Modified Q-index for prediction of rock mass quality around a tunnel excavated with a tunnel boring machine (TBM)

  • Feng Ji
  • Yuchuan ShiEmail author
  • Renjie Li
  • Chunhong Zhou
  • Ning Zhang
  • Jishun Gao
Original Paper


Rock mass quality is closely related to tunnel stability and supporting measures. The Q-system, based on the drilling and blasting method, is one of the most important methods for rock mass classification systems and provides reliable long-term protection for tunnel excavation and reinforcement. However, in comparison to the drilling and blasting method, tunnels excavated using the tunnel boring machine (TBM) method have smooth and integral walls. The number of structural planes in these tunnels, their extension lengths, opening widths, and other characteristics are significantly different from those excavated using the drilling and blasting method. These differences lead to prediction errors in rock mass quality when the Q-system is applied to tunnels excavated by a TBM, and the coincidence rate is less than 70%. In this study, a reduction factor RKv, based on the wave velocity test, is used to replace the RQD/Jn term in the Q-system to reflect the integrity of the rock mass. This replacement can overcome the shortcomings that result from the smooth walls in TBM tunnels by applying the wave velocity during tunnel construction. Based on multiple regression analysis of RKv, we established a QT method for rock classification of material surrounding TBM tunnels. This new method provides a prediction coincidence rate of more than 85%.


Rock mass classification Rock mass integrity Reduction factor TBM tunnel Q-system 



We acknowledge the support of the National Natural Science Foundation of China (no. 51308082), the Key Fund Project of the Sichuan Provincial Department of Education (no. 15ZA0075), and the Discovery Fund of the State Key Laboratory of Geohazard Prevention and Geoenvironment Protection (SKLGP00002296, SKLGP2016Z011, SKLGP2017Z008). The authors are grateful to all technicians who worked in the laboratory at SKLGP for providing assistance throughout the experimental work. We especially thank Dr. Ming Zeng who provided valuable advice on this research.


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Copyright information

© Springer-Verlag GmbH Germany, part of Springer Nature 2018

Authors and Affiliations

  1. 1.State Key Laboratory of Geohazard Prevention and Geoenvironment ProtectionChengdu University of TechnologyChengduPeople’s Republic of China
  2. 2.China Hydropower Consulting Group Co.East China Investigation & Design InstituteFuzhouPeople’s Republic of China

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