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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 505 records · Page 28

Axially-deformed solution of the Skyrme-Hartree-Fock-Bogoliubov equations using the transformed harmonic oscillator basis (IV) HFBTHO (v4.0): A new version of the program

We describe the new version 4.0 of the code HFBTHO that solves the nuclear Hartree-Fock-Bogoliubov problem by using the deformed harmonic oscillator basis in cylindrical coordinates. In the new version, we have implemented the restoration of rotational, particle number, and reflection symmetry for even-even nuclei. The restoration of rotational symmetry does not require using bases closed under rotation. Furthermore, we added the SeaLL1 functional and improved the calculation of the Coulomb potential. Finally, we refactored the code to facilitate maintenance and future developments.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗

GenASiS Basics: Object-oriented utilitarian functionality for large-scale physics simulations (Version 4)

GenASiS Basics provides modern Fortran classes furnishing extensible object-oriented utilitarian functionality for large-scale physics simulations on distributed memory supercomputers. This functionality includes physical units and constants; display to the screen or standard output device; message passing; I/O to disk; and runtime parameter management and usage statistics. Herein, this revision—Version 4 of Basics—includes a name change and additions to functionality, including the facilitation of direct communication between GPUs.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

Development and performance of a HemeLB GPU code for human-scale blood flow simulation

In recent years, it has become increasingly common for high performance computers (HPC) to possess some level of heterogeneous architecture - typically in the form of GPU accelerators. In some machines these are isolated within a dedicated partition, whilst in others they are integral to all compute nodes - often with multiple GPUs per node - and provide the majority of a machine's compute performance. In light of this trend, it is becoming essential that codes deployed on HPC are updated to execute on accelerator hardware. Here, in this paper, we introduce a GPU implementation of the 3D blood flow simulation code HemeLB that has been developed using CUDA C++. We demonstrate how taking advantage of NVIDIA GPU hardware can achieve significant performance improvements compared to the equivalent CPU only code on which it has been built whilst retaining the excellent strong scaling characteristics that have been repeatedly demonstrated by the CPU version. With HPC positioned on the brink of the exascale era, we use HemeLB as a motivation to provide a discussion on some of the challenges that many users will face when deploying their own applications on upcoming exascale machines.

59 BASIC BIOLOGICAL SCIENCES↗

Accelerating multicanonical sampling with irreversibility

Flat-histogram Monte Carlo simulations are well-established, robust methods to perform random walks in a physical observable or parameter space, making them suitable for finding ground states or studying phase transitions in complex systems in statistical physics. However, their efficiency can be limited by the time to attain the desired flat distribution, which is generally unknown prior to the simulations. In particular, they might suffer from slowing down towards the end of a simulation due to the diffusive nature of random walks. In this work we apply irreversibility to the multicanonical Monte Carlo method via the lifting approach to alleviate this behavior. We achieve a 2–4 times speedup in ground-state search for a two-dimensional (2D) Ising model, and up to an order of magnitude of speedup for finding the ground-state energy in an Edwards–Anderson spin glass, compared to traditional multicanonical sampling. In conclusion, the round-trip times between ground states show a narrower distribution and are significantly shorter compared to the reversible counterpart, suggesting that a lower convergence time with a smaller time variance is feasible.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

Introduction to MDSplus using Docker

With increased use of MDSplus comes an influx of new users. With them comes a need for more and better ways to learn the suite of tools that is MDSplus. Therefore, the MDSplus team continually evaluates new technologies to improve our software and user experience. To this end, we investigated Docker to determine if and how it could help new users understand MDSplus, make MDSplus easier to install, and allow us to easily test old/new versions. To achieve this, a set of Docker images and instructions have been developed. This paper will provide an overview of MDSplus, and detail the methods to create and use the Docker images. Additionally, we will explore the limitations of such an approach, and the recommended applications. The project where these Docker Images were built, along with the Demo is here: https://github.com/WhoBrokeTheBuild/DockerizedMDSplus https://hub.docker.com/r/whobrokethebuild/mdsplus The now official Docker Images are available here: https://github.com/MDSplus/Docker https://hub.docker.com/r/mdsplus/mdsplus

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗

Catalytic consequences of hydrogen addition events and solvent-adsorbate interactions during guaiacol-H 2 reactions at the H 2 O-Ru(0 0 0 1) interface

Catalytic reactions of biomass-derived phenolics and H 2 occur on transition metal surfaces via competitive C–O cleavage and ring saturation pathways, with both requiring multiple hydrogen addition events before forming their respective rate limiting transition states. These events are markedly affected by solvent chemical identity, with polar protic solvents ionizing hydrogen adatoms (H*) to interfacial protons (H + ) and opening up new catalytic routes. Here, we establish the reaction coordinate space for guaiacol-H 2 reactions on Ru(0 0 0 1) using density functional theory and describe the atomic-scale effect of a polar protic solvent, H 2 O. Coupled H + and H* attack leads to quasi-equilibrated enol and keto intermediates as the precursors for C–O cleavage and ring saturation, respectively. For C–O cleavage, H 2 O solvent enables a lower energy pathway via concomitant transfer of the hydroxyl H + to the methoxy oxygen during C–OCH 3 cleavage, forming a charge separated [Ru(s)–(C 6 H 5 O – )…(H + )…OCH 3 ] transition state and reducing the barrier by up to 0.8 eV as compared to unassisted C–OCH 3 cleavage. For ring saturation, H* attack onto an unsaturated meta carbon is rate limiting with no direct solvent participation, suggesting that protic polar solvents selectively promote the C–O cleavage pathway. Taken together, we show that activating guaiacol for either C–O bond cleavage or ring saturation product formation depends on the reactive hydrogen identity (H* or H + ), enol/keto isomerization equilibrium, and accessibility of the proton assisted Car–OCH 3 cleavage transition state. Here, all such factors are tunable via changes to the solvent or metal identity.

09 BIOMASS FUELS↗

Efficient smoothed particle radiation hydrodynamics I: Thermal radiative transfer

This work presents efficient solution techniques for radiative transfer in the smoothed particle hydrodynamics discretization. Two choices that impact efficiency are how the material and radiation energy are coupled, which determines the number of iterations needed to converge the emission source, and how the radiation diffusion equation is solved, which must be done in each iteration. The coupled material and radiation energy equations are solved using an inexact Newton iteration scheme based on nonlinear elimination, which reduces the number of Newton iterations needed to converge within each time step. During each Newton iteration, the radiation diffusion equation is solved using Krylov iterative methods with a multigrid preconditioner, which abstracts and optimizes much of the communication when running in parallel. The code is verified for an infinite medium problem, a one-dimensional Marshak wave, and a two and three-dimensional manufactured problem, and exhibits first-order convergence in time and second-order convergence in space. For these problems, the number of iterations needed to converge the inexact Newton scheme and the diffusion equation is independent of the number of spatial points and the number of processors.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗

Parallel physics-informed neural networks via domain decomposition

Here we develop a distributed framework for the physics-informed neural networks (PINNs) based on two recent extensions, namely conservative PINNs (cPINNs) and extended PINNs (XPINNs), which employ domain decomposition in space and in time-space, respectively. This domain decomposition endows cPINNs and XPINNs with several advantages over the vanilla PINNs, such as parallelization capacity, large representation capacity, efficient hyperparameter tuning, and is particularly effective for multi-scale and multi-physics problems. Here, we present a parallel algorithm for cPINNs and XPINNs constructed with a hybrid programming model described by MPI + X, where X ∈ {CPUs, GPUs}. The main advantage of cPINN and XPINN over the more classical data and model parallel approaches is the flexibility of optimizing all hyperparameters of each neural network separately in each subdomain. We compare the performance of distributed cPINNs and XPINNs for various forward problems, using both weak and strong scalings. Our results indicate that for space domain decomposition, cPINNs are more efficient in terms of communication cost but XPINNs provide greater flexibility as they can also handle time-domain decomposition for any differential equations, and can deal with any arbitrarily shaped complex subdomains. To this end, we also present an application of the parallel XPINN method for solving an inverse diffusion problem with variable conductivity on the United States map, using ten regions as subdomains.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

Entropy stable modal discontinuous Galerkin schemes and wall boundary conditions for the compressible Navier-Stokes equations

Entropy stable schemes ensure that physically meaningful numerical solutions also satisfy a semi-discrete entropy inequality under appropriate boundary conditions. Here in this work, we describe a discretization of viscous terms in the compressible Navier-Stokes equations which enables a simple and explicit imposition of entropy stable no-slip and reflective (symmetry) wall boundary conditions for discontinuous Galerkin (DG) discretizations. Specifically, we derive methods for imposing adiabatic no-slip and reflective (symmetry) boundary conditions for modal entropy stable DG formulations which preserve a semi-discrete entropy inequality. Numerical results confirm the robustness and accuracy of the proposed approaches.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

A unified formulation of splitting-based implicit time integration schemes

Splitting-based time integration approaches such as fractional step, alternating direction implicit, operator splitting, and locally one dimensional methods partition the system of interest into components, and solve individual components implicitly in a cost-effective way. Here this work proposes a unified formulation of splitting time integration schemes in the framework of general-structure additive Runge–Kutta (GARK) methods. Specifically, we develop implicit-implicit (IMIM) GARK schemes, provide the order conditions for this class, and explain their application to partitioned systems of ordinary differential equations. We show that classical splitting methods belong to the IMIM GARK family, and therefore can be studied in this unified framework. New IMIM-GARK splitting methods are developed and tested using parabolic systems.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

A level-set immersed boundary method for reactive transport in complex topologies with moving interfaces

A simulation framework based on the level-set and the immersed boundary methods (LS-IBM) has been developed for reactive transport problems in porous media involving a moving solid-fluid interface. The interface movement due to surface reactions is tracked by the level-set method, while the immersed boundary method captures the momentum and mass transport at the interface. The proposed method is capable of accurately modeling transport near evolving boundaries in Cartesian grids. The framework formulation guarantees second order accuracy in space. Since the interface velocity is only defined at the moving boundary, an interface velocity propagation method is also proposed. The method can be applied to other moving interface problems of the “Stefan” type. Here, we validate the proposed LS-IBM both for flow and transport close to an immersed object with reactive boundaries as well as for crystal growth. Lastly, the proposed method provides a powerful tool to model more realistic problems involving moving reactive interfaces in complex domains.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

Ensuring Σ s Y s = 1 in transport of species mass fractions

When transporting species mass fractions in reacting flow simulations, there are physical constraints that must be met. Unfortunately, nonlinear transport schemes such as weighted essentially non-oscillatory (WENO) schemes do not ensure that the sum of mass fractions equals 1. In detonation simulations, errors in the sum of mass fractions are observed to worsen over time when the standard WENO scheme is used. To prevent this, typically one species is forced to absorb all or most of the error in the sum of mass fractions. Here, this work presents an alternative method for correcting the WENO-interpolated mass fractions such that inert species do not change. The method is demonstrated for both argon and nitrogen-diluted hydrogen detonations in one dimension. Using the modified WENO interpolations, the error in the sum is reduced significantly. In addition, the new approach is better able to capture the physical instability expected for nitrogen-diluted detonations.

74 ATOMIC AND MOLECULAR PHYSICS↗

DG-IMEX method for a two-moment model for radiation transport in the $\mathscr{O}$($v$/$c$) limit

Here, we consider neutral particle systems described by moments of a phase-space density and propose a realizability-preserving numerical method to evolve a spectral two-moment model for particles interacting with a background fluid moving with nonrelativistic velocities. The system of nonlinear moment equations, with special relativistic corrections to $\mathscr{O}$($v$/$c$), expresses a balance between phase-space advection and collisions and includes velocity-dependent terms that account for spatial advection, Doppler shift, and angular aberration. The model is conservative for the correct $\mathscr{O}$($v$/$c$) Eulerian-frame number density and is consistent, to $\mathscr{O}$($v$/$c$), with Eulerian-frame energy and momentum conservation. This model is closely related to the one promoted by Lowrie et al. and similar to models currently used to study transport phenomena in large-scale simulations of astrophysical environments. The proposed numerical method is designed to preserve moment realizability, which guarantees that the moments correspond to a nonnegative phase-space density. The realizability-preserving scheme consists of the following key components: (i) a strong stability-preserving implicit-explicit (IMEX) time-integration method; (ii) a discontinuous Galerkin (DG) phase-space discretization with carefully constructed numerical uxes; (iii) a realizability-preserving implicit collision update; and(iv) a realizability-enforcing limiter. In time integration, nonlinearity of the moment model necessitates solution of nonlinear equations, which we formulate as fixed-point problems and solve with tailored iterative solvers that preserve moment realizability with guaranteed global convergence. We also analyze the simultaneous Eulerian-frame number and energy conservation properties of the semi-discrete DG scheme and propose a "spectral redistribution" scheme that promotes Eulerian-frame energy conservation. Through numerical experiments, we demonstrate the accuracy and robustness of this DG-IMEX method and investigate its Eulerian-frame energy conservation properties.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗

Validation of electron backscattering in the MCNP6.3 code

A new electron backscattering validation suite has been developed for the MCNP® code. The calculations in this suite cover both condensed history and single-event transport methods, seven different elemental materials ranging from beryllium to uranium, and incident electron energies from 200 eV to 14.1 MeV. In general, the accuracy of the MCNP code for electron backscattering calculations is energy-dependent. For incident electron energies below 2 keV, the condensed history method is not applied while the single-event method shows poor agreement with experimental measurements due to poor accuracy of the underlying atomic data. For incident energies between 2 keV and 256 keV, the single-event method typically shows better agreement with experiments, while for incident energies above 256 keV the condensed history method gives better accuracy. Additionally, agreement with experimental data is generally worse for low- Z materials such as beryllium and carbon, which may reflect deficiencies in the data or physics underlying electron transport through light elements in the MCNP code. The new electron backscattering validation suite, along with the previously introduced electron stopping power and Lockwood energy deposition validation suites, provide MCNP users with a quantified understanding of the uncertainties in electron transport calculations. Future improvements to electron transport in the MCNP code are necessary for low energies (≤ 2 keV) and for low- Z materials.

36 MATERIALS SCIENCE↗

Three dimensional cluster analysis for atom probe tomography using Ripley’s K-function and machine learning

The size and structure of spatial molecular and atomic clustering can significantly impact material properties and is therefore important to accurately quantify. Ripley’s K-function (K(r)), a measure of spatial correlation, can be used to perform such quantification when the material system of interest can be represented as a marked point pattern. This work demonstrates how machine learning models based on K (r)-derived metrics can accurately estimate cluster size and intra-cluster density in simulated three dimensional (3D) point patterns containing spherical clusters of varying size; over 90% of model estimates for cluster size and intra-cluster density fall within 11% and 18% error of the true values, respectively. These K (r)-based size and density estimates are then applied to an experimental APT reconstruction to characterize MgZn clusters in a 7000 series aluminum alloy. Here we find that the estimates are more accurate, consistent, and robust to user interaction than estimates from the popular maximum separation algorithm. Using K (r) and machine learning to measure clustering is an accurate and repeatable way to quantify this important material attribute.

36 MATERIALS SCIENCE↗