Abstract
•The manuscript presents method to characterize solid particle clusters using digital image analysis and Eulerian CFD.•Cluster size increases with the increase in particle dimeter as well as with the increase in initial solid concentration.•1% concentration shows single peak while 5 & 10% show bimodal cluster distribution.
Presence of meso-scale structures such as particle clusters and gas bubbles is ubiquitous in fluidized beds frequently used in pyrolysis of coal and biomass. In recent years, bubbling and circulating fluidized beds have become popular for highly efficient conversion of carbonaceous feedstock into pyrolysis products. The characterization and study of hydrodynamics inside these reactors can provide an insight into the mechanisms controlling the performance of these reactors. Among others, cluster size distribution and mean cluster size are the key parameters defining the hydrodynamics of these reactors. In the current work, Digital Image Analysis (DIA) was applied to computationally obtained instantaneous snapshots during the CFD simulations of gas-solid flows. Transient two fluid modeling (TFM) was applied to three different gas-solid systems in periodic domains with different particulate systems keeping same grid size. The dimensionless axial cluster size was defined in line with literature. The cluster sizes and their distributions are obtained and compared with the available empirical correlations present in the literature based on experimental observations having similar range of operating conditions as well as system characteristics. It is found that the results of current approach agree well with the available data. The methodology followed in current work presents an alternative to expensive experimentation for development of a universal cluster size correlation.