arXiv subjects

Ryan G. McClarren

Publications and source records attributed to Ryan G. McClarren.

53 records · Page 3Linked to original sources

arXiv2021

Data-Driven Acceleration of Thermal Radiation Transfer Calculations with the Dynamic Mode Decomposition and a Sequential Singular Value Decomposition

We present a method for accelerating discrete ordinates radiative transfer calculations for radiative transfer. Our method works with nonlinear positivity fixes, in contrast to most acceleration schemes. The method is based on the dynamic mode decomposition (DMD) and using a sequence of rank-one updates to compute the singular value decomposition needed for DMD. Using a sequential method allows us to automatically determine the number of solution vectors to include in the DMD acceleration. We present results for slab geometry discrete ordinates calculations with the standard temperature linearization. Compared with positive source iteration, our results demonstrate that our acceleration method reduces the number of transport sweeps required to solve the problem by a factor of about 3 on a standard diffusive Marshak wave problem, a factor of several thousand on a cooling problem where the effective scattering ratio approaches unity, and a factor of 20 improvement in a realistic, multimaterial radiating shock problem.

physics.comp-ph↗

arXiv2020

A high-order / low-order (HOLO) algorithm for preserving conservation in time-dependent low-rank transport calculations

Dynamical low-rank (DLR) approximation methods have previously been developed for time-dependent radiation transport problems. One crucial drawback of DLR is that it does not conserve important quantities of the calculation, which limits the applicability of the method. Here we address this conservation issue by solving a low-order equation with closure terms computed via a high-order solution calculated with DLR. We observe that the high-order solution well approximates the closure term, and the low-order solution can be used to correct the conservation bias in the DLR evolution. We also apply the linear discontinuous Galerkin method for the spatial discretization to obtain the asymptotic limit. We then demonstrate with the numerical results that this so-called high-order / low-order (HOLO) algorithm is conservative without sacrificing computational efficiency and accuracy.

physics.comp-ph↗

arXiv2020

High-Energy Density Hohlraum Design Using Forward and Inverse Deep Neural Networks

We present a study of using machine learning to enhance hohlraum design for opacity measurement experiments. For opacity experiments we desire a hohlraum that, when its interior walls are illuminated by theNational Ignition Facility (NIF) lasers, will produce a high radiation flux that heats a central sample to a temperature that is constant over a measurement time window. Given a baseline hohlraum design and a computational model, we train a deep neural network to predict the time evolution of the radiation temperature as measured by the Dante diagnostic. This enables us to rapidly explore design space and determine the effect of adjusting design parameters. We also construct an "inverse" machine learning model that predicts the design parameters given a desired time history of radiation temperature. Calculations using the machine learning model demonstrate that improved performance over the baseline hohlraum would reduce uncertainties in experimental opacity measurements.

physics.ins-det↗

arXiv2020

Frequency-Dependent Material Motion Benchmarks for Radiative Transfer

We present a general solution for the radiation intensity in front of a purely absorbing slab moving toward an observer at constant speed and with a constant temperature. The solution is obtained by integrating the lab-frame radiation transport equation through the slab to the observer. We present comparisons between our benchmark and results from the Kull simulation code for an aluminum slab moving toward the observer at 2% the speed-of-light. We demonstrate that ignoring certain material motion correction terms in the transport equation can lead to 20-80% errors with the error magnitude growing as the frequency resolution is improved. Our results also indicate that our benchmark can identify potential errors in the implementation of material motion corrections.

cs.CE↗

arXiv2019

A low-rank method for time-dependent transport calculations

Low-rank approximation is a technique to approximate a tensor or a matrix with a reduced rank to reduce the memory required and computational cost for simulation. Its broad applications include dimension reduction, signal processing, compression, and regression. In this work, a dynamical low-rank approximation method is developed for the time-dependent radiation transport equation in slab geometry. Using a finite volume discretization in space and Legendre polynomials in angle we construct a system that evolves on a low-rank manifold via an operator splitting approach. We demonstrate that the lowrank solution gives better accuracy than solving the full rank equations given the same amount of memory.

physics.comp-ph↗

arXiv2019

Calculating Time Eigenvalues of the Neutron Transport Equation with Dynamic Mode Decomposition

A novel method to compute time eigenvalues of neutron transport problems is presented based on solutions to the time dependent transport equation. Using these solutions we use the dynamic mode decomposition (DMD) to form an approximate transport operator. This approximate operator has eigenvalues that can be directly related to the time eigenvalues of the neutron transport equation. This approach works for systems of any level of criticality and does not require the user to have estimates for the eigenvalues. Numerical results are presented for homogeneous and heterogeneous media. The numerical results indicate that the method finds the eigenvalues that are most important to the solution evolution over a given time range, and the eigenvalue with the largest real part is not necessarily important to the system evolution.

physics.comp-ph↗

arXiv2018

Acceleration of Source Iteration using the Dynamic Mode Decomposition

We present a novel acceleration technique for improving the convergence of source iteration for discrete ordinates transport calculations. Our approach uses the idea of the dynamic mode decomposition (DMD) to estimate the slowly decaying modes from source iteration and remove them from the solution. The memory cost of our acceleration technique is that the scalar flux for a number of iterations must be stored; the computational cost is a singular value decomposition of a matrix comprised of those stored scalar fluxes.On 1-D slab geometry problems we observe an order of magnitude reduction in the number of transport sweeps required compared to source iteration and that the number of sweeps required is independent of the scattering ratio in the problem. These observations hold for an extremely heterogeneous problem and a 2-D problem. In 2-D we do observe that the effectiveness of the approach slowly degrades as the mesh is refined, but is still about one order of magnitude faster than source iteration.

physics.comp-ph↗

arXiv2018

Filtered Stochastic Galerkin Methods For Hyperbolic Equations

Uncertainty Quantification for nonlinear hyperbolic problems becomes a challenging task in the vicinity of shocks. Standard intrusive methods lead to oscillatory solutions and can result in non-hyperbolic moment systems. The intrusive polynomial moment (IPM) method guarantees hyperbolicity but comes at higher numerical costs. In this paper, we filter the gPC coefficients of the Stochastic Galerkin (SG) approximation, which allows a numerically cheap reduction of oscillations. The derived filter is based on Lasso regression which sets small gPC coefficients of high order to zero. We adaptively choose the filter strength to obtain a zero-valued highest order moment, which allows optimality of the corresponding optimization problem. The filtered SG method is tested for Burgers' and the Euler equations. Results show a reduction of oscillations at shocks, which leads to an improved approximation of expectation values and the variance compared to SG and IPM.

math.NA↗

arXiv2017

An Accurate Globally Conservative Subdomain Discontinuous Least-squares Scheme for Solving Neutron Transport Problems

In this work, we present a subdomain discontinuous least-squares (SDLS) scheme for neutronics problems. Least-squares (LS) methods are known to be inaccurate for problems with sharp total-cross section interfaces. In addition, the least-squares scheme is known not to be globally conservative in heterogeneous problems. In problems where global conservation is important, e.g. k-eigenvalue problems, conservative treatment must be applied. We, in this study, proposed a SDLS method that retains global conservation. Such a method resembles the LS formulation in each subdomain without material interface and differs from LS in that an additional least-squares interface term appears for each interface. Scalar flux is continuous in each subdomain with continuous finite element method (CFEM) while discontinuous on interfaces for every pair of contiguous subdomains. SDLS numerical results are compared with those obtained from other numerical methods with test problems having material interfaces. High accuracy of scalar flux in fixed-source problems and $k_\mathrm{eff}$ in eigenvalue problems are demonstrated.

physics.comp-ph↗

arXiv2017

Accurate Least-Squares P$_N$ Scaling based on Problem Optical Thickness for solving Neutron Transport Problems

In this paper, we present an accurate and robust scaling operator based on material optical thickness (OT) for the least-squares spherical harmonics (LSP$_N$) method for solving neutron transport problems. LSP$_N$ without proper scaling is known to be erroneous in highly scattering medium, if the optical thickness of the material is large. A previously presented scaling developed by Manteuffel, et al.\ does improve the accuracy of LSP$_N$, in problems where the material is optically thick. With the method, however, essentially no scaling is applied in optically thin materials, which can lead to an erroneous solution with presence of highly scattering medium. Another scaling approach, called the reciprocal-removal (RR) scaled LSP$_N$, which is equivalent to the self-adjoint angular flux (SAAF) equation, has numerical issues in highly-scattering materials due to a singular weighting. We propose a scaling based on optical thickness that improves the solution in optically thick media while avoiding the singularity in the SAAF formulation.

physics.comp-ph↗

arXiv2017

Mathematical and numerical validation of the simplified spherical harmonics approach for time-dependent anisotropic-scattering transport problems in homogeneous media

In this work, we extend the solid harmonics derivation, which was used by Ackroyd et al to derive the steady-state SP$_N$ equations, to transient problems. The derivation expands the angular flux in ordinary surface harmonics but uses harmonic polynomials to generate additional surface spherical harmonic terms to be used in Galerkin projection. The derivation shows the equivalence between the SP$_N$ and the P$_N$ approximation. Also, we use the line source problem and McClarren's "box" problem to demonstrate such equivalence numerically. Both problems were initially proposed for isotropic scattering, but here we add higher-order scattering moments to them. Results show that the difference between the SP$_N$ and P$_N$ scalar flux solution is at the roundoff level.

physics.comp-ph↗

arXiv2016

Effective Non-oscillatory Regularized L$_1$ Finite Elements for Particle Transport Simulations

In this work, we present a novel regularized L$_1$ (RL$_1$) finite element spatial discretization scheme for radiation transport problems. We review the recently developed least-squares finite element method in nuclear applications. We then derive an L$_1$ finite element by minimizing the L$_1$ norm of the transport residual. To ensure the stability on incident boundary, we newly develop a consistent L$_1$ boundary condition (BC). The numerical tests demonstrate such a method effectively prevents the oscillations which would occur to least-squares finite element when discontinuity exists such as void and absorber. Further, the RL$_1$ method is accurate in problems with scattering.

physics.comp-ph↗

arXiv2016

Adjoint-based Sensitivity Analysis for High-Energy Density Radiaitive Transfer using Flux-Limited Diffusion

Uncertainty quantification and sensitivity analyses are a vital component for predictive modeling in the sciences and engineering. The adjoint approach to sensitivity analysis requires solving a primary system of equations and a mathematically related set of adjoint equations. The information contained in the equations can be combined to produce sensitivity information in a computationally efficient manner. In this work, sensitivity analyses are performed on systems described by flux-limited radiative diffusion using the adjoint approach. The sensitivities computed are shown to agree with standard perturbation theory, and can be obtained in significantly less computational time.

physics.comp-ph↗

arXiv2016

Approximate One-Dimensional Models for Monoenergetic Neutral Particle Transport in Ducts with Wall Migration

The problem of monoenergetic neutral particle transport in a duct, where particles travel inside the duct walls, is treated using an approximate one-dimensional model. The one-dimensional model uses three-basis functions, as part of a previously derived weighted-residual procedure, to account for the geometry of particle transport in a duct system (where particle migration into the walls is not considered). Our model introduces two stochastic parameters to account for particle-wall interactions: an albedo approximation yielding the fraction of particles that return to the duct after striking the walls, and a mean-distance travelled in the walls transverse to the duct by particles that re-enter the duct. Our model produces a set of three transport equations with a non-local scattering kernel. We solve these equations using discrete ordinates with source iteration. Numerical results for the reflection and transmission probabilities of neutron transport in ducts of circular cross section are compared to Monte Carlo results computed using the MCNP code.

physics.comp-ph↗

arXiv2016

Globally Conservative, Hybrid Self-Adjoint Angular Flux and Least-Squares Method Compatible with Void

In this paper, we derive a method for the second-order form of the transport equation that is both globally conservative and compatible with voids, using Continuous Finite Element Methods (CFEM). The main idea is to use the Least-Squares (LS) form of the transport equation in the void regions and the Self-Adjoint Angular Flux (SAAF) form elsewhere. While the SAAF formulation is globally conservative, the LS formulation need a correction in void. The price to pay for this fix is the loss of symmetry of the bilinear form. We first derive this Conservative LS (CLS) formulation in void. Second we combine the SAAF and CLS forms and end up with an hybrid SAAF-CLS method, having the desired properties. We show that extending the theory to near-void regions is a minor complication and can be done without affecting the global conservation of the scheme. Being angular discretization agnostic, this method can be applied to both discrete ordinates (SN) and spherical harmonics (PN) methods. However, since a globally conservative and void compatible second-order form already exists for SN (Wang et al. 2014), but is believed to be new for PN, we focus most of our attention on that latter angular discretization. We implement and test our method in Rattlesnake within the Multiphysics Object Oriented Simulation Environment (MOOSE) framework. Results comparing it to other methods are presented.

physics.comp-ph↗

arXiv2016

Moment Closures Based on Minimizing the Residual of the P$_N$ Angular Expansion in Radiation Transport

In this work we present two new closures for the spherical harmonics (PN) method in slab geometry transport problems. Our approach begins with an analysis of the squared-residual of the transport equation where we show that the standard truncation and diffusive closures do not minimize the residual of the PN expansion. Based on this analysis we derive two models, a moment-limited diffusive MLDN closure and a transient PN (TPN) closure that attempt to address shortcomings of common closures. The form of these closures is similar to flux-limiters for diffusion with the addition of a time-derivative in the definition of the closure. Numerical results on a pulsed plane source problem, the Gordian knot of slab-geometry transport problems, indicate that our new closure outperforms existing linear closures. Additionally, on a deep penetration problem we demonstrate that the TPN closure does not suffer from the artificial shocks that can arise in the MN entropy-based closure. Finally, results for Reed's problem demonstrate that the TPN solution is as accurate as the PN+3 solution. We further extend the TPN closure to 2D Cartesian geometry. The line source test problem demonstrates the model effectively damps oscillations and negative densities

physics.comp-ph↗

arXiv2016

Implicit Filtered PN for High-Energy Density Thermal Radiation Transport using Discontinuous Galerkin Finite Elements

In this work, we provide a fully-implicit implementation of the time-dependent, filtered spherical harmonics (FPN) equations for non-linear, thermal radiative transfer. We investigate local filtering strategies and analyze the effect of the filter on the conditioning of the system, showing in particular that the filter improves the convergence properties of the iterative solver. We also investigate numerically the rigorous error estimates derived in the linear setting, to determine whether they hold also for the non-linear case. Finally, we simulate a standard test problem on an unstructured mesh and make comparisons with implicit Monte-Carlo (IMC) calculations.

physics.comp-ph↗