Modelling the cyclic ratcheting of sands through memory-enhanced bounding surface plasticity

Abstract

The modelling and simulation of cyclic sand ratcheting is tackled via a plasticity model formulated within the well-known critical state, bounding surface SANISAND framework. For this purpose, a third locustermed 'memory surface'-is cast into the constitutive formulation, so as to phenomenologically capture micro-mechanical, fabric-related processes directly relevant to the cyclic response. The predictive capability of the model under numerous loading cycles ('high-cyclic' loading) is explored with focus on drained loading conditions, and validated against experimental test results from the literature-including triaxial, simple shear and oedometer cyclic loading. The model proves capable of reproducing the transition from ratcheting to shakedown response, in combination with a single set of soil parameters for different initial, boundary and loading conditions. This work contributes to the analysis of soil-structure interaction under high-cyclic loading events, such as those induced by environmental and/or traffic loads.

Prediction of oedometer terminal densities through a memory-enhanced cyclic model for sand

“…Since the model is inherently unsuitable for monotonic oedometer loading, an iterative procedure was established to transit from an assumed initial void ratio e in to the target pre-cyclic value e 0 . This procedure enabled the pre-cyclic initialisation of all hardening variables, and to finally obtain µ 0ζ-β values in good agreement with those calibrated in Liu et al (2018a) for the quartz sand tested by Wichtmann (2005).…”

“…The memory locus is introduced to track fabric effects, and hence simulate realistic sand behaviour under high-cyclic loading. Compared to SANISAND04, Liu et al (2018a) introduced in the normalised π-plane a third circular locus, the memory surface ( Figure 1a), which evolves during soil straining so as to (i) modify its size/position in reflection of fabric changes, (ii) always enclose the yield surface, (iii) influence changes in sand stiffness and dilatancy. Most other ingredients of SANISAND04 were instead kept unaltered.…”

“…The memory-related parameter µ 0 links fabric effects to soil stiffness, with major influence on drained cyclic strain accumulation, or equivalently on the rate of pore pressure buildup under undrained conditions (Liu et al, 2018b). Relevant to predictive capability is also the presence of the pressuredependent term (p/p atm ) 0.5 term in Equation (2) (Corti et al, 2017;Liu et al, 2018a).…”

“…Evolution laws for the memory surface, namely for the memory back-stress α α α M and size m M , were inspired by experimental evidence (Liu et al, 2018a). As contractive soil behaviour promotes 'fabric reinforcement', stages of cyclic contraction were linked to an expansion of the memory surface (dm M > 0), and therefore to gradual stiffening through Equations (1)-(2).…”

“…Finally, the memory locus was also exploited to capture the higher contractancy exhibited by the sand when unloaded after dilative deformation -a phenomenon usually associated to 'fabric re-orientation' and modelled in SANISAND04 through the concept of 'fabric tensor'. Liu et al (2018a) proposed the following re-definition of SANISAND04's dilatancy coefficient (D):…”