1 research outputs found
Stochastic methods for slip prediction in a sheared granular system
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.Comment: 14 pages, 13 figure