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

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.