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A stable multiplicative dynamical low-rank discretization for the linear Boltzmann-BGK equation

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arxiv 2411.06844 v2 pith:IO5DTHDP submitted 2024-11-11 math.NA cs.NA

classification math.NAcs.NA
keywords numericalboltzmann-bgkbasiscomputationaldiscretizationdlradynamicalequation
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The numerical method of dynamical low-rank approximation (DLRA) has recently been applied to various kinetic equations showing a significant reduction of the computational effort. In this paper, we apply this concept to the linear Boltzmann-Bhatnagar-Gross-Krook (Boltzmann-BGK) equation which due its high dimensionality is challenging to solve. Inspired by the special structure of the non-linear Boltzmann-BGK problem, we consider a multiplicative splitting of the distribution function. We propose a rank-adaptive DLRA scheme making use of the basis update & Galerkin integrator and combine it with an additional basis augmentation to ensure numerical stability, for which an analytical proof is given and a classical hyperbolic Courant-Friedrichs-Lewy (CFL) condition is derived. This allows for a further acceleration of computational times and a better understanding of the underlying problem in finding a suitable discretization of the system. Numerical results of a series of different test examples confirm the accuracy and efficiency of the proposed method compared to the numerical solution of the full system.

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Reviewed papers in the Pith corpus that reference this work. Sorted by Pith novelty score. Full citation record

  1. A Nodal Discontinuous Galerkin Method with Rank-Adaptive Velocity Space Representation for the Multiscale BGK Model

    math.NA 2025-08 conditional novelty 6.0 of 10

    A full-rank-in-space, low-rank-in-velocity nodal DG solver for 1d2v BGK is shown to be high-order, conservative, and asymptotic-preserving, with complexity linear in the velocity grid size.

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