Prediction of fragmentation by blasting operation in mines- case study: Gol-e-Gohar iron mine
Subject Areas :
Ahmad Asadi
1
(
استادیار دانشگاه آزاد اسلامی، واحد تهران جنوب
)
Eman Enayatollahi
2
(
دانش آموخته کارشناسی ارشد استخراج معدن، دانشگاه آزاد اسلامی واحد تهران جنوب
)
Keywords: Blasting, rock fragmentation, linear and nonlinear regression, statistic analyses,
Abstract :
Blasting is a key element in mining operation that constitutes near 30% of total mining cost. If this process doesnot carry out correctly, it will increase up to 50% with secondary blasting. A proper basis blasting operation notonly can reduce side effect on the environment, but also can get rid of some undesirable consequences such asback break, fly rock and secondary blasting. Concerning the above notations a predetermination of a method toestimate the size of the fragmented rock and scattered fragmentation is so important and the results are sobeneficial. In this study after performing a series of blasting at Gol-e-Gohar iron mine using artificial neuralnetwork some models for predicting fragmentation have been achieved. In order to select the best blastingpattern concerning fragmentation, Tagochi method was utilized. In these series of experiments, fragmentationresults by using these two methods was 57.5 and 60 cm respectively, which are close to fragmentation at themine. Consequently, some environmental problems were solved by using this pattern of blasting at the Gol-eGohar iron mine.