Estimation of fines generated by blasting – applications for the mining and quarrying industries

estimate the proportion of fines generated during the blasting process. The proposed framework is based on the combination of two Rosin-Rammler based distribution functions to model the full range of fragments expected to be produced during this process. This particular approach, which has been successfully applied for a number of years by the Julius Kruttschnitt Mineral Research Centre (JKMRC), has been improved with the introduction of a new model to predict the potential volume of crushed material resulting from the crushing and shearing stages of blasting. Other sources of fines including liberation of infilling from discontinuities, particle collisions and post-blast processes have been excluded to simplify the modelling process. Validation analysis of the proposed framework has shown that there is good agreement between model predictions and the measured distribution of fines. In three distinct cases, results verified the hypothesis that a single index of uniformity can be used to describe the distribution of fragments in the range of 1 mm through to the expected post-blast mean fragment size (x50). Although some limitations have been noted, the approach appears to provide useful approximations for continuous improvement analysis and applications. The practical application of the proposed modelling framework is demonstrated with an engineering study aimed at assessing the impact of blast fragmentation on the overall production of fines in a hard rock quarry. Results from simulations showed that less crushing requirements due to an overall increase in fragmentation contribute to a decrease in the specific crushing energy and hence a reduction in power consumption requirements. This analysis helped demonstrate the importance of addressing the impact of blast fragmentation distribution on overall quarry productivity requirements; and highlights the importance of adopting a holistic approach when addressing the blast optimisation problem.