Numerical simulation of direct shear tests on mechanical properties of talus deposits based on self-adaptive PCNN digital image processing

Abstract

The macro mechanical properties of materials with characteristics of large scale and complicated structural composition can be analyzed through its reconstructed meso-structures. In this work, the meso-structures of talus deposits that widely exist in the hydro-power engineering in the southwest of China were first reconstructed by small particles according to the in-situ photographs based on the self-adaptive PCNN digital image processing, and then numerical direct shear tests were carried out for studying the mechanical properties of talus deposits. Results indicate that the reconstructed meso-structures of talus deposits are more consistent with the actual situation because the self-adaptive PCNN digital image processing has a higher discrimination in the details of soil-rock segmentation. The existence and random distribution of rock blocks make the initial shear stiffness, the peak strength and the residual strength higher than those of the “pure soil” with particle size less than 1.25 cm apparently, but reduce the displacements required for the talus deposits reaching its peak shear strength. The increase of rock proportion causes a significant improvement in the internal friction angle of talus deposit, which to a certain degree leads to the characteristics of shear stress-displacement curves having a changing trend from the plastic strain softening deformation to the nonlinear strain hardening deformation, while an unconspicuous increase in cohesion. The uncertainty and heterogeneity of rock distributions cause the differences of rock proportion within shear zone, leading to a relatively strong fluctuation in peak strengths during the shear process, while movement features of rock blocks, such as translation, rotation and crossing, expand the scope of shear zone, increase the required shear force, and also directly lead to the misjudgment that the lower shear strength is obtained from the samples with high rock proportion. That, however, just explains the reason why the shear strength gained from a small amount of indoor test data is not consistent with engineering practice.

Keywords

talus deposits / digital image processing / pulse coupled neural networks (PCNN) / direct shear test / mechanical property / granular discrete element method

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