JOURNAL OF ROCK MECHANICS

JOURNAL OF ROCK MECHANICS

Development of a Mathematical Model for Predicting Blast-Induced Fragmentation Considering Elastic Wave Velocities

Document Type : Original Article

Authors
1 Exploitation Division, Faculty of Mining and Materials, Tarbiat Modares University
2 Head of Research, Mining and Geology Department, Gol-Gohar Iron Ore Mine
Abstract
Blasting is a critical step in open pit mining and has a significant impact on the efficiency of other mining operations. Predicting blasting fragmentation is of particular importance, and in this regard, mathematical and intelligent models have been developed to improve the accuracy of predictions. In this study, Golgohar Mine No. 1 was selected as a case study. Using a downhole seismograph, the elastic wave velocities (longitudinal and transverse) were measured for thirteen blast blocks, and the quality of the fragmentation was evaluated using an image analysis method. Two mathematical models based on multivariate regression were developed: one was a linear model and the other was a nonlinear model. The results showed that the nonlinear model with a determination coefficient of 95% performed better than the linear model with a determination coefficient of 80%. These findings indicate that considering the elastic wave characteristics of the rock mass can significantly increase the accuracy of predicting blasting fragmentation. Therefore, using these advanced models can help improve the mining process and reduce costs. This study also emphasizes the importance of using seismic data in optimizing blasting operations.
Keywords

 
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