Multiscale modeling of granular dynamics on flowslide triggering and runout

Abstract A hierarchical multiscale modeling framework is proposed to simulate flowslide triggering and runout. It couples a system‐scale sliding‐consolidation model (SCM) resolving hydro‐mechanical feedbacks within a flowslide with a local‐scale solver based on the discrete element method (DEM) replicating the sand deformation response in the liquefied regime. This coupling allows for the simulation of a seamless transition from solid‐ to fluid‐like behavior following liquefaction, which is controlled by the grain‐scale dynamics. To investigate the role of grain‐scale interactions, the DEM simulations replace the constitutive model within the SCM framework, enabling the capture of the emergent rate‐dependent behavior of the sand during the inertial regime of motion. For this purpose, a novel algorithm is proposed to ensure the accurate passage of the strain rate from the global analysis to the local DEM solver under both quasi‐static (pre‐triggering) and dynamic (post‐triggering) regimes of motion. Our findings demonstrate that the specifics of the coupling algorithm do not bear significant consequences to the triggering analysis, in that the grain‐scale dynamics is negligible. By contrast, major differences between the results obtained with traditional algorithms and the proposed algorithm are found for the post‐triggering stage. Specifically, the existing algorithms suffer from loss of convergence and require proper numerical treatment to capture the micro‐inertial effects arising from the post‐liquefaction particle agitation responsible for viscous‐like effects that spontaneously regulate the flowslide velocity. These findings emphasize the important role of rate‐dependent feedback for the analysis of natural hazards involving granular materials, especially for post‐failure propagation analysis.