Data-driven identification of coherent structures in gas–solid system using proper orthogonal decomposition and dynamic mode decomposition

Abstract

Spatiotemporal coherent structures are critical in quantifying the hydrodynamics of dense gas–solid flows. In this study, two data-driven methods, proper orthogonal decomposition (POD) and dynamic mode decomposition (DMD), are applied to identify and characterize the dominant spatiotemporal coherent structures in a bubbling fluidized bed. It is found that (i) with the same number of modes (or coherent structures), POD captures more defined energy than DMD; (ii) the main coherent structure of POD is symmetric and confirms the existence of bubble-emulsion two-phase structure; (iii) the coherent structures with a frequency of 0 Hz in DMD analysis can construct the mean flow field more reasonably than POD; and (iv) POD reconstructs the transient flow fields more accurately with the same number of modes. This study offers insights into the coherent structures in gas–solid systems.