Bhagat, Narayan Kumar and Rana, Aditya and Singh, Madan M and Singh, Atul and Singh, Pradeep K. (2021) Prediction of fly-rock during boulder blasting on infrastructure slopes using CART technique. Geomatics, Natural Hazards and Risk, 12 (1).

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Abstract

Boulder blasting is a different process from conventional bench blasting. Fly-rock produced in boulder blasting is a major safety con�cern due to the presence of 360� free-face which may result into excessive throw of the fragments radially up to 900 m distance caus�ing accidents. Many researchers have attempted to predict the fly�rock using empirical and soft computing tools in bench blasting. But, there is paucity of literature to predict the extent of fly-rock in boulder blasting. Machine learning techniques are frequently used in bench blasting to predict ground vibrations, air overpressure, fly�rocks, but it has been rarely used in boulder blasting. In this study, an attempt has been made to use Classification and Regression Trees (CART) technique to predict the fly-rock distance in boulder blasting. Multiple linear regression (MLR) technique has been used to compare the results obtained by the CART technique. Sixty-one boulder blasting events were monitored while excavating the acci�dent-prone slope areas of Konkan Railways. The performance of the developed models using both the techniques has been evaluated using the coefficients of determination (R2 ) and root-mean-square error (RSME) values. The results indicate that CART model (R2 ¼ 0.9555 and RMSE ¼ 1.141) provides better output than MLR model. This paper suggests the use of CART technique in boulder blasting, which will be useful in execution at sensitive locations to predictand control the fly-rock distance.

Item Type:	Article
Uncontrolled Keywords:	Boulder blasting; fly-rock; infrastructure slopes; CART; MLR
Subjects:	Blasting
Divisions:	UNSPECIFIED
Depositing User:	Mr. B. R. Panduranga
Date Deposited:	09 Jul 2021 04:34
Last Modified:	09 Jul 2021 04:34
URI:	http://cimfr.csircentral.net/id/eprint/2368

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