Is a direct numerical simulation (DNS) of Navier-Stokes equations with small enough grid spacing and time-step definitely reliable/correct?

IF 13 1区 工程技术 Q1 ENGINEERING, MARINE Journal of Ocean Engineering and Science Pub Date : 2024-05-14 DOI:10.1016/j.joes.2024.04.002
Shijie Qin , Yu Yang , Yongxiang Huang , Xinyu Mei , Lipo Wang , Shijun Liao
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Abstract

Turbulence is strongly associated with the vast majority of fluid flows in nature and industry. Traditionally, results given by the direct numerical simulation (DNS) of Navier-Stokes (NS) equations that relate to a famous millennium problem are widely regarded as ‘reliable’ benchmark solutions of turbulence, as long as grid spacing is fine enough (i.e. less than the minimum Kolmogorov scale) and time-step is small enough, say, satisfying the Courant-Friedrichs-Lewy condition (Courant number < 1). Is this really true? In this paper a two-dimensional sustained turbulent Kolmogorov flow driven by an external body force governed by the NS equations under an initial condition with a spatial symmetry is investigated numerically by the two numerical methods with detailed comparisons: one is the traditional DNS, the other is the ‘clean numerical simulation’ (CNS). In theory, the exact solution must have a kind of spatial symmetry since its initial condition is spatially symmetric. However, it is found that numerical noises of the DNS are quickly enlarged to the same level as the ‘true’ physical solution, which finally destroy the spatial symmetry of the flow field. In other words, the DNS results of the turbulent Kolmogorov flow governed by the NS equations are badly polluted mostly. On the contrary, the numerical noise of the CNS is much smaller than the ‘true’ physical solution of turbulence in a long enough interval of time so that the CNS result is very close to the ‘true’ physical solution and thus can remain symmetric, which can be used as a benchmark solution for comparison. Besides, it is found that numerical noise as a kind of artificial tiny disturbances can lead to huge deviations at large scale on the two-dimensional Kolmogorov turbulence governed by the NS equations, not only quantitatively (even in statistics) but also qualitatively (such as spatial symmetry of flow). This highly suggests that fine enough spatial grid spacing with small enough time-step alone could not guarantee the validity of the DNS of the NS equations: it is only a necessary condition but not sufficient. All of these findings might challenge some of our general beliefs in turbulence: for example, it might be wrong in physics to neglect the influences of small disturbances to NS equations. Our results suggest that, from physical point of view, it should be better to use the Landau-Lifshitz-Navier-Stokes (LLNS) equations, which consider the influence of unavoidable thermal fluctuations, instead of the NS equations, to model turbulent flows.

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用足够小的网格间距和时间步长对纳维-斯托克斯方程进行直接数值模拟(DNS)是否绝对可靠/正确?
湍流与自然界和工业界的绝大多数流体流动密切相关。传统上,只要网格间距足够细(即小于最小 Kolmogorov 尺度),时间步长足够小,例如满足 Courant-Friedrichs-Lewy 条件(Courant 数为 1),与著名的千年难题有关的纳维-斯托克斯(Navier-Stokes,NS)方程的直接数值模拟(DNS)结果就被广泛视为湍流的 "可靠 "基准解。事实果真如此吗?本文通过两种数值方法:一种是传统的 DNS,另一种是 "纯数值模拟"(CNS),对空间对称初始条件下由外力驱动的二维持续湍流 Kolmogorov 流进行了数值研究,并进行了详细比较。从理论上讲,精确解必须具有某种空间对称性,因为其初始条件是空间对称的。然而,人们发现 DNS 的数值噪声会迅速扩大到与 "真实 "物理解相同的水平,最终破坏流场的空间对称性。换句话说,由 NS 方程支配的湍流 Kolmogorov 流的 DNS 结果大多受到严重污染。相反,在足够长的时间间隔内,CNS 的数值噪声远小于湍流的 "真实 "物理解,因此 CNS 结果非常接近 "真实 "物理解,从而可以保持对称性,可作为基准解进行比较。此外,研究还发现,数值噪声作为一种人为的微小扰动,会导致受 NS 方程支配的二维 Kolmogorov 湍流在大尺度上出现巨大偏差,不仅在数量上(甚至在统计量上),而且在质量上(如流动的空间对称性)也会出现巨大偏差。这高度表明,仅靠足够细的空间网格间距和足够小的时间步长并不能保证 NS 方程 DNS 的有效性:它只是一个必要条件,而不是充分条件。所有这些发现可能会挑战我们对湍流的一些普遍看法:例如,在物理学中,忽视小扰动对 NS 方程的影响可能是错误的。我们的研究结果表明,从物理学角度来看,使用考虑了不可避免的热波动影响的兰道-利夫希茨-纳维尔-斯托克斯(LLNS)方程来模拟湍流应该比使用 NS 方程更好。
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来源期刊
CiteScore
11.50
自引率
19.70%
发文量
224
审稿时长
29 days
期刊介绍: The Journal of Ocean Engineering and Science (JOES) serves as a platform for disseminating original research and advancements in the realm of ocean engineering and science. JOES encourages the submission of papers covering various aspects of ocean engineering and science.
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