A gas pressure gradient-dependent subgrid drift velocity model for drag prediction in fluidized gas-particle flows

Due to the linear correlation between the subgrid drift velocity and the filtered drag force, modeling the drift velocity would be an alternative way to obtain the filtered drag force for coarse-grid simulations. This work aims to improve the predictability of models for the drift velocity using a new effective marker, the filtered gas pressure gradient, which is identified by momentum balance analysis. New models are constructed based on conditional averaging of the results obtained from fine-grid two-fluid model simulations of three-dimensional unbounded fluidized systems. A priori assessment is presented with the comparison between the proposed models and the best available Smagorinsky-type model with dynamic adjustment technique proposed in the literature. Results show that the proposed models give satisfactory performance. More important, the proposed models are demonstrated to have a better adaptability for cases under various physical conditions than the Smagorinsky-type model.