Seismic Reliability Assessment of Anti‐Sliding Pile Reinforced Slopes Considering Coupled Randomness of Ground Motions and Shear Strength Parameters via DPIM

Slope instability under seismic loading is a common geohazard, and the inherent randomness of both seismic excitations and soil properties further exacerbates the uncertainty in slope reliability assessments. This study proposes a novel framework for evaluating the seismic reliability of slopes from a probabilistic and statistical perspective. Stochastic ground motions and random soil parameters were generated using the spectral expression–random function (SERF) method and the generalized F‐discrepancy method, respectively. The random factors were incorporated into the finite element model to perform a series of deterministic time‐history analyses. Subsequently, statistical and probabilistic information was extracted from these time‐history analysis results using the direct probability integration method (DPIM), enabling a comprehensive evaluation of slope performance under seismic loading. The proposed framework was applied to a real‐world excavated slope, and three representative cases were analyzed. The influence of randomness in both soil parameters and seismic inputs on the stochastic response and seismic reliability of slopes reinforced with anti‐sliding piles was systematically compared. The results demonstrate that, even under stochastic conditions, anti‐sliding piles significantly enhance slope stability. However, the introduction of random factors markedly increases the variability in slope response and contributes to higher uncertainty in reliability outcomes. Overall, these findings highlight the necessity of incorporating seismic and soil parameter randomness into seismic slope reliability assessments to accurately capture system behavior and risk.