Modelling of probability liquefaction based on standard penetration tests using the jointly distributed random variables method

Soil liquefaction during an earthquake can be a major cause of damage to structures. The inherent variability of the soil parameters which affect liquefaction potential dictates that the problem is of a probabilistic nature rather than being deterministic. Probabilistic assessment of liquefaction potential has received considerable attention in the past few years. In this research, the Jointly Distributed Random Variables (JDRV) method is used as an analytical method to develop a model for probability of liquefaction potential based on standard penetration tests. The selected stochastic parameters are corrected SPT blow count and stress reduction factor, which are modeled using a truncated normal probability density function and the peak horizontal earthquake acceleration ratio and earthquake magnitude, which are considered to have a truncated exponential probability density function. The depth of water table and fines content are regarded as constant parameters. The results of JDRV method are verified with those of the Monte Carlo simulation. It is shown that the moment magnitude is the most effective parameter in soil liquefaction potential. Comparison of the model results indicates reasonable performance of the proposed approach in assessment of probability of liquefaction and empirical data.