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Abstract: In this study, we propose a digital image processing technology for estimating the macro permeability property of heterogeneous geomaterials. The technology is based on a connected-component labeling algorithm and provides a novel and effective method for geometry vectorization and microstructure identification. A color photo of a soil and rock mixture (SRM) is taken as an example. Information about the distribution of aggregate and a vectorgraph, which can be used in numerical analysis, are obtained automatically. A numerical permeability test is carried out to estimate the macro permeability coefficient of the heterogeneous medium. The effects on macro permeability of three parameters, scale dependency, material heterogeneity and the rock fraction, are discussed. The results indicate that the SRM has a scale dependent property and the representative element volume (REV) length is about six times the maximum major axis of the aggregate. The heterogeneity parameter has a major effect on macro permeability characteristics within a certain range. There is a weak tendency for the macro permeability to decrease as the rock fraction increases. Although the rock fraction is not the only factor, it does have an influence on the macro permeability. We conclude that the novel method developed in this study has good prospects for widespread application in macro parameter estimation and related research fields.

The authors establishes a digital image processing together with FEM numerical method for permeability analysis of geomaterials considering the material heterogeneity. The manuscript is well organized and easy to follow.

基于数字图像的非均匀岩土材料渗透系数研究

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