岩土工程学报2026，Vol.48Issue(3)：590-598,9.DOI:10.11779/CJGE20240839
盾构下穿既有隧道扰动预测模型及掘进参数优化
Prediction model for disturbance induced by shield tunneling underneath existing tunnels and optimization of tunneling parameters
摘要
Abstract
To address the issues of structural damage to existing tunnels and operational safety risks of high-speed railways caused by excessive deformation of high-speed railway tunnels due to shield tunneling underneath,accurate prediction of the maximum deformation of overlying tunnels induced by shield tunnel excavation is crucial.Based on a multi-source heterogeneous database of disturbance deformation from shield tunneling underneath existing tunnels,this study constructs a general prediction model for deformation of overlying high-speed railway tunnels induced by new shield tunneling underneath using machine learning algorithms including XGBoost,support vector machine(SVM),and neural network.Taking the project case as the research object,the XGBoost algorithm is used to model and predict the settlement of high-speed railway tunnels induced by shield tunneling underneath.Bayesian algorithm is employed to optimize the model hyperparameters,and the recommended range of tunneling parameters for shield tunneling underneath is proposed based on the settlement limits of high-speed railway tunnels.The results show that:(1)The XGBoost model optimized by Bayesian algorithm is used to establish a surrogate model for predicting disturbance of existing tunnels induced by shield tunneling.Over 95%of the prediction errors of this model are less than 0.65 mm,with the coefficient of determination(R²)reaching 0.997,which is significantly better than the SVM and neural network models.(2)By combining the prediction surrogate model with the particle swarm optimization(PSO)algorithm,an optimization control model with decision variables including shield tunneling speed,cutter head rotation speed,synchronous grouting pressure,and synchronous grouting volume is established.The optimization of tunneling parameters is implemented for the shield tunneling section underneath the Liuyang River Tunnel to guide construction,and the maximum settlement of the ballastless track structure is 1.12 mm,meeting the track deformation control standards.(3)The temporal variation law of the predicted settlement values of the high-speed railway tunnel after optimization of shield tunneling parameters is consistent with that of on-field monitoring values,with a maximum deviation of 0.198 mm,verifying the practicability and accuracy of the disturbance prediction and tunneling parameter optimization control method for shield tunneling underneath existing tunnels.The research results can further guide the determination of the range of tunneling parameters for shield tunneling underneath high-speed railway tunnels and provide a theoretical reference for ensuring the safe operation of high-speed railways.关键词
隧道沉降/盾构下穿既有隧道/扰动预测模型/掘进参数/安全控制Key words
tunnel settlement/shield tunneling underneath existing tunnels/settlement prediction model/tunneling parameters/safety control分类
交通工程引用本文复制引用
费瑞振,施成华,张春雷,李敬梅..盾构下穿既有隧道扰动预测模型及掘进参数优化[J].岩土工程学报,2026,48(3):590-598,9.基金项目
国家自然科学基金项目(51778636) （51778636）
中国铁路设计集团有限公司科研课题(2024CJ0102)This study was supported by National Natural Science Foundation of China(Grant No.51778636),and Research Projects of China Railway Design Corporation(Grant No.2024CJ0102). （2024CJ0102）
