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Published November 2020 | public
Journal Article

Investigating the Incremental Behavior of Granular Materials with the Level-Set Discrete Element Method


A computational framework is presented for high-fidelity virtual (in silico) experiments on granular materials. By building on i) accurate mathematical representation of particle morphology and contact interaction, ii) full control of the initial state of the assembly, and iii) discrete element simulation of arbitrary stress paths, the proposed framework overcomes important limitations associated with conventional experiments and simulations. The framework is utilized to investigate the incremental response of sand through stress probing experiments, focusing on key aspects such as elasticity and reversibility, yielding and plastic flow, as well as hardening and fabric evolution. It is shown that reversible strain envelopes are contained within elastic envelopes during axisymmetric loading, the yield locus follows approximately the Lade-Duncan criterion, and the plastic flow rule exhibits complex nonassociativity and minor irregularity. Hardening processes are delineated by examining the stored plastic work and the fabric evolution in the strong and weak networks. Special attention is given to isolating in turn the effect of particle shape and interparticle friction on the macroscopic response. Interestingly, idealization of particle shape preserves qualitatively most aspects of material behavior, but proves quantitatively inadequate especially in anisotropic stress states. The results point to the importance of accurately resolving particle-scale interactions, that allows macroscopic behavior to emerge free from spurious micromechanical artifacts present in an idealized setting.

Additional Information

© 2020 Published by Elsevier Ltd. Received 26 April 2020, Revised 6 July 2020, Accepted 30 July 2020, Available online 8 August 2020. The authors would like to acknowledge the detailed analysis of this work by the two anonymous reviewers, which has contributed to its substantial improvement. Their feedback is gratefully appreciated. The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper.

Additional details

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October 20, 2023