In order to establish the relationship among microscopic properties

loading rates and macroscopic responses of cemented geo-materials

the parallel bond model was employed to simulate the physical and mechanical characteristics of the cemented materials based on the discrete element method(DEM). Moreover

a series of undrained triaxial numerical tests were performed with different microscopic parameters (number

cohesion

Young's modulus

internal friction angle of bonds

and void ratio) and loading rates (1

0.1

0.01

0.002 mm/min). Based on three parameters include residual strength

peak strength and the corresponding axial strain

the rate-dependent behaviors of the cemented geo-materials under different microscopic parameters were discussed. Furthermore

based on the numerical test results

BP neural network algorithm is used to establish an intelligent model for predicting the rate-dependent behavior of the macroscopic properties in cemented materials. The results show that: (1) the cemented material has a significant loading rate sensitivity characteristics

presenting a significant increase of the peak strength with the increase of loading rate

and it has a semi-logarithmic linear correlation. However the residual strength and axial strain at peak strength are less sensitive to the loading rates; (2) the rate-dependent behavior of the cemented material is mainly caused by the fragmentation of internal bonds. During the whole shearing process

the evolution of average bond breakage percentage per unit strain shows a similar trend as that of the deviatoric stress. In addition

the average bond breakage percentage increases with the increase of loading rates; (3) the proposed BP neural network model

which considers the influence of microscopic parameters and loading rates on macroscopic responses

can reasonably describe the rate-dependent behavior of the macroscopic properties in cemented materials with the relative error around 10%.