| The objective of this research is to develop simplified CPT-based methods for evaluating liquefaction potential and liquefaction induced damaging effect. First, a relatively large database consisting of CPT measurements and field liquefaction performance observations in historical earthquakes is analyzed, and from which a simplified model to assess the liquefaction resistance of soils is developed using the artificial neural network approach. Based on this deterministic model, probabilistic analyses of the cases in the database are conducted using the Bayesian mapping approach. The results of the probabilistic analyses, expressed as a mapping function, provide a simple means for probability-based evaluation of liquefaction potential. Secondly, the simplified method is compared to existing CPT-based methods for evaluating liquefaction potential using case histories obtained from the 1999 Chi-Chi, Taiwan, earthquake, and it is found to compare favorably. Thirdly, 189 cases of ground performance in various seismic events are compiled. Both deterministic and probabilistic models for predicting liquefaction-induced ground failure potential using cone penetration tests are developed. These simplified models are shown to be able to explain field observations of ground failure. Finally, an empirical procedure for assessing the severity of liquefaction-induced damage at or near foundations of existing buildings is established. This procedure represents a significant attempt to address an important issue of liquefaction effect, that is, prediction of the severity of ground failure. |
