In this paper, a new SPT-based simplified method, MaxSRP, for assessing the liquefaction potential, probability and associated damages is established. The assessment model is developed using the method of information theory and the results of logistic regression. The performance of the model is better than that of other simplified methods such as Seed method because of the higher success rate of prediction (87%), wider range of application, consistency of evaluation process for damages evaluation, and inclusion of the experiences from the 921 Chi-Chi earthquake. In this model, relationships between the calculated factors of safety (FS) and probability of liquefaction (P(subscript L)) are calibrated using the logistic mapping approach and Bayesian mapping approach. Damage indices, including reduction factor of soil (D(subscript E)), liquefaction potential index (I(subscript L)), are also revised and proposed for the new simplified method. A design chart for soil improvement based on liquefaction probability is also prepared. The newly developed model provides a method to assess liquefaction probability by factors of safety easily, and forms a basis for risk-based evaluation of liquefaction potential and damages quantitatively and consistently. Applying these concepts and results can be beneficial for the engineering community.
In this paper, a new SPT-based simplified method, MaxSRP, for assessing the liquefaction potential, probability and associated damages is established. The assessment model is developed using the method of information theory and the results of logistic regression. The performance of the model is better than that of other simplified methods such as Seed method because of the higher success rate of prediction (87%), wider range of application, consistency of evaluation process for damages evaluation, and inclusion of the experiences from the 921 Chi-Chi earthquake. In this model, relationships between the calculated factors of safety (FS) and probability of liquefaction (P(subscript L)) are calibrated using the logistic mapping approach and Bayesian mapping approach. Damage indices, including reduction factor of soil (D(subscript E)), liquefaction potential index (I(subscript L)), are also revised and proposed for the new simplified method. A design chart for soil improvement based on liquefaction probability is also prepared. The newly developed model provides a method to assess liquefaction probability by factors of safety easily, and forms a basis for risk-based evaluation of liquefaction potential and damages quantitatively and consistently. Applying these concepts and results can be beneficial for the engineering community.