Analysis and Intelligent Prediction of Mechanical Properties of Similar Materials Under Hydro-dynamic Coupling and the Application to Complex Rock Mass Engineering Model Tests
摘要
The damage process of geotechnical materials under hydro-dynamic coupling is nonlinear and time-varying, making it difficult to describe using hydraulic or dynamic analysis alone. A novel hydro-dynamic coupled similar material is urgently needed to study the disaster mechanisms of the slope and tunnel. Based on the seepage-vibration equation and dimensional analysis, similarity criteria under hydro-dynamic coupling were derived. A new similar material was developed using quartz sand, iron powder, barite powder, gypsum, sodium silicate, and glycerol. The influence of material composition on physical and mechanical parameters was explored through a series of laboratory tests, including dynamic triaxial tests, SEM, sensitivity analysis, and PCA. Meanwhile, the material was successfully applied in rock slope and tunnel model tests. The results show that the physical and mechanical parameters of the materials have a wide adjustable range. The dynamic elastic modulus and permeability depend on the model’s geometric dimensions, with permeability primarily controlled by gypsum and the elastic modulus by the binder. Additionally, a MIMO-PSO-BP neural network was proposed to predict physical parameters. Both the PCA and the MIMO-PSO-BP model effectively capture nonlinear relationships between composition and parameters. In summary, the novel similar material meets the requirements (parameter variation, hydraulic stability, and dynamic response) for slope shaking table model tests and tunnel excavation model tests under hydro-dynamic coupling effects. This work provides the theoretical support and experimental basis for understanding the disaster evolution mechanism of slopes or tunnels under complex geological conditions.