ANALYSIS OF POROSITY, PERMEABILITY, AND ANISOTROPY OF SANDSTONE IN FREEZE–THAW ENVIRONMENTS USING COMPUTED TOMOGRAPHY AND FRACTAL THEORY

曲折 分形维数 各向异性 分形 地质学 磁导率 多孔性 矿物学 几何学 断裂(地质) 岩土工程 材料科学 数学 物理 化学 数学分析 光学 生物化学
作者
Hao Tan,Yongjun Song,Xixi Guo
出处
期刊:Fractals [World Scientific]
卷期号:29 (08) 被引量:6
标识
DOI:10.1142/s0218348x2150239x
摘要

An in-depth understanding of the deterioration characteristics of porous rock materials in freeze–thaw (F–T) environments is very important for rock mass engineering in cold regions. However, quantitative descriptions of key rock indicators such as porosity, permeability, and anisotropy are lacking. In this paper, computed tomography (CT) was used to study saturated intact sandstone, saturated fractured sandstone, and ice-filled fractured sandstone under various F–T cycles and stress states. Meso-structural parameters were obtained by reconstructing the three-dimensional fracture networks from CT images. Then, based on fractal geometry theory, the fractal dimension ([Formula: see text], tortuosity fractal dimension ([Formula: see text], and anisotropic two-dimensional fractal dimension ([Formula: see text] of the sandstone samples were analyzed quantitatively. The [Formula: see text] gradually increased during the F–T process, while [Formula: see text] gradually decreased. Compared with [Formula: see text], [Formula: see text] was found to describe changes in the absolute permeability of rocks under F–T cycling more accurately. Anisotropy in sandstone was enhanced by F–T cycling. After uniaxial compression, the [Formula: see text] value was the greatest in ice-filled fractured sandstone. In addition, the tree-like fracture structure produced by F–T cycling expanded the range of self-similarity, which enhanced the fractal characteristics of sandstone. However, due to the large frost heave pressure of ice-filled sandstone, fracture expansion accelerated in the later period of F–T cycling, which destroyed the self-similarity. These results assist in understanding the F–T characteristics of porous rock materials. The method described provides a new way to better evaluate and predict F–T-related engineering disasters.
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