The absence of information on lateral variability in the soil is detrimental to estimating accurately the local site response in the event of an earthquake. To address this problem, the use of densely sampled seismic data together with sparsely distributed but detailed vertical soil profiles obtained from cone penetration tests (CPTs) is advantageous. This study explores the adaptation of suitable machine learning (ML) approaches to derive reliable, site- and depth-specific correlations between seismic shear-wave velocity (Vs) and cone-tip resistance (qc). Such correlation could be successfully established by combining information from seismic CPT surveys with available borehole information for the Groningen region in the Netherlands. It is found that, even over substantial distances, ML-based techniques offer site- and depth-specific correlations between Vs and qc.@en

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.

@en

Stratification identification and spatial interpolation play a fundamental role in geotechnical site characterization. A unified approach is needed to perform these two tasks simultaneously to reduce overall uncertainty in site characterization. This paper explores the applicability of the Mixture of Gaussian Processes (MoGP) to address this gap, with a specific focus on characterizing and completing missing CPT data. The investigation encompasses both synthetic and real-world field CPT datasets and includes a comparison of the MoGP's interpolation accuracy with the use of a single GP for entire datasets. Additionally, the study examines the sensitivity of the model's performance with respect to the number of training data points. Although the interpolation performance of the MoGP model is promising with synthetic data, limitations appear in its application to real-site CPT data. @en

Capturing the spatial variability in soil is crucial for ground response analyses in the context of seismic hazard mitigation. The lateral variability in thickness and properties of the different soil layers is one of the main factors that determines the variability of the ground motion spectrum from one location to another. The absence of such lateral variability information in the subsoil in between the locations of Cone Penetration Tests (CPTs) may be compensated by the use of more densely sampled seismic data. In this research we aim to derive a shear-wave velocity field through seismic full-waveform inversion that yields a model resolution approaching that of high-resolution seismic CPT surveys. Following this, a datadriven correlation between geophysical and geotechnical information is attempted through the application of new machine-learning-based approaches. @en

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.

@en

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.

@en

The stability of six regional dyke cross-sections in the Netherlands was re-assessed using the random finite element method (RFEM), which explicitly accounts for the spatial variability of strength parameters. The RFEM assessments of the cross-sections were shown to result in significantly narrower response distributions than those obtained by ignoring the spatial variability, and therefore would result in more economical designs. Given the complexity of RFEM for applications in daily engineering practice, the results obtained from the re-assessments of the six dyke cross-sections were used to propose partial factors that can be used in practice to achieve the desired reliability levels for regional dykes. When applied in a conventional semi-probabilistic assessment of a dyke cross-section, these partial factors would result in the same level of reliability as would have been obtained by carrying out an RFEM analysis of the same cross-section.

@en

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.

@en

The effect of temperature on the monotonic and cyclic shearing response of a soil–structure interface is of critical importance for the application of thermal-active geo-structures. To investigate this, soils and soil–concrete interfaces were comprehensively tested with a temperature-controlled direct shear device under both fixed temperatures and thermal/mechanical cycles within the range of 2–38 °C. Monotonic and cyclic shearing with various boundary conditions, including constant normal load (CNL), constant normal stiffness (CNS) and constant volume (CV), were conducted to resemble the conditions that thermal-active-geo-structures may experience. The strength properties of the sand, clay, and sand–concrete and clay–concrete interfaces were partially influenced by heating and cooling under all boundary conditions. However, several effects were observed which could affect the performance of thermo-active structures. Heating cycles caused the clay–concrete interface to be overconsolidated, implying a lower excess pore pressure would be generated during shearing. The cyclic CNS tests suggested that the interface strength could degrade due to (thermally induced) cyclic shear displacements, with this effect strongly related to the state of the soil rather than the temperature directly. In these tests, the medium-dense sand–concrete interface degraded to almost zero shear strength after 5 cycles, whereas the clay–concrete interface asymptotically degraded to around 60% of its strength after 10 cycles.

@en

This research focuses on investigating the relative performance of a range of machine learning algorithms, namely the artificial neural network, support vector machine, Gaussian process regression, random forest, and XGBoost, for predicting the undrained shear strength from cone penetration test data. This is to assess how machine learning could help us lower the need for laboratory test data. The training dataset compiles 526 data from 12 regions and the testing dataset consists of 20 data from a polder located close to Leiden in the Netherlands. In addition, k-fold and group k-fold cross-validation strategies are both applied to validate the models. The poor performance of the models during group k-fold cross-validation suggests that, while machine learning techniques can perform well when site-specific data are included during training, they struggle to generalize without site-specific data. This highlights the difficulty of capturing soil heterogeneity and suggests that either machine learning methods should be trained on specific sites for which some data are already available, or much larger training datasets are needed.@en

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.

@en

Retrogressive failures occur in slopes consisting of sensitive materials such as snow or quick clay. They can be triggered by a small disturbance at the slope toe, but can cause propagated failure spreading miles away. Understanding the physical mechanism and predicting the retrogressive failure process are particularly important. Previous studies have discussed the failure criteria, the soil properties or the method of numerical modeling of retrogressive slope failure. However, little attention has been paid to the microscopic failure mechanism, especially relating to various possible failure patterns. In this study, multiscale modeling is incorporated to study the physical mechanism of different retrogressive failure patterns, including earth flow, flowslide and spread failure, within a unified framework. Utilizing multiscale analysis, we found that earth flow failure is related to the shear failure of granular materials. In contrast, the development of macroscopic shear bands is accompanied by tensile failure. As shear and tension failures are typical failure mechanisms of frictional and cohesive materials, it is deduced that friction and cohesion effects play key roles in different retrogressive failure patterns. Therefore, the distributions of attractive and repulsive contact forces are explored and a novel parameter η is proposed to quantify the interplay between friction and cohesion. Further analysis proves that η can capture the effect of friction and cohesion and distinguish different retrogressive failure patterns. Finally, a spectrum of retrogressive failures for a granular slope is established, in which the failure mechanism is explained by the changeable dominant effect, that is, frictional or cohesive in soil.

@en

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.

@en

Geological uncertainty can significantly influence the computed response of a geotechnical structure. For example, ignoring the presence of a weak soil layer embedded within a stronger layer and assuming a deterministic stratigraphic boundary can significantly underestimate the probability of failure. In this paper, the coupled Markov chain method has been used for modelling this form of uncertainty. A strategy for estimating the horizontal transition probability matrix with limited data has been proposed, which is one of the biggest challenges with using this method. In particular, different sampling intervals in the vertical and horizontal directions have been considered in estimating the matrix for simulating realistic field situations. The applicability of the proposed method has been demonstrated using a set of CPTs in the Netherlands. The results highlight a problem that arises due to the coupling algorithm used in this method.@en

To protect embankments along German inland waterways against local slope sliding failure caused by ship-induced water level drawdown, they are mainly secured by bank revetments. Often, large embankment sections are designed on the basis of a limited number of field and laboratory tests. Thus, uncertainties arise with regard to the mechanical and hydraulic ground properties. Current design standards account for these uncertainties by conservative design assumptions and empirical knowledge. This paper investigates the effects of vertically non-homogeneous ground properties on the required armour layer thickness using 1D random fields and an infinite slope model, which was modified to account for ship-induced drawdowns. Within the limitations of the infinite slope assumptions, the effects of a spatially variable friction angle and hydraulic conductivity are investigated and compared to deterministic benchmark cases. The investigations show that the level of safety obtained with the deterministic design depends strongly on the choice of the characteristic values. Particularly, the hydraulic conductivity determines the reliability of the design. In some cases, the 5 % quantile of the hydraulic conductivity does not yield a conservative estimate of the required armour layer thickness. In the case of the effective friction angle, the 5 % quantile may overestimate the required armour layer thickness for permeable soils. For less permeable soils, the 5 % quantile meets the solution of the random field analyses. For the combination of random effective friction angle and random hydraulic conductivity, all investigated benchmark studies seem to ensure engineering safety, but on different reliability levels. Based on these findings, recommendations regarding site exploration and choice of characteristic values of hydraulic conductivity and effective friction angle are provided.@en

Soil liquefaction is investigated considering a saturated soil deposit and by implementing standard techniques of random field theory to distribute initial void ratio values and assess liquefaction risk. The soil domain is represented in a 2-dimensional (2D) random finite element model for the dynamic analysis of coupled behavior. Multiple Monte Carlo realizations are subjected to a base acceleration, while cyclic and small strain soil behaviours are achieved through a hypoplastic constitutive model. This investigation demonstrates that 2D stochastic simulations converge to 2D deterministic simulations when small standard deviations and/or small scales of fluctuation are used. However, large standard deviations combined with relatively large scales of fluctuation may cause significant uncertainty in the response of the soil deposit. Finally, common techniques employed to assess soil liquefaction are evaluated based on the results of the deterministic and random field analyses.

@en

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.

@en

Offshore monopile foundations are exposed to misaligned wind and wave loadings, which are respectively dominated by (nearly) static and cyclic load components. While the response of these systems to unidirectional cyclic loading has been extensively investigated, only a few studies have been devoted to the realistic case of misaligned static and cyclic loads, and particularly to the effects of such misalignment on the accumulation of pile rotation under prolonged cycling. This paper presents a 3D finite-element (FE) modelling study on the relationship between load misalignment and cyclic monopile tilt under drained conditions, based on the use of the SANISAND-MS model to enable accurate simulation of cyclic sand ratcheting. After qualitatively identifying the relationship between relevant loading parameters and cyclic stress/densification mechanisms in the soil, specific parametric studies are performed to explore the impact on pile tilt accumulation. The results show that, in comparison to unidirectional loading, misaligned static–cyclic loading gives rise to lesser-known pile–soil interaction mechanisms: when the direction of cycling deviates from that of the static load, “cyclic compression” and “direct cyclic shearing” mechanisms begin to co-exist. This is quantitatively captured by a newly proposed empirical equation for monopile tilt calibrated against the 3D FE simulation results obtained in this work.

@en

Free-field site response analysis is a standard technique used to predict soil deposit dynamic response and liquefaction susceptibility. Such analyses are typically carried out by implementing periodic boundaries to guarantee the same speed of the dynamic waves travelling across them. However, when using random fields to consider the impact of soil spatial variability there is the possibility of an inconsistency with periodic boundaries. This is due to the generation of non-identical properties at the lateral boundaries on using traditional random fields. To overcome this inconsistency, this paper proposes periodic random fields to model spatial variability by matching the periodicity at the boundaries. To investigate the significance of using the proposed approach, a heterogeneous soil deposit subjected to earthquake loading is analysed using the random finite element method. The results show that, for certain values of the horizontal scale of fluctuation, ensuring consistency at the lateral boundaries could result in less conservative predictions of the extent of the liquefied areas. @en

Natural soil deposits may possess a highly anisotropic nature. The fabric anisotropy of soils which is induced during the soil formation process can lead to severe variation in field scale responses. Although the influence of fabric on the response of sands is well known and several advanced constitutive models have been developed to account for it, most of the studies incorporating anisotropy have focused on element test simulations while practical boundary value problem simulations are usually omitted. In this paper, the undrained response and liquefaction resistance of anisotropic sand deposits with different inherent fabric anisotropies are numerically investigated through element test simulations and one-dimensional nonlinear effective stress site response analyses. A novel semi-micromechanical constitutive model accounting for the effect of fabric anisotropy on sand liquefaction has been incorporated into a fully coupled dynamic in-house code employing the u-p formulation. The proposed numerical framework shows that, in both element test simulations and site response analyses, the fabric effects stemming from both the inherent and induced anisotropies can significantly influence the liquefaction resistance of sands.@en