journal article·2024-09

Collapse characteristics of binary granular columns considering inhomogeneous particle size distributions

Hao Sun, Jun‐Ze Jia, François Nicot, Xiao‐Xiao Wang, Li‐Shan Zhao

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Abstract

Abstract Debris avalanches and dry granular flows exhibit similar characteristics. In order to comprehend the fundamental mechanisms and improve the accuracy in predicting disasters such as landslides, debris flows, and rock avalanches, the collapse characteristics of a binary granular column are investigated through a three‐dimensional discrete element model. A novel approach is proposed by incorporating the concept of local granular velocity fluctuation and applying a cluster analysis method. Then, the flow mechanism of the binary granular column is analyzed, by considering the inhomogeneous particle size distribution. The research results show that: (1) The normalized final packing height of the granular column gradually increases when the content of coarse particles exceeds 20% and when the coarse‐fine particle size ratio increases. Conversely, the normalized run‐out distance of the granular column decreases gradually with the increase in coarse particle content and the coarse‐fine particle size ratio. (2) The particles with higher granular velocity fluctuations tend to move together and form clusters, demonstrating dynamical heterogeneity. As the coarse particle content and coarse‐fine particle size ratio increase, there is a greater tendency for particles to assemble into larger‐scale active clusters. This means that a larger number of particles exhibit collective behavior during the collapse process, resulting in increased resistance to shear deformation. Ultimately, this leads to a greater packing height and a reduced run‐out distance when observed from a macroscopic perspective.
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Research context

OpenAlex topics: Landslides and related hazards · Rock Mechanics and Modeling · Geotechnical Engineering and Analysis

SciVX discovery tags are terminology-based. OpenAlex topics are source-provided classifications.

Affiliations

Key Laboratory of Ministry of Education for Efficient Mining and Safety of Metal Mines University of Science and Technology Beijing Beijing China

School of Civil and Resource Engineering University of Science and Technology Beijing Beijing China

ISTerre Université Savoie Mont Blanc Le Bourget du Lac France

Funding

National Natural Science Foundation of China

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