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Journal of the Southern African Institute of Mining and Metallurgy

versão On-line ISSN 2411-9717
versão impressa ISSN 2225-6253

J. S. Afr. Inst. Min. Metall. vol.111 no.5 Johannesburg Mai. 2011

 

JOURNAL PAPER

 

A model to predict the performance of roadheaders based on the Rock Mass Brittleness Index

 

 

A. EbrahimabadiI; K. GoshtasbiII; K. ShahriarIII; M. Cheraghi SeifabadIV

IDepartment of Mining, Islamic Azad University,Science and Research Branch, Tehran, Iran
IIDepartment of Mining, Faculty of Engineering, Tarbiat Modares University, Tehran, Iran
IIIDepartment of Mining, Metallurgical and Petroleum Engineering, Amirkabir University of Technology, Tehran, Iran
IVDepartment of Mining, Isfahan University of Technology, Isfahan, Iran

 

 


SYNOPSIS

Roadheaders are very versatile excavation machines used in tunnelling, mine development, and mine production for soft to medium strength rock formations. Performance prediction is an important factor for successful roadheader application and generally deals with machine selection, production rate and bit consumption. Among many different parameters, brittleness is also one of the material properties related to breakage characteristics and can be used as a cuttability parameter from a mechanical excavation point of view. The main objective of the research study is to contribute the brittleness of rock excavated to construct a new empirical equation for predicting the performance of roadheaders in different material and operational conditions. In this regard, a new performance prediction model for medium duty roadheaders based on a brittleness index (BI) is presented. In this study, rock mass brittleness index (RMBI) is defined in order to investigate the influence of BI on roadheader performance. RMBI is an index which can be used to relate the intact and rock mass characteristics to machine performance. Results demonstrated that RMBI is highly correlated to instantaneous cutting rate (ICR) (R2=0.94). Moreover, through the further analysis and normalization, the pick consumption index (PCI) was introduced as a parameter having a good relation with pick or bit consumption rates (PCR) (R2=0.79). Finally, the new predictive models for ICR and PCR showed very good correlations with the actual measured values.

Keywords: Performance prediction, roadheader, brittleness index, mechanical excavation


 

 

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