PurposeThis paper aims to develop a probabilistic framework which combines uncoupled cofferdam stability analysis, random forest and Monte Carlo simulation for cofferdam reliability analysis.Design/methodology/approachThe finite element method and limit equilibrium method are used to calculate the seepage field and stability of cofferdam, respectively. Sufficient training and validating random samples are generated to obtain a random forest surrogate model with acceptable accuracy. The calibrated random forest model combined with MCS is used to conduct cofferdam reliability analysis. The proposed methodology is illustrated using a typical cofferdam model.FindingsThe numerical simulation results demonstrate that a larger pore water pressure leads to a lower stability of the cofferdam and vice versa. The increase in the slope angle significantly reduces the stability of cofferdam on the corresponding side, while the stability of cofferdam on the other side is mainly affected by the internal pore water pressure. The increase in the width and height of the reverse pressure platform significantly enhances the stability of cofferdam, and the changes in the angle of the reverse pressure platform affect the stability of cofferdam to some extent. The probability of failure (Pf) of cofferdam increases gradually with increasing vertical and horizontal scales of fluctuation, coefficient of variation, and cross-correlation coefficient when the degradation degree of soil properties is low. It is worth noting that the effect of vertical and horizontal scales of fluctuation, coefficient of variation, and cross-correlation coefficient on the Pf of cofferdam changes significantly when degradation coefficient decreases to a critical value.Practical implicationsA geotechnical engineer could use the proposed method to perform cofferdam reliability analysis.Originality/valueThe reliability of cofferdam can be efficiently and accurately studied using the proposed framework.

The slope has an adverse effect on the ultimate bearing capacity of shallow foundations. Due to inherent variability in soil properties and geometric factors of slopes, designing a foundation on slopes is a perplexing and challenging task. The spatial variation in the soil's shear strength property is commonly ignored by the designers to avoid complexity in design. Shear strength property in real scenarios increases along the depth and simultaneously it poses spatial variability. This kind of randomness is modelled using a non-stationary random field. The proposed study aims to evaluate the probabilistic bearing capacity of strip footing on spatially varying slopes. The probabilistic bearing capacity factor is analyzed for different influential factors like geometry and footing placements, correlation distances and coefficient of variation of soil properties. Slopes exhibiting nonstationary characteristics contribute to remarkable differences in the bearing capacity of footing as compared to the stationary condition. The study highlights that the geometry factors, footing placements, soil spatial variability and most importantly the increasing trend of soil strength play a critical role in the bearing capacity and risk of failure of a footing. High variations in the failure probability can be observed even after considering safety factors.

Watery strata and the influence of pore water pressure cannot be ignored when calculating the deformation of existing tunnels induced by the excavation of new undercrossing tunnels. Many parameters can affect the deformation of existing tunnels during the excavation of a new undercrossing tunnel. In this work, an optimized method was developed for calculating the settlement of an existing tunnel undercrossed by a newly excavated tunnel in water-rich strata. This method includes a deterministic calculation model and a probability analysis model. Based on the constitutive behavior of the soil and the poroelasticity theory, the excess pore water pressure at the axis of the existing tunnel was obtained and used in the deterministic calculation model, which computes the deformation of the existing tunnel. In addition, we established a probability model based on Kriging metamodeling, the Latin Hypercube sampling (LHS) and Monte Carlo sampling (MCS) methods, and conducted global sensitivity analysis (GSA) and failure probability analysis. The optimized parameters can be input into the deterministic model to make more accurate predictions. The optimized method was applied in and validated by a metro project in Beijing.

Multiple research studies and seismic data analyses have shown that multi-directional long-period ground motion affects crucial and intricate large-scale structures like oil storage containers, long-span bridges, and high-rise buildings. Seismic damage data show a 3-55% chance of long-period ground motion. To clarify, the chance of occurrence is 3% in hard soil and 83% in soft soil. Due of the above characteristics, the aseismic engineering field requires a realistic stochastic model that accounts for long-period multi-directional ground motion. A weighted average seismic amplification coefficient selected NGA database multi-directional long-period ground motion recordings for this study. Due to the significant low-frequency component in the long-period ground motion, this research uses empirical mode decomposition (EMD) to efficiently decompose it into a composite structure with high- and low-frequency components. Given the above, further investigation is needed on the evolutionary power spectrum density (EPSD) functions of high- and low-frequency components. Analyzing the recorded data will reveal these functions and their corresponding parameters. Proper orthogonal decomposition (POD) is needed to simulate samples of high- and low-frequency components in different directions. These samples can be combined to illustrate multi-directional long-period ground motion. Representative samples exhibit the seismic characteristics of long-period multi-directional ground motion, as shown by numerical examples. This proves the method's engineering accuracy and usefulness. Moreover, this study used incremental dynamic analysis (IDA) to apply seismic vulnerability theory. This study investigated whether long-period ground motions in both x and multi-directional directions could enhance the seismic response of a high-rise frame structure. By using this method, a comprehensive seismic economic loss rate curve was created, making economic loss assessment clearer. This study shows that multi-directional impacts should be included when studying seismic events and calculating structure economic damages.