CFD simulation of a fluidized bed using the EMMS approach for the gas-solid drag force

On the drag force closures for multiphase flow modeling

Drag force models are one of the most important factors that can affect TFM and CFD-DEM simulation results of two-phase systems. This article investigates the accuracies, implementation issues and limitations of the majority of the drag models for spherical, non-spherical and systems with size distribution and evaluates their performance in various simulations. Around 1888 data points were collected from 19 different sources to evaluate the drag force closures on mono-dispersed spherical particles. The Reynolds number and fluid volume fraction ranges were between 0.01 and 10,000 and between 0.33 and 1, respectively. In addition, 776 data points were collected from seven different sources to evaluate the drag force closures on poly-dispersed spherical particles. The Reynolds numbers were between 0.01 and 500, fluid volume fractions between 0.33 and 0.9, and diameter ratios up to 10. A comprehensive discussion on the accuracy and application of these models is given in the article.

From Multiscale to Mesoscience: Addressing Mesoscales in Mesoregimes of Different Levels

This review covers three decades of research on mesoscale phenomena in chemical engineering, from the energy minimization multiscale (EMMS) model specific for gas-solid fluidization to a general principle of compromise in competition between dominant mechanisms, leading to the proposed concept of mesoscience. First, the concept of mesoscales is reviewed with respect to their commonality, diversity, and misunderstanding in different fields. Then, the evolution from the EMMS model to the EMMS principle common to all mesoscales is described to show the rationale of mesoscience referring to both mesoscales and mesoregimes. Finally, the potential universality of mesoscience and its importance, particularly to enable virtual process engineering (VPE) by realizing the consistency of logic and structure between the problem, the model, the software, and the computer, are discussed. The review concludes by illustrating possible case studies to collect more evidence and a potential framework for mesoscience.