A Novel Density Correction Method for Improved Prediction of Pressure Fields in SPH

IF 2.9 3区 工程技术 Q1 ENGINEERING, MULTIDISCIPLINARY
Yoon Sung Jeong, Phill-Seung Lee
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引用次数: 0

Abstract

Smoothed particle hydrodynamics (SPH) has been extensively studied for several decades, yet accurate calculation of pressure fields remains a significant challenge, hindering its widespread application in practical engineering. This paper focuses on developing a novel density correction method to enhance the accuracy of hydrostatic pressure distribution in SPH, both near solid boundaries and within the fluid domain. The method incorporates two innovative concepts: an interpolation grid and supplementary particles, both aimed at refining density distributions. The proposed method is straightforward to implement, making it accessible for a wide range of applications. It proves highly effective in calculating improved hydrostatic pressure fields in high-pressure regions close to solid boundaries. Moreover, the proposed method effectively suppresses unphysical oscillations and peaks in the hydrodynamic pressure fields while alleviating unintended numerical dissipation that often occurs in long-term simulations. Additionally, the method offers greater flexibility in determining the correction interval and demonstrates excellent compatibility with various solid boundary treatments. The performance of the proposed method is validated through several numerical tests, and comparisons with other related numerical schemes are presented.

一种改进SPH压力场预测的新型密度校正方法
光滑颗粒流体力学(SPH)已经被广泛研究了几十年,但压力场的精确计算仍然是一个重大挑战,阻碍了其在实际工程中的广泛应用。本文重点研究了一种新的密度校正方法,以提高SPH中固体边界附近和流体域内静水压力分布的精度。该方法结合了两个创新的概念:插值网格和补充粒子,两者都旨在细化密度分布。所提出的方法易于实现,使其可用于广泛的应用程序。结果表明,该方法对于计算靠近固体边界的高压区域的改进静水压力场是非常有效的。此外,该方法有效地抑制了水动压力场的非物理振荡和峰值,同时减轻了长期模拟中经常出现的非预期数值耗散。此外,该方法在确定校正间隔方面具有更大的灵活性,并且与各种固体边界处理具有良好的兼容性。通过若干数值试验验证了该方法的性能,并与其他相关数值格式进行了比较。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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来源期刊
CiteScore
5.70
自引率
6.90%
发文量
276
审稿时长
5.3 months
期刊介绍: The International Journal for Numerical Methods in Engineering publishes original papers describing significant, novel developments in numerical methods that are applicable to engineering problems. The Journal is known for welcoming contributions in a wide range of areas in computational engineering, including computational issues in model reduction, uncertainty quantification, verification and validation, inverse analysis and stochastic methods, optimisation, element technology, solution techniques and parallel computing, damage and fracture, mechanics at micro and nano-scales, low-speed fluid dynamics, fluid-structure interaction, electromagnetics, coupled diffusion phenomena, and error estimation and mesh generation. It is emphasized that this is by no means an exhaustive list, and particularly papers on multi-scale, multi-physics or multi-disciplinary problems, and on new, emerging topics are welcome.
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