Bubbles in biomass fluidized bed gasifiers: A phenomenological probabilistic predictive model

Abstract

Bubble properties in fluidized beds including size, velocity, and path, vary randomly. This article proposes a new PPPM (Phenomenological Probabilistic Predictive Model) l, that allows one to establish a vrb-BAC prediction band, to describe bubble data, obtained in a lab scale biomass-sand fluidized bed, by using CREC Optiprobes. The PPPM, represents a significant improvement from an earlier Probabilistic Predictive Model (PPM) reported by Torres and de Lasa in 2021, with the new PPPM being based on a balance of forces including gravity, drag, buoyancy, and minimum fluidization excess velocity. The resulting PPPM bubble rise velocity (vrb) is obtained as a function of the bubble axial chord (BAC) and is specifically evaluated by studying bubbles in a high-density sand (above 2500 kg/m3) fluidized bed. The PPPM leads to a behavioral band showing a normal bubble frequency distribution that becomes increasingly skewed as the gas superficial velocity increases. The proposed PPPM is shown to be applicable to single bubbles in a sand bed at incipient fluidization and to multiple bubbles in a biomass-sand bubbling bed. The PPPM is validated in the present study, by comparing it against 46,000 bubbles, under different gas superficial velocities and biomass loadings. By using the PPPM, it is shown 91% of all bubbles studied fall within the PPPM prediction band. Given the demonstrated ability of the PPPM, it is anticipated that this model will significantly contribute to the development of large-scale multiphase biomass gasifier models.