A Theoretical Model for Predicting the Blasting Energy Factor in Underground Mining Tunnels

Optimizing the blast energy distribution is crucial for enhancing rock fragmentation, minimizing overexcavation, and boosting profitability in mining operations. This study introduces a theoretical model to predict the blasting Energy Factor (Fe) in mining tunnels, based on the Cracking Energy (Eg) of the rock mass, derived from the deformation energy of brittle materials (Young’s modulus) and adjusted by the Rock Mass Rating (RMR). The model was validated using 42 blasting datasets from horizontal galleries at El Teniente mine, Chile. Data included geometric parameters (tunnel sections, drilling length, diameter, number of holes, meters drilled), explosive type and consumption, and geomechanical properties, particularly the RMR. Results show that as rock mass quality improves (higher RMR), both Fe and %Eg increase, more competent rock masses require higher input energy to initiate and propagate cracks, and a greater portion of that energy is effectively utilized for crack formation. For instance, rock masses with an RMR of 66 exhibited an average Fe of 7.62 MJ/m3 and %Eg of 4.8%, while those with an RMR of 75 showed higher values (Fe = 8.47 MJ/m3, %Eg = 6.4%). This confirms that less fractured rock masses require higher Fe and %Eg for effective fragmentation. Lithology also plays a significant role in energy consumption. Diorite displayed the highest Fe (8.34 MJ/m3) and higher efficiency (%Eg = 7.0%), whereas andesite showed lower Fe (7.61 MJ/m3) and lower crack propagation efficiency (%Eg = 3.7%). Unlike traditional Fe prediction methods, which rely solely on explosive data and excavation volume, this model integrates RMR, enabling more precise energy allocation and fostering sustainable mining practices. This approach enhances decision-making in blast design, offering a more robust framework for optimizing energy use in mining operations.