• Home
  • Browse
    • Current Issue
    • By Issue
    • By Author
    • By Subject
    • Author Index
    • Keyword Index
  • Journal Info
    • About Journal
    • Aims and Scope
    • Editorial Board
    • Editorial Staff
    • Publication Ethics
    • Indexing and Abstracting
    • Related Links
    • FAQ
    • Peer Review Process
    • News
  • Guide for Authors
  • Submit Manuscript
  • Reviewers
  • Contact Us
 
  • Login
  • Register
Home Articles List Article Information
  • Save Records
  • |
  • Printable Version
  • |
  • Recommend
  • |
  • How to cite Export to
    RIS EndNote BibTeX APA MLA Harvard Vancouver
  • |
  • Share Share
    CiteULike Mendeley Facebook Google LinkedIn Twitter Telegram
Journal of Mining and Environment
Articles in Press
Current Issue
Journal Archive
Volume Volume 9 (2018)
Volume Volume 8 (2017)
Issue Issue 4
Issue Issue 3
Issue Issue 2
Issue Issue 1
Volume Volume 7 (2016)
Volume Volume 6 (2015)
Volume Volume 5 (2014)
Volume Volume 4 (2013)
Volume Volume 3 (2012)
Volume Volume 2 (2011)
Volume Volume 1 (2010)
Ataei, M., Sereshki, F. (2017). Improved prediction of blast-induced vibrations in limestone mines using Genetic Algorithm. Journal of Mining and Environment, 8(2), 291-304. doi: 10.22044/jme.2016.654
M. Ataei; F. Sereshki. "Improved prediction of blast-induced vibrations in limestone mines using Genetic Algorithm". Journal of Mining and Environment, 8, 2, 2017, 291-304. doi: 10.22044/jme.2016.654
Ataei, M., Sereshki, F. (2017). 'Improved prediction of blast-induced vibrations in limestone mines using Genetic Algorithm', Journal of Mining and Environment, 8(2), pp. 291-304. doi: 10.22044/jme.2016.654
Ataei, M., Sereshki, F. Improved prediction of blast-induced vibrations in limestone mines using Genetic Algorithm. Journal of Mining and Environment, 2017; 8(2): 291-304. doi: 10.22044/jme.2016.654

Improved prediction of blast-induced vibrations in limestone mines using Genetic Algorithm

Article 14, Volume 8, Issue 2, Spring 2017, Page 291-304  XML PDF (659 K)
Document Type: Original Manuscript
DOI: 10.22044/jme.2016.654
Authors
M. Ataei ; F. Sereshki
School of Mining, Petroleum & Geophysics Engineering, Shahrood University of Technology, Shahrood, Iran
Abstract
Like most limestone mines, which produce the raw materials required for cement companies, the transportation cost of the raw materials used in the Shahrood Cement Company is high. It has been tried to build the crushing and grinding plant close to the mine as much as possible. On the other hand, blasting has harmful effects, and the impacts of blast-induced damages on the sensitive machinery, equipment, and buildings are considerable. In such mines, among the blasting effects, blast-induced vibrations have a great deal of importance. This research work was conducted to analyze the blasting effects, and to propose a valid and reliable formula to predict the blast-induced vibration impacts in such regions, especially for the Shahrood Cement Company. Up to the present time, different indices have been introduced to quantify the blast vibration effects, among which peak particle velocity (PPV) has been widely considered by a majority of researchers. In order to establish a relationship between PPV and the blast site properties, different formulas have been proposed till now, and their frequently-used versions have been employed in the general form of , where W and D are the maximum charge per delay and the distance from the blast site, respectively, and , , and describe the site specifications. In this work, a series of tests and field measurements were carried out, and the required parameters were collected. Then in order to generalize the relationship between different limestone mines, and also to increase the prediction precision, the related data for similar limestone mines was gathered from the literature. In order to find the best equation fitting the real data, a simple regression model with genetic algorithm was used, and the best PPV predictor was achieved. At last, the results obtained for the best predictor model were compared with the real measured data by means of a correlation analysis.
Keywords
Blasting; Blast-Induced Vibration; PPV; Limestone Mine; Cement Company; Genetic Algorithm
Statistics
Article View: 3,020
PDF Download: 1,769
Home | Glossary | News | Aims and Scope | Sitemap
Top Top


free web tracker

 Creative Commons License

JME is licensed under a Creative Commons Attribution 4.0 International License.

Journal Management System. Designed by sinaweb.