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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 1,729 records · Page 96
All sourcesNASA NTRSDOE OSTI
DOE OSTI2017

Modal Substructuring of Geometrically Nonlinear Finite Element Models with Interface Reduction

Substructuring methods have been widely used in structural dynamics to divide large, complicated finite element models into smaller substructures. For linear systems, many methods have been developed to reduce the subcomponents down to a low order set of equations using a special set of component modes, and these are then assembled to approximate the dynamics of a large scale model. In this paper, a substructuring approach is developed for coupling geometrically nonlinear structures, where each subcomponent is drastically reduced to a low order set of nonlinear equations using a truncated set of fixedinterface and characteristic constraint modes. The method used to extract the coefficients of the nonlinear reduced order model (NLROM) is non-intrusive in that it does not require any modification to the commercial FEA code, but computes the NLROM from the results of several nonlinear static analyses. The NLROMs are then assembled to approximate the nonlinear differential equations of the global assembly. The method is demonstrated on the coupling of two geometrically nonlinear plates with simple supports at all edges. The plates are joined at a continuous interface through the rotational degrees-of-freedom (DOF), and the nonlinear normal modes (NNMs) of the assembled equations are computed to validate the models. The proposed substructuring approach reduces a 12,861 DOF nonlinear finite element model down to only 23 DOF, while still accurately reproducing the first three NNMs of the full order model.

42 ENGINEERING↗
DOE OSTI2015

Reference interaction site model with hydrophobicity induced density inhomogeneity: An analytical theory to compute solvation properties of large hydrophobic solutes in the mixture of polyatomic solvent molecules

Reference interaction site model (RISM) has recently become a popular approach in the study of thermodynamical and structural properties of the solvent around macromolecules. On the other hand, it was widely suggested that there exists water density depletion around large hydrophobic solutes (>1 nm), and this may pose a great challenge to the RISM theory. In this paper, we develop a new analytical theory, the Reference Interaction Site Model with Hydrophobicity induced density Inhomogeneity (RISM-HI), to compute solvent radial distribution function (RDF) around large hydrophobic solute in water as well as its mixture with other polyatomic organic solvents. To achieve this, we have explicitly considered the density inhomogeneity at the solute-solvent interface using the framework of the Yvon-Born-Green hierarchy, and the RISM theory is used to obtain the solute-solvent pair correlation. In order to efficiently solve the relevant equations while maintaining reasonable accuracy, we have also developed a new closure called the D2 closure. With this new theory, the solvent RDFs around a large hydrophobic particle in water and different water-acetonitrile mixtures could be computed, which agree well with the results of the molecular dynamics simulations. Furthermore, we show that our RISM-HI theory can also efficiently compute the solvation free energy of solute with a wide range of hydrophobicity in various water-acetonitrile solvent mixtures with a reasonable accuracy. We anticipate that our theory could be widely applied to compute the thermodynamic and structural properties for the solvation of hydrophobic solute.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2021

Simplifying computational workflows with the Multiscale Atomic Zeolite Simulation Environment (MAZE)

Zeolites, an important class of 3-dimensional nanoporous materials, have been widely explored for a variety of applications including gas storage, separations, and catalysis. As the properties of these aluminosilicate materials depend on a number of factors (e.g., framework topology, Si/Al ratio, extra-framework cations etc.), detailed experiments (e.g., catalytic properties, adsorption capacities etc.) are often limited to only a handful of materials. Computational methods have played an important role in (1) providing molecular level insights to rationalize experimental observations, and (2) screening large libraries of zeolites to identify promising candidates for experimental synthesis and validation. Different levels of theory and computational chemistry codes are necessary to describe the range of relevant phenomena such as adsorption (e.g., grand canonical Monte Carlo), diffusion (e.g., molecular dynamics), and chemical reactions (e.g., density functional theory). Manipulation of atomic structures, handling of input files, and developing robust workflows becomes quite cumbersome. To mitigate these challenges, we describe the development of the Multiscale Atomic Zeolite Simulation Environment (MAZE) – a Python package that simplifies zeolite-specific calculation workflows by providing a user-friendly interface for systematically manipulating zeolite structures

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2017

Diffusive confinement of free radical intermediates in the OH radical oxidation of semisolid aerosols

Multiphase chemical reactions (gas + solid/liquid) involve a complex interplay between bulk and interface chemistry, diffusion, evaporation, and condensation. Reactions of atmospheric aerosols are an important example of this type of chemistry: the rich array of particle phase states and multiphase transformation pathways produce diverse but poorly understood interactions between chemistry and transport. Their chemistry is of intrinsic interest because of their role in controlling climate. Their characteristics also make them useful models for the study of principles of reactivity of condensed materials under confined conditions. Previously, we have reported a computational study of the oxidation chemistry of a liquid aliphatic aerosol. In this study, we extend the calculations to investigate nearly the same reactions at a semisolid gas-aerosol interface. A reaction-diffusion model for heterogeneous oxidation of triacontane by hydroxyl radicals (OH) is described, and its predictions are compared to measurements of aerosol size and composition, which evolve continuously during oxidation. Our results are also explicitly compared to those obtained for the corresponding liquid system, squalane, to pinpoint salient elements controlling reactivity. The diffusive confinement of the free radical intermediates at the interface results in enhanced importance of a few specific chemical processes such as the involvement of aldehydes in fragmentation and evaporation, and a significant role of radical-radical reactions in product formation. The simulations show that under typical laboratory conditions semisolid aerosols have highly oxidized nanometer-scale interfaces that encapsulate an unreacted core and may confer distinct optical properties and enhanced hygroscopicity. This highly oxidized layer dynamically evolves with reaction, which we propose to result in plasticization. The validated model is used to predict chemistry under atmospheric conditions, where the OH radical concentration is much lower. The oxidation reactions are more strongly influenced by diffusion in the particle, resulting in a more liquid-like character.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2013

Wedgehog Manual and Interface Guide, Jayenne-7_0_0

Wedgehog is an IMC package developed by the CCS–2’s Monte Carlo Team1 . Wedgehog is designed to interface with a time-split radiation-hydrodynamics (rad-hydro) code and supports one-dimensional R, two-dimensional RZ or three dimensional XY Z geometry. The geometry is confined to logically rectangular Adaptive Mesh Refinement (AMR) meshes with unit aspect ratios and 2:1 refinement between adjacent cells. Wedgehog supports both two and three temperature simulations. Available scattering models for photon-electron interaction include Compton and isotropic scattering. It maintains a census of particles in between time steps to preserve the contents of the radiation field. Wedgehog can accommodate frequency dependence by using a “Multigroup” (MG) approximation that essentially averages the frequency-dependent opacity information into discrete bins. Additionally, Wedge hog includes a capability to use Opacity Distribution Factors (ODFs) that may be generated with the XCP-5 code TOPS. A previous version of Wedgehog that utilizes IBM’s Cell chip is available for the Roadrunner petascale computer at Los Alamos National Laboratory (circa 2006-2013, estimated). However, as Roadrunner is going out of service in the near future, we have dropped support for the interfaces that were deprecated in Jayenne 6 4 0 and removed in Jayenne-7 0 0. The Roadrunner version had the same interface as the mainline code and is available in RZ and XYZ geometry with all the same features except for flux tallies across a surface (i.e., tally sphere and RZ line-segment).

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2023

Density variance dynamics in disparate shock tubes

This report discusses two experiments which investigate thin layer, heavy curtain fragmentation from the perspective of a Reynolds-Averaged mix model, in drastically disparate experimental regimes. The first, the centimeter/millisecond-scale “Horizontal Shock Tube” (HST) is a compressed-gas piston-driven shock tube experiment. The second, the “Multishock thin layer” (Mshock) experiment performed at the National Ignition Facility, is a micrometer/nanosecond-scale laser-driven shock tube experiment. Both are situations in which a heavy plane layer (a ‘curtain’) is initially suspended in a lighter medium. After being shocked from at least one side, the layer translates while its interfaces evolve due to the excitation of the Richtmyer-Meshkov instability at its surfaces. The evolution of density variance, which initially exists only on the surface of the layer, as it comes to encompass the whole layer interior is used as a description of layer fragmentation and dissolution. These experiments have each been simulated in the Los Alamos National Laboratory multi-physics code xRAGE, which includes fundamental hydrodynamics, extended plasma physics and radiation effects which are important to drive the high-energy density experiment, and the Besnard-Harlow-Rauenzahn (BHR) turbulence model. In each, the principal diagnostic for comparison is an experimental metric for the density (co)variance, b, which tracks the moments of the density field at the curtain interfaces and body. Due to experimental constraints in different regimes (i.e. optical diagnostics can be deployed on conventional shock tubes, while the plasma shock tubes must be imaged by x-rays; interfaces can be imposed to specification on laser-driven experiments, which are stored in the solid phase, while conventional experiments have imperfect control of the flow fields which separate the layer, etc.) the experiments are not designed to be perfect scaled cognates of one another. However, despite the separation of six orders of magnitude of scaling in time, and four in space, we are able to demonstrate that the same turbulence model, operating in the same fashion in the same computer code, is able to reproduce results in each experiment, by tracking evolution due to common relevant physics. Additionally, we will present preliminary work toward density variance comparisons in a single-interface Richtmyer-Meshkov configuration, the conventional fluid “Vertical Shock Tube” (VST) experiment, and the Modal Initial Conditions (ModCons) campaign fielded at the OMEGA-EP laser facility.

42 ENGINEERING↗
DOE OSTI2024

Interpretable Machine Learning Models for Practical Antimonate Electrocatalyst Performance

Computationally predicting the performance of catalysts under reaction conditions is a challenging task due to the complexity of catalytic surfaces and their evolution in situ, different reaction paths, and the presence of solid-liquid interfaces in the case of electrochemistry. We demonstrate here how relatively simple machine learning models can be found that enable prediction of experimentally observed onset potentials. Inputs to our model are comprised of data from the oxygen reduction reaction on non-precious transition-metal antimony oxide nanoparticulate catalysts with a combination of experimental conditions and computationally affordable bulk atomic and electronic structural descriptors from density functional theory simulations. From human-interpretable genetic programming models, we identify key experimental descriptors and key supplemental bulk electronic and atomic structural descriptors that govern trends in onset potentials for these oxides and deduce how these descriptors should be tuned to increase onset potentials. Here, we finally validate these machine learning predictions by experimentally confirming that scandium as a dopant in nickel antimony oxide leads to a desired onset potential increase. Macroscopic experimental factors are found to be crucially important descriptors to be considered for models of catalytic performance, highlighting the important role machine learning can play here even in the presence of small datasets.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2022

Analytical advances to study the air – water interfacial chemistry in the atmosphere

Formation of aqueous secondary organic aerosol (aqSOA) at the air – liquid interface recently has attracted a lot of attention in atmospheric chemistry. The discrepancies in mass distributions, aerosol oxidative capacity, liquid water content, hygroscopic growth of aerosols, and formation of clouds and fogs suggest that interfacial chemistry play a more important role than previously deemed. However, detailed mechanisms at the air–water interface remain unclear owing to the lack of comprehensive understanding that underpins complicated interfacial phenomena, which are not easily measurable from field campaigns, laboratory measurements, or computational simulations. Here, this review highlights relevant and recent technical advancement employed to study aqSOA encompassing spectroscopy and mass spectrometry. The current knowledge on the aqSOA processes is digested with an emphasis on recent research of interfacial aqSOA formation including laboratory studies and model simulations. Finally, future directions of the interfacial chemistry are recommended for field and laboratory studies as well as theoretical efforts to resolve interfacial challenges in atmospheric chemistry.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2011

A posteriori error analysis for a cut cell finite volume method

We study the solution of a diffusive process in a domain where the diffusion coefficient changes discontinuously across a curved interface. We consider discretizations that use regularly-shaped meshes, so that the interface “cuts” through the cells (elements or volumes) without respecting the regular geometry of the mesh. Consequently, the discontinuity in the diffusion coefficients has a strong impact on the accuracy and convergence of the numerical method. This motivates the derivation of computational error estimates that yield accurate estimates for specified quantities of interest. For this purpose, we adapt the well-known adjoint based a posteriori error analysis technique used for finite element methods. In order to employ this method, we describe a systematic approach to discretizing a cut-cell problem that handles complex geometry in the interface in a natural fashion yet reduces to the well-known Ghost Fluid Method in simple cases. We test the accuracy of the estimates in a series of examples.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2011

Scale 6.1 Enhancements for Nuclear Criticality Safety

The Scale code system developed at Oak Ridge National Laboratory provides a comprehensive, verified and validated, user-friendly tool set for criticality safety, reactor physics, radiation shielding, and sensitivity and uncertainty analysis. For more than 30 years, regulators, licensees, and research institutions around the world have used Scale for safety analysis and design. Scale provides a 'plug-and-play' framework with 89 computational modules, including three deterministic and three Monte Carlo radiation transport solvers that are selected based on the desired solution. Scale's graphical user interfaces assist with accurate system modeling and convenient access to desired results. Scale 6.1 builds on the existing capabilities and ease-of-use of Scale and provides several new features such as improved options and capabilities for sensitivity and uncertainty analysis calculations, improved flexibility in shielding and criticality accident alarm system calculations with automated variance reduction, and new options for the definition of group structures for depletion calculations. The Scale 6.1 development team has focused on improved robustness via substantial additional regression testing and verification for new and existing features, providing improved performance relative to Scale 6.0, especially in reactor physics calculations and in the nuclear data used for source term characterization and shielding calculations.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗
DOE OSTI2015

Radiograph and passive data analysis using mixed variable optimization

Disclosed herein are representative embodiments of methods, apparatus, and systems for performing radiography analysis. For example, certain embodiments perform radiographic analysis using mixed variable computation techniques. One exemplary system comprises a radiation source, a two-dimensional detector for detecting radiation transmitted through a object between the radiation source and detector, and a computer. In this embodiment, the computer is configured to input the radiographic image data from the two-dimensional detector and to determine one or more materials that form the object by using an iterative analysis technique that selects the one or more materials from hierarchically arranged solution spaces of discrete material possibilities and selects the layer interfaces from the optimization of the continuous interface data.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2026

A Graphical User Interface for the Deep Underground Neutrino Experiment Robotic Test Stand

In preparation for DUNE, Fermilab along with six other institutions are testing cold electronics for quality control before components placed in the far detector. We test them by using a robotic arm that places these chips into sockets on a computer board that will test their functionality. Up until now, the chips have been tested using a command line script that drives a state machine to conduct tests step-by-step. In order to lower the skill barrier to conduct tests and to speed up the quality control process, I was tasked to create a graphical user interface that would allow users to use buttons, text boxes, and drop-down menus to input information and tell the testing state machine how to operate. I had to learn about the Python package Tkinter to start the process of widget placement. I further developed a pause feature unused in the previous command line script that would allow the user to shut down testing gracefully, bring the robotic arm to go back to ground state, and go forward or backward a step in the testing process. After completing the basic functionality of the GUI, I started testing production chips with the GUI to debug. Some issues were found, which required me to further develop parts of the inherited state machine code. The code for the GUI has now been pushed into the copy the DUNE/FD_CE git repository and will soon be merged with the official DUNE/FD_CE repository so that the other institutions testing DUNE cold electronics can use and expand upon it.

Gutierrez Villanueva, Jaziel [Fermilab]↗
DOE OSTI2012

Enhancements in SCALE 6.1

The SCALE code system developed at Oak Ridge National Laboratory provides a comprehensive, verified and validated, user-friendly tool set for criticality safety, reactor physics, radiation shielding, and sensitivity and uncertainty analysis. For more than 30 years, regulators, licensees, and research institutions around the world have used SCALE for nuclear safety analysis and design. SCALE provides a 'plug-and-play' framework with 89 computational modules, including three deterministic and three Monte Carlo radiation transport solvers that are selected based on the desired solution. SCALE's graphical user interfaces assist with accurate system modeling, visualization, and convenient access to desired results. SCALE 6.1 builds on the existing capabilities and ease-of-use of SCALE and provides several new features such as enhanced lattice physics capabilities and multigroup Monte Carlo depletion, improved options and capabilities for sensitivity and uncertainty analysis calculations, improved flexibility in shielding and criticality accident alarm system calculations with automated variance reduction, and new options for the definition of group structures for depletion calculations. The SCALE 6.1 development team has focused on improved robustness via substantial additional regression testing and verification for new and existing features, providing improved performance relative to SCALE 6.0, especially in reactor physics calculations and in the nuclear data used for source term characterization and shielding calculations.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗