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Plate anchors have been recognized as an attractive option for floating offshore structures due to their low cost and high effectiveness. The prediction of anchor pullout capacity often assumes a homogeneous sand with uniform properties over the entire soil mass. However, natural soils typically exhibit significant spatial variability due to their geological history of soil formation. To account for this inherent spatial variability, this paper has proposed an analytical approach to probabilistically estimate the pullout capacity of strip plate anchors in sand. The soil friction angle was represented by a random field, and the first two moments and the probability density function of the anchor breakout factor were determined analytically using a local average theory. The proposed analytical approach was validated by the random finite-element method (RFEM) over a wide range of soil and anchor parameters. The findings suggest that the anchor embedment depth ratio has a limited effect on the estimated anchor failure probability, whereas the coefficient of variation and correlation length of the soil friction angle have a significant influence. This confirms the importance of sufficient site investigation for cost-effective and reliable anchor design. Overall, the proposed analytical framework can be regarded as a reliable and practical alternative to the computationally intensive RFEM. [ABSTRACT FROM AUTHOR]

Natural soils often exhibit significant spatial variability due to their geological history of soil formation. As an attractive anchoring solution for floating offshore structures, this paper has investigated the pullout capacity of strip plate anchors in clay considering the inherent soil spatial variability. In this study, the soil properties were represented by random fields, and an analytical framework was developed to estimate the first two moments and the probability density function of the pullout capacity factor for shallowly and deeply embedded anchors. The analytical approach was validated by the random finite element method (RFEM) over a wide range of soil and anchor parameters. The results show that the coefficient of variation and correlation length of the soil significantly affect the prediction of anchor pullout capacity, providing evidence that sufficient site investigation is of great importance for cost-effective and reliable anchor design. Probabilistic charts were also developed to aid in the probabilistic analysis of anchor pullout capacity. Overall, the developed analytical framework can be used as a good approximation to the computationally intensive RFEM. [ABSTRACT FROM AUTHOR]

Geotechnical design codes have been migrating from the traditional allowable stress design towards load and resistance factor design (LRFD). In this paper, calibration of the geotechnical resistance factors for sliding and overturning limit states of gravity retaining walls is performed using a reliability-based method. For each limit state, the LRFD approach is applied to design the gravity retaining wall, and its probability of failure is estimated using the Random Finite Element Method (RFEM). An example gravity retaining wall is analyzed using the described methodology, and the results suggest that for a given resistance factor the sliding failure probability is greater than the overturning failure probability, and a positive correlation between the soil effective internal frictional angle and unit weight random fields significantly reduces the failure probability. For reasonable ranges of the target maximum lifetime failure probability, the required resistance factor for the sliding limit state is close to that for the overturning limit state. In addition, the sliding resistance factor given by the Canadian Highway Bridge Design Code seems slightly unconservative, while the recommended overturning resistance factor is slightly conservative. The current analysis can be used to guide the calibration of these geotechnical resistance factors used in design codes. [ABSTRACT FROM AUTHOR]

The load and resistance factor design (LRFD) approach employed in geotechnical design codes is often calibrated using the reliability-based design (RBD) method. However, the LRFD may not achieve the target safety level exactly. This paper makes comparisons between the LRFD and RBD by considering the ultimate and serviceability limit state design of strip foundations. The RBD is carried out via the Random Finite Element Method. It is found that the failure probability and the resulting foundation width for ULS obtained using the RBD increase with the soil spatial correlation length, gradually reaching a plateau. The comparison between the LRFD and RBD results for ULS suggests that the LRFD is conservative for low to medium soil variability, particularly at smaller correlation lengths. The reliability-based SLS design is less dependent on the soil correlation length, particularly for lower coefficients of variation of the soil elastic modulus. However, a resistance factor of 1.0 for SLS is unconservative, and resistance factors of 0.65, 0.7 and 0.8 are better aligned with the RBD when the target failure probabilities are 1×10−3, 1×10−2 and 1×10−1. The current study can be used to guide the design of shallow foundations and the calibration of the LRFD approach. [ABSTRACT FROM AUTHOR]

An evaluation of the spatial correlation length of two geological formations known as mudflows and residual soils has been conducted using standard penetration test (N1)60 values. The spatial correlation length is an important property in reliability-based design, in addition to the mean and standard deviation of soil parameters, but it is rarely estimated in geotechnical projects. Reported results in this paper from both geologies show the geological origin's importance in the spatial variability analysis. Residual soils are more likely to display isotropic spatial correlation lengths horizontally when compared with the mudflows. The results show that the random field represents more accurately the mudflows' soil variability when the residual soils must be complemented with shear strength tendency analyses. [ABSTRACT FROM AUTHOR]