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Fluid-immersed granular avalanche: Coupled computational fluid dynamics and discrete element method modeling, experimental validation, and internal flow characterization

物理 离散元法 机械 流体力学 计算流体力学 流量(数学) 动力学(音乐) 颗粒流 两相流 经典力学 声学
作者
Cheng-Chuan Lin,Wei Lee,Yun-Chi Chung,Shibo Kuang
出处
期刊:Physics of Fluids [American Institute of Physics]
卷期号:37 (9)
标识
DOI:10.1063/5.0287194
摘要

Developing a comprehensive understanding of fluid-immersed granular avalanches through laboratory-scale models is crucial for advancing research on submarine landslides. The unresolved CFD–DEM (computational fluid dynamics–discrete element method) approach has emerged as a promising numerical technique for simulating two-phase particulate flow systems. However, its predictive capability still requires rigorous validation. To address this, an experimental setup was developed to investigate the avalanching behavior of aluminum oxide beads within a narrow, water-filled chute, with the aim of validating the unresolved CFD–DEM model. The study systematically examined the effects of fluid grid resolution, drag force models, virtual mass force models, and their combinations. Among these, the combination of the Di Felice drag model and Paladino's virtual mass model yielded the best agreement with experimental observations—particularly in terms of velocity profiles, flow rates, and surface evolution of the granular column during avalanching. The validated CFD–DEM model further enabled detailed analysis of the internal flow dynamics of submerged granular columns. A power-law relationship was established between the rotation index and the scaled slip velocity, applicable to both the boundary layer and the interior of the flow. This correlation reveals a robust, flow-independent coupling between particle rotational and translational motions, highlighting the fundamental role of particle rotation in granular rheology. Moreover, it introduces a physically grounded scaling law that improves the predictive accuracy of existing friction-based rheological models. In summary, the validation and findings presented in this study provide a solid foundation for advancing unresolved CFD–DEM modeling of immersed granular flows.
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