General synthetic iterative scheme for multiscale radiative transfer in the finite-volume framework

TL;DR

This paper introduces a general synthetic iterative scheme for multiscale radiative transfer that accelerates simulations, handles opacity discontinuities, and preserves asymptotic limits, demonstrated by significant speed-ups in optically thick problems.

Contribution

The paper presents a novel synthetic iterative scheme combining a macroscopic equation with adaptive gradient approximation, improving efficiency and accuracy in multiscale radiative transfer simulations.

Findings

Achieves significant speed-up in optically thick problems

Effectively handles opacity discontinuities with adaptive least square method

Reveals the importance of resolving the Knudsen layer in initial stages

Abstract

Achieving efficient and accurate simulation of the radiative transfer has long been a research challenge. Here we introduce the general synthetic iterative scheme as an easy-to-implement approach to address this issue. First, a macroscopic synthetic equation, which combines the asymptotic equation at the diffusion limit and the "high-order terms" extracted from the transport equation to account for transport effects, is introduced to accelerate the simulation of the radiative transfer equation. Second, the asymptotic preserving property is directly provided by the macroscopic process, eliminating the need for fine spatial discretization in optically thick media, as well as the need for consistency enforcement. Third, to address the issue of opacity discontinuity in the finite volume method, an adaptive least square method for gradient approximation is proposed. Numerical results on several canonical tests demonstrate that, in optically thick problems, our method achieves significant speed-up over the conventional iterative schemes. Finally, with our newly developed method, we reveal the importance of resolving the Knudsen layer in the initial stage of Tophat problem, while in steady-state the Knudsen layer can be under-resolved.