Research on Optimization of an Open-Bench Deep-Hole Blasting Parameter Using an Improved Gray Wolf Algorithm
Source abstract
Abstract
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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Research context
OpenAlex topics: Simulation and Modeling Applications · Technology and Security Systems · Industrial Technology and Control Systems
SciVX discovery tags are terminology-based. OpenAlex topics are source-provided classifications.
Affiliations
School of Environment and Resources, Southwest University of Science and Technology, Mianyang 621000, China
Funding
Sichuan Natural Science Foundation Project (Youth Science Foundation Project) · Natural Science Foundation of the Southwest University of Science and Technology
References (33)
Show source-provided references
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