This paper presents an objective comparison between two recent constitutive models employing the concept of the hardening memory surface to predict the high cyclic loading behaviour of granular soils. The hardening memory surface is applied to the well-known Severn-Trent sand and the SANINSAND04 constitutive models. While the addition of the new model surface (the memory surface) leads to enhanced model capabilities, slight differences in the implementation can lead to different model performances and simulations. This paper describes the differences between the two implementations and highlights the most relevant modelling ingredi-ents to predict particular features of the cyclic soil behaviour. This paper will help the reader in selecting the most suitable model and related ingredients for a particular geotechnical application.@en

The modelling and simulation of cyclic sand ratcheting is tackled by means of a plasticity model formulated within the well-known critical state, bounding surface SANISAND framework. For this purpose, a third locus – termed the ‘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 cyclic loading by oedometer test. 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.@en

Earthquake-induced build-up of pore water pressure may be responsible for reduced soil capacity, while the accumulation of shear strains may lead to a violation of serviceability limits. Predicting accurately the soil cyclic behaviour in relation to seismic numerical simulations is still a challenging topic in many respects. Efforts are required to improve several technical aspects, including the development of a reliable and complete constitutive model. This paper reports recent developments after the work of Liu et al. (2018a), and particularly about the performance of a new SANISAND formulation incorporating the memory surface concept (Corti et al., 2016). The performance of the model in terms of strain accumulation and pore pressure build-up is validated against high-quality laboratory test results. A modified dilatancy relationship is given to reproduce within the proposed framework proper cyclic mobility response. The effects of preliminary drained cyclic preloading on soil liquefaction resistance are also studied.@en

Predicting accurately the response of sands to cyclic loads is as relevant as still challenging when many loading cycles are involved, for instance, in relation to offshore or railway geo-engineering applications. Despite the remarkable achievements in the field of soil constitutive modelling, most existing models do not yet capture satisfactorily strain accumulation under high-cyclic drained loading, nor the the build-up of pore pressures under high-cyclic undrained conditions. Recently, bounding surface plasticity enhanced with the concept of memory surface has proven promising to improve sand ratcheting simulations under drained loading conditions (Corti et al. 2016). This paper presents a new model built by combining the memory surface conceptby Corti et al. (2016) with the well-known SANISAND04 bounding surface formulation proposed by Dafalias and Manzari (2004). The outcome is a new sand model that can reproduce phenomenologically the fabric evolution  mechanisms governing strain accumulation under long-lasting loading histories (here up to 104 loading cycles). In undrained test simulations, the model proves capable of correctly capturing the rate of pore pressure accumulation, preventing precocious occurrence of cyclic liquefaction.@en