Bubble hydrodynamic characterization in gas–solid fluidized beds via marching squares method based on TFM

Accurate characterization of bubble hydrodynamics is critical for the optimization and scale-up of gas–solid fluidized bed reactors, yet existing bubble identification methods suffer from inherent limitations, including interpolation errors from image conversion, grid resolution dependency, and inadequate handling of bubble coalescence and breakup events. In this work, a fully automated, high-fidelity bubble recognition and hydrodynamic characterization framework is developed based on the Marching Squares (MS) method, coupled with a two-fluid model (TFM) for 2D gas–solid fluidized bed simulation. This framework realizes direct in-situ processing of grid node void fraction data without image conversion, with an optimized tracking algorithm for bubble topological changes, and systematic calculation of full-spectrum bubble hydrodynamic parameters. The calculated bubble size, rise velocity and shape parameters show good agreement with classical empirical correlations. Bubble equivalent diameter and vertical velocity increase with bed height, while horizontal velocity has no significant correlation with bubble size, and bubbles are predominantly near-spherical with an aspect ratio peak at ∼2. This work provides a robust tool for bubble dynamics research and technical support for fluidized bed reactor optimization.