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Author:

Gong, Qiuming (Gong, Qiuming.) (Scholars:龚秋明) | Xu, Hongyi (Xu, Hongyi.) | Lu, Jianwei (Lu, Jianwei.) | Wu, Fan (Wu, Fan.) | Zhou, Xiaoxiong (Zhou, Xiaoxiong.) | Yin, Lijun (Yin, Lijun.)

Indexed by:

EI Scopus SCIE

Abstract:

Rock mass characteristics (RMC) model is the one of serval prediction models for TBM penetration rate that considers the interaction between the rock mass and cutters. The first version was developed in 2009. However, it was a relative site specific model and the machine parameters were ignored. To update the RMC model, a comprehensive data base which included the results of the laboratory cutting tests and the in site penetration tests was compiled. Firstly, the correction factors of the cutter spacing and cutter shape were set up based on the laboratory tests, which were then used to normalize the data with the given machine parameters. Finally, two critical parameters in RMC model, i.e., the specific rock mass boreability index (SRMBI) and the exponent c, were estimated by regression analysis using the rock mass parameters. Now SRMBI in the updated model represents the boreability of a rock mass excavated by the given machine setup at penetration rate of 1 mm/rev. A higher SRMBI implies the rock mass is more difficult to be bored. The exponent c decides the increment in cutter normal force for the increasing penetration rate, c together with the rock mass strength reflect the different TBM cutting modes. Since the rock specimens in the laboratory tests was intact and the rock masses in the in site penetration tests contain the joints, the updated model reflects the reduction in the required thrust force caused by the joints in nature. The updated RMC model covered a wide range of the geological context and machine parameters. It could be used to predict TBM penetration rate and optimize the operating parameter in the given stroke. The equations in the updated model need further modification when more test data is collected, and the in situ stress needs to be taken into consideration.

Keyword:

Rock mass boreability Rock breakage process TBM penetration Rate Test database TBM performance Prediction

Author Community:

  • [ 1 ] [Gong, Qiuming]Beijing Univ Technol, Key Lab Urban Secur & Disaster Engn, Minist Educ, Beijing 100124, Peoples R China
  • [ 2 ] [Xu, Hongyi]Beijing Univ Technol, Key Lab Urban Secur & Disaster Engn, Minist Educ, Beijing 100124, Peoples R China
  • [ 3 ] [Lu, Jianwei]Beijing Univ Technol, Key Lab Urban Secur & Disaster Engn, Minist Educ, Beijing 100124, Peoples R China
  • [ 4 ] [Wu, Fan]Beijing Univ Technol, Key Lab Urban Secur & Disaster Engn, Minist Educ, Beijing 100124, Peoples R China
  • [ 5 ] [Zhou, Xiaoxiong]Beijing Univ Technol, Key Lab Urban Secur & Disaster Engn, Minist Educ, Beijing 100124, Peoples R China
  • [ 6 ] [Yin, Lijun]Beijing Univ Technol, Key Lab Urban Secur & Disaster Engn, Minist Educ, Beijing 100124, Peoples R China
  • [ 7 ] [Zhou, Xiaoxiong]Tsinghua Univ, State Key Lab Hydrosci & Engn, Beijing 100084, Peoples R China

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Source :

INTERNATIONAL JOURNAL OF ROCK MECHANICS AND MINING SCIENCES

ISSN: 1365-1609

Year: 2021

Volume: 149

7 . 2 0 0

JCR@2022

ESI Discipline: GEOSCIENCES;

ESI HC Threshold:64

JCR Journal Grade:1

Cited Count:

WoS CC Cited Count: 8

SCOPUS Cited Count: 8

ESI Highly Cited Papers on the List: 0 Unfold All

WanFang Cited Count:

Chinese Cited Count:

30 Days PV: 7

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