A data-driven framework was used to predict the macroscopic mechanical behavior of dense packings of polydisperse granular materials. The discrete element method, DEM, was used to generate 92,378 sphere packings that covered many different kinds of particle size distributions, PSD, lying within 2 particle sizes. These packings were subjected to triaxial compression and the corresponding stress-strain curves were fitted to Duncan-Chang hyperbolic models. An artificial neural network (NN) scheme was able to anticipate the value of the model parameters for all these PSDs, with an accuracy similar to the precision of the experiment and even when the NN was trained with a few hundred DEM simulations. The estimations were indeed more accurate than those given by multiple linear regressions (MLR) between the model parameters and common geotechnical and statistical descriptors derived from the PSD. This was achieved in spite of the presence of noise in the training data. Although the results of this massive simulation are limited to specific systems, ways of packing and testing conditions, the NN revealed the existence of hidden correlations between PSD of the macroscopic mechanical behavior.

Second-order work analyses, based on elasto-plastic models, have been frequently carried out leading to the result that failure may occur the limit yield condition is encountered. In this article, second-order work investigations are carried out with barodesy regarding standard element tests and finite element applications. In barodesy, it was shown-like in hypoplasticity and elasto-plasticity-that second-order work may vanish at stress states inside the critical limit surface. For boundary value problems, an end-to-end shear band of vanishing second-order work marks situations, where failure is imminent.

Soil flow is involved in many earth surface processes such as debris flows and landslides. It is a very challenging task to model this large deformational phenomenon because of the extreme change in material configurations and properties when soil flows. Most of the existing models require a two-dimensional (2D) simplification of actual systems, which are however three-dimensional (3D). To overcome this issue, we develop a novel 3D particle finite element method (PFEM) for direct simulation of complex soil flows in 3D space. Our PFEM model implemented in a fully implicit solution framework based on a generalised Hellinger-Reissner variational principle permits the use of a large time step without compromising the numerical stability. A mixed quadratic-linear element is used to avoid volumetric locking issues and ensure computational accuracy. The correctness and robustness of our 3D PFEM formulation for modelling large deformational soil flow problems are demonstrated by a series of benchmarks against analytical or independent numerical solutions. Our model can serve as an effective tool to support the assessment of catastrophic soil slope failures and subsequent runout behaviours.

The intergranular strain concept (IGS) and intergranular strain anisotropy formulation (ISA) are state of the art extensions to describe small-strain effects. The main conceptional difference between ISA and IGS is the purely elastic strain range introduced by ISA. In addition, the ISA formulation used in this article includes an additional state variable in order to reduce accumulation effects for cyclic loading with a larger number of repetitive cycles. Barodesy is enhanced here with ISA to improve its small-strain predictions. The performance of this new model is compared with barodesy enhanced with IGS. It turned out that the small-strain extensions do not negatively influence predictions under monotonic loading. Differences between ISA and ISG are only remarkable for very small-strain cycles and even there they are negligible for certain parameter values.

The peak pressure of a granular debris flow at low Froude conditions can be calculated with knowledge of the stress anisotropy and the bulk density as well as the run-up height at impact. Based on a small-scale physical model, measurements of stress anisotropy and flow density values at impact are presented and applied to existing run-up prediction models, and further compared with back-calculated run-up coefficients from measured maximum impact pressures. For this purpose, we conducted 17 experiments with impact measurements and six experiments without impact measurements at Froude numbers, ranging from 0.84 to 2.41. Our results indicate that run-up heights are best reproduced by predictive models, either based on energy or mass and moment conservation, when anisotropic stress conditions, found in this study to range from 1.2 to 5.0, and bulk density variations due to impact, ranging in this study from 0.8 to 2.3, are considered. The influence of stress anisotropy and density variation on the run-up prediction differs, depending on the modelling approach. For the calculation of run-up heights based on the energy conservation concept, the influence of stress anisotropy becomes more significant with increasing Froude number, whereas for models based on mass and momentum conservation, bulk density variations have a greater influence on the estimation of the potential run-up.

Sustainable biopolymer additives offer a promising soil stabilisation methodology, with a strong potential to be tuned to soil's specific nature, allowing the tailoring of mechanical properties for a range of geotechnical applications. However, the biopolymer chemical characteristics driving soil mechanical property modifications have yet to be fully established. Within this study we employ a cross-scale approach, utilising the differing galactose:mannose (G:M) ratios of various Galactomannan biopolymers (Guar Gum G:M 1:2, Locust Bean Gum G:M 1:4, Cassia Gum G:M 1:5) to investigate the effect of microscale chemical functionality upon macroscale soil mechanical properties. Molecular weight effects are also investigated, utilising Carboxy Methyl Cellulose (CMC). Soil systems comprising of SiO (100%) (SiO) and a Mine Tailing (MT) exemplar composed of SiO (90%) + FeO (10%) (SiO + Fe) are investigated. The critical importance of biopolymer additive chemical functionality for the resultant soil mechanical properties, is demonstrated.For Galactomannan G:M 1:5 stabilised soils the 'high-affinity, high-strength', mannose-Fe interactions at the microscale (confirmed by mineral binding characterisation) are attributed to the 297% increase in the SiO + Fe systems Unconfined Compressive Strength (UCS), relative to SiO only. Conversely for SiO Galactomannan-stabilised soils, when increasing the G:M ratio from 1:2 to 1:5, a 85% reduction in UCS is observed, attributed to mannose's inability to interact with SiO. UCS variations of up to a factor of 12 were observed across the biopolymer-soil mixes studied, in line with theoretically and experimentally expected values, due to the differences in the G:M ratios. The limited impact of molecular weight upon soil strength properties is also shown in CMC-stabilised soils. When considering a soil's stiffness and energy absorbance, the importance of biopolymer-biopolymer interaction and is discussed, further deciphering biopolymer characteristics driving soil property modifications. This study highlights the importance of biopolymer chemistry for biopolymer stabilisation studies, illustrating the use of simple low-cost, accessible chemistry-based instrumental tools and outlining key design principles for the tailoring of biopolymer-soil composites for specific geotechnical applications.

This paper introduces a new hypoplastic model characterized by a simple and elegant formulation. It requires only 7 material parameters to depict salient mechanical behaviors of granular materials. The numerical implementation employs an explicit integration method, enhanced by a best-fit stress correction algorithm in a smoothed particle hydrodynamics code. The performance of this model in capturing soil behavior across a range of scenarios is demonstrated by conducting various numerical tests, including triaxial and simple shear at low strain rates, as well as granular collapse, rigid penetration and landslide process at high strain rates.

We propose a constitutive model for both the solid-like and fluid-like behavior of granular materials by decomposing the stress tensor into quasi-static and collisional components. A hypoplastic model is adopted for the solid-like behavior in the quasi-static regime, while the viscous and dilatant behavior in the fluid-like regime is represented by a modified rheology model. This model effectively captures the transition between solid-like and fluid-like flows. Performance and validation of the proposed model are demonstrated through numerical simulations of element tests.

Constitutive models that are able to accurately predict cyclic soil behaviour are crucial for finite element design of offshore foundation or railway embankments. Basic hypoplastic models introduce the history of loading in state variables such as the stress and void ratio and are therefore incapable of describing small-strain stiffness and cyclic loading. In this work, clay hypoplasticity is extended with a modified intergranular strain proposed by Duque et al. [3]. The new model is compared to the one coupled previously with ISA based on unconventional as well as complex cyclic loading paths. Abilities and limitations of the models are addressed: (i) showing that both models predict a reduction in strain accumulation with an increasing number of cycles. (ii) For both models pronounced over- and undershooting effects can occur for certain cyclic loading paths and certain parameters. Despite the consensus in the literature, the results show that a yield surface in the (intergranular) strain space is not sufficient to ban these effects. Furthermore, the models' predictive capabilities are verified with simulations of monotonic and cyclic tests of Lower Rhine clay.

Liquefaction can have devastating consequences by causing increased mobility of debris flows, tailings dam breaches, and settlement following seismic shaking. Observations on the consolidation behaviour of liquefied soils in 1-g or centrifuge shake table tests have permitted significant advancements in analytical and numerical methods to predict the rate and magnitude of consolidation settlement. However, advanced consolidation models introduce material parameters which are currently difficult to define quickly and at low cost. The objective of this paper is to demonstrate the development of a simple, low-cost test that can be used to quickly estimate the spatially and temporally varying coefficient of consolidation, which controls post-liquefaction settlements. Using the proposed simple setup, experiments were conducted on four uniformly graded sands of varying grain size and on one well-graded mixture. A range of analytical and numerical approaches from literature were assessed for their ability to back-analyse the observed pore pressure dissipation and settlement. Estimated values for the coefficient of consolidation were comparable between models and estimates of surface settlement matched well the experimental results. The simplicity of the proposed test combined with its low-cost and mobile nature, raise significant possibilities for quick estimations of the evolution of the coefficient of consolidation post-liquefaction.

Three-dimensional and spatial variability effects on slope failure processes are investigated for an idealised slope stability problem with the random material point method (RMPM). A 45 degree slope is brought to failure by either its own weight or by a combination of its own weight and an additional surface load applied at the crest. The ultimate failure load and potential failure processes are studied for various (heterogeneous) material strength profiles. In 3D, failures tend to spread sideways and backwards. For the slope geometry considered, the resistance to initial and secondary failures in 3D simulations tends to be higher than in 2D simulations, probably due to the additional resistance from the ends of the failure surfaces. The failure behaviour changes when a depth trend in the material strength is introduced. A depth trend in the material strength triggers a flow-like failure process, instead of distinct (approximately) circular failure surfaces which are encountered in a material without a depth trend. The flow-like behaviour causes an expansion in the failure zone in all directions while avoiding (where possible) local strong zones.