Exploitation
Patrick Adeniyi Adesida; Sunday Adex Adaramola
Abstract
This study focuses on predicting the drillability of granitic rocks—precisely the wear rate of button bits, by integrating rock strength and mineralogical properties. The objective is to develop a predictive model for bit wear rate using a Rock Engineering System (RES) approach. Key rock parameters ...
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This study focuses on predicting the drillability of granitic rocks—precisely the wear rate of button bits, by integrating rock strength and mineralogical properties. The objective is to develop a predictive model for bit wear rate using a Rock Engineering System (RES) approach. Key rock parameters (uniaxial compressive strength, porosity, specific gravity, and the mineral content of quartz, plagioclase, hornblende, and biotite) were analysed via a RES interaction matrix to derive a new Drillability Index capturing their combined influence. This analysis revealed that UCS and porosity are the most influential factors in the system. The resulting RES-based model correlates strongly with observed bit wear rates, achieving a high coefficient of determination (R² ≈ 0.93) and low prediction errors (RMSE = 2.79, MAE = 2.14). The MAPE (= 38%) indicates a marked improvement in accuracy over traditional regression methods. Integrating mechanical and mineralogical factors is a novel approach to drillability prediction, providing a more comprehensive account of rock characteristics than conventional models. Validation results show that the RES-derived Drillability Index reliably predicts field performance, offering practical value for optimising drilling operations and guiding geomechanical analysis. Additionally, the study proposes a drillability classification scheme to further support the field application of the findings.
R. Mikaeil; Y. Ozcelik; M. Ataei; S. Shaffiee Haghshenas
Abstract
Evaluation and prediction of performance of diamond wire saw is one of the most important factors involved in planning the dimension stone quarries. The wear rate of diamond wire saw can be investigated as a major criterion to evaluate its performance. The wear rate of diamond wire saw depends upon non-controlled ...
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Evaluation and prediction of performance of diamond wire saw is one of the most important factors involved in planning the dimension stone quarries. The wear rate of diamond wire saw can be investigated as a major criterion to evaluate its performance. The wear rate of diamond wire saw depends upon non-controlled parameters related to rock characteristics and controlled parameters related to characteristics of the cutting machine and operational parameters. Under the same working conditions, the wear rate of diamond wire saw is strongly affected by the rock properties. This is a key factor that required in evaluating the wear rate of diamond wire saw. In this work, the four major dimension stone properties uniaxial compressive strength, Schimazek F-abrasivity factor, Shore hardness, and Young's modulus were selected as the criteria to evaluate the wear rate of diamond wire saw using the harmony search algorithm (HSA). HSA was used to cluster the fifteen different andesite quarries located in Turkey. The studied dimension stones were classified into three classes. The results obtained show that the algorithm applied can be used to classify the performance of diamond wire saw according to its wear rate by only some famous physical and mechanical properties of dimension stone.
