On the Numerical Solution of the Poisson Equation in the Smoothed Particle Hydrodynamics

IF 2.4 2区 数学 Q1 MATHEMATICS, APPLIED
Matteo Antuono, Julien Michel, Salvatore Marrone
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引用次数: 0

Abstract

In the present work, we address some aspects related to the numerical solution of the Poisson equation within the framework of the Smoothed Particle Hydrodynamics (SPH). In this case, the Poisson equation is solved using nonlocal, kernel-based discretizations of the differential operators (i.e., gradient, divergence, and Laplacian operators) defined on scattered particle sets without topological connections. This paper clarifies two distinct sources of pressure artifacts that are often conflated in the SPH literature: (i) checkerboard-like spurious pressure modes caused by discrete operator incompatibility and pressure-velocity decoupling, and (ii) loss of accuracy due to particle disorder and kernel support truncation near boundaries. We propose diagnostics and procedures that separate these mechanisms and use representative benchmark tests to compare common SPH Poisson/Laplacian formulations in terms of robustness, convergence, and sensitivity to disorder and boundary deficiency. The resulting perspective reconciles conflicting claims and provides a theoretical guidance for practical applications.

光滑粒子流体力学泊松方程的数值解
在目前的工作中,我们在光滑粒子流体力学(SPH)的框架内讨论了与泊松方程数值解有关的一些方面。在这种情况下,泊松方程是使用微分算子(即梯度、散度和拉普拉斯算子)的非局部、基于核的离散化来求解的,这些微分算子定义在没有拓扑连接的分散粒子集上。本文阐明了SPH文献中经常混淆的两种不同的压力伪影来源:(i)离散算子不相容和压力-速度解耦引起的棋盘状虚假压力模式,以及(ii)由于粒子无序和核支持截断而导致的精度损失。我们提出了分离这些机制的诊断和程序,并使用代表性的基准测试来比较常见的SPH泊松/拉普拉斯公式在鲁棒性、收敛性以及对无序和边界缺陷的敏感性方面。由此产生的观点调和了相互矛盾的主张,并为实际应用提供了理论指导。
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
Studies in Applied Mathematics
Studies in Applied Mathematics 数学-应用数学
CiteScore
4.30
自引率
3.70%
发文量
66
审稿时长
>12 weeks
期刊介绍: Studies in Applied Mathematics explores the interplay between mathematics and the applied disciplines. It publishes papers that advance the understanding of physical processes, or develop new mathematical techniques applicable to physical and real-world problems. Its main themes include (but are not limited to) nonlinear phenomena, mathematical modeling, integrable systems, asymptotic analysis, inverse problems, numerical analysis, dynamical systems, scientific computing and applications to areas such as fluid mechanics, mathematical biology, and optics.
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