Given the critical role of hydraulic blasting in practical blasting engineering and the fundamental importance of crack propagation studies for revealing blasting mechanisms, this research focused on investigating the crack propagation evolution law in water pressure blasting through model experiments. Small-scale cement mortar specimens were prepared for blasting tests, with high-speed photography employed to capture dynamic fracture processes. The study systematically analyzed surface crack characteristics, quantified crack propagation velocities, and examined the stress field distributions in the specimens during hydraulic blasting operations. The experimental results indicate that the water-coupled charge structure generates 5 extensive surface cracks on the test block after blasting, whereas the non-hydraulic structure produces only 1 primary fracture, clearly demonstrating the superior fracturing effectiveness of hydraulic blasting technology. Experimental measurements reveal that the water-coupled charge specimen initiates cracking 0.112 ms earlier than its non-hydraulic counterpart, achieving a peak crack propagation velocity of 645.85 m/s. This represents approximately a 2.5-fold increase over the non-hydraulic structure′s performance, with a corresponding substantial enhancement in average propagation speed. Lateral tensile stress predominantly governs crack propagation on specimen surfaces, with the water-coupled charge structure exhibiting consistently higher surface strain magnitudes than non-hydraulic configurations throughout the fracturing process. These findings establish crucial theoretical foundations for optimizing hydraulic blasting techniques in engineering practice.

Optimizing blasting plans according to actual rock mass classification represents a critical approach for enhancing blasting outcomes. However, field construction conditions present significant challenges in obtaining direct rock mass classification data across different excavation face zones. This study proposes a rock mass classification method utilizing on-site drilling parameters, with application to a Chongqing tunnel project. Firstly, the characteristics of the rock mass were investigated, and the rock mass class was dⅣided. The drilling data were then collected, and drilling parameters related to the rock mass class were screened. Furthermore, the data volume of small sample classes was expanded by the Mahalanobis Distance-based Over-sampling technique (MDO). Meanwhile, the relationship between drilling parameters and rock mass class was modeled using the Extreme Gradient Boosting (XGBoost) algorithm, and an identification model for rock mass class was then established. Finally, the site blasting scheme was optimized based on the identification results. The results show that the MDO-XGBoost model achieves an overall classification accuracy of 80% for rock mass grade identification. The optimized blasting scheme has increased blasting penetration and shortened deslagging time, based on the rock mass classification results. This research presents a viable method for accurately identifying rock mass classes based on drilling parameters, particularly in the context of sample imbalance, thereby contributing to intelligent blasting and efficient construction in tunnel projects.