Investigation of mechanical failure performance of a large-diameter shield tunnel segmental ring

The control criteria for structural deformation and the evaluation of operational safety performance for large-diameter shield tunnel segments are not yet clearly defined.To address this issue,a refined 3D finite element model was established to analyze the transverse deformation response of a large-diameter segmental ring.By analyzing the stress,deformation,and crack distribution of large-diameter segments under overload conditions,the transverse deformation of the segmental ring could be divided into four stages.The main reasons for the decrease in segmental ring stiffness were found to be the extensive development of cracks and the complete formation of four plastic hinges.The deformation control value for the large-diameter shield tunnel segment is chosen as 8%o of the segment's outer diameter,representing the transverse deformation during the formation of the first semi-plastic hinge(i.e.,the first yield point)in the structure.This control value can serve as a reinforcement standard for preventing the failure of large-diameter shield tunnel segments.The flexural bearing capacity characteristic curve of segments was used to evaluate the structural strength of a large-diameter segmental ring.It was discovered that the maximum internal force combination of the segment did not exceed the segment ultimate bearing capacity curve(SUBC).However,the combination of internal force at 9°,85°,and 161°of the joints,and their symmetrical locations about the 0°-180°axis exceeded the joint ultimate bearing capacity curve(JUBC).The results indicate that the failure of the large-diameter segment lining was mainly due to insufficient joint strength,leading to an instability failure.The findings from this study can be used to develop more effective maintenance strategies for large-diameter shield tunnel segments to ensure their long-term performance.

Prediction of shield tunneling-induced ground settlement using machine learning techniques

Predicting the tunneling-induced maximum ground surface settlement is a complex problem since the settlement depends on plenty of intrinsic and extrinsic factors.This study investigates the efficiency and feasibility of six machine learning(ML)algorithms,namely,back-propagation neural network,wavelet neural network,general regression neural network(GRNN),extreme learning machine,support vector machine and random forest(RF),to predict tunneling?induced settlement.Field data sets including geological conditions,shield operational parameters,and tunnel geometry collected from four sections of tunnel with a total of 3.93 km are used to build models.Three indicators,mean absolute error,root mean absolute error,and coefficient of determination the(7?2)are used to demonstrate the performance of each computational model.The results indicated that ML algorithms have great potential to predict tunneling-induced settlement,compared with the traditional multivariate linear regression method.GRNN and RF algorithms show the best performance among six ML algorithms,which accurately recognize the evolution of tunneling-induced settlement.The correlation between the input variables and settlement is also investigated by Pearson correlation coefficient.

Long-term settlement behavior of ground around shield tunnel due to leakage of water in soft deposit of Shanghai

The lining of shield tunnel is usually composed of segments,in which the joints,cracks,and the grouting holes(hereafter called lining deficit)exist.During the long-term running,soils and groundwater may leak from these kinds of lining deficit.The leaking of soil and groundwater causes the long-term ground loss around tunnel and thus results in the settlement of ground surface.This paper aims to analyze the impact of the leakage of groundwater through segments on the long-term settlement of ground surface.The adopted analytical method is based on the theory of groundwater seepage by using numerical simulation.The analyzed results show that settlement of ground surface increases gradually with the increase of the leaked volume of tunnel segments.When the leaked volume was unevenly distributed,differential settlement occurred locally.Comparative analysis by changing the leaked volume was conducted.The results reveal that there is a linear relationship between settlement and leaked volume when the leaked volume was controlled within the allowable limit.