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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 1,261 records · Page 70
All sourcesNASA NTRSDOE OSTI
DOE OSTI2024

Validation of a synthetic fast ion loss detector model for Wendelstein 7-X

Abstract We present the first validated synthetic diagnostic for fast ion loss detectors (FILDs) in the Wendelstein 7-X (W7-X) stellarator. This model has been developed on, and validated against experimental data from, a FILD provided by the National Institute for Fusion Science (NIFS-FILD), with potential future applicability to the existing Faraday Cup FILD (FC-FILD) on W7-X as well as the scintillating FILD (S-FILD) currently under development. A workflow combining Monte Carlo codes BEAMS3D and ASCOT5 is used to track fast ions produced by neutral beam injection from the moment of ionization until they are thermalized or lost from the last closed flux surface, and from there to a virtual plane which serves as a projection of the entrance aperture to the FILD. Simulations in ASCOT5 are analyzed via a geometric method to determine the probability of transmission through the FILD aperture and onto the detector as a function of normalized momentum, pitch angle, gyrophase, and position at the virtual plane. This probability is then applied to the simulated ions arriving from the plasma, producing a simulated signal from a computationally tractable number of simulated fast ions. Simulated signals are presented for two W7-X experiments with neutral beam injection and quantitatively compared with experimental measurements from the NIFS-FILD diagnostic. An estimate of the frequency of charge-exchange with neutral particles in the edge is performed, and it is found that this process may have a significant impact on the measured signals.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2016

Contributions of the stochastic shape wake model to predictions of aerodynamic loads and power under single wake conditions

The contribution of wake meandering and shape asymmetry to load and power estimates is quantified by comparing aeroelastic simulations initialized with different inflow conditions: an axisymmetric base wake, an unsteady stochastic shape wake, and a large-eddy simulation with rotating actuator-line turbine representation. Time series of blade-root and tower base bending moments are analyzed. We find that meandering has a large contribution to the fluctuation of the loads. Moreover, considering the wake edge intermittence via the stochastic shape model improves the simulation of load and power fluctuations and of the fatigue damage equivalent loads. Furthermore, these results indicate that the stochastic shape wake simulator is a valuable addition to simplified wake models when seeking to obtain higher-fidelity computationally inexpensive predictions of loads and power.

17 WIND ENERGY↗
DOE OSTI2022

Solutes that reduce yield strength anisotropies in magnesium from first principles

Using Labusch-type solid solution strengthening models parameterized with DFT-computed solute-dislocation interaction energies, we perform a computational search for 63 solutes across the periodic table to find those that lower anisotropy ratios (non-basal to basal CRSS) of magnesium potentially increasing its ductility per the von Mises criterion. For this purpose, we compute changes in strength for solutes as a function of composition and temperature, and compute anisotropy ratios for solutes that include both rare earth and non-rare earth elements. Here we specifically focus on solute-dislocation interaction energies in the following DFT-optimized dislocations as representative of three non-basal plastic deformation modes: $\langle c + a \rangle$ edge, (10$\bar1$2) tension twinning edge, and the (10$\bar{1}$1) compression twinning edge. We find that solute-induced changes in non-basal deformation modes can be approximated using a second-order polynomial in the size misfit of the solutes, which permits rapid screening of solutes. Our approach to identify solutes known to improve strengthening incorporates solute solubility, and suggests other solutes that not have been previously explored for strengthening. The 8 rare-earth solutes that our method suggests as the best, ordered by increasing anisotropy ratios at their optimal concentrations, are: Gd, Tb, Dy, Nd, Ho, Er, Tm, and Yb. The 12 non-rare-earth solutes that our method suggests as the best, ordered by increasing anisotropy ratios, are: Y, Mn, Sc, Pb, Ca, Ag, Bi, Tl, Zn, Li, Ga, and Al. Of these, Gd, Nd, Er, Yb, Y, Mn, Ca, Zn, Li, and Al are used in commercial Mg alloys.

36 MATERIALS SCIENCE↗
DOE OSTI2021

Dotted-line FLEET for two-component velocimetry

Femtosecond laser electronic excitation tagging (FLEET) is a powerful unseeded velocimetry technique typically used to measure one component of velocity along a line, or two or three components from a dot. In this Letter, we demonstrate a dotted-line FLEET technique which combines the dense profile capability of a line with the ability to perform two-component velocimetry with a single camera on a dot. Our set-up uses a single beam path to create multiple simultaneous spots, more than previously achieved in other FLEET spot configurations. We perform dotted-line FLEET measurements downstream of a highly turbulent, supersonic nitrogen free jet. Dotted-line FLEET is created by focusing light transmitted by a periodic mask with rectangular slits of 1.6 × 40 mm 2 and an edge-to-edge spacing of 0.5 mm, then focusing the imaged light at the measurement region. Up to seven symmetric dots spaced approximately 0.9 mm apart, with mean full-width at half maximum diameters between 150 and 350 µm, are simultaneously imaged. Both streamwise and radial velocities are computed and presented in this Letter.

47 OTHER INSTRUMENTATION↗
DOE OSTI2012

Porosity in Millimeter-Scale Welds of Stainless Steel: Three-Dimensional Characterization

A variety of edge joints utilizing a continuous wave Nd:YAG laser have been produced and examined in a 304-L stainless steel to advance fundamental understanding of the linkage between processing and resultant microstructure in high-rate solidification events. Acquisition of three-dimensional reconstructions via micro-computed tomography combined with traditional metallography has allowed for qualitative and quantitative characterization of weld joints in a material system of wide use and broad applicability. The presence, variability and distribution of porosity, has been examined for average values, spatial distributions and morphology and then related back to fundamental processing parameters such as weld speed, weld power and laser focal length.

36 MATERIALS SCIENCE↗
DOE OSTI2014

Band-selective shaped pulse for high fidelity quantum control in diamond

High fidelity quantum control of qubits is crucially important for realistic quantum computing, and it becomes more challenging when there are inevitable interactions between qubits. We introduce a band-selective shaped pulse, refocusing BURP (REBURP) pulse, to cope with the problems. The electron spin of nitrogen-vacancy centers in diamond is flipped with high fidelity by the REBURP pulse. In contrast with traditional rectangular pulses, the shaped pulse has almost equal excitation effect in a sharply edged region (in frequency domain). So the three sublevels of host {sup 14}N nuclear spin can be flipped accurately simultaneously, while unwanted excitations of other sublevels (e.g., of a nearby {sup 13}C nuclear spin) is well suppressed. Our scheme can be used for various applications such as quantum metrology, quantum sensing, and quantum information process.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
DOE OSTI2016

Computing Maximum Cardinality Matchings in Parallel on Bipartite Graphs via Tree-Grafting

It is difficult to obtain high performance when computing matchings on parallel processors because matching algorithms explicitly or implicitly search for paths in the graph, and when these paths become long, there is little concurrency. In spite of this limitation, we present a new algorithm and its shared-memory parallelization that achieves good performance and scalability in computing maximum cardinality matchings in bipartite graphs. This algorithm searches for augmenting paths via specialized breadth-first searches (BFS) from multiple source vertices, hence creating more parallelism than single source algorithms. Algorithms that employ multiple-source searches cannot discard a search tree once no augmenting path is discovered from the tree, unlike algorithms that rely on single-source searches. We describe a novel tree-grafting method that eliminates most of the redundant edge traversals resulting from this property of multiple-source searches. We also employ the recent direction-optimizing BFS algorithm as a subroutine to discover augmenting paths faster. Our algorithm compares favorably with the current best algorithms in terms of the number of edges traversed, the average augmenting path length, and the number of iterations. Here, we provide a proof of correctness for our algorithm. Our NUMA-aware implementation is scalable to 80 threads of an Intel multiprocessor and to 240 threads on an Intel Knights Corner coprocessor. On average, our parallel algorithm runs an order of magnitude faster than the fastest algorithms available. The performance improvement is more significant on graphs with small matching number.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2019

Development of a Novel Accelerator for Neutron Transport Solution Using the Galerkin Spectral Element Methods (Final Report)

This report summarizes the results of a three-year research project sponsored by the U.S. Department of Energy (DOE) Nuclear Energy University Program (NEUP) to develop and implement advanced acceleration schemes for the DOE NEAMS neutronics code PROTEUSSN. The project team included the University of Massachusetts Lowell, The Ohio State University, University of Michigan, and Argonne National Laboratory. The PROTEUS code is a high-fidelity capable deterministic neutron transport code based on unstructured finite element meshes, which solves the steady-state and transient neutron transport problem using the 2nd-order discrete ordinate method (SN2ND), the method of characteristics (MOC), and the advanced nodal transport method (NODAL). The DSA scheme has been implemented in PROTEUS to speed up SN transport calculations. The existing DSA scheme employs a consistent finite element formulation on the same fine mesh structure as the SN solution While the use of consistent discretizations makes the DSA method effective, it does not necessarily make it efficient because the numerical solution of a discretized elliptic diffusion problem itself can be costly, particularly when the problem size becomes large. We developed a new discontinuous Galerkin (DG) discretization of the diffusion equation, called DG-DSA, which can effectively and efficiently accelerate the SN transport iterations. As compared with the previous work, the novelty of our method is that the diffusion equation is solved on a coarse-mesh grid using the DG methods, and the DG diffusion discretization incorporates local hp adaptation, i.e., local adaptation of mesh size and/or polynomial degree, based on local total cross section (or optical thickness). Therefore, the resulting number of degrees of freedom (DOF) of the DG discretization is much less than the conventional consistent DSA discretizations, and thus DG-DSA can achieve significant improvement in computational efficiency. We implemented this scheme in PROTEUS-SN. In addition, we developed a new stabilization scheme named linear prolongation CMFD (lpCMFD). A novel feature of this scheme is that the conventional flat flux ratio–based scaling approach is replaced with a linear interpolation of the scalar flux differences at the coarse-mesh cell edges between the neutron transport and CMFD calculations. Fourier convergence analysis and numerical results show that lpCMFD is unconditionally stable and more effective than other CMFD based on acceleration schemes such as pCMFD, odCMFD. We also developed a new nonlinear diffusion acceleration scheme for solving neutron transport equations. This scheme, called LR-NDA, employs a local refinement approach on the framework of CMFD by solving a local boundary value problem of the scalar flux on the coarse-mesh structure to replace the piecewise constant scalar flux obtained by CMFD. The refined flux is then used to update the scalar flux in the neutron transport source iteration. It has been demonstrated that that LR-NDA is much more effective and stable than CMFD for a wide range of optical thicknesses. LR-NDA is a local adaptive method, which means LR-NDA does not necessarily require local refinement for all the coarse-mesh cells on the problem domain, i.e., it can be used only for relatively optically thick regions where the standard CMFD scheme would encounter the convergence problem.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2014

Quantifying Barotrauma Risk to Juvenile Fish during Hydro-turbine Passage

We introduce a method for hydro turbine biological performance assessment (BioPA) to bridge the gap between field and laboratory studies on fish injury and turbine engineering design. Using this method, a suite of biological performance indicators is computed based on simulated data from a computational fluid dynamics (CFD) model of a proposed hydro turbine design. Each performance indicator is a measure of the probability of exposure to a certain dose of an injury mechanism. If the relationship between the dose of an injury mechanism (stressor) and frequency of injury (dose-response) is known from laboratory or field studies, the likelihood of fish injury for a turbine design can be computed from the performance indicator. By comparing the values of the indicators from various turbine designs, engineers and biologists can identify the more-promising designs and operating conditions to minimize hydraulic conditions hazardous to passing fish. In this paper, the BioPA method is applied to estimate barotrauma induced mortal injury rates for Chinook salmon exposed to rapid pressure changes in Kaplan-type hydro turbines. Following the description of the general method, application of the BioPA to estimate the probability of mortal injury from exposure to rapid decompression is illustrated using a Kaplan hydro turbine at the John Day Dam on the Columbia River in the Pacific Northwest region of the USA. The estimated rates of mortal injury increased from 0.3% to 1.7% as discharge through the turbine increased from 334 to 564 m3/s for fish assumed to be acclimated to a depth of 5 m. The majority of pressure nadirs occurred immediately below the runner blades, with the lowest values in the gap at the blade tips and just below the leading edge of the blades. Such information can help engineers focus on problem areas when designing new turbine runners to be more fish-friendly than existing units.

computational fluid dynamics (CFD)↗
DOE OSTI2017

On eigenvalues of a P T-symmetric operator in a thin layer

We consider an elliptic operator with variable coefficients in a thin three-dimensional layer with P T-symmetric boundary conditions. We study the effect of the appearance of isolated eigenvalues at the edges of the gaps in the essential spectrum. We obtain sufficient conditions that guarantee that such eigenvalues either exist or are absent near a given edge of a gap. In the case of existence, the first terms in the asymptotic expansion of these emerging eigenvalues are calculated. Bibliography: 34 titles. (paper)

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2021

Machine Learning Based Software Package for Reproducible Data Analysis for Electron Microscopy

Advances in hardware and computation technologies are enabling large hyperspectral imaging during Electron Microscopy (EM), resulting in datasets being produced at rapidly increasing spatial and temporal resolutions. This presents exciting opportunities for microstructure analysis, but also poses great challenges in data analysis. Under this STTR program, QuesTek Innovations LLC, a leader in the field of integrated computational materials engineering (ICME), collaborated with Lawrence Livermore National Laboratory and Argonne National Laboratory. The team developed an open-source machine learning (ML) powered tool for EM data analysis of multiple systems and data types, and collected EM data for ML model development using the cutting-edge PicoProbe equipment at Argonne National Laboratory.

Lin, Yu↗
DOE OSTI2023

FPGA Acceleration of GCN in Light of the Symmetry of Graph Adjacency Matrix

Graph Convolutional Neural Networks (GCNs) are widely used to process large-scale graph data. Different from deep neural networks (DNNs), GCNs are sparse, irregular, and unstructured, posing unique challenges to hardware acceleration with regular processing elements (PEs). In particular, the adjacency matrix of a GCN is extremely sparse, leading to frequent but irregular memory access, low spatial/temporal data locality and poor data reuse. Furthermore, a realistic graph usually consists of unstructured data (e.g., unbalanced distributions), creating significantly different processing times and imbalanced workload for each node in GCN acceleration. To overcome these challenges, we propose an end-to-end hardware-software co-design to accelerate GCNs on resource-constrained FPGAs with the features including: (1) A custom dataflow that leverages symmetry along the diagonal of the adjacency matrix to accelerate feature aggregation for undirected graphs. We utilize either the upper or the lower triangular matrix of the adjacency matrix to perform aggregation in GCN to improve data reuse. (2) Unified compute cores for both aggregation and transform phases, with full support to the symmetry-based dataflow. These cores can be dynamically reconfigured to the systolic mode for transformation or as individual accumulators for aggregation in GCN processing. (3) Preprocessing of the graph in software to rearrange the edges and features to match the custom dataflow. This step improves the regularity in memory access and data reuse in the aggregation phase. Moreover, we quantize the GCN precision from FP32 to INT8 to reduce the memory footprint without losing the inference accuracy. We implement our accelerator design in Intel Stratix10 MX FPGA board with HBM2, and demonstrate 1.3x-110.5x improvement in end-to-end GCN latency as compared to the state-of the-art FPGA implementations, on the graph datasets of Cora, Pubmed, Citeseer and Reddit.

Nair, Gopikrishnan R.↗
DOE OSTI2016

Broadly Applicable Dose Model for Radiotherapy Beams from 6-25 MV

The goal of modern external beam radiotherapy is to deliver a highly targeted radiation dose to a specified treatment volume while sparing the healthy surrounding tissue as much as possible. However, some healthy tissue radiation exposure is unavoidable. Healthy tissue in the margin of the treatment field will receive absorbed doses on the order of the prescribed dose, and tissue far out of field will receive stray dose from scattered and leakage radiation. These doses can lead to late effects such as secondary cancers both near the treatment field and far out of field in tissues only receiving stray radiation dose. Many researchers have investigated algorithms to model absorbed dose from external beam photon radiation therapy; however, none of these works have fully addressed the stray dose far from the treatment field. The AAPM Task Group Report No. 36 described three main sources of stray radiation from external beam radiation therapy delivered with electron linear accelerators. Radiation scattered from the treatment head, known as head scatter, is primarily important within about 10 cm from the field edge. Patient scatter is an important source up to around 30 cm from the field edge. Finally, leakage radiation emanates from the treatment enclosure and predominates the stray radiation dose beyond about 30 cm. Monte Carlo simulations have been a useful research tool for modeling stray dose, but these methods have not found use in clinical settings due to their complexity and long computational times. The feasibility of analytical models to predict stray dose from radiation therapy has been supported by several works, but few attempts have been made at developing models accurate for both in-field and out-of-field doses. Jagetic and Newhauser reported on one such model that predicts absorbed dose from therapeutic, scatter, and leakage radiation with promising results. This model was validated at 6 MV for Conformal Radiation Therapy (CRT) beams from an Elekta linac. Intensity Modulated Radiation Therapy (IMRT) was not considered, and the model has not been tested at beam energies greater than 6 MV. Additionally, this model relies on proprietary, machine specific parameters, and so adapting the model for use on treatment units from other manufacturers is not straightforward. In this study we aim to test whether a physics-based analytical modeling approach is broadly applicable and if sufficient accuracy can be achieved without the need for proprietary, machine specific parameters. In order to accomplish this, a new analytical model was developed that does not rely on machine specific parameters, so that it can easily be trained on measurements from whatever treatment machine is available at a given clinic. This model was tested using measured data from a variety of treatment machines and techniques in the 6 MV to 25 MV energy interval. (authors)

61 RADIATION PROTECTION AND DOSIMETRY↗
DOE OSTI2024

Ligand Controls Excited Charge Carrier Dynamics in Metal-Rich CdSe Quantum Dots: Computational Insights

Small metal-rich semiconducting quantum dots (QDs) are promising for solid-state lighting and single-photon emission due to their highly tunable yet narrow emission line widths. Nonetheless, the anionic ligands commonly employed to passivate these QDs exert a substantial influence on the optoelectronic characteristics, primarily owing to strong electron–phonon interactions. In this work, we combine time-domain density functional theory and nonadiabatic molecular dynamics to investigate the excited charge carrier dynamics of Cd 28 Se 17 X 22 QDs (X = HCOO – , OH – , Cl – , and SH – ) at ambient conditions. These chemically distinct but regularly used molecular groups influence the dynamic surface-ligand interfacial interactions in Cd-rich QDs, drastically modifying their vibrational characteristics. The strong electron–phonon coupling leads to substantial transient variations at the band edge states. The strength of these interactions closely depends on the physicochemical characteristics of passivating ligands. Consequently, the ligands largely control the nonradiative recombination rates and emission characteristics in these QDs. Our simulations indicate that Cd 28 Se 17 (OH) 22 has the fastest nonradiative recombination rate due to the strongest electron–phonon interactions. Conversely, QDs passivated with thiolate or chloride exhibit considerably longer carrier lifetimes and suppressed nonradiative processes. The ligand-controlled electron–phonon interactions further give rise to the broadest and narrowest intrinsic optical line widths for OH and Cl-passivated single QDs, respectively. Finally, obtained computational insights lay the groundwork for designing appropriate passivating ligands on metal-rich QDs, making them suitable for a wide range of applications, from blue LEDs to quantum emitters.

36 MATERIALS SCIENCE↗
DOE OSTI2015

Dimeric [Mo 2 S 12 ] 2− Cluster: A Molecular Analogue of MoS 2 Edges for Superior Hydrogen‐Evolution Electrocatalysis

Abstract Proton reduction is one of the most fundamental and important reactions in nature. MoS 2 edges have been identified as the active sites for hydrogen evolution reaction (HER) electrocatalysis. Designing molecular mimics of MoS 2 edge sites is an attractive strategy to understand the underlying catalytic mechanism of different edge sites and improve their activities. Herein we report a dimeric molecular analogue [Mo 2 S 12 ] 2− , as the smallest unit possessing both the terminal and bridging disulfide ligands. Our electrochemical tests show that [Mo 2 S 12 ] 2− is a superior heterogeneous HER catalyst under acidic conditions. Computations suggest that the bridging disulfide ligand of [Mo 2 S 12 ] 2− exhibits a hydrogen adsorption free energy near zero (−0.05 eV). This work helps shed light on the rational design of HER catalysts and biomimetics of hydrogen‐evolving enzymes.

Huang, Zhongjie↗
DOE OSTI2022

Understanding and Leveraging the I/O Patterns of Emerging Machine Learning Analytics

The scientific community is currently experiencing unprecedented amounts of data generated by cutting-edge science facilities. Soon facilities will be producing up to 1 PB/s which will force scientist to use more autonomous techniques to learn from the data. The adoption of machine learning methods, like deep learning techniques, in large-scale workflows comes with a shift in the workflow’s computational and I/O patterns. These changes often include iterative processes and model architecture searches, in which datasets are analyzed multiple times in different formats with different model configurations in order to find accurate, reliable and efficient learning models. This shift in behavior brings changes in I/O patterns at the application level as well at the system level. These changes also bring new challenges for the HPC I/O teams, since these patterns contain more complex I/O workloads. In this paper we discuss the I/O patterns experienced by emerging analytical codes that rely on machine learning algorithms and highlight the challenges in designing efficient I/O transfers for such workflows. We comment on how to leverage the data access patterns in order to fetch in a more efficient way the required input data in the format and order given by the needs of the application and how to optimize the data path between collaborative processes. We will motivate our work and show performance gains with a study case of medical applications.

Gainaru, Ana↗
DOE OSTI2026

Switching speed limits in electrically driven VO 2 structural Mott–Peierls transition

Mott materials are archetypal quantum systems actively explored as next-generation electronic and photonic platforms, with potential applications spanning non-Von Neumann computing, robotics, energy storage, and microwave technologies. Among these, vanadium dioxide (VO 2 ) has emerged as one of the most intensively studied compounds, owing to its sharp, near-room-temperature insulator-to-metal phase transition. VO 2 also serves as a benchmark system for testing cutting-edge theories and experimental techniques. Here, we directly visualize the electrically driven transition dynamics in VO 2 using a microwave-driven, frequency-tunable pulsed transmission electron microscope that combines nanometer spatial and picosecond temporal resolution. Under high-frequency (MHz–GHz) excitation, we capture the ultrafast nucleation, propagation, and dissolution of metallic domains within an operating device over millions of reversible cycles. We observe the ultrafast formation of consistent metallic nuclei beneath the electrodes, followed by the propagation of a structural phase front at 4.54 nm/ns. Our experiments show that phonon-mediated structural recovery ultimately limits reversible switching of VO 2 at GHz frequencies, and that a tunable regime for reversible operation spans from kHz to GHz through device engineering. Beyond VO 2 , our approach provides a powerful framework for probing non-equilibrium structural transformations in correlated and functional materials under realistic electrical stimuli.

36 MATERIALS SCIENCE↗
DOE OSTI2025

Dislocation-Grain Boundary Interaction Dataset for FCC Cu

Interactions between dislocations and grain boundaries play a major role in controlling the strength and ductility of structural materials. Experimentally, assessing and probing geometric and stress-based criteria at the local level for dislocation transmission through grain boundaries remains challenging. Therefore, there have been many efforts to systematically generate datasets of dislocation-grain boundary interactions (DGI) via computational models such as molecular dynamics simulations. So far, most DGI datasets have focused only on the subset of nominal minimum-energy grain boundary structures, which limits their applicability, especially to materials processed far from equilibrium. We present a comprehensive database of dislocation-grain boundary interactions for edge, screw, and 60° mixed dislocation with 330 <110> and 257 <112> symmetric tilt grain boundaries (total of 587) in FCC Cu consisting of 73 minimum-energy grain boundary structures and 514 metastable structures. The dataset contains the outcomes for 5234 unique interactions for various dislocation types, grain boundary structures, and applied shear stresses.

36 MATERIALS SCIENCE↗