Visualization of Fluid Structure by Dynamic Mode Decomposition

Abstract

Since fluid phenomena have complex spatio-temporal behaviors, it is still not easy to find physically important features in the fluid data obtained from experiments and numerical analyses. Dynamic mode decomposition (DMD), which is introduced in this paper, is one of the data analysis methods that have been actively studied in recent years, and can extract spatial and temporal features inherent in fluid data. DMD has the advantage of being applicable to a wide variety of data because it does not assume any governing equations. In this paper, some examples of the research on dynamic mode decomposition are briefly introduced.