Mesoscale drag modeling: a critical review

In Silico CFD Investigation of the Granulation Hydrodynamics in Rotating Drum: Process Sensitivity to the Operating Parameters and Drag Models

Computational fluid dynamics (CFD) have been extensively used to simulate the hydrodynamics of multiphase flows (MPFs) in rotating machinery. In the presence of a granular dense phase, the Kinetic Theory of Granular Flow (KTGF) is usually coupled to Eulerian multi-fluid models to obtain tractable computational fluid models. In the present work, the hydrodynamic behavior of a three dimensional, industrial scale, and rotating drum granulator with gas–solid flows is assessed using the Eulerian–Eulerian approach coupled with the k-ε standard turbulence model. A Eulerian–Eulerian Two-Fluid Model (TFM) is used with the KTGF model for the granular phase. The sensitivities to different operating parameters, including the rotational speed (8, 16, and 24 rpm), inclination degree (3.57∘, 5.57∘, and 7.57∘), and degree of filling (20%, 30%, and 40%) are studied. Moreover, the impact of the drag model on the simulation accuracy is investigated. The flow behavior, regime transitions, and particle distribution are numerically evaluated, while varying the operating conditions and the drag models. The rotational speed and filling degree appear to have greater influences on the granulation effectiveness than on the inclination degree. Three drag models are retained in our analysis. Both the Gidaspow and Wen and Yu models successfully predict the two-phase flow in comparison to the Syamlal and O’Brien model, which seems to underestimate the hydrodynamics of the flow in both its axial and radial distributions (a fill level less than 35%). The methodology followed in the current work lays the first stone for the optimization of the phosphates fertilizer wet-granulation process within an industrial installation.

Multilevel Mesoscale Complexities in Mesoregimes: Challenges in Chemical and Biochemical Engineering

This review discusses the complex behaviors in diverse chemical and biochemical systems to elucidate their commonalities and thus help develop a mesoscience methodology to address the complexities in even broader topics. This could possibly build a new scientific paradigm for different disciplines and could meanwhile provide effective tools to tackle the big challenges in various fields, thus paving a path toward combining the paradigm shift in science with the breakthrough in technique developments. Starting with our relatively fruitful understanding of chemical systems, the discussion focuses on the relatively pristine but very intriguing biochemical systems. It is recognized that diverse complexities are multilevel in nature, with each level being multiscale and the complexity emerging always at mesoscales in mesoregimes. Relevant advances in theoretical understandings and mathematical tools are summarized as well based on case studies, and the convergence between physics and mathematics is highlighted. Expected final online publication date for the Annual Review of Chemical and Biomolecular Engineering, Volume 13 is October 2022. Please see http://www.annualreviews.org/page/journal/pubdates for revised estimates.

Coupling Euler-Euler and Microkinetic Modeling for the Simulation of Fluidized Bed Reactors: an Application to the Oxidative Coupling of Methane

We propose a numerical methodology to combine detailed microkinetic modeling and Eulerian-Eulerian methods for the simulation of industrial fluidized bed reactors. An operator splitting-based approach has been applied to solve the detailed kinetics coupled with the solution of multiphase gas-solid flows. Lab and industrial reactor configurations are simulated to assess the capability and the accuracy of the method by using the oxidative coupling of methane as a showcase. A good agreement with lab-scale experimental data (deviations below 10%) is obtained. Moreover, in this specific case, the proposed framework provides a 4-fold reduction of the computational cost required to reach the steady-state when compared to the approach of linearizing the chemical source term. As a whole, the work paves the way to the incorporation of detailed kinetics in the simulation of industrial fluidized reactors.