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Most slope collapses have three-dimensional (3D) characteristics due to the uniform soil. The traditional plane-strain analyses neglect the 3D effects and could yield an overestimation or underestimation of the slope stability. The present study analyzes the stability of 3D slopes characterized by spatially variable undrained shear strength. A 3D slope reliability analysis approach that can fully consider the spatial variability of soil properties is proposed based on the plastic limit analysis upper-bound theorem. Within the framework of Monte Carlo simulation, the effects of strength gradient, the coefficient of variation, and the scale of fluctuation of soil undrained shear strength on the slope reliability index are examined. The length of the 3D failure surface is highlighted as an essential characteristic in 3D slope analysis. The slope failure mechanisms are classified, and the occurrence probability of each type is quantified. The obtained results indicate that the degree of nonstationarity and the coefficient of variation of undrained shear strength have significant impacts on the slope failure width, and the variation of failure mechanism highly depends on the combined effect of slope inclination and soil strength. The findings could guide slope reinforcement and facilitate a more efficient and accurate risk evaluation of slopes. [ABSTRACT FROM AUTHOR]

The paper presented probabilistic analyses of the bearing capacity of strip footings in spatially variable undrained soil with a linearly increasing mean shear strength profile. The probabilistic response of strip footings was approached by the random finite element method (RFEM) in conjunction with the Monte Carlo simulation. Probabilistic failure envelopes were constructed to analyze the effect of spatial variability on strip footings subjected to different combinations of horizontal (H) and moment (M) loading. The probability of failure was independent on the strength gradient in the HM plane, but tended to increase with a wide fluctuation. Tabulated values of factor of safety for the probability of failure at 1% in different undrained shear strength random fields were also provided, which could be applied toward a foundation safety assessment. [ABSTRACT FROM AUTHOR]

A probabilistic study on the bearing capacity of two parallel strip footings on a spatially variable soil where the mean of undrained shear strength increased linearly with depth was performed. For the comparative purpose, the single footing case was also investigated. Stationary and nonstationary random fields obeying log-normal distribution of undrained shear strength were generated and further mapped into nonlinear finite-element analysis. Monte Carlo simulations were then performed to evaluate the bearing capacity for the selected ranges of the degree of nonstationarity and the spatial correlation length in undrained shear strength. The normalized bearing capacities derived from two different random field models for the cases of single and two footings were compared, and the effect of footing interference was also discussed. [ABSTRACT FROM AUTHOR]

The objective of this paper is to investigate the effect of soil variability on bearing capacity of an embedded foundation in the presence of nonstationary undrained shear strength. The nonstationary undrained shear strength is simulated by a nonstationary random field generator based on the spectral representation method. An embedded foundation buried into the soil to two times of width is presented to investigate the influence of spatially variable undrained shear strength on bearing capacity. Firstly, Monte Carlo simulations are carried out to discuss the effect of distribution type, nonstationary gradient parameter, and horizontal autocorrelation length on the bearing capacity from the standpoint of mean value and standard deviation. Then, the influence of the distribution type on the failure probability of nonstationary random soil is also investigated, with the failure probability for the Beta distribution being demonstrated to be always larger than that for the Lognormal and Gamma distribution. [ABSTRACT FROM AUTHOR]

Abstract The objective of this paper is to investigate the bearing capacity of spatially varying soil in the presence of non-stationary feature of undrained shear strength. Firstly, undrained shear strength is modeled by a non-stationary random field. In this model, the mean of undrained shear strength is non-zero at the ground surface and linearly increases with depth, while the coefficient of variation (COV) of undrained shear strength keeps constant. Based on this non-stationarity, an algorithm is proposed to produce the corresponding random field. Then, Monte Carlo Simulations are carried out to evaluate the statistical characteristics of the resulted bearing capacity, followed by a detailed discussion on the effects of COV, strength gradient parameter, distribution type, and vertical autocorrelation length. At last, two computation schemes that enable the prediction of statistical characteristics (e.g., mean, standard deviation, and cumulative probability function) of bearing capacity in non-stationary random fields utilizing results from a stationary one are proposed, and demonstrated through numerical examples. [ABSTRACT FROM AUTHOR]

Spudcan foundations are widely used in the offshore gas and oil industry to support mobile jack-up drilling rigs. During the service period, the spudcan foundations need to resist large vertical-horizontal-moment (VHM) loads that are transmitted from the superstructure. The bearing capacity of foundations in complicated stress conditions is usually based on VHM failure envelopes. These are commonly constructed by using numerical methods where the soil properties are assumed to be deterministic, ignoring the inherent spatial variability. This paper investigates the influence of spatially variable undrained shear strength and embedment depth on the capacity of spudcan foundations under VHM combined loads. The linearly increasing undrained shear strength with depth obeying log-normal distribution was taken into account. Probabilistic failure envelops were constructed to analyse the effect of spatial variability on the bearing capacity of spudcan foundations at various embedment depths when subjected to different combinations of VHM loads. The influence of horizontal scale of fluctuation for a specific embedment depth was also investigated. The results indicated that under combined loading the embedment depth significantly influenced the shape and size of failure envelopes. The probability of failure at each embedment depth based on the obtained probabilistic failure envelopes was intuitionally represented by means of a factor of safety, which can provide specific guidance for foundation reliable designs. • A non-stationary random field model was established. • Uniaxial ultimate bearing capacities were analyzed and VHM failure envelopes were constructed for various embedment depths. • Factors of safety were provided. [ABSTRACT FROM AUTHOR]

The objective of this paper is to investigate how the non-stationary features of soil properties affect the stochastic result of bearing capacity of embedded shallow foundations. Undrained shear strength was modelled as a non-stationary random field with mean value increasing with depth. A nonlinear finite element analysis combined with random fields generated by the Spectral Representation Method was employed to obtain the bearing capacity in random soils. Monte Carlo simulations were applied to obtain statistical characteristics of the resulting bearing capacity. The effect of non-stationary features of random soil properties on foundations with different embedment depths is discussed from three aspects, i.e. the failure mechanisms, the statistical characteristics of the bearing capacity factors, and the probability of failure of the foundation. Interestingly, it was found that the effects of non-stationary random soil properties on some of the three aspects change with the embedment depths of the foundations. Furthermore, some suggestions for foundation design are given, based on the obtained results. [ABSTRACT FROM AUTHOR]

In geological surveys of coastal regions, data interpretation and site identification are usually affected by underground water (including salinity). This study aimed to investigate the effect of pore-water salinity on soil identification via in situ CPTs. Combinations of triaxial shearing, cone penetration, and vane shear tests were also performed at a laboratory scale on Lianyungang marine clay with different pore-water salinities. The results suggested that the effective friction angles and shear strength increased with the pore-water salinity. The in situ CPTs showed that the normalized tip resistances increased with an increase in pore-water salinity, whereas no significant correlation between the normalized sleeve fraction and salinities was found. The use of the conventional soil identification method (soil-behavior-type chart, i.e., SBT chart) may be effective in very low-salinity conditions despite that it does not take into account the pore-water salinity effect. The salinity investigation of Lianyungang marine clay suggests that an inhomogeneous salinity distribution significantly influences soil identification when with rich clay mineral of montmorillonite and high pore-water salinity. From the theoretical and practical analyses, an improved soil identification method considering pore-water salinity modification was proposed to avoid the misclassification of in situ soil. • Effective friction angles and shear strengths increases with an increase in pore water salinity. • Normalized tip resistances increases withpore water salinity. • Soil identification by cone penetration tests is influenced by pore water salinity. • An improved model based on an SBT chart considering the salinity effect is proposed. [ABSTRACT FROM AUTHOR]

Spudcan foundations for mobile jack-up units are large diameter conical foundations that can penetrate into the seabed to a maximum depth of three times the diameter of the spudcan. As a deeply penetrated foundation, the bearing capacity of a spudcan is highly dependent on the failure mechanism and the strength distribution of the seabed soil, which exhibits strong spatial variability. While many recent studies have explored the failure mechanism and bearing capacity of spudcan foundations, these studies have commonly deterministically described the soil in which the spudcan is embedded. Therefore, this paper aimed to investigate the probabilistic bearing capacity of spudcan foundations embedded in the seabed at various depths, under the condition of spatially variable undrained shear strength that increased linearly with depth. The random finite element method was used to study this problem, where nonlinear finite element analysis was combined with random field theory within a Monte Carlo framework. The variability in undrained shear strength was modelled as a random field and characterised by a log-normal distribution with anisotropic autocorrelation distances. The influence of autocorrelation distance on the mean bearing capacity and the failure mechanism was discussed for each embedment depth. A correlation between the probability of failure and the factor of safety was established based on the obtained results. These findings can provide guidance for reliability-based design of spudcan foundations embedded in spatially variable soil. [ABSTRACT FROM AUTHOR]

Spudcan foundations have been widely used in offshore oil and gas engineering for jack-up rigs. During penetration into seabed soil, spudcan foundations may encounter large uncertainties in soil properties, which have a strong impact on its bearing capacity. A large number of studies have been conducted to demonstrate the failure mechanisms and the bearing capacity of spudcan foundations in soils with deterministic properties, but the influence of spatially variable soil properties on spudcan foundations remains unclear and should be accounted for. In this study, we aimed to investigate the failure mechanisms and the bearing capacity of a spudcan foundation embedded in soils where the mean undrained shear strength increased linearly with depth. The spectral representation method (SRM) was used to generate a non-stationary non-Gaussian random field. The random finite element method (RFEM) in conjunction with Monte Carlo simulations was carried out to evaluate the statistical characteristics of the bearing capacity for spudcan foundations, followed by a series of comparisons and discussion. The results indicated that the mean bearing capacity for the spatial variability of undrained shear strength was smaller than that obtained from the corresponding deterministic case. The probability of failure decreased slightly with an increase in the degree of non-stationarity under the constant coefficient of variation (COV) condition. Upon comparing the results obtained from different random field models, we found that the probability of failure under the non-constant condition was smaller than that under the stationary and constant COV conditions. • A modified spectral representation method is proposed to generate two different kinds of non-stationary random fields. • Establish the connection between dimensionless bearing capacities and failure mechanism modes. • Typical factors of safety under different degrees of non-stationarity are calculated and compared. [ABSTRACT FROM AUTHOR]