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By Ana Chiquini, Clayton V. Deutsch

The most common approach used in the mining industry for mineral resources modeling is to estimate the grades using ordinary kriging and report the recoverable resources based on this deterministic estimated model. Mineral resources calculated with kriging are a smooth representation of the actual distribution of grades and do not provide an assessment of uncertainty. Unlike kriging, simulation reproduces the variability of the grades in the mineral deposit and provides an assessment of uncertainty. Reporting mineral resources directly on high-resolution simulation results would assume perfect knowledge of the grade at the time of mining and selectivity at the scale of the data. There will always be uncertainty left at the time of mining, so assuming perfect knowledge of the grade in the future is incorrect. There are two concerns when geostatistical simulation is used for resources modeling: the information and the mining selectivity effects. A new framework for resource estimation is proposed with two separate modules to address those concerns. The information effect is accounted for by anticipating the additional production data that will be available at the time mining to guide the destination for the mined material. The mining selectivity effect is addressed by mimicking the grade control procedure to get mineable dig limits at a chosen selectivity, represented by a minimum mineable unit size. In addition to a prediction of recoverable resources that will be closer to the material mined in the future, the framework proposed provides an assessment of local and global uncertainty for risk management.

May 26, 2020

By Mingfei He, Jianhua Chen, Yingchao Liu, Yuqiong Li

Pyrite is one of the most common sulfide minerals on earth, which is usually grown with chalcopyrite and other sulfide minerals. In flotation practice, pyrite from different mines or different sections in a same mine may have different flotation behaviors. This is because the pyrite crystal contains lattice defect, including ionic vacancy and lattice impurity. The present work investigates the effects of three typical 3d transition metal (Co, Ni, and Fe) on the adsorption of CH3OCS2 −, OH−, and CN− on pyrite surface by density functional theory (DFT) calculations. Calculated results show that Co impurity reduces the adsorption energies of CH3OCS2 − and CN− on the surface of pyrite, while Ni and Cu impurities significantly increase the adsorption energies of CH3OCS2 − and CN− on the surface of pyrite. Co impurity has small influence on the adsorption of OH−, but Ni and Cu impurities significantly increase the adsorption energies. Calculations on Mulliken charge population of Co2+, Ni2+, and Cu2+ indicate that the Mulliken charges of Co2+, Ni2+, and Cu2+ after OH− adsorption are more than those after CN− adsorption. This suggests that the ionic property of the M-OH- coordination bond is greater than that of M-CN- coordination bond, while covalent bonding of M-CN- coordination bond is greater than that of M-OH- coordination bond. The adsorption results are discussed based on coordination field theory (CFT).

Oct 6, 2020

By Jafar Safarian, Leiv Kolbeinsen, Stian Seim, Hossein Salehi

The present work aims to investigate the link between the oxidation and reduction of a weathered ilmenite concentrate in terms of phase transitions, microstructural changes, and element distribution. An ilmenite concentrate sample was pelletized and fired at 1000 °C in air, and as a result, the pellets were oxidized. The oxidized pellets were reduced by hydrogen gas at 1000 °C, which yielded almost complete metallization of the iron content of the pellets. The ore and the pellets were characterized in each step by XRD and SEM techniques, and distribution of elements and phases were investigated. Ilmenite, pseudorutile, and rutile were the main phases detected in the ilmenite concentrate sample, and depending on the weathering degree of the particles, different fractions of the phases were identified in their microstructure. It was found that irregular rutile grains dispersed in a pseudobrookite matrix is the morphology of the oxidized ilmenite phase. However, increasing microcracks and porosities were the only microstructural changes in the pseudorutile phase after oxidation in air. Studying the specific types of the ore particles and their oxidized and reduced forms indicated that the phase distribution in the ilmenite ore particles dictates the phase distribution in the oxidized and reduced ones. Results show that the morphology of the reduced particles includes a titanium (III) oxide matrix in which reduced iron globules are dispersed.

Feb 8, 2021

By Brenton Fletcher, Yongjun Peng, Wonder Chimonyo

As a cheap, renewable and non-toxic material, starch can contribute to the sustainability of the flotation process, albeit in a minor way as one type of reagent in systems involving materials with far greater impact. But the physical and chemical versatility of starch can help address another issue, namely, that of processing complex ores with decreasing grades of valuable minerals and increasing mixtures of gangue. This paper compares the results of two lab scale flotation studies where starches (native wheat starch (NWS), dextrin and two oxidised wheat starches) were used to depress two common gangue minerals, copper-activated pyrite and carbon (graphite), over a range of dosages. The oxidised starch with the larger molecular weight structures depressed copper-activated pyrite best, and the oxidised starch with lower molecular weight structures was better at depressing graphite. In both cases, the oxidised starches allowed greater recovery of chalcopyrite, pointing to selectivity potential. The extent to which the carbonyl and carboxyl moieties of the oxidised starches contribute to depressant performance is difficult to quantify, but it should not be discounted. Importantly, the results demonstrate relatively simple modifications of native starch by oxidation can yield structures suitable for depressing gangue minerals with diverse surface properties. The challenge remaining for greater application of modified starch depressants is being able to replicate the desired structures at scale in cold-water-soluble form.

Jan 18, 2021

By Sebastian Avalos, Julian M. Ortiz, Willy Kracht

Semi-autogenous grinding mills play a critical role in the processing stage of many mining operations. They are also one of the most intensive energy consumers of the entire process. Current forecasting techniques of energy consumption base their inferences on feeding ore mineralogical features, SAG dimensions, and operational variables. Experts recognize their capabilities to provide adequate guidelines but also their lack of accuracy when real-time forecasting is desired. As an alternative, we propose the use of real-time operational variables (feed tonnage, bearing pressure, and spindle speed) to forecast the upcoming energy consumption via machine learning and deep learning techniques. Several predictive methods were studied: polynomial regression, k-nearest neighbor, support vector machine, multilayer perceptron, long short-term memory, and gated recurrent units. A step-by-step workflow on how to deal with real datasets, and how to find optimum models and final model selection is presented. In particular, recurrent neural networks achieved the best forecasting metrics in the energy consumption prediction task. The workflow has the potential of being extended to any other temporal and multivariate mineral processing datasets.

Jun 16, 2020

By FELIPE SÁNCHEZ, PHILIPP HARTLIEB

Innovation plays a critical role in the mining industry as a tool to improve the efficiency of its processes, to reduce costs, but also to meet the increasing social and environmental concerns among communities and authorities. Technological progress has also been crucial to allow the exploitation of new deposits in more complex scenarios: lower ore grades, extreme weather conditions, deeper deposits, harder rock mass, and high-stress environments. This paper discusses the importance of innovation for the mining industry and describes the mechanisms by which it is carried out. It includes a review of the drivers and actors involved and current trends. The digital transformation process that the industry is going through is analyzed, along with other relevant trends that are likely to shape the mining of the future. Additionally, a case study is presented to illustrate the technical and economic implications of developing a disruptive innovation project.

Jul 23, 2020

By Timothy J. Orr, Robin J. Burgess-Limerick, Jennica L. Bellanca, MARGARET E. RYAN

Powered haulage continues to be a large safety concern for the mining industry, accounting for approximately 50%of the mining fatal accidents every year. Among these fatal accidents, haul-truck-related accidents are the most common, with 6 of 28 and 6 of 27 fatal accidents occurring in 2017 and 2018, respectively. To better understand why these accidents continue to occur and what can be done to prevent them, researchers reviewed the 91 haul-truck-related fatal accidents that occurred in the USA from 2005 to 2018 and performed bow-tie analyses using the final reports published by the Mine Safety and Health Administration. The analyses explore the context of the accidents with a focus on the initiating event, event outcome, hazards present, and possible preventative and mitigative controls. Overall, the vast majority of the accidents resulted in a haul truck colliding with the environment, and the majority of these events were initiated by loss of situational awareness or loss of control. The majority of the hazards were related to design and organizational controls. The results of this study suggest a need to investigate operator decision-making and organizational controls and to focus on improving design and operation controls such as mine design and operational procedures.

Feb 22, 2021

By Mei Long, Tawum Juvert Mbah, Jianhua Zhang, Haiwang Ye

There have been many improvements and advancements in the application of neural networks in the mining industry. In this study, two advanced deep learning neural networks called recurrent neural network (RNN) and autoregressive integrated moving average (ARIMA) were implemented in the simulation and prediction of limestone price variation. The RNN uses long shortterm memory layers (LSTM), dropout regularization, activation functions, mean square error (MSE), and the Adam optimizer to simulate the predictions. The LSTM stores previous data over time and uses it in simulating future prices based on defined parameters and algorithms. The ARIMA model is a statistical method that captures different time series based on the level, trend, and seasonality of the data. The auto ARIMA function searches for the best parameters that fit the model. Different layers and parameters are added to the model to simulate the price prediction. The performance of both network models is remarkable in terms of trend variability and factors affecting limestone price. The ARIMA model has an accuracy of 95.7% while RNN has an accuracy of 91.8%. This shows that the ARIMA model outperforms the RNN model. In addition, the time required to train the ARIMA is than that of the RNN. Predicting limestone prices may help both investors and industries in making economical and technical decisions, for example, when to invest, buy, sell, increase, and decrease production.

Jan 6, 2021

By Andrea Brickey, JUDITH BUABA, RICHARD AMOAKO

The global mining industry has recorded significant declines in accident and injury rates attributed to the advancement in technology, increased enforcement, and safety consciousness. A goal of the mining industry is to achieve zero injury and occupational illness on all mine sites, prompting increased research into ways to further reduce mine accidents. A machine learning technique known as multiclass logistic regression is applied on a 10-year injury dataset from the Mine Safety and Health Administration (MSHA) to determine a miner’s susceptibility to a class of injury and to help identify significant risk factors associated with different classes of injury. The data is aggregated based on injury classification to provide statistically relevant results. The analysis identifies specific risk factors that influence a mine worker’s susceptibility to a given class of injury, i.e., non-fatal with no days lost or restricted activity, non-fatal with days lost and/or days of restricted work activity, and fatal and total permanent or partial permanent disability. These factors include miner’s age, mine type (coal vs. non-coal), experience on the current job (years), shift start time, employment type (operator vs. contractor), mining district, and type of accident. The results of the analysis indicate that a miner’s experience on the job, i.e., the number of years worked in a current job, is a significant risk to injury occurrence, even for those with decades of total mining experience. We further show the differences and similarities between the surface and underground mine incidents.

Nov 3, 2020

By Diler Katircioglu-Bayel

This manuscript aimed to examine the impact of operating parameters on the wet grinding of talc in a vertical-type stirred media mill. Within the scope of the research, the effects of operating parameters including media filling ratio, solid mass fraction, grinding media size, and grinding time were studied. The findings were assessed based on the product particle size (d50, d10), surface area (Sw), and energy consumption (Em). As a result of the present research, the following optimum grinding test conditions were determined: 65% media filling ratio, 40% solid mass fraction, 1 mm grinding media size, and 120 min grinding time. After determining the optimum grinding conditions, the Box–Behnken statistical design was used to determine the effect of parameter interactions on the d50 size. The media filling ratio was found to significantly affect the decrease in d50 compared to the other two parameters. Furthermore, the minimum d50 size was also achieved under optimum grinding conditions.

Aug 12, 2020

By İsmail İnce

The existence of water is one of the most effective factors in deterioration of natural building stones. In the process of deterioration, capillary water absorption is the most significant procedure of water penetration into the building stones. Pyroclastic rocks have been widely utilized as building stone especially in historical buildings and monuments since ancient times in the Central Anatolia in Turkey. Nowadays, this type of rocks is used in the restoration of historical buildings as well as in the construction of modern buildings. Pyroclastic rocks are highly susceptible to deterioration process. Capillary rise has a significant influence on water penetration into building stones. Therefore, it is quite important to identify the factors affecting the values of capillarity, capillary rising speed, and capillary rise that define capillary water absorption in these rocks. To this end, pyroclastic rock samples in different textures were compiled from the Cappadocia region, in Central Anatolia. First, petrographic, mineralogical, geochemical, physical, and pore diameter distribution properties of the samples were determined in the laboratory. Then, capillarity values with capillary rise and capillary rise speeds dependent on time were established. Based on the data obtained, correlation coefficients between matrix percentage and capillary water absorption rate and capillary rise values of pyroclastic rocks were calculated and found to be as 0.850 and 0.891, respectively. Thus, the article proposes a new empirical equation to practically calculate the capillary rise value depending on the matrix percentage (MP) and median pore diameter (MPD) values.

Nov 30, 2020

By K. V. Raj, R. Jacksha

Conveyor systems persist in being a source of injuries and fatalities in the mining industry. To reduce these incidents, better methods are needed to enhance the monitoring of probable hazards and improve situational awareness during the normal operation and maintenance of conveyor systems. To address these issues, researchers from the National Institute for Occupational Safety and Health (NIOSH) continue to investigate emerging technologies that show the potential to improve miner safety around conveyors. This paper presents a feasibility assessment by NIOSH researchers of a fully integrated, commercially available wireless Internet of Things (IoT) system to improve situational awareness around conveyor systems. Included are discussions of a full-scale laboratory test bed that was designed to simulate a working conveyor system as well as the challenges and successes of integrating the IoT system with the test bed.

Oct 6, 2020

By Muhammad Zia-ur Rehman, Sajjad Ahmad Baig, Gao Lei Fu, Muhammad Mohsin, Sobia Naseem

The environmental sustainability is linked back to human sustainability; the sustainability development comprises the environment, society, and economics. This study mainly focused on mining sustainability and its impact on the environment of Pakistan. For measuring the level and environmental mining sustainability nature to Environmental Impact Assessment (EIA) of the world’s second largest salt mine “Khewra,” Folchi and Phillips environmental sustainability mathematics (PESM) models are applied. The results indicated that Khewra was deemed to be potentially sustainable for the environment and quality of salt. The results suggest the delicate balance of maintaining sustainability successfully, regarding the mining process in Pakistan which has been affecting the local environment and community so badly. The paper lays emphasis on the potential significance of the model’s application for the attainment of sustainable mining goal. This study is essential for researchers,

May 11, 2020

By Morgan M. Sears, Gamal Rashed, Michael M. Murphy, Brent Slaker

In this study, a parametric study was conducted using FLAC3D numerical models to examine the impact of oblique loading, generated from seam dip, on the strength and the failure propagation pattern of a stone pillar using two simplified geometry types. In type 1, the sidewalls of the pillars were assumed to be perpendicular to the roof and the floor, while in type 2, the sidewalls of pillars were assumed to be vertical. The complex pillar geometry in dipping mines was frequently modeled using these two geometries. To capture a complete picture of the effect of seam dip on pillar stability, the modeled width-to-height (W/H) ratio of the pillars, in situ stress field, and pillars roof/floor interfaces were systematically varied to account for the potential distribution of values for these parameters across the underground stone mines in USA. Results from the numerical modeling indicate that dipping pillars have reduced strength compared with horizontal pillars. Also, an asymmetric failure propagation pattern could be obtained depending on an interaction between the W/H ratio, seam dip, in situ stresses, and pillar geometry.

Feb 5, 2021

By Jürgen Kretschmann

The European climate and energy framework for 2030 is highlighting the reduction of man-made CO2 by increasing the use of renewable energy to mitigate climate change. In this spirit, Germany has decided to erase the coal use as an energy source by 2038 completely. Inevitably, this strategy promises a feasible, responsible, and sustainable post-mining management, because 200 years of coal mining have created numerous challenges necessary to tend to once the mining ends. Thus, the Research Institute for Post- Mining (FZN) at the TH Georg Agricola University in Bochum, Germany, has developed a holistic approach to meet these postmining challenges including further expertise present at our university. Here, the four strategic research pillars are (1) technical geoecology and hydrogeology to avoid and mitigate risks underground, (2) geomonitoring to evaluate and protect the surface, (3) industrial heritage preservation and engineering to secure and reuse brownfields such as mine sites, and (4) economic transformation planning of mining regions to enable a prosper future for generations to come. In all efforts, we aim to achieve the fundamental goals of the UN to deal with the resources of our planet responsibly and sustainably. Furthermore, we are synergizing increasingly with national and international networks in the interest of social, economic, and environmental stakeholders.

Jul 23, 2020

By Jorge Alberto Soares Tenório, Denise Crocce Romano Espinosa, Amilton Barbosa Botelho Junior

A new step in the Bayer process has been used to recover NaOH and to reduce its content in red mud. After digestion, the residue is separated from the Bayer liquor and goes through press filters, which enables the recovery of NaOH and decreases the moisture content. It is well known that red mud is one of the most important sources of scandium. For this reason, the goal of this work was to characterize a Brazilian red mud (BRM) for scandium recovery. The sample was collected after the press filter system process. Analysis of energy-dispersive X-ray fluorescence (EDXRF), scanning electron microscopy/energy-dispersive X-ray spectroscopy (SEM/EDS), and X-ray diffraction (XRD) was performed. Microwave digestion using an acid mixture was carried out to determine the concentration of the main elements. Fe2O3 represented 40% of the BRM, and the Sc concentration was 43 mg/kg. The SiO2 content was 24%, which is the highest value found in the literature, whereas the sodium concentration was the lowest. A literature review was carried out to compare results with BRM, as well as the current studies for recovery of scandium by the leaching/ion-exchange process. Scandium recovery using a leaching/ion exchange process may be possible with efficiency higher than 90%. The greatest challenge is the occurrence of silica gel formation during leaching.

Oct 19, 2020

By Sihua Lei, Hong Zhong, Shuai Wang, Yu Gan, Zhanfang Cao

High purity MgO is widely used in various fields as an important magnesiumcompound. The separation of Mg and Ca is of great importance for the preparation of high purity MgO from dolomite. In this study, the key effects of carbonization temperature and nano-calcium carbonate agglomeration on the separation mechanism of calcium and magnesium have been investigated. The results indicated that the reaction in the carbonization process was stepwise. Precise control of the carbonization temperature was essential for the formation of Mg(HCO3)2 due to its low reaction efficiency at lower temperatures or decomposition markedly at higher temperatures. Meanwhile, there was a common-ion effect in solutions containing Mg2+ and Ca2+. Nano-CaCO3 particles were formed during carbonization and agglomerated with the prolongation of static time. A product with a purity of 99.56% MgO and 0.16% CaO was obtained under the optimized conditions: ratio of liquid–solid 30 L/g, carbonization temperature 22–25 °C, carbonization time 1 h, and refining time 4 h. This work has important guiding significance for the preparation of high purity magnesium oxide from dolomite.

Apr 21, 2020

By Danqing Gao, Brijes Mishra

Spatial variance of rock properties is an important characteristic of rock which addresses the heterogeneity of mechanical and physical properties and their effect on underground mining. Assessing spatial variance can be useful for both locating potential difficult grounds and performing reliability analysis in the mining support system. This study shows a microscale numerical model for rock material based on continuum mechanics. To consider the spatial correlation factor of mechanical properties in realistic rock mass, this study introduces a spatial correlation concept into the traditional type III extreme value distribution model. Based on the improved microscale random model, we conducted a series of numerical uniaxial compressive tests and one longwall mine model to investigate the progressive failure of rock. The results show that spatial correlation factor can significantly affect the load-deformation curves and fracture patterns. The spatial variance model was applied to a longwall mine that included several cutting sequences to observe the influence of the spatial variance on roof behavior. The cohesion and friction random fields induced failure that propagated randomly through the immediate roof in different entries. The results showed that the spatial variance provides an accurate prediction of erratic roof falls in coal mines.

Jul 20, 2020

By W. R. Reed, Y. Zheng

A recent study conducted by the National Institute for Occupational Safety and Health (NIOSH) evaluated the roof bolter canopy air curtain (CAC) systemin a blowing face ventilation system, demonstrating its effectiveness and illustrating the CAC protection zones. This study evaluates the roof bolter machine CAC while operating in an exhausting face ventilation system. This study considers two similar locations to allow comparison with the previous blowing face ventilation (Zheng et al., Min Metal Explor 36(6):1115–1126, (2019)) study: (1) a roof bolter machine bolting the roof at 20 ft (6.1 m) from the face and (2) a roof bolting machine bolting at 4 ft (1.2 m) from the face. The environment introduces 6.0 mg/m3 of respirable dust to represent the roof boltingmachine operating downstreamof the continuous miner. However, the exhausting face ventilation uses an exhaust curtain with 9000 cfm (4.25 m3/s) of air. Two roof bolter machine working positions are simulated with the use of dual drill heads in the inward position for two inside bolts and in the outward position for two outside bolts. The influence of the CAC on airflows and dust dispersion is evaluated with the CAC operating at 250 cfm (0.12 m3/s) with dust reductions ranging from 39.5 to 82.8%. When the roof bolter machine operated close to the face, increasing CAC airflow was required for adequate protection since the dust reductions can be as low as 39.5%. Additional CAC airflows of 350 cfm(0.17 m3/s) and 450 cfm(0.21 m3/s) were evaluated and demonstrated that dust reductions increased to 59.7% (350 cfm) and 72.0% (450 cfm) for the worst location where the roof bolter operators located.

Aug 26, 2020

By Yongsik Jeong, Kwangmin Kim

Conventional tailings slurry contains a significant amount of water, and water management is key to ensuring the stability of a tailings storage facility (TSF). Simply reducing the water content in the slurry before discharging it from the mill could be an effective way to improve TSF water management. This study investigated the potential for using an environmentally friendly polymer as a new drag reduction agent (DRA) to reduce frictional pressure loss and also conserve water. It entailed conducting pipe loop tests to assess the polymer’s effect on pressure loss in tailings flow and then applying the test results to validate a numerical model using computational fluid dynamics (CFD). The model was also used to determine the polymer’s optimal concentrations at given solid concentrations and flow rates, its effect on energy efficiency for tailings transportation, and its potential for saving water. A case study for a mid-sized, hard-rock mine with a throughput of 50,000 t/day found that the solid concentration could be increased from 30 to 45% with no pressure loss by applying 1996 m3 of the polymer per day. Adding the polymer also resulted in water savings of 57,552 m3/day. The results of this study demonstrated the potential for using the new DRA not only to improve TSF stability but also to save water.

Jun 29, 2020