Applied Sciences (Apr 2024)

Research on Optimization of an Open-Bench Deep-Hole Blasting Parameter Using an Improved Gray Wolf Algorithm

  • Li Zhao,
  • Dengfeng Su,
  • Zhengguo Li,
  • Banghong Chen,
  • Rui Wang,
  • Rongkai Chen

DOI
https://doi.org/10.3390/app14083514
Journal volume & issue
Vol. 14, no. 8
p. 3514

Abstract

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The blasting quality of open-pit mining can be enhanced and the production cost of stope reduced by establishing a mathematical model for step drilling and blasting costs based on stope consumption. By enhancing the Gray Wolf algorithm, the parameters for step drilling and blasting are optimized, resulting in improved effectiveness for step blasting mining, as demonstrated through modeling and calculation. The enhanced Gray Wolf algorithm effectively enhances the blasting performance, reduces production costs, and increases production efficiency. Taking a limestone mine as an example, the optimized drilling and blasting parameters are as follows: hole spacing of 4.62 m, row spacing of 4 m, and explosive consumption rate of 0.23 kg/t; based on these parameters, the stope’s production cost is reduced to CNY 7.7.

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