Optimization of Blast Parameters based on Geo-mechanical Properties of Rock to Prevent Creation of Toes and Boulders in Mine Benches

Toe and boulder due to blasts in the open pit mines reduce the production efficiency and increase extraction costs. In this study, these phenomena were reduced to correct the blast parameters of the ore blocks in the Sirjan Golgohar-2 Mine. For this purpose, the values of seven effective parameters including, an average of depth holes, burden, sub-drilling, powder factor, spacing, rock quality designation, and blastability index were collected for 19 blasting blocks in the studied mine. In this research, the values of Geo-mechanical properties of rock mass were obtained by the photogrammetric method and discontinuity set extractor software. Subsequently, the experimental models were created to predict the volume of boulder and toe relative to the volume of blasting block by nonlinear multiple regression. The predicted ability related to each of the created models by statistical indicators was investigated, and it was determined that the polynomial model to product boulder and the exponential model for toe are more accurate with 94.43 and 98.13 coefficients of determination respectively. Then, the minimization process of these phenomena was performed to access optimal values of controllable parameters and their coefficients in each of the created two models simultaneously by the combinational algorithm of Particle Swarm Optimization-Genetic algorithm. Finally, to evaluate the predicted ability of two optimized models, four blasts based on the optimized information were performed on the mine. The results showed that the models predicted the volume of boulder and toe relative to the block volume with the Root Mean Square Error 0.47 and 0.08 respectively.