English

Optimal prediction for moment models: Crescendo diffusion and reordered equations

Mathematical Physics 2023-10-10 v2 math.MP

Abstract

A direct numerical solution of the radiative transfer equation or any kinetic equation is typically expensive, since the radiative intensity depends on time, space and direction. An expansion in the direction variables yields an equivalent system of infinitely many moments. A fundamental problem is how to truncate the system. Various closures have been presented in the literature. We want to study moment closure generally within the framework of optimal prediction, a strategy to approximate the mean solution of a large system by a smaller system, for radiation moment systems. We apply this strategy to radiative transfer and show that several closures can be re-derived within this framework, e.g. PNP_N, diffusion, and diffusion correction closures. In addition, the formalism gives rise to new parabolic systems, the reordered PNP_N equations, that are similar to the simplified PNP_N equations. Furthermore, we propose a modification to existing closures. Although simple and with no extra cost, this newly derived crescendo diffusion yields better approximations in numerical tests.

Keywords

Cite

@article{arxiv.0902.0076,
  title  = {Optimal prediction for moment models: Crescendo diffusion and reordered equations},
  author = {Benjamin Seibold and Martin Frank},
  journal= {arXiv preprint arXiv:0902.0076},
  year   = {2023}
}

Comments

Revised version: 17 pages, 6 figures, presented at Workshop on Moment Methods in Kinetic Gas Theory, ETH Zurich, 2008 2 figures added, minor corrections

R2 v1 2026-06-21T12:06:40.227Z