Predictive model for seismic displacements of flexible sliding block subjected to near-fault pulse-like ground motions

A post investigation of landslides induced by strong earthquake events in recent years shows that near-fault pulse-like ground motions have a considerable impact on slopes. Accurate evaluation of the stability of slopes under near-fault earthquakes has become a crucial issue in seismic-prone areas. Permanent displacement is widely recognized as an effective index for evaluating the stability of slope. Based on the coupled analysis, an empirical earthquake-induced permanent displacement prediction model was developed. A displacement database of 318 pulse-like ground motions from 50 earthquake events was established. The proposed predictive model is a function of the maximum seismic coefficient-time history (k(max)), maximum velocity coefficient of velocity-time history of the k-time history (k(v-max)), yield acceleration (k(y)), and period ratio (ratio of the natural period of the slope to the mean period of input motion, T-s/T-m). The dynamic responses (k(max )and k(v-max)) are represented by two different functions. At small period ratios (T-s/T-m=1.8), it is a function of peak ground acceleration (PGA), peak ground velocity (PGV) and k(y). At large period ratios (Ts/Tm > 1.8), it is a function of PGV, T-s and k(y). It successfully captured the velocity pulse and long period characteristics of pulse-like ground motions. Compared to the existing model, it is found that the model is more accurate when considering pulse-like ground motions. This prediction model can be used not only for the preliminary evaluation of slope stability but also for probabilistic seismic demand analysis of flexible slopes considering pulse-like ground motion in near-fault regions.

Automated summary

A post investigation shows that near-fault pulse-like ground motions have a significant impact on slope stability under earthquakes. Therefore, an empirical earthquake-induced permanent displacement prediction model was developed based on a displacement database of 318 pulse-like ground motions. The model considers factors such as seismic coefficient, velocity coefficient, yield acceleration, and period ratio, successfully capturing the characteristics of pulse-like ground motions. Compared to existing models, this prediction model shows higher accuracy in considering pulse-like ground motions and can be used for slope stability evaluation and seismic demand analysis in near-fault regions.