快速收敛并行离线-在线迭代多尺度混合方法

IF 2.6 2区 数学 Q1 MATHEMATICS, APPLIED
Dilong Zhou , Rafael T. Guiraldello , Felipe Pereira
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引用次数: 0

摘要

在这项工作中,我们建立了最近引入的多尺度罗宾耦合方法与过采样和平滑(MRCM-OS),以开发两种高效的迭代多尺度方法。MRCM-OS方法证明了在具有挑战性的行业基准(即SPE10渗透率场)中实现10−4量级的通量误差的能力。这两种新提出的迭代方法,通过构建在线信息空间,显著提高了求解精度,在减少步骤数的情况下,达到了10−10阶的通量误差。所提出的方法基于在线信息空间的构建,并对其进行迭代改进以提高求解精度。在初始离线阶段之后,已知的边界条件被应用于构建多尺度基函数,通过利用由最近计算的解变量定义的边界条件的迭代过程更新信息空间。介绍了两种不同的方法,每种方法都利用这个框架来交付高效和准确的迭代解决方案。在SPE10基准上进行的一系列数值模拟表明,迭代解的收敛速度非常快。这些结果突出了这两种方法的计算效率和竞争力,并与文献中现有的多尺度迭代方法进行了彻底的比较。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Fast converging parallel offline–online iterative multiscale mixed methods
In this work, we build upon the recently introduced Multiscale Robin Coupled Method with Oversampling and Smoothing (MRCM-OS) to develop two highly efficient iterative multiscale methods. The MRCM-OS methodology demonstrated the ability to achieve flux error magnitudes on the order of 104 in a challenging industry benchmark, namely the SPE10 permeability field. The two newly proposed iterative procedures, through the construction of online informed spaces, significantly enhance the solution accuracy, reaching flux error magnitudes of order 1010 for a reduced number of steps.
The proposed methods are based on the construction of online informed spaces, which are iteratively refined to improve solution accuracy. Following an initial offline stage, where known boundary conditions are applied to construct multiscale basis functions, the informed spaces are updated through iterative procedures that utilize boundary conditions defined by the most recently computed solution variables. Two distinct approaches are introduced, each leveraging this framework to deliver efficient and accurate iterative solutions.
A series of numerical simulations, conducted on the SPE10 benchmark, demonstrates the very rapid convergence of the iterative solutions. These results highlight the computational efficiency and competitiveness of the two proposed methods, which are thoroughly compared to each other and to an existing multiscale iterative method from the literature.
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来源期刊
CiteScore
5.40
自引率
4.20%
发文量
437
审稿时长
3.0 months
期刊介绍: The Journal of Computational and Applied Mathematics publishes original papers of high scientific value in all areas of computational and applied mathematics. The main interest of the Journal is in papers that describe and analyze new computational techniques for solving scientific or engineering problems. Also the improved analysis, including the effectiveness and applicability, of existing methods and algorithms is of importance. The computational efficiency (e.g. the convergence, stability, accuracy, ...) should be proved and illustrated by nontrivial numerical examples. Papers describing only variants of existing methods, without adding significant new computational properties are not of interest. The audience consists of: applied mathematicians, numerical analysts, computational scientists and engineers.
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