Probabilistic air-overpressure simulation resulting from blasting operations

Abstract

Air-overpressure (AOp) is one of the significant environmental issues that may be produced by blasting operations. As AOp may result in serious damages in neighboring areas, it has to be predicted and controlled before carrying out the blasting operations. In this paper, in order to address the AOp problem, multiple linear regression (MLR) and Monte Carlo simulation techniques were employed. 76 blasting operations from a quarry site in Malaysia were investigated and used to predict AOp using MLR equation. Then, the developed equation was used to develop the Monte Carlo simulation. Hole depth, stemming, burden, spacing, maximum charge per delay, powder factor, total charge, and distance from the blast face are the eight variable that used for Monte Carlo simulation. There are 10,000 iterations that have been applied in the Monte Carlo simulation and the results showed that the minimum, maximum amount of AOp is 67.17 and 134.24 dB, respectively. Performing the Monte Carlo simulation with 10,000 trials ensures that all probability of any combinations between variables had been considered in AOp simulation. Moreover, the mean of the amount of predicted and simulated AOp is very close, which means that the Monte Carlo simulation is well capable of AOp simulation. Regression and correlation sensitivity analyses were carried out in order to find out the most sensitive and effective variable in the result of AOp. The results of sensitivity analyses indicated that distance from the blast face and maximum charge per delay were the most effective variables in the calculation of AOp. It is worth mentioning that the proposed MLR and Monte Carlo models should be reconsidered for different conditions.