Bearing capacity of eccentrically loaded strip footing on spatially variable cohesive soil

The study considers the bearing capacity of eccentrically loaded strip footing on spatially variable, purely cohesive soil. The problem is solved using the random finite element method. The anisotropic random field of cohesion is generated using the Fourier series method, and individual problems within performed Monte Carlo simulations (MCSs) are solved using the Abaqus finite element code. The analysis includes eight different variants of the fluctuation scales and six values of load eccentricity. For each of these 48 cases, 1000 MCSs are performed and the probabilistic characteristics of the obtained values are calculated. The results of the analysis indicate that the mean value of the bearing capacity decreases linearly with eccentricity, which is consistent with Meyerhof's theory. However, the decrease in standard deviation and increase in the coefficient of variation of the bearing capacity observed are non-linear, which is particularly evident for small eccentricities. For one chosen variant of fluctuation scales, a reliability analysis investigating the influence of eccentricity on reliability index is performed. The results of the analysis conducted show that the value of the reliability index can be significantly influenced even by small eccentricities. This indicates the need to consider at least random eccentricities in future studies regarding probabilistic modelling of foundation bearing capacity.

An approach for modelling spatial variability in permeability of cement-admixed soil

This paper presents a framework for modelling the random variation in permeability in cement-admixed soil based on the binder content variation and thereby relating the coefficient of permeability to the unconfined compressive strength of a cement-admixed clay. The strength–permeability relationship was subsequently implemented in random finite element method (RFEM). The effects of spatial variation in both strength and permeability of cement-admixed clays in RFEM is illustrated using two examples concerning one-dimensional consolidation. Parametric studies considering different coefficient of variation and scale of fluctuation configurations were performed. Results show that spatial variability of the cement-admixed clay considering variable permeability can significantly influence the overall consolidation rate, especially when the soil strength variability is high. However, the overall consolidation rates also depend largely on the prescribed scales of fluctuation; in cases where the variation is horizontally layered, stagnation in pore pressure dissipation may occur due to soft parts yielding.

Slope stability analysis considering the rotated anisotropy in soil properties

Purpose This paper aims to analyze the influence of rotated anisotropy on the stability of slope, the random finite element method is used in this study. Design/methodology/approach The random field is generated by the discrete cosine transform (DCT) method, which can generate random field with different rotated angles conveniently. Findings Two idealized slopes are analyzed; it is observed that the rotated angle significantly affects the slope failure risk. The two examples support the conclusion that when the orientation of the layers is nearly perpendicular to the slip surface, the slope is in a relative stable condition. The results of heterogeneous slope with two clay layers demonstrate that the rotated angle of lower layer mainly controls the failure mechanism of the slope, and the rotated angle of upper layer exhibits a significant influence on the probability of slope failure. Originality/value The method for rotated anisotropy random field generation based on the DCT has a simple expression with few parameters and is convenient for implementation and practical application. The proposed method and the results obtained are useful for analyzing the stability of the heterogeneous slopes in engineering projects.

Microstructure-Based Random Finite Element Method Model for Freezing Effects in Soils and Cold Region Retaining Walls

This paper describes the development of a random finite element model that allows holistic simulation of the phase transition and consequent development of internal stress and volume changes in frozen soils. The simulation capabilities of the model are first validated with laboratory scale experiments. The validated model is then implemented to study the soil lateral stress on the retaining wall subjected to frost action. The results show that the frost action leads to an increase of lateral stresses along the retaining wall. Strategies to mitigate the frost loads on the retaining wall are analyzed with this model; drainage of water in the backfill and use of thermal insulation layer both help to mitigate the lateral frost loads. Overall, by accounting for the spatial nonhomogeneity and coupled thermo-mechanical responses in frozen soils, the model provides holistic simulation of the responses of retaining walls subjected to freezing conditions.

Probabilistic seismic slope stability analysis and design

Deterministic seismic slope stability design charts for cohesive–frictional ([Formula: see text]) soils are traditionally used by geotechnical engineers to include the effects of earthquakes on slopes. These charts identify the critical seismic load event that is sufficient to bring the slope to a state of limit equilibrium, but they do not specify the probability of this event. In this paper, the probabilistic seismic stability of slopes, modeled using a two-dimensional spatially random [Formula: see text] soil, is examined for the first time using the random finite element method (RFEM). Slope stability design aids for seismic loading, which consider spatial variability of the soil, are provided to allow informed geotechnical seismic design decisions in the face of geotechnical uncertainties. The paper also provides estimates of the probability of slope failure without requiring computer simulations. How the design aids may be used is demonstrated with an example of slope remediation cost analysis and risk-based design.