Applying stiffness migration method,a 3D finite element mechanical model is established to simulate the excavation and advance processes.By using 3D nonlinear finite element method,the tunnel boring machine(TBM) excav...Applying stiffness migration method,a 3D finite element mechanical model is established to simulate the excavation and advance processes.By using 3D nonlinear finite element method,the tunnel boring machine(TBM) excavation process is dynamically simulated to analyze the stress and strain field status of surrounding rock and segment.The maximum tensile stress of segment ring caused by tunnel construction mainly lies in arch bottom and presents zonal distribution.The stress increases slightly and limitedly in the course of excavation.The maximum and minimum displacements of segment,manifesting as zonal distribution,distribute in arch bottom and vault respectively.The displacements slightly increase with the advance of TBM and gradually tend to stability.展开更多
Long tunnel excavation with tunnel boring ily affected by uncertainties and needs to be adjusted machine （TBM） is a complex and stochastic process. It is eas- according to specific geological conditions in different...Long tunnel excavation with tunnel boring ily affected by uncertainties and needs to be adjusted machine （TBM） is a complex and stochastic process. It is eas- according to specific geological conditions in different tunnel sections, which makes the construction scheduling and management difficult. Based on the rock mass classification, this paper estimates the penetration rate. Using the rate, a cyclic network simulation （CYCLONE） model of TBM boring system is established, and the advance rates under different geological conditions are determined. Then, the impact of different cutter head thrust, which is chosen in reasonable range according to previous experiences, on pro- ject schedule is analyzed. Moreover, the simulation model of mucking system is built to determine the number of muck trains and rail intersections reasonably, regarding the efficiency of muck loading and material transporting. Based on the interaction and interrelation between TBM boring system and mucking system, the combined CY- CLONE model for the entire tunneling process is established. Then reasonable construction schedule, the utilization rate of working resources, and the probability of project completion are obtained through the model programming. At last, a project application shows the feasibility of the presented method.展开更多
Real-time dynamic adjustment of the tunnel bore machine(TBM)advance rate according to the rockmachine interaction parameters is of great significance to the adaptability of TBM and its efficiency in construction.This ...Real-time dynamic adjustment of the tunnel bore machine(TBM)advance rate according to the rockmachine interaction parameters is of great significance to the adaptability of TBM and its efficiency in construction.This paper proposes a real-time predictive model of TBM advance rate using the temporal convolutional network(TCN),based on TBM construction big data.The prediction model was built using an experimental database,containing 235 data sets,established from the construction data from the Jilin Water-Diversion Tunnel Project in China.The TBM operating parameters,including total thrust,cutterhead rotation,cutterhead torque and penetration rate,are selected as the input parameters of the model.The TCN model is found outperforming the recurrent neural network(RNN)and long short-term memory(LSTM)model in predicting the TBM advance rate with much smaller values of mean absolute percentage error than the latter two.The penetration rate and cutterhead torque of the current moment have significant influence on the TBM advance rate of the next moment.On the contrary,the influence of the cutterhead rotation and total thrust is moderate.The work provides a new concept of real-time prediction of the TBM performance for highly efficient tunnel construction.展开更多
基金Supported by National Natural Science Foundation of China(No.90815019)National Key Basic Research Program of China("973" Program,No.2007CB714101)Key Project in the National Science and Technology Pillar Program during the Eleventh Five-Year Plan Period(No.2006BAB04A13)
文摘Applying stiffness migration method,a 3D finite element mechanical model is established to simulate the excavation and advance processes.By using 3D nonlinear finite element method,the tunnel boring machine(TBM) excavation process is dynamically simulated to analyze the stress and strain field status of surrounding rock and segment.The maximum tensile stress of segment ring caused by tunnel construction mainly lies in arch bottom and presents zonal distribution.The stress increases slightly and limitedly in the course of excavation.The maximum and minimum displacements of segment,manifesting as zonal distribution,distribute in arch bottom and vault respectively.The displacements slightly increase with the advance of TBM and gradually tend to stability.
基金Supported by National Natural Science Foundation of China (No.50709024)Program for New Century Excellent Talents in University (No. NCET-08-0391)
文摘Long tunnel excavation with tunnel boring ily affected by uncertainties and needs to be adjusted machine （TBM） is a complex and stochastic process. It is eas- according to specific geological conditions in different tunnel sections, which makes the construction scheduling and management difficult. Based on the rock mass classification, this paper estimates the penetration rate. Using the rate, a cyclic network simulation （CYCLONE） model of TBM boring system is established, and the advance rates under different geological conditions are determined. Then, the impact of different cutter head thrust, which is chosen in reasonable range according to previous experiences, on pro- ject schedule is analyzed. Moreover, the simulation model of mucking system is built to determine the number of muck trains and rail intersections reasonably, regarding the efficiency of muck loading and material transporting. Based on the interaction and interrelation between TBM boring system and mucking system, the combined CY- CLONE model for the entire tunneling process is established. Then reasonable construction schedule, the utilization rate of working resources, and the probability of project completion are obtained through the model programming. At last, a project application shows the feasibility of the presented method.
基金Supports from National Natural Science Foundation of China(Grant No.11902069)Sichuan University,State Key Lab Hydraul&Mt River Engn(No.SKHL1915)+2 种基金and the Research Project of China Railway First Survey and Design Institute Group Co.,Ltd(No.19-15 and No.20-17-1)are also acknowledgedsupported by the 111 Project(B17009)under the framework of Sino-Franco Joint Research Laboratory on Multiphysics and Multiscale Rock Mechanics.
文摘Real-time dynamic adjustment of the tunnel bore machine(TBM)advance rate according to the rockmachine interaction parameters is of great significance to the adaptability of TBM and its efficiency in construction.This paper proposes a real-time predictive model of TBM advance rate using the temporal convolutional network(TCN),based on TBM construction big data.The prediction model was built using an experimental database,containing 235 data sets,established from the construction data from the Jilin Water-Diversion Tunnel Project in China.The TBM operating parameters,including total thrust,cutterhead rotation,cutterhead torque and penetration rate,are selected as the input parameters of the model.The TCN model is found outperforming the recurrent neural network(RNN)and long short-term memory(LSTM)model in predicting the TBM advance rate with much smaller values of mean absolute percentage error than the latter two.The penetration rate and cutterhead torque of the current moment have significant influence on the TBM advance rate of the next moment.On the contrary,the influence of the cutterhead rotation and total thrust is moderate.The work provides a new concept of real-time prediction of the TBM performance for highly efficient tunnel construction.
