DPT-based seismic liquefaction triggering assessment in gravelly soils based on expanded case history dataset

The gravelly soil liquefaction caused by earthquake motions has been observed and reported in different regions in the world. However, few studies have been conducted to develop models for its prediction and risk assessment. Furthermore, the single available model was developed merely based on one case history earthquake. Thus, to bridge this gap in research, this study first created a comprehensive database of dynamic penetration test (DPT) using the documentation of eight global earthquakes, which includes a considerable variation of earthquake magnitudes, the frequencies of motions, epi-central distance, geometry type, deposit layering, gravelly soil depth, geometry type, and soil properties. Then, a deterministic model was developed to estimate the cyclic strength ratio (CRR) to estimate the safety factor (SF) against liquefaction triggering. Then, to account for uncertainties in the estimations of parameters and model prediction, Bayesian mapping function and logistic regression were applied to develop probabilistic models to classify liquefied and non-liquefied regions for liquefaction occurrence prediction. The maximizing likelihood function was used to calculate the model's parameters. The effect of the bias sampling factor was surveyed via supposing a range of variation for its value to discover its decent value. To validate the presented models, they were compared to the existed model. The results were studied via two issues, as a capability that shows the accuracy of the model's prediction and a risk issue via a recall index.