The strength and consistency of cemented paste backfill (CPB) are of key concerns in the stope stability and cost control for underground mines. It is common practice to use additives, such as superplasticizer, to improve the performance of CPB. This study mainly focuses on the effects of superplasticizer on the hydration, consistency, and strength of CPB. In this study, a polynaphtalene sulfonate was used as the superplasticizer. The binder is a mix of 33.3% ordinary Portland cement and 66.7% fly ash. The CPB specimens with a tailings-binder ratio of 3:1 and a solid concentration of 70% were then tested by a low field nuclear magnetic resonance system after different hydration times. Effects of polynaphtalene sulfonate on the hydration, fluidity, and strength were investigated. Results showed that the polynaphtalene sulfonate has a strong influence on short-duration hydration, which may contribute to the strength increase of CPB. It has been demonstrated that the polynaphtalene sulfonate improved the fluidity of the CPB mixture. With the increased dosage of polynaphtalene sulfonate, the slump increased. It was also found that the polynaphtalene sulfonate dosage has a negligible effect on the 1 day (d) strength while it has a strengthening effect on the 7 d, 14 d, and 28 d strength of CPB specimens.

The pore structure of rock has a great influence on its physical and mechanical properties. Factors such as chemical corrosion and temperature changes affect the pore structure evolution. In this paper, the pore structure of sandstone was investigated under rapid freeze-thaw (F-T) cycles and chemical corrosion. A nuclear magnetic resonance (NMR) testing system is used to study the pore structure of tight sandstone samples immersed in different chemical solutions after 10, 20, and 30 F-T cycles. Permeability is determined by using empirical method. Results found that permeability is strongly affected by the erosion of NaOH and NaCl solutions. The pores in the rock were divided into three categories based on the pore size, i.e., mini-pores, mesopores, and macropores. The results showed that the amount of mini-pores and mesopores both decreased with an increase in the number of F-T cycles while the amount of macropores increased for groups of NaOH, NaCl, and pure water. No conclusive trend can be found in the H ₂ SO ₄ group. Fractal analysis of the pore structure revealed that no conclusive trend was observed for fractal dimension of mini-pores D ₁ . Fractal dimension of mesopores D ₂ ranged from 2.79 to 2.93, indicating a medium complexity pore structure of the mesopores. Fractal dimension of macropores D ₃ was over 2.9, implying that the pore structure of the macropores is the most complex. The fractal dimension of the T ₂ spectrum $\text{D}_{\mathrm {NMR}}$ ranged from 2.55 to 2.77. Correlations between the fractal dimensions and porosity are also presented. Results showed that D ₂ and D ₃ can be good indicators for the pore size volume of sandstone samples immersed in H ₂ SO ₄ , NaOH and NaCl solutions, while $\text{D}_{\mathrm {NMR}}$ is a good indicator for the pore size volume of sandstone samples immersed in NaOH solution and pure water.

For San-Xin gold and copper mine, deep blasting large block rate is high resulting in difficulty in transporting the ore out; secondary blasting not only increases blasting costs but is more likely to cause the top and bottom plate of the underground to become loose causing safety hazards. Based on the research background of Sanxin gold and copper mine, deep hole blasting parameters were determined by single-hole, variable-hole pitch, and oblique hole blasting tests, further using the inversion method to determine the optimal deep hole blasting parameters. Meanwhile, the PSO-BP neural network method was used to predict the block rate in deep hole blasting. The results of the study showed that the optimal minimum resistance line was 1.24–1.44 m, which was lower than 1.6–1.8 m in the original blasting design, which was one of the reasons for the higher blasting block rate. In addition, the PSO-BP deep hole blasting fragmentation prediction model predicts the block rate of the optimized blasting parameters and predicted a block rate of 6.83% after the optimization of hole network parameters. Its prediction accuracy is high, and the blasting parameter optimization can effectively reduce the block rate. It can reasonably reduce the rate of large pieces produced by blasting, improve blasting efficiency, and save blasting costs for enterprises. The result has wide applicability and can provide solutions for underground mines that also have problems with blasting large block rate.