Torque fluctuation analysis and penetration prediction of EPB TBM in rock–soil interface mixed ground. (September 2019)

• Record Type: Journal Article
• Authors: Zhao, Yu; Gong, Quanmei; Tian, Zhiyao; Zhou, Shunhua; Jiang, He
• Is Part Of: Tunnelling and underground space technology. Volume 91(2019)
• Publication Date: 2019-09
• Subjects: EPB TBM -- Rock–soil interface -- Torque fluctuation -- Penetration prediction -- TBM operation; Tunneling -- Periodicals; Underground construction -- Periodicals; Tunnels -- Periodicals; Underground areas -- Periodicals; 624.193
• DOI: 10.1016/j.tust.2019.103002
• Languages: English
• ISSNs: 0886-7798

Abstract

Highlights: A theoretical TBM torque model was developed in rock–soil interface mixed ground. A new prediction index, MTPI, was proposed to evaluate the cutability of mixed face. TBM performance prediction method based on MTPI and torque capacity was proposed. The predictive capability of the proposed method was validated by field data. Abstract: Tunnelling in rock–soil interface (RSI) mixed ground often results in high cutterhead torque and torque fluctuation. Therefore, choosing a reasonable penetration rate to reduce the torque and improve tunnelling efficiency is paramount. In this study, considering the interaction between the cutterhead and RSI, an excavation torque model was first established based on the CSM model for a disc cutter and a new three-dimensional limit analysis model for a scraper. Further, considering the friction at the cutterhead in RSI, a total torque model was developed. Based on the study of excavation torque change characteristics when the cutterhead located in RSI, a simplified relationship among torque, face composition, penetration and rock strength was established. Subsequently, a new prediction index, Mixed-face Torque Penetration Index (MTPI), which includes the torque exerted by the TBM in the calculated penetration rate, was proposed to evaluate rock-soil mixed face cutability. This index allows for the inclusion of a TBM–rock mass and TBM–soil interaction factor. The methodology based on MTPI and TBM torque capacity to predict the penetration rate of the machine in different geological conditions and TBM specifications was proposed. Finally, the predictive capability of the proposed torque model and penetration prediction model were validated by the good agreement between the predictions and field measurement data from the Guangzhou Metro Line 21 tunnel in China. This study can match the tunneling parameters with the geological conditions within the limitation of TBM and provide guidance for TBM operation or evaluate whether the TBM satisfies the project schedule.