Memory in three-dimensional cyclically driven granular material.

Phys Rev E

Institute for Physical Science and Technology, University of Maryland, College Park, Maryland 20742-2431, USA.

Published: June 2021

We perform experimental and numerical studies of a granular system under cyclic compression to investigate reversibility and memory effects. We focus on the quasistatic forcing of dense systems, which is most relevant to a wide range of geophysical, industrial, and astrophysical problems. We find that soft-sphere simulations with proper stiffness and friction quantitatively reproduce both the translational and rotational displacements of the grains. We then utilize these simulations to demonstrate that such systems are capable of storing the history of previous compressions. While both mean translational and rotational displacements encode such memory, the response is fundamentally different for translations compared to rotations. For translational displacements, this memory of prior forcing depends on the coefficient of static interparticle friction, but rotational memory is not altered by the level of friction.

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http://dx.doi.org/10.1103/PhysRevE.103.062906DOI Listing

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