拉格朗日流体力学的现代概念

IF 2.6 2区 数学 Q1 MATHEMATICS, APPLIED
L. G. Margolin, J. M. Canfield
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引用次数: 0

摘要

我们对可压缩流体流动的拉格朗日模拟中所采用的拉格朗日流体力学进行了现代诠释。我们的主要成果是证明了人工粘度--传统上被视为控制带有冲击的流动中的非物理振荡的数值工具--实际上代表了一个物理过程,并且是在任何可压缩流动中获得精确模拟所必需的。我们首先回顾了人工粘性和有限体积法这两种数值方法的起源。接着,我们构建了一个数学(PDE)模型,其中包含了这些数值方法,并在离散化过程中产生了一个新的长度尺度--观测器。与该长度尺度相关的是新的不粘性通量,即 Richtmyer 首次提出的人工粘性和 Noh 假设的人工热通量,但通常不包括在拉格朗日代码中。我们讨论了我们的结果与双速度流体力学的联系。最后,随着计算机速度越来越快、内存越来越大,我们对多维拉格朗日代码的未来发展方向进行了一些推测。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
A modern concept of Lagrangian hydrodynamics

We offer a modern interpretation of Lagrangian hydrodynamics as employed in Lagrangian simulations of compressible fluid flow. Our main result is to show that artificial viscosity, traditionally viewed as a numerical artifice to control unphysical oscillations in flows with shocks, actually represents a physical process and is necessary to derive accurate simulations in any compressible flow. We begin by reviewing the origins of two numerical devices, artificial viscosity and finite-volume methods. We proceed to construct a mathematical (PDE) model that incorporates those numerics and in which a new length scale, the observer, arises representing the discretization. Associated with that length scale, there are new inviscid fluxes that are the artificial viscosity as first formulated by Richtmyer and an artificial heat flux postulated by Noh but typically not included in Lagrangian codes. We discuss the connection of our results to bivelocity hydrodynamics. We conclude with some speculation as to the direction of future developments in multidimensional Lagrangian codes as computers get faster and have larger memories.

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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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