Engineering Papers⌕ Search

SEARCH · Engineering Papers

Results for “eigenvalue problem”

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.

Quote a phrase for an exact phrase match. Source license links do not imply unrestricted reuse.

At least 361 records · Page 20
All sourcesNASA NTRSDOE OSTI
DOE OSTI2014

Plasma Energetic Particles Simulation Center (PEPSC)

The main effort of the Texas group was to develop theoretical and simplified numerical models to understand chirping phenomena often seen for Alfven and geodesic acoustic waves in experimental plasmas such as D-III-D, NSTX and JET. Its main numerical effort was to modify the AEGIS code, which was originally developed as an eigenvalue solver. To apply to the chirping problem this code has to be able to treat the linear response to the continuum and the response of the plasma to external drive or to an internal drive that comes from the formation of phase space chirping structures. The theoretical underpinning of this investigation still needed to be more fully developed to understand how to best formulate the theoretical problem. Considerable progress was made on this front by B.N. Breizman and his collaborators and a new reduced model was developed by H. L. Berk and his PhD student, G. Wang which can be uses as simplified model to describe chirping in a large aspect ratio tokamak. This final report will concentrate on these two directions that were developed as well as results that were found in the work with the AEGIS code and in the progress in developing a novel quasi-linear formulation for a description of Alfvenic modes destabilized by energetic particles, such as alpha particles in a burning plasma.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2020

Survey of Dynamic Mode Decomposition Methods

Dynamic mode decomposition (DMD) is a data-driven reduced order modeling (ROM) technique used for dynamic systems. The widely adopted algorithm was first introduced and demonstrated on fluid flow data by Schmid. In recent years, various other fields, such as nuclear engineering, have begun to adopt this method. For example, DMD has been used for estimating α-eigenvalues, as an ROM for pulsed neutron problems, for predicting isotopic composition in burnup calculations, as acceleration techniques for iterative methods, and in capturing dynamic behaviors in molten salt reactor transients. This report seeks to demonstrate the capabilities and limits of the standard DMD algorithm, and identify problem spaces where variants may be better suited. The primary variant this report considers is Multi-Resolution DMD (mrDMD). Because this serves as a survey, synthetically produced data is used in lieu of simulation results. The remainder of this report will go into detail on the DMD theory, outline the standard DMD and mrDMD algorithms, present test cases highlighting the applicability of each, and finally present a discussion on how to determine the best suited algorithm for a given problem. All calculations performed in this report are carried out using the open source DMD library, PyDMD.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2020

Learning in Modal Space: Solving Time-Dependent Stochastic PDEs Using Physics-Informed Neural Networks

One of the open problems in scientific computing is the long-time integration of nonlinear stochastic partial differential equations (SPDEs), especially with arbitrary initial data. We address this problem by taking advantage of recent advances in scientific machine learning and the spectral dynamically orthogonal (DO) and borthogonal (BO) methods for representing stochastic processes. The recently introduced DO/BO methods reduce the SPDE to solving a system of deterministic PDEs and a system of stochastic ordinary differential equations. Specifically, we propose two new physics-informed neural networks (PINNs) for solving time-dependent SPDEs, namely the neural network (NN)-DO/BO methods. The proposed methods incorporate the DO/BO constraints into the loss function (along with the modal decomposition of the SPDE) with an implicit form instead of generating explicit expressions for the temporal derivatives of the DO/BO modes. Hence, the NN-DO/BO methods can overcome some of the drawbacks of the original DO/BO methods. For example, we do not need the assumption that the covariance matrix of the random coefficients is invertible as in the original DO method, and we can remove the assumption of no eigenvalue crossing as in the original BO method. Moreover, the NN-DO/BO methods can be used to solve time-dependent stochastic inverse problems with the same formulation and same computational complexity as for forward problems. Furthermore, we demonstrate the capability of the proposed methods via several numerical examples, namely: (1) A linear stochastic advection equation with deterministic initial condition: we obtain good results with the proposed methods, while the original DO/BO methods cannot be applied directly in this case. (2) Long-time integration of the stochastic Burgers' equation: we show the good performance of NN-DO/BO methods, especially the effectiveness of the NN-BO approach for such problems with many eigenvalue crossings during the whole time evolution, while the original BO method fails. (3) Nonlinear reaction diffusion equation: we consider both the forward problem and the inverse problems, including very noisy initial point values, to investigate the flexibility of the NN-DO/BO methods in handling inverse and mixed type problems. Taken together, these simulation results demonstrate that the NN-DO/BO methods can be employed to effectively quantify uncertainty propagation in a wide range of physical problems, but future work should address the efficiency issue of PINNs for forward problems.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2013

Development of a S{sub n} transport code based on discontinuous finite element method and coarse mesh finite difference formulation

The methods and performance of a three-dimensional S{sub n} transport code employing the Discontinuous Finite Element Method (DFEM) and the Coarse Mesh Finite Difference (CMFD) formulation are presented. The mesh generator GMSH and a post processing visualization tool Visit are combined with the code for flexible geometry processing and versatile visualization. The CMFD method for DFEM Sn applications is formulated and the performance of the CMFD acceleration of eigenvalue calculations is demonstrated for a simple set of neutron transport problems. (authors)

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2014

An approach for coupled-code multiphysics core simulations from a common input

This study describes an approach for coupled-code multiphysics reactor core simulations that is being developed by the Virtual Environment for Reactor Applications (VERA) project in the Consortium for Advanced Simulation of Light-Water Reactors (CASL). In this approach a user creates a single problem description, called the “VERAIn” common input file, to define and setup the desired coupled-code reactor core simulation. A preprocessing step accepts the VERAIn file and generates a set of fully consistent input files for the different physics codes being coupled. The problem is then solved using a single-executable coupled-code simulation tool applicable to the problem, which is built using VERA infrastructure software tools and the set of physics codes required for the problem of interest. The approach is demonstrated by performing an eigenvalue and power distribution calculation of a typical three-dimensional 17 × 17 assembly with thermal–hydraulic and fuel temperature feedback. All neutronics aspects of the problem (cross-section calculation, neutron transport, power release) are solved using the Insilico code suite and are fully coupled to a thermal–hydraulic analysis calculated by the Cobra-TF (CTF) code. The single-executable coupled-code (Insilico-CTF) simulation tool is created using several VERA tools, including LIME (Lightweight Integrating Multiphysics Environment for coupling codes), DTK (Data Transfer Kit), Trilinos, and TriBITS. Parallel calculations are performed on the Titan supercomputer at Oak Ridge National Laboratory using 1156 cores, and a synopsis of the solution results and code performance is presented. Finally, ongoing development of this approach is also briefly described.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2019

REBUS-PC v1.5 Verification Test Summary

Motivated in part by its usage for analysis of the University of Missouri Research Reactor (MURR), the verification of the REBUS-PC software for θ-R-Z geometries is discussed and displayed in this manuscript. Of particular importance is to show that the eigenvalue, flux, power, and burnup outputs of the software given a user problem is correct. REBUS-PC contains many features and MURR only makes use of some of those aspects. As an example, the use of region specific cross section sets, interpolation of the cross section data with respect to burnup, and automatic movement of control rods during the fuel cycle is discussed and displayed. To demonstrate the accuracy, 22 verification tests based upon 7 physical geometries are discussed. Geometry descriptions are provided in Section 2 and the REBUS-PC results for each verification test are discussed in Section 3. These verification tests consist of both analytic problems with known solutions and a more complicated input consistent with usage of REBUS-PC on the MURR reactor itself called STRZ. In this verification test summary report, the REBUS-PC software is repeatedly demonstrated to reproduce, or closely match, the eigenvalue, flux, and power distributions from analytic test problem solutions, demonstrating that the implemented finite difference approximation in θ-R-Z is working as intended. Several additional REBUS-PC features are tested, such as control rod movement by detailed comparisons of the results against reference solutions obtained using an auxiliary implemented MatLab program. As expected, the REBUS-PC software produces results that are 100% consistent with the stated capabilities and thus the verification exercise is completed. These verification tests should be executed with each re-compilation of the REBUS-PC source and after any source code changes. All output results from any such new work should be rigorously compared against the stored output of the 22 verification tests cited in this report that forms the basis of the verification process.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2017

Extension of the DIF3D Code for Molten Salt Reactor Analysis

The molten salt reactor (MSR) with the fuel dissolved into the liquid salt has been selected as one of the six Generation-IV reactors due to its excellent characteristics in the aspects of sustainability, economy, passive safety, and resource utilization. In a MSR, the fuel salt is circulated throughout the whole system and thus some of delayed neutron precursors generated in the core decay in position of low importance or even out of the core. As a result, the multiplication factor (k-eff) of MSR is smaller than that of a reactor of stationary fuel when all the other conditions are same. Therefore, the neutronics code developed for stationary fuel cannot be applied directly to MSR analysis. In this paper, we describe the extension and application of the DIF3D code to MSR neutronics analysis. The DIF3D code system is a multi-group steady-state neutron diffusion and transport theory solver. It provides three flux solution options: finite-difference diffusion theory, nodal diffusion theory, and variational nodal transport theory methods. Eigenvalue, adjoint, fixed source and criticality (concentration) search problems are permitted. The DIF3D code has recently been modified to model the flowing fuel. To verify the new capability of DIF3D, the MSFR [4] core was analyzed with a wide range of velocity field of fuel salt and time spent outside of the core.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2023

Exact QFT duals of AdS black holes

We construct large N saddle points of the matrix model for the $\mathcal{N}$ = 4 Yang- Mills index dual to the BPS black holes in AdS 5 × S 5 , in two different setups. When the two complex chemical potentials for the angular momenta are collinear, we find linear eigenvalue distributions which solve the large N saddle point equation. When the chemical potentials are not collinear, we find novel solutions given by areal eigenvalue distributions after slightly reformulating the saddle point problem. We also construct a class of multi-cut saddle points, showing that they sometimes admit nontrivial filling fractions. As a byproduct, we find that the Bethe ansatz equation emerges from our saddle point equation.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2022

Machine Learning Moment Closure Models for the Radiative Transfer Equation III: Enforcing Hyperbolicity and Physical Characteristic Speeds

This is the third paper in a series in which we develop machine learning (ML) moment closure models for the radiative transfer equation. In our previous work (Huang et al. in J Comput Phys 453:110941, 2022), we proposed an approach to learn the gradient of the unclosed high order moment, which performs much better than learning the moment itself and the conventional $P_N$ closure. However, while the ML moment closure has better accuracy, it is not able to guarantee hyperbolicity and has issues with long time stability. In our second paper (Huang et al., in: Machine learning moment closure models for the radiative transfer equation II: enforcing global hyperbolicity in gradient based closures, 2021. arXiv:2105.14410), we identified a symmetrizer which leads to conditions that enforce that the gradient based ML closure is symmetrizable hyperbolic and stable over long time. The limitation of this approach is that in practice the highest moment can only be related to four, or fewer, lower moments. In this paper, we propose a new method to enforce the hyperbolicity of the ML closure model. Motivated by the observation that the coefficient matrix of the closure system is a lower Hessenberg matrix, we relate its eigenvalues to the roots of an associated polynomial. Here, we design two new neural network architectures based on this relation. The ML closure model resulting from the first neural network is weakly hyperbolic and guarantees the physical characteristic speeds, i.e., the eigenvalues are bounded by the speed of light. The second model is strictly hyperbolic and does not guarantee the boundedness of the eigenvalues. Several benchmark tests including the Gaussian source problem and the two-material problem show the good accuracy, stability and generalizability of our hyperbolic ML closure model.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2014

Nonlinear quantum-mechanical system associated with Sine-Gordon equation in (1 + 2) dimensions

Despite the fact that it is not integrable, the (1 + 2)-dimensional Sine-Gordon equation has N-soliton solutions, whose velocities are lower than the speed of light (c = 1), for all N ≥ 1. Based on these solutions, a quantum-mechanical system is constructed over a Fock space of particles. The coordinate of each particle is an angle around the unit circle. U, a nonlinear functional of the particle number-operators, which obeys the Sine-Gordon equation in (1 + 2) dimensions, is constructed. Its eigenvalues on N-particle states in the Fock space are the slower-than-light, N-soliton solutions of the equation. A projection operator (a nonlinear functional of U), which vanishes on the single-particle subspace, is a mass-density generator. Its eigenvalues on multi-particle states play the role of the mass density of structures that emulate free, spatially extended, relativistic particles. The simplicity of the quantum-mechanical system allows for the incorporation of perturbations with particle interactions, which have the capacity to “annihilate” and “create” solitons – an effect that does not have an analog in perturbed classical nonlinear evolution equations.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2015

Analyzing the properties of acceptor mode in two-dimensional plasma photonic crystals based on a modified finite-difference frequency-domain method

In this paper, the properties of acceptor mode in two-dimensional plasma photonic crystals (2D PPCs) composed of the homogeneous and isotropic dielectric cylinders inserted into nonmagnetized plasma background with square lattices under transverse-magnetic wave are theoretically investigated by a modified finite-difference frequency-domain (FDFD) method with supercell technique, whose symmetry of every supercell is broken by removing a central rod. A new FDFD method is developed to calculate the band structures of such PPCs. The novel FDFD method adopts a general function to describe the distribution of dielectric in the present PPCs, which can easily transform the complicated nonlinear eigenvalue equation to the simple linear equation. The details of convergence and effectiveness of proposed FDFD method are analyzed using a numerical example. The simulated results demonstrate that the enough accuracy of the proposed FDFD method can be observed compared to the plane wave expansion method, and the good convergence can also be obtained if the number of meshed grids is large enough. As a comparison, two different configurations of photonic crystals (PCs) but with similar defect are theoretically investigated. Compared to the conventional dielectric-air PCs, not only the acceptor mode has a higher frequency but also an additional photonic bandgap (PBG) can be found in the low frequency region. The calculated results also show that PBGs of proposed PPCs can be enlarged as the point defect is introduced. The influences of the parameters for present PPCs on the properties of acceptor mode are also discussed in detail. Numerical simulations reveal that the acceptor mode in the present PPCs can be easily tuned by changing those parameters. Those results can hold promise for designing the tunable applications in the signal process or time delay devices based on the present PPCs.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2015

Coherent states for nonlinear harmonic oscillator and some of its properties

A one-dimensional nonlinear harmonic oscillator is studied in the context of generalized coherent states. We develop a perturbative framework to compute the eigenvalues and eigenstates for the quantum nonlinear oscillator and construct the generalized coherent states based on Gazeau-Klauder formalism. We analyze their statistical properties by means of Mandel parameter and second order correlation function. Our analysis reveals that the constructed coherent states exhibit super-Poissonian statistics. Moreover, it is shown that the coherent states mimic the phenomena of quantum revivals and fractional revivals during their time evolution. The validity of our results has been discussed in terms of various parametric bounds imposed by our computational scheme.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2021

Recent Updates in ETOE-2 and MC 2 -3

The MC 2 -3 code is a multigroup cross section generation code for fast reactor applications, developed by Argonne National Laboratory (ANL) under the DOE Nuclear Energy Advanced Modeling and Simulation (NEAMS) program. In this work, first, the cross section libraries for ENDF/B-VII.1 and ENDF/B-VIII.0 data were generated using the updated ETOE-2 code. Preliminary verification and validation tests of the ENDF/B-VII.1 MC 2 -3 library were performed with the selected fast reactor benchmark problems. Processing and verifying the libraries suggested that significant efforts would be required for thoroughly verifying the ENDF/B-VII.1 MC 2 -3 library and successfully processing the ENDF/B-VIII.0 MC 2 -3 library. Secondly, the cross section generation capability of MC 2 -3 was updated with the intermediate group lattice calculation and the equivalent Dancoff-factor cell (EDC) method to significantly improve the performance of a twodimensional assembly calculation using the method of characteristics (MOC). This effort was made useful in implementing and verifying the EDC method in the Griffin cross section API. Finally, we analyzed a SFR problem, for which unusually large deviations in core eigenvalues from Monte Carlo solutions were reported, by generating multigroup cross sections with MC 2 -3, performing core calculations with DIF3D-VARIANT, and analyzing cross section and eigenvalue results against Monte Carlo solutions. The analysis confirmed that the MC 2 -3/DIF3D solutions were in good agreement with Monte Carlo solutions, providing the correct process of accurately generating broad-group cross sections with MC 2 -3

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2013

Analysis of physics-based preconditioning for single-phase subchannel equations

The (single-phase) subchannel approximations are used throughout nuclear engineering to provide an efficient flow simulation because the computational burden is much smaller than for computational fluid dynamics (CFD) simulations, and empirical relations have been developed and validated to provide accurate solutions in appropriate flow regimes. Here, the subchannel equations have been recast in a residual form suitable for a multi-physics framework. The Eigen spectrum of the Jacobian matrix, along with several potential physics-based preconditioning approaches, are evaluated, and the the potential for improved convergence from preconditioning is assessed. The physics-based preconditioner options include several forms of reduced equations that decouple the subchannels by neglecting crossflow, conduction, and/or both turbulent momentum and energy exchange between subchannels. Eigen-scopy analysis shows that preconditioning moves clusters of eigenvalues away from zero and toward one. A test problem is run with and without preconditioning. Without preconditioning, the solution failed to converge using GMRES, but application of any of the preconditioners allowed the solution to converge. (authors)

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2017

Evaluation of Rapid for a UNF cask benchmark problem

To ensure criticality safety and maintain a high level of security of Used Nuclear Fuel (UNF), it is necessary to perform detailed Particle Transport simulations. The commonly used technique is the 3-D, continuous energy Monte Carlo method that is time-consuming and, for eigenvalue calculations, may have difficulties with the source convergence. Wenner and Haghighat and Dufek demonstrated that in criticality problems with high dominance ratio and/or under-sampling possibilities, the fission matrix (FM) methodology should be used in order to be able to obtain unbiased solution. The RAPID (Real-time Analysis for Particle transport and In-situ Detection) code system is based on the Multi-stage Response-function Transport (MRT) methodology, and uses the FM formulation to determine eigenvalue, subcritical multiplication and fission density distribution of nuclear systems. This paper uses a benchmark problem similar to the GBC-32 Cask to evaluate the accuracy and performance of RAPID against the results of a reference MCNP solution. We performed a detailed sensitivity analysis on a single-assembly model in order to determine the MCNP eigenvalue parameters necessary to obtain a reliable reference solution. These results provided a guide for the selection of an appropriate set of parameters for the eigenvalue calculation for the whole cask. The paper is organized as follows: initially, the RAPID code system is briefly discussed; then, the benchmark problem is introduced. The methodology used to analyze results is proposed and some of the results of different cases are analyzed to identify the best set of eigenvalue parameters for a reference MCNP calculation. The selected case is then compared with the RAPID calculation for both a single assembly and a full cask model. In the end some conclusions and future work perspectives are drawn.

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗
DOE OSTI2020

MPACT Verification With Magnox Reactor Neutronics Progression Problems

MPACT is a state-of-the-art core simulator designed to perform high-fidelity analysis using whole-core, three-dimensional, pin-resolved neutron transport calculations on modern parallel computing hardware. MPACT was originally developed to model light water reactors, and its capabilities are being extended to simulate gas-cooled, graphite-moderated cores such as Magnox reactors. To verify MPACT’s performance in this new application, the code is being formally benchmarked using representative problems. Progression problems are a series of example models that increase in complexity designed to test a code’s performance. The progression problems include both beginning-of-cycle and depletion calculations. Reference solutions for each progression problem have been generated using Serpent 2, a continuous-energy Monte Carlo reactor physics burnup calculation code.Using the neutron multiplication eigenvalue ke as a metric, MPACT’s performance is assessed on each of the progression problems. Initial results showed that MPACT’s multi-group cross section libraries, originally developed for pressurized water reactor problems, were not sufficient to accurately solve Magnox problems. MPACT’s improved performance on the progression problems is demonstrated using this new optimized cross section library.

Luciano, Nicholas↗
DOE OSTI2018

A new relaxed splitting preconditioner for the generalized saddle point problems from the incompressible Navier–Stokes equations

Based on the modified relaxed splitting (MRS) preconditioner proposed by Fan and Zhu (Appl Math Lett 55:18–26, 2016), a new relaxed splitting preconditioner is proposed for the generalized saddle point problems arising from the incompressible Navier–Stokes equations. The eigenvalue distribution and an upper bound of the degree of the minimal polynomial of the preconditioned matrix are analyzed. Numerical results show that the proposed preconditioner is superior to the MRS preconditioner when they are used as preconditioners to accelerate the convergence rate of the Krylov subspace methods, such as GMRES.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2018

The parameterized preconditioner for the generalized saddle point problems from the incompressible Navier–Stokes equations

A parameterized preconditioner is proposed for the generalized saddle point problems arising from the incompressible Navier–Stokes equations. The eigenvalues and eigenvectors of the preconditioned matrix are analyzed. Numerical results show that the proposed preconditioner is efficient to accelerate the convergence rate of Krylov subspace methods, such as GMRES method.

97 MATHEMATICS AND COMPUTING↗