Multiscale framework for behavior prediction in granular media

In this work, a predictive multiscale framework for modeling the behavior of granular materials is presented. The method is particularly attractive due to its simplicity and ability to exploit the existing finite element and computational inelasticity technologies. Furthermore, this semi-concurrent multiscale method extracts two key material parameters from the granular structure: dilatancy and frictional resistance. The evolution of these material parameters is upscaled into classical two- and three-invariant plasticity models, effectively bypassing phenomenological hardening laws. The predictiveness of the method is clearly demonstrated by comparing its performance with experimental results and direct numerical simulations under homogeneous and inhomogeneous conditions. The high-quality predictions obtained using the multiscale method highlight its potential to unravel complex material behavior where hitherto phenomenological models have failed.