Year of Publication

2020

Degree Name

Master of Science in Mining Engineering (MSMIE)

Document Type

Master's Thesis

College

Engineering

Department/School/Program

Mining Engineering

First Advisor

Dr. Zach Agioutantis

Abstract

Pillar stability has been a matter of study for the last 70 years. The determination of pillar strength had taken different solutions and approaches over that time. This research has led to numerous empirical formulations that have reduced the number of pillar failures worldwide. However, new numerical approaches are being studied. In the last 20 years, the Ground Reaction Curve concept has been examined as a way of understanding the convergence of the rock-mass. Although the Ground Reaction Curve was first introduced in the civil tunneling industry, several authors have introduced the Ground Reaction Curve concept as an approach for an integrated pillar design methodology.

Furthermore, the intersection of the Ground Reaction Curve and Support Reaction Curves can be used to determine the appropriate support systems for underground excavations. The man-made support structures (i.e., pumpable cribs, concrete cribs, and wood cribs) in a mine will have a unique Support Reaction Curve. Literature suggests that the pillar structures in underground mines can also be regarded as support structures and their reaction to tributary and or abutment stress can be viewed with respect to the ground reaction curve at the pillar location. In this study, an underground limestone mine was instrumented with borehole pressure cells and roof extensometers. This thesis presents a series of two-dimensional and three-dimensional finite element numerical models that were used to estimate the Ground Reaction Curve and the Support Reaction Curve for a pillar. The numerical models consider the stages of development and benching around the pillar. Numerical results are compared with field measurements of the study case located in northern Kentucky.

Digital Object Identifier (DOI)

https://doi.org/10.13023/etd.2020.449

Funding Information

This research was supported by the Alpha Foundation (Grant No. AFC 719) 2019-2020.

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