Stochastic Methods for Slip Detection in a Sheared Granular System

Bretz, Philip

Stochastic Methods for Slip Detection in a Sheared Granular System

dc.contributor.advisor	Kramar, Miroslav
dc.contributor.author	Bretz, Philip
dc.contributor.committeeMember	Petrov, Nikola
dc.contributor.committeeMember	Grigo, Alexander
dc.contributor.committeeMember	Diochnos, Dimitrios
dc.date.accessioned	2023-12-15T21:41:11Z
dc.date.available	2023-12-15T21:41:11Z
dc.date.issued	2023-12-15
dc.date.manuscript	2023-12
dc.description.abstract	We develop a flexible methodology for predicting slip events in a sheared granular system. The considered system consists of two-dimensional soft disks between two rigid horizontal walls, where the top wall is exposed to downward pressure and horizontal elastic shearing force, resulting in intermittent stick-slip regimes. The prediction methodology first uses topological data analysis to compute the persistent homology between successive force networks of the system and then quantifies the topological change by placing a metric between the respective persistence diagrams, resulting in a time series. Next, we construct a Bayesian stochastic state space model, which describes the behavior of the time series during the stick regime. We also create similar models for the stick regime behavior of the time series of more traditional measures on the granular system. A model identifies departure from the stick regime by detecting when the predictive error exceeds a specified threshold. The resulting detections demonstrate that this approach can detect the slip events in advance, with further investigation revealing a rough sequence of events. First, a local change appears in the force network and either dissipates or spreads globally. Next, the global change either triggers a slip event or a much smaller ‘micro-slip,’ depending on if its magnitude exceeds a critical threshold.	en_US
dc.identifier.uri	https://hdl.handle.net/11244/340056
dc.language	en_US	en_US
dc.rights	Attribution 4.0 International	*
dc.rights.uri	http://creativecommons.org/licenses/by/4.0/	*
dc.subject	Bayesian Statistics	en_US
dc.subject	Stochastic Processes	en_US
dc.subject	Topological Data Analysis	en_US
dc.subject	Granular Media	en_US
dc.thesis.degree	Ph.D.	en_US
dc.title	Stochastic Methods for Slip Detection in a Sheared Granular System	en_US
ou.group	Dodge Family College of Arts and Sciences::Department of Mathematics	en_US
shareok.orcid	0000-0002-8072-7108	en_US