4.6 Article

Effects of Crushing Characteristics on Rheological Characteristics of Particle Systems

Journal

WATER
Volume 14, Issue 4, Pages -

Publisher

MDPI
DOI: 10.3390/w14040532

Keywords

ring-shear test; stress fluctuation; particle breakage

Funding

  1. National Natural Science Foundation of China [41831291]

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The large-deformation shear flow of a particle system exhibits random characteristics, making accurate modeling difficult. This study conducted ring-shear experiments on common engineering materials to quantify the effect of dynamic crushing on the instability of shear flow. The fluctuation characteristics of the stress ratio are negatively correlated with the shear rate. The research on the fluctuation characteristics of particle systems will help in developing a dynamic model for landslide systems, improving prediction and prevention of landslide disasters.
A particle system's large-deformation shear flow exhibits obvious random characteristics, making accurate modeling of the particle system difficult. Particle systems, which are frequently used in engineering, are prone to breakage, which introduces additional uncertainty into the system. The purpose of this study was to conduct ring-shear experiments on a variety of common engineering materials in order to quantify the effect of the dynamic crushing process of the particle system on the instability of shear flow. Different shear fracture characteristics may result in a change in the volume trend of the system, from dilatancy to shrinkage. While the mean value of the crushable system's stress ratio does not increase with shear rate, the stress ratio's fluctuation characteristic parameters are negatively correlated with shear rate. As particles become more easily sheared, the initial value of the stress ratio fluctuation increases. The effect of shear rate on the fluctuation in the system stress ratio is determined indirectly by the degree of system fragmentation. The study of the particle system's fluctuation characteristics will aid in developing a stochastic dynamic model for the landslide system in the future, allowing for improved prediction and prevention of landslide disasters.

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