A Lagrangian–Eulerian hybrid framework for identification of cluster topology and breakup in gas–solid flows

Abstract Traditional cluster identification via Eulerian thresholding often fragments connected structures and fails to capture transport dynamics. We propose a Lagrangian–Eulerian hybrid framework based on Finite‐Time Lyapunov Exponent (FTLE) analysis to identify cluster topology and predict breakup. Backward FTLE ridges serve as the attracting backbone to recover dynamically connected structures, providing more robust connectivity and stable statistics than scalar thresholding. Compared with conventional Eulerian thresholding, the proposed framework better preserves finite‐time cluster connectivity and reduces sensitivity to local concentration fluctuations that may artificially fragment dense structures. Meanwhile, forward FTLE ridges identify regions prone to necking, offering an advance indication of cluster rupture. By redefining mesoscale clusters as dynamically connected transport structures rather than mere density peaks, this framework provides a physically meaningful basis for analyzing cluster evolution in gas–solid flows.