The long water transfer tunnel of Kerman in the length of 63.5 kilometers is a part of the long term water supply project of the city of Kerman, which should be conveyed water from Safa and Sarmeshk dam reservoir to the Kerman water treatment plant. Due to the high length and depth of this tunnel, it may face difficulties during excavation. In this paper, a method for probabilistic quantifying these problems is proposed. Using the computational model it is possible to determine the uncertainties of the geological prediction, the distribution of the geotechnical parameters and the rock mass characterization. Each model provides a physical value in which one aspect of the rock mass response, such as displacements, depth of failure zone, level of squeezing, intensity of rock burst and etc is described. In this paper, the rock mass of the tunnel path is divided into calculation segments according to the rock mass types and influencing factors and its parameters are studied in the form of probabilities distribution. By using empirical correlations and computer simulation, the strength and the behavior of the rock mass in tunnel path are assessed in the form of probability, and finally the results are demonstrated in quantities. According to the obtained results, during tunnel excavation, the risk of failure, serious instability, squeezing and rock burst are predicted the position and the quantity probability of the expressed risks at different parts of the tunnel route are determined.
The necessary information for the design of underground structures, are mainly obtained from local exploration and measurements, but these data are very limited, therefore, a great deal of uncertainty (geological and hydrogeological conditions) is concluded from the construction of underground structures in rock mass. So, design engineers and decision makers carry out parameter optimizations not only in their own desires but also with risk. The risk can be defined as the product of the probability and the eventual impact of a hazard. This risk gets new side in the long tunnels that its rate of danger depends on the type and the amount of geotechnical datas. Ideally, all potential risks are related to the rock mass characteristics and should be covered by a rock mass classification system. With this proposed computational model, it is possible to take into account the uncertainties of the geological prediction and the distribution of the geotechnical parameters. The Monte-Carlo method is now one of the most powerful and commonly used techniques for analyzing complex problems. In this paper, the data of the water transfer tunnel of Kerman are entered to the @Risk software in the form of probabilities distribution. By using empirical correlations and simulation, strength and behavior of the rock mass in tunnel route are obtained in the form of probability, and finally the results are demonstrated in quantities. It should be noted that the obtained results give us only an aspect of tunnel behavior and not more, so for more detailed evaluation, more precise data and general analysis methods are needed.