Low-cost adaptive pressure-correction projection method for the 2D/3D time-dependent natural convection problems

IF 2.9 2区 数学 Q1 MATHEMATICS, APPLIED
Jilian Wu , Ning Li , Mengru Jiang , Xinlong Feng
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引用次数: 0

Abstract

The paper firstly develops a high-order and low-complexity time-stepping technique for solving two- and three-dimensional (2D/3D) natural convection problems, which is based on the standard pressure-correction projection (PCP) method and achieves higher-order accuracy by introducing the time filter (TF) technique. The new method can offset the weakness of PCP method while preserving its inherent advantages and can achieve higher-order in time by making a minimally intrusive modification to the PCP program at no extra computational and cognitive complexity. More importantly, it generates a low cost error estimator for adapting the time stepsize that can enhance time efficiency and reliability. Subsequently, the unconditional stability and error analysis of the fully-discrete PCP plus TF (PCP+TF) finite element method are proved. Notably, we construct low-complexity adaptive PCP algorithm, adaptive PCP+TF algorithm and the variable step, variable order (VSVO) algorithm using the TF technique. Ultimately, we verify the above viewpoints and theoretical analysis through some 2D/3D numerical experiments.
二维/三维时变自然对流问题的低成本自适应压力校正投影方法
本文首先在标准压力校正投影(PCP)方法的基础上,通过引入时间滤波器(TF)技术,实现了求解二维和三维(2D/3D)自然对流问题的高阶低复杂度时间步进技术。该方法在保留PCP方法固有优点的同时,弥补了PCP方法的不足,并且在不增加计算和认知复杂度的情况下,对PCP程序进行了最小程度的修改,在时间上实现了高阶。更重要的是,它产生了一个低成本的误差估计器来适应时间步长,提高了时间效率和可靠性。随后,证明了全离散PCP+TF (PCP+TF)有限元法的无条件稳定性和误差分析。值得注意的是,我们构建了低复杂度的自适应PCP算法、自适应PCP+TF算法和使用TF技术的变步长变阶(VSVO)算法。最后,我们通过一些二维/三维数值实验验证了上述观点和理论分析。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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来源期刊
Computers & Mathematics with Applications
Computers & Mathematics with Applications 工程技术-计算机:跨学科应用
CiteScore
5.10
自引率
10.30%
发文量
396
审稿时长
9.9 weeks
期刊介绍: Computers & Mathematics with Applications provides a medium of exchange for those engaged in fields contributing to building successful simulations for science and engineering using Partial Differential Equations (PDEs).
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