Crank-Nicolson-type iterative decoupled algorithms for Biot’s consolidation model using total pressure

IF 2.6 3区 数学 Q2 MATHEMATICS, APPLIED
Huipeng Gu, Mingchao Cai, Jingzhi Li
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引用次数: 0

Abstract

In this work, we propose and analyze Crank-Nicolson-type iterative decoupled algorithms for a three-field formulation of Biot’s consolidation model using total pressure. These algorithms are derived from an equivalent, reformulated fully coupled system based on the Crank-Nicolson method, which is then decomposed using an iterative decoupled strategy. Two variants are introduced, differing in the solving order of temporal computation and iteration: a time-stepping and a global-in-time approach. The latter is particularly notable for its potential for parallel-in-time computing, offering an efficient approach for long-time simulations. Capitalizing on the properties of the underlying methods, both algorithms are proven to achieve second-order accuracy in time and unconditional stability. Through numerical experiments, we validate theoretical predictions and demonstrate the effectiveness and efficiency of these novel approaches.

总压力下Biot固结模型的crank - nicolson型迭代解耦算法
在这项工作中,我们提出并分析了crank - nicolson型迭代解耦算法,用于使用总压力的Biot固结模型的三场公式。这些算法来源于基于Crank-Nicolson方法的等效的,重新表述的全耦合系统,然后使用迭代解耦策略对其进行分解。介绍了两种不同的时间计算和迭代求解顺序的变体:时间步进法和全局实时法。后者尤其值得注意的是其并行计算的潜力,为长时间模拟提供了一种有效的方法。利用基础方法的性质,证明了这两种算法在时间上都能达到二阶精度和无条件稳定性。通过数值实验,我们验证了理论预测,并证明了这些新方法的有效性和效率。
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来源期刊
CiteScore
3.00
自引率
5.90%
发文量
68
审稿时长
3 months
期刊介绍: Advances in Computational Mathematics publishes high quality, accessible and original articles at the forefront of computational and applied mathematics, with a clear potential for impact across the sciences. The journal emphasizes three core areas: approximation theory and computational geometry; numerical analysis, modelling and simulation; imaging, signal processing and data analysis. This journal welcomes papers that are accessible to a broad audience in the mathematical sciences and that show either an advance in computational methodology or a novel scientific application area, or both. Methods papers should rely on rigorous analysis and/or convincing numerical studies.
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