Yazar "Ghasemi, Ebrahim" seçeneğine göre listele

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  • Küçük Resim
    Öğe
    Development of an empirical model for predicting the effects of controllableblasting parameters on flyrock distance in surface mines
    (Elsevier, 2012) Ghasemi, Ebrahim; Sarı, Mehmet; Ataei, Mohammad
    Prediction of flyrock distance has a remarkable role in reduction and control of blasting accident in surface mines. In this paper, at first a new empirical equation for predicting flyrock distance was developed using dimensional analysis. The equation extended based on controllable blasting parameters that compiled from 150 blasting events in Sungun copper mine, Iran. Then, flyrock phenomenon is simulated using this equation and Monte Carlo (MC) method. Results showed that MC is a good means for modeling and assessing the variability of blasting parameters. Finally, sensitivity analysis was conducted to analyze the effects of the controllable blasting parameters on flyrock distance. Based on correlation sensitivity, the most effective parameters were powder factor, stemming and burden. Finally, it should be noted that the proposed flyrock equation and obtained results are site-specific; it should be used only in the Sungun copper mine, and it should not be used directly in other surface mines.
  • Küçük Resim
    Öğe
    Stochastic assessment of rockburst potential in underground spaces using Monte Carlo simulation
    (Springer, 2022) Kadkhodaei, Mohammad Hossein; Ghasemi, Ebrahim; Sarı, Mehmet
    Rockburst (RB) is known as one of the deadliest and most destructive geotechnical events in deep underground spaces under high stresses. The complexity of the RB phenomenon and uncertainty arising from variability in geotechnical and geomechanical conditions makes its prediction very difficult. The current study is an attempt to address the suitability of the stochastic modeling approach for the evaluation of RB potential and to assess the effects of the contributing parameters on the phenomenon. To do this study, a database containing the major effective parameters on RB potential (i.e. stress concentration coefficient, brittleness coefficient, and elastic energy index) compiled from 335 case histories of RB in various underground projects worldwide was applied. Using this database, first, a new deterministic mathematical relation for predicting RB potential was developed using gene expression programming (GEP) method. Then, the RB phenomenon was simulated by the Monte Carlo (MC) method. The results reveal that stochastic modeling is a good means for modeling and evaluating the effects of the variability of contributing parameters on RB. Finally, sensitivity analysis was conducted to analyse the effects of the contributing parameters on RB potential. Sensitivity analysis showed that stress concentration coefficient, brittleness coefficient, and elastic energy index have a direct relationship with RB potential. Furthermore, the elastic energy index was found to be the most effective parameter on the RB potential with regression coefficient of + 0.50.