The instability of seabed slope sediments is the main factor influencing the safety of marine resource development. Therefore, to ensure the safe operation of submarine pipelines under complex and uncertain seabed rock and soil conditions, a reliability model was developed to elucidate the trend of impact-related pipeline damage due to submarine slides. Then, a risk assessment of the damage process of submarine slides impacting pipelines was conducted, which is of great significance for the in-depth safety assessment of pipelines impacted by submarine slides. Based on the copula function, a joint probability distribution model considering the correlation among risk variables was established for rational correlation characterization. A probability analysis method of impact-related pipeline damage attributed to submarine slides based on the copula function was proposed. The Monte Carlo simulation (MCS) method was employed to simulate the random uncertainty in limited observation values and accurately determine the reliability of safe pipeline operation under the action of submarine slides. The conclusions were as follows: (1) Based on the copula function, a joint probability distribution model of risk variables with any marginal distribution function and related structure could be developed. (2) The copula function could reasonably characterize relevant nonnormal distribution characteristics of risk variables and could simulate samples conforming to the distribution pattern of the risk variables. (3) The failure probability calculated with the traditional independent normal distribution model was very low, which could result in a notable overestimation of the reliability of submarine pipelines.

Because rockfill strength and seismic ground motion are dominant factors affecting the slope stability of rockfill dams, it is very important to accurately characterize the distribution of rockfill strength parameters, develop a stochastic ground motion model suitable for rockfill dam engineering, and effectively couple strength parameters and seismic ground motion to precisely evaluate the dynamic reliability of the three-dimensional (3D) slope stability of rockfill dams. In this study, a joint probability distribution model for rockfill strength based on the copula function and a stochastic ground motion model based on the improved Clough-Penzien spectral model were built; the strength parameters and the seismic ground motion were coupled using the GF-discrepancy method, a method for the analysis of dynamic reliability of the 3D slope stability of rockfill dams was proposed based on the generalized probability density evolution method (GPDEM), and the effectiveness of the proposed method was verified. Moreover, the effect of different joint distribution models on the dynamic reliability of the slope stability of rockfill dams was revealed, the effect of the copula function type on the dynamic reliability of the slope stability was analysed, and the differences in the dynamic reliability of the slope stability under parameter randomness, seismic ground motion randomness, and coupling randomness of parameters and seismic ground motion were systematically determined. The results were as follows: the traditional joint distribution models ignored related nonnormal distribution characteristics of rockfill strength parameters, which led to excessively low calculated failure probabilities and overestimations of the reliability of the slope stability; in practice, we found that the optimal copula function should be selected to build the joint probability distribution model, and seismic ground motion randomness must be addressed in addition to parameter randomness.

Pipelines in soft soil are prone to deformation and failure under traffic loads. Therefore, it is highly important to accurately characterize the dynamic response of pipelines under traffic loads and reasonably evaluate their operational status. First, for rigid pipelines, a Dload subroutine is written in the FORTRAN language to accurately characterize traffic loads, and a 3D numerical analysis model of the rigid pipe‒soil system is established using ABAQUS software to simulate the dynamic response of rigid pipelines in soft soil under traffic loads. The simulation results are validated against data from field tests. Second, an improved particle swarm optimization (PSO) algorithm is introduced to optimize the weights and thresholds of a backpropagation neural network (BPNN). An improved PSO-BPNN method for predicting the dynamic response of pipelines is proposed, and the accuracy and applicability of the method are verified. Finally, using the prediction model, a reliability analysis is conducted on the dynamic response of rigid pipelines in soft soil under traffic loads. The results show that compared with smaller-diameter pipelines, larger-diameter pipelines exhibit lower axial stress and vertical displacement, with more concentrated distributions. During pipeline construction, larger-diameter pipelines should be chosen whenever possible to reduce the adverse impact of factors such as traffic loads on the dynamic response of pipelines. These research results provide a new theoretical basis and technical support for enhancing the reliability of rigid pipelines in soft soil and conducting in-depth safety assessments of pipelines under traffic loads.