Predicting settlement of embankments built on PVD-improved soil using Bayesian back analysis and elasto-viscoplastic modelling
Shan Huang, Jinsong Huang, Richard Kelly, Merrick Jones, A.H.M. Kamruzzaman
Abstract
In this study, an implicit finite difference program, 1DFDM, based on the fully coupled one dimensional elasto-viscoplastic (1D EVP) model combining radial and vertical drainage is developed to perform consolidation analysis of embankments constructed on soft soils. Class A prediction (prior prediction) is performed by using 1DFDM for the embankment constructed on soft clay in Ballina, Australia. However, the prediction deviates significantly from the measurements, and the model parameters need to be calibrated. Bayesian back analysis is thus combined with 1DFDM in this study to do Class C prediction. Three updating schemes (using monitoring settlement only, using monitoring pore water pressure only, and using both monitoring settlement and pore water pressure) are employed to shed light on the effects of the monitoring data types on settlement prediction. The results show that the long-term settlement and pore water pressure predictions could be further improved if both the monitoring settlement and pore water pressure data are incorporated. The coupling effects in the constitutive model can reduce the fluctuations in the updated optimum parameters. A stable and physically reasonable parameter set could be obtained if enough monitoring data is incorporated into the Bayesian back analysis.