In uncoupled consolidation analysis, settlement and pore water pressure are solved independently, whereas in coupled analysis, they are solved simultaneously to ensure continuity (i.e., the volume change in soil due to compression must equal the water volume change caused by dissipation). This study investigates the coupling effects of soil deformation and pore water pressure dissipation in the back analysis of soft soil settlements. It further evaluates the suitability of both coupled and uncoupled constitutive models with different types of monitoring data, providing practical guidance for selecting consolidation models and achieving reliable long-term predictions. The one-dimensional governing equations for soft soil consolidation, incorporating prefabricated vertical drains and creep deformation, are first reviewed. A case study of a trial embankment in Ballina, New South Wales, Australia, is then used to demonstrate the impact of coupling effects and monitoring data on settlement predictions. The results show that considering coupling effects not only improves long-term settlement predictions but also reduces uncertainties in the updated soil parameters, especially when both settlement and pore water pressure data are used.

When analyzing the engineering characteristics of pile-supported embankments in deep soft soil regions, the creep behavior of soft soils cannot be overlooked. In previous numerical analyses, empirical formulas were often used to determine related parameters, which limited the accuracy of the calculations. This study validated the reliability of the soft soil creep (SSC) model using measurement data and proposed an optimized process for SSC parameter selection, aiming to improve both accuracy and practical applicability. A numerical model was established based on actual engineering to study the effects of different pile lengths and spacing on settlement, soil arching, and reinforcement material stress. Key findings include as follows: (1) The SSC model outperforms the Mohr-Coulomb and soft soil models in predicting settlement and stress concentrations. (2) An optimized SSC parameter selection process is proposed, providing reference values for typical soft soils in Zhejiang, China. (3) Settlement increases significantly when pile spacing exceeds 2.8 m in this project, suggesting the existence of a threshold effect of pile spacing on settlement. (4) Increasing pile length reduces differential settlement and the tensile force on reinforcement material, with differential settlement decreasing from 0.268 to 0.114 mm and tensile force dropping from 106 to 89 kN/m as pile length increases from 24 to 30 m. This finding shows the importance of balancing pile length and reinforcement material strength, which can reduce project costs while ensuring the stability and quality of the embankment. This study provides a theoretical basis for the design of pile-supported reinforced embankments in soft soil regions.

The prediction of time-dependent deformations of embankments constructed on soft soils is essential for preloading or surcharge design. The predictions can be obtained by Bayesian back analysis methods progressively based on measurements so that practical decisions can be made after each monitoring round. However, the effect of creep is typically ignored in previous settlement predictions based on Bayesian back analysis to avoid the heavy computational costs. This study aims to fill this gap by combining the Bayesian back analysis with a decoupled consolidation constitutive model, which accounts for creep to perform long-term settlement predictions of the trial embankment with prefabricated vertical drains (PVDs) constructed in Ballina, Australia. The effect of creep on settlement predictions is illustrated by the comparisons of the cases with and without considering creep. The results show that good settlement predictions could be obtained if creep is ignored and could be further improved if creep is incorporated when the monitoring settlement data is applied in the Bayesian back analysis. Ignoring creep could lead to an underestimation of the ultimate consolidation settlement. The swelling index kappa and the compression index lambda need to be adjusted to larger values to match the measurements if creep is ignored. Four updating schemes (using surface settlement data only, using settlement data at all monitoring depths, using pore water pressure data only, and using both settlement and pore water pressure data) are applied to study the effects of monitoring data on the accuracy of settlement prediction. The results show that the variability introduced by the noisy pore water pressure data result in fluctuating settlement predictions. Incorporating both settlement and pore water pressure observations into the Bayesian updating process reduces the variability in the updated soil parameters.