The constitutive model is essential for predicting the deformation and stability of rock-soil mass. The estimation of constitutive model parameters is a necessary and important task for the reliable characterization of mechanical behaviors. However, constitutive model parameters cannot be evaluated accurately with a limited amount of test data, resulting in uncertainty in the prediction of stress-strain curves. This paper proposes a Bayesian analysis framework to address this issue. It combines the Bayesian updating with the structural reliability and adaptive conditional sampling methods to assess the equation parameter of constitutive models. Based on the triaxial and ring shear tests on shear zone soils from the Huangtupo landslide, a statistical damage constitutive model and a critical state hypoplastic constitutive model were used to demonstrate the effectiveness of the proposed framework. Moreover, the parameter uncertainty effects of the damage constitutive model on landslide stability were investigated. Results show that reasonable assessments of the constitutive model parameter can be well realized. The variability of stress-strain curves is strongly related to the model prediction performance. The estimation uncertainty of constitutive model parameters should not be ignored for the landslide stability calculation. Our study provides a reference for uncertainty analysis and parameter assessment of the constitutive model.

Soft clays exhibit significant challenges in geotechnical engineering due to their low permeability, high compressibility, and susceptibility to settlement under applied loads. These geological factors pose unique difficulties in predicting long-term settlement accurately and efficiently, particularly through Class C prediction methods that involve iterative processes with complex numerical models. To address these challenges, this study presents an efficient approach for Class C prediction of long-term settlement in soft clays. This approach integrates Bayesian updating with structural reliability methods (BUS) and the general simplified Hypothesis B method which is a semi-analytical method based on one-dimensional elastic visco-plastic (1D EVP) model. Unlike previous research that used Response Surface Model (RSM) with polynomial function for consolidation evaluation, the proposed approach enhances both accuracy and performance consistency under varying conditions. Additionally, by leveraging analytical solutions instead of iterative small-time steps required by Finite Element Method (FEM) or Finite Difference Method (FDM), the computational efficiency is also enhanced. The effectiveness of the proposed approach is demonstrated through its application to an embankment improved with prefabricated vertical drain (PVD) in Ballina, New South Wales, Australia. Comparative analyses demonstrate that the predicted settlements from this study, using only the monitoring settlement data collected prior to the 76th day of the project, align closely with the results from established RSM and FEM-based Bayesian back analysis approaches. The obtained results also indicate that the predicted settlements, based on 76 days of monitoring data, closely match field measurements at various depths, whether relying solely on settlement data or integrating additional pore water pressure data. For the Ballina embankment, over 40,000 consolidation analyses required for a single BUS simulation can be completed within 10 h using the general simplified Hypothesis B method, compared to months it might take with FEM or FDM approaches. This makes the proposed approach a practical tool for geotechnical engineers, enabling reliable settlement predictions early in the project timeline while maintaining low computational costs.

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.

A novel method for back analysis was used for an embankment over deep soft soil along a major highway upgrade between Woolgoolga and Ballina, NSW. Bayesian back analysis was undertaken using monitored settlement data. The key parameters of interest were the compression ratio, recompression ratio, creep strain rate and coefficient of vertical and horizontal consolidation. Posterior distributions were sampled using a multi-chain Monte Carlo algorithm through a likelihood function to estimate the updated model parameters and subsequent settlement prediction. The simplified geotechnical model, incorporating parameter ratios, can be shown to reduce the amount of computational time required. The predictions were shown to converge to the field measurements regardless of some assumptions made about measurement error and aided in providing a more consistent prediction based on the available data. The intent of the study was to demonstrate that key geotechnical parameters can be updated, and settlement predictions revised and verified from limited site investigation data using Bayesian back analysis incorporating monitored surface settlement data.

Rapid and partial acquisition are features of rock drilling for obtaining rock properties. Most previous research has primarily concentrated on how to quickly obtain rock mechanics parameters, with limited emphasis on extracting rock parameter fields, particularly in three dimensions. This study attempted to develop a numerical integrated method to extract 3D parameter fields of rocks based on a newly developed digital-controlled drilling platform. The importance of incorporating a damage model for accurate simulations of rock drilling through finite element analysis (FEA) was investigated. By calibrating damage parameters through uniaxial compressive strength (UCS) and Brazilian tensile strength (BTS) tests, these parameters can be considered constants in rock drilling simulations across various rock types. The accuracy of rock parameters estimated by the proposed method and the derived analytical model were further demonstrated through comparison with the corresponding standard tests. Furthermore, the 3D parameter field of rocks was obtained by integrating a deep learning method and micro-CT technology. The numerical prediction illustrated the advantages of acquiring a rock parameter field in achieving more accurate simulations of the rock failure process. Besides, our solution can also provide support for the parameter selection of numerical models considering spatial variability for natural rocks. A digital-controlled equipment for rock drilling was developed.Equations were derived for extracting rock parameters through the drilling data.A deep learning method was developed to reproduce the three-dimensional parameter field of rocks.The significance of considering the realistic rock parameter field was numerically demonstrated.

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.

Chiaia station is one of the art stations of Line 6 of the Naples underground network; it was constructed in a 50-m-deep excavation, a few meters from historic buildings and 4.5 m from the main facade of a sixteenth-century Basilica. The excavation, carried out partially in loose to medium dense sands overlying the soft rock formation of Neapolitan Yellow Tuff (NYT), was supported by a retaining wall made of contiguous bored piles braced with internal struts and prestressed ground anchors. The excavation sequence was quite complex due to archeological findings and to the presence of anthropic cavities used over the centuries to quarry NYT blocks. One of the key goals of the design was to limit movements around the shaft to prevent damage in the historical buildings. Long-term monitoring data obtained during nearly 9 years confirm the success of the overall construction process. A rather complex three-dimensional (3D) finite-element model with constitutive relationships for both the upper sandy layers and the soft rock is presented in the paper; this model was adopted to back-analyze the data from the monitoring and explore the influence of some of the key features of the case study. The role of the building bending and shear stiffness, of the soft rock stiffness, and of further apparently minor issues-such as the seepage and the ground anchors' prestress-were investigated and discussed with the support of the model calculations. Observed settlements at the end of the excavation were in the range 10-15 mm, and in the long term they increased by 20%-50% to as much as 20 mm. The deflection ratios were very small, in the range 0.05 parts per thousand-0.15 parts per thousand, and no visible damages to the buildings were recorded. These values were reproduced by the finite-element model only after the introduction of the relevant building stiffness.

Landslides govern the evolution of landforms and pose a serious threat across the globe, especially in mountainous areas. In the northwestern area of Vietnam, a slow -moving landslide occurred near an important economic road corridor in Caumay Ward, Sapa Town, Laocai Province. In December 2019, some serious cracks were observed at a construction site near this landslide. Since this phenomenon could cause not only loss of life but also damage to the properties located downhill, the construction was abandoned until the slope was rehabilitated. Geological investigations, laboratory tests, and surface displacement monitoring were conducted to understand the failure mechanism. The analysis results showed that the anthropogenic activities associated with the rising groundwater level due to frequent rainfall events, owing to climate change, had contributed to the sliding of the sloping soil mass. The rehabilitation works at the failed area were conducted chronologically in two stages: (1) backfilling at the downhill area; demolishing two villas located within the sliding area to reduce surcharge; constructing an anchor system in the uphill area, and (2) constructing the anchored wall at the downhill area. During the rehabilitation works, the Caumay landslide was observed to initially undergo gradual movement and then stabilize at the end of the first stage of the rehabilitation works. The rehabilitation techniques adopted at the failed site were validated using both numerical analysis and field measurements. The anchor reinforcement methodology adopted in this study is expected to help agencies and the public in stabilizing landslide -prone areas for residential and other infrastructure construction.

As a critical urban infrastructure, the subway station damaged in an earthquake not only leads to interruption of underground transportation, but may also result in serious casualties and economic losses. The current seismic design of underground structures only considers the mainshock effects but ignores the potential hazards of aftershocks. However, most mainshocks are often followed by aftershocks in a short period of time. In the past earthquakes, it was reported that the mainshock-damaged engineering structures suffered more serious structural damage and even complete collapse when subjected to aftershocks before restoration. This paper proposes a framework for the development of seismic fragility curves of underground structures subjected to sequence-type ground motions. Finite element models of a two-story, three-span subway station considering nonlinear dynamic soil-structure interaction (SSI) was established in this study. A comprehensive assessment of the seismic performance of the subway station structure under the sequence-type ground motions was conducted on the SSI model. Both the mainshock-aftershock fragility analysis of the intact structure and the aftershock fragility analysis of the mainshock-damaged structures were performed by combining the traditional seismic probability demand model and the back-to-back mainshock-aftershock probability demand model. The numerical results indicated that the impact of aftershocks on the seismic performance of subway station structures cannot be ignored. The aftershock fragility of the structure is highly dependent on the mainshock-damaged state. The failure probability of a severely mainshock-damaged subway station structure is much higher in the aftershocks than structures in other damage states. Besides, the probability of the mainshock-damaged structure transferring to a more severe level of damage state increases with the increase of the intensity of aftershock motions. For the subway station under sequence-type ground motions, the transition probability of one severer level of damage state is greater than 40 % for the 1.0 g peak ground acceleration of aftershocks and the transition probability of more than two severer level of damage state is less than 10 %.

In response to the problem of significant post-construction settlement that may occur in a motor racing circuit (MRC), two representative composite foundation testing areas, PHC pile (pre-tensioned spun high-strength concrete pile) and CFG pile (cement fly ash gravel pile), were selected for field tests to obtain the deformation law of pile-soil. Then, finite element numerical simulation was used to carry out back analysis on the geological mechanical parameters of the testing areas. The results showed that the error of soil settlement between the piles in the PHC pile and CFG pile testing areas were 8.2% and 9.6%, respectively, with good inversion precision. The obtained geological mechanical parameters can be used to predict the settlement of the rest of the MRC. On this basis, a finite element numerical model was constructed to analyze the bearing and deformation characteristics of the foundation of the MRC under five types of working conditions that may cause significant post-construction settlement. It showed that the settlement of the embankment was large in the middle and small on both sides after the consolidation of the embankment. The maximum settlement was about 27.0 mm, and the maximum longitudinal uneven settlement ratio of the embankment was 1.3/4000. The axial force of piles in the PHC pile and CFG pile composite foundations increased first and then decreased with depth. The maximum bending moment was located at the foot of slopes or at the boundary of strata, which was relatively small in the middle of the embankment. The deformation of the embankment and the bearing capacity of the piles could meet engineering requirements. This study has certain guiding significance for the design and construction of similar pile-net composite foundations.