ON AUGMENTED SPATIO-TEMPORAL DYNAMIC MODE DECOMPOSITION

Dynamic mode decomposition (DMD) is a data-driven modeling technique suitable to analyze flow structures in numerical and experimental data. It is widely used to extract temporal information about coherent structures from data. In its standard form, however, it cannot simultaneously extract information on temporal and spatial development, such as wave number and spatial growth rate, which are essential in fully developed flows. Spatio-temporal dynamic mode decomposition (STDMD) is an extension of DMD designed to handle spatio-temporal datasets. The framework is extended to analyze data that varies both spatially and temporally. In this paper we introduce an augmented modification of the STDMD method. It consists of applying delay-embedded coordinates to STDMD sequentially, in time and space. Using this method, dominant frequencies, wavenumbers, and their harmonics can be accurately calculated for complex flows. With different illustrative examples, we demonstrate the applicability of the introduced technique.