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The precision of determining rock mass mechanical parameters is notably impacted by mining blast activities. An advanced method for inverse analysis of these parameters, predicated upon measured blasting vibrations, has been developed. This approach employs a meticulous recognition of initial P-wave and S-wave arrivals within the vibrational energy spectrum. Utilizing principles from elastic wave theory, a novel framework has been established, correlating P-wave and S-wave velocities with dynamic characteristics of rock masses. The efficacy of this method has been substantiated through practical implementation, particularly in the Guanbaoshan Open-pit Iron Mine, Liaoning Province. Here, the derived density ratios were observed to range between 0.98 and 1.01, aligning closely with figures provided by authoritative research institutes. Additionally, the dynamic-tostatic Poisson's ratio exhibited variations from 0.85 to 1.03, while the modulus of elasticity ratio dynamically to statically spanned from 2.0 to 2.6. These results, falling within anticipated theoretical ranges, underscore the robust applicability and accuracy of this method. The research contributes significantly to the domain of mining operations, particularly in optimizing blasting processes and enhancing the precision of mechanical parameter acquisition. It presents a pioneering approach, essential for addressing similar challenges in the mining sector.
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Yan et al. (2023) studied this question.
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