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MODERN TUNNELLING TECHNOLOGY 2020, Vol. 57 Issue (2) :26-33    DOI:
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Prediction Model of TBM Net Advance Rate Based on Parameters of Rock Mass and Tunnelling
(School of Civil Engineering, Zhengzhou University, Zhengzhou 450001)
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Abstract Net advance rate is a main evaluation index of TBM construction speed and it has something to do with the mechanical behavior of surrounding rocks and tunnelling parameters. Taking the double shield TBM adopted in the water diversion tunnel of Lanzhou water source construction project as the research background, a correlation analysis on single factor between TBM net advance rate and relevant influential parameters is conducted in terms of uniaxial compressive strength, tensile strength, modulus of deformation, Poisson′s ratio and CAI value of rock wear resistance as well as cutterhead thrust and rotation speed, and the corresponding fitting formula is obtained based on the field data. A prediction model of TBM net advance rate is established by multivariate nonlinear regression method in light of a correlation among TBM net advance rate, rock mass properties and tunnelling parameters. By comparing the measured TBM net advance rate and the predicted results of the water conveyance tunnel in Lanzhou water source construction project, the rationality of prediction model for TBM net advance rate is verified. The research results show that: (1) in complex and various geological conditions, the TBM net advance rate has a negative correlation with uniaxial compressive strength, tensile strength, modulus of deformation, CAI value of rock wear resistance, thrust and rotating speed of cutterhead while it has a positive correlation with the Poisson's ratio; (2) the moisture state has certain effect on CAI value of rock wear resistance, and there is a closer correlation between CAI value of rock wear resistance and TBM net tunneling rate under saturation condition; (3) this multivariate nonlinear regression prediction model with a high precision can be used to estimate the TBM net advance rate under similar geological conditions.
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YAN Changbin JIANG Xiaodi
KeywordsTBM   Net advance rate   Rock mass parameters   Tunneling parameters   Multivariate nonlinear regres? sion   Prediction model     
Abstract: Net advance rate is a main evaluation index of TBM construction speed and it has something to do with the mechanical behavior of surrounding rocks and tunnelling parameters. Taking the double shield TBM adopted in the water diversion tunnel of Lanzhou water source construction project as the research background, a correlation analysis on single factor between TBM net advance rate and relevant influential parameters is conducted in terms of uniaxial compressive strength, tensile strength, modulus of deformation, Poisson′s ratio and CAI value of rock wear resistance as well as cutterhead thrust and rotation speed, and the corresponding fitting formula is obtained based on the field data. A prediction model of TBM net advance rate is established by multivariate nonlinear regression method in light of a correlation among TBM net advance rate, rock mass properties and tunnelling parameters. By comparing the measured TBM net advance rate and the predicted results of the water conveyance tunnel in Lanzhou water source construction project, the rationality of prediction model for TBM net advance rate is verified. The research results show that: (1) in complex and various geological conditions, the TBM net advance rate has a negative correlation with uniaxial compressive strength, tensile strength, modulus of deformation, CAI value of rock wear resistance, thrust and rotating speed of cutterhead while it has a positive correlation with the Poisson's ratio; (2) the moisture state has certain effect on CAI value of rock wear resistance, and there is a closer correlation between CAI value of rock wear resistance and TBM net tunneling rate under saturation condition; (3) this multivariate nonlinear regression prediction model with a high precision can be used to estimate the TBM net advance rate under similar geological conditions.
KeywordsTBM,   Net advance rate,   Rock mass parameters,   Tunneling parameters,   Multivariate nonlinear regres? sion,   Prediction model     
Cite this article:   
YAN Changbin JIANG Xiaodi .Prediction Model of TBM Net Advance Rate Based on Parameters of Rock Mass and Tunnelling[J]  MODERN TUNNELLING TECHNOLOGY, 2020,V57(2): 26-33
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