Cold Regions Science and Technology | 2019

Micromechanical analysis of frozen silty clay-sand mixtures with different sand contents by triaxial compression testing combined with real-time CT scanning

 
 
 
 
 

Abstract


Abstract Frozen soil-rock mixtures are widely used as geological materials in engineering construction in cold regions. In this paper, a silty clay-sand mixture was selected to simulate the mechanical properties of a frozen soil-rock mixture. A series of triaxial compression tests on frozen silty clay-sand mixtures with different sand contents of 0%, 10%, 20%, and 40% under confining pressures of 0.5\u202fMPa, 1\u202fMPa, 2\u202fMPa and 3\u202fMPa at −6\u202f°C, respectively, was conducted in combination with real-time computed tomography (CT) scanning. The test results indicate that under the same sand content, the strength of the frozen silty clay-sand mixture is maximized when the confining pressure is within the range of approximately 0.5 to 1.0\u202fMPa. By calculating the CT values of all the samples with different sand contents before axial loading, the relationships between the average CT values of the whole samples and the sand contents were determined. In addition, vertical section CT images of the silty clay-sand mixture were collected during the loading process. Based on homogenization theory, a macroscopic yield criterion was formulated to describe the nonlinear behavior of the frozen silty clay-sand mixture considering the influence of the sand content. The evolution laws of the mean CT values of the whole samples with different sand contents were explored throughout the loading process. The CT value of a whole sample decreases linearly with increasing axial strain. By applying a nonassociated flow rule, an elastoplastic constitutive model was established to consider the influence of sand content. The simulation results of the deviatoric stresses versus axial strains and volumetric strains versus axial strains obtained with the proposed model are in good agreement with the experimental results.

Volume 168
Pages 102872
DOI 10.1016/j.coldregions.2019.102872
Language English
Journal Cold Regions Science and Technology

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