Author ORCID Identifier
Patrick Adeniyi Adesida: 0000-0003-3384-0412
Abioye Victor Aknibinu: 0000-0002-7347-2995
Babatunde Adebayo: 0000-0001-6939-6486
Abstract
This study aimed to evaluate rock fragmentation risk indexes and develop a predictive model for the median size of fragment (X50) using the Rock Engineering System (RES). The methodology includes the analysis of 15 significant parameters of rock properties and blast design, which are considered to be important to rock fragmentation from 30 selected blast sites. These parameters include rock type, hardness, blast-hole diameter, charge weight, blast pattern, and others that control fragmentation results. Statistical analysis was performed to validate the RES-based model developed from these parameters. The model exhibited a strong predictive capacity, evidenced by a high correlation coefficient (R² = 0.922) with a low associated p-value (1.27E-13). In comparison, error analysis methods were used to evaluate the performance of the RES model against other models, including statistical, Kuz-Ram and modified Kuz-Ram. The outcomes showed that the RES model achieved the best accuracy, and the VAF, RMSE, MAPE, and MAE were 93.57%, 1.46 cm, 3.112% and 1.73 cm, respectively. This re-emphasises the model's reliability and effectiveness with regard to predicting the fragmentation result. The RES-based model has a good prospect as a tool for assisting in blast design and optimisation of fragmentation and, consequently, the efficiency of mining and construction.
Recommended Citation
Adesida, Patrick Adeniyi; Akinbinu, Victor Abioye; and Adebayo, Babatunde
(2025)
"A rock engineering system model for predicting fragment size of muck-pile using geometric parameters and rock mass properties,"
Journal of Sustainable Mining: Vol. 24
:
Iss.
4
, Article 9.
Available at: https://doi.org/10.46873/2300-3960.1479
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