利用列导数公式实现奥尔德罗伊德-B 粘弹性流体流动的离散化

IF 1.7 3区 数学 Q2 MATHEMATICS, APPLIED
Ben S. Ashby, Tristan Pryer
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引用次数: 0

摘要

在这篇文章中,我们介绍了奥尔德罗伊德-B 流体斯托克斯流的数值方法。粘弹性应力根据上对流时间导数制定的构成定律演变。采用有限差分法沿流体轨迹离散,以简单、廉价和内聚的方式逼近上对流导数的平流和变形项,并确保离散构象张量为正定。本文介绍了与流体流动耦合的完整实施方案,并详细讨论了此类方案中出现的问题。我们在盖子驱动的空腔设置中进行了详细的数值实验,证明了该方法的性能。数值结果与已公布的数据进行了比对,结果表明该方法在这种具有挑战性的情况下表现良好。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Discretisation of an Oldroyd-B viscoelastic fluid flow using a Lie derivative formulation

In this article, we present a numerical method for the Stokes flow of an Oldroyd-B fluid. The viscoelastic stress evolves according to a constitutive law formulated in terms of the upper convected time derivative. A finite difference method is used to discretise along fluid trajectories to approximate the advection and deformation terms of the upper convected derivative in a simple, cheap and cohesive manner, as well as ensuring that the discrete conformation tensor is positive definite. A full implementation with coupling to the fluid flow is presented, along with a detailed discussion of the issues that arise with such schemes. We demonstrate the performance of this method with detailed numerical experiments in a lid-driven cavity setup. Numerical results are benchmarked against published data, and the method is shown to perform well in this challenging case.

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来源期刊
CiteScore
3.00
自引率
5.90%
发文量
68
审稿时长
3 months
期刊介绍: Advances in Computational Mathematics publishes high quality, accessible and original articles at the forefront of computational and applied mathematics, with a clear potential for impact across the sciences. The journal emphasizes three core areas: approximation theory and computational geometry; numerical analysis, modelling and simulation; imaging, signal processing and data analysis. This journal welcomes papers that are accessible to a broad audience in the mathematical sciences and that show either an advance in computational methodology or a novel scientific application area, or both. Methods papers should rely on rigorous analysis and/or convincing numerical studies.
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