The distribution characteristics of rock fractures determine the hydro-mechanical behavior of natural barriers. Rock fractures are defined by various parameters, which are analyzed as the probability distribution from observation results by surveying the exposed rock surface or borehole. The size is known to have the most uncertainty among the fracture parameters because it cannot be directly measured. Therefore, various estimation methods have been proposed for fracture size distribution using the fracture traces observable on the rock surface. However, most methods are based on a planar survey area, limiting their applicability to the underground research laboratory (URL) excavated in the form of tunnels. This study aims to review a method that can be applied to estimate the size distribution of fractures in deep rock masses at the URL site. The estimation method using the joint center volume (JCV) has recently been extended to be applicable regardless of the geometry of the survey area, which means that it can be applied to the URL site with complex structures. To apply the JCV-based estimation method to non-planar survey areas, JCV calculation using Monte Carlo simulation and estimation of fracture size distribution using the maximum likelihood method are required. In this study, we applied the JCV-based estimation method to a tunnel-shaped survey area to examine its applicability to the URL site. The error rates were analyzed when there were fracture sets with various orientations, size distributions, and maximum fracture sizes in the rock mass, and it was found to be less than 10% in all cases. This result indicates that the JCV-based estimation method can be used to estimate the fracture size distribution of the surrounding rock mass if accompanied by a reliable survey of fracture traces on the tunnel surface inside the URL site. Also, since there are no restrictions on the geometry of the survey area, we can continuously update the estimation results during the URL excavation process to increase reliability. The fracture size distribution is essential for constructing the discrete fracture network (DFN) model of the rock mass units at the URL site. In the future, the uncertainty for the fracture size in the DFN model is expected to be reduced by applying the JCV-based estimation method.

• Yong-Ki Lee(Korea Atomic Energy Research Institute (KAERI)) Corresponding author
• Chae-Soon Choi(Korea Atomic Energy Research Institute (KAERI))
• Seungbeom Choi(Korea Atomic Energy Research Institute (KAERI))
• Kyung-Woo Park(Korea Atomic Energy Research Institute (KAERI))