详情

Uncertainty Modeling and Risk Assessment for Tunnel Design

项目名称：	Uncertainty Modeling and Risk Assessment for Tunnel Design
摘要：	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.
状态：	Active
资金：	330000
资助组织：	Office of the Assistant Secretary for Research and Technology
管理组织：	University Transportation Center for Underground Transportation Infrastructure
执行机构：	Colorado School of Mines, Golden
主要研究人员：	Kim, Eunhye
开始时间：	20150101
预计完成日期：	20190531
实际结束时间：	0