scholarly journals Prediction of maximum surface settlement caused by earth pressure balance (EPB) shield tunneling with ANN methods

2019 ◽  
Vol 59 (2) ◽  
pp. 284-295 ◽  
Author(s):  
Ren-Peng Chen ◽  
Pin Zhang ◽  
Xin Kang ◽  
Zhi-Quan Zhong ◽  
Yuan Liu ◽  
...  
Keyword(s):  
Earth Pressure ◽  
Surface Settlement ◽  
Pressure Balance ◽  
Shield Tunneling ◽  
Maximum Surface ◽  
Earth Pressure Balance ◽  
Maximum Surface Settlement ◽  
Epb Shield

Research on Chamber Earth Pressure of EPB Shield Considering Soil Arching Effect

2014 ◽  
Vol 1065-1069 ◽  
pp. 373-377
Author(s):  
Jing Cao ◽  
Hai Xing Yang ◽  
Bo Liang ◽  
Hai Ming Liu
Keyword(s):  
Earth Pressure ◽  
Shield Tunnel ◽  
Pressure Balance ◽  
Soil Arching ◽  
Shield Tunneling ◽  
Arching Effect ◽  
Soil Arching Effect ◽  
Earth Pressure Balance ◽  
Tunnel Depth ◽  
Epb Shield

Chamber earth pressure is one of the significant parameters during the Earth Pressure Balance (EPB) shield construction processing. The soil arching effect is existence when the tunnel depth is enough. It is significant to consider the influence of arching effect to analyze the pressure in soil chamber in shield tunneling. In this paper, the influence of arching effect is considered to calculate the chamber earth pressure. Firstly, the soil is supposed as loose media, and the necessary buried depth of producing arching affects is deduced according to the loose media theory. Then, based on the characteristic of proper arching axis, the equation and the height of proper arch are obtained. At last, the calculation formula of minimum chamber earth pressure of EPB shield tunnel is deduced which can consider the effect of arching effect.

Online Fault Prediction for EPB Shield Tunneling Based on Neural Network

2012 ◽  
Vol 457-458 ◽  
pp. 1287-1293 ◽  
Author(s):  
Bu Hai Shi ◽  
Wei Qing Li
Keyword(s):  
Neural Network ◽  
Earth Pressure ◽  
Risk Process ◽  
Fault Prediction ◽  
Pressure Balance ◽  
Shield Tunneling ◽  
The Neural Network ◽  
Earth Pressure Balance ◽  
Artificial Neural Network Ann ◽  
Epb Shield

For the complex earth conditions and uncertain factors, the earth pressure balance (EPB) shield tunneling is a complicated and high-risk process. There would cause some faults, such as earth caking, soil occluding in the capsule, water spewing, surface settlement. To avoid them, this paper applies artificial neural network (ANN) to predict the common shielding faults. The neural network is trained by several samples about the tunnel boring machine’s (TBM) parameters, and then it will have self-learning to identify the fault. With the parallel computing ability, the network could detect and predict abnormal behaviors online. This paper includes three parts, firstly, the introduction of EPB, and four usual blockings; and then the principle of BP neural network is present, for the defect of BP algorithm, two kinds of improved BP algorithms are applied in the network; finally, an simulation is given to illustrate the prediction.

scholarly journals Experimental Study of the Influence of Excavation Surface Stability and Sand Flowability Caused by Dense Slurry–Earth Pressure Balance Shield Tunneling in Silty Sand Stratum

2020 ◽  
Vol 2020 ◽  
pp. 1-14 ◽  
Author(s):  
Yongjin Qian ◽  
Fanlu Min ◽  
Zhenze Mo ◽  
Xihui Fan
Keyword(s):  
Pore Pressure ◽  
Filter Cake ◽  
Earth Pressure ◽  
Rate Of Change ◽  
Silty Sand ◽  
Pressure Balance ◽  
Shield Tunneling ◽  
Earth Pressure Balance ◽  
Sand Stratum ◽  
Epb Shield

Silty sand is highly permeable and has a large internal friction angle. To ensure the stable and efficient construction of the Earth pressure balance (EPB) shield in silt stratum, it is necessary to reduce the disturbance to the stratum during tunneling and reduce the risk of spewing and blocking during soil discharge. Thus, a new type of dense slurry-EPB shield construction technology is proposed. Using a custom-made test device, the consolidation tests were conducted on sand after mixing it with different amounts of slurry to study the change in the pore pressure in the mixed soil and sand stratum and analyze the stress transmission rule. In addition, slump tests were conducted on the mixed soil to study the change in the fluidity. Based on the laboratory test results, a field investigation was carried out to study the effects of the amount of slurry addition on the pore pressure in the stratum, the driving parameters, and the sand’s flowability during shield tunneling. The results show that when the amount of slurry reaches a certain value, the filter cake effect occurs. The greater the amount of slurry added during the shield tunneling, the smaller the rate of change of the pore pressure in the stratum. When the amount of BC2 slurry added reached 8 m3 per ring, the rate of change was reduced by 57%, and the slump value improved by 93%. The type of filter cake of the DS-EPB shield was only internal filter cake during tunneling, which reduced the disturbance of the excavation face and improved the flowability of the sand. These results are of great significance to the application and promotion of DS-EPB shields in sandy cobble strata.

Geological Adaptive Cutterhead Selection for EPB Shield Based on BP Neural Network

2014 ◽  
Vol 607 ◽  
pp. 118-123
Author(s):  
Lai Kuang Lin ◽  
Yi Min Xia ◽  
Fei He ◽  
Qing Song Mao ◽  
Kui Zhang
Keyword(s):  
Neural Network ◽  
Bp Neural Network ◽  
Earth Pressure ◽  
Training Model ◽  
Structure Design ◽  
Pressure Balance ◽  
Selection For ◽  
Earth Pressure Balance ◽  
Set Up ◽  
Epb Shield

In view of complex and fuzziness of geological adaptive cutterhead selection for earth pressure balance (EPB) shield, a cutterhead selection method based on BP neural network is put forward. Considering the structure characteristics of EPB shield cutterhead, typical cutterhead types are classified and summarized based on cutterhead topology structure and number of spokes. After analyzing the determinants of cutterhead selection, one-to-many mapping relation between cutterhead type and geological parameters is put forward, and then core geologic parameters related to cutterhead selection are concluded. The feasibility of using neural network method to choose the cutterhead type is analyzed, and a BP neural network training model for cutterhead selection is set up and tested in testing sample data. The result shows that the selected cutterhead and the construction cutterhead are basically consistent. The feasibility of this method is proved and it can be theoretical basis for the cutterhead structure design which will improve scientific of cutterhead selection.

Surface settlement during shield tunnelling at CH218 in Taipei

1998 ◽  
Vol 35 (1) ◽  
pp. 159-168 ◽  
Author(s):  
Chang-Yu Ou ◽  
Richard N Hwang ◽  
Wei-Jung Lai
Keyword(s):  
Ground Surface ◽  
Earth Pressure ◽  
Surface Settlement ◽  
Pressure Balance ◽  
Transit System ◽  
Ground Surface Settlement ◽  
Earth Pressure Balance Shield ◽  
Shield Tunnelling ◽  
Earth Pressure Balance ◽  
Twin Tunnels

This paper presents the surface settlement performance induced by the foamed type of earth pressure balance shield in contract CH218 of the Hsintien Line of the Taipei Rapid Transit System. The surface settlement characteristics caused by the single tunnel and by twin tunnels with reference to two sections spaced at 87 m are studied. Field observations indicate that the surface settlement trough due to the single tunnel can be represented by the normal distribution. The distance of the inflection point to the tunnel center and maximum surface settlement value are consistent with those found in the literature. The characteristics of the surface settlement trough are related to the type of the soil, particularly where the crown of the tunnel is located in a layered soil deposit. The ground surface settlement induced by twin tunnels was found to be larger than estimated using the principle of superposition.Key words: shield tunnelling, surface settlement, field observation.

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