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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 253 records · Page 14
All sourcesNASA NTRSDOE OSTI
DOE OSTI2022

Additive manufacturing methods using aluminum-rare earth alloys and products made using such methods

Described herein are additive manufacturing methods and products made using such methods. The alloy compositions described herein are specifically selected for the additive manufacturing methods and provide products that exhibit superior mechanical properties as compared to their cast counterparts. Using the compositions and methods described herein, products that do not exhibit substantial coarsening, such as at elevated temperatures, can be obtained. The products further exhibit uniform microstructures along the print axis, thus contributing to improved strength and performance. Additives also can be used in the alloys described herein.

Plotkowski, Alex J.↗
DOE OSTI2023

Assemblies, riveted assemblies, methods for affixing substrates, and methods for mixing materials to form a metallurgical bond

Riveted assemblies are provided that can include a substrate extending between two ends to define opposing substrate surfaces having a first opening extending between the opposing substrate surfaces; a metal-comprising substrate extending between two ends to define opposing metal-comprising substrate surfaces having a second opening extending between the opposing metal-comprising substrate surfaces. The riveted assemblies can further provide that the first and second openings complement one another when the substrate and metal-comprising substrate are engaged; and a rivet shaft extends through the openings and engages the substrate with the rivet head and the metal-comprising substrate with the rivet stop head, at least a portion of the stop head being mixed with, and forming a metallurgical bond with the metal-comprising substrate. Assemblies are provided that can include a rivet stop head mixed with, and metallurgically bonded with a metal-comprising substrate.Methods for affixing substrates to one another are also provided. The methods can include providing a substrate defining an opening configured to receive a rivet shaft; providing a metal-comprising substrate defining a complimentary opening; operatively engaging the substrates with the rivet shaft; and forming a stop head from the rivet shaft to affix the substrates. The method further includes that the stop head mixes with, and forms a metallurgical bond with the metal-comprising substrate. Methods for mixing materials to form a metallurgical bond are also provided. The methods can include forming a metallurgical bond between a stop head of a rivet and a metal-comprising substrate.

Whalen, Scott A.↗
DOE OSTI2023

Nanotube structures, methods of making nanotube structures, and methods of accessing intracellular space

In accordance with the purpose(s) of the present disclosure, as embodied and broadly described herein, embodiments of the present disclosure, in one aspect, relate to methods of making a structure including nanotubes, a structure including nanotubes, methods of delivering a fluid to a cell, methods of removing a fluid to a cell, methods of accessing intracellular space, and the like.

VanDersarl, Jules J.↗
DOE OSTI2020

Lattice Physics Calculations Using the Embedded Self-Shielding Method in Polaris, Part I: Methods and Implementation

Polaris is a 2-dimensional multigroup lattice physics capability in the SCALE code system for the analysis of light water reactor fuel designs. The goal of light water reactor lattice physics codes is to generate few-group homogenized cross sections for downstream full-core nodal diffusion calculations. Additionally, lattice physics calculations contain three primary components: the cross section processing calculation, the 2D transport calculation, and the depletion calculation. This paper summarizes the calculational methods and their implementation into Polaris, with an emphasis on implementation of the embedded self-shielding method. The accuracy of the embedded self-shielding method depends on the procedure used to generate self-shielding factors on the multigroup library. Numerical benchmarks calculations reveal that the accuracy of Polaris eigenvalue predictions is enhanced by (1) using heterogeneous unit cell models to generate the self-shielding factors on the library and (2) using self-shielding factors for within-group scattering cross section.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗
DOE OSTI2022

Quantum Orbital Minimization Method for Excited States Calculation on a Quantum Computer

Herein we propose a quantum-classical hybrid variational algorithm, the quantum orbital minimization method (qOMM), for obtaining the ground state and low-lying excited states of a Hermitian operator. Given parametrized ansatz circuits representing eigenstates, qOMM implements quantum circuits to represent the objective function in the orbital minimization method and adopts a classical optimizer to minimize the objective function with respect to the parameters in ansatz circuits. The objective function has an orthogonality constraint implicitly embedded, which allows qOMM to apply a different ansatz circuit to each input reference state. We carry out numerical simulations that seek to find excited states of H 2 , LiH, and a toy model consisting of four hydrogen atoms arranged in a square lattice in the STO-3G basis with UCCSD ansatz circuits. Comparing the numerical results with existing excited states methods, qOMM is less prone to getting stuck in local minima and can achieve convergence with more shallow ansatz circuits.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2020

The matrix product approximation for the dynamic cavity method

Stochastic dynamics of classical degrees of freedom, defined on vertices of locally tree-like graphs, can be studied in the framework of the dynamic cavity method which is exact for tree graphs. Such models correspond for example to spin-glass systems, Boolean networks, neural networks, and other technical, biological, and social networks. The central objects in the cavity method are edge messages—conditional probabilities of two vertex variable trajectories. In this paper, we discuss a rather pedagogical derivation for the dynamic cavity method, give a detailed account of the novel matrix product edge message (MPEM) algorithm for the solution of the dynamic cavity equation as introduced, and present optimizations and extensions. Matrix product approximations of the edge messages are constructed recursively in an iteration over time. Computation costs and precision can be tuned by controlling the matrix dimensions of the MPEM in truncations. Without truncations, the dynamics is exact. Data for Glauber–Ising dynamics shows a linear growth of computation costs in time. In contrast to Monte Carlo simulations, the approach has a much better error scaling. Hence, it gives for example access to low probability events and decaying observables like temporal correlations. Here, we discuss optimized truncation schemes and an extension that allows to capture models which have a continuum time limit.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2017

A Preconditioned Low-Rank Projection Method with a Rank-Reduction Scheme for Stochastic Partial Differential Equations

Herein, we consider the numerical solution of large systems of linear equations obtained from the stochastic Galerkin formulation of stochastic partial differential equations. We propose an iterative algorithm that exploits the Kronecker product structure of the linear systems. The proposed algorithm efficiently approximates the solutions in low-rank tensor format. Using standard Krylov subspace methods for the data in tensor format is computationally prohibitive due to the rapid growth of tensor ranks during the iterations. To keep tensor ranks low over the entire iteration process, we devise a rank-reduction scheme that can be combined with the iterative algorithm. The proposed rank-reduction scheme identifies an important subspace in the stochastic domain and compresses tensors of high rank on-the-fly during the iterations. The proposed reduction scheme is a coarse-grid method in that the important subspace can be identified inexpensively in a coarse spatial grid setting. The efficiency of the present method is displayed by numerical experiments on benchmark problems.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2016

Improved Quasi-Static Method: IQS Method Implementation for CFEM Diffusion in Rattlesnake

The improved quasi-static (IQS) method is a transient spatial kinetics method that involves factorizing flux into space- and time-dependent components. These components include the flux’s power and shape. Power is time-dependent, while the shape is both space- and time-dependent. However, the impetus of the method is the assumption that the shape is only weakly dependent on time; therefore, the shape may not require computation at every time step, invoking the quasi-static nature. This paper describes the implementation and testing of IQS as an alternative kinetics solver within Rattlesnake to provide improved time performance with minimal reduction in accuracy.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗
DOE OSTI2017

Chapter 1: Introduction. The Uniform Methods Project: Methods for Determining Energy-Efficiency Savings for Specific Measures

This chapter provides a set of model protocols for determining energy and demand savings that result from specific energy efficiency measures implemented through state and utility efficiency programs. The methods described here are approaches that are or are among the most commonly used and accepted in the energy efficiency industry for certain measures or programs. As such, they draw from the existing body of research and best practices for energy efficiency program evaluation, measurement, and verification (EM&V). These protocols were developed as part of the Uniform Methods Project (UMP), funded by the U.S. Department of Energy (DOE). The principal objective for the project was to establish easy-to-follow protocols based on commonly accepted methods for a core set of widely deployed energy efficiency measures.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2017

Chapter 2: Commercial and Industrial Lighting Evaluation Protocol. The Uniform Methods Project: Methods for Determining Energy Efficiency Savings for Specific Measures

The Commercial and Industrial Lighting Evaluation Protocol (the protocol) describes methods to account for gross energy savings resulting from the programmatic installation of efficient lighting equipment in large populations of commercial, industrial, and other nonresidential facilities. This protocol does not address savings resulting from changes in codes and standards, or from education and training activities. A separate Uniform Methods Project (UMP) protocol, Chapter 3: Commercial and Industrial Lighting Controls Evaluation Protocol, addresses methods for evaluating savings resulting from lighting control measures such as adding time clocks, tuning energy management system commands, and adding occupancy sensors.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2021

Prognostics and Health Management in Nuclear Power Plants: An Updated Method-Centric Review With Special Focus on Data-Driven Methods

In a carbon-constrained world, future uses of nuclear power technologies can contribute to climate change mitigation as the installed electricity generating capacity and range of applications could be much greater and more diverse than with the current plants. To preserve the nuclear industry competitiveness in the global energy market, prognostics and health management (PHM) of plant assets is expected to be important for supporting and sustaining improvements in the economics associated with operating nuclear power plants (NPPs) while maintaining their high availability. Of interest are long-term operation of the legacy fleet to 80 years through subsequent license renewals and economic operation of new builds of either light water reactors or advanced reactor designs. Recent advances in data-driven analysis methods—largely represented by those in artificial intelligence and machine learning—have enhanced applications ranging from robust anomaly detection to automated control and autonomous operation of complex systems. The NPP equipment PHM is one area where the application of these algorithmic advances can significantly improve the ability to perform asset management. This paper provides an updated method-centric review of the full PHM suite in NPPs focusing on data-driven methods and advances since the last major survey article was published in 2015. The main approaches and the state of practice are described, including those for the tasks of data acquisition, condition monitoring, diagnostics, prognostics, and planning and decision-making. Research advances in non-nuclear power applications are also included to assess findings that may be applicable to the nuclear industry, along with the opportunities and challenges when adapting these developments to NPPs. Finally, this paper identifies key research needs in regard to data availability and quality, verification and validation, and uncertainty quantification.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗
DOE OSTI2015

Analytic second derivative of the energy for density functional theory based on the three-body fragment molecular orbital method

Analytic second derivatives of the energy with respect to nuclear coordinates have been developed for spin restricted density functional theory (DFT) based on the fragment molecular orbital method (FMO). The derivations were carried out for the three-body expansion (FMO3), and the two-body expressions can be obtained by neglecting the three-body corrections. Also, the restricted Hartree-Fock (RHF) Hessian for FMO3 can be obtained by neglecting the density-functional related terms. In both the FMO-RHF and FMO-DFT Hessians, certain terms with small magnitudes are neglected for computational efficiency. The accuracy of the FMO-DFT Hessian in terms of the Gibbs free energy is evaluated for a set of polypeptides and water clusters and found to be within 1 kcal/mol of the corresponding full (non-fragmented) ab initio calculation. The FMO-DFT method is also applied to transition states in S{sub N}2 reactions and for the computation of the IR and Raman spectra of a small Trp-cage protein (PDB: 1L2Y). Some computational timing analysis is also presented.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2017

Methods for multitasking among real-time embedded compute tasks running on the GPU: Methods for Multitasking Real-time Embedded GPU Computing Tasks

Here, we provide an extensive survey on wide spectrum of scheduling methods for multitasking among graphics processing unit (GPU) computing tasks. We then design several schedulers and explain in detail the selected methods we have developed to implement our scheduling strategies. Next, we compare the performance of schedulers on various workloads running on Fermi and Kepler architectures and arrive at the following major conclusions: (1) Small kernels benefit from running kernels concurrently. (2) The combination of small kernels, high-priority kernels with longer runtimes, and lower-priority kernels with shorter runtimes benefits from a CPU scheduler that dynamically changes kernel order on the Fermi architecture. (3) Because of limitations of existing GPU architectures, currently CPU schedulers outperform their GPU counterparts. We also provide results and observations obtained from implementing and evaluating our schedulers on the NVIDIA Jetson TX1 system-on-chip architecture. We observe that although TX1 has the newer Maxwell architecture, the mechanism used for scheduler timings behaves differently on TX1 compared to Kepler leading to incorrect timings. In this paper, we describe our methods that allow us to report correct timings for CPU schedulers running on TX1. Lastly, we propose new research directions involving the investigation of additional scheduling strategies.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2018

Interface and embedded joint methods for modeling dynamic fracture opening by explosive products [Two methods for modeling dynamic fracture opening by explosive products]

Two computational approaches are proposed in the paper to model dynamic fracture opening by explosive products. The first method assumes that the fractures may be modeled using flow elements embedded along the mesh lines. This method models crack opening in a straightforward way by splitting the nodes of the computational grid. It can account for crack branching; however, the crack directions are constrained by existing mesh faces, which may lead to mesh dependence. Also, the stress in flow elements is calculated explicitly separate from the surrounding solid elements that can impose additional limits on the time step stability condition for explicit integration. The second approach uses embedded flow elements to model the cracks. Typical thickness of the cracks is much smaller than the element size. Therefore, gas pressure in the cracks is assumed to be in stress equilibrium with the element stress. To achieve this, the crack thickness and the state of the gas is updated simultaneously with the state of the solid element which contains the crack. Therefore, the time step is controlled by the explicit solver applied for the solid and does not depend on the thickness of the crack. In conclusion, the main disadvantage of the second approach is due to the complexity of modeling multiple intersecting cracks, which go through the same element. We discuss the areas of possible applications of these 2 methods and the ways to improve and enhance them for future practical applications.

58 GEOSCIENCES↗
DOE OSTI2015

Correlations of Apparent Cellulose Crystallinity Determined by XRD, NMR, IR, Raman, and SFG Methods

Although the cellulose crystallinity index (CI) is used widely, its limitations have not been adequately described. In this study, the CI values of a set of reference samples were determined from X-ray diffraction (XRD), nuclear magnetic resonance (NMR), and infrared (IR), Raman, and vibrational sum frequency generation (SFG) spectroscopies. The intensities of certain crystalline peaks in IR, Raman, and SFG spectra positively correlated with the amount of crystalline cellulose in the sample, but the correlation with XRD was nonlinear as a result of fundamental differences in detection sensitivity to crystalline cellulose and improper baseline corrections for amorphous contributions. It is demonstrated that the intensity and shape of the XRD signal is affected by both the amount of crystalline cellulose and crystal size, which makes XRD analysis complicated. It is clear that the methods investigated show the same qualitative trends for samples, but the absolute CI values differ depending on the determination method. This clearly indicates that the CI, as estimated by different methods, is not an absolute value and that for a given set of samples the CI values can be compared only as a qualitative measure.

09 BIOMASS FUELS↗
DOE OSTI2019

Immersed Boundary Method Halo Exchange in a Hemodynamics Application

In recent years, highly parallelized simulations of blood flow resolving individual blood cells have been demonstrated. Simulating such dense suspensions of deformable particles in flow often involves a partitioned fluid-structure interaction (FSI) algorithm, with separate solvers for Eulerian fluid and Lagrangian cell grids, plus a solver - e.g., immersed boundary method - for their interaction. Managing data motion in parallel FSI implementations is increasingly important, particularly for inhomogeneous systems like vascular geometries. In this study, we evaluate the influence of Eulerian and Lagrangian halo exchanges on efficiency and scalability of a partitioned FSI algorithm for blood flow. We describe an MPI+OpenMP implementation of the immersed boundary method coupled with lattice Boltzmann and finite element methods. We consider how communication and recomputation costs influence the optimization of halo exchanges with respect to three factors: immersed boundary interaction distance, cell suspension density, and relative fluid/cell solver costs.

Gounley, John↗