AES for multiscale localization modeling in granular media

Abstract

This work presents a multiscale strong discontinuity approach to tackle key challenges in modeling localization behavior in granular media: accommodation of discontinuities in the kinematic fields, and direct linkage to the underlying grain-scale information. Assumed enhanced strain (AES) concepts are borrowed to enhance elements for post-localization analysis, but are reformulated within a recently-proposed hierarchical multiscale computational framework. Unlike classical AES methods, where material properties are usually constants or assumed to evolve with some arbitrary phenomenological laws, this framework provides a bridge to extract evolutions of key material parameters, such as friction and dilatancy, based on grain scale computational or experimental data. More importantly, the phenomenological softening modulus typically used in AES methods is no longer required. Numerical examples of plane strain compression tests are presented to illustrate the applicability of this method and to analyze its numerical performance.

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