Analytical Method for Evaluation of Coupled Responses of a Multidirectionally Loaded Pile-Raft Foundation Induced by Tunnelling in Layered Soils

The tunnelling effect on a pile-raft foundation is usually studied in either the horizontal or vertical direction separately, while, in practice, the responses of a pile-raft foundation induced by tunnelling in the horizontal and vertical directions occur simultaneously. Typically, a pile-raft foundation is usually loaded by vertical and horizontal loads and moments when a tunnel is constructed. Since little effort has been conducted to evaluate the coupled responses of multidirectionally loaded pile-raft foundations subjected to tunnelling, a modified two-stage method is proposed in this paper to evaluate the coupled responses of a multidirectionally loaded pile-raft foundation in layered soil. After careful verification of the method, a parametric study was carried out to evaluate whether it is necessary to consider the influences of tunnelling on a loaded pile-raft foundation from the design stages. Our study showed that it is more necessary to consider the influence of tunnelling on a pile-raft foundation when the working load on the pile-raft foundation is small. When there was only a vertical load working on the raft, the horizontal deformation and the rotation of the raft, as well as any horizontal deformation and moment along the piles, were controlled by tunnelling

Intelligent Prediction of Maximum Ground Settlement Induced by EPB Shield Tunneling Using Automated Machine Learning Techniques

Predicting the maximum ground subsidence (Smax) in the construction of soil pressure balanced shield tunnel, particularly on soft foundation soils, is essential for safe operation and to minimize the possible risk of damage in urban areas. Although some research has been done, this issue has not been solved because of its complexity and many other influencing factors. Due to the increasing accuracy of machine learning (ML) in predicting surface deformation of shield tunneling and the development of automated machine learning (AutoML) technology. In the study, different ML prediction models were constructed using an open source AutoML framework. The prediction model was trained by the dataset, which contains 14 input parameters and an output (i.e., Smax). Different AutoML frameworks were employed to compare their validities and efficiencies. The performance of the model is estimated by contrasting the prediction accuracy parameters, including root mean square error (RMSE), mean absolute error (MAE) and determinant coefficient (R2).With a coefficient of determination (R2) of 0.808, MAE of 3.7, and RMSE of 5.2 on the testing dataset, the best prediction model i.e., extra tree regressor showed better performance, proving that our model has advantages in predicting Smax. Furthermore, the SHAP analysis reveal that the soil type (ST), torque (To), cover depth (H), groundwater level (GW), and tunneling deviation have a significant effect on Smax compared to other model inputs

Intelligent Prediction of Maximum Ground Settlement Induced by EPB Shield Tunneling Using Automated Machine Learning Techniques

Predicting the maximum ground subsidence (Smax) in the construction of soil pressure balanced shield tunnel, particularly on soft foundation soils, is essential for safe operation and to minimize the possible risk of damage in urban areas. Although some research has been done, this issue has not been solved because of its complexity and many other influencing factors. Due to the increasing accuracy of machine learning (ML) in predicting surface deformation of shield tunneling and the development of automated machine learning (AutoML) technology. In the study, different ML prediction models were constructed using an open source AutoML framework. The prediction model was trained by the dataset, which contains 14 input parameters and an output (i.e., Smax). Different AutoML frameworks were employed to compare their validities and efficiencies. The performance of the model is estimated by contrasting the prediction accuracy parameters, including root mean square error (RMSE), mean absolute error (MAE) and determinant coefficient (R2).With a coefficient of determination (R2) of 0.808, MAE of 3.7, and RMSE of 5.2 on the testing dataset, the best prediction model i.e., extra tree regressor showed better performance, proving that our model has advantages in predicting Smax. Furthermore, the SHAP analysis reveal that the soil type (ST), torque (To), cover depth (H), groundwater level (GW), and tunneling deviation have a significant effect on Smax compared to other model inputs

Correction: Hussaine, S.M.; Mu, L. Intelligent Prediction of Maximum Ground Settlement Induced by EPB Shield Tunneling Using Automated Machine Learning Techniques. <i>Mathematics</i> 2022, <i>10</i>, 4637

The authors wish to make the following corrections to this paper [...

Impact of Seepage on the Underground Water Level in a Complex Soil-Water-Structure System

The antifloating design of underground structures is very important in areas with high underground water levels, and reasonable evaluation of the buoyancy is based on accurately describing the distribution of the groundwater level. However, the natural groundwater flow would be disturbed by the structure, which is not considered in the antifloating design. In the present paper, the influence of the width of an underground structure on the groundwater level in homogeneous soil is investigated through an indoor physical model test in the first place, which serves as a benchmark for the numerical simulation. Then, the parametrical study is carried out with numerical simulation. The results show that the width of the structure has the greatest influence on the water level around the structure, followed by the influence of the insertion depth, whereas the length has little influence. The hydraulic gradient has a significant effect on that as well. Moreover, the hydraulic conductivity ratio between different soil layers also affects the water level magnitude. Based on the results, a prediction method for the groundwater level around the structure for both homogeneous soil and multilayer soil has been developed and evaluated

Hybrid Approach for Rigid Piled-Raft Foundations Subjected to Coupled Loads in Layered Soils

This paper proposes an efficient hybrid approach for analysis of the responses of piled-raft foundations subjected to coupled loads (combination of vertical loads, horizontal loads, and moments) in layered soils. The proposed method comprehensively accounts for pile–pile, pile–soil surface, soil surface–pile, and soil surface–soil surface interactions. Moreover, to capture the influence of embedment and active/passive effects of piles, a modified Vesic’s subgrade modulus for embedded piles and passive piles was adopted. To avoid a large number of time-consuming integration processes, the shear displacement method and elastic foundation beam method were employed to calculate the vertical and horizontal responses of a single pile, respectively, and the results were then extended for the pile group. The results calculated with the proposed method for piled-raft foundations in layered soils were found to have good agreement with those obtained from the more rigorous finite-element methods (FEMs) and elastic theory method in layered soils. It was found that the proposed procedure can accurately predict the responses of piled-raft foundations under complex loads in layered soils

Buoyancy Force Acting on Underground Structures considering Seepage of Confined Water

The antifloating property of underground structures in areas with high underground water levels is a key design aspect. Evaluating the buoyancy forces acting on underground structures is complicated, particularly in the presence of confined water beneath the structures. Herein, the effects of the permeability coefficient of layered soil, hydraulic gradient, and embedment depth of the aquiclude on the buoyancy force acting on underground structures are investigated through three model tests: (1) calibration of the test system, (2) buoyancy force acting on a structure located in homogeneous soil considering vertical direction seepage, and (3) buoyancy force acting on a structure located in layered soil considering vertical seepage of confined water. The results show that the pore pressure along the structure and the buoyancy force acting on the underground structure considering seepage are greater than those obtained under hydrostatic conditions. The raising ratios of the pore pressure and buoyancy force are equal to the vertical hydraulic gradient when seepage occurs in homogeneous soil. In the presence of confined water, the raising ratio is significantly greater than the hydraulic gradient. In the cases studied herein, the raising ratio is approximately twice the hydraulic gradient. Simplified equations are proposed to calculate the buoyancy force acting on underground structures considering the vertical seepage of confined water. Finally, a finite element analysis is carried out to verify the conclusions obtained from the model test and the rationality of the proposed equations