Abstract
ABSTRACT: The stress-seepage tests are conducted on sandstone samples that containing inclined rough fracture under three-dimensional stress conditions. The surface scanners are utilized to scan and analyze the morphology of the fractures before and after the tests, studying the relationship between morphology and mechanical and seepage characteristics. The research results demonstrate that: (i) Confining pressure has a significantly strengthening effect on the peak stress and crack damage threshold, while pore pressure has the opposite effect; (ii) As the confining pressure increases, the JRC in vertical (JRCV) and absolute difference between JRC in vertical and horizontal (|JRCV−JRCH|) nonlinear decreases, this trend can be described by power function properly; (iii) A revised permeability calculation formula for a rough single fracture was proposed by introducing the fractal dimension D. The negative correlation between the fractal dimension of fracture surface and permeability, which confirms the validity of the revised formula; (iv) Based on gray threshold segmentation methods, the seepage channels have been identified and segmented, the ratio of the area of seepage channels to the entire fracture surface area, defined as connectivity ratio Ф, exhibited a basic positive correlation with permeability. During the compression, the permeability dynamic evolution can be divided into two modes. 1. INTRODUCTION In rock engineering fields such as water conservancy and underground resource exploitation, the coupling effect between the seepage field and stress field of fractured rock masses has a significant impact on the response of rock masses under engineering actions (Snow 1969, Tsang and Tsang 1987). The hydraulic conductivity of fractures is much greater than the intact rock matrix, fractures are the main pathways for water movement in rock masses. The complex fracture network system is composed of interconnected individual fractures, and the study of the groundwater movement mechanism within individual fractures forms the foundation of research on complex fracture network systems (Ju et al. 2013, Zhao et al. 2017, 2021, Khanal et al. 2019, Li et al. 2022).
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