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The verification efficiency and precision of copper ore grade has a great influence on copper ore mining. At present, the common method for the exploration of reserves often uses chemical analysis and identification, which have high costs, long cycles, and pollution risks but cannot realize the in situ determination of the copper grade. The existing scalar spectrometric techniques generally have limited accuracy. As a vector spectrum, polarization state information is sensitive to mineral particle distribution and composition, which is conducive to high-precision detection. Taking the visible-near infrared parallel polarization reflectance spectrum data and grade data of a copper mine in Xiaoyuan village, Huaining County, Anhui Province, China, as an example, the characteristics of the parallel polarization spectra of the copper mine were analyzed. The spectra were pretreated by first-order derivative transform and wavelet denoising, and the dimensions of wavelet denoising spectra, parallel polarization spectra, and first-order derivative spectra were also reduced by principal component analysis (PCA). Three, four, and eight principal components of the three types of spectra were selected as variables. Four machine learning models, the radial basis function (RBF), support vector machine (SVM), generalized regression neural network (GRNN), and partial least squares regression (PLSR), were selected to establish the PCA parallel polarization reflectance spectrum and copper grade prediction model. The accuracy of the model was evaluated by the determination coefficient (R2) and root mean square error (RMSE). The results show that, for parallel polarization spectra, first-order derivative spectra, and wavelet denoising spectra, the PCA-SVM model has better results, with R2 values of 0.911, 0.942, and 0.953 and RMSE values of 0.022, 0.019, and 0.017, respectively. This method can effectively reduce the redundancy of polarized hyperspectral data, has better model prediction ability, and provides a useful exploration for the grade analysis of hydrothermal copper deposits at meso-low temperatures.

The copper ore in Chilean copper porphyry deposits is often associated with molybdenum minerals. This copper–molybdenum (Cu–Mo) sulfide ore is generally mined from various locations in the mining site, thus, the mineral composition, oxidation degree, mineral particle size, and grade vary. Therefore, in the mining operation, it is common to blend the ores mined from various spots and then process them using flotation. In this study, the floatability of five types of Cu–Mo ores and the blending of these ores in seawater was investigated. The oxidation degree of these Cu–Mo ores was evaluated, and the correlation between flotation recovery and oxidation degree is presented. Furthermore, the flotation kinetics of each Cu–Mo ore were calculated based on a mineralogical analysis using mineral liberation analysis (MLA). A mineralogical prediction model was proposed to estimate the flotation behavior of blended Cu–Mo ore as a function of the flotation behavior of each Cu–Mo ore. The flotation results show that the recovery of copper and molybdenum decreased with the increasing copper oxidization degree. In addition, the recovery of blended ore can be predicted via the flotation rate equation, using the maximum recovery (Rmax) and flotation rate coefficient (k) determined from the flotation rate analysis of each ore before blending. It was found that Rmax and k of the respective minerals slightly decreased with increasing the degree of copper oxidation. Moreover, Rmax varied greatly depending on the mineral species. The total copper and molybdenum recovery were strongly affected by the degree of copper oxidation as the mineral fraction in the ore varied greatly depending upon the degree of oxidation.

Three factors were measured in the flotation process of copper ore: the copper grade in a concentrate (β), the copper grade in tailings (ϑ), and the recovery of copper in a concentrate (ε). The experiment was conducted by means of a Jameson cell. The factors influencing the quality of the process were the particle size (d), the flotation time (t), the type of collector (k), and the dosage of the collector (s). The considered vector function is then (β(d, t, k, s), ϑ(d, t, k, s), ε(d, t, k, s)). In this work, the optimization was based on determining the values of the adjustable factors (d, t, k, s). The goal was to obtain the possibly highest values of the functions β and ε (maximum) with the possibly lowest values of the function ϑ (minimum). To this end, taxonomic methods were applied. Thanks to the applied method, the optimum—with the adopted assumptions—was found. The presented methodology can be successfully applied in the search for the optima in a variety of technological processes.

The article presents a novel yielding mechanism, especially designed for the rock bolt support. Mechanical rock bolts with an expansion head and equipped with one, two, four and six dome bearing plates were tested in the laboratory conditions. Furthermore, in the Phase2D numerical program, five room and pillar widths were modeled. The main aim of numerical modeling was to determine the maximal range of the rock damage area and the total displacements in the expanded room. The models were made for a room and pillar method with a roof sag for copper ore deposits in the Legnica-Głog&oacute, w Copper District in Poland. Additionally, in the article a load model of the rock bolt support as a result of a geomechanical seismic event is presented. Based on the results of laboratory tests (load &ndash, displacement characteristics), the strain energy of the bolt support equipped with the yielding device in the form of dome bearing plates was determined and compared with the impact energy caused by predicted falling rock layers. Based on the laboratory tests, numerical modeling and mathematical dynamic model of rock bolt support, the dependence of the drop height and the corresponding impact energy for the expanded room was determined.

Blasting and fracking of rock in mines exposes fresh rock surfaces to the local water and microbial communities. This may lead to leaching of metals from the rock by chemical or biological means and can cause acidification of the water system in the mine, i.e., acid rock drainage (ARD). Failure to prevent leakage of metal contaminated mine water may be harmful for the environment, especially to the local groundwater. In the Rudna mine, Poland, an in situ bioleaching pilot test at approximately 1 km depth was performed in the H2020 BIOMOre project (Grant Agreement #642456). After the leaching stage, different methods for irreversible inhibition of acidophilic iron oxidizing microorganisms used for reoxidation of reduced iron in the leaching solution were tested and were shown to be effective. However, the potential of the natural mine water microbial communities to cause leaching of copper or acidification of the mine waters has not been tested. In this study, we set up a microcosm experiment simulating the exposure of freshly fractionated Kupferschiefer sandstone or black schist to two different chloride-rich water types in the Rudna mine. The pH of the microcosms water was measured over time. At the end of an 18-week incubation, the bacterial community was examined by high throughput sequencing and qPCR, and the presence of copper tolerant heterotrophic bacteria was tested by cultivation. The dissolution of copper into the chloride rich microcosm water was measured. The pH in the microcosms did not decrease over the time of incubation. The sandstone increased the number of bacteria in the microcosms with one or over two orders of magnitude compared to the original water. The bacterial communities in the two tested mine waters were diverse and similar despite the difference in salinity. The bacterial diversity was high but changed in the less saline water during the incubation. There was a high content of sulphate reducing bacteria in the original mine waters and in the microcosms, and their number increased during the incubation. No acidophilic iron oxidizers were detected, but in the microcosms containing the less saline water low numbers of Cu tolerant bacteria were detected. Copper to a concentration of up to 939 mg L−1 was leached from the rock also in the microbe-free negative controls, which was up to 2.4 times that leached in the biotic microcosms, indicating that the leaching was also abiotic, not only caused by bacteria.

The paper shows the preparation of the numerical models necessary for the simulation mapping of industrial-scale crushers of problematic material, such as copper ore with complex lithology. The crushers investigated in this work are located in the KGHM Polska Miedz S.A. copper ore processing plant. The complex ore consisting of sandstone, dolomite and shale is modeled using the Discrete Element Method (DEM) with Particle Replacement Model (PRM) that was chosen to simulate the crushing process. The article discusses the tests and calibration of material parameters and proceeds to test a breakage model in a laboratory-scale jaw crusher. The results are finally validated with the data from actual industrial-scale crushers and compared with the simulations. As an optimization option, the new shape of hammers is proposed and tested in a numerical environment. The performance of the newly designed hammers was examined using numerical methods. The numerical tests showed that the new design performed worse than the current solution. As a result, time and money were saved by avoiding industrial tests. In conclusion, the work shows how complex processes can be characterized in the numerical environment and used for further analysis.

In both aquatic and terrestrial environment, selenium contamination may exist at concentrations above the micronutrient limit. Since there is such a narrow bandwidth between which selenium concentration is acceptable, the health of the public may be at risk of selenium toxicity once the concentration increases beyond a threshold. Selenium contamination in an aqueous environment can occur due to anthropogenic activities and/or from natural sources. This study presents a review of the forms of selenium, inorganic and organic selenium contamination, mobilization, analytical methods for various forms of selenium and remediation strategies. The review also provides recent advances in removal methods for selenium from water including bioremediation, precipitation, coagulation, electrocoagulation, adsorption, nano-zerovalent iron, iron co-precipitation and other methods. A review of selenomethionine and selenocysteine removal strategy from industrial wastewaters is presented. Selenium resource recovery from copper ore processing has been discussed. Various analytical methods used for selenium and heavy metal analysis were compared. Importantly, existing knowledge gaps were identified and prospective areas for further research were recommended.

Ore retention bunkers and receiving bins are important for continuous operation of transport system in a mine. Although the designs of the bins used in the KGHM PM S.A. mines have undergone modifications, their operating principle has remained unchanged since their initial commissioning. Their operation entails many problems, which are caused by the durability and functionality of the entire structure. Preventive actions and research into directions for possible modernizations require the type of damage and its reasons to be identified in the first place. This article presents an evaluation of the documented types of damage and an analysis of the repair works performed for the entire population of the receiving bins operated in one mine. The comparative evaluation of the bin failure rate is here proposed to be performed with the use of a number-based failure indicator and of a mass indicator. The key problem identified in the research was the wear and tear on steel elements due to abrasive processes. The linings of the bin elements were observed to undergo intensive abrasive wear. This abrasive wear of the analyzed bin elements is influenced by a combination of factors, the most important of which include variable physical and mechanical properties of the copper ore.

This publication presents the results of laboratory tests of idler rolling resistance under operational loads. Operational loads are understood as radial and axial forces acting on the idler, with values corresponding to those that occur in the conditions of its operation in copper ore mines. Knowing the rolling resistance is important not only at the stage of conveyor design, selection of the drive power or calculations of the necessary belt strength, but also when improving and searching for new idler design solutions. The idlers adopted for this research were differentiated in terms of bearings and idler axial clearance. The investigations were carried out on a unique test stand designed and built by the authors. The construction of the stand enables simulating operational loads while measuring the rolling resistance. The test rig measures idler bearing losses and rolling drag, not belt indentation rolling resistance. The object of the research were &oslash, 133&times, 465 idlers, which are most commonly used in the raw materials industry. The results show the possibility of reducing the belt conveyor energy consumption by appropriate selection of the design features of the idler bearing unit.

Copper is an important national resource, which is widely used in various sectors of the national economy. The traditional detection of copper content in copper ore has the disadvantages of being time-consuming and high cost. Due to the many drawbacks of traditional detection methods, this paper proposes a new method for detecting copper content in copper ore, that is, through the spectral information of copper ore content detection method. First of all, we use chemical methods to analyze the copper content in a batch of copper ores, and accurately obtain the copper content in those ores. Then we do spectrometric tests on this batch of copper ore, and get accurate spectral data of copper ore. Based on the data obtained, we propose a new two hidden layer extreme learning machine algorithm with variable hidden layer nodes and use the regularization standard to constrain the extreme learning machine. Finally, the prediction model of copper content in copper ore is established by using the algorithm. Experiments show that this method of detecting copper ore content using spectral information is completely feasible, and the algorithm proposed in this paper can detect the copper content in copper ores faster and more accurately.

The possibility of metal removal from the real acid mine drainage (AMD) in the area of copper ore mines in the southeast Serbia, was investigated through a combination of neutralization and adsorption methods. This approach of metal removal from AMD includes a two-step neutralization method in the first phase, aiming to separate metals as sludge. The results of laboratory test revealed that more than 99 mass % of Fe is removed up to pH 4 and more than 99 mass % of Cu up to pH 7. Based on the results obtained in laboratory conditions, a test on a semi industrial plant was carried out. The two-step neutralization separately removed Fe and Cu at pH 4 and 7, respectively. Especially, the obtained sludge at pH 7 included 1.24 mass % of Cu, much higher than usual Cu ore. Chitosan was applied for dissolved Mn removal from treated AMD. After 24 h incubation, 70 mass % of Mn is removed from the treated AMD at pH 7.4. Mn concentration was reduced from approx. 35 mg L&minus, 1 to 5 mg L&minus, 1. These results have indicated that a combination of neutralization and adsorption methods could be used effectively for metal removal from real AMD.

Globally, copper, silver, and gold orebody grades have been dropping, and the mineralogy surrounding them has become more diversified and complex. The cyanidation process for gold production has remained dominant for over 130 years because of its selectivity and feasibility in the mining industry. For this reason, the industry has been adjusting its methods for the extraction of gold, by utilizing more efficient processes and technologies. Often, gold may be found in conjunction with copper and silver in ores and concentrates. Hence, the application of cyanide to these types of ores can present some difficulty, as the diversity of minerals found within these ores can cause the application of cyanidation to become more complicated. This paper outlines the practices, processes, and reagents proposed for the effective treatment of these ores. The primary purpose of this review paper is to present the hydrometallurgical processes that currently exist in the mining industry for the treatment of silver, copper, and gold ores, as well as concentrate treatments. In addition, this paper aims to present the most important challenges that the industry currently faces, so that future processes that are both more efficient and feasible may be established.

The paper presents a way of combining neural networks with evolutionary algorithms in order to find optimal parameters of the copper flotation enrichment process. The neural network was used in order to build a model describing the flotation process. The network learning was carried out with the use of samples from previous empirical measurements of the actual process. The model created in this way made it possible to find optimal parameters not only from among the measurement spaces, but also those that go beyond the measurements. Then, evolutionary algorithms were used in order to find optimal flotation parameters. The learned neural network previously described was used to calculate the criterion in the evolutionary algorithm.

This work is part of a project focused on the Somma&ndash, Vesuvius volcano and aimed at identifying Cu minerals related to mineralizing processes associated with magmatic activity in an active magmatic-hydrothermal system. A mineralogical survey was carried out on a set of samples represented by sublimates and fumarolic products from the collection of the Mineralogical Museum of the University of Naples Federico II (Italy). These samples are mainly related to most recent eruptive episodes of Vesuvius activity, from 1631 onward. Copper-bearing minerals were characterized, as well as associated minerals, by X-ray diffraction (XRD) scanning electron microscopy with energy dispersive X-ray spectroscopy (SEM-EDS). An investigation on the structural complexity of Cu-mineral assemblages with different temperature formations was also carried out using the TOPOS software package. The main copper phases are sulfates, followed by vanadates, hydroxyhalides, oxides, carbonates, silicates and finally, phosphates. New mineral occurrences for Vesuvius, both Cu-bearing and Cu-free, are described. Nevertheless, the fumarolic/alteration minerals at Vesuvius cannot be considered of economic relevance as a copper reservoir, this type of mineralizations are significant for copper crystal chemistry and for the knowledge of the mineralogical variants. The obtained datasets can be of interest for the knowledge of volcanic byproducts of copper ore deposits (i.e., porphyry copper systems) and of (base) metal segregation processes.