ABSTRACT: The transition from open-pit to underground mining is a practical strategy to meet the growing demand for minerals while extending mine life and optimizing resource utilization. However, this transition introduces a series of challenges, particularly in managing blast-induced ground vibrations, which are an integral part of drilling operations. The stress waves associated with these vibrations, known as Peak Particle Velocity (PPV), can significantly impact both operational safety and environmental sustainability. This paper provides a comprehensive review of various predictive methods for PPV, evaluating their strengths and weaknesses within the context of the transition from open-pit to underground mining. It highlights gaps in existing models and proposes potential research directions to enhance vibration management in both mining environments. The review aims to offer valuable insights to support the development of a hybrid predictive modeling approach that integrates empirical models, machine learning algorithms, and numerical simulations. Such an approach facilitates data-driven transition strategies, reducing vibration impacts on both surface and underground operations while contributing to the broader goal of safer and more sustainable mining practices.
Moradi et al. (Sun,) studied this question.
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