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Probabilistic air-overpressure simulation resulting from blasting operations

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...

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Main Authors: Mahdiyar, Amir, Marto, Aminaton, Mirhosseinei, Seyed Abolghasem
Format: Article
Published: Springer 2018
Subjects:
T Technology (General)
Online Access:http://eprints.utm.my/id/eprint/85652/
http://dx.doi.org/10.1007/s12665-018-7293-x
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spelling my.utm.856522020-07-07T05:16:18Z http://eprints.utm.my/id/eprint/85652/ Probabilistic air-overpressure simulation resulting from blasting operations Mahdiyar, Amir Marto, Aminaton Mirhosseinei, Seyed Abolghasem T Technology (General) 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. Springer 2018-02 Article PeerReviewed Mahdiyar, Amir and Marto, Aminaton and Mirhosseinei, Seyed Abolghasem (2018) Probabilistic air-overpressure simulation resulting from blasting operations. Environmental Earth Sciences, 77 (4). p. 123. ISSN 1866-6280 http://dx.doi.org/10.1007/s12665-018-7293-x
institution Universiti Teknologi Malaysia
building UTM Library
collection Institutional Repository
continent Asia
country Malaysia
content_provider Universiti Teknologi Malaysia
content_source UTM Institutional Repository
url_provider http://eprints.utm.my/
topic T Technology (General)
spellingShingle T Technology (General)
Mahdiyar, Amir
Marto, Aminaton
Mirhosseinei, Seyed Abolghasem
Probabilistic air-overpressure simulation resulting from blasting operations
description 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.
format Article
author Mahdiyar, Amir
Marto, Aminaton
Mirhosseinei, Seyed Abolghasem
author_facet Mahdiyar, Amir
Marto, Aminaton
Mirhosseinei, Seyed Abolghasem
author_sort Mahdiyar, Amir
title Probabilistic air-overpressure simulation resulting from blasting operations
title_short Probabilistic air-overpressure simulation resulting from blasting operations
title_full Probabilistic air-overpressure simulation resulting from blasting operations
title_fullStr Probabilistic air-overpressure simulation resulting from blasting operations
title_full_unstemmed Probabilistic air-overpressure simulation resulting from blasting operations
title_sort probabilistic air-overpressure simulation resulting from blasting operations
publisher Springer
publishDate 2018
url http://eprints.utm.my/id/eprint/85652/
http://dx.doi.org/10.1007/s12665-018-7293-x
_version_ 1672610564611768320
score 13.211869

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