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Peculiarities of Dynamic Slip Nucleation in a Thin Granular Layer

Authors
  • Ostapchuk, A. A.1, 2
  • Kocharyan, G. G.1
  • Morozova, K. G.1
  • Pavlov, D. V.1
  • Gridin, G. A.1, 3
  • 1 Sadovsky Institute of Geosphere Dynamics, Russian Academy of Sciences, Moscow, 119334, Russia , Moscow (Russia)
  • 2 Moscow Institute of Physics and Technology (State University), Dolgoprudnyi, 141701, Russia , Dolgoprudnyi (Russia)
  • 3 Faculty of Geology, Moscow State University, Moscow, 119991, Russia , Moscow (Russia)
Type
Published Article
Journal
Izvestiya, Physics of the Solid Earth
Publisher
Pleiades Publishing
Publication Date
Sep 01, 2021
Volume
57
Issue
5
Pages
659–670
Identifiers
DOI: 10.1134/S106935132105013X
Source
Springer Nature
Keywords
Disciplines
  • Article
License
Yellow

Abstract

Abstract—Granular media determine the dynamics of many natural systems including faults in the Earth’s crust. The paper addresses the laboratory study of shear deformation of a model fault simulated by a layer of granular material located between rock blocks. A model fault is a complex dynamic system characterized by the presence of bifurcations and fast and slow slips may take turn aperiodically during deformation. The sliding of the rock blocks is accompanied by the generation of acoustic emission pulses (AEs) which are identified based on the Akaike information criterion. The dynamics of AEs reflects the evolution of mechanical properties of the fault. In the flow of AEs, the subsets with different rise time/amplitude values (RA-values) and different scaling relations are identified. Applying the random forest machine learning algorithm to the analysis of AE catalogue demonstrates the possibility of determining the velocity of fault sliding and the time to both fast and slow slips. The nucleation of a certain slip mode is predetermined by the self-organization processes taking place in the central zone of a fault, and the characteristics of the AE reflect these processes. The proposed approach to the estimation of fault sliding parameters can be promising for the design of new methods for monitoring stressed massifs at mining.

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