Abstract
Blast-induced ground vibration is one of the most important environmental impacts of blasting operations because it may cause severe damage to structures and plants in nearby environment. Estimation of ground vibration levels induced by blasting has vital importance for restricting the environmental effects of blasting operations. Several predictor equations have been proposed by various researchers to predict ground vibration prior to blasting, but these are site specific and not generally applicable beyond the specific conditions. In this study, an attempt has been made to predict the peak particle velocity (PPV) with the help of fuzzy logic approach using parameters of distance from blast face to vibration monitoring point and charge weight per delay. The PPV and charge weight per delay were recorded for 33 blast events at various distances and used for the validation of the proposed fuzzy model. The results of the fuzzy model were also compared with the values obtained from classical regression analysis. The root mean square error estimated for fuzzy-based model was 5.31, whereas it was 11.32 for classical regression-based model. Finally, the relationship between the measured and predicted values of PPV showed that the correlation coefficient for fuzzy model (0.96) is higher than that for regression model (0.82).
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Ambraseys, N. R., & Hendron, A. J. (1968). Dynamic behavior of rock masses. In K. G. Stagg, & O. C. Zeinkiewicz (Eds.), Proceedings of the rock mechanics in engineering practices (pp. 203–227). London: Wiley.
Babuska, R., Verbruggen, H. B., & Hellendoorn, H. (1999). Promising fuzzy modeling and control methodologies for industrial applications. In ERUDIT (Ed.), CD-ROM Proceedings of European symposium on intelligent techniques, 3–4 June, Greece.
Berga, C. G. (2005). A new approach to the synthesis of intelligible fuzzy models from input–output data. Ph.D. thesis, Enginyeria i Arquitectura La Salle, Universitat Ramon Llull, Spain.
Berta, G. (1994). Blasting induced vibration in tunneling. Nobel Hefte, 2, 61–76.
Dowding, C. H. (1985). Blast vibration monitoring and control. Englewood Cliffs: Prentice-Hall.
Drew, L. J., Langer, W. H., & Sachs, J. S. (2002). Environmentalism and natural aggregate mining. Natural Resources Research, 11, 19–28.
Duvall, W. I., & Fogelson, D. E. (1962). Review of criteria for estimating damage to residences from blasting vibration. Washington: U.S. Bureau of Mines R.I. 5968.
Grima, M. A., & Babuska, R. (1999). Fuzzy model for the prediction of unconfined compressive strength of rock samples. International Journal of Rock Mechanics and Mining Sciences, 36, 339–349.
Khandelwal, M., & Singh, T. N. (2007). Evaluation of blast-induced ground vibration predictors. Soil Dynamics and Earthquake Engineering, 27, 116–125.
Klir, G. J. (2004). Fuzzy logic: A specialized tutorial. In R. V. Demicco, & G. J. Klir (Eds.), Fuzzy logic in geology (pp. 11–61). New York: Academic.
Konya, C. J. & Walter, E. J. (1990). Surface blast design. Englewood Cliffs: Prentice-Hall.
Kuzu, C. (2008). The importance of site-specific characters in prediction models for blast-induced ground vibrations. Soil Dynamics and Earthquake Engineering, 28, 405–414.
Kuzu, C., & Ergin, H. (2005). An assessment of environmental impacts of quarry-blasting operation: A case study in Istanbul, Turkey. Environmental Geology, 48, 211–217.
Langefors, U., & Kihlstrom, B. (1978). The modern technique of rock blasting. New York: Wiley.
Langer, W. H. (2001). Environmental impacts of mining natural aggregate. In: R. L. Bon, R. F. Riordan, B. T. Tripp, & S. T. Krukowski (Eds.), Proceedings of the 35th forum on the geology of industrial minerals—The Intermountain West forum (pp. 127–138). Utah: Geological Survey Miscellaneous Publication.
Mamdani, E. H., & Assilian, S. (1975). An experiment in linguistic synthesis with a fuzzy logic controller. International Journal of Man–Machine Studies, 7, 1–13.
Mohamed, M. T. (2009). Artificial neural network for prediction and control of blasting vibrations in Assiut (Egypt) limestone quarry. International Journal of Rock Mechanics & Mining Sciences, 46, 426–431.
Rosenthal, M. F., & Morlock, G. L. (1987). Blasting guidance manual. U.S Office of Surface Mining Reclamation and Enforcement: U.S. Department of The Interior.
Ross, T. J. (2004). Fuzzy logic with engineering applications. London: Wiley.
Roy, P. P. (1991). Vibration control in an opencast mine based on improved blast vibration predictors. Mining Science and Technology, 12, 157–165.
Singh, T. N. (2004). Artificial neural network approach for prediction and control of ground vibrations in mines. Transactions of the Institution of Mining and Metallurgy Security A, 113, A251–A256.
Singh, T. N., & Singh, V. (2005). An intelligent approach to prediction and control ground vibration in mines. Geotechnical and Geological Engineering, 23, 249–262.
White, T. J., & Farnfield, R. A. (1993). Computers and blasting. Transactions of the Institution of Mining and Metallurgy Security A, 102, A1–A70.
Zadeh, L. A. (1965). Fuzzy sets. Information and Control, 8, 338–353.
Zadeh, L. A. (1973). Outline of a new approach to the analysis of complex systems and decision processes. IEEE Transactions on Systems, Man and Cybernetics, SMC-3, 28–44.
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Fişne, A., Kuzu, C. & Hüdaverdi, T. Prediction of environmental impacts of quarry blasting operation using fuzzy logic. Environ Monit Assess 174, 461–470 (2011). https://doi.org/10.1007/s10661-010-1470-z
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DOI: https://doi.org/10.1007/s10661-010-1470-z