A Coupling Algorithm of Computational Fluid and Particle Dynamics (CFPD)

A. Kim, Hyeon-Ju Kim
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引用次数: 2

Abstract

Computational fluid dynamics (CFD) and particle hydrodynamics (PHD) have been developed almost independently. CFD is classified into Eulerian and Lagrangian. The Eulerian approach observes fluid motion at specific locations in the space, and the Lagrangian approach looks at fluid motion where the observer follows an individual fluid parcel moving through space and time. In classical mechanics, particle dynamic simulations include molecular dynamics, Brownian dynamics, dissipated particle dynamics, Stokesian dynamics, and granular dynamics (often called discrete element method). Dissipative hydrodynamic method unifies these dynamic simulation algorithms and provides a general view of how to mimic particle motion in gas and liquid. Studies on an accurate and rigorous coupling of CFD and PHD are in literature still in a growing stage. This chapter shortly reviews the past development of CFD and PHD and proposes a general algorithm to couple the two dynamic simulations without losing theoretical rigor and numerical accuracy of the coupled simulation.
一种计算流体与粒子动力学(CFPD)耦合算法
计算流体力学(CFD)和粒子流体力学(PHD)几乎是独立发展起来的。CFD分为欧拉型和拉格朗日型。欧拉方法观察空间中特定位置的流体运动,拉格朗日方法观察流体运动,观察者跟随单个流体包在空间和时间中运动。在经典力学中,粒子动力学模拟包括分子动力学、布朗动力学、耗散粒子动力学、斯托克动力学和颗粒动力学(通常称为离散元法)。耗散流体动力学方法统一了这些动态模拟算法,提供了如何模拟气体和液体中粒子运动的一般观点。关于CFD与PHD精确、严格耦合的文献研究尚处于发展阶段。本章简要回顾了CFD和PHD过去的发展,并提出了一种通用的算法来耦合两种动态模拟,同时又不会失去耦合模拟的理论严谨性和数值精度。
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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