Department of Mining and Minerals Engineering
Permanent URI for this community
Browse
Browsing Department of Mining and Minerals Engineering by Department "Mining & Minerals Engineering"
Now showing 1 - 3 of 3
Results Per Page
Sort Options
- Characterization of Particulates from Australian Underground Coal MinesLaBranche, Nikky; Keles, Cigdem; Sarver, Emily A.; Johnstone, Kelly; Cliff, David (MDPI, 2021-04-23)The re-identification of coal workers’ pneumoconiosis in Queensland in 2015 has prompted improvements in exposure monitoring and health surveillance in Australia. The potential consequences of excessive exposure to respirable dust may depend upon the size, shape and mineralogical classes of the dust. Technology has now advanced to the point that the dust characteristics can be explored in detail. This research collected respirable dust samples from four operating underground coal mines in Australia for characterization analysis using scanning electron microscopy (SEM) with energy dispersive X-ray (EDX). The research found multiple mineralogical classes present with their own particle size distributions. The variation between mines appears to have had a larger effect on particle size distribution than the differences in mining processes within individual mines. This may be due to variations in the geologic conditions, seam variation or mining conditions.
- Demonstration of Optical Microscopy and Image Processing to Classify Respirable Coal Mine Dust ParticlesSanta, Nestor; Keles, Cigdem; Saylor, J. R.; Sarver, Emily A. (MDPI, 2021-08-02)Respirable coal mine dust represents a serious health hazard for miners. Monitoring methods are needed that enable fractionation of dust into its primary components, and that do so in real time. Near the production face, a simple capability to monitor the coal versus mineral dust fractions would be highly valuable for tracking changes in dust sources—and supporting timely responses in terms of dust controls or other interventions to reduce exposures. In this work, the premise of dust monitoring with polarized light microscopy was explored. Using images of coal and representative mineral particles (kaolinite, crystalline silica, and limestone rock dust), a model was built to exploit birefringence of the mineral particles and effectively separate them from the coal. The model showed >95% accuracy on a test dataset with known particles. For composite samples containing both coal and minerals, the model also showed a very good agreement with results from the scanning electron microscopy classification, which was used as a reference method. Results could further the concept of a “cell phone microscope” type monitor for semi-continuous measurements in coal mines.
- Pore-Scale Simulation of Confined Phase Behavior with Pore Size Distribution and Its Effects on Shale Oil ProductionHuang, Jingwei; Wang, Hongsheng (MDPI, 2021-02-28)Confined phase behavior plays a critical role in predicting production from shale reservoirs. In this work, a pseudo-potential lattice Boltzmann method is applied to directly model the phase equilibrium of fluids in nanopores. First, vapor-liquid equilibrium is simulated by capturing the sudden jump on simulated adsorption isotherms in a capillary tube. In addition, effect of pore size distribution on phase equilibrium is evaluated by using a bundle of capillary tubes of various sizes. Simulated coexistence curves indicate that an effective pore size can be used to account for the effects of pore size distribution on confined phase behavior. With simulated coexistence curves from pore-scale simulation, a modified equation of state is built and applied to model the thermodynamic phase diagram of shale oil. Shifted critical properties and suppressed bubble points are observed when effects of confinement is considered. The compositional simulation shows that both predicted oil and gas production will be higher if the modified equation of state is implemented. Results are compared with those using methods of capillary pressure and critical shift.