- Title
- Blasting pattern optimization using gene expression programming and grasshopper optimization algorithm to minimise blast-induced ground vibrations
- Creator
- Bayat, Parichehra; Monjezi, Mejrdamesj; Mehrdanesh, Amirhosseina; Khandelwal, Manoj
- Date
- 2022
- Type
- Text; Journal article
- Identifier
- http://researchonline.federation.edu.au/vital/access/HandleResolver/1959.17/186590
- Identifier
- vital:16906
- Identifier
-
https://doi.org/10.1007/s00366-021-01336-4
- Identifier
- ISBN:0177-0667 (ISSN)
- Abstract
- Blast-induced ground vibration is considered as one of the most hazardous phenomena of mine blasting, which can even cause casualties and severe damages to the adjacent properties. Measuring peak particle velocity (PPV) is helpful to know the actual vibration level but prediction of blast vibration prior to the blast is a tedious job due to involvement of blast design, explosive and rock parameters. Nowadays, efficient application of intelligent systems has been approved in different branches of science and technology. In this paper, a gene expression programming (GEP) model was developed to predict PPV using various blasting patterns as model inputs, which showed a high level of accuracy for the implemented model. Also, to optimize blast pattern attaining minimum ground vibration during blasting operation, the developed functional GEP model was taken as objective function for grasshopper optimization algorithm (GOA). Construction of GOA model was performed using a trial and error mechanism to find out the best possible pertinent GOA parameters. Finally, it was observed that utilizing GOA technique, PPV can be reduced by 67% with optimized blast parameters including burden of 3.21 m, spacing of 3.75 m, and charge per delay of 225 kg. A sensitivity analysis was also performed to understand the influence of each input parameters on the blast vibrations. © 2021, The Author(s), under exclusive licence to Springer-Verlag London Ltd. part of Springer Nature.
- Publisher
- Springer Science and Business Media Deutschland GmbH
- Relation
- Engineering with Computers Vol. 38, no. 4 (2022), p. 3341-3350
- Rights
- All metadata describing materials held in, or linked to, the repository is freely available under a CC0 licence
- Rights
- Copyright © 2021, The Author(s)
- Rights
- Open Access
- Subject
- 40 Engineering; 46 Information and computing sciences; Gene expression programming; Grasshopper optimization algorithm; Ground vibration; Meta-heuristic optimization
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