Explicit time marching method with enhanced stability.

IF 2.2 3区 物理与天体物理 Q2 PHYSICS, FLUIDS & PLASMAS Physical Review E Pub Date : 2024-10-01 DOI:10.1103/PhysRevE.110.045302
Nishant Soni, Akshaysingh Shekawat, Santosh Ansumali, S V Diwakar
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Abstract

Recent developments in distributed computing architecture are slowly changing the way we develop partial differential equation solvers for simulating complex industrial and natural systems. Since achieving perfect parallelization of implicit temporal schemes is quite challenging, there is a growing interest in using explicit procedures with enhanced stability limits. The current work focuses on one such enhancement obtained by modifying an asynchronous delayed difference method. The proposed scheme, called the weighted difference scheme, is obtained as a weighted average of the delayed and conventional explicit schemes. This method exhibits an improved stability limit of 1.5 and also helps overcome the checkerboard instability associated with the delayed difference scheme. In the current paper, we discuss the different attributes of the proposed weighted scheme using a series of numerical analyses.

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增强稳定性的显式时间行进法
分布式计算架构的最新发展正在慢慢改变我们开发偏微分方程求解器以模拟复杂工业和自然系统的方式。由于实现隐式时程方案的完美并行化具有相当大的挑战性,因此人们对使用具有增强稳定性极限的显式程序越来越感兴趣。目前的工作重点是通过修改异步延迟差分法来增强稳定性。所提出的方案被称为加权差分方案,是延迟方案和传统显式方案的加权平均。这种方法的稳定性极限提高到了 1.5,而且还有助于克服与延迟差分方案相关的棋盘式不稳定性。在本文中,我们通过一系列数值分析讨论了拟议加权方案的不同属性。
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来源期刊
Physical Review E
Physical Review E PHYSICS, FLUIDS & PLASMASPHYSICS, MATHEMAT-PHYSICS, MATHEMATICAL
CiteScore
4.50
自引率
16.70%
发文量
2110
期刊介绍: Physical Review E (PRE), broad and interdisciplinary in scope, focuses on collective phenomena of many-body systems, with statistical physics and nonlinear dynamics as the central themes of the journal. Physical Review E publishes recent developments in biological and soft matter physics including granular materials, colloids, complex fluids, liquid crystals, and polymers. The journal covers fluid dynamics and plasma physics and includes sections on computational and interdisciplinary physics, for example, complex networks.
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