A particle discontinuous deformation analysis approach integrated with smooth-joint model for simulating mechanical properties of layered rock mass

This study develops and implements a smooth joint model (SJM) within the framework of particle discontinuous deformation analysis (DDA). By integrating experimental results, the study investigates the strength and failure behavior of stratified rock samples subjected to various bedding inclinations and microparameters. Initially, seven stratified rock samples with differing bedding inclinations were created using the SJM, and a sensitivity analysis of the SJM microparameters was performed through uniaxial compression simulations. The results indicate that the compressive strength of the samples exhibits anisotropy with changing bedding inclination angles, with the highest strength observed at bedding angles of 0°or 15°and the lowest at 60°or 75°. The SJM tensile strength significantly influences samples with high inclinations, while cohesion notably affects samples in the mid-to-high inclination range. The internal friction angle of the SJM has a strong impact on samples within the 30°–75° range. In contrast, the SJM stiffness parameters have a minor effect on compressive strength. The elastic modulus of the samples is less influenced by bedding inclination and SJM strength parameters, with SJM stiffness being the primary influencing factor. Based on these findings, a microparameter calibration method for the Smooth Joint Model within the proposed framework is introduced and applied to analyze the mechanical properties of stratified rock masses. The trends in compressive strength and elastic modulus for different inclination angles observed in the simulations are generally consistent with theoretical solutions and align well with experimental data. Furthermore, the simulated failure modes correlate with the experimental results. The simulation outcomes validate the effectiveness of the proposed method, providing new tools for simulating complex jointed rocks in engineering applications, particularly in predicting mechanical behavior and analyzing failure modes.