A Dynamic Method to Predict the Earthquake-Triggered Sliding Displacement of Slopes

Abstract

The earthquake-induced permanent displacement is an important index of the potential damage to a slope during an earthquake. The Newmark method assumes that a slope is a rigid-plastic body, and the seismic responses of sliding masses or seismic forces along the slide plane are ignored. The decoupled method considers no relative displacement across the sliding plane, so it overpredicts the seismic response of the sliding mass. Both dynamic and sliding analyses are performed in the coupled method, but when Ts/Tm is large, the results are unconservative. In this paper, a method is proposed to predict the earthquake-triggered sliding displacement of slopes. The proposed method is based on the Newmark rigid method, coupled method, and decoupled method considering both the forces at the sliding interface and the system dynamics under critical conditions. For the flexible system, the displacements are calculated with different stiffness values, and the results show that as the stiffness increases and tends to infinity, the critical acceleration and displacements of the proposed method are close to those of the Newmark method. The proposed method is also compared with the Newmark method with the period ratio Ts/Tm. At small values of Ts/Tm, the flexible system analysis results of the displacement are more conservative than those of the rigid block model; at larger values of Ts/Tm, the rigid block model is more conservative than the flexible system.

Interval Prediction of Building Foundation Settlement Using Kernel Extreme Learning Machine

“…Ground settlement is a common geological phenomenon and poses a risk to local communities. The major factor that induces ground settlement is soil liquefaction, which softens soil and causes buildings to settle more than the soil (Feng et al, 2021;Li et al, 2022). Consequently, the shear stresses and contact pressure imposed by buildings change due to soil softening and impact building settlement levels (Karimi et al, 2018;Wei et al, 2020).…”