Developing region-specific fragility function for predicting probability of liquefaction induced ground failure. (January 2023)

• Record Type: Journal Article
• Authors: Ge, Yixun; Zhang, Zechao; Zhang, Jie; Huang, Hongwei
• Is Part Of: Probabilistic engineering mechanics. Volume 71(2023)
• Publication Date: 2023-01
• Subjects: Soil liquefaction -- Model uncertainty -- Failure probability -- Hierarchical Bayesian Model; Engineering -- Statistical methods -- Periodicals; Mechanics, Applied -- Statistical methods -- Periodicals; Probabilities -- Periodicals; Ingénierie -- Méthodes statistiques -- Périodiques; Mécanique appliquée -- Méthodes statistiques -- Périodiques; Probabilités -- Périodiques; 620.100727
• DOI: 10.1016/j.probengmech.2022.103381
• Languages: English
• ISSNs: 0266-8920

Abstract

Abstract: The liquefaction potential index (LPI) has been widely used to develop fragility function for predicting the liquefaction-induced ground failure. As the fragility function tends to vary from one region to another, it is best developed based on region-specific data. When the amount of region-specific data is limited, how to develop the region-specific fragility curve is a challenging problem. In this study, a Hierarchical Bayesian Model (HBM) is suggested for developing region-specific fragility functions based on LPI, which can systematically consider the effects of the amount and characteristics of the local data as well as the data from other regions. The suggested method is illustrated with an example. It is shown that the HBM outperforms the lumped parameter model (LPM) which does not consider the inter-region variability of the fragility curves. When the amount of region-specific data is large, the fragility function developed based on the HBM is very close to that developed based on the independent parameter model (IPM), which constructs a region-specific fragility function utilizing only the region-specific data. When the region-specific data is not enough, the HBM also outperforms the IPM through borrowing information from other regions.