Risk assessment and prediction of rock fragmentation produced by blasting operation: a rock engineering system

Poor fragmentation is one of the most side effects induced by blasting operations. Therefore, risk assessment and prediction of rock fragmentation are essential to reduce the mentioned effects. In the present study, an attempt has been made to evaluate the risk associated with rock fragmentation as well as its prediction at Sarcheshmeh copper mine, Iran, proposing the rock engineering system (RES) technique. A total number of 52 blasting events were collected and considered and the values of 10 key effective parameters in rock fragmentation were carefully measured in the mine. These 10 key parameters were only related to blasting design and rock mass properties were not considered in the analysis of this study due to some limitations regarding their measurements in the mine. The RES result showed that the level of overall risk, based on the considered blast events, is in the range of medium–high. Furthermore, it was found that the burden is the most interaction factor in the rock fragmentation. In case of rock fragmentation prediction, all of datasets were divided randomly to training and testing datasets for proposing RES model. For comparison purpose, non-linear multiple regression (NLMR) was also employed for estimating rock fragmentation. The performances of the proposed predictive models were examined according to three performance indices, i.e. coefficient of determination (R ²), root mean square error (RMSE) and variance account for (VAF). The obtained results of this study indicated that the RES is a reliable method to predict rock fragmentation with a higher degree of accuracy in comparison to NLMR model. For instance, RMSE values of 1.95 and 4.002 for testing datasets of RES and NLMR models, respectively, suggest the superiority of the RES model in predicting rock fragmentation compared to other developed model.