Statistical Error Estimation Methods for Engineering-Relevant Quantities From Scale-Resolving Simulations
Statistical Error Estimation Methods for Engineering-Relevant Quantities From Scale-Resolving Simulations
复制标题
尺度解析模拟中工程相关量的统计误差估计方法
DOI：
10.1115/1.4052402
复制
发表时间：
2021
期刊：
影响因子：
--
通讯作者：
E. Kügeler
中科院分区：
文献类型：
--
作者：
M. Bergmann;C. Morsbach;G. Ashcroft;E. Kügeler
尺度解析模拟（例如大涡模拟）已成为研究涡轮机械部件流动的经济工具。所得到的时间分辨流场通常使用一阶和二阶统计矩进行分析。然而，在计算尺度解析模拟的统计矩时，存在两个不确定性来源：初始瞬态的影响和由于样本数量有限而导致的统计误差。在本文中，使用低压涡轮叶栅 T106C 的长时间大涡模拟的时间序列，系统地分析了几个工程兴趣量。评估了一组消除或量化这些不确定性来源的统计工具。首先，边际标准误差规则用于检测初始瞬态的结束。该方法针对积分和局部量进行了验证，并制定了如何处理空间变化的初始瞬态的指南。在可靠地消除初始瞬态的情况下，考虑时间序列中的相关性，基于标准误差关系来估计统计误差。利用累积和简单移动平均线仔细验证所得到的置信区间，以了解工程兴趣的数量。此外，还研究了大规模涡旋脱落的周期含量对误差估计的影响。根据置信区间，为每个考虑的数量指示将统计不确定性降低到特定水平所需的平均区间。
Scale-resolving simulations, such as large eddy simulations, have become affordable tools to investigate the flow in turbomachinery components. The resulting time-resolved flow field is typically analyzed using first- and second-order statistical moments. However, two sources of uncertainty are present when statistical moments from scale-resolving simulations are computed: the influence of initial transients and statistical errors due to the finite number of samples. In this paper, both are systematically analyzed for several quantities of engineering interest using time series from a long-time large eddy simulation of the low-pressure turbine cascade T106C. A set of statistical tools to either remove or quantify these sources of uncertainty is assessed. First, the Marginal Standard Error Rule is used to detect the end of the initial transient. The method is validated for integral and local quantities and guidelines on how to handle spatially varying initial transients are formulated. With the initial transient reliably removed, the statistical error is estimated based on standard error relations considering correlations in the time series. The resulting confidence intervals are carefully verified for quantities of engineering interest utilizing cumulative and simple moving averages. Furthermore, the influence of periodic content from large scale vortex shedding on the error estimation is studied. Based on the confidence intervals, the required averaging interval to reduce the statistical uncertainty to a specific level is indicated for each considered quantity.
影响因子：
3.6
作者：
Hoad, K.;Robinson, S.;Davies, R.
通讯作者：
Davies, R.
影响因子：
2.5
作者：
K. White;S. Robinson
通讯作者：
K. White;S. Robinson
影响因子：
3.4
作者：
Ries F;Nishad K;Dressler L;Janicka J;Sadiki A
通讯作者：
Sadiki A