物理
级配
粒子(生态学)
粒径
沉积沉积环境
机械
流量(数学)
粒状材料
包络线(雷达)
强度(物理)
地质学
质点速度
流速
磁层粒子运动
运动学
粒度分布
信号(编程语言)
泥石流
粒度
粒度
动力学(音乐)
流体力学
岩土工程
作者
Ke Zhang,Zhende Sui,Kai Zhang,Guowei Ma
摘要
Rock avalanches are highly destructive geological hazards characterized by complex dynamic behaviors, and their granular flow processes are strongly influenced by particle size distribution. To reveal the effects of particle size non-uniformity on the kinematic, depositional, and seismic characteristics of granular flows, a controllable granular flow collapse simulation system is designed. Five gradation conditions are constructed by varying the particle size non-uniformity coefficient (Cu), and the particle motion is quantitatively analyzed using particle image velocimetry, multi-view three-dimensional reconstruction, and seismic signal monitoring techniques. The results show that Cu is a key factor controlling the dynamic evolution of granular flows. As Cu increases, the maximum mean velocity (Vmax), runout distance (R), and both deposit length (L) and width (D) increase significantly, indicating that particle size non-uniformity enhances flow mobility and energy transfer efficiency. In terms of depositional morphology, the deposits evolve from a typical fan-shaped structure to a transitional pattern and finally to a “W”-shaped double-peaked structure with increasing Cu. Seismic signal analysis reveals that the peak ground acceleration, mean envelope value, and Arias intensity all increase markedly with higher Cu, while the spectral characteristics of the signals shift from high-frequency dominance to multi-frequency coupling, indicating that particle size non-uniformity intensifies inter-particle collisions and frictional interactions. Correlation analysis further shows that the seismic signal parameters are significantly and positively correlated with the kinematic parameters (R, Vmax) and depositional parameters (L, D), demonstrating that seismic signals effectively reflect the flow intensity and depositional characteristics of granular flows.
科研通智能强力驱动
Strongly Powered by AbleSci AI