The present study is an extension of the work done in [16] and [10], where a two-level Parareal method with averaging was examined. The method proposed in this paper is a multi-level Parareal method with arbitrarily many levels, which is not restricted to the two-level case. We give an asymptotic error estimate which reduces to the two-level estimate for the case when only two levels are considered. Introducing more than two levels has important consequences for the averaging procedure, as we choose separate averaging windows for each of the different levels, which is an additional new feature of the present study. The different averaging windows make the proposed method especially appropriate for multi-scale problems, because we can introduce a level for each intrinsic scale of the problem and adapt the averaging procedure such that we reproduce the behavior of the model on the particular scale resolved by the level.
翻译:本研究是[16]年和[10]年所做工作的延伸,其中审查了平均的双级半数法,本文件建议的方法是一种多级半半数法,分多级,不仅限于两级。我们给出了无症状的误差估计数,在只考虑两个等级时,该估计数降为两级。引入两个以上等级对平均程序具有重要影响,因为我们为每个不同等级选择了不同的平均窗口,这是本研究的另一个新特点。不同的平均窗口使得拟议的方法特别适合多级问题,因为我们可以为问题的每个内在规模设定一个等级,并调整平均程序,以便复制由该等级解决的特定尺度上的模型行为。