Implications of the selection of a particular modal decomposition technique for the analysis of shallow flows
Implications of the selection of a particular modal decomposition technique for the analysis of shallow flows
复制标题
DOI：
10.1080/00221686.2017.1419990
复制
发表时间：
2018-11-02
影响因子：
2.3
通讯作者：
Keylock, C. J.
中科院分区：
文献类型：
--
作者：
Higham, J. E.;Brevis, W.;Keylock, C. J.
这项工作涉及两种天气模态分解技术的能力，用于识别浅流中相干结构的空间模式和时间动力学。利用两种不同的实验数据表明，由于大尺度准二维流动结构的线性特性，传统的固有正交分解和最近发展的动态模态分解的结果在识别主导模态方面几乎没有差异。然而，也表明非线性动力学可以在这些结构向准二维行为的转变中出现，这可以导致适当的正交分解，识别由多频率组成的结构，这是一个复杂动力学的标志。因此，动态模态分解被推荐用于分析这种现象。此外，本文还介绍了一种基于适当正交分解结果的浅层流动态模态分解技术的简单排序方法。
This work deals with the capabilities of two synoptic modal decomposition techniques for the identification of the spatial patterns and temporal dynamics of coherent structures in shallow flows. Using two different experimental datasets it is shown that due to the linear behaviour of large-scale, quasi-two-dimensional flow structures, there are almost no differences in the identification of dominant modes between the results obtained from a traditional proper orthogonal decomposition and the more recently developed dynamic mode decomposition. However, it is also shown that nonlinear dynamics can arise in the transition of these structures to a quasi-two-dimensional behaviour, which can result in the proper orthogonal decomposition identifying structures composed of multi-frequencies, a sign of a convoluted dynamics. Thus dynamic mode decomposition is recommended instead for the analysis of such phenomena. In addition, this paper introduces a simple ranking methodology for the use of the dynamic mode decomposition technique in shallow flows, which is based on the results of the proper orthogonal decomposition.