论文标题
在剪切颗粒系统中进行滑移预测的随机方法
Stochastic methods for slip prediction in a sheared granular system
论文作者
论文摘要
我们考虑了一个剪切的颗粒系统,通过离散元素模拟经历了粘液滑移类型的间歇性动力学。所考虑的设置由夹在固体壁之间的二维软摩擦颗粒组成,其中之一暴露于剪切力。使用应用于描述系统的各种度量的随机状态空间模型检测到滑移事件。我们表明,描述粒子之间力量的措施提供了对即将到来的滑移事件的早期检测,而不是仅基于壁移动的措施。通过比较从所考虑的度量获得的检测时间,我们观察到典型的滑移事件始于力网络中的局部变化。但是,某些局部变化不会在力网络上遍布全球。对于成为全球的变化,我们发现其大小的急剧临界价值。如果全局变化的大小超过临界值,则会触发滑移事件;如果没有,那么会弱的微滑。通过制定描述其静态和动态特性的清晰,精确的度量,使力网络中的变化量化成为可能。
We consider a sheared granular system experiencing intermittent dynamics of stick-slip type via discrete element simulations. The considered setup consists of a two-dimensional system of soft frictional particles sandwiched between solid walls, one of which is exposed to a shearing force. The slip events are detected using stochastic state space models applied to various measures describing the system. We show that the measures describing the forces between the particles provide earlier detection of an upcoming slip event than the measures based solely on the wall movement. By comparing the detection times obtained from the considered measures, we observe that a typical slip event starts with a local change in the force network. However, some local changes do not spread globally over the force network. For the changes that become global, we find a sharp critical value for their size. If the size of a global change exceeds the critical value, then it triggers a slip event; if it does not, then a much weaker micro-slip follows. Quantification of the changes in the force network is made possible by formulating clear and precise measures describing their static and dynamic properties.