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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 271 records · Page 15
All sourcesNASA NTRSDOE OSTI
DOE OSTI2010

Quantification of margins and uncertainty for risk-informed decision analysis.

QMU stands for 'Quantification of Margins and Uncertainties'. QMU is a basic framework for consistency in integrating simulation, data, and/or subject matter expertise to provide input into a risk-informed decision-making process. QMU is being applied to a wide range of NNSA stockpile issues, from performance to safety. The implementation of QMU varies with lab and application focus. The Advanced Simulation and Computing (ASC) Program develops validated computational simulation tools to be applied in the context of QMU. QMU provides input into a risk-informed decision making process. The completeness aspect of QMU can benefit from the structured methodology and discipline of quantitative risk assessment (QRA)/probabilistic risk assessment (PRA). In characterizing uncertainties it is important to pay attention to the distinction between those arising from incomplete knowledge ('epistemic' or systematic), and those arising from device-to-device variation ('aleatory' or random). The national security labs should investigate the utility of a probability of frequency (PoF) approach in presenting uncertainties in the stockpile. A QMU methodology is connected if the interactions between failure modes are included. The design labs should continue to focus attention on quantifying uncertainties that arise from epistemic uncertainties such as poorly-modeled phenomena, numerical errors, coding errors, and systematic uncertainties in experiment. The NNSA and design labs should ensure that the certification plan for any RRW is supported by strong, timely peer review and by an ongoing, transparent QMU-based documentation and analysis in order to permit a confidence level necessary for eventual certification.

98 NUCLEAR DISARMAMENT, SAFEGUARDS, AND PHYSICAL P↗
DOE OSTI2022

MISPR : an open-source package for high-throughput multiscale molecular simulations

Computational tools provide a unique opportunity to study and design optimal materials by enhancing our ability to comprehend the connections between their atomistic structure and functional properties. However, designing materials with tailored functionalities is complicated due to the necessity to integrate various computational-chemistry software (not necessarily compatible with one another), the heterogeneous nature of the generated data, and the need to explore vast chemical and parameter spaces. The latter is especially important to avoid bias in scattered data points-based models and derive statistical trends only accessible by systematic datasets. Here, we introduce a robust high-throughput multi-scale computational infrastructure coined MISPR (Materials Informatics for Structure–Property Relationships) that seamlessly integrates classical molecular dynamics (MD) simulations with density functional theory (DFT). By enabling high-performance data analytics and coupling between different methods and scales, MISPR addresses critical challenges arising from the needs of automated workflow management and data provenance recording. The major features of MISPR include automated DFT and MD simulations, error handling, derivation of molecular and ensemble properties, and creation of output databases that organize results from individual calculations to enable reproducibility and transparency. In this work, we describe fully automated DFT workflows implemented in MISPR to compute various properties such as nuclear magnetic resonance chemical shift, binding energy, bond dissociation energy, and redox potential with support for multiple methods such as electron transfer and proton-coupled electron transfer reactions. The infrastructure also enables the characterization of large-scale ensemble properties by providing MD workflows that calculate a wide range of structural and dynamical properties in liquid solutions. MISPR employs the methodologies of materials informatics to facilitate understanding and prediction of phenomenological structure–property relationships, which are crucial to designing novel optimal materials for numerous scientific applications and engineering technologies.

36 MATERIALS SCIENCE↗
DOE OSTI2024

Quantum Computing and Simulations for Energy Applications

While quantum computing (QC) is considered as a paradigm shift in our basic understanding of physical computation, effective implementation of QC in energy applications also depends on progress and development in the dimensions of both QC hardware and algorithms. To fully address the status and future challenges of QC applied within the energy sector, in this presentation, we firstly summarize recent advancements on the applications of QC to energy infrastructure and materials, complex energy system processes, advanced manufacturing, and energy system security. Then, we will demonstrate the results of QC performed both on a simulator and a quantum device targeting on energy-related applications.

Paudel, Hari P.↗
DOE OSTI2011

Many-Group Cross-Section Adjustment Techniques for Boiling Water Reactor Adaptive Simulation

Computational capability has been developed to adjust multigroup neutron cross sections, including self-shielding correction factors, to improve the fidelity of boiling water reactor (BWR) core modeling and simulation. The method involves propagating multigroup neutron cross-section uncertainties through various BWR computational models to evaluate uncertainties in key core attributes such as core k{sub eff}, nodal power distributions, thermal margins, and in-core detector readings. Uncertainty-based inverse theory methods are then employed to adjust multigroup cross sections to minimize the disagreement between BWR core modeling predictions and observed (i.e., measured) plant data. For this paper, observed plant data are virtually simulated in the form of perturbed three-dimensional nodal power distributions with the perturbations sized to represent actual discrepancies between predictions and real plant data. The major focus of this work is to efficiently propagate multigroup neutron cross-section uncertainty through BWR lattice physics and core simulator calculations. The data adjustment equations are developed using a subspace approach that exploits the ill-conditioning of the multigroup cross-section covariance matrix to minimize computation and storage burden. Tikhonov regularization is also employed to improve the conditioning of the data adjustment equations. Expressions are also provided for posterior covariance matrices of both the multigroup cross-section and core attributes uncertainties.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2011

COMPUTER MODELING OF HIGH-LEVEL WASTE GLASS TEMPERATURES WITHIN DWPF CANISTERS DURING POURING AND COOL DOWN

This report describes the results of a computer simulation study to predict the temperature of the glass at any location inside a DWPF canister during pouring and subsequent cooling. These simulations are an integral part of a larger research focus aimed at developing methods to predict, evaluate, and ultimately suppress nepheline formation in HLW glasses. That larger research focus is centered on holistically understanding nepheline formation in HLW glass by exploring the fundamental thermal and chemical driving forces for nepheline crystallization with respect to realistic processing conditions. Through experimental work, the goal is to integrate nepheline crystallization potential in HLW glass with processing capability to ultimately optimize waste loading and throughput while maintaining an acceptable product with respect to durability. The results of this study indicated severe temperature gradients and prolonged temperature dwell times exist throughout different locations in the canister and that the time and temperatures that HLW glass is subjected to during processing is a function of pour rate. The simulations indicate that crystallization driving forces are not uniform throughout the glass volume in a DWPF (or DWPF-like) canister and illustrate the importance of considering overall kinetics (chemical and thermal driving forces) of nepheline formation when developing methods to predict and suppress its formation in HLW glasses. The intended path forward is to use the simulation data both as a driver for future experimental work and, as an investigative tool for evaluating the impact of experimental results. Simulation data will be used to develop laboratory experiments to more acutely evaluate nepheline formation in HLW glass by incorporating the simulated temperatures throughout the canister into the laboratory experiments. Concurrently, laboratory experiments will be performed to identify nepheline crystallization potential in HLW glass as a function of time and temperature, the results of which will be fed back into simulations to evaluate the potential impacts. Through an iterative process involving computer simulations and experimental results, the potential for nepheline crystallization in HLW glass can be predicted, evaluated, and suppressed to maximize waste loading and throughput of canisters.

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗
DOE OSTI2022

Sensitivity Analyses for Monte Carlo Sampling-Based Particle Simulations

Computational design-based optimization is a well-used tool in science and engineering. Our report documents the successful use of a particle sensitivity analysis for design-based optimization within Monte Carlo sampling-based particle simulation—a currently unavailable capability. Such a capability enables the particle simulation communities to go beyond forward simulation and promises to reduce the burden on overworked analysts by getting more done with less computation.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2017

Advanced Simulation and Computing FY18 Implementation Plan, Rev. 0

The ASC Program continues to improve its unique tools to solve stockpile problems— with a focus on sufficient resolution, dimensionality, and scientific detail—to enable Quantification of Margins and Uncertainties (QMU) and to resolve the increasingly difficult analyses needed for stockpile stewardship. The needs of the Directed Stockpile Work (DSW) and major modernization programs also drive the requirements for simulation and computational resources. These requirements include planned LEPs, stockpile support activities, and mitigation efforts against the potential for technical surprise. All of the weapons within the current stockpile are in some stage of the life extension process. The simulation and computational capabilities are crucial for successful execution of these lifetime extensions and for ensuring NNSA can certify these life-extended weapons without conducting a UGT. Specific work activities and scope contained in this Implementation Plan (IP) represent the full-year annual operating plan for FY18. The Initial IP effective October 1, 2017, should be consistent with: 1) the Department’s Base Table when operating under a Continuing Resolution (CR); and 2) the final signed appropriation or full-year CR once enacted.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2018

Advanced Simulation and Computing FY19 Implementation Plan, Rev. 0

The ASC Program continues to improve its unique tools to solve stockpile problems— with a focus on sufficient resolution, dimensionality, and scientific detail—to enable Quantification of Margins and Uncertainties (QMU) and to resolve the increasingly difficult analyses needed for stockpile stewardship. The needs of the Directed Stockpile Work (DSW) and major modernization programs also drive the requirements for simulation and computational resources. These requirements include planned LEPs, stockpile support activities, and mitigation efforts against the potential for technical surprise. All of the weapons within the current stockpile are in some stage of the life extension process. The simulation and computational capabilities are crucial for successful execution of these lifetime extensions and for ensuring NNSA can certify these life-extended weapons without conducting a UGT. Specific work activities and scope contained in this Implementation Plan (IP) represent the full-year annual operating plan for FY19. The Initial IP, effective August 8, 2018, should be consistent with the Department’s Base Table when operating under a Continuing Resolution (CR). The final IP, effective date TBD, is consistent with the final, enacted appropriation.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2011

X-ray ablation rates in inertial confinement fusion capsule materials

X-ray ablation rates have been measured in beryllium, copper-doped beryllium, germanium-doped plastic (Ge-doped CH), and diamondlike high density carbon (HDC) for radiation temperatures T in the range of 160–260 eV. In beryllium, the measured ablation rates range from 3 to 12 mg/cm2/ns; in Ge-doped CH, the ablation rates range from 2 to 6 mg/cm2/ns; and for HDC, the rates range from 2 to 9 mg/cm2/ns. The ablation rates follow an approximate T3 dependence and, for T below 230 eV, the beryllium ablation rates are significantly higher than HDC and Ge-doped CH. The corresponding implied ablation pressures are in the range of 20–160 Mbar, scaling as T3.5. The results are found to be well predicted by computational simulations using the physics packages and computational techniques employed in the design of indirect-drive inertial confinement fusion capsules. An iterative rocket model has been developed and used to compare the ablation rate data set to spherical indirect-drive capsule implosion experiments and to confirm the validity of some aspects of proposed full-scale National Ignition Facility ignition capsule designs.

Olson, R. E.↗
DOE OSTI2014

Onboard functional and molecular imaging: A design investigation for robotic multipinhole SPECT

Purpose: Onboard imaging—currently performed primarily by x-ray transmission modalities—is essential in modern radiation therapy. As radiation therapy moves toward personalized medicine, molecular imaging, which views individual gene expression, may also be important onboard. Nuclear medicine methods, such as single photon emission computed tomography (SPECT), are premier modalities for molecular imaging. The purpose of this study is to investigate a robotic multipinhole approach to onboard SPECT. Methods: Computer-aided design (CAD) studies were performed to assess the feasibility of maneuvering a robotic SPECT system about a patient in position for radiation therapy. In order to obtain fast, high-quality SPECT images, a 49-pinhole SPECT camera was designed which provides high sensitivity to photons emitted from an imaging region of interest. This multipinhole system was investigated by computer-simulation studies. Seventeen hot spots 10 and 7 mm in diameter were placed in the breast region of a supine female phantom. Hot spot activity concentration was six times that of background. For the 49-pinhole camera and a reference, more conventional, broad field-of-view (FOV) SPECT system, projection data were computer simulated for 4-min scans and SPECT images were reconstructed. Hot-spot localization was evaluated using a nonprewhitening forced-choice numerical observer. Results: The CAD simulation studies found that robots could maneuver SPECT cameras about patients in position for radiation therapy. In the imaging studies, most hot spots were apparent in the 49-pinhole images. Average localization errors for 10-mm- and 7-mm-diameter hot spots were 0.4 and 1.7 mm, respectively, for the 49-pinhole system, and 3.1 and 5.7 mm, respectively, for the reference broad-FOV system. Conclusions: A robot could maneuver a multipinhole SPECT system about a patient in position for radiation therapy. The system could provide onboard functional and molecular imaging with 4-min scan times.

62 RADIOLOGY AND NUCLEAR MEDICINE↗
DOE OSTI2019

Rigorous Data Fusion for Computationally Expensive Simulations

This manuscript comprises the final report for the 1-year, FY19 LDRD project "Rigorous Data Fusion for Computationally Expensive Simulations," wherein an alternative approach to Bayesian calibration was developed based a new sampling technique called VoroSpokes. Vorospokes is a novel quadrature and sampling framework defined with respect to Voronoi tessellations of bounded domains in $R^d$ developed within this project. In this work, we first establish local quadrature and sampling results on convex polytopes using randomly directed rays, or spokes, to approximate the quantities of interest for a specified target function. A theoretical justification for both procedures is provided along with empirical results demonstrating the unbiased convergence in the resulting estimates/samples. The local quadrature and sampling procedures are then extended to global procedures defined on more general domains by applying the local results to the cells of a Voronoi tessellation covering the domain in consideration. We then demonstrate how the proposed global sampling procedure can be used to define a natural framework for adaptively constructing Voronoi Piecewise Surrogate (VPS) approximations based on local error estimates. Finally, we show that the adaptive VPS procedure can be used to form a surrogate model approximation to a specified, potentially unnormalized, density function, and that the global sampling procedure can be used to efficiently draw independent samples from the surrogate density in parallel. The performance of the resulting VoroSpokes sampling framework is assessed on a collection of Bayesian inference problems and is shown to provide highly accurate posterior predictions which align with the results obtained using traditional methods such as Gibbs sampling and random-walk Markov Chain Monte Carlo (MCMC). Importantly, the proposed framework provides a foundation for performing Bayesian inference tasks which is entirely independent from the theory of Markov chains.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2014

Nonlinear buckling analyses of a small-radius carbon nanotube

Carbon nanotube (CNT) was first discovered by Sumio Iijima. It has aroused extensive attentions of scholars from all over the world. Over the past two decades, we have acquired a lot of methods to synthesize carbon nanotubes and learn their many incredible mechanical properties such as experimental methods, theoretical analyses, and computer simulations. However, the studies of experiments need lots of financial, material, and labor resources. The calculations will become difficult and time-consuming, and the calculations may be even beyond the realm of possibility when the scale of simulations is large, as for computer simulations. Therefore, it is necessary for us to explore a reasonable continuum model, which can be applied into nano-scale. This paper attempts to develop a mathematical model of a small-radius carbon nanotube based on continuum theory. An Isotropic circular cross-section, Timoshenko beam model is used as a simplified mechanical model for the small-radius carbon nanotube. Theoretical part is mainly based on modified couple stress theory to obtain the numerical solutions of buckling deformation. Meanwhile, the buckling behavior of the small radius carbon nanotube is simulated by Molecular Dynamics method. By comparing with the numerical results based on modified couple stress theory, the dependence of the small-radius carbon nanotube mechanical behaviors on its elasticity constants, small-size effect, geometric nonlinearity, and shear effect is further studied, and an estimation of the small-scale parameter of a CNT (5, 5) is obtained.

42 ENGINEERING↗
DOE OSTI2011

Computational Particle Dynamic Simulations on Multicore Processors (CPDMu) Final Report Phase I

Statement of Problem - Department of Energy has many legacy codes for simulation of computational particle dynamics and computational fluid dynamics applications that are designed to run on sequential processors and are not easily parallelized. Emerging high-performance computing architectures employ massively parallel multicore architectures (e.g., graphics processing units) to increase throughput. Parallelization of legacy simulation codes is a high priority, to achieve compatibility, efficiency, accuracy, and extensibility. General Statement of Solution - A legacy simulation application designed for implementation on mainly-sequential processors has been represented as a graph G. Mathematical transformations, applied to G, produce a graph representation {und G} for a high-performance architecture. Key computational and data movement kernels of the application were analyzed/optimized for parallel execution using the mapping G {yields} {und G}, which can be performed semi-automatically. This approach is widely applicable to many types of high-performance computing systems, such as graphics processing units or clusters comprised of nodes that contain one or more such units. Phase I Accomplishments - Phase I research decomposed/profiled computational particle dynamics simulation code for rocket fuel combustion into low and high computational cost regions (respectively, mainly sequential and mainly parallel kernels), with analysis of space and time complexity. Using the research team's expertise in algorithm-to-architecture mappings, the high-cost kernels were transformed, parallelized, and implemented on Nvidia Fermi GPUs. Measured speedups (GPU with respect to single-core CPU) were approximately 20-32X for realistic model parameters, without final optimization. Error analysis showed no loss of computational accuracy. Commercial Applications and Other Benefits - The proposed research will constitute a breakthrough in solution of problems related to efficient parallel computation of particle and fluid dynamics simulations. These problems occur throughout DOE, military and commercial sectors: the potential payoff is high. We plan to license or sell the solution to contractors for military and domestic applications such as disaster simulation (aerodynamic and hydrodynamic), Government agencies (hydrological and environmental simulations), and medical applications (e.g., in tomographic image reconstruction). Keywords - High-performance Computing, Graphic Processing Unit, Fluid/Particle Simulation. Summary for Members of Congress - Department of Energy has many simulation codes that must compute faster, to be effective. The Phase I research parallelized particle/fluid simulations for rocket combustion, for high-performance computing systems.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2011

Redox-Promoting Protein Motions in Rubredoxin

Proteins are dynamic objects, constantly undergoing conformational fluctuations, yet the linkage between internal protein motion and function is widely debated. This manuscript reports on the characterization of temperature-activated collective and individual atomic motions of oxidized rubredoxin, a small 53 residue protein from thermophilic Pyrococcus furiosus (RdPf), by neutron scattering and computational simulations. The changes in motion have been explored in connection to their role in promoting reduction of the Fe+3 ion which is responsible for the electron transfer function of RdPf. Just above the dynamical transition temperature of 220 K which marks the onset of significant anharmonic motions of the protein, the computer simulations show both a significant reorientation of the average electrostatic force experienced by the Fe+3 ion and a dramatic rise in its strength. At higher temperatures, additional anharmonic modes become activated which dominate the electrostatic fluctuations experienced by the ion. At 360 K, close to the optimal growth temperature of Pyrococcus furiosus, computer simulations show that three anharmonic modes involving two conserved residues located at the protein active site (Ile7 and Ile40) give rise to the majority of the electrostatic fluctuations experienced by the Fe+3 ion and include displacements which allow solvent access to the ion. The low-frequency, high amplitude motions of these residues at low temperatures may be precursors of the high temperature, anharmonic motions necessary for protein function.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2019

Advanced Simulation and Computing (ASC) Software Quality Plan: ASC Software Quality Engineering Practices (V.4.0)

The purpose of the Sandia National Laboratories (SNL) Advanced Simulation and Computing (ASC) Software Quality Plan is to clearly identify the software quality engineering practices that are the basis for continually improving the quality of ASC software products. This plan defines the SNL ASC Program software quality engineering practices and provides a mapping of these practices to Laboratory Policy System IT008: Provide Quality Software Policy. This plan also identifies ASC Program Management and the software project teams' responsibilities in implementing quality software engineering practices and in assessing progress towards achieving their software quality goals.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2015

A 2.5D Computational Method to Simulate Cylindrical Fluidized Beds

In this paper, the limitations of axisymmetric and Cartesian two-dimensional (2D) simulations of cylindrical gas-solid fluidized beds are discussed. A new method has been proposed to carry out pseudo-two-dimensional (2.5D) simulations of a cylindrical fluidized bed by appropriately combining computational domains of Cartesian 2D and axisymmetric simulations. The proposed method was implemented in the open-source code MFIX and applied to the simulation of a lab-scale bubbling fluidized bed with necessary sensitivity study. After a careful grid study to ensure the numerical results are grid independent, detailed comparisons of the flow hydrodynamics were presented against axisymmetric and Cartesian 2D simulations. Furthermore, the 2.5D simulation results have been compared to the three-dimensional (3D) simulation for evaluation. This new approach yields better agreement with the 3D simulation results than with axisymmetric and Cartesian 2D simulations.

Li, Tingwen↗