Multivariate statistics application in development of blast fragmentation charts for different rock formations in quarries


Elevli B., Topal I., Elevli S.

Acta Montanistica Slovaca, cilt.17, sa.4, ss.300-309, 2012 (SCI-Expanded) identifier

  • Yayın Türü: Makale / Tam Makale
  • Cilt numarası: 17 Sayı: 4
  • Basım Tarihi: 2012
  • Dergi Adı: Acta Montanistica Slovaca
  • Derginin Tarandığı İndeksler: Science Citation Index Expanded (SCI-EXPANDED), Scopus
  • Sayfa Sayıları: ss.300-309
  • Anahtar Kelimeler: Fragmentation, Image processing, Multiple regression, Rock formations, UCS
  • Ondokuz Mayıs Üniversitesi Adresli: Evet

Özet

Rock fragmentation is considered to be one of the most important aspects of quarrying because of its direct effect on the costs of drilling, which include blasting, loading, hauling and crushing. Thus, it is essential to consider fragmentation size in blasting design. Fragmentation depends on many variables, such as rock properties, geological structures, and blasting parameters. Although empirical models for the estimation of the size distribution of rock fragmentation have been developed by considering these parameters, no complete empirical prediction model for fragmentation exists since rock properties and geological structures vary from site to site. However, these models regard rock properties as constant. In this study, a step-wise multiple linear regression analysis has been carried out to determine the degree of dominance of various influencing parameters on fragmentation and to develop a fragmentation prediction model. The results showed that the rock mass properties, burden width and specific charge are the main parameters affecting fragmentation. The relations among those parameters were used to develop guideline charts to determine blast layouts for desired fragmentation on the basis of rock characteristics.