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DPT-based seismic liquefaction triggering assessment in gravelly soils based on expanded case history dataset
Abstract 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.
Highlights Extending the gravelly soil liquefaction dataset by adding new global case histories is provided solely in gravelly soils The sampling bias sensitivity analysis is applied to study its considerable effect on liquefaction triggering assessment in gravelly soils Two different probabilistic frameworks are applied to develop models The recall parameter is applied for risk assessment analysis except for extra criteria to show risk assessment of the models associated with life danger and cost in addition to the performance of the models to predict liquefaction occurrence.
DPT-based seismic liquefaction triggering assessment in gravelly soils based on expanded case history dataset
Abstract 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.
Highlights Extending the gravelly soil liquefaction dataset by adding new global case histories is provided solely in gravelly soils The sampling bias sensitivity analysis is applied to study its considerable effect on liquefaction triggering assessment in gravelly soils Two different probabilistic frameworks are applied to develop models The recall parameter is applied for risk assessment analysis except for extra criteria to show risk assessment of the models associated with life danger and cost in addition to the performance of the models to predict liquefaction occurrence.
DPT-based seismic liquefaction triggering assessment in gravelly soils based on expanded case history dataset
Pirhadi, Nima (author) / Wan, Xusheng (author) / Lu, Jianguo (author) / Fang, Yu (author) / Jairi, Idriss (author) / Hu, Jilei (author)
Engineering Geology ; 311
2022-10-12
Article (Journal)
Electronic Resource
English
Recent Advances in Gravelly Soils Liquefaction Evaluation
| Trans Tech Publications | 2011