Explicit synchronous partitioned algorithms for interface problems based on Lagrange multipliers
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97 MATHEMATICS AND COMPUTING↗
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The VTK-m User's Guide (V. 2.2)
High-performance computing relies on ever finer threading. Advances in processor technology include ever greater numbers of cores, hyperthreading, accelerators with integrated blocks of cores, and special vectorized instructions, all of which require more software parallelism to achieve peak performance. Traditional visualization solutions cannot support this extreme level of concurrency. Extreme scale systems require a new programming model and a fundamental change in how we design algorithms. To address these issues we created VTK-m: the visualization toolkit for multi-/many-core architectures. VTK-m supports a number of algorithms and the ability to design further algorithms through a top-down design with an emphasis on extreme parallelism. VTK-m also provides support for finding and building links across topologies, making it possible to perform operations that determine manifold surfaces, interpolate generated values, and find adjacencies. Although VTK-m provides a simplified high-level interface for programming, its template-based code removes the overhead of abstraction.
97 MATHEMATICS AND COMPUTING↗
Analytical Modeling of Triple-Metal Hetero-Dielectric DG SON TFET
In this paper, a 2-D analytical model of triple-metal hetero-dielectric DG TFET is presented by combining the concepts of triple material gate engineering and hetero-dielectric engineering. Three metals with different work functions are used as both front- and back gate electrodes to modulate the barrier at source/channel and channel/drain interface. In addition to this, front gate dielectric consists of high-K HfO{sub 2} at source end and low-K SiO{sub 2} at drain side, whereas back gate dielectric is replaced by air to further improve the ON current of the device. Surface potential and electric field of the proposed device are formulated solving 2-D Poisson’s equation and Young’s approximation. Based on this electric field expression, tunneling current is obtained by using Kane’s model. Several device parameters are varied to examine the behavior of the proposed device. The analytical model is validated with TCAD simulation results for proving the accuracy of our proposed model.
75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
Reactive Flows in Porous Media: Challenges in Theoretical and Numerical Methods
We review theoretical and computational research, primarily from the past 10 years, addressing the flow of reactive fluids in porous media. The focus is on systems where chemical reactions at the solid–fluid interface cause dissolution of the surrounding porous matrix, creating nonlinear feedback mechanisms that can often lead to greatly enhanced permeability. Here, we discuss insights into the evolution of geological forms that can be inferred from these feedback mechanisms, as well as some geotechnical applications such as enhanced oil recovery, hydraulic fracturing, and carbon sequestration. Until recently, most practical applications of reactive transport have been based on Darcy-scale modeling, where averaged equations for the flow and reactant transport are solved. We summarize the successes and limitations of volume averaging, which leads to Darcy-scale equations, as an introduction to pore-scale modeling. Pore-scale modeling is computationally intensive but offers new insights as well as tests of averaging theories and pore-network models. We include recent research devoted to validation of pore-scale simulations, particularly the use of visual observations from microfluidic experiments.
wormhole formation↗
V&V for turbulent mixing in the intermediate asymptotic regime
Turbulent fluid flow interacts nonlinearly with a number of processes, including reactive flow (chemistry), radiation, and the transport of particles embedded in the flow. Subgrid scale modeling of these nonlinear processes is a major challenge to computational science. To this end, turbulent mixing of dissimilar fluids is a driver. Here we study validation issues for a class of turbulent mixing simulations. In previous work, we have obtained agreement between simulation and experiment. The present paper addresses a remaining issue, the role of meniscus related boundary effects for immiscible fluids in the validation process. Validation and even verification has been controversial for turbulent mixing flows, as commonly used numerical models are diffusive and the resulting numerical diffusion modifies the parameters of the problem and its solution. Additionally, numerical diffusion of concentration and temperature is well documented in the scientific literature for Eulerian simulations. Lagrangian simulations, which might appear to avoid this problem, are subject to mesh tangling, ensuing regridding and use of Arbitrary Lagrangian Eulerian codes to substitute for a pure Lagrangian algorithm. In practice, Lagrangian methods are potentially subject to the same numerical diffusion issues when used to study complex interface instabilities.
97 MATHEMATICS AND COMPUTING↗
Toward Higher Voltage Solid-State Batteries by Metastability and Kinetic Stability Design
The energy density of battery systems is limited largely by the electrochemical window of the electrolyte. Here, the combined thermodynamic and kinetic effects of mechanically induced metastability are shown to greatly widen the operational voltage window of solid-state batteries based on ceramic-sulfide electrolytes. Solid electrolyte voltage stability up to 10 V is achieved with minimal degradation, far beyond the capability of organic liquid electrolytes. Furthermore, combined experiment, ab initio computation, and theoretical modeling identify the nature of mechanically constrained Li 10 GeP 2 S 12 decomposition both within the bulk and at interfaces with cathode materials at very high voltages. Previously unclear kinetic processes are identified that, when properly implemented, can potentially allow solid-state full cells with remarkably high operational voltages.
25 ENERGY STORAGE↗
Modeling deformation and failure in AlSi-polyester abradable sealcoating material using microstructure-based finite element simulation
A plasma-sprayed aluminum-silicon (AlSi)/polyester coating is applied in modern gas turbine engines as an abradable sealcoating to maintain tight clearances between the rotating blades and the static casing. While running the engine, the rotating blades “rub” with the abradable coating, which results in extreme strain rate (up to 10 6 ) dynamics and a high-temperature environment. Due to the difficulty of collecting direct measurements, predictive computational models are important for analyzing the deformation and failure of the abradable material, to help meet the design target of avoiding damage to the blade tip and maintaining high fuel efficiency. In this research, a microstructure-based finite element (FE) computational model was developed to capture the complex mechanical behavior of the AlSi/polyester microstructure. The model is based on a virtual representative-volume-element (RVE) of a metal-polymer microstructure, reconstructed from x-ray computed tomography. It models the plastic deformation of, and damage to, each AlSi and polyester constituents, as well as the failure at their interface. The model was calibrated and validated with uniaxial tension and compression experiments, conducted at two temperatures (298 K and 533 K) at an applied strain rate of 10 3 - 10 4 s -1 . The material exhibited strongly asymmetric tension-compression behavior and a sensitivity to temperature, which was well captured by the model. The model was further applied to investigate changes in mechanical behavior due to variations in constituents’ volume fractions, which provides guidance to the microstructural design of AlSi/polyester abradable materials. The model is expected to facilitate the development of improved abradable materials by bypassing the conventional trial-and-error approach and extensive testing requirements.
37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
Condensed Phase Water Molecular Multipole Moments from Deep Neural Network Models Trained on Ab Initio Simulation Data
Ionic solvation phenomena in liquids involve intense interactions in the inner solvation shell. For interactions beyond the first shell, the ion–solvent interaction energies result from the sum of many smaller-magnitude contributions that can still include polarization effects. Deep neural network (DNN) methods have recently found wide application in developing efficient molecular models that maintain near-quantum accuracy. In this work, we extend the DeePMD-kit code to produce accurate molecular multipole moments in the bulk and near interfaces. The new method is validated by comparing the DNN moments with those generated by ab initio simulations. The moments are used to compute the electrostatic potential at the center of a molecular-sized hydrophobic cavity in water. The results show that the fields produced by the DNN models are in quantitative agreement with the AIMD-derived values. These efficient methods will open the door to more accurate solvation models for large solutes such as proteins.
37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
Edge-Enhanced Oxygen Evolution Reactivity at Ultrathin, Au-Supported Fe 2 O 3 Electrocatalysts
Transition metal oxides have gained attention as promising oxygen evolution reaction (OER) electrocatalysts in alkaline electrolytes, but heterogeneities in typical catalyst samples often obscure key structure–property relationships that are essential for developing higher performance materials. Here, we have combined ultrahigh vacuum surface science techniques, electrochemical measurements, and density functional theory (DFT) to quantify structure-dependent OER activity in a series of well-defined electrocatalysts. We describe a direct correlation between the population of Fe edge-site atoms and the OER activity of ultrathin Fe 2 O 3 nanostructures (~0.5 nm apparent height) grown on Au(111) substrates. Hydroxylated Fe atoms residing at edge-sites along the catalyst/support interface were spectroscopically identified as key reaction centers, and these Fe edge-site atoms were estimated to produce OER turnover frequencies approximately 150 times higher than that of Fe atoms on the catalyst surface at an applied potential of 1.8 V vs the reversible hydrogen electrode. Impressively, ultrathin Fe 2 O 3 /Au nanostructures with a high density of catalytically active Fe edge-site atoms outperformed an ultrathin IrOx/Au catalyst at moderate overpotentials. DFT calculations revealed more favorable OER at edge sites along the Fe 2 O 3 /Au interface, with lower predicted overpotentials due to beneficial modification of intermediate binding. Our results demonstrate how a combination of surface science, electrochemistry, and computational modeling can be used to identify key structure–property relationships in a well-defined electrocatalytic system.
37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
A New Method for the Solution of Group Diffusion Equations
Here, the diffusion equations associated with the multigroup, multiregion problem are solved by expansions in eigenfunctions which are solutions of the Helmholtz equation. A determinantal criticality equation is exhibited in which the order of the determinant is independent of the number of groups and which can be solved without recourse to complicated computational procedures. Moreover, the need to fulfill explicitly the requirements that the flux and current associated with each neutron group be continuous across interfaces is eliminated.
73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
A Look At Topics and Topic Clusters for DOE Laboratories, 1996 - 2021 [Slides]
Beginning in 2018, Elsevier through its Scopus database introduced topics to further refine its classification of publications: Previous classification schemes used concepts such as subject areas, e.g., physics and astronomy, chemistry, computer science, etc.; Topics, in contrast, are much more granular. There are over 96,000 and their titles/contents are very specific, e.g., “Multilayers; Interfaces (materials); Individual layer." Elsevier topic clusters or Clarivate citation topics represent good approaches to examining an institution’s scientific productivity areas. These approaches have the granularity that is not present in the previous categorization approaches used by these databases. The Elsevier topic clusters for the DOE Laboratories do not appear to vary that much over the 1996 – 2021 period. In some cases (ANL, LBNL, LANL, ORNL, and PNNL), there were over 1000 topic clusters at these Laboratories, but a consistent set formed the core of the publication activity. Diversity is viewed as a desirable property of a research portfolio. Examining the balance component of the DOE laboratories, the spread is uneven or not diverse. This may be due to the missions of these laboratories. The balance of a single university was unequal too.
96 KNOWLEDGE MANAGEMENT AND PRESERVATION↗
A Comparison between Invariant and Equivariant Classical and Quantum Graph Neural Networks
Machine learning algorithms are heavily relied on to understand the vast amounts of data from high-energy particle collisions at the CERN Large Hadron Collider (LHC). The data from such collision events can naturally be represented with graph structures. Therefore, deep geometric methods, such as graph neural networks (GNNs), have been leveraged for various data analysis tasks in high-energy physics. One typical task is jet tagging, where jets are viewed as point clouds with distinct features and edge connections between their constituent particles. The increasing size and complexity of the LHC particle datasets, as well as the computational models used for their analysis, have greatly motivated the development of alternative fast and efficient computational paradigms such as quantum computation. In addition, to enhance the validity and robustness of deep networks, we can leverage the fundamental symmetries present in the data through the use of invariant inputs and equivariant layers. In this paper, we provide a fair and comprehensive comparison of classical graph neural networks (GNNs) and equivariant graph neural networks (EGNNs) and their quantum counterparts: quantum graph neural networks (QGNNs) and equivariant quantum graph neural networks (EQGNN). The four architectures were benchmarked on a binary classification task to classify the parton-level particle initiating the jet. Based on their area under the curve (AUC) scores, the quantum networks were found to outperform the classical networks. However, seeing the computational advantage of quantum networks in practice may have to wait for the further development of quantum technology and its associated application programming interfaces (APIs).
Forestano, Roy T. (ORCID:0000000203552076)↗
SIMULATIONS OF THE KELVIN–HELMHOLTZ INSTABILITY DRIVEN BY CORONAL MASS EJECTIONS IN THE TURBULENT CORONA
Recent high-resolution Atmospheric Imaging Assembly/Solar Dynamics Observatory images show evidence of the development of the Kelvin–Helmholtz (KH) instability, as coronal mass ejections (CMEs) expand in the ambient corona. A large-scale magnetic field mostly tangential to the interface is inferred, both on the CME and on the background sides. However, the magnetic field component along the shear flow is not strong enough to quench the instability. There is also observational evidence that the ambient corona is in a turbulent regime, and therefore the criteria for the development of the instability are a priori expected to differ from the laminar case. To study the evolution of the KH instability with a turbulent background, we perform three-dimensional simulations of the incompressible magnetohydrodynamic equations. The instability is driven by a velocity profile tangential to the CME–corona interface, which we simulate through a hyperbolic tangent profile. The turbulent background is generated by the application of a stationary stirring force. We compute the instability growth rate for different values of the turbulence intensity, and find that the role of turbulence is to attenuate the growth. The fact that KH instability is observed sets an upper limit on the correlation length of the coronal background turbulence.
79 ASTRONOMY AND ASTROPHYSICS↗
Effective Lanthanide Diffusivity through U-Zr Metallic Fuel
Fuel-cladding chemical interaction (FCCI) is one of the main concerns for the performance of U-Zr metallic fuels. Although FCCI results in complex phase transformations and morphological changes in both the fuel and cladding sides of the interface, the formation of a brittle layer in the cladding side of the interface (sometimes referred to as wastage) has one of the most significant impacts on the cladding mechanical integrity. This brittle layer is associated with the formation of intermetallic compounds between the cladding constituents Fe, Cr and the lanthanide fission product species. The formation of this cladding wastage layer has been the focus of recent efforts to develop a mechanistic modeling framework, including production of lanthanides in the fuel, transport through the fuel to the fuel-cladding interface, and phase transformation to form intermetallic phases. To calculate the rate of transport of lanthanides through the fuel, a multi-scale computational approach has been used. Atomistic calculations have been performed to determine the diffusivities of Nd, the most prevalent lanthanide species, through the solid fuel matrix and along pore surfaces. These diffusivities have been used as input parameters for a mesoscale model to determine an effective diffusion coefficient that accounts for the formation of porosity, its interconnection, and infiltration with bond sodium from the fuel-cladding gap. The effective diffusivity has been used in engineering-scale simulations using the BISON fuel performance code, and BISON simulations have been compared to representative validation cases from the EBR-II reactor.
11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
Development of CFD Flow Analysis for Nuclear Facility Ventilation Systems
Understanding and modeling of particulate transport has importance related to safety in ventilated environments that contain hot cells, gloveboxes, and fume hoods. In particular, good modeling of the airflow in these spaces is required to understand areas of stagnation where particles drop out of the free stream and accumulate. This accumulation of particulate can cause either contamination and/or higher than acceptable local dose levels. It is known that multiple sites across the DOE complex take credit for hot cells, gloveboxes, and/or hoods in their safety basis for providing a defense-in-depth benefit for both onsite and offsite releases. By providing confinement of radioactive materials, such features serve to reduce direct doses to facility workers and mitigate the consequences to the environment due to an uncontrolled release. Each of these features has access points that interface with the personnel space. Understanding how air flow behaves at these access points is of great interest to those performing hazard analysis. Computational Fluid Dynamics (CFD) can be used to analyze and model the flows in hot cells and glove boxes as a way to confirm operation. While CFD capability continues to advance, there are still important modeling assumptions that are left to the analyst's discretion. These are most notably the choice of the turbulence models, mesh structure, and wall boundary condition assumptions used in the model. In this work, we apply CFD in modeling airflow through an occupiable work area of the Alpha Gamma Hot Cell Facility (AGHCF) at Argonne National Laboratory (ANL). This modeling is then compared to field test data to both inform and verify the modeling assumptions. Based on the results of field tests, modeling assumptions and boundary conditions are refined and the process is repeated until the results are found to be reliable with a high level of confidence.
22 GENERAL STUDIES OF NUCLEAR REACTORS↗
A New Semistructured Algebraic Multigrid Method
Multigrid methods are well suited to large massively parallel computer architectures because they are mathematically optimal and display good parallelization properties. Since current architecture trends are favoring regular compute patterns to achieve high performance, the ability to express structure has become much more important. The hypre software library provides high-performance multigrid preconditioners and solvers through conceptual interfaces, including a semistructured interface that describes matrices primarily in terms of stencils and logically structured grids. This paper presents a new semistructured algebraic multigrid (SSAMG) method built on this interface. The numerical convergence and performance of a CPU implementation of this method are evaluated for a set of semistructured problems. In conclusion, SSAMG achieves significantly better setup times than hypre’s unstructured AMG solvers and comparable convergence. In addition, the new method is capable of solving more complex problems than hypre’s structured solvers.
97 MATHEMATICS AND COMPUTING↗
Self-Organization of Plasma-Material Interfaces
The primary goals of the project are a) improve the understanding of transport processes, chemical reactions and plasma-driven self-organization such as stratification and filamentation, formation of anode spots, liquid droplets ejection from cathodes, and plasma electrolysis, b) utilize and share among the project participants computational tools developed by the participants to understand plasma-based surface functionalization and plasma-enabled pattern nucleation in a wide range of scales from nano- to millimeters, and c) use experimental methods and facilities available at the University of Alabama in Huntsville (UAH) and Sandia National Laboratories (SNL) to understand and control plasma processes, reaction pathways and the electric nature of self-organization of the plasma-exposed interface structures.
70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
Sculpt: Automatic Parallel Hexahedral Mesh Generation
Sculpt is a companion application to Cubit designed to run in parallel for generating all-hex meshes of complex geometry. It uses a unique overlay-grid procedure that extracts surfaces from a volume-fraction representation of the geometry. This allows for fast, automatic, fault-tolerant meshing in a high-performance computing (HPC) environment. Although Sculpt can be driven from Cubit as a GUI front-end, Sculpt was developed as a separate application so that it can be run independently from Cubit on HPC computing platforms. It was also designed as a separable software library so it can be easily integrated as an in-situ meshing solution within other codes. This work provides a brief technical discussion of the algorithms used in Sculpt as well as a complete user's manual. It includes details of the Cubit interface to Sculpt and the complete manual for the stand-alone application, including examples.
97 MATHEMATICS AND COMPUTING↗