Use of intelligent methods to design effective pattern parameters of mine blasting to minimize flyrock distance
Flyrock is one of the most important environmental issues in mine blasting, which can affect equipment, people and could cause fatal accidents. Therefore, minimization of this environmental issue of blasting must be considered as the ultimate objective of many rock removal projects. This paper descr...
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my.utm.907582021-04-30T14:57:18Z http://eprints.utm.my/id/eprint/90758/ Use of intelligent methods to design effective pattern parameters of mine blasting to minimize flyrock distance Zhou, Jian Koopialipoor, Mohammadreza Murlidhar, Bhatawdekar Ramesh Fatemi, Seyed Alireza M. Tahir, M. Armaghani, Danial Jahed Li, Chuanqi TA Engineering (General). Civil engineering (General) Flyrock is one of the most important environmental issues in mine blasting, which can affect equipment, people and could cause fatal accidents. Therefore, minimization of this environmental issue of blasting must be considered as the ultimate objective of many rock removal projects. This paper describes a new minimization procedure of flyrock using intelligent approaches, i.e., artificial neural network (ANN) and particle swarm optimization (PSO) algorithms. The most effective factors of flyrock were used as model inputs while the output of the system was set as flyrock distance. In the initial stage, an ANN model was constructed and proposed with high degree of accuracy. Then, two different strategies according to ideal and engineering condition designs were considered and implemented using PSO algorithm. The two main parameters of PSO algorithm for optimal design were obtained as 50 for number of particle and 1000 for number of iteration. Flyrock values were reduced in ideal condition to 34 m; while in engineering condition, this value was reduced to 109 m. In addition, an appropriate blasting pattern was proposed. It can be concluded that using the proposed techniques and patterns, flyrock risks in the studied mine can be significantly minimized and controlled. Springer 2020-04-01 Article PeerReviewed Zhou, Jian and Koopialipoor, Mohammadreza and Murlidhar, Bhatawdekar Ramesh and Fatemi, Seyed Alireza and M. Tahir, M. and Armaghani, Danial Jahed and Li, Chuanqi (2020) Use of intelligent methods to design effective pattern parameters of mine blasting to minimize flyrock distance. Natural Resources Research, 29 (2). pp. 625-639. ISSN 1520-7439 http://dx.doi.org/10.1007/s11053-019-09519-z DOI:10.1007/s11053-019-09519-z |
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TA Engineering (General). Civil engineering (General) Zhou, Jian Koopialipoor, Mohammadreza Murlidhar, Bhatawdekar Ramesh Fatemi, Seyed Alireza M. Tahir, M. Armaghani, Danial Jahed Li, Chuanqi Use of intelligent methods to design effective pattern parameters of mine blasting to minimize flyrock distance |
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Flyrock is one of the most important environmental issues in mine blasting, which can affect equipment, people and could cause fatal accidents. Therefore, minimization of this environmental issue of blasting must be considered as the ultimate objective of many rock removal projects. This paper describes a new minimization procedure of flyrock using intelligent approaches, i.e., artificial neural network (ANN) and particle swarm optimization (PSO) algorithms. The most effective factors of flyrock were used as model inputs while the output of the system was set as flyrock distance. In the initial stage, an ANN model was constructed and proposed with high degree of accuracy. Then, two different strategies according to ideal and engineering condition designs were considered and implemented using PSO algorithm. The two main parameters of PSO algorithm for optimal design were obtained as 50 for number of particle and 1000 for number of iteration. Flyrock values were reduced in ideal condition to 34 m; while in engineering condition, this value was reduced to 109 m. In addition, an appropriate blasting pattern was proposed. It can be concluded that using the proposed techniques and patterns, flyrock risks in the studied mine can be significantly minimized and controlled. |
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Article |
author |
Zhou, Jian Koopialipoor, Mohammadreza Murlidhar, Bhatawdekar Ramesh Fatemi, Seyed Alireza M. Tahir, M. Armaghani, Danial Jahed Li, Chuanqi |
author_facet |
Zhou, Jian Koopialipoor, Mohammadreza Murlidhar, Bhatawdekar Ramesh Fatemi, Seyed Alireza M. Tahir, M. Armaghani, Danial Jahed Li, Chuanqi |
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Zhou, Jian |
title |
Use of intelligent methods to design effective pattern parameters of mine blasting to minimize flyrock distance |
title_short |
Use of intelligent methods to design effective pattern parameters of mine blasting to minimize flyrock distance |
title_full |
Use of intelligent methods to design effective pattern parameters of mine blasting to minimize flyrock distance |
title_fullStr |
Use of intelligent methods to design effective pattern parameters of mine blasting to minimize flyrock distance |
title_full_unstemmed |
Use of intelligent methods to design effective pattern parameters of mine blasting to minimize flyrock distance |
title_sort |
use of intelligent methods to design effective pattern parameters of mine blasting to minimize flyrock distance |
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Springer |
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2020 |
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http://eprints.utm.my/id/eprint/90758/ http://dx.doi.org/10.1007/s11053-019-09519-z |
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