(647d) A Structural Model of Sub-Grid Drift Velocity for Fluidized Gas-Particle Flows | AIChE

(647d) A Structural Model of Sub-Grid Drift Velocity for Fluidized Gas-Particle Flows


Chen, X., Xi'an Jiaotong University
Zhou, Q., Xi'an Jiaotong University
The drift velocity, defined as the correlation between the local fluid velocity and the local solid volume fraction, is a sub-grid quantity representing the local inhomogeneity of the meso-scale structure for fluidized gas-particle flows. It is shown that the drift velocity correlates well with the filtered drag force through analysis of numerous numerical results. However, the drift velocity is not available in coarse-grid simulations and a closure is required. In analogy to the modelling of the sub-grid scale (SGS) scalar flux in single-phase turbulent flows, several models for the drift velocity have been developed in the literature. This work aims to propose a new structural model for the drift velocity. This model considers the effect of the adjusted slip velocity, the summation of slip velocity and drift velocity, at scales above the filter size Δ. Denoting the scale larger than the filter size as γΔ, it is found that the magnitude of the drift velocity at the scale of ∆ decreases with the increase of the ratio between the adjusted slip velocity and the slip velocity at the scale of γΔ. The database used is generated through fully resolved two-fluid model (TFM) simulations in a 3D periodic fluidized system with Geldart A particles in different volume fractions. The TFM results are filtered by volume averaging and used to construct the closure of drift velocity. Furthermore, a priori assessment of the present model is presented.The comparisons between the present model and the models proposed by Parmentier et al. (AIChE J. 2017;63:3544–3562) and Ozel et al. (Int J Multiphase Flow. 2013;55:43–63) are made. Results show that this new structural model gives better performance than the previous models in terms of higher Pearson correlation coefficients as well as narrower probability distribution function of the relative error between the predicted filtered drag force and the exact filtered drag force directly obtained from the database. Besides, the new model requires less computational costs than previous models due to that the necessity of dynamic adjustment of the model constant is diminished. It is concluded that this work provides an accurate and efficient model to estimate the drift velocity in coarse grid simulation for the drag force modeling.