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Mohammad Rezaei

Mohammad Rezaei

Academic rank: Associate Professor
ORCID: 0000-0002-0619-2846
Education: PhD.
ScopusId: 16639269700
HIndex:
Faculty: Faculty of Engineering
Address: University of Kurdistan - Faculty of Engineering - Department of Mining Engineering
Phone: 087-33660073

Research

Title
Assessment of Effect of Rock Properties on Horizontal Drilling Rate in Marble Quarry Mining: Field and Experimental Studies
Type
JournalPaper
Keywords
Marble quarry mine, Horizontal drilling rate, Physical properties, Mechanical properties, Statistical modeling
Year
2023
Journal Journal of Mining and Environment
DOI
Researchers Mohammad Rezaei ، Navid Nyazian

Abstract

Rock drilling is one of the most important processes in the mining operations, which involves high costs. Deep knowledge of the drilling conditions and rock mass properties can help the optimum selection of drilling system, precise determination of type and number of drilling equipment, and accurate prediction of drilling rate. The above process leads to enhance the drilling efficiency and mining productivity. In this work, relationships between the rock the physico-mechanical properties and horizontal drilling rate (HDR) are investigated. For this purpose, HDR is firstly measured during the drilling process at the Malawi marble quarry mine, Islamabad-e-Gharb, Iran. Then core samples are prepared from the representative minor rock blocks to conduct the laboratory tests and evaluate the influence of rock properties on HDR. The experimental results prove that natural density (ρn), dry density (ρd), slake durability index (Id), Schmidt hammer rebound (SHR), compression wave velocity (Vp), point load index (PLI), uniaxial compressive strength (UCS), and modulus of elasticity (E) have inverse relationships with HDR. Conversely, HDR has a direct relationship with porosity (n), water content (Wa), Los Angeles abrasion (LAA), and Poisson ratio (ν). Generally, it is proved that HDR is more associated with the rock's physical properties than the mechanical characteristics. Moreover, sensitivity analysis confirm that n and ρd are the most and least effective variables on HDR. Furthermore, new optimum empirical equations with acceptable accuracy are proposed to predict HDR based on the statistical modeling. Finally, experimental verification analysis confirm the superiority of this study compared to the prior similar studies.