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Evaluation and prediction of flyrock resulting from blasting operations using empirical and computational methods

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Abstract

Mines, quarries and construction sites face environmental impacts, such as flyrock, due to blasting operations. Flyrock may cause damage to structures and injury to human. Therefore, flyrock prediction is required to determine safe blasting zone. In this regard, 232 blasting operations were investigated in five granite quarries, Malaysia. Blasting parameters comprising maximum charge per delay and powder factor were prepared to predict flyrock using empirical and intelligent methods. An empirical graph was proposed to predict flyrock distance for different powder factor values. In addition, using the same datasets, two intelligent systems, namely artificial neural network (ANN) and adaptive neuro-fuzzy inference system (ANFIS) were used to predict flyrock. Considering some model performance indices including coefficient of determination (R 2), value account for and root mean squared error and also using simple ranking procedure, the best flyrock prediction models were selected. It was found that the ANFIS model can predict flyrock with higher performance capacity compared to ANN predictive model. R 2 values of testing datasets are 0.925 and 0.964 for ANN and ANFIS techniques, respectively, suggesting the superiority of the ANFIS technique in predicting flyrock.

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Acknowledgments

The authors would like to extend their appreciation to the Government of Malaysia and Universiti Teknologi Malaysia for the FRGS Grant No. 4F406 and for providing the required facilities that made this research possible.

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Authors and Affiliations

  1. Department of Geotechnics and Transportation, Faculty of Civil Engineering, Universiti Teknologi Malaysia, UTM, 81310, Skudai, Johor, Malaysia

    D. Jahed Armaghani, E. Tonnizam Mohamad, S. V. Alavi Nezhad Khalil Abad & A. Marto

  2. Construction Research Alliance, Universiti Teknologi Malaysia, UTM, 81310, Skudai, Johor, Malaysia

    M. Hajihassani

  3. South Tehran Branch, Islamic Azad University, Tehran, Iran

    M. R. Moghaddam

  4. Saman Zamin Hamgam Engineering Company, Tehran, Iran

    M. R. Moghaddam

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  1. D. Jahed Armaghani
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  2. E. Tonnizam Mohamad
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Correspondence to D. Jahed Armaghani.

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Jahed Armaghani, D., Tonnizam Mohamad, E., Hajihassani, M. et al. Evaluation and prediction of flyrock resulting from blasting operations using empirical and computational methods. Engineering with Computers 32, 109–121 (2016). https://doi.org/10.1007/s00366-015-0402-5

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