The anisotropic behaviour of sands, which is associated with their grain-scale microstructural characteristics such as the distribution of voids and the spatial orientation of particles, can lead to significant variations in macro-scale predictions. In this paper, a bounding surface plasticity based anisotropic semi-micromechanical constitutive model is developed, within the multilaminate framework, to describe the effects of fabric on the cyclic behaviour of sands. A novel plastic strain driven semi-micromechanical fabric evolution framework fulfilling the premises of anisotropic critical state theory is proposed. Rather than using a single scalar-valued fabric anisotropic variable, which is the general practise in anisotropic critical state theory based models, independently evolving fabric anisotropic variables are employed at so-called sampling planes. In addition, the semifluidised state concept is utilised at low mean effective stresses to realistically capture post-liquefaction responses, including large shear deformations and accumulative plastic strains during flow liquefaction and cyclic mobility types of behaviour. The procedure for calibrating model parameters is briefly described and the prediction capabilities of the proposed model under drained and undrained monotonic and cyclic loading conditions at different stress states, relative densities and loading orientations are demonstrated by simulating experimental data for Toyoura sand using a single set of parameters.

Despite the advantages of using Bayesian networks for probabilistic risk assessment, adoption in practice has been limited due to the lack of realistic, facility-scale studies. Scaling up from systems to facility-level safety assessments poses challenges in (i) integrating external hazards and their cascading effects, and (ii) resolving non-homogeneity of various technical and human reliability models. The novelty of the study is in formalising risk integration using Bayesian networks, at facility scale, and demonstrating its effectiveness in addressing associated challenges. A Bayesian network-based multi-hazard risk framework is introduced and demonstrated for a nuclear power plant subject to flooding and earthquake hazards, capturing dependencies among hazards and consequences. Individual reliability models – conventionally extraneous to facility-wide risk models – are included as subnetworks by using Bayesian network-based surrogate models for technical systems and a Bayesian networks approach for human reliability modelling. Two approaches are used for subnetwork integration – object-oriented and unified Bayesian networks. The unified approach allows for prediction, diagnostics and inter-causal reasoning since Bayesian inference is bi-directional. Conversely, in the object-oriented approach, diagnostics are limited to within individual subnetworks and as a consequence the model can potentially neglect dependencies between objects. However, the object-oriented model requires only 50 % of the computational memory and consumes less than 25% of the runtime as the unified network, while improving visual clarity of the risk model. The model reveals key insights – for example, variations in operator stress or available response time during a hazard event can result in up to a 77 % change in top event probability – demonstrating its effectiveness in capturing critical relationships in complex, facility-scale risk scenarios. These findings can be used to suitably allocate resources towards risk mitigation and plant safety management.

Geological materials exhibit spatial variability in their properties as a result of their formation. Many studies have focussed on how to characterise this spatial variation by means of the correlation length θ. Such a characterisation has been applied in the geotechnical design of geostructures at numerous sites where cone penetration tests (CPTs) were available, because θ can be relatively easily estimated from this in-situ information. However, the CPTs available at a given site are often part of the initial site investigation, and hence carried out before the application of any ground improvement technique. This raises the question of how (and by how much) the estimated θ is affected by subsequent stages of the construction project and, more specifically, by the application of ground improvement processes intended to alter the initially poor mechanical condition of the in-situ soil. This paper investigates in-situ data from three trial test sites, where CPT data before and after application of vibro-compaction are available. In addition to the expected overall mechanical improvement of the soil, the application of vibro-compaction has a significant impact on soil heterogeneity, with a substantial reduction in the coefficient of variation and θ of the cone tip resistance and sleeve friction.

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.

This paper investigates the implementation of a nonlocal regularisation of the material point method to mitigate mesh-dependency issues for the simulation of large deformation problems in brittle soils. The adopted constitutive description corresponds to a simple elastoplastic model with nonlinear strain softening. A number of benchmark simulations, assuming static and dynamic conditions, were performed to show the importance of regularisation, as well as to assess the performance and robustness of the implemented nonlocal approach. The relevance of addressing stress oscillation issues, due to material points crossing element boundaries, is also demonstrated. The obtained results provide relevant insights into brittle materials undergoing large deformations within the MPM framework.

As the Material Point Method (MPM) uses both a mesh and a point discretisation scheme, the application of boundary conditions is difficult, currently limiting the flexibility of the method. While many boundary condition options have been used in the literature, the accuracy of Neumann boundary condition options has not yet been studied. Four options have here been evaluated for 1D and 2D benchmarks, although none of the options were found to be both accurate and generally applicable in MPM. However, for the generalised interpolation material point method (GIMP), the application of surface tractions on support domain boundaries or on a detected surface are valid options. Large differences between these two accurate options and the application of tractions at surface material points, a method regularly used in the literature, have been observed.

A hybrid material point/finite volume method for the numerical simulation of shallow water waves caused by large dynamic deformations in the bathymetry is presented. The proposed model consists of coupling the nonlinear shallow water equations for the water flow and a dynamic elastoplastic system for the seabed deformation. As a constitutive law, we consider a linear elastic-non-associative plastic model with the Drucker-Prager yield criterion allowing for large deformations under undrained cases. The transfer conditions between these models are achieved by using forces sampled from the hydraulic pressure and the friction terms along the interface between the seabed soil and shallow water. A detailed description regarding the coupled algorithm for the hybrid material point/finite volume method is presented. Several numerical examples are investigated to demonstrate the performance of the finite volume method for simulations of shallow water flow and the material point method for capturing the large deformation process of the solid phase. We also present numerical simulations of an undrained clay column collapse that induced shallow water waves and a dam-break problem to demonstrate the excellent performance of the proposed hybrid material point/finite volume method.

The coupling effect of initial shear stress and thermal cycles on the thermomechanical behaviour of clay concrete and sand-concrete interfaces has been studied. A set of drained monotonic direct shear tests was conducted at the soil-concrete interface level. Samples were initially sheared to half of the material's shear strength and then they were subjected to five heating/cooling cycles before being sheared to failure. The test results showed that the effect of thermal cycles on the shear strength of the materials was negligible, yet shear displacement occurred during application of thermal cycles without an increase in shear stress, confirming the coupling between the shear stress and temperature. In addition, a slight increase of stiffness due to the coupling was observed which diminished with further shearing.

Uncertainty is inevitable in the characterisation of a geotechnical site, especially due to the inherently heterogeneous nature of the ground. In this paper, a method for characterising a subsurface with limited cone penetration test (CPT) data is proposed. The method is based on integrating predictions of CPT parameters with a probabilistic approach for subsoil classification at the CPTs. The predicted stratigraphy is able to capture the spatial variability of soil measured via CPTs and takes account of the uncertainties that arise from transforming CPT measurements into soil units as well as errors in the measurements themselves. The applicability of the proposed method is demonstrated for a site in the Netherlands. The results show that the proposed approach can identify the most likely classification in the domain with good accuracy. Furthermore, the significance of considering the uncertainties in predicting the most likely classification is illustrated via finite element stability analyses of a slope cut-out in the domain.

In this paper, a state-dependent semi-micromechanical framework for anisotropic sands is proposed. A simple constitutive model based on critical state theory and bounding surface (BS) plasticity is used to describe idealized micro-level soil behaviour, and a slip theory based multilaminate framework employed to create a link between the micro and macro level responses of soil. A contact normal based second order fabric tensor is used to create a mathematical description of the anisotropic nature of sand. The proposed constitutive framework can reproduce various soil responses, stemming from both the inherent anisotropy which highly depends on the sample preparation method and induced anisotropy resulting from the applied stress path. This paper presents concise theoretical aspects of the multilaminate framework and the anisotropic elastoplastic constitutive formulation. Finally, the model's performance in predicting sand response is demonstrated under drained and undrained conditions at different stress states, relative densities and loading conditions by simulating Karlsruhe sand, and is examined through a comparison with two other sophisticated constitutive models for sand, namely the Dafalias and Manzari (2004) version of Sanisand and hypoplasticity with intergranular strain.

Experimental studies show that initial fabric and its evolution under different stress paths greatly influences soil behaviour. Even though different sample preparation methods create different inherent anisotropies and cause different material responses, the same initial fabric structure under different stress paths also results in different material behaviours. In this paper, a simple state-dependent, bounding surface-based elastoplastic constitutive model, which can simulate the anisotropic nature of sands including the effect of principal stress rotation, is described. The model is developed based on a semi-micromechanical concept within the multilaminate framework and, to include the inherent anisotropy of sand, a deviatoric fabric tensor describing the initial microstructure is introduced. In addition, a fabric evolution rule compatible with anisotropic critical state theory is employed to describe the evolving fabric structure and induced anisotropy towards the critical state. In contrast to the classical strain-driven formulation for fabric evolution, a micro-level evolution rule is proposed. This paper presents concise theoretical aspects of the multilaminate framework and the anisotropic elastoplastic constitutive formulation. The model's capability under drained and undrained monotonic loading conditions at different stress states, relative densities and principal stress orientations is demonstrated by simulating experimental data for Toyoura sand.