Bonizzoni Francesca, Freese Philip, Peterseim Daniel
MOX-Dipartimento di Matematica, Politecnico di Milano, Piazza Leonardo da Vinci 32, 20133 Milan, Italy.
Institute of Mathematics, Hamburg University of Technology, Am Schwarzenberg-Campus 3, 21073 Hamburg, Germany.
BIT Numer Math. 2024;64(3):33. doi: 10.1007/s10543-024-01035-8. Epub 2024 Aug 5.
This paper presents a novel multi-scale method for convection-dominated diffusion problems in the regime of large Péclet numbers. The method involves applying the solution operator to piecewise constant right-hand sides on an arbitrary coarse mesh, which defines a finite-dimensional coarse ansatz space with favorable approximation properties. For some relevant error measures, including the -norm, the Galerkin projection onto this generalized finite element space even yields -independent error bounds, being the singular perturbation parameter. By constructing an approximate local basis, the approach becomes a novel multi-scale method in the spirit of the Super-Localized Orthogonal Decomposition (SLOD). The error caused by basis localization can be estimated in an a posteriori way. In contrast to existing multi-scale methods, numerical experiments indicate -robust convergence without pre-asymptotic effects even in the under-resolved regime of large mesh Péclet numbers.
本文提出了一种针对大佩克莱数 regime 下对流主导扩散问题的新型多尺度方法。该方法涉及在任意粗网格上对分段常数右侧项应用解算子,这定义了一个具有良好逼近性质的有限维粗近似空间。对于一些相关的误差度量,包括 - 范数,在此广义有限元空间上的伽辽金投影甚至能产生与 无关的误差界, 为奇异摄动参数。通过构造一个近似局部基,该方法成为一种符合超局部正交分解(SLOD)精神的新型多尺度方法。基局部化引起的误差可以后验方式进行估计。与现有的多尺度方法相比,数值实验表明即使在大网格佩克莱数的欠分辨率 regime 中也具有 - 鲁棒收敛性且无预渐近效应。