Application of the dynamic mode decomposition to experimental data

被引:0
|
作者
Peter J. Schmid
机构
[1] Ecole Polytechnique,Laboratoire d’Hydrodynamique (LadHyX)
来源
Experiments in Fluids | 2011年 / 50卷
关键词
Shear Layer; Proper Orthogonal Decomposition; Proper Orthogonal Decomposition Mode; Dynamic Mode Decomposition; Arnoldi Method;
D O I
暂无
中图分类号
学科分类号
摘要
The dynamic mode decomposition (DMD) is a data-decomposition technique that allows the extraction of dynamically relevant flow features from time-resolved experimental (or numerical) data. It is based on a sequence of snapshots from measurements that are subsequently processed by an iterative Krylov technique. The eigenvalues and eigenvectors of a low-dimensional representation of an approximate inter-snapshot map then produce flow information that describes the dynamic processes contained in the data sequence. This decomposition technique applies equally to particle-image velocimetry data and image-based flow visualizations and is demonstrated on data from a numerical simulation of a flame based on a variable-density jet and on experimental data from a laminar axisymmetric water jet. In both cases, the dominant frequencies are detected and the associated spatial structures are identified.
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页码:1123 / 1130
页数:7
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