Low-memory, discrete ordinates, discontinuous Galerkin methods for radiative transport

TL;DR

This paper introduces a low-memory variation of the $S_N$-DG method for radiative transport that reduces degrees of freedom while preserving key properties, and employs upwind reconstruction to improve accuracy.

Contribution

It develops a memory-efficient $S_N$-DG method that maintains asymptotic limits and introduces upwind reconstruction for second-order accuracy.

Findings

The low-memory method reduces degrees of freedom compared to standard methods.

Second-order convergence is observed in diffusive regimes with the proposed reconstruction.

Numerical procedures effectively reduce system dimension in Krylov solvers.

Abstract

The discrete ordinates discontinuous Galerkin ($S_N$-DG) method is a well-established and practical approach for solving the radiative transport equation. In this paper, we study a low-memory variation of the upwind $S_N$-DG method. The proposed method uses a smaller finite element space that is constructed by coupling spatial unknowns across collocation angles, thereby yielding an approximation with fewer degrees of freedom than the standard method. Like the original $S_N$-DG method, the low memory variation still preserves the asymptotic diffusion limit and maintains the characteristic structure needed for mesh sweeping algorithms. While we observe second-order convergence in scattering dominated, diffusive regime, the low-memory method is in general only first-order accurate. To address this issue, we use upwind reconstruction to recover second-order accuracy. For both methods, numerical procedures based on upwind sweeps are proposed to reduce the system dimension in the underlying Krylov solver strategy.