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چکیده
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The primary objective of open-pit blasting is to achieve optimal rock fragmentation while minimizing undesirable side effects such as flyrock, backbreak, and vibrations. Accurate prediction of these blasting side effects plays a pivotal role in preventing accidents and enhancing overall mine safety and productivity. This paper introduces a simulation model that integrates Classification and Regression Tree (CART) analysis and Principal Component Analysis (PCA) to simulate and predict flyrock occurrences during mine blasting operations. The research focuses on the Sangan iron ore mine as a case study, collecting a dataset of 96 observations from various mine locations during blasting operations. The dataset includes controllable parameters such as burden (B), spacing (S), hole length (L), sub-drilling (U), specific drilling (SD), stemming (T), specific charge (P), and average charge per blast hole (Q). PCA is employed to assess correlations among these input variables. Notably, strong correlations are identified between variables S and B, T and L, and SD and P, leading to the selection of S, L, and P as representative variables. Consequently, S, L, U, P, and Q are chosen as uncorrelated inputs for the CART-based flyrock modeling. Of the 96 datasets, 81 are employed to train the CART model, while the remaining datasets are reserved for testing its performance. The determination coefficients achieved during the training and testing phases are 0.924 and 0.945, respectively, indicating a high level of accuracy in the CART modeling. Additionally, performance indices, including performance index (PI), variance accounted for (VAF), and normalized root mean square error (NRMSE), are calculated, yielding values of 1.423, 92.351 %, and 0.095, respectively. Based on the CART modeling, 21 key guidelines for designing blasting patterns are proposed. Furthermore, sensitivity analysis conducted to highlight the varying importance of input variables in flyrock prediction, wherein variables P and S identified as having the highest and lowest impact, respectively. Finally, the study’s findings are applied to recommend and implement a modified blasting pattern in the Sangan iron mine, resulting in a substantial reduction in both vertical and horizontal flyrock incidents.
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