Numerical Errors in Unsteady Flow Simulations

IF 0.5 Q4 ENGINEERING, MECHANICAL Journal of Verification, Validation and Uncertainty Quantification Pub Date : 2019-06-01 DOI:10.1115/1.4043975
L. Eça, G. Vaz, S. Toxopeus, M. Hoekstra
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引用次数: 24

Abstract

This article discusses numerical errors in unsteady flow simulations, which may include round-off, statistical, iterative, and time and space discretization errors. The estimation of iterative and discretization errors and the influence of the initial condition on unsteady flows that become periodic are discussed. In this latter case, the goal is to determine the simulation time required to reduce the influence of the initial condition to negligible levels. Two one-dimensional, unsteady manufactured solutions are used to illustrate the interference between the different types of numerical errors. One solution is periodic and the other includes a transient region before it reaches a steady-state. The results show that for a selected grid and time-step, statistical convergence of the periodic solution may be achieved at significant lower error levels than those of iterative and discretization errors. However, statistical convergence deteriorates when iterative convergence criteria become less demanding, grids are refined, and Courant number increased.For statistically converged solutions of the periodic flow and for the transient solution, iterative convergence criteria required to obtain a negligible influence of the iterative error when compared to the discretization error are more strict than typical values found in the open literature. More demanding criteria are required when the grid is refined and/or the Courant number is increased. When the numerical error is dominated by the iterative error, it is pointless to refine the grid and/or reduce the time-step. For solutions with a numerical error dominated by the discretization error, three different techniques are applied to illustrate how the discretization uncertainty can be estimated, using grid/time refinement studies: three data points at a fixed Courant number; five data points involving three time steps for the same grid and three grids for the same time-step; five data points including at least two grids and two time steps. The latter two techniques distinguish between space and time convergence, whereas the first one combines the effect of the two discretization errors.
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非定常流场模拟中的数值误差
本文讨论了非定常流模拟中的数值误差,包括舍入误差、统计误差、迭代误差以及时间和空间离散化误差。讨论了迭代和离散化误差的估计以及初始条件对变为周期性非定常流的影响。在后一种情况下,目标是确定将初始条件的影响降低到可忽略水平所需的模拟时间。使用两个一维非定常制造解来说明不同类型的数值误差之间的干扰。一种解决方案是周期性的,另一种方案在达到稳态之前包括瞬态区域。结果表明,对于选定的网格和时间步长,周期解的统计收敛可以在显著低于迭代和离散化误差的误差水平下实现。然而,当迭代收敛准则要求降低、网格细化和库朗数增加时,统计收敛性会恶化。对于周期流的统计收敛解和瞬态解,与离散化误差相比,获得迭代误差的可忽略影响所需的迭代收敛标准比公开文献中的典型值更严格。当网格被细化和/或Courant数量增加时,需要更苛刻的标准。当数值误差由迭代误差主导时,细化网格和/或减少时间步长是毫无意义的。对于数值误差由离散化误差主导的解,应用三种不同的技术来说明如何使用网格/时间细化研究来估计离散化的不确定性:固定Courant数的三个数据点;涉及同一网格的三个时间步长和同一时间步长的三个网格的五个数据点;包括至少两个网格和两个时间步长的五个数据点。后两种技术区分了空间收敛和时间收敛,而第一种技术结合了两个离散化误差的影响。
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来源期刊
CiteScore
1.60
自引率
16.70%
发文量
12
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