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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 343 records · Page 19
All sourcesNASA NTRSDOE OSTI
DOE OSTI2020

CEA/DAM - CEA/DEN - LANL - IAEA - IPHC Collaboration Meeting on Nuclear Data, Nuclear Reaction Theories, and Machine Learning (Summary Report)

Dupuis hosted our biennial CEA/NNSA collaboration meeting, and Kawano and Lovell of LANL and Tamagno of CEA/DEN (Cadarache) visited CEA/DAM to discuss current issues and further developments in nuclear reaction modeling, nuclear data evaluation, and relevant programs of modern computer science, especially the machine learning technology. The discussions included topics of our common interest such as neutron inelastic scattering, capture, and fission, with particular emphasis on the actinide nuclear data evaluations. We report briefly the summary of our discussions. We also had a half-day video meeting with Capote of IAEA and Kerveno of IPHC to discuss nuclear reactions on actinides.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2022

A mortar thermomechanical contact computational framework for nuclear fuel performance simulation

Nuclear fuel performance simulations involve the modeling of complex physical phenomena, ranging from fission gas release to fuel swelling and other temperature-induced effects. For light-water reactors (LWRs), swelling of the fuel and the pressure it imposes on the clad when they come into contact causes permanent clad deformation. Accurately characterizing the fuel-cladding interaction, which involves multiple physics, is essential to accurately simulate the fuel/cladding system. Thermomechanical modeling of this problem using a variationally consistent enforcement (e.g., a mortar approach) has been shown to improve the quality of results and facilitate convergence. Here, we present a general multiphysics computational framework for solving nuclear fuel problems using a mortar approach in BISON, a nuclear fuel performance code. In this study analyses show that using the mortar approach, which enables variationally consistent constraint enforcement, improves the quality of results as compared to the more commonly used node-on-face enforcement for representative LWR nuclear fuel simulations.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2022

Sensitivity/Uncertainty Comparison Study Involving IRSN, LANL, and ORNL Tools to Support Validation

Under a DOE Nuclear Criticality Safety Program (NCSP) task involving Analytical Methods, three Laboratories collaborated in a comparison of results obtained from Sensitivity/Uncertainty (S/U) packages relevant to validation of transport codes. The task involves Institut de Radioprotection et de Sûreté Nucléaire (IRSN), Los Alamos National Laboratory (LANL), and Oak Ridge National Laboratory (ORNL) comparing results of MORET 5/MACSENS V3.0, MCNP6.2/Whisper-1.1, and SCALE 6.2.3/TSUNAMI/USLSTATS respectively. All Monte Carlo transport code results utilize nuclear data from ENDF/B-VII.1 evaluation. This study examines five cases from the International Handbook of Evaluated Criticality Safety Benchmark Experiments (ICSBEP Handbook) selected as application models: IEU-MET- FAST-002-001, LEU-COMP-THERM-001-001, LEU-SOL-THERM-004-001, MIX-COMP- THERM-001-001, and U233-SOL-THERM-001-001. This is a continuation of a previous study to examine Pu and HEU cases: HEU-MET-FAST-013-001, HEU-SOL-THERM-001-008, PU-MET- FAST-022-001, and PU-SOL-THERM-001-001. Ultimately, comparison is made between Upper Subcritical Limits (USLs) obtained using each code package for each application case. Since differences exist in whether packages take into account margin of subcriticality (MOS), the USL is computed using only bias and bias uncertainty, also known as the calculational margin (CM) in ANSI/ANS-8.24. Results comparison appears to show that benchmark selection has a greater influence on the USL than the method used for calculation of bias and bias uncertainty.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2023

Generalized Bayesian Framework for Evaluation of Integral Benchmark Experiments

A recently published generalized Bayesian optimization framework has provided a way to retract any or all of the three common assumptions underlying the conventional Generalized Linear Least Squares (GLLS) optimization method based on the concepts introduced in Ref. [2]. These assumptions are: 1. Perfection: The model used for data evaluation and the prior probability distribution function (PDF) of generalized data are perfect. 2. Normality: The prior and posterior PDF are normal. 3. Linearity: The model is linear. In this work we outline how the framework in [1] could be directly adopted for improved evaluation of nuclear criticality integral benchmark experiments (IBEs) by: 1. Removing the first assumption alone by utilizing the concept of imperfections introduced in [1] to enable evaluation in the presence of discrepancies between the data and model or of missing covariance information by a GLLS method that will be seen as a generalization of the conventional GLLS method employed by the TSURFER code, and by 2. Removing the remaining two assumptions by implementing a Markov Chain Monte Carlo method for computation of the posterior PDF in the SAMPLER code, where TSURFER and SAMPLER are the uncertainty quantification (UQ) codes for IBEs in the SCALE code system based on the GLLS and the stochastic method, respectively. The graphic in Figure 1 categorizes the methods discussed in terms of the assumptions that they employ to determine posterior PDFs.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2020

Koopman–von Neumann approach to quantum simulation of nonlinear classical dynamics

Quantum computers can be used to simulate nonlinear non-Hamiltonian classical dynamics on phase space by using the generalized Koopman–von Neumann formulation of classical mechanics. The Koopman–von Neumann formulation implies that the conservation of the probability distribution function on phase space, as expressed by the Liouville equation, can be recast as an equivalent Schrödinger equation on Hilbert space with a Hermitian Hamiltonian operator and a unitary propagator. This Schrödinger equation is linear in the momenta because it derives from a constrained Hamiltonian system with twice the classical phase-space dimension. A quantum computer with finite resources can be used to simulate a finite-dimensional approximation of this unitary evolution operator. Quantum simulation of classical dynamics is exponentially more efficient than a deterministic Eulerian discretization of the Liouville equation if the Koopman–von Neumann Hamiltonian is sparse. Utilizing quantum walk techniques for state preparation and amplitude estimation for the calculation of observables leads to a quadratic improvement over classical probabilistic Monte Carlo algorithms.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2020

Validation of Thermal Scattering Laws for Light Water at Elevated Temperatures with Diffusion Experiments

Light water is the most important neutron moderator in many reactor applications. Thermal neutron scattering kernels for H bound in H 2 O are represented by ENDF-format thermal scattering laws (TSLs) evaluated at discrete temperatures T . Nuclear data evaluations are conventionally validated utilizing a combination of critical benchmarks and experimental cross section data. Existing public critical benchmarks may be inadequate for testing water TSLs over the full range of T of interest in reactor applications, and experimental thermal scattering cross section data for water is sparse at elevated T . In this work, MC21 is used to simulate the decay of the equilibrium thermal neutron flux in light-water spheres of several radii. The fundamental-mode time eigenvalue $\mathcal{a}$ is calculated at 22 °C and 227 °C (at saturation pressure) for each sphere using three different H-H 2 O TSLs. Fitting $\mathcal{a}$ to a polynomial function of geometric buckling allows calculation of the thermal neutron diffusion length L . Extrapolation lengths are treated as a function of the transport mean free path and geometry. Experimental L data from 25 publications at 49 temperatures (from 10 °C to 295 °C), computed by several different time-dependent and space-dependent decay methods, is used to develop an empirical fit of L vs. T . The MC21-calculated L for the TSLs tested are within ±1% of the predicted values at 22 °C and 227 °C. This validation approach, which may be repeated at arbitrary T , constitutes an integral benchmark specific to and characterizing the detailed physics of the thermal scattering kernel applied.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2024

Scalable semidefinite programming approach to variational embedding for quantum many-body problems

In quantum embedding theories, a quantum many-body system is divided into localized clusters of sites which are treated with an accurate ‘high-level’ theory and glued together self-consistently by a less accurate ‘low-level’ theory at the global scale. The recently introduced variational embedding approach for quantum many-body problems combines the insights of semidefinite relaxation and quantum embedding theory to provide a lower bound on the ground-state energy that improves as the cluster size is increased. The variational embedding method is formulated as a semidefinite program (SDP), which can suffer from poor computational scaling when treated with black-box solvers. Here, we exploit the interpretation of this SDP as an embedding method to develop an algorithm which alternates parallelizable local updates of the high-level quantities with updates that enforce the low-level global constraints. Moreover, we show how translation invariance in lattice systems can be exploited to reduce the complexity of projecting a key matrix to the positive semidefinite cone.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2020

System and method for controlling an energy beam of an additive manufacturing system

An additive manufacturing system includes an energy beam generator that generates an energy beam to melt and fuse raw materials for a part and a computing device that controls operation of the energy beam generator. The computing device includes a memory element that stores or access a three-dimensional model of the part, and a processing element that receives at least a portion of the three-dimensional model and controls a parameter of the energy beam generator according to a gradient function so as to apply a variable amount of heat to the raw material that forms an overhang on the part.

42 ENGINEERING↗
DOE OSTI2020

Quantum Physics without the Physics

This report explains the basic theory and common terminology of quantum physics without assuming any knowledge of physics. It was written by a group of applied mathematicians while they were reading up on the subject. The intended audience consists of applied mathematicians, computer scientists, or anyone else who wants to improve their understanding of quantum physics. We assume that the reader is familiar with fundamental concepts of linear algebra, differential equations, and to some extent the theory of Hilbert spaces. Most of the material can be found in the book by Nielsen and Chuang and in the lecture notes on open quantum systems by Lidar. Another excellent online source of information is Wikipedia, even though most of its articles on quantum physics assume a solid understanding of physics.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2022

Sierra/SolidMechanics 5.4 User's Guide

Sierra/SolidMechanics (Sierra/SM) is a Lagrangian, three-dimensional code for finite element analysis of solids and structures. It provides capabilities for explicit dynamic, implicit quasistatic and dynamic analyses. The explicit dynamics capabilities allow for the efficient and robust solution of models with extensive contact subjected to large, suddenly applied loads. For implicit problems, Sierra/SM uses a multi-level iterative solver, which enables it to effectively solve problems with large deformations, nonlinear material behavior, and contact. Sierra/SM has a versatile library of continuum and structural elements, and a large library of material models. The code is written for parallel computing environments enabling scalable solutions of extremely large problems for both implicit and explicit analyses. It is built on the SIERRA Framework, which facilitates coupling with other SIERRA mechanics codes. This document describes the functionality and input syntax for Sierra/SM.

74 ATOMIC AND MOLECULAR PHYSICS↗
DOE OSTI2021

HPC for Fission Modeling in Support of Nuclear Data [Slides]

The presentation discusses the background of the High-Performance Computing (HPC) division at the Los Alamos National Laboratory (LANL), with emphasis on its computational needs and computational techniques. It also discusses the highlights of the HPC and the results of calculations, including energy sharing parameterized from DFT calculations, parameterization used in CGMF calculations, angular momentum from microscopic calculations, and correlations between FF angular momenta. The presentation concludes with an outlook including what remains to be done in the HPC division and how it will benefit nuclear data, specifically how it will provide a better understanding of the fission process.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2025

Memristive linear algebra

The advent of memristive devices offers a promising avenue for efficient and scalable analog computing, particularly for linear algebra operations essential in various scientific and engineering applications. This paper investigates the potential of memristive crossbars in implementing matrix inversion algorithms. We explore both static and dynamic approaches, emphasizing the advantages of analog and in-memory computing for matrix operations beyond multiplication. In particular, we demonstrate that the electrical properties of memristive crossbars uniquely suit them for the evolution of a family of matrix exponentials, which can be exploited for the efficient computation of matrix inverses and online solutions for linear problems. Our results demonstrate that memristive arrays can reduce computational complexity. We also study power consumption and show a tradeoff between precision and energy. Furthermore, we address the challenges of device variability, precision, and scalability, providing insights into the practical implementation of these algorithms.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2023

Computing dissipation for molecular-level turbulence simulations

A major difficulty in the analysis of molecular-level simulations is that macroscopic flow quantities are inherently noisy due to molecular fluctuations. An important example for turbulent flows is the kinetic energy dissipation rate. Traditionally, this quantity is calculated from gradients of the macroscopic velocity field, which exacerbates the noise problem. The inability to accurately compute the dissipation rate makes meaningful comparison of molecular-level and continuum simulation results a serious challenge. Herein, we extend previously developed coarse-graining theories to derive an exact molecular-level expression for the dissipation rate, which would circumvent the need to compute gradients of noisy fields. Although the exact expression cannot feasibly be implemented in Sandia’s direct simulation Monte Carlo (DSMC) code SPARTA, we utilize an approximate “hybrid” approach and compare it to the conventional gradient-based approach for planar Couette flow and the two-dimensional Taylor-Green vortex, demonstrating that the hybrid approach is significantly more accurate. Finally, we explore the possibility of adopting a Lagrangian approach to calculate the energy dissipation rate.

74 ATOMIC AND MOLECULAR PHYSICS↗
DOE OSTI2022

Modeling multiple scattering transient of an ultrashort laser pulse by spherical particles

The multiple scattering of an ultrashort laser pulse by a turbid dispersive medium (namely a cloud of bubbles in water) is investigated by means of Monte Carlo simulations. The theory of Gouesbet and Gréhan (2000) is used to derive an energetic model of the scattering transient. It is shown that the spreading and extinction of the pulse can be decoupled from the transient of scattering, which allows to describe each phenomenon individually. The transient of scattering is modeled with the Lorenz-Mie Theory and thus is also valid for a relative refractive index lower than one, contrary to the Debye series expansion which does not converge close to the critical angle. This is made possible after the introduction of a new physical object, the Scattering Impulse Response Function (SIRF) which allows to detect the different modes of scattering transient, in time and direction. Here the present approach is more generic, as it enables to simulate clouds of air bubbles in water, which was not possible previously. Two different approaches are proposed within the Monte Carlo framework. The first is a pure Monte Carlo approach where the delay due to the scattering is randomly drawn at each event, while the second is based on the transport of the whole scattering signal. They are both embedded in the Monte Carlo code Scatter3D. Both models produce equivalent trends and are validated against published numerical results. They are then applied to the multiple scattering of ultra short pulse by a cloud of bubble in water in the forward direction. The pulse spread due to the propagation in water is computed for a wide range of traveled distances and pulse durations, and the optimal pulse duration is given to minimize the pulse spread at a given distance. The main result is that the scattered photons exit the turbid medium earlier than the ballistic photons and produce a double peak related to the refraction in the bubble. This demonstrates the possibility to develop new diagnostics to characterize dynamic bubbly flows.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2024

MCNPs Easy Sources for (α,n) (MESA):Verification with Sources4c

MESA is intended to be a direct re-implementation of the algorithms documented in the Sources manual in C++. However, some fundamental changes to the computational structure and logic were made to avoid the use of goto, require consistency in input definition, and reduce computational approximations in later steps of three-layer problems. In addition, MESA uses α-decay information from ISC libraries (based on ENDF). In most cases, differences between Sources4c and MESA are dominated by differences in decay energy spectra and intensities. To verify this we have reproduced 6 problems that are documented examples or samples in Sources4c. These problems cover the three types of problems MESA currently supports: homogeneous, interface, and three-layer.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2021

Variational quantum algorithms

Applications such as simulating complicated quantum systems or solving large-scale linear algebra problems are very challenging for classical computers, owing to the extremely high computational cost. Quantum computers promise a solution, although fault-tolerant quantum computers will probably not be available in the near future. Current quantum devices have serious constraints, including limited numbers of qubits and noise processes that limit circuit depth. Variational quantum algorithms (VQAs), which use a classical optimizer to train a parameterized quantum circuit, have emerged as a leading strategy to address these constraints. VQAs have now been proposed for essentially all applications that researchers have envisaged for quantum computers, and they appear to be the best hope for obtaining quantum advantage. Nevertheless, challenges remain, including the trainability, accuracy and efficiency of VQAs. Here we overview the field of VQAs, discuss strategies to overcome their challenges and finally, we highlight the exciting prospects for using them to obtain quantum advantage.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2022

Adaptive Space-Time Methods for Large Scale Optimal Design

When modeling complex physical systems with advanced dynamics, such as shocks and singularities, many classic methods for solving partial differential equations can return inaccurate or unusable results. One way to resolve these complex dynamics is through r-adaptive refinement methods, in which a fixed number of mesh points are shifted to areas of high interest. The mesh refinement map can be found through the solution of the Monge-Ampére equation, a highly nonlinear partial differential equation. Due to its nonlinearity, the numerical solution of the Monge-Ampére equation is nontrivial and has previously required computationally expensive methods. In this report, we detail our novel optimization-based, multigrid-enabled solver for a low-order finite element approximation of the Monge-Ampére equation. This fast and scalable solver makes r-adaptive meshing more readily available for problems related to large-scale optimal design. Beyond mesh adaptivity, our report discusses additional applications where our fast solver for the Monge-Ampére equation could be easily applied.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗