Quantification of geological uncertainty and risk using stochastic simulation and applications in the coal mining industry

Stochastic simulation is a recognised tool for quantifying the spatial distribution of geological uncertainty and risk in earth science and engineering. Metals mining is an area where simulation technologies are extensively used; however, applications in the coal mining industry have been limited. This is particularly due to the lack of a systematic demonstration illustrating the capabilities these techniques have in problem solving in coal mining. This paper presents two broad and technically distinct areas of applications in coal mining. The first deals with the use of simulation in the quantification of uncertainty in coal seam attributes and risk assessment to assist coal resource classification, and drillhole spacing optimisation to meet pre-specified risk levels at a required confidence. The second application presents the use of stochastic simulation in the quantification of fault risk, an area of particular interest to underground coal mining, and documents the performance of the approach. The examples presented demonstrate the advantages and positive contribution stochastic simulation approaches bring to the coal mining industry

Methacryloxyethyl phosphate-grafted expanded polytetrafluoroethylene membranes for biomedical applications

Expanded polytetrafluoroethylene (ePTFE) membranes were modified by graft copolymerization with methacryloxyethyl phosphate (MOEP) in methanol and 2-butanone (methyl ethyl ketone (MEK)) at ambient temperature using gamma irradiation. The effect of dose rate (0.46 and 4.6 kGyh(-1)), monomer concentration (1-40 %) and solvent were studied and the modified membranes were characterized by weight increase, X-ray photoelectron spectroscopy (XPS), Fourier transform infrared spectroscopy (FTIR) and scanning electron microscopy (SEM). XPS was used to determine the % degree of surface coverage using the C-F (ePTFE membrane) and the C-C (MOEP graft copolymer) peaks. Grafting yield, as well as surface coverage, were found to increase with increasing monomer concentration and were significantly higher for samples grafted in MEK than in methanol solution. SEM images showed distinctly different surface morphologies for the membranes grafted in methanol (smooth) and MEK (globular), hence indicating phase separation of the homopolymer in MEK. We propose that in our system, the non-solvent properties of MEK for the homopolymer play a more important role than solvent chain transfer reactions in determining grafting outcomes. (c) 2005 Society of Chemical Industry.

Magnetic susceptibility measurement applied to the minerals industry

The efficiency of numerous mineral processing operations can be determined by measuring the magnetic properties of the process streams. This measurement, if done at all, is currently performed by laboratory testing of spot samples. This is an inherently slow process and, where feed grades are variable, optimum performance is generally not achieved. This paper describes the rapid measurement of the magnetic properties of minerals. AC measurement techniques, including the analysis of the phase component of the magnetic vector; frequency dependent magnetic susceptibility and the effect of applied magnetic field strength will be discussed. Industrial applications in mineral sands, copper smelting, ferrosilicon testing and drill core scanning will be reported. (C) 2006 Elsevier Ltd. All rights reserved.

Tyre-force estimation by Kalman inverse filtering: applications to off-highway mining trucks

Kalman inverse filtering is used to develop a methodology for real-time estimation of forces acting at the interface between tyre and road on large off-highway mining trucks. The system model formulated is capable of estimating the three components of tyre-force at each wheel of the truck using a practical set of measurements and inputs. Good tracking is obtained by the estimated tyre-forces when compared with those simulated by an ADAMS virtual-truck model. A sensitivity analysis determines the susceptibility of the tyre-force estimates to uncertainties in the truck's parameters.