Maximum Ground Surface Settlement Research Articles

Prediction of ground surface settlements by analytical and finite element methods

The soil surrounding the excavation of shallow tunnels may experience destructive deformation near the tunnels. Particularly in densely populated areas where land resources are scarce, ground subsidence caused by tunnel excavation, which in turn affects surrounding structures, deserves more attention. Over the past few decades, various research methods for predicting the maximum vertical ground surface settlement have been proposed. In this study, an empirical estimation method, an analytical technique for evaluating ground movements, and a numerical simulation method using Plaxis 2D, a finite element model software, were selected as prediction approaches for ground surface settlements. Subsidence measurements were obtained from a metro tunnel excavated using an earth pressure balance shield tunnel boring machine and constructed in a dense sandy gravel layer. Comparison of the monitored deformations with the estimation results calculated by different prediction approaches showed that the maximum vertical settlement of the ground surface evaluated by the analytical technique and finite element model agreed well with the actual measured values. This suggests that these two prediction methods have the potential for conserving nearby structures during the construction of underground infrastructures.

Deterministic and probabilistic analysis of great-depth braced excavations: A 32 m excavation case study in Paris

The Fort d’Issy-Vanves-Clamart (FIVC) braced excavation in France is analyzed to provide insights into the geotechnical serviceability assessment of excavations at great depth within deterministic and probabilistic frameworks. The FIVC excavation is excavated at 32 m below the ground surface in Parisian sedimentary basin and a plane-strain finite element analysis is implemented to examine the wall deflections and ground surface settlements. A stochastic finite element method based on the polynomial chaos Kriging metamodel (MSFEM) is then proposed for the probabilistic analyses. Comparisons with field measurements and former studies are carried out. Several academic cases are then conducted to investigate the great-depth excavation stability regarding the maximum horizontal wall deflection and maximum ground surface settlement. The results indicate that the proposed MSFEM is effective for probabilistic analyses and can provide useful insights for the excavation design and construction. A sensitivity analysis for seven considered random parameters is then implemented. The soil friction angle at the excavation bottom layer is the most significant one for design. The soil-wall interaction effects on the excavation stability are also given.

Deformation characteristics of excavation supported by prefabricated recyclable structures

With the development of urban underground space, green and efficient excavation supporting structures are receiving increasing attention. Prefabricated recyclable supporting structures (PRSSs) have been developed for this reason. A deep circular excavation supported by PRSSs in low-plasticity clay (CL) was extensively instrumented to explore its deformation characteristics. Measurement results showed that the lateral displacement of the supporting piles (δhp) presented a typical cumulative pattern dominated by deep inward movement. The maximum lateral displacements of the supporting piles (δhpm) varied between 0.28%H–0.52%H (H is the excavation depth). The maximum lateral pile displacements mostly occurred above the excavation surface, ranging from H + 0.5 m to H − 7.0 m. The soils 3 m and 10 m from the excavation had the largest lateral displacement at the top and a cantilever shape. The ground surface settlements tended to follow a convex pattern. The maximum ground surface settlements (δvm) were normalised by the final excavation depth (He) on the east and south sides, and determined to be 0.43% and 0.50%, respectively. The ratio δvm/δhpm tended to increase as excavation and dewatering proceeded, with a value of 0.49–1.15. The ground surface settlement due to dewatering was 19% of the maximum settlement.

PSO-based Machine Learning Methods for Predicting Ground Surface Displacement Induced by Shallow Underground Excavation Method

Four hybrid intelligent methods are developed to predict the maximum ground surface settlement (Smax) induced by shallow underground excavation method (SUEM). Particle swarm optimization (PSO) algorithm with k-fold cross validation is used to determine the optimal hyperparameters or random parameters in the four machine learning (ML) methods, namely that, back-propagation neural network (BPNN), extreme learning machine (ELM), support vector regression (SVR) and random forest (RF). 100 field engineering samples are collected from published papers. In each data sample, the effect of stratum mechanical conditions, tunnel geometric parameters and construction parameters on Smax is considered. Correlation laws among parameters are investigated through Pearson correlation coefficient, data distribution histogram and correlation confidence ellipse. The performance of four PSO-based ML methods is comprehensively compared by fitness function, time cost and prediction accuracy in the training and test processes. PSO-RF outperforms PSO-SVR, PSO-ELM and PSO-BPNN in the prediction accuracy for Smax owing to larger R2, smaller MAE and RMSE. Calculation time that the optimal hyperparameters are determined is the fastest for PSO-RF, and PSO-ELM has the smallest fitness function. The prediction performance of PSO-RF method for construction parameters is also discussed. This work can provide theoretical guidance for design and construction of SUEM.

Model test and numerical simulation of a new prefabricated double-row piles retaining system in silty clay ground

This paper introduces a new prefabricated recyclable double-row piles retaining system for excavations in silty clay ground. Laboratory model test and numerical simulation are conducted to study the system behavior upon excavation. The horizontal displacement (δh), Von Mises stress (σM), strain (ε), ground surface settlement (δv), and earth pressure are systematically investigated. Furthermore, the monitoring data of 13 excavation cases supported by double-row piles retaining system are presented and discussed. The experimental results can basically match the numerical results, and the maximum σM, maximum bending moment (Mmax), maximum horizontal displacement (δhm) of structural members are all less than the tolerance limits. The ground surface settlement model of double-row piles retaining system consists of three zones, i.e., rebound influence zone, primary influence zone and secondary influence zone. The δhm values are 0.07%–1.42% of the excavation depth (He). The maximum ground surface settlement (δvm) is generally less than δhm. The ratio of δvm/δhm varies between 0.09 and 0.76, with an average value of 0.5. The observed earth pressure on the retained side of front pile (paf) is about 0.53–0.57 γH below the excavation surface. Above the excavation surface, paf decreases dramatically when getting closer to the ground surface.

Estimating Maximum Surface Settlement Caused by EPB Shield Tunneling Utilizing an Intelligent Approach

To control tunneling risk, the prediction of the surface settlement rate induced by shield tunneling using earth pressure balance plays a crucial role. To achieve this, ten independent variables were identified that can affect the amount of settlement. The nonlinear relationship between maximum ground surface settlements and ten influential independent variables was considered in artificial neural network (ANN) models. A total of 150 genuine datasets derived from the Southern Development Section of the Tehran Metro Line 6 project were used to train, validate, and test ANN techniques. Hence, the ground surface settlements of the mentioned project were predicted by the most accurate back propagation ANN technique. Ultimately, the importance level of different influential parameters on ground settlement at tunneling is relatively determined based on the results of the optimal neural network. The results used in this paper to evaluate the relative importance of each variable involved in the rate of ground surface settlement demonstrate that the parameters of grout injection and permeability equivalent to the proportions of approximately 16.91% and 5.07% have the highest and lowest impact, successively.

Influence of disturbance degree on the propped excavation stability in sandy soil in Shenyang, China

The stability of deep excavation is often investigated through numerical simulation. However, most constitutive models cannot take into account the influence of disturbance on soil response, especially for excavations in sandy soils. In this study, the conventional Duncan–Chang constitutive model is modified based on the data obtained from a series of triaxial consolidated drained tests on medium coarse sand with different relative densities, where all input parameters in the model are correlated with the changes in relative density due to disturbance. The modified hyperbolic model is then implemented in the general-purpose finite element code, ABAQUS. The efficiency of the proposed constitutive mode is demonstrated by comparing with the experimental data. Furthermore, a case study of a large-scale propped excavation for a subway station in Shenyang is analyzed through numerical calculations with the conventional Mohr–Coulomb model and the proposed hyperbolic model, and theoretical derivations based on the current technical code in China. It is found that the proposed approach can provide reasonable estimations compared with field measurements with a maximum error of 28% for maximum horizontal displacement of the solider pile and of 8% for maximum ground surface settlement, whereas the other techniques overestimate the behaviour of deep excavation significantly by more than 90%.

Spatial-temporal fusion network for maximum ground surface settlement prediction during tunnel excavation

The maximum ground surface settlement prediction is a complex problem as the settlement depends on plenty of intrinsic and extrinsic factors. To obtain the approximate range of the settlement, a hybrid prediction dataset including the geological and construction parameters is built using spatial and temporal series according to the sampling methods. The settlement prediction task is transformed into a multi-modal and multi-variate series prediction task. Hence, a spatial-temporal fusion network (STF-Network) is proposed. The spatial-temporal fusion mechanism is firstly designed to establish the spatial-temporal fusion map, which makes spatial and temporal series interact earlier. Then, the 3D residual unit structure is designed to capture the features of temporal series and spatial-temporal fusion map, and two fully-connected layers are established to capture the spatial structural information. Finally, the final output is merged by the three components. The experimental results for STF-Network demonstrate the superiority over state-of-the-art methods.

Influence of Pipeline Leakage on the Ground Settlement around the Tunnel during Shield Tunneling

Shield tunneling is widely used in urban subway tunnel construction. Old urban underground pipelines generally have small leakages that are difficult to find. The water leakage significantly reduces the stability of the stratum, posing a threat to the safety of tunnel shield construction. Therefore, this study established 2D and 3D calculation models for analyzing the law of the leakage diffusion in the ground under water pressure, and the influences of the pipeline leakage range and leakage length on the changes in ground settlement during shield tunneling. The 2D model calculation results show that seepage water mainly diffuses vertically under gravity. As the pipeline leakage gradually reaches a predetermined depth, the simulation results tend to be consistent with the test results. The 3D model is more accurate than the theoretical solution in predicting the ground settlement because it can consider the influences of repeated disturbances in twin tunnel shield construction. The maximum ground surface settlement increases with the extent of the leakage length and leakage range, and the range is the main factor determining the settlement. At the interior of the ground, the seepage water has a greater impact on areas with strong disturbances and large soil losses.

Prediction of maximum ground surface settlement induced by shield tunneling using XGBoost algorithm with golden-sine seagull optimization

In order to avoid damage during shield tunnel construction to adjacent buildings on the ground, it is of paramount importance to precisely predict the Maximum Surface Settlement (MSS) deformation induced by shield tunneling under the surface. In this paper, a hybrid algorithm model incorporating the Extreme Gradient Boosting (XGBoost) with the Golden-sine Seagull Optimization Algorithm (GSOA) is proposed, namely the GSOA-XGBoost model. A total of 323 datasets including torque, penetration rate, thrust, cutterhead rotation speed, slurry pressure, grouting pressure, cover depth, and distance between cutting face and monitored section are taken as input parameters, and the corresponding measured MSS deformation is adopted as the output parameter. This dataset is employed to train the MSS prediction algorithm model. The analysis results indicate that the proposed GSOA-XGBoost hybrid algorithm model is much superior to other models in terms of accuracy, stability and computation time, and strong correlations are discovered between the predicted and measured settlements. Our model can predict the MSS deformation caused by shield tunnel construction with higher reliability, strong robustness and fault-tolerant capacity, and greatly reduces the engineering risk. Simultaneously, the consistency of the slurry pressure and grouting pressure values is calculated by the SOA-XGBoost and the grid search method, which demonstrates the feasibility and rationality of proposed hybrid algorithm model.

Settlement and Stress Characteristics of the Ground in the Project of a Double-Line Tunnel Undercrossing an Airport Runway in a Sandy Cobble Region

The engineering technology of undercrossing an airport flight area is relatively mature; however, the use of shield tunnels crossing the operating airport flight area in high liquidity sandy cobble stratum has rarely been reported. To discuss the feasibility of a double-line shield tunnel undercrossing the airport flight area in a sandy cobble region. Based on the case of the Chengdu Metro Line 10 that undercrosses the Shuang-Liu Airport, which is located in sandy cobble region, the deformation and stress laws of airport runway pavement structures were investigated via a three-dimensional numerical model. Stratum displacement, ground settlement and pavement tensile stress under different tunnel depths were analysed. Then, the pavement tensile stress was taken as the safety evaluation index and the vulnerable area of the pavement structure was proposed. The results show that after excavation of the double-line tunnel, the maximum ground surface settlement occurred above the tunnel centreline and the ground settlement curves presented a V-type settlement trough instead of a W-type. The existence of a runway greatly limited the deformation of the surrounding soil; with increasing depth, the effect degree of the runway pavement on the soil settlement decreased. The most unfavourable region of the runway pavement structure under the influence of tunnel excavation was found. With increasing burial depth, the maximum settlement of the surface centre point decreased continuously. It is recommended that the tunnel burial depth not exceed 23.5 m in this project. According to the displacement and stress control limitation of the airport pavement, it can be judged that the shield construction method meets the structural stability requirements of the pavement. The calculated results provide a reference for the shield tunnel construction in the same geological condition areas.

Performance of a 56 m deep circular excavation supported by diaphragm and cut-off double-wall system in Shanghai soft ground

The performance of a 56 m deep circular excavation supported by a double-wall system, consisting of an inner circular diaphragm wall and an outer rectangular cut-off wall, in Shanghai soft ground is studied in this paper. The surveyed data (e.g., lateral wall deflections ( δ h), horizontal displacement of soil ( δ s), ground surface settlement ( δ v), soil rebound ( δ v+), earth pressure ( P), pore water pressure ( Pw), and soil stress path) are systematically investigated. The results show that the maximum lateral wall deflections are 0.002% ∼ 0.03% of the excavation depth ( H e). The maximum ground surface settlement ( δ v m) is generally larger than δ h m, which is located at 0.4 ∼ 0.6 H e. Moreover, an innovative formula is proposed to estimate the ground settlement. It is able to distinguish various characteristics of surface settlement in different zones of the settlement profile. The ground surface settlements are mainly induced by surcharge loading and continuous excavation, and they are related to the change in confined water level. The lateral earth and pore water pressures in the active zone are relatively insensitive to the excavation, while the correlation becomes obvious in the passive zone. The findings from this study can be helpful to the design of other similar deep excavations in soft clay.

Theoretical Analysis on the Effectiveness of Pipe Roofs in Shallow Tunnels

When a pipe roof is used as a pre-support for the surrounding rock in a shallowly buried tunnel, accurate prediction of the support effectiveness of the pipe roof is important in order to ensure the rationality of the pipe roof structure design. Based on analysis of pipe roof pre-support effects, considering the construction time of pipe roof structures and the interaction mechanisms between the steel pipes of the pipe roof and the surrounding rock, we establish a calculation model of the surrounding rock pressure acting on each steel pipe of the pipe roof on the semi-circular pre-support boundary. Through comparison and analysis with the measured results, we demonstrate that the calculation model for surrounding rock pressure and the calculation model for stress and deformation of the pipe roof are reasonable. According to the deformation coordination conditions between the steel pipe of the pipe roof and the surrounding rock on the pre-support boundary and alongside the Peck formula, we establish a theoretical analysis method for pipe roof pre-support effectiveness based on the indexes of the ground loss rate, settlement trough width, and maximum ground surface settlement, thereby realizing a quantitative evaluation of pipe-roof pre-support effectiveness. At the same time, the effects of steel pipe diameter, circumferential spacing, and excavation footage length on the pre-support effectiveness of the pipe roof are analyzed. The conclusions can be used as a basis for the design and optimization of pipe roofs and as a guide for the application of pipe roofs.

A numerical approach to evaluating the asymmetric ground settlement response to twin-tunnel asynchronous excavation

Due to the importance of surface and subsurface settlements to prevent damages to building foundations and sensitive structures in the urban cities, in this study, the ABAQUS finite element software has used to conduct a series of numerical modeling analysis on ground surface settlement caused from the asynchronous excavation of twin-tunnel. The effects of tunnel diameter, center-to-center tunnel spacing, and tunnel depth are discussed in detail and the shape of the surface settlement curves is also plotted. The numerical modeling has been verified by the results of three sequential twin-tunneling centrifuge tests conducted by the City University of London with 94.22%, 98.71% and 99.56% accuracy, respectively. Based on the results of this study, reducing the tunnel diameter decreases the amount of the maximum ground surface settlements and reducing the depth of tunnels and the distance between twin-tunnel to less than 2D (D is the diameter of the tunnels) increase the maximum surface settlements. Installation of 30 cm of tunnel lining can decrease the maximum ground surface settlement up to almost 79%.

Equation for Maximum Ground Surface Settlement due to Bored Tunnelling in Cohesive and Cohesionless Soils Obtained by Numerical Simulations

Equation for Maximum Ground Surface Settlement due to Bored Tunnelling in Cohesive and Cohesionless Soils Obtained by Numerical Simulations

Analysis of ground surface settlement in anisotropic clays using extreme gradient boosting and random forest regression models

Excessive ground surface settlement induced by pit excavation (i.e. braced excavation) can potentially result in damage to the nearby buildings and facilities. In this paper, extensive finite element analyses have been carried out to evaluate the effects of various structural, soil and geometric properties on the maximum ground surface settlement induced by braced excavation in anisotropic clays. The anisotropic soil properties considered include the plane strain shear strength ratio (i.e. the ratio of the passive undrained shear strength to the active one) and the unloading shear modulus ratio. Other parameters considered include the support system stiffness, the excavation width to excavation depth ratio, and the wall penetration depth to excavation depth ratio. Subsequently, the maximum ground surface settlement of a total of 1479 hypothetical cases were analyzed by various machine learning algorithms including the ensemble learning methods (extreme gradient boosting (XGBoost) and random forest regression (RFR) algorithms). The prediction models developed by the XGBoost and RFR are compared with that of two conventional regression methods, and the predictive accuracy of these models are assessed. This study aims to highlight the technical feasibility and applicability of advanced ensemble learning methods in geotechnical engineering practice.

Field investigation of the influence of basement excavation and dewatering on ground and structure responses

Although much research attention has been paid to ground and structure responses due to basement excavation, effects of dewatering during basement excavation on the deformation characteristics are not fully explored. A long and narrow basement with a final excavation depth of 14.5–17.0 m was heavily instrumented in soft clay. Basement excavation and dewatering induce substantially lateral wall movement at the pile toe of the retaining structure. The maximum lateral movement at the pile toe is up to 64.9% of the maximum lateral wall movement. Compared with the maximum ground surface settlement at the end of basement excavation, the maximum ground surface settlement is increased by 37% after casting concrete slab. Because of dewatering, the maximum lateral wall movement, vertical wall movement and ground settlement are up to 42.9%, 16.7% and 26.4% of the total movements, respectively. Moreover, building settlement due to dewatering is about 25–70% of the total building settlement. Dewatering and basement excavation-induced building settlement is in a range of 0.07% H to 0.15% H (excavation depth). Upon completion of casting concrete slab, the maximum building settlement is increased to 0.27% H. Thus, long-term effects of basement excavation on surrounding buildings should be taken into consideration.

Application of machine learning for predicting ground surface settlement beneath road embankments

Predicting the maximum ground surface settlement (MGS) beneath road embankments is crucial for safe operation, particularly on soft foundation soils. Despite having been explored to some extent, this problem still has not been solved due to its inherent complexity and many effective factors. This study applied support vector machines (SVM) and artificial neural networks (ANN) to predict MGS. A total of four kernel functions are used to develop the SVM model, which is linear, polynomial, sigmoid, and Radial Basis Function (RBF). MGS was analysed using the finite element method (FEM) with three dimensionless variables: embankment height, applied surcharge, and side slope. In comparison to the other kernel functions, the Gaussian produced the most accurate results (MARE = 0.048, RMSE = 0.007). The SVM-RBF testing results are compared to those of the ANN presented in this study. As a result, SVM-RBF proved to be better than ANN when predicting MGS.

Numerical analysis of excavation stability of transfer station of Jinan Metro

The influence of the excavating deformation on the surrounding environment should be extremely controlled in the excavation of metro transfer station and it is important to study the stability of excavation. Here we establish three-dimensional finite element models with the fluid-solid coupling effect aimed to perform analysis on the stability of excavation based on the background of the Jinan metro transfer station in this paper. The location is determined through simulation in which the maximum horizontal displacement of diaphragm wall appears as well as the maximum ground surface settlement. The research results can provide useful reference in analysis and calculation for other similar underground engineering excavation and construction design.

Effectiveness of servo struts in controlling excavation-induced wall deflection and ground settlement

Deformations in deep excavations can be controlled by providing adjustable support using servo struts; however, the design of strut positions and applied forces remains to be optimized. In this study, the influences of varied forces applied by servo struts on excavation-induced wall deflection and ground settlement were analyzed through numerical simulations and a field investigation. A reference numerical model and input parameters were validated using a well-documented excavation case study. Using the validated model, three servo struts were installed on a diaphragm wall at the top, middle, and bottom levels of an excavation model, and a constant force was applied on the beam elements. Comprehensive numerical simulations were carried out with various forces applied at the upper-, middle-, and lower-level struts. Both wall deflection and ground settlement were analyzed in relation to the applied force. Additionally, a field investigation was carried out at an excavation site in Hangzhou, China, where comparative analyses of applied forces and servo strut locations were performed. Both the numerical and field results confirm the effectiveness of servo struts in controlling excavation-induced wall deflection and ground surface settlement. Their effectiveness is closely related to their applied force and installation position. Wall deformation and ground settlement decrease with increases in applied force. Middle-level servo struts showed the greatest efficiency in controlling maximum wall displacement and maximum ground surface settlement.