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By I Govender, T L. Moodley

Tumbling mills are grossly inefficient, using only 5 per cent of the total energy supplied for actual breakage. A significant proportion of this inefficiency is unavoidable owing to geometric limitations; rotating drum systems are prone to exhibiting certain regions (energy barriers) that resist particle entry thereby restricting the transfer of energy. Though such systems are inherently inefficient, improved modelling schemes may lead to slightly enhanced efficiency through better microscale predictions of key breakage drivers (stress, force). Central to achieving such incremental advances is the development of a universally accepted rheology for dense granular flows. Armed with a better understanding of these macro-scale ingredients, classical process modelling offers an efficient, spreadsheet friendly framework for recovering the spatial distributions of the comminution drivers. At this real-time level of process control, it should be possible to tune comminution operations towards more energy efficient configurations – the ultimate goal of this research. The present work employs validated DEM data to recover the full continuum field which will ultimately serve as a basis for calibrating process model outputs based on different rheological hypotheses. Such a continuumbased approach captures tensor properties like the shear stress and strain rate – both of which are necessary to developing a dense granular rheology. Moreover, DEM captures this data at the momentum transfer timescale of 10-6 s – no other measurement technique is capable of this level of spatial and temporal resolution. Importantly, the confidence in this DEM data is strengthened because it has been validated at the continuum scale using Positron Emission Particle Tracking (PEPT) kinematic measurements. Validated DEM data is derived from batch experiments conducted within a 300 mm ID laboratory drum using three and five millimetre glass beads at 60 and 75 percent critical speed; such mill speeds are typically encountered in the tumbling mill industry. Dimensional analysis is conducted using critical rheological parameters (shear rate, shear stress, granular temperature etc), which are key to not only developing a granular rheology but ultimately will be used to tune our mechanistic models.

Aug 24, 2022

By J Cortinez, P Vallejos, J Yianatos, M Rodriguez

Nowadays, one of the main problems in current flotation plants and new projects is the significant decrease in feed grades and changes in the mineral composition, which has an important effect on the mineral liberation and associations. Additionally, flotation plants usually operate with feed throughput higher than the original design, which has a significant impact on the feed particle size. All these conditions affect metallurgical performance, and must be evaluated and addressed, by improving control strategies for banks optimisation. For this purpose, the flotation of valuable minerals along the circuits requires better understanding, considering the compromise between performance and selectivity in flotation circuits. This paper presents a characterisation of the different minerals recovered along industrial flotation circuits. Plant sampling campaigns, performed in a copper industrial concentrator in Chile, provided the data for the study. Two rougher flotation banks consisting of cells of 130 m3 and 300 m3 were analysed. All the samples from the industrial surveys were analysed by screening and mineralogy, and the mineral recovery along the circuits was evaluated per particle size class, liberation class, type of associations, and others. Additionally, operating data on froth depth profiles complemented the evaluation of the mineral composition of concentrate streams, along the circuit. The results allowed for identifying and quantifying the main factors that affect the copper recovery and concentrate grade along the flotation banks. It was found that minerals with liberation lower than 50 per cent have a significant impact on the recovery. On the other hand, the decrease in the Cu grade in concentrates along the flotation circuits is mainly due to the relative increase of middling minerals (less liberated), non-valuable floatable minerals, such as free pyrite, and gangue entrainment. The characterisation of the gangue entrainment flow rate along the flotation banks showed a strong relationship with froth depth, which becomes more critical towards the last cells of the banks.

Aug 24, 2022

By J Lainé, M Badawi, A C. de Araujo, Y Foucaud, C Veloso

Flotation is the one of the most used techniques for the mineral separation of non-ferrous ores worldwide. However, the increase of the complexness along with the decrease of ores liberation sizes ought to become important challenges for mineral processing, including flotation. It now appears necessary to better understand the fundamentals of the flotation process, particularly the adsorption of flotation reagents at the liquid/mineral interfaces, to propose further improvements. Flotation relies on different phenomena: surfactants adsorption, on one hand, and collision, adhesion, and transport of particles with bubbles, on the other hand. For acknowledging the reagents adsorption mechanisms, molecular modelling tools borrowed from chemical and material sciences, are increasingly used. Atomistic simulations were successfully applied to study the flotation reagents interaction with various mineral surfaces, eg of two common minerals from iron ores, kaolinite, and magnetite surfaces, or with fluorite surface, a tungsten ores common gangue mineral.

Aug 24, 2022

By T M. Campos, H A. Petit, L M. Tavares, R Olympio

Much practical experience has been gathered in the last 30 years of application of high-pressure grinding rolls (HPGR) integrated with ball milling in size reduction of fine iron ore concentrates. The company Vale S.A, in Complexo de Tubarão (Brazil), was one of the pioneers applying the technology prior to pelletisation with an outstanding size reduction energy efficiency in the circuit and a significant increment in the specific surface area of the product. Recent studies by the authors demonstrated benefits of modelling and simulation to improve the performance of HPGRs in this particular application, with the model being able to describe HPGR performance under different operating conditions and under variations of feed size distribution. Despite these important advances, this modelling approach has only been used offline and under steady-state conditions. The present work applies the modified Torres and Casali model proposed by the authors in pseudodynamic simulations. The ability of the model to predict the characteristics of the product in real-time is evaluated using data available online for the pellet feed preparation circuit. Results demonstrated the model capabilities to map the physical operation and give a realistic representation of the process. Additionally, the model is demonstrated to be able to support the pellet feed production by providing extended real-time information of the process, making it a useful tool for improvement of the operational strategies and process stability.

Aug 24, 2022

By D Teyhan, J Kirsch

Traditionally, most Australian iron ore mining operations have been surface-based. Processing plants were designed to handle dry ores. In recent years mining operations in the Pilbara have progressively moved below the water table exposing wet, sticky ores which have caused lost efficiency in screening operations as particles tend to agglomerate and adhere, blinding screening media. Miners and vibrating screen manufacturers have experimented with a shift from linear motion to elliptical motion screens. Elliptical motion conveys and lifts particles. Effective on flat deck (horizontal and inclined) or sloping decks it can be configured to provide a controlled transport rate, applying pressure in all directions to maximise screening efficiency. In practice, elliptical motion screens have proven to be effective in dislodging sticky particles from screening media, reducing blinding rates and improving screen efficiency. Moisture and clay content change during the life of a mine. These changes are sometimes the effect of seasonal rainfall, in other cases due to increased groundwater and clay content as mining operations go deeper. To compensate for such changes and optimise screen efficiency, changing the ‘shape’ of elliptical screen motion is required. This has traditionally required shutting down processing plants and making mechanical screen adjustments. Plant downtime is costly and machine adjustment has been a ‘trial and error’ practice. This paper will explore the results of a field trial that is currently underway in Brazil of a next generation elliptical motion screen design that allows operators to make changes to exciter rotational direction, speed and screen stroke angle, through electronic drive phase control. The machine’s electronic drive system synchronisation is enhanced for stability with a unique mechanical timing system. Operating at up to 6 g, screen adjustments can be made on the fly without stopping production. Early trial results are showing up to 50 per cent improvement in screen efficiency compared with traditional elliptical motion machines under certain feed conditions.

Aug 24, 2022

By H Park, L Wang

Froth flotation is one of the most widely used beneficiation processes for fine and ultrafine coals and minerals. Maintaining optimal metallurgical performance in industrial flotation operation is still a challenging task owing to the lack of an effective tool to diagnose the flotation performance in realtime. For this purpose, a number of flotation performance monitoring systems with different working principles have been developed to provide instant feedback for process control and optimisation. In this paper, for the first time, five different flotation performance monitoring systems were systematically compared through an on-site trial in a coking coal flotation plant in Queensland, Australia. The monitoring systems were used to measure (i) gas holdup, (ii) overflowing froth velocity, (iii) overflowing froth height, (iv) air recovery and (v) drag force exerted by overflowing froth, in an industrial flotation column and the outputs of these systems were collected simultaneously at a wide range of operating conditions. For each monitoring system, the best regression model describing the correlation between the system output and the flotation performance was selected from various regression models (eg linear, quadratic, power-law and logarithmic) using the Akaike information criterion (AIC). A comparison of the coefficient of determination (R2 ), residual sum of squares (RSS) and measuring accuracy at 95 per cent confidence level of the best regression models of these monitoring systems suggested that the drag sensor outperformed the other systems at a wide range of flotation operating conditions. The superior performance of the drag sensor was attributed to its distinctive design that enabled intimate sensing of variation of the overflowing froth properties. Furthermore, the drag sensor had the ability to monitor feed ash content variation when the other operation variables were set almost constant.

Aug 24, 2022

By G R. Ballantyne, A N. Mainza, M S. Powell, M Evertsson

Quantifying the performance of a comminution circuit relative to the potential that can be achieved is a standard requirement in justifying operating practice (the stick) and seeking operational upside (the carrot). Historic measures tend to focus on performance relative to laboratory design tests that provide a direct measure of specific grinding energy, such as the Bond Work index; or use dropweight breakage tests calibrated to a substantial database of operating sites, such as the SMC methodology. Although of value, such approaches are flawed in significant aspects. The assumption is that the laboratory prediction is correct and the single sample it is based on is representative. The database benchmarking methods are, by definition, locked into current average operating practice. These approaches do not illuminate upside; can ‘punish’ operations that are actually more efficient, such as grinding finer than standard operation; and reward poor operation that may comfortably produce a coarser grind than optimal for recovery or excess slimes that reduce recovery and increase water consumption and tailings volume. The authors present a set of established and easily applied measures, that draw together daily operation, highlight areas of opportunity and inefficiency, use simple samples and data, and can be used to provide the ‘size of the prize’ in pursuing specific areas of process improvement. These tools include size specific energy (SSE), overall operating effectiveness (OEE) which includes product quality, theory of constraints, and links this to the end objective – maximising the efficient production of valuable metals. Feeds into objective function driven by economics – financial return, energy, environment.

Aug 24, 2022

By J Moffatt, T Payten, N Spooner, L Teixeira, L A. Balzan, G Wilkie, G Tsiminis

Fluorine is a penalty element due to its reactive nature. In acidic environments many fluorine minerals dissolve to form hydrofluoric acid (HF), changing processing conditions. When smelted HF can be released, causing negative effects to nearby people and the environment, as well as potentially damaging the smelter. Sale of ore with high fluorine levels elicit a financial penalty or are banned outright. Real-time sensors create the opportunity for instantaneous decisions on ore processing due to changing conditions. A fluorine sensor would allow rises in fluorine concentration in a processing stream to be flagged, and decisions on processing conditions or diversion to stockpile before processing could be undertaken. As fluorine is a light element, it is difficult to detect with in-field XRF devices and does not work well with PGNAA. There are currently no existing sensors to quantify the presence of fluorine in real-time, and thus decisions based on fluorine grade cannot be made at minute- or even hour-scales. Sensors designed to measure the presence of minerals that contain fluorine are a possible avenue to enable the real-time detection of this element. Mineral-based sensing may also give an added advantage of additional information about how the fluorine will react under different processing steps. The authors were given a grant under CRC ORE II (project number P1–005) to search for mineralspecific signatures suitable for real-time analysis. The work focused on novel regimes and applications of fluorescence as a means to detect specific minerals. The aim was to exploit fluorescence responses unique to minerals of interest in mining systems in order to produce sensors that address gaps in existing capability. After the successful discovery of signatures specific to two major fluorine minerals an additional grant (P1–014) was funded to develop the research into a prototype on-belt sensor, in partnership with Scantech International Pty Ltd. This paper details the development of a sensor package through multiple Technology Readiness Levels (TRLs) through collaboration with government/industry grant schemes, academics from university, and a sensor-focused Mining Equipment and Technology Services (METS) company. We give a brief description of the new sensor technique and provide a case study of multi-disciplinary collaboration.

Aug 24, 2022

By W. P. Arnott, P. Nascimento, X. L. Wang, K. C. Kocsis, S. J. Taylor, H. Firouzkouhi

We report the first spectral photoacoustic measurements of silica, coal, and kaolinite dust absorption coefficients from 11 to 13 μm at 5 nm resolution made with a tunable quantum cascade laser. This is important because airborne silica dust and coal dust within mining environments continue to be a problem for mine workers and staff due to their severe health effects on the respiratory system, while other dust types are potentially interferents to their detection. Our real-time spectra compare favorably with the non-real-time filter-based Fourier transform infrared spectrometer (FTIR) spectra obtained using the sampling system developed by NIOSH for their end-of-shift method to determine silica dust concentrations using a portable FTIR. We discuss our new dust generation system and instrument testing chamber. We also show that our PM4 silica mass concentration measurements by a low-cost air quality sensor (SPS30) are in good agreement with the TSI Aerosol Particle Sizer instrument, the NIOSH end of shift method, gravimetric mass, and correlate well with photoacoustic light absorption measurements at a wavelength where silica absorbs strongly.

Aug 20, 2022

By Jingzhi Liu, Xueping Hu, Huai Wang, Simin Yang, Baoqiang Yu, Deguang Zhan

In this study, response surface methodology (RSM) and Box-Behnken design to improve copper extraction from refractory copper oxide ore were investigated. Based on single factor tests, quadratic polynomial equation to describe the relationship between influencing factors (particle size, leaching temperature, sulfuric acid concentration, leaching time) and copper leaching rate could be obtained by RSM. The optimum parameters determined by the model are as follows: particle size 64.60% − 74 μm, leaching temperature 74.15 °C, sulfuric acid concentration 0.49 mol/L, and leaching time 140.85 min. Under these conditions, experimental copper leaching rate of 85.12% could be achieved, which was very close to the predicted maximum value (85.34%) by the model, indicating the quadratic polynomial model was accurate and reliable. Copper leaching rate increased approximately by five percentage points comparing to the result of single factor tests. This study indicates that response surface methodology is an effective method to optimize experiment conditions and achieve an ideal experiment result.

Aug 17, 2022

By LUKAS FAHLE, Andrew J. Petruska, JURGEN F. BRUNE, Gabriel Walton, Elizabeth A. Holley

Adverse ground behavior events, such as convergence and ground falls, pose critical risks to underground mine safety and productivity. Today, monitoring of such failures is primarily conducted using legacy techniques with low spatial and temporal resolution while exposing workers to hazardous environments. This study assesses the potential of novel simultaneous localization and mapping (SLAM)-based light detection and ranging (Lidar) data quality for rapid, digital, and eventually autonomous mine-wide underground geotechnical monitoring. We derive a comprehensive suite of quality metrics based on tests in two underground mines for two state-of-the-art mobile laser scanning (MLS) systems. Our results provide evidence that SLAM-based MLS provides data of the quality required to detect geotechnically relevant changes while being significantly more efficient for large mine layouts when compared to traditional static systems. Additionally, we show that SLAM-specific processing can achieve an order of magnitude better relative accuracy relevant for change detection than quality metrics derived from traditionally deployed tests would suggest while reducing SLAM drift error by up to 90%. In collaboration with an operating block cave mine, we confirm these capabilities in field tests on a mine-wide scale and, for the first time, demonstrate methods of rockfall detection using MLS data. While more work is required to investigate optimal collection, processing, and utilization of MLS data, we demonstrate its potential to become an effective and widely applicable data source for rapid, accurate, and comprehensive geotechnical inspections.

Aug 16, 2022

By A. Juganda, F. WILSON, H. PINHEIRO, N. SANDOVAL, J. F. Brune, G. E. Bogin Jr.

To evaluate methane explosion hazards in longwall coal mines, a CFD model was developed along with a 1/40th-scale, optically accessible model of an underground longwall coal mining section. In this project, CFD models assisted in the design of the physical model to ensure specifications were met for accurately representing the scaling physics as well as to assist in narrowing the experimental matrix and identifying key locations for sensor placement to measure velocity, pressure, and gas concentrations. This research will help develop strategies for methane monitoring that prevent methane ignitions and explosions in longwall coal operations.

Aug 15, 2022

By F. Nakhaei, M. Le Roux, Q. P. Campbell, S. Botlhoko

The results of coal sink and float tests are plotted as washability curves. Analysis of these curves indicates the most effective method by which the coal can be cleaned. Sink and float experiments are samplingdependent, destructive, and use toxic chemicals. The present research introduces an alternative method based on a 3D imaging system called RhoVol, in which the density of individual particles is determined from mass and volume measurements. A quantitative error analysis was conducted on coal sample density measurements obtained by RhoVol, and the main factors influencing the errors identified and investigated. The results show that the drawback of this technique is related to its not being able to detect hidden concavities in the particle, resulting in an overestimation of particle volume. Furthermore, it is difficult to capture the impact of porosity and cracks on the volume of coal particles obtained from 3D silhouette images. This mismatch between the RhoVol data and sink and float test results has led to attempts to apply neural network (NN) and linear regression techniques to produce a fully reliable model for correction and estimation of coal density. The NN approach offers superior predictive capability over linear regression, and the estimated density distribution is in line with the sink and float analysis. The root mean square error in estimation of density using the NN model was less than 0.05 g/cm³.

Aug 2, 2022

By K. Isaac, S. O. Bada

This research focuses on the co-firing of discard coal with refuse-derived fuel (RDF) to utilize this abundant resource in South Africa for energy generation and reduce the volume of waste disposed of at landfills. The potential of a coal with a high ash content (> 40%), which is a grade used in some power stations in South Africa, and its combustion compatibility with two different RDFs in terms of emission reductions has been established. Gaseous emissions and ash residues from the combustion and cocombustion of the coal, two different RDFs and coal/RDF blends of different proportion were analysed. One of the RDF samples contained mostly paper (PB) and the other mostly plastic (PL). Co-combustion ash from the discard coal and RDFs showed a decrease in chloride and alkali metal contents as the coal ratio in the blend increased. The slagging propensity of the co-fired blends was found to be very low, while the propensity for fouling decreased from high to medium for all the blends with < 75% RDF. Cocombustion of RDF with coal showed a decrease in SO2 emissions from 387 ppm (discard coal) to 50 ppm for the sample containing 25% coal discard plus 75% PL. A 15% PL to 85% coal blend also reduced NOx emissions from 145 ppm (100% PL) to 88 ppm. The lowest CO2 emission observed was 6000 ppm for the blend of 85% discard coal plus 15% PB. It was established that the most favourable fuel blend that can produce the lowest sulphur emissions if used for power generation is the 25% coal discard plus 75% PL sample.

Aug 2, 2022

By JUAN DIAZ, Kray Luxbacher, Steven Schafrik, Dionissios T. Hristopulos, Zach Agioutantis

Methane gas is emitted during both underground and surface coal mining. Underground coal mines need to monitor methane gas emissions to ensure adequate ventilation is provided to guarantee that methane concentrations remain low under different production and environmental conditions. Prediction of methane concentrations in underground mines can also contribute towards the successful management of methane gas emissions. The main objective of this research is to develop a forecasting methodology for methane gas emissions based on time series analysis. Methane time series data were retrieved from atmospheric monitoring systems (AMS) of three underground coal mines in the USA. The AMS data were stored and pre-processed using an Atmospheric Monitoring Analysis and Database Management system. Furthermore, different statistical dependence measures such as cross-correlation, autocorrelation, cross-covariance, and variograms were implemented to investigate the potential autocorrelations of methane gas as well as its association with auxiliary variables (barometric pressure and coal production). The autoregressive integrated moving average (ARIMA) time series model which is based on auto-correlations of the methane gas is investigated. It is established that ARIMA used in the one-step-ahead forecasting mode provides accurate estimates that match the direction (increase/decrease) of the methane gas emission data.

Aug 2, 2022

By Nasser Madani, SULTAN ABULKHAIR

The geological and geostatistical modeling of mineral deposits requires densely sampled drillholes that provide accurate and reliable hard data. Furthermore, quantifying orebody uncertainty through geostatistical simulation can allow mining engineers to assess long-term risk in mine planning. Nevertheless, ore deposits can sometimes lack dense drillhole information, reliable hard data with proper quality assurance/quality control (QA/QC), or sometimes both. This study is based on a coal mine located in the Republic of Kazakhstan, where an iron dataset is based on data from three newly drilled drillholes, and geological information comes from a massive collection of legacy drillhole data with no evidence of proper QA/QC. For this reason, a workflow was introduced to construct a representative training image from legacy data and stochastically model geological domains within these three drillholes using a multiple-point geostatistics technique. Once the geological model was obtained, a two-point geostatistics algorithm was applied to model the iron inside each geological domain. The direct sampling algorithm was chosen for modeling geological domains, and sequential Gaussian simulation for iron grade calculation. Both methods were extensively evaluated using different statistical tools and analyses.

Aug 1, 2022

By CLAIRE STREBINGER, ADITYA JUGANDA, JURGEN F. BRUNE, GREGORY E. BOGIN JR.

Methane gas explosions are a major risk in underground coal mining operations. The severity of such explosions can range from local area damage to massive loss of miners’ lives along with significant damage to mine infrastructure and ventilation controls that may lead to mine closure and loss of the entire operation. This study demonstrates the viability of integrating a computational fluid dynamics (CFD) combustion model into a longwall mine ventilation model to simulate methane gas explosions in the longwall face area. The resulting 3D methane gas explosion simulation can provide better understanding of the fundamental physics and the potential impact of an explosion in an underground longwall coal mine.

Aug 1, 2022

By Kanhaiya Mishra, Phanil. K. Mandal, S. K. Behera, P. S. Paul, Prashant Singh, C. N. Ghosh

The techno-economic and social benefits of cemented paste backfill (CPB) resulted in its wide acceptance by the mining industry. The Ordinary Portland Cement (OPC) remains the key binder but to diminish its economical constraints, suitability of alternate binders has been examined worldwide. The present study aimed to investigate the effect of partial replacement of OPC with fly ash on the CPB’s strength and to determine the most optimal mix to achieve the required strength (1 MPa at 28 days of curing) at the most cost-effective way using the Bayesian network (BN). The CPB mixes were prepared at 72 wt.% solid concentration with mill tailings (87–91%), OPC (6–13%), and fly ash (0–4%), and instantly after mixing, fresh (slump, bleeding, density) CPB properties were measured. The strength was tested at 7, 14, 28, and 56 days of curing and initially analysed through traditional model. The traditional models follow the aleatory principle and are considered not appropriate for geotechnical engineering. Hence, the BN model was developed and tested. The reliability of two classifiers in learning model structure was compared which gives Naïve Bayes as the highest reliable tool. The CPB’s strength is most sensitive to the OPC content. The most consistent mix(s) is mill tailings: 87–88%, OPC: 9–11%, fly ash: 1–4%. Adding fly ash at 89–91wt% mill tailings possesses high failure probability of the CPB. The collinearity test indicates that the fines percentage and chemical composition of CPB’s ingredients are highly correlated with its slump, bleeding, and strength development.

Jul 14, 2022

By Michael David Harmse, Wiehan Adriaan Pelser, Jean Herman van Laar, Cornelius Stephanus Lodewyk Schutte

The South African deep-level mining industry is characterised by high operating costs and narrowing profit margins. Compressed air is commonly the largest consumer of energy in these mines, and any inefficiencies reduce profitability. Various methods aiming to optimise the compressed air networks have been implemented without an ideal economic dispatch strategy due to the lack of compressed air storage. In this study, a genetic algorithm was developed to evaluate the financial benefit of converting underground haulage to act as an air receiver (compressed air storage). By converting inactive haulage of 1.17 km in length into a volumetric air receiver, an annual monetary benefit of R2.5 million ($163 200) can be achieved, with a payback period of fewer than eight months. However, implementing the ideal size air receiver would result in an annual monetary benefit of R7.67 million ($500 700).

Jul 11, 2022

By Ihsan Berk Tulu, Mustafa Can Suner

The synthetic rock mass (SRM) approach and discrete fracture network (DFN) model, generated from the field surveys, are novel methodologies to study fracture rock mass behavior. In this paper, SRM and DFN methodologies were used to understand the influence of natural fractures on the mechanical response and failure mechanisms of stone mine pillars. First, a multi-stage up-scaling procedure with the homogenization process is established. Later, a stochastic sampling process on the SRM model to have further insight on the stone mine pillar mechanics is performed. Two-dimensional Universal Distinct Element Code (UDEC) is utilized to represent intact rock with the Voronoi-Trigon discretized blocks and to capture fractured rock mass behavior. The laboratory-size limestone mine rock specimens are systematically up-scaled to the average width of the field-size stone mine pillars. Then, the DFN model, generated from field data, is sampled to construct the SRM of the field-size pillars. By doing so, the effect of discrete discontinuities on pillar stability is studied by assessing the pillar strengths and failure mechanisms in various width-to-height ratios.

Jul 8, 2022