Monte Carlo Methodology Applied to Rockfall Prevention in Underground Mines in Central Peru (#1637)

Authors

Portillo – Salvador, Jail

Gavilano–Alvarado, Tania

Pehovaz-Alvarez, Humberto

Abstract

Rockfall is a common problem in the mining industry that affects the safety and health of workers during the execution of their activities. This research proposal seeks to identify the most relevant factors that can influence rockfall accidents in an underground mine. A new random simulation methodology is proposed, based on a probabilistic model that helps us predict different scenarios and offers a more comprehensive view than traditional deterministic approaches. This method is used to evaluate the impact of risk and uncertainty in many real-life scenarios. In this case, an analysis of rockfall accidents in underground mining over the last 5 years in Peru was carried out. From this analysis, the most common factors influencing rockfall and the incidence of accidents associated with each one were identified. With the collected data, 100 simulations were performed using the Monte Carlo method, which allowed us to obtain the different probability percentages of occurrence for the factors considered in this research. It was found that geological factors had an occurrence probability of 34%, the highest among all the factors analyzed.