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- W4210695986 abstract "Blastability is defined as the resistance of rock mass to fragmentation due to the dynamic stress of blasting. Comprehensive study and understanding of geomechanical conditions of the in-situ rock mass are necessary to analyze the blastability along with optimal blasting design. Blastability Index (BI) is one of the most widely applied methods for the classification of rock mass and predicting the specific charge of blasting in open pit mines. Regarding the existence of uncertainty in the geomechanical characteristics of in-situ rock masses, accurate BI assessment requires a wide range of field studies. It could lead designers to a wrong decision about rock mass classification. Simulation is one of the reliable and applicable approaches to overcome the geomechanical uncertainties in rock mass studies. Therefore, in this paper, the Monte Carlo simulation method has been applied to blastability assessment in Sungun Copper Mine, Iran. For this purpose, the geological factors, including rock mass description, joint plane spacing, joint plane orientation, specific gravity influence, and hardness, were measured and implemented in 46 points of the pit wall. Statistical analysis was carried out to find out the best fit-distribution functions of all mentioned parameters. After that, the Monte Carlo simulation program was developed and carried out in MATLAB software. The overall results of the simulation reveal that the Monte Carlo method could provide a better vision of any possible combination of geological factors. It is also found out that less than two percent of the rock masses do have challenging blastability conditions, and the average blastability of rock masses in the studied mine is 18, which is close to an average score of blastability classification as well." @default.
- W4210695986 created "2022-02-08" @default.
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- W4210695986 date "2021-06-30" @default.
- W4210695986 modified "2023-09-26" @default.
- W4210695986 title "Uncertainty consideration in rock mass blastability assessment in open pit mines using Monte Carlo simulation" @default.
- W4210695986 doi "https://doi.org/10.17580/em.2021.01.07" @default.
- W4210695986 hasPublicationYear "2021" @default.
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