Probabilistic analysis for large strain radial consolidation of soft soils considering creep

Abstract

Effective design of prefabricated vertical drains (PVDs) requires accurate prediction of soil consolidation behavior incorporating creep and spatial variability in soil properties. This study develops a probabilistic analysis framework that integrates random field theory, the piecewise-linear method, and Monte Carlo simulation to evaluate the long-term consolidation of soft soils with PVDs. The framework accounts for spatial variability in soil parameters, creep strain, large-strain effects, hydraulic conductivity anisotropy, soil smear, and time-dependent loading. Three routinely measured soil parameters, including plasticity index, liquid limit, and void ratio, are treated as random variables. The proposed method is validated through comparison with field measurements from a preloaded embankment site along the Sydney-Newcastle Freeway extension equipped with PVDs. Results show that the field data align closely with the high-probability density predictions from the probabilistic analy-sis. Sensitivity analysis indicates that increasing the coefficient of variation leads to an almost linear widening of the estimated range, while autocorrelation distances and cross-correlation coefficients exert a relatively minor influence on consolidation be-havior. These findings highlight the importance of accurately estimating the coefficient of variation in a cost-effective manner during field investigations and statistical analysis.