Scielo RSS <![CDATA[Journal of the Southern African Institute of Mining and Metallurgy]]> vol. 113 num. 11 lang. pt <![CDATA[SciELO Logo]]> <![CDATA[<b>Where are all the coal researchers?</b>]]> <![CDATA[<b>Coal - balance between supplies to Eskom and exports</b>]]> <![CDATA[<b>SANCOT and the International Tunnelling Association (ITA)</b>]]> <![CDATA[<b>The looming skills crunch in mining and the need to join hands</b>]]> <![CDATA[<b>Moisture adsorption and desorption characteristics of some South African coals</b>]]> The high final total moisture content of fine coal after mining and processing is one of the major reasons that this resource is not extensively used in subsequent power generation, combustion, or other conversion processes. Some coal products, like export coal, may be subjected to a variety of environmental conditions during transport and storage, such as temperature and humidity. To understand the mechanisms by which moisture is attracted and held on and within fine coal particles, further information is needed regarding the processes occurring at the coal surface. In order to determine the correlation between physical coal properties and its moisture adsorption and desorption characteristics, a series of sorption experiments were conducted on various coal samples under climatically controlled conditions. Equilibrium moisture data was collected while changing the temperature and humidity. This data was correlated to coal properties such as particle size, porosity, maceral composition, and mineral content. All the coals that were studied were medium-rank bituminous coals. It was found that the best predictors for moisture adsorption and desorption were the mineral and inertinite contents. <![CDATA[<b>The effect of substituting fractions of imported coking coals with coke oven tar on coal blend, carbonization, and coke properties</b>]]> In this study, coke oven tar additions over a range of 0-8 wt.% were evaluated as a possible substitute for imported coal fractions. The coke oven tar used was collected from tar decanters in the byproducts section of the coking plant. The moisture content in the tar varied depending on the residence time and water carryover from the coke oven tar separators to the storage tanks. Moisture contents of 1 wt.%, 3 wt.%, and 6 wt.% were investigated in order to evaluate the effect on coal blend, carbonization, and coke properties. At 6 wt.% moisture content with 6 wt.% coke oven tar, although the coke quality improved the yield showed a 4% decrease. On the other hand, 1 wt.% moisture content with coke oven tar of 6 wt.%, increased the yield by 1% and the coke quality improved. However, the latter process was characterized by an excessive increase in wall pressure and pushing energy, both of which are detrimental to the oven walls. The optimum moisture content in coke oven tar was found to be 3 wt.% with a coke oven tar addition of 6 wt.% in the coal blend. With these conditions, the coke properties improved and wall pressure and pushing energy were acceptable. However, a decrease in coke yield of up to 2% was observed. Despite this, coke oven tar addition is considered to be a viable option based upon economic factors of a reduction in the quantity and cost of imported coking coals that is required to achieve the same optimum final coke product. <![CDATA[<b>Techno-economic impact of optimized low-grade thermal coal export production through beneficiation modelling</b>]]> The advent of low-quality export coal demand has brought a new range of possibilities to the South African coal industry. Products that traditionally were only of value to the domestic or combustion industry sectors now have the potential to be exported, with only minor amounts of upgrading required through beneficiation. Comparatively high steam-coal export prices can be obtained for low-quality export coal, which enhances the economic feasibility of expanding low-quality thermal coal exports. There are, however, increasing concerns about the feasibility of lower quality thermal coal exports and the broader implications. These concerns relate to the environmental impact of low-quality thermal coal production for export and the inherent threat to the security of domestic thermal coal supply in South Africa. Against this background, this paper serves to explain the extended value chain in the production of export coal. The technical and economic advantages and disadvantages of low-grade exports versus coal production for domestic use are evaluated. The value chain estimation is calculated by the beneficiation modelling and characterization of two coals. Based on the value estimation, the low-grade export production scenario, and finally the modelling of potential pollutant distribution, are described. <![CDATA[<b>Update of coal pillar database for South African coal mining</b>]]> Following the Coalbrook disaster in 1960, research into coal pillar strength resulted in the adoption of the concept of a safety factor for the design of stable pillars in South African coal mining. At the time when the original statistical analysis was performed by Salamon and Munro in the early 1960s, 27 cases of failed pillar workings were considered suitable for inclusion in the database of failed pillars. Pillar failure did not stop after the introduction of the safety factor formula by Salamon and Munro (1967). In the ensuing years, pillars that were created before the application of the formula deteriorated and later failed, as did ones that were created after the introduction of the formula. This means that over time, the database of failed pillar cases increased in size, allowing ever more reliable analyses to be performed. The number of failed cases in the database had grown from the original 27 in the 1960s to 86 by 2011. All the failed cases are contained in the updated database. The database of stable pillars, which is also used in the derivation of strength formulae, has now been extended from 125 to 337 cases. The new database of intact pillar cases is more complete as it bridges the time gap between the Salamon and Munro (1967) and the Van der Merwe (2006) databases. The original requirements for inclusion into the database were satisfied in the compilation of this latest collection. The characteristics of the original database of intact pillars did not change in a meaningful way. The mining depth and pillar dimensions of the new database are largely as they were in the original database. Time-related trends with regard to pillar dimensions and depth of mining could not be found, indicating that the geometrical parameters of coal mining in South Africa have not changed meaningfully in approximately a century of mining. The characteristics of cases in the updated database of failed pillars does not differ substantially from the one published by Van der Merwe (2006). The same difference between that database and the original Salamon and Munro database, namely that the average safety factor of the failed cases had increased dramatically, from 1.0 to 1.5, is still apparent. This may be due to the inclusion of more failures from specific areas that exhibit a disproportionate number of failures at higher safety factors. These areas are the Vaal Basin, Klip River, and Free State coalfields. The new database confirms yet again that there is no correlation between the safety factors of failed pillars and their time of failure. The safety factor on its own is thus not a reliable predictor of longterm stability of pillars. <![CDATA[<b>Update of coal pillar strength formulae for South African coal using two methods of analysis</b>]]> The pioneers in the field of coal pillar strength in South Africa were M.D.G. Salamon and A.H. Munro, who preferred to use statistical back-analysis of failed and intact pillars to determine the pillar strength, and Z.T. Bieniawski, whose attempt was based on the direct strength determination of coal pillars using specimens of various sizes. At the time when the original statistical analysis was performed, 27 cases of failed pillar workings were considered suitable for inclusion in the database of failed pillars. The databases of failed and stable pillar cases have recently been updated to include cases of pillar failure that occurred in the past few years (Van der Merwe and Mathey, 2013a). The work described in this paper relates to a review of pillar strength formulae using the latest available data and using two different approaches to the analysis. A clear distinction was found between pillar failure in the so-called 'weak coal' areas, comprising the Klip River, Vaal Basin, and Free State coalfields, and the rest of the areas in South Africa. It was not possible to derive satisfactory strength formulae for the 'weak coal' areas using either the maximum likelihood or the overlap reduction technique of analysis. The pillars in these areas tended to fail at much higher safety factors, calculated by using the strength formulae developed for the 'normal coal' areas. It is postulated that the mode of failure may be different in these areas. This distinction reinforces the notion that coals in different areas have different characteristics and that there is scope to develop site-specific strength formulae. However, the scarcity of data for the different areas prohibits the development of reliable formulae at this stage, and therefore the broad distinction of 'weak' and 'normal' coals has to suffice for the present. The updated databases resulted in only slightly different strength formulae for the different approaches to the analysis than were obtained previously. Both the maximum likelihood and the overlap reduction technique resulted in usable formulae. The maximum likelihood technique resulted in a closer grouping around the average safety factor of unity for the failed cases, while the overlap reduction technique resulted in better distinction between cases of failed and stable pillars. For the same pillar geometries, the overlap reduction formula predicted lower strength than the maximum likelihood formula for pillars with width-to-height ratios less than 1.88, and higher strength for pillars with higher width-to-height ratios. Further work is required to review the squat pillar formula in the light of these new formulae, as the transition between the formulae presented here and the squat pillar formula is no longer continuous. In similar vein, the previous work to predict the stable life-span of coal pillars should also be reviewed using the latest available data. <![CDATA[<b>Probability of failure of South African coal pillars</b>]]> Following the Coalbrook disaster in 1960, research into coal pillar strength resulted in the adoption of the concept of a safety factor in the design of stable pillars in South African coal mining. The safety factor on its own can be regarded as only a relative measure of stability. It stands to reason that a pillar with a higher safety factor will be 'more stable' than a pillar with lower safety factor, but how much more stable cannot be quantified. Links between the safety factor and the probability of failure (PoF) were established for two new coal pillar strength formulae. The method behind the determination of the probability of failure was a comparison of the observed number of failures to a predicted number of stable cases for each safety factor in the entire population of pillars in South Africa. The prediction of the latter was made by fitting characteristic distribution curves (lognormal, Weibull, and gamma density distributions) to the samples of stable cases in the database and extrapolating the responding frequency distributions by a constant factor. The resulting PoF per safety factor is significantly less than previously assumed. A more accurate approach to the solution for the link between safety factor and the probability of failure would be to determine regional or seam-specific probabilities of failure. However, this would require more statistical evidence for the separate regions or seams to improve the meaningfulness and reliability of the predictions. The amount of data available at present is not considered sufficient for this purpose. It is shown that the pillar strength formula derived by means of the maximum likelihood function results in larger pillars than with the formula derived by means of the overlap reduction technique for the same safety factor, but that the PoF of the larger pillars is less than that for the smaller pillars obtained with the alternative formula. Compared on the basis of the same pillar sizes, the PoF derived for the two different formulae are in close agreement. This conclusion confirms that basing design on PoF as opposed to a safety factor is much more satisfactory, and it also removes the ambiguity arising out of using different strength formulae. It is concluded that a PoF of 1% for general bord and pillar workings could be obtained with a safety factor of 1.3 by using the maximum likelihood formula, and 1.4 by using the minimum overlap formula. Significant benefits in extraction can be expected from the use of either of the new formulae, basing the design on a PoF of 1% for general underground workings. <![CDATA[<b>The three-product cyclone</b>: <b>adding value to South African coal processing</b>]]> The three-product cyclone was originally developed in Russia and is now extensively used in China. The cyclone has recently entered the South African coal industry, and with the obvious advantages that this item of process equipment offers our ever-evolving industry it is safe to assume that it will add value to dense medium circuits in South Africa. Some of the possible applications include: > Producing multiple products using a single dense medium circuit. These can typically be a primary product with calorific value of 27.50 MJ/kg and a secondary (middling) product with a calorific value of 22 MJ/kg > High-density separation with a low circulating medium density. Anglo Thermal Coal and Exxaro have pioneered the use of these units at Umlalazi and New Clydesdale respectively. Extensive test work has been performed at Umlalazi to determine the efficiency of the unit and to determine how it compares with the conventional DSM (Dutch School of Mines) cyclone. Some people in the coal industry were initially sceptical and expected the performance of the three-product cyclone to be inferior to that of the conventional dense medium cyclone. The results of the test work have, however, shown that the efficiency of the unit is comparable to that of the cyclones currently employed. A valid concern expressed is the control over the cut-point density of the second stage separation, and work is on-going to find the optimal way to control the secondary separation density. Theoretically, the secondary separation density can be manipulated by changing the orifices of the unit, especially the spigot of the secondary stage. This remains to be proven, and a series of tests is currently being planned. Whatever the result of these tests may be, the three-product cyclone definitely has a place in the South African coal processing industry as it offers a low OPEX and CAPEX solution for producing multiple products from a single circuit, as well as the ability to operate at very high separation densities, while making use of low-density circulating medium. <![CDATA[<b>Petrological characterization of coal</b>: <b>an evolving science</b>]]> For most of the 20th century optical petrography has been the primary petrological and mineralogical tool used to characterize coal. The development of quantitative SEM-based techniques, e.g. QEMSCANĀ®, for coal began only about a decade ago. The application of these techniques for coal lagged behind other commodities, but they are currently being developed with the aim to provide 'one complete analysis' for coal. Quantitative SEM-based techniques are supplemented by quantitative X-ray diffraction (XRD). Recent indications are that these more modern techniques cannot replace the 'standard' petrographic and chemical evaluations, but rather complement them where and when required. The great advantage of quantitative SEM-based techniques is that they are very rapid, with the result that large volumes of samples can be processed on a routine basis. This is ideal for coal type identification, since the results can be used in the creation of 'intelligent' composites. This can lead to the more speedy evaluation of coal deposits by reducing the number of samples on which detailed metallurgical and characterization test work is required, without an increase in the overall statistical error of the resource model. Coal petrography, however, remains important for the prediction of the coking characteristics of certain coals and coal products. As a consequence it is therefore important that any coal laboratory be able to produce data with confidence. This requires strict quality control and assurance protocols that adhere to international standards. <![CDATA[<b>Effect of microemulsified collector on froth flotation of coal</b>]]> The performance of microemulsified diesel and conventional diesel collectors in coal flotation was compared by flotation indicators, including combustible recovery, ash content of the clean coal, and the flotation index. An efficient separation with lower dosage was obtained using the microemulsified diesel collector. Under optimum separation conditions, the microemulsion consumption was 100 g/t less compared with diesel. The saving in diesel consumption using the microemulsion reached about 70%, disregarding the consumption of the surfactant and cosurfactant. Frothing tests showed that the frother dosage was decreased by using the microemulsion collector, because of the surfactant and cosurfactant added during preparation. The microemulsified diesel collector is superior to the conventional diesel collector in terms of diesel consumption and separation efficiency, but the selectivity requires further improvement. <![CDATA[<b>Truck cycle and delay automated data collection system in surface coal mining</b>]]> This paper presents the results of research on the development and application of a custom-made truck cycle and delay automated data collection system (TCD-ADCS) in a surface coal mining. Truck cycle and delay field data are locally stored in trucks and then synchronized and replicated through a wireless network into a centralized server containing an already-developed integrated production management system (IPMS). The system relies on motion sensing and distance travelled in order to automatically define the cycle starting/ending points, cycle time, position, and delay time. Connectivity and communication between loading equipment and trucks are also established. Communication between the equipment operators and TCD-ADCS system is via a user-friendly graphic interface. The hardware used for the development of this system consists of a rugged touch-screen personal computer, 2.4 GHz radio transmitter antenna, and a commercial GPS receiver. The system was developed, tested, and deployed at a surface coal mine in the USA.