Bubbles in Sand-Fluidized Bed Gasifiers: Bubble Motion under Inherent Conditional Randomness

Abstract

Fluidized biomass gasification can be employed for agricultural waste conversion, including the production of syngas and biochar. Syngas is a valuable, renewable, and clean energy source, while biochar is a good supplement for soil remineralization. Fluidized bed biomass gasifiers are strongly influenced in their performance by bubble flow dynamics. In 2023, Chemical Reactor Engineering Centre (CREC) researchers, at the University of Western Ontario, introduced a phenomenological probabilistic predictive model (PPPM), which takes into consideration bubble motion randomness, and it was established on the basis of both theoretical principles and experimental data. Computational particle fluid dynamics (CPFD), and in particular, a multiphase particle-in-cell (MP-PIC) model, are considered in the present study to predict bubble sizes, bubble velocities, and bed pressure drops. MP-PIC simulations, yielding bubble rising velocity (BRV) and bubble axial chord (BAC) data, based on more than a +80,000 bubble population were considered to confirm inherently constrained bubble randomness motion. Results show that even if there are unavoidable and random variations in local bed density, bubble motion, and bubble interactions, simulated bubbles consistently fall within MP-PIC behavioral bands. It is anticipated that the observed fluid dynamic probabilistic trends, as obtained with both the MP-PIC and the PPPM, could be used in the future to improve sand-fluidized bed drag correlations and the scale-up of lab-scale gasifiers for agricultural waste gasification while accounting for the unavoidable conditional inherent randomness in bubble motion.