Uncertainty Analysis in Rock Mass Classification and its Application To Reliability Evaluation In Tunnel Construction

Geological uncertainty is one of the most important uncertainties during underground construction as mischaracterizing the geology condition or disregarding the geological uncertainty may cause delay and cost overrun and even fatalities and casualties in some cases. However, if we can well model or assess the geological uncertainty before construction, it would be very helpful and can provide design aids for the subsequent underground excavation and support. In other words, the construction uncertainty would be reduced, and the construction procedures can be optimized accordingly. Moreover, construction time and cost can also be optimized and could be helpful to the contract-bidding phase. Currently, however, most of the geological conditions are described using deterministic (fixed value) or qualitative, subjective assessment by on-site engineering geologists based on their experiences, knowledge and available geological data. In addition, ground classification (GC) of rock masses, subjectively determined by tunneling experts via combining a few geologic parameters, is commonly used to describe the overall rock mass quality. Nevertheless, the chosen geological parameters in ground classification may not be the most influential geologic parameters. Also, GC has only a few geologic parameters with qualitatively described parameter states (sometimes only two). Moreover, all the geological parameters are typically assumed to be independent, neglecting inherent interdependency among some parameters. Once the GC is determined, the corresponding deterministic excavation method and support measures would be given to each GC. These decisions may be highly dependent on the level of expertise of tunneling experts, and it may also be disputable among different experts with different levels of knowledge and experiences. To overcome these disadvantages of the current industrial practice, a Q-based Markovian geologic prediction approach, which is the combination of the probabilistic Markovian geologic prediction approach and Rock Tunneling Quality Index (Q) system, is proposed in this project.


  • English


  • Status: Completed
  • Funding: $330000
  • Contract Numbers:


  • Sponsor Organizations:

    University Transportation Center for Underground Transportation Infrastructure

    Colorado School of Mines
    Golden, CO  United States  80401


    Dever,   United States 

    Colorado School of Mines

    Golden,   United States 

    Office of the Assistant Secretary for Research and Technology

    University Transportation Centers Program
    Department of Transportation
    Washington, DC  United States  20590
  • Managing Organizations:

    University Transportation Center for Underground Transportation Infrastructure

    Colorado School of Mines
    Golden, CO  United States  80401
  • Performing Organizations:

    Colorado School of Mines, Golden

    1500 Illinois Street
    Golden, CO  United States  80401
  • Principal Investigators:

    Gutierrez, Marte

    Kim, Eunhye

  • Start Date: 20150101
  • Expected Completion Date: 20190531
  • Actual Completion Date: 0
  • USDOT Program: University Transportation Centers

Subject/Index Terms

Filing Info

  • Accession Number: 01660183
  • Record Type: Research project
  • Source Agency: University Transportation Center for Underground Transportation Infrastructure
  • Contract Numbers: 69A3551747118
  • Files: UTC, RIP
  • Created Date: Jan 23 2018 5:07PM