Modified block shape characterization method for classification of fractured rock: A python-based GUI tool

Abstract

The presence of discontinuities in fractured rocks contributes to the formation of blocks. Characterizing the size and shape of the congregation of blocks in the rock mass provides a comprehensive understanding for studying its engineering properties. The existing block shape characterization method (BSCM) considers two factors: α describes the shortening of the minor principal axis of the block, and β describes the elongation of the major axis. The parameter β used the average angular relation between the chords greater than the median, considering the average angle could produce skewed results towards elongated blocks. This study proposed a modified block shape classification method (MBSCM), where parameter β is provided with a new definition and procedure for calculation. To reckon the elongation index (β) of the block, the maximum angular extension between the chords was considered and the parameter α remained unchanged in the modified approach. The developed method was validated with synthetic rock masses of known shapes (i.e., cubic, elongated, elongated platy) constructed in the 3DEC (Three-dimensional distinct element code). Two case studies were also conducted on the Himalayan slopes to demonstrate the new method's applicability. Discrete Fracture Network (DFN) were generated for both the slopes to find the block related data formed by the intersection of the fracture network. The results show that the first slope was dominated with elongated (73.52%), elongated platy (16.53%) and platy (6.1%) blocks while the second slope was composed of elongated (59.17%), cubic elongated/platy (22.3/11.98%) and cubic (4.21%) blocks. The slopes were also classified using the existing method to compare the outcomes. The result shows that the existing method categorized about 5% more elongated blocks as compared to the proposed modified approach. A python-based GUI tool was developed for the modified approach and was successfully used to directly plot the classification diagrams by importing the raw data file.