(206g) Multiscale Computational Fluid Dynamics Method for Slug Flow Reactor Simulation

Millifluidic slug-flow reactors recently have been attracting attention for the manufacturing of micron-sized particles. However, simulation methods for predicting the physicochemical phenomena inside the slug-flow reactor have been lacking. Microparticle formed within slugs spontaneously formed in gas-liquid multi-phase flows induces gas-liquid-solid three-phase flows that interact to result in the final particle size distribution at the outlet of the reactor. A multi-scale simulation method that can predict three-phase flows and the resulting particle size distribution in slug-flow reactors is desired, for use in process design and control.

This work introduces a MultiPhase Particle-In-Cell model coupled with Volume of Fluid and Population Balance Equation (MP-PIC-VPBE), which is an upgraded version of MP-PIC-PBE [1, 2]. The MP-PIC-VPBE method predicts the slug flow formation in the gas-liquid phase based on the VOF method and simultaneously calculates the particulate flow pattern and particle size change in the liquid-solid phase using Lagrangian parcels combined with PBE. In addition, the energy equation, species equation, and equation of state are implemented to accurately predict the effects of temperature, concentration, and density of the gas-liquid phase on PBE kernels about the particle size distribution.

In this study, the newly developed method is used to simulate the crystallization of L-asparagine monohydrate (LAM) in a slug-flow reactor and this model is validated through direct comparison with experimental data. An optical microscope combined with a digital camera and a transparent tubular reactor is used to observe slug flow and particulate flow patterns inside the reactor, in a configuration similar to past work [3]. Also, the particle distribution of the end product is measured using a high-magnification stereo microscope and compared with the simulation results. The MP-PIC-VPBE is able to simulate effects of changing process operations that are not predicted well by simpler models.

[1] S. H. Kim, Richard D. Braatz, and Jay H. Lee, “Multi-scale fluid dynamics simulation based on MP-PIC-PBE method for PMMA suspension polymerization,” Computers and Chemical Engineering, 152, 107391, 2021.

[2] S. H. Kim, Richard D. Braatz, and Jay H. Lee, “Multi-phase particle-in-cell coupled with population balance equation (MP-PIC-PBE) method for multiscale computational fluid dynamics simulation,” Computers and Chemical Engineering, 134, 106686, 2020.

[3] Mo Jiang and Richard D. Braatz, “Low-cost noninvasive real-time imaging for tubular continuous-flow crystallization,” Chemical Engineering & Technology, 41(1), 143-148, 2018.