Browsing by Author "Monsalve, Juan J."

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    Integrating Laser Scanning with Discrete Element Modeling for Improving Safety in Underground Stone Mines
    Monsalve, Juan J. (Virginia Tech, 2019-05-10)
    According to the Mine Health and Safety Administration (MSHA), between 2006 and 2016, the underground stone mining industry had the highest fatality rate in 4 out of 10 years, compared to any other type of mining in the United States. Additionally, the National Institute for Occupational Safety and Health (NIOSH) stated that structurally controlled instability is a predominant failure mechanism in underground limestone mines. This type of instability occurs when the different discontinuity sets intercept with each other forming rock blocks that displace inwards the tunnel as the excavation takes place, posing a great hazard for miners and overall mine planning. In recent years, Terrestrial laser scanning (TLS) has been used for mapping and characterizing fractures present in a rock mass. TLS is a technology that allows to generate a three-dimensional multimillion point cloud of a scanned area. In addition to this, the advances in computing power throughout the past years, have allowed numerical modeling codes to represent more realistically the behavior of a fractured rock masses. This work presents and implements a methodology that integrates laser scanning technology along with Discrete Element Modeling as tools for characterizing, preventing, and managing structurally controlled instability that may affect large-opening underground mines. The stability of an underground limestone mine that extracts a dipping ore body with a room and pillar (and eventual stoping) mining method is analyzed with this approach. While this methodology is proposed based on a specific case study that does not meet the requirements to be designed with current NIOSH published guidelines, this process proposes a general methodology that can be applied in any mine experiencing similar failure mechanisms, considering site-specific conditions. The aim of this study is to ensure the safety of mine workers and to reduce accidents that arise from ground control issues. The results obtained from this methodology allowed us to generate Probability Density Functions to estimate the probability of rock fall in the excavations. These models were also validated by comparing the numerical model results with those obtained from the laser scans.
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    Stochastic Continuous Modeling for Pillar Stress Estimation and Comparison with 2D Numerical, and Analytical Solutions in an Underground Stone Mine
    Monsalve, Juan J.; Soni, Aman; Karfakis, Mario; Hazzard, Jim; Ripepi, Nino (Springer, 2022-09)
    Pillar collapses are events that due to their severe consequences can be classified as high risk. The design of pillars in underground room-and-pillar operations should migrate to risk-based design approaches. The authors of this work proposed a risk-based pillar design methodology that integrates stochastic discrete element modeling for pillar strength estimation, and stochastic finite volume modeling (FVM) for stress estimation. This paper focuses on the stochastic FVM component for stress estimation. The mining and geomechanical aspects of a case study mine (CSM) are described and pillar stresses are estimated by using three approaches: (1) analytical solutions, (2) 2D finite element modeling, and (3) 3D finite volume modeling. This operation extracts a 30 degrees dipping deposit, which makes current underground stone mine design guidelines inapplicable for this CSM. This work compares results from each stress estimation approach and discusses uses the point estimate method as a simplified stochastic approach to evaluate the effect of rock mass elastic properties variability on pillar stress distribution. Results from this work show that the three estimation approaches lead to different estimations, possibly, due to the wide range of assumptions each estimation approach considers. It was also determined that the horizontal to vertical stress ratio has a significant impact on pillar stress magnitude. Therefore, it is recommended to perform in situ stress measurements, or assume worst-case-scenario values to account and reduce uncertainty due to this parameter. The stochastic stress estimation approach used in this paper provides results that can integrate a risk-based pillar design framework.