The Probability and Reliability Analyses on the SPT Methods for Soil Liquefaction Assessment
Date Issued
2011
Date
2011
Author(s)
Huang, Wei-Li
Abstract
In engineering practices, the assessment of liquefaction potential of soils is usually represented by a safety factor, in which FS<1 indicates that soil will liquefy whereas FS>1 indicates that soil will not liquefy. However, the risk of soil liquefaction resulting from earthquakes contains a lot of uncertainties in nature. Therefore, it will be more suitable if statistics and probability theory can be applied to the estimation of liquefaction potential of soils.
For this purpose, 669 domestic and international cases of SPT-N liquefaction and non-liquefaction were collected as the data base in this study. The liquefaction evaluation methods selected for study are the commonly used simplified empirical SPT-N methods, such as the Seed, Japan Road Association, Tokimatsu and Yoshimi, and Hyperbolic Function methods. The probability models applied are based on the logistic regression, the reliability-based theory, and the Bayes’ theorem, respectively. In addition, information theory is then employed to evaluate the reliability of each probability model. Meanwhile, the variation and relative conservatism between models were compared, and the applicability of each model in each evaluation method was also investigated. The results showed that the reliability and applicability of the four probability models were excellent, in which the Seed and HBF methods had a better performance. As for the reliability of different probability models, the one based on the logistic regression was the highest.
For this purpose, 669 domestic and international cases of SPT-N liquefaction and non-liquefaction were collected as the data base in this study. The liquefaction evaluation methods selected for study are the commonly used simplified empirical SPT-N methods, such as the Seed, Japan Road Association, Tokimatsu and Yoshimi, and Hyperbolic Function methods. The probability models applied are based on the logistic regression, the reliability-based theory, and the Bayes’ theorem, respectively. In addition, information theory is then employed to evaluate the reliability of each probability model. Meanwhile, the variation and relative conservatism between models were compared, and the applicability of each model in each evaluation method was also investigated. The results showed that the reliability and applicability of the four probability models were excellent, in which the Seed and HBF methods had a better performance. As for the reliability of different probability models, the one based on the logistic regression was the highest.
Subjects
soil liquefaction
logistic regression
reliability
the Bayes’ theorem
information theory
Type
thesis
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