Energy-stable and efficient finite element schemes for the Shliomis model of ferrofluid flows

IF 2.1 3区 数学 Q2 MATHEMATICS, APPLIED
Guo-Dong Zhang, Kejia Pan, Xiaoming He, Xiaofeng Yang
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引用次数: 0

Abstract

In this paper, we aim to design two energy-stable and efficient finite element schemes for simulating the ferrofluid flows based on the well-known Shliomis model. The model is a highly nonlinear, coupled, multi-physics system, consisting of the Navier–Stokes equations, magnetostatic equation, and magnetization field equation. We propose two reliable numerical algorithms with the following desired features: linearity and unconditional energy stability. Several key techniques are used to achieve the required features, including the auxiliary variable method, consistent terms method, prediction-correction method, and semi-implicit stabilization method. The first scheme is based on a hybrid continuous/discontinuous finite elements spatial approximation, and the second utilizes decoupled continuous finite element spatial discretization. We have rigorously demonstrated that the proposed schemes are unconditionally energy stable and carried out extensive numerical simulations to illustrate the accuracy and stability of the developed schemes, as well as some interesting controllable characteristics of the ferrofluid flows.

铁磁流体Shliomis模型的能量稳定和高效有限元格式
本文旨在基于著名的Shliomis模型,设计两种能量稳定且高效的有限元方案来模拟铁磁流体的流动。该模型是一个高度非线性、耦合的多物理场系统,由Navier-Stokes方程、静磁方程和磁化场方程组成。我们提出了两种可靠的数值算法,它们具有以下期望的特征:线性和无条件能量稳定性。采用了辅助变量法、一致项法、预测校正法和半隐式稳定化法等关键技术来实现所要求的特征。第一种方案基于连续/不连续混合有限元空间逼近,第二种方案采用解耦连续有限元空间离散化。我们严格地证明了所提出的格式是无条件能量稳定的,并进行了大量的数值模拟来说明所开发格式的准确性和稳定性,以及一些有趣的铁磁流体流动的可控特性。
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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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