LAUSR

Abstract The prediction of slope stability is difficult due to the spatial variability of soil parameters and measurement errors from core samples. This study proposed a Bayesian updating framework that based on the random finite element model (RFEM) method. The proposed approach was applied in a field excavation slope project. The field data of a soil slope with anti-slide bored piles under four-stage excavations were compared to elucidate the spatial variability of the cohesion, friction angle and stiffness in different soil layers. Then, a Bayesian updating model with random finite element analysis was developed by considering the COV and SOF of the soil parameters. The proposed analysis approach utilized the prior information from the site investigation and field measurement results. The posterior statistical characteristic values of the soil parameters were obtained from equivalent samples calculated by Markov Chain Monte Carlo simulations. The results indicated that the proposed method can reduce the effect of uncertainty related to the soil properties. Finally, the effects of soil parameters and excavation conditions on the slope stability were established, enabling an evaluation of safety based on field measurement results.