A new empirical model for prediction of jumbo drills' penetration rate in underground mines based on the rock mass characteristics

Jumbo drills are widely used in underground mining for tunnel drivages. The drilling rate is significantly influenced by intact rock characteristics and the structural parameters of the rock mass. A non-linear multiple regression model (NLMR) was employed to assess the rate of penetration of jumbo drills. For this purpose, field data, including 737 boreholes, were utilized. This paper developed an empirical model that incorporated the Rock Mass Drillability Index (RDi) to predict the rate of penetration (ROP) of jumbo drills in underground mines. Performance indexes such as R2, RMSE, MAE, MAPE, and VAF were evaluated to gauge the prediction accuracy of the model. The developed model exhibited values of 0.88, 0.22, 0.17, 7.3, and 88.84 for R2, RMSE, MAE, MAPE, and VAF, respectively, when applied to the training data. By considering both intact rock mechanical properties and structural properties of rock masses, the model demonstrated accurate predictions of jumbo drill penetration rates.

Keywords: Penetration rate, Jumbo drill, Rock mass drillability index (RDi), NMLR.
For citation:

Sasan Heydari, Seyed Hadi Hoseinie, Raheb Bagherpour A new empirical model for prediction of jumbo drills' penetration rate in underground mines based on the rock mass characteristics. MIAB. Mining Inf. Anal. Bull. 2024;(5):17-35. DOI: 10.25018/0236_1493_2024_ 5_0_17.

Acknowledgements:
Issue number: 5
Year: 2024
Page number: 17-35
ISBN: 0236-1493
UDK: 622.24
DOI: 10.25018/0236_1493_2024_5_0_17
Article receipt date: 03.12.2023
Date of review receipt: 29.01.2024
Date of the editorial board′s decision on the article′s publishing: 10.04.2024
About authors:

S. Heydari1, PhD Candidate, e-mail: sasanheydari@mi.iut.ac.ir, ORCID ID: 0000-0001-9140-3486,
S.H. Hoseeinie1, Associate Professor, e-mail: hadi.hoseinie@iut.ac.ir, ORCID ID: 0000-0002-9767-3644,
R. Bagherpour1, Professor, e-mail: bagherpour@iut.ac.ir, ORCID ID: 0000-0002-7235-9966,
1 Department of Mining Engineering, Isfahan University of Technology, Isfahan, Iran.

 

For contacts:

S.H. Hoseeinie, e-mail: hadi.hoseinie@iut.ac.ir.

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