Determination of the size of rock fragments using RVM, GPR, and MPMR

Abstract

For predicting the size of rock fragments during drilling and blasting operations, this article uses GPR, RVM, and MPMR. The current analysis makes use of a blast data set generated in a prior investigation. In this study, a portion of the blast data was utilized to train a model to determine the mean particle size arising from blast fragmentation for each of the similarity groups generated. The particle size was modeled as a function of seven different variables. The dataset contains information about the bench height and drilled burden ratio ($H/B$), spacing to burden ratio ($S/B$), burden to hole diameter ratio ($B/D$), stemming to burden ratio ($T/B$), powder factor ($P_f$), modulus of elasticity ($E$), and in-situ block size ($X_B$) are the input and output is $X_{50}$. By comparing forecasts with actual mean particle size values and predictions based on one of the most widely used fragmentation estimation techniques in the blasted literature, the capacity of the generated models may be established. The statistical parameters, actual vs predicted curve, Taylor diagram, error bar, and developed discrepancy ratio are used to analysis the performance of models. A comparative study has been carried out between the developed RVM, GPR, and MPMR. The results show the developed models have the capability for prediction of $X_{50}$. From these comparisons, the MPMR has the highest value with a high degree of precision and robustness in the size of rock fragments $X_{50}$.

Keywords
Blasting; GPR; MPMR; RVM; Rock fragmentation