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By Nikhil Dhawan, Shrey Agrawal

India’s most extensive renewable energy expansion program targets 280 GW of solar energy by 2030. Due to the massive generation of photovoltaic waste (expected 34,600 T by 2030), stringent recycling effort to recover metal resources from endof- life PVs is required for resource recovery, circular economy, and subsequent reduction in the environmental impact. The present study investigates the recycling potential of end-of-life silicon solar modules. The feed characterization reveals that most of the values in PV modules are concentrated in the frame (pure Al), Si wafer (72–84% Si, 9–12% Al, and 0.13–0.71% Ag), and electrical connections (Cu wire coated with Sn). The Si and Ag values in the feed were beneficiated using water fluidization, and concentrate with 90% Si and 2% Ag was attained in the underflow concentrate. Ag values were recovered in the form of AgCl by leaching in nitric acid and precipitation. After the purification step, the residue containing 99% Si can be further utilized to fabricate Si wafer and Al-Si alloy. The preliminary cost estimations suggest that the proposed process is economically viable for the recycling of solar panels with the maximum value generated from the AgCl precipitate followed by Al panels and Si wafers.

Nov 14, 2022

By JESSICA W. A. AZURE, Kansake A. Bruno, Samuel Frimpong, AZUPURI G. A. KABA, FORSYTH A. KADINGDI, PROSPER E. A. AYAWAH

Blasting generates undesirable ground vibration with adverse effects on humans, the environment, and structures. Numerous studies have used various techniques including machine learning (ML) to predict the peak particle velocity (PPV) caused by blasting in surface mines. These studies used the validation-set approach to evaluate the performance of their predictive models. In this study, Random Forest (RF), Gaussian Process (GP), and Gradient Boosting Machine (GBM) were applied for the prediction of PPV using data from a large open-pit gold mine in Ghana. An ensemble model based on a stacked generalization approach was then built on these three base models to significantly improve the PPV prediction performance. The model evaluation was done using repeated tenfold cross-validation which resolves the challenges with the validationset approach for small datasets. The dataset used in this study comprised a total of 196 measurements taken from different blasting operations. R-squared ( R2 ), mean absolute error (MAE), and root mean square error (RMSE) were used to evaluate the model performance. The results obtained from these models revealed that all the base models did not significantly outperform each other. However, the stacked generalization approach had a better performance, with RMSE = 0.12, R2 = 0.96, and MAE = 0.07. This approach presented an improvement over the existing methods and will be useful for highly accurate predictions of ground vibration during blast design. The application of this model will be useful for efficient and effective blast design.

Nov 8, 2022

By Zhonglin Ye, Guangping Dai, Ba Zhang, Yonggang Wei, Shiwei Zhou, Bo Li, Hua Wang

Decreasing copper content in slag is critical for improving copper recovery, where apparent viscosity is the main factor affecting the separation of matte/copper from the slag. The viscous behavior of copper converter slag was investigated during reduction process in this paper, and its non-Newtonian viscous behavior and shear thickening characteristics were clarified. The effects of silicate structure and solid particles in the melt on the slag apparent viscosity were investigated. As slag cleaning proceeded in an electric furnace, the magnetite gradually transformed into ferrous oxide, increasing the FeO/SiO2 ratio. With this ratio increased from 1.2 to 2.0, the slag structure was simplified, and its apparent viscosity decreased from 0.26 to 0.12 Pa·s at 1523 K. The iron phase was excessively reduced to metallic state; the slag contained metallic copper-iron alloy particles, increasing apparent viscosity. The apparent viscosity and phase structure of the slag corresponding to the iron phase reduction process were analyzed in detail; the results obtained in the present study are of great significance to the reasonable control of the converter copper slag cleaning process.

Nov 7, 2022

By Jianbo Hu, Tao Zheng, Zhao Qihua, Rui Su

Rock mass discontinuities play a significant role in evaluating the stability of rock slopes. It is necessary to collect and analyze these discontinuities to fully understand the mechanical and deformational behaviors of rock masses. Based on the digital images of some slope faces, this paper proposes a framework based on machine learning for detecting and extracting discontinuities. First, digital images and photo poses are combined, the original scene is reconstructed, and 3D point cloud data are obtained. All captured point clouds can be mapped with each image by the direct linear transformation algorithm. Next, the detection machine learning algorithm is used to segment rock mass discontinuities on 2D digital images. Finally, based on the mapping relationship, the 2D digital images that were segmented are transformed into 3D point cloud data. The geometric parameters of the corresponding discontinuities can be extracted by the DBSCAN and the Skmeans algorithm and the characterization of specific rules. The proposed framework was evaluated utilizing a quantity of slope digital images in the Yebatan hydropower under construction, located in Sichuan Province, China, as a case study. The results illustrate that most deviations are less than 10° for the dip direction and dip angle, which verifies the reliability of the proposed framework and maintains acceptable measurement accuracy.

Nov 6, 2022

By Jagannath Pal, Ammasi Ayyandurai

Hematite ore pellets require a much higher induration temperature than magnetite ore pellets because no exothermic heat is generated due to oxidation inside during induration-like magnetite pellets. Carbon is used as in situ heat source in hematite ore pellets which can reduce temperature requirement in the induration strand and hence decreases energy consumption. Many investigators have reported that a 0.8–1.25% addition of carbon in hematite pellets can improve the pellet properties also. However, to investigate the exact role of carbon in hematite pellets, its reaction mechanisms and kinetics study are required which have not been done so far. Therefore, the reaction mechanism and its kinetics have been studied in this investigation. It has been found that carbon reaction happens in pellets from the surface towards the center in a topochemical manner which is controlled by pore diffusion of gas, and its activation energy is around 52 k J mol− 1. It is also found that apart from in situ heat, carbon in hematite pellets enhances diffusion bonding which improves pellet properties. This study ascertains the exact role of carbon in hematite pellets which may help operators to use carbon effectively to reduce energy consumption and improve pellet properties.

Nov 6, 2022

By Miguel Reyes, Chenming Zhou, MATTHEW GIRMAN

Electromagnetic energy emitted from electronic devices has been known to interfere with other electronic systems, hindering their ability to function properly. Mines have many electronic devices critical to the health and safety of mine workers that could be negatively affected by electromagnetic interference (EMI). To ensure that devices are electromagnetically compatible, tests must first be conducted to measure emissions and check for immunity. Standards are available across multiple industries that prescribe emission limits and test methods for electronic devices. A literature review was conducted in this study, and an overview of EMI standards in other industries is provided. Also, an example of how a standard can be applied to mining equipment is presented.

Nov 1, 2022

By Y. Pan, P. Tukkaraja, R. BHARGAVA, V.V.S. VYTLA, S.J. SRIDHARAN

Panel caving is an underground bulk mining method that uses gravitational force to mine massive, steeply dipping and deep-seated ore deposits at lower operating cost. To control dust and gas emissions entering the production level during the extraction of ore from the draw points in a panel cave, relatively negative pressure is created in the cave by installing an exhaust fan in the exhaust drift located on top of the cave. As caving is a dynamic process, designing an effective ventilation system is challenging; therefore, estimating the airflow resistance offered by the broken rock inside the cave is critical. This study investigates the effect of changes in the bulk porosity of the broken rock on the cave airflow resistance using the computational fluid dynamics (CFD) approach. The results show an inverse relationship between the cave airflow resistance and the bulk cave porosity. The pressure-quantity characteristic curves presented in this paper provide valuable information for sizing and operating an exhaust fan used for a mature panel cave ventilation.

Nov 1, 2022

By M.P. ROY, ASHISH K. VISHWAKARMA, A.K. MISHRA, P.K. SINGH, VIVEK K. HIMANSHU

Principal component analysis (PCA) is one of the dimension reduction techniques widely used to classify data based on features. Ground vibration is a major hazard arising from rock blasting operations, and accurate prediction of the vibration is necessary for designing controlled blasting parameters. Most of the widely accepted predictors of ground vibration consider the maximum explosive charge weight per delay (MCPD) and distance as the parameters responsible for ground vibration, but mining sites with bigger production targets have varying geometrical parameters to suit the excavator utility. Accordingly, other blast design parameters will also have impacts on ground-vibration intensity. A blast vibration predictor considering all the blast design parameters would be complicated, and some of the parameters will have overlapping contributions to ground-vibration intensity. Data classification using PCA is a feasible solution, and regression analysis may be performed to develop predictors using the classified input data. In this study, PCA was used along with multivariate logarithmic regression to predict ground vibration, and the performance of this technique to predict ground vibration was compared with the performances of various existing empirical predictors. The evaluation suggests that the predictor with logarithmic regression followed by PCA performs better than the existing empirical predictors.

Nov 1, 2022

By DEVY DYSON, Brian Hart, JOHN LANGHANS, Stamen Dimov, STEVE YOPPS

A recent Nevada Gold Mines research program focused on the pressure oxidation (POx) pretreatment of a Carlin-type double refractory ore from the Turquoise Ridge Mine. The research team found that both arsenian pyrite and carbonaceous matter were highly oxidized within an hour at 300 °C using a bench-top autoclave reactor and that the gold recovery from the residues after cyanide/carbon-in-leach (CIL) approached the technical limit set by the amount of gold encapsulated by silicate minerals. Although the 60-min pretreatment at 300 °C yields robust performance when treating a whole ore, copper additives can catalyze the oxidation rate of carbonaceous matter and reduce the residence time needed at elevated temperatures. Certain gangue minerals are susceptible to dissolution in acidic solutions at 300 °C, and this may cause poor gold recovery. This recovery challenge is mitigated by keeping free acid in the discharge solution below a key threshold.

Nov 1, 2022

By K. KAKLIS, O. SAUBI, Z. Agioutantis, R. JAMISOLA

Machine learning in the form of artificial neural networks was applied to investigate whether specimen load evolution can be predicted as a function of acoustic emission (AE) signals in the case of three-point bending (TPB) marble specimens instrumented with piezoelectric sensors. The ultimate objective of this study is to develop a model that can quantify rock behavior under loading that can lead to rock-failure prediction in underground structures subjected to bending, such as roof failure in development or production openings.

Nov 1, 2022

By Ajit Godbole, Ping Chang, Ramakrishna Morla, Purushotham Tukkaraja, Shivakumar Karekal

This paper presents the optimum auxiliary fan(s) location to control air recirculation in dead-end workings where dieselpowered vehicles operate. Investigations were conducted with various secondary fan locations from the dead-end crosscut with varying the intake air quantities using a 30 m3/ s capacity twin 75 kW auxiliary fan and 45 m3/ s capacity twin 110 kW auxiliary fan to control air recirculation and DPM. The results showed that if the drive intake airflow rate matches the fan capacity, air recirculation will occur even when the fan is located 10 m away from the crosscut entry. Results also showed that if the intake drive air quantity was greater than or equal to 150% of fan capacity, no recirculation was observed when the twin 75 kW fan location was at least 5 m and the twin 110 kW fan location was at least 10 m away from the dead-end crosscut access.

Oct 18, 2022

By Anna Gustafson, Sohail Manzoor, Håkan Schunnesson

Sublevel caving operation relies on the estimation of ore grade at drawpoints, as the mine management uses grade to decide whether the material at a certain ring should be loaded or abandoned. Grade is estimated in various ways, including visual estimation, density-based calculation, and sampling and assay methods. The grade estimation at the world’s two largest underground iron ore mines owned by LKAB in northern Sweden is based on the density difference between ore and waste. The calculations assume a constant swell factor, a theoretical fill of 100%, and a linear relationship between bucket weight and material grade. This study evaluated these assumptions in detail based on the loading data for 12,237 buckets and concluded that the method has some shortcomings which render the assumptions invalid. Further research is required to deal with these shortcomings to improve estimation of the material grade.

Oct 17, 2022

By Aimee A. Woolsey

Enterprise Unmanned Traffic Management is a holistic system concept evolving from technological developments in radio frequency where dynamic tracking can be added into current and emerging platforms. This is done through inexpensive RF sensors capable of real-time and cooperative, non-GPS tracking enabling digital visualization of assets, including unmanned aerial systems (UAS). The RF sensors are low size, weight, and power (SWaP), creating efficiencies in energy and material consumption while transmitting positions in real-time and at long ranges. Multiple UAS and other unmanned vehicles can be visualized for risk mitigation in operations,

Oct 17, 2022

By Roberto Fustos, Gonzalo Nelis, Víctor Sanhueza, René Gómez

Hang-ups are a challenging operational problem in block caving mines. They interrupt ore flow and imply hang-up removal activities, which take time, increase operational costs, and involve safety risks for workers. In block caving, the number of hangup events of mechanical arches that appear in the drawbell could be decreased if the drawbell geometry is adequately designed based on the expected rock fragmentation. Here, we compile and analyze hang-ups reported in several block caving mines to evaluate the impact of drawbell geometry, rock size, and vertical load on hang-up frequency at the mine scale. Results show that the ratios between drawbell length and d80 (dL/d80), between drawbell width and d80 (dW/d80), between drawbell volume and rock volume (VDB/VP), and vertical stress are critical parameters that define hang-up frequency. These findings confirm previous experimental studies, where a decrease in hang-up events is associated with an increase in these ratios. Additionally, these outcomes are used in a support vector machine algorithm to define categories of hang-up frequency. The results of this classification algorithm are presented in diagrams, which can be used to estimate the hang-up frequency in block caving projects.

Oct 15, 2022

By Shiwei Wang, Ziwen Li, Chenhu Zhang, Peng Chen, Chengyong Wang

Accurate prediction of the partition coefficients in coal gravity separation is key to improving the preparation efficiency of coal and promoting its clean utilization. In China, the approximate formula method (AFM) has been applied to the calculation of coal gravity separation partition coefficients for decades, but its accuracy is limited. To improve the accuracy of the predicted partition coefficients, and thus the product yield of coal preparation plants, the present study proposes a modified hyperbolic tangent model to derive direct calculation formulas for the heavy medium and water medium separation partition coefficients. Four groups of coal samples were used to verify the accuracy of the direct formulas, and their predictions were compared with those of the AFM. The results showed that the partition coefficients and partition curves predicted by the direct formulas were closer to the actual values than those predicted by the AFM. Further, when the cleaned coal ash content was basically the same, the cleaned coal yield predicted by the direct formula was lower than that predicted by the AFM, and was also closer to the actual value. These results demonstrate that the direct formula produces more accurate results compared to the conventional AFM. As this formula has a reasonable theoretical basis, is simple to apply, and produces accurate results, it is expected to help improve the design and management level of coal preparation plants.

Oct 15, 2022

By Justin Srednicki, Chenming Zhou

Ambient electromagnetic (EM) noise (natural or manmade) is a major limiting factor for the design and operation of many electronic devices, including through-the-earth (TTE) communications and tracking systems. Extensive studies on EM noise were conducted by the US Bureau of Mines in the 1970s and 1980s. Changes in the design and operation of electrical equipment since then, however, have resulted in changes in the EM noise environment. This paper reviews past research on surveying EM noise in the extremely low-frequency (ELF) and very-low-frequency (VLF) bands, which are the operating bands for TTE systems, and introduces a new battery-powered, rugged, portable measurement system for surveying EM noise in mining environments. Examples of surveyed EM noise measurement results in and above an active underground coal mine, using the new system, are presented in terms of absolute magnetic field strength levels. A new metric, average noise level (ANL), is introduced to characterize the noise level relative to a particular frequency band for a specific location. It is found that EM noise in mining environments varies significantly with time and location. EM noise levels at frequencies of 30 Hz that shifted from power harmonics (e.g., 90, 150, 210, 270 Hz) are relatively low and their variation with time can be statistically modeled by a Gaussian distribution. The conclusions and findings presented in this paper can help better design and operate TTE communications and tracking systems in underground mines.

Oct 14, 2022

By Congcong Chen, Bo Ma

When assessing the safety of a tailings dam, the constant weight method (CWM) is one of the most commonly used methods. However, when the evaluation indicator value suggests serious defects, the evaluation value is often inconsistent with the actual situation. To address this issue, the variable weight method (VWM) is introduced to assess the safety of the tailings dam. Initially, a three-layer indicator system for dam failure safety assessment is built, and individual indicator values are divided into four grades. Then, an appropriate state variable weight function is constructed and relevant parameters are determined. Finally, a case study is illustrated to verify the effectiveness of the model. The assessment results of the VWM more closely represent the actual situation than that of the CWM, which is more helpful for decision makers and technicians to take scientific and reasonable precautionary measures, thereby improving the safety management of the tailings pond.

Oct 8, 2022

By Xiaodong Yu, Jinxia Zhang, Fusheng Niu, Hongmei Zhang

The three-dimensional (3D) fractal dimension is an important parameter to analyze the 3D structure and flocculation effect of the hematite flocs. In this work, the 3D fractal dimension of hematite flocs was predicted by establishing the particle swarm optimization (PSO) algorithm optimized with the back propagation (BP) neural network (PSO-BP). The proposed model considers four factors, namely, the flocculant quantity, flocculation time, stirring speed, and temperature, as the input parameters. We normalize the input data during the preprocessing stage. The BP neural network was optimized by using the PSO algorithm for realizing the 3D fractal dimension. The prediction accuracy and effectiveness of the model were evaluated. The experimental results showed that the predictions performed by the proposed PSO-BP neural network were better than that of BP neural network. In addition, the root mean square error (RMSE), mean squared relative error (MSRE), mean absolute error (MAE), and mean absolute relative error (MARE) of the proposed model are lower, compared with the errors of the BP network. Similarly, the measurement coefficient R2 of the proposed model is higher, compared with the BP network. The maximum absolute error of the model is 0.0772, the maximum relative error is 0.02405, and the regression coefficient r is 0.98592. These results showed that the proposed model has a good performance and high prediction accuracy. When verifying the practicability and the effectiveness of the proposed PSO-BP model, the prediction results of 10 groups of hematite flocculation experimental data under different conditions showed that the prediction value of the proposed PSO-BP model was closer to the ground truth as compared to the BP model. Therefore, the proposed model is suitable for predicting the 3D fractal dimension of hematite flocculation.

Oct 3, 2022

By Liming Yuan, Wei Tang, RICHARD THOMAS, JOHN SOLES, DAVOOD BAHRAMI

Mine equipment fires remain as one of the most concerning safety issues in the mining industry, and most equipment fires were caused by hot surface ignitions. Detailed experimental investigations were conducted at the National Institute for Occupational Safety and Health’s (NIOSH) Pittsburgh Mining Research Division on hot surface ignition of liquid fuels under ventilation in a mining environment. Three types of metal surface materials (stainless steel, cast iron and carbon steel), three types of liquids (diesel fuel, hydraulic fluid and engine oil) and four air ventilation speeds (0, 0.5, 1.5 and 3 m/s) were used to study the hot surface ignition probability under these conditions. Visual observation and thermocouples attached on the metal surface were used to indicate the hot surface ignition from the measured temperatures. Results show that the type of metal has a noticeable effect on the hot surface ignition, while ventilation speed has a mixed influence on ignition. Different types of liquid fuels also show different ranges of ignition temperatures. Results from this work can be used to help understand equipment mine fires and develop mitigation strategies.

Oct 1, 2022

By HONGWEI YANG, Lili Zhang

Copper slag is mainly used in cutting tools, abrasives, asphalt pavement, road construction, and in the production of concrete as an alternative to sand and cement [1]. As a renewable resource, only about 15-20 percent of the slag is used for these applications, and the dumping or disposal of surplus unused slag results in waste of a certain amount of usable metal in the feedstock [2]. In this work, the oxidation behavior of copper smelting slag under nonisothermal condition is studied using data obtained by the thermogravimetric (TG) method, and the kinetics parameters and reaction mechanism of oxidation are determined. It provides a theoretical basis for the comprehensive recovery of iron resources in slag and the selection of reasonable slag-making conditions.

Oct 1, 2022