specimens for microstructural and mechanical characterization. A significant issue regarding the samples is the radioactivity of the neutron irradiated specimens as well as the need to characterize both irradiation types using the same equipment to maintain consistency and repeatability. The use of the Nuclear Science User Facilities (NSUF) has been central towards overcoming the mentioned issues and thereby enabling robust PIE in both the ion and neutron irradiated specimens of interest. In particular, the electron microscopes housed within the Low Activation Materials Development and Analysis (LAMDA) facility at Oak Ridge National Laboratory (ORNL) - an NSUF partner facility - has been instrumental in gathering high quality data for analysis. This paper will briefly highlight the PIE efforts using the NSUF capabilities within LAMDA.

36 MATERIALS SCIENCE↗

NASA NTRS1999

Giant Magnetoresistive (GMR) Sensor Microelectromechanical System (MEMS) Device

The measurement of acceleration has been accomplished using several technologies in high-reliability applications such as guidance control, detonation, and shock/vibration measurement. Electromechanical, piezoelectric, piezoresistive, and capacitive acceleration sensors are available and the literature pertinent to giant magnetoresistive sensors (GMR) for the above applications are scanty.

acceleration MEMS GMR giant magnetoresistive senso↗

DOE OSTI2023

Reinforcement learning for real-time process control in high-temperature superconductor manufacturing

With high efficiency and low energy loss, high-temperature superconductors (HTS) have demonstrated their profound applications in various fields, such as medical imaging, transportation, accelerators, microwave devices, and power systems. The high-field applications of HTS tapes have raised the demand for producing cost-effective tapes with long lengths in superconductor manufacturing. However, achieving the uniform and enhanced performance of a long HTS tape is challenging due to the unstable growth conditions in the manufacturing process. Although it is confirmed that the process parameters during the advanced metal organic chemical vapor deposition (A-MOCVD) process influence the uniformity of the produced HTS tapes, the high-dimensional process parameter signals and their complicated interactions make it difficult to develop an effective control policy. In this paper, we propose a local measure for the uniformity of HTS tapes to provide instant feedback for our control policy. Then, we model the manufacturing of HTS tapes as a Markov decision process (MDP) with continuous state and action spaces to assess the instant reward in real time in our feedback control model. As our MDP involves continuous and high-dimensional state and action spaces, a neural fitted Q-iteration (NFQ) algorithm is adopted to solve the MDP with artificial neural network (ANN) function approximation. The collinearity of process parameters can restrict our capability of adjusting the process parameters, which is addressed by the principal component analysis (PCA) in our method. The control policy adjusts the PCA of process parameters using the NFQ algorithm. In conclusion, based on our case studies on real A-MOCVD dataset, the obtained control policy increases the average uniformity of tapes by 5.6% and performs especially well on sample HTS tapes with a low uniformity.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗

DOE OSTI2025

Advancing the utility of Data flow accelerators: Kokkos backend for Next Silicon

Next Silicon provides a novel reconfigurable accelerator, which is inherently a high-risk, early exploration effort. Higher readiness level for running NNSA mini-apps and initial mission applications on a data-flow accelerator Enable and demonstrate a new Kokkos back-end that directly drives an underlying dataflow accelerator

Garcia de Gonzalo, Simon Pedro [Sandia National La↗

DOE OSTI2019

Experimental Demonstration of the Henon-Heiles Quasi-Integrable System at IOTA

The Integrable Optics Test Accelerator is a research electron and proton storage ring recently commissioned at the Fermilab Accelerator Science and Technology facility. Its research program is focused on testing novel techniques for improving beam stability and quality, notably the concept of non-linear integrable optics. In this paper, we report the first results of experimental investigation of a quasi-integrable transverse focusing system with one invariant of motion, a Henon-Heiles type system implemented with octupole magnets. Good agreement with simulations is demonstrated on key parameters of achievable tune spread and dynamic aperture preservation. Resilience to perturbations and imperfections in the lattice is explored. We conclude by outlining future research plans and discussing applicability to future high intensity accelerators.

43 PARTICLE ACCELERATORS↗

NASA NTRS2002

Experimental Methods in Reduced-gravity Soldering Research

The National Center for Microgravity Research, NASA Glenn Research Center, and NASA Johnson Space Center are conducting an experimental program to explore the influence of reduced gravity environments on the soldering process. An improved understanding of the effects of the acceleration environment is important to application of soldering during current and future human space missions. Solder joint characteristics that are being considered include solder fillet geometry, porosity, and microstructural features. Both through-hole and surface mounted devices are being investigated. This paper focuses on the experimental methodology employed in this project and the results of macroscopic sample examination. The specific soldering process, sample configurations, materials, and equipment were selected to be consistent with those currently on-orbit. Other apparatus was incorporated to meet requirements imposed by operation onboard NASA's KC-135 research aircraft and instrumentation was provided to monitor both the atmospheric and acceleration environments. The contingent of test operators was selected to include both highly skilled technicians and less skilled individuals to provide a population cross-section that would be representative of the skill mix that might be encountered in space mission crews.

Pettegrew, Richard D.↗

NASA NTRS2024

EdgeCortix SAKURA-I Machine-Learning, PCIe Accelerator SEE Heavy Ion Test Report

To enable autonomy in space, machine-learning and computer vision applications become invaluable for sensor processing. However, these algorithms are computationally complex and unfeasible for many embedded central processing units (CPUs) and usually require external coprocessors, such as graphics processing units (GPUs) or accelerators specific to the application, including application specific integrated circuits (ASICs). In power-constrained systems, GPUs tend to consume more power than is acceptable (>40W), so lower-power accelerators have shown promise to provide the performance needed under spacecraft constraints. For radiation engineers, developing methodologies that can properly test CPUs, GPUs, and accelerators, and enable comparisons between them remains a necessary complication to solve as the devices become more complex. The methodology in this test aims to be a start in developing a baseline single-event effect (SEE) test for client-device machine learning accelerators. This category of devices do not host their own operating system. This testing campaign is a continuation of a previous 200 MeV proton test performed in January 2024. This report covers two heavy ion tests of the SAKURA-I card: one in April 2024, and one in June 2024. Additional data was needed after the April test due to ion-range issues experienced at higher linear-energy transfers (LETs). These range issues are described in more detail in Section 8. This experiment characterizes SEEs and data error susceptibility of the EdgeCortix SAKURA-I machine-learning accelerator under heavy ions. The device was monitored for single event upsets (SEUs) and single event functional interrupts (SEFIs) at the Lawrence Berkeley National Laboratory’s 88-inch cyclotron. The SAKURA-I board accelerates machine-learning inference applications on a host computer through a PCIex16 connection. For the purposes of devising an end to end automated analysis workflow for this experiment, the YOLO-V5 and SSD300 objection-detection models, and the ResNet-50, EfficientNet, and MobileNetV2 image classification models were used as a representative suite of analytical machine-learning models.

Seth S Roffe↗

DOE OSTI2022

Design and demonstration of an economical SRF structure for Continuous Wave (CW), high-energy, Megawatt-class beams

Due to its very high RF-to-beam efficiency, superconducting radiofrequency (SRF) cavities have become the technology of choice for the construction of large linear accelerators (linacs) for basic science applications (examples, ESS and PIP-II). The technology is also attractive for high volume industrial applications such as electron irradiation processing of wastewater and flue gas. However, SRF’s current reliance on liquid helium for cryogenic cooling introduces infrastructural and safety challenges for use in industrial settings. Cryocooler conduction-cooling is a recently developed novel technique for operating SRF cavities without requiring liquid helium. This project aims for technical design and economic assessment of a medium energy, high average power e-beam linac based on the conduction-cooled SRF technique for high volume irradiation treatment of wastewater. The goals of this project are (1) to design a medium energy (10 MeV), high average power (1 MW) electron beam accelerator around the cryocooler conduction-cooled SRF cavity technology, (2) demonstrate the required accelerating voltage on a prototype cavity, and (3) build a cost-model to evaluate capital and operating expense of the accelerator.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗

DOE OSTI2026

Mixed-precision numerics in scientific applications: survey and perspectives

The explosive demand for artificial intelligence (AI) workloads has led to a significant increase in silicon area dedicated to lower-precision computations on recent high-performance computing hardware designs. However, mixed-precision capabilities, which can achieve performance improvements of up to 8x compared to double-precision in extreme compute-intensive workloads, remain largely untapped in most scientific applications. A growing number of efforts have shown that mixed-precision algorithmic innovations can deliver superior performance without sacrificing accuracy. These developments should prompt computational scientists to seriously consider whether their scientific modeling and simulation applications could benefit from the acceleration offered by new hardware and mixed-precision algorithms. In this survey, we (1) review progress across diverse scientific domains—fluid dynamics, weather and climate, quantum chemistry, and computational genomics—that have begun adopting mixed-precision strategies; (2) examine state-of-the-art algorithmic techniques such as iterative refinement, splitting and emulation schemes, and adaptive precision solvers; (3) assess their implications for accuracy, performance, and resource utilization; and (4) survey the emerging software ecosystem that enables mixed-precision methods at scale. We conclude with perspectives and recommendations on cross-cutting opportunities, domain-specific challenges, and the role of co-design between application scientists, numerical analysts, and computer scientists. Collectively, this survey underscores that mixed-precision numerics can reshape computational science by aligning algorithms with the evolving landscape of hardware capabilities.

Graphics processing units↗