With the expansion of underground construction, deep rock mass excavation technology has attracted growing attention, as complex geology and developed joints in deep rock masses challenge rock mass integrity and stability. This paper, based on blasting excavation at Meizhou Pumped Storage Power Station, studies cavern displacement and surrounding rock damage from blasting in jointed rock masses via on-site vibration tests and ultrasonic experiments. Joints significantly increase blasting vibration velocity and rock damage depth. Two control measures are proposed: joint grouting and precision blasting, validated by numerical simulation. Joint grouting enhances joint stiffness, reducing unloading stress wave reflection and rock damage. Post-grouting, peak vibration velocities on both cavern sides decrease, more notably on the joint side, with reductions of 3.05 cm/s, 2.86 cm/s, and 3.97 cm/s in three directions. The right-side damage depth is reduced by 1.01 m, 40%. Precision blasting optimizes borehole layout and initiation networks, extending unloading time and reducing transient unloading effects. Its three-directional peak vibration velocity reductions are 2.53 cm/s, 2.53 cm/s, and 3.07 cm/s; non-joint side reductions are 1.85 cm/s, 1.53 cm/s, and 2.03 cm/s. Average damage depth decreases by 0.47 m (left) and 0.61 m (right).

To address pilot shaft blockage and fragmentation control issues in inclined shaft blasting excavation, this study investigated the coupling mechanism between excavated rock mass damage distribution and fragmentation gradation using the Tianchi Pumped Storage Power Station water diversion tunnel inclined shaft project. A statistical correlation between dynamic damage distribution and blasting fragmentation was established through field blasting experiments and LS-DYNA numerical simulations. Based on this correlation, a fragmentation prediction model was developed using the dynamic damage distribution of the excavated rock mass.The study analyzed the influence mechanisms of three key parameters - decoupling coefficient, blasthole spacing, and detonating delay time - on rock fragmentation and size distribution, determining optimized blasting parameters for the project. Results show the damage distribution-based prediction model achieved high fitting accuracy (R²=0.9689) with maximum field validation deviation of only 2.49%, demonstrating excellent engineering applicability and promotional value. The decoupling coefficient and blasthole spacing are primary controlling factors for fragmentation distribution. Reducing the decoupling coefficient and decreasing blasthole spacing significantly enhance rock fragmentation degree and fine particle content while suppressing oversized fragment generation. Detonating delay time has limited impact, serving primarily an auxiliary optimization function. Optimized blasting parameters effectively reduced oversized fragment percentage and improved blasting efficiency and economic viability. The proposed blasting fragmentation statistical prediction method provides a novel and implementable technical approach for fragmentation prediction and parameter optimization in complex underground engineering projects.

Aging river levees are heterogeneous flood-defense earthworks whose reliability is affected by limited site data, interparameter dependence, and spatial variability. This study develops an integrated framework combining normal information diffusion (NID), Copula-based dependence identification, cross-correlated random fields (CCRFs), and Monte Carlo reliability analysis. Reliability was evaluated using Monte Carlo simulation based on a simplified infinite-slope benchmark model. Data were obtained from the authors’ own site investigations and laboratory tests. NID yields the lowest Kolmogorov–Smirnov statistics for all documented variables and better preserves local fluctuations and lower-strength tails than four classical marginals. Gaussian Copula is preferred for the representative bivariate cases and slightly outperforms the multivariate t Copula for Hongpaihe. For strongly dependent Beiwei data, the correlated model gives a mean factor of safety of 1.235 and a failure probability of 0.153, whereas independence gives a similar mean factor of safety of 1.238 but increases failure probability to 0.200. The weakly dependent main-dike case changes negligibly, while the φ–γ pair dominates the trivariate response. Illustrative CCRF realizations show how pointwise dependence can propagate into spatially continuous weak zones. Failure probability is therefore more diagnostic than mean factor of safety when stochastic model form is uncertain. The main novelty lies in the consistent integration and propagation of marginal, dependence, and spatial uncertainties within a unified levee reliability framework.

To address the coordinated control of rock-breaking energy efficiency and construction-induced vibration of a twin-wheel trench cutter in vibration-sensitive urban environments, a three-dimensional explicit dynamic model of twin-wheel rock cutting was established based on the JH-2 constitutive model, and multi-objective optimization of construction parameters was performed by combining response surface methodology (RSM) with the NSGA-II algorithm. The applicability of the adopted JH-2 parameter set for describing the dynamic response of sandstone was evaluated through comparison with split Hopkinson pressure bar (SHPB) test results. On this basis, the stress response, damage propagation, fragmentation evolution, and vibration characteristics of the rock under the successive action of multiple cutter teeth were investigated. The results show that rock failure within the twin-wheel interaction zone evolves successively from localized damage and damage-band propagation to coalescence of the damaged zones between the two cutter wheels and continuous fragmentation. Free surfaces generated by preceding fragmentation reduce the confinement of subsequent cutter–rock interaction zones and facilitate further rock breakage. The cutting load exhibits pronounced intermittent impact and non-stationary characteristics, while the induced rock vibration shows broadband and multi-frequency responses. The peak particle velocity (PPV) generally decreases with increasing propagation distance and is positively correlated with the milling force. Response surface models were established with specific energy (SE) and PPV as the optimization objectives. In terms of the linear effects, SE is influenced, in descending order, by milling thickness, cutting angle, and milling speed, whereas PPV is mainly governed by milling thickness and milling speed, with milling angle exhibiting a pronounced nonlinear effect. Increasing the milling thickness reduces SE but simultaneously increases PPV, demonstrating a distinct trade-off between rock-breaking energy efficiency and vibration control. The proposed SE–PPV multi-objective optimization framework provides a basis for selecting twin-wheel cutting parameters that balance efficient rock breaking and vibration control in vibration-sensitive urban environments.