Robust Linearly-Implicit Backward Difference Formulas for Navier–Stokes Equations: Computations of Steady and Unsteady Flows

IF 1.8 4区 工程技术 Q3 COMPUTER SCIENCE, INTERDISCIPLINARY APPLICATIONS
Kak Choon Loy, Yves Bourgault
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引用次数: 0

Abstract

We propose a linearly-implicit method (called LBDFT) to solve the incompressible Navier–Stokes equations. Linearly-implicit methods have an algorithmic complexity that lies between fully-implicit and semi-implicit time-stepping schemes. In LBDFT, the nonlinear advection in the Navier–Stokes equations is split into three linear terms using a Taylor series expansion. One term is taken explicitly, and the other two are updated with the linear diffusion term at each time step. An additional variant of linearly-implicit methods, referred to as LBDFE, was also included in this study. It is based on an extrapolation formula similar to those used in semi-implicit methods. For the sake of comparison, we recall a set of fully-implicit and semi-implicit time-stepping methods, for the most part based on backward differentiation formulae (BDF). These methods are compared in terms of accuracy, stability, computing time, and ability to compute various flows. We first use a two-dimensional manufactured problem to assess the order convergence (in time) of the methods. The second test case is a two-dimensional unsteady flow around a cylinder at R e = 100 $$ \mathit{\operatorname{Re}}=100 $$ . We observed that linearly-implicit methods are more CPU efficient compared to fully-implicit BDF, both at second- and third-order accuracy. Our third test case explores the ability of the methods to compute steady flows at high Reynolds numbers, in our case a steady two-dimensional lid-driven cavity for R e = 1,000 $$ \mathit{\operatorname{Re}}=\mathrm{1,000} $$ to 65 , 000 $$ 65,000 $$ . Our LBDFT method was the most efficient for capturing these flows, with solutions almost identical to published results, while LBDFE methods do not work at all. LBDFT was able to compute steady cavity flows for R e = 100 , 000 $$ \mathit{\operatorname{Re}}=100,000 $$ to 500 , 000 $$ 500,000 $$ . Our last test case explores unsteady flows at large Reynolds numbers. Both LBDFT and LBDFE methods do not require any stabilization strategies for an unsteady two-dimensional lid-driven cavity at R e = 100 , 000 $$ \mathit{\operatorname{Re}}=100,000 $$ . We generated so-called Schlieren plots, which are comparable with the vorticity plots found in the literature. It was observed that the linearly-implicit methods allow significantly larger critical time steps (approximately 40–50 times higher) compared to the semi-implicit methods, the latter needing a grad-div stabilization term to maintain their stability.

Navier-Stokes方程的鲁棒线性隐式后向差分公式:定常和非定常流动的计算
我们提出了一种线性隐式方法(称为LBDFT)来求解不可压缩Navier-Stokes方程。线性隐式方法的算法复杂性介于全隐式和半隐式时间步进方案之间。在LBDFT中,利用泰勒级数展开将Navier-Stokes方程中的非线性平流分解为三个线性项。其中一项是显式的,另外两项在每个时间步用线性扩散项更新。线性隐式方法的另一种变体,称为LBDFE,也包括在本研究中。它基于类似于半隐式方法中使用的外推公式。为了便于比较,我们回顾了一组全隐式和半隐式时间步进方法,其中大部分是基于后向微分公式(BDF)。从精度、稳定性、计算时间和计算各种流的能力等方面对这些方法进行了比较。我们首先使用一个二维制造问题来评估方法的阶收敛性(在时间上)。第二个测试用例是绕圆柱体的二维非定常流场,雷诺数为100 $$ \mathit{\operatorname{Re}}=100 $$。我们观察到,与全隐式BDF相比,线性隐式方法在二阶和三阶精度上都具有更高的CPU效率。我们的第三个测试案例探讨了在高雷诺数下计算稳定流动的方法的能力,在我们的案例中,一个稳定的二维盖子驱动腔,Re = 1,000 $$ \mathit{\operatorname{Re}}=\mathrm{1,000} $$到65,000 $$ 65,000 $$。我们的LBDFT方法对于捕获这些流是最有效的,其解决方案几乎与公布的结果相同,而LBDFE方法根本不起作用。LBDFT能够计算R = 100,000 $$ \mathit{\operatorname{Re}}=100,000 $$到500,000 $$ 500,000 $$的稳定空腔流动。我们的最后一个测试案例探讨了大雷诺数下的非定常流。LBDFT和LBDFE方法都不需要任何稳定化策略来求解R = 100,000 $$ \mathit{\operatorname{Re}}=100,000 $$的非定常二维盖子驱动腔。我们生成了所谓的纹影图,它与文献中发现的涡度图相当。与半隐式方法相比,线性隐式方法允许更大的临界时间步长(大约40-50倍),后者需要一个梯度稳定项来保持其稳定性。
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来源期刊
International Journal for Numerical Methods in Fluids
International Journal for Numerical Methods in Fluids 物理-计算机:跨学科应用
CiteScore
3.70
自引率
5.60%
发文量
111
审稿时长
8 months
期刊介绍: The International Journal for Numerical Methods in Fluids publishes refereed papers describing significant developments in computational methods that are applicable to scientific and engineering problems in fluid mechanics, fluid dynamics, micro and bio fluidics, and fluid-structure interaction. Numerical methods for solving ancillary equations, such as transport and advection and diffusion, are also relevant. The Editors encourage contributions in the areas of multi-physics, multi-disciplinary and multi-scale problems involving fluid subsystems, verification and validation, uncertainty quantification, and model reduction. Numerical examples that illustrate the described methods or their accuracy are in general expected. Discussions of papers already in print are also considered. However, papers dealing strictly with applications of existing methods or dealing with areas of research that are not deemed to be cutting edge by the Editors will not be considered for review. The journal publishes full-length papers, which should normally be less than 25 journal pages in length. Two-part papers are discouraged unless considered necessary by the Editors.
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