Tailings Grade Research Articles

Influence of Grinding and Classification Circuit on the Performance of Iron Ore Beneficiation – A Plant Scale Study

ABSTRACT Process flowsheet has a greater effect on equipment performance and operating conditions. For this purpose, performance of two iron ore beneficiation plants with the same equipment and feed characteristics but different arrangements in the grinding and classification circuit has been investigated. The first difference between the two plants was the screening type of HPGR product. Wet screening in the second plant caused higher classification efficiency, decreasing the circulating load, removing the dust production during operation. Wet screening caused to increased the moisture of HPGR feed which helped in improving the lifetime of HPGR rolls by a protective layer on the surfaces of HPGR rolls and between studs. Furthermore, it led to a reduction of HPGR feed rate, roll speed, and operating pressure. The feed rate of Ball mill in the second plant is lower and it has a finer product. As a result, ball consumption and rejected materials from trommel screen was decreased and pulp lifters lifetime was increased. In the second plant as well as the first plant,, the same hydrocyclone overflow d80 was achieved under lower operating pressure and the larger vortex finder diameter but the wear rate of hydrocyclone’s internal parts has been approximately double. The iron grade of tailings in the second plant was lesser by 2% and the iron recovery noted to be higher by 2%. The energy consumption decreased by 2 kWh/t of the ground ore in the second plant. As a result, the second plant was considered to be more efficient.

ELM-Based AFL–SLFN Modeling and Multiscale Model-Modification Strategy for Online Prediction

Online prediction of key parameters (e.g., process indices) is essential in many industrial processes because online measurement is not available. Data-based modeling is widely used for parameter prediction. However, model mismatch usually occurs owing to the variation of the feed properties, which changes the process dynamics. The current neural network online prediction models usually use fixed activation functions, and it is not easy to perform dynamic modification. Therefore, a few methods are proposed here. Firstly, an extreme learning machine (ELM)-based single-layer feedforward neural network with activation-function learning (AFL–SLFN) is proposed. The activation functions of the ELM are adjusted to enhance the ELM network structure and accuracy. Then, a hybrid model with adaptive weights is established by using the AFL–SLFN as a sub-model, which improves the prediction accuracy. To track the process dynamics and maintain the generalization ability of the model, a multiscale model-modification strategy is proposed. Here, small-, medium-, and large-scale modification is performed in accordance with the degree and the causes of the decrease in model accuracy. In the small-scale modification, an improved just-in-time local modeling method is used to update the parameters of the hybrid model. In the medium-scale modification, an improved elementary effect (EE)-based Morris pruning method is proposed for optimizing the sub-model structure. Remodeling is adopted in the large-scale modification. Finally, a simulation using industrial process data for tailings grade prediction in a flotation process reveals that the proposed method has better performance than some state-of-the-art methods. The proposed method can achieve rapid online training and allows optimization of the model parameters and structure for improving the model accuracy.

Shape-weighted bubble size distribution based reagent predictive control for the antimony flotation process

Antimony flotation is a complicated industrial process with an unknown system structure. Manual manipulation is still widely used by observing the froth appearance, which relies on operators’ experience. Therefore, this paper proposes a reagent predictive control strategy for the antimony flotation process based on machine vision, which is an optional replacement of manual control. Froth image is a good indicator to reflect the working conditions of the process. A shape-weighted bubble size distribution (SWBSD) is developed to characterize the froth image feature. The SWBSD combines the bubble size and bubble shape, which differs from the separate use of froth features. Since lots of the froth images can be obtained, a random selection of an image from a froth video as the indicator of the working conditions is not advisable. A typical froth image selection method is proposed to choose the froth image which can best characterize the current working conditions. Due to the unknown system model, multi-output least square support vector regressor (LS-SVR) is used to predict the future image feature according to the current image feature and reagent dosages. Based on the above methods, predictive control technique is employed to calculate the optimal control inputs of the reagents. Simulations using the real-world production data verify the effectiveness of the proposed control strategy. In further, industrial experiments in the antimony flotation plant of China demonstrate that our control strategy improved the tracking performance and decreased the tailing grade, compared with the manual manipulation.

Beneficiation of copper ores based on high-density separation fluidized bed

Copper is a necessary resource for the development of society. During copper ore beneficiation, gangue minerals consume a lot of energy. A gas–solid separation fluidized bed has potential application in the enrichment of copper ore. In this paper, the separation and enrichment of copper ore using a high-density gas–solid fluidized bed were studied. The characteristics of copper ore, the distribution characteristics of crushing products, copper, and the occurrence characteristics of Pb in copper ore were investigated. The results show that more than 80% of copper is distributed at a density of +4.0 g/cm3, and Pb exists in the pyrite. The fluidization characteristics and material enrichment principle of high-density ferrosilicon powder were investigated. The results show that the fluidized density is in the range of 2.42–2.77 g/cm3, and the minimum density standard deviation is 0.04 g/cm3. Under the optimal sorting conditions, the ore grades of −10 mm, 10–20 mm, and 20–30 mm sizes increased to 1.57%, 1.79%, and 2.33%, respectively, and the tailings grade decreased to 0.24%, 0.55%, and 0.30%, respectively. Thus, a gas–solid separation fluidized bed can achieve efficient enrichment of copper.

State controllability of a froth flotation cell

Abstract The control goals for a froth flotation cell are to maintain a stable pulp level and maximise the separation between valuable minerals to the concentrate and gangue to the tailings. Only a limited set of manipulated variables are available to achieve a target concentrate grade and tailings grade for a specific pulp level. The froth flotation cell can be represented by a non-linear phenomenological state-space model. The states of the model are the concentration of minerals in the froth and the pulp, and the volume of liquid in the froth and pulp. A state controllability analysis of the model indicates that the states are controllable using air flow-rate, tailings flow-rate, and feed-rate as manipulated variables. Therefore, given these three manipulated variables, a controller should be able to maximise the separation between minerals in the concentrate and tailings, while maintaining a pulp level within acceptable bounds.

Leaching of a Tailings from Oxy-sulfur Copper Ore with Sulfuric Acid

In this paper, mineralogy and leaching comprehensive utilization of tailings from an oxy-sulfide copper ore were studied. Tailings grade was 0.526%, of which copper was primary free copper oxide. Malachite was not completely dissolved although it flake aggregate size was much larger than other minerals. When the tailings were ground again to a fineness of -0.074 mm 93.5%, the copper grade in the tailings could only be reduced to 0.489% after one roughing and two scavenging. It was difficult to effectively recover copper with conventional flotation methods. Under the pulp concentration of 33%, the pulp temperature of 45 °C and 55 °C, sulfuric acid dosage of 160 kg/t, leaching time of 0.5 h, immersion liquid contained copper 2.37 g/L, the leaching rate of 91.34% was obtained with acid leaching, which the copper tailings got effectively recycled.

A soft sensor based on case-based reasoning for iron ores flotation

ABSTRACTConcentrate grade and tailings grade are two vital parameter indexes in a flotation process. To detect the grade succinctly and continuously, a soft sensor based on case-based reasoning (CBR) is proposed. Historic production data is first switched into the form of a case. The case problem includes feed grade, raw ore grade, raw ore ferrous oxide content, raw ore magnetic iron content, target concentrate grade, target tailings grade, dosage of four kinds of reagents; the case solution includes concentrate grade and tailings grade. Simulation result shows that the CBR soft sensor has a higher accuracy and speed in forecasting both concentrate grade and tailings grade when compared with soft sensors supported by other algorithms. The application result in a Chinese iron core dressing mill indicates that the soft sensor presented by this paper causes no damage to people and it can forecast product quality in real-time.

The Optimized Design on Spodumene Recovery from Iron Tailings in Kangding,Sichuan

In this paper, a flotation that implementing desliming in anticipation aimed at comprehensively recycling lithium from iron tailings in Kangding, Sichuan is put forward. Component of the iron tailings mainly with mica, limonite and chlorite which can result the serious sliming easily. Spodumene as the only desired mineral, the average grade of iron tailings is 0.76% Li2O. After predesliming process, the combined modifying agent Na2CO3-NaOH is used to inhibit mica, and the Laboratory-made collector QA-7 served as the collector to recycling spodumene. The results indicated that, via the Design-expert8.0 software to optimize the dosage of the regulators, the optimal dosage of Na2CO3-NaOH and QA-7 are selected as 1700g/t and 800 g/t, respectively. Meanwhile, via the predesliming-one roughing-five cleaning-two scavenging and middlings back to the flowsheet in turn process, the Li2O concentrate grade reached 5.71% with a recovery of 75.78% after a closed circuit experiment. In addition to realizing comprehensive utilization of iron tailings, the treatment is also a technical reference for handling the similar secondary resource.

Data-Driven Flotation Industrial Process Operational Optimal Control Based on Reinforcement Learning

This paper studies the operational optimal control problem for the industrial flotation process, a key component in the mineral processing concentrator line. A new model-free data-driven method is developed here for real-time solution of this problem. A novel formulation is given for the optimal selection of the process control inputs that guarantees optimal tracking of the operational indices while maintaining the inputs within specified bounds. Proper tracking of prescribed operational indices, namely concentrate grade and tail grade, is essential in the proper economic operation of the flotation process. The difficulty in establishing an accurate mathematic model is overcome, and optimal controls are learned online in real time, using a novel form of reinforcement learning we call interleaved learning for online computation of the operational optimal control solution. Simulation experiments are provided to verify the effectiveness of the proposed interleaved learning method and to show that it performs significantly better than standard policy iteration and value iteration.

Adsorptive Recovery of Auro-Dicyanide Anions from Aqueous Solutions using Activated Carbon-Magnesium Oxide (C-MgO) Nanocomposite as Adsorbent

ABSTRACTThe reprocessing of tailings or gold mine waste dumps to extract gold has become an attractive proposition for mining houses worldwide because of the availability of gold which was not easily recovered using old technologies. This study seeks to exploit the novel properties of nanostructured materials in enhancing gold extraction from gold mine tailings. The beneficiation of slimes or tailings involved taking samples for mineralogical studies, synthesis of a novel adsorbent medium (nano C-MgO) prepared by using both chemical and mechano-synthesis methods, oxidative pre-treatment of flotation concentrates, cyanidation and final recovery of the precious metal from solution in a Carbon in Column (CIC) system. The nanocomposite adsorbent was studied by powder X-ray Diffraction (XRD) for structural analysis, Field Emission Scanning Electronic Microscopy (FESEM) for surface morphology, Energy-dispersive X-ray spectroscopy (EDX) for elemental analysis and Fourier Transform Infrared (FTIR) spectroscopy for chemical structure analysis. The Brunauer-Emmett-Teller (BET) Surface Area Analysis procedure was employed to determine the total specific surface area of the nano-adsorbent. Representative tailings samples of 100-500 g were obtained for different analytical investigations using a riffle splitter. The tailings grade was analysed using the Atomic Absorption Spectroscopy (AAS) technique and was found to be an average of 0.5 g/tonne. A comparative Pseudo-Equilibrium test showed that the novel C-MgO nano adsorbent had an average of 84% recovery against 70 % for convectional activated carbon. The average crystalline size of 4.5 -11nm for the majority of MgO nanoparticles was obtained using Debye-Scherrer formula. FESEM confirmed that nano MgO was porous in nature and highly agglomerated whilst EDX exhibited the successful synthesis of the nano-composite product. This work also shows that the nano-adsorbent presents a huge potential for application in the conventional processes for gold adsorption.

A hybrid approach to modeling the flotation process from the 'Veliki Krivelj' plant

The purpose of the flotation process control is optimization the concentrate grade and recovery, while maximizing profits. Consequently, the research into modeling and control of this process has always been an important area in control engineering practice. This paper presents the results of development and validation the predictive models, based on the ANFIS hybrid system. Models predict the values of copper concentrate and tailings grade as well as copper recovery in the flotation plant 'Veliki Krivelj'. The copper content in the feed ore, collector consumption in the rough flotation stage and consumption of frother, were selected as the independent variables. Other technical and technological parameters, relevant for the process of flotation concentration were considered constant. The results of the models validation have showed that the models provide the good predictions of changes in the copper concentrate grade, while the predictions of changes in the copper recovery and tailings grade are somewhat poorer.

A Simplified Ultrasound Comet Tail Grading Scoring to Assess Pulmonary Congestion in Patients with Heart Failure.

Ultrasound lung comets (ULCs) are a nonionizing bedside approach to assess extravascular lung water. We evaluated a protocol for grading ULC score to estimate pulmonary congestion in heart failure patients and investigated clinical and echocardiographic correlates of the ULC score. Ninety-three patients with congestive heart failure, admitted to the emergency department, underwent pulmonary ultrasound and echocardiography. A ULC score was obtained by summing the ULC scores of 7 zones of anterolateral chest scans. The results of ULC score were compared with echocardiographic results, the New York Heart Association (NYHA) functional classification, radiologic score, and N-terminal pro-b-type natriuretic peptide (NT-proBNP). Positive linear correlations were found between the 7-zone ULC score and the following: E/e′, systolic pulmonary artery pressure, severity of mitral regurgitation, left ventricular global longitudinal strain, NYHA functional classification, radiologic score, and NT-proBNP. However, there was no significant correlation between ULC score and left ventricular ejection fraction, left ventricle diameter, left ventricular volume, or left atrial volume. A multivariate analysis identified the E/e′, systolic pulmonary artery pressure, and radiologic score as the only independent variables associated with ULC score increase. The simplified 7-zone ULC score is a rapid and noninvasive method to assess lung congestion. Diastolic rather than systolic performance may be the most important determinant of the degree of lung congestion in patients with heart failure.

Biological Production of Copper Sulfide Concentrate from Flotation Tailings and Low Grade Ore

Flotation tailings are hazardous due to physical and chemical instability and are currently considered one of the main pollution concerns of mining industry. Most of these tailings are fine-grained residues with low copper content (0.1-0.8%) and include toxic compounds, such as heavy metals, arsenic, and flotation reagents, among others. Another hazard is the generation of acid mine drainage (AMD) due to biological oxidation of tailings. On the other hand, low-grade ore is challenging the mining industry to commercially produce copper.The main objective of this work was to assess the use of flotation tailings and low-grade ore to produce a biologically-produced copper sulfide, as a product for further pyrometallurgical or fine chemistry processing. Low-grade ore and flotation tailings were first agglomerated at different proportions and leaching tests were performed in 1m columns, using either industrial or synthetic raffinate solution. Then, the PLS solution obtained from the column tests was subjected to selective precipitation of copper by using biogenic hydrogen sulfide (H2S) generated by a mixed culture of neutrophilic sulfate reducing bacteria (SRB), enriched from sediments of Caracarani river (located at 4,600 m over sea level in northern Chile).Over 91% of the copper soluble present in the PLS was recovered as copper sulfide in 28 days, while ferrous iron, other metals and arsenic remained in solution. Analysis performed by XRD confirmed the presence of copper in the precipitate (58% as covellite). This work demonstrates the possibility to apply bioleaching and bio-precipitation technologies to treat tailings and low-grade copper ore to produce a high quality copper sulfide.

Selective Flocculation of Iron Ore Slimes: Results of Successful Pilot Plant Trials at Tata Steel, Noamundi

A significant portion of currently mined iron ores, that is, 15–20% of run of mine ore, typically ends up as slimes—a slurry of fine particles (<45 micron) with relatively higher alumina contents (7–15% Al2O3). The only viable option currently is to dispose these slimes in tailing ponds for water recovery and future use. Due to increasing demand for steel and rapid consumption of high grade ores, processing and utilization of these slimes has become an urgent necessity. Traditional gravity and magnetic separation is not very effective in the ultrafine size range (less than 45 microns) and hence most of the flowsheets have a desliming step ahead of gravity and magnetic separation. Selective dispersion—flocculation is commercially proven technology to accomplish efficient separation in this size range, provided appropriate selective reagents are available. Our earlier work in TRDDC laboratories has demonstrated that selective flocculation with starch and guar gum is sufficiently selective for the reduction of alumina contents and thus this process should be scaled up for the processing of alumina rich Indian iron ore slimes. TRDDC has also designed a portable set-up which can be used to run pilot plant trials in a continuous mode onsite in the mines. The successful pilot plant trials of a selective flocculation separation process were completed by us at Noamundi mines recently. The results of these plant trials, using a portable pilot plant set up, designed by TRDDC, are summarized in this paper. The slimes sample for these plant trials, was withdrawn from one of the slimes stream at the Tata Steel’s iron ore beneficiation plant at Noamundi mines. Though there was considerable variation in the grade and pulp density of the slimes sample, it was possible to produce a concentrate of consistent quality in a continuous mode. It was for example demonstrated that one can produce a concentrate assaying 65.3% Fe and 2.5% alumina with a yield of 80.4% from a relatively richer grade slime sample containing 60.3% Fe and 4.8% alumina. More importantly, the corresponding tails contained less than 39.7% Fe. For a leaner grade slime sample assaying 53.4% Fe and 7.3% alumina, the corresponding concentrate grade was 63.5% Fe and 3.1% alumina, tailings grade 35.7% Fe and the yield achieved during the plant trials was 63.5%.

Recovery improvement of coarse particles by stage addition of reagents in industrial copper flotation circuit

ABSTRACTObtaining high recovery in coarse particle size fractions has been always under investigation in recent years. In the present study, stage addition of chemical reagents is used to improve copper grade and recovery of coarse size fractions (i.e., >100 µm) at industrial rougher flotation cells. Due to the poor efficiency of primary grinding circuit, coarse particles were detected as predominate size fraction in rougher flotation feed. Sampling results from rougher tailings showed that 58% of precious copper minerals were distributed to size fraction of −105 + 297 µm. Stage addition of collectors including sodium isopropyl xanthate (Z11), dithiophosphate and mercaptobenzthiazole (Nascol-451), and xanthate-flomin (C-4132) and frothers as methyl isobutyl carbonyl (MIBC) and Aerofroth 65 (A65) were implemented to avoid losing of coarse valuable particles in rougher tailings. Three different patterns were given for stage additions as 75-25-0, 75-0-25, and 75-13-12. The results indicated that copper grade of tailings declined relatively 56% using optimized stage addition of reagents at the head of rougher banks (i.e., 75-13-12). In addition, copper recovery of rougher cells improved around 2%. Size by size analysis of copper recovery for the rougher cells revealed the significant effect of the stage addition of chemical reagents on recovery improvement of coarse particles.

Online hybrid modeling method with application for predicting Bauxite production indicators

In the bauxite flotation process, concentrate grade and tailings grade are key production indicators; however, they are difficult to measure online. It is also difficult to develop an effective mathematical model for the process because of the complex non-linear and uncertain relationship among the feed parameters (feed grade, pulp density, slurry particle size, etc.), froth features and production indicators. Therefore, an online hybrid modeling method is proposed by analyzing the multiple parameters that affect the production indicators. First, according to the correlation and redundancy in the feed and froth feature parameters, the kernel principle component analysis (KPCA) is used to reduce the number of the parameters. Then, a neutral network model of the regular extreme learning machine (RELM), which is based on wavelet function, is presented to predict these two indicators. To improve generalization capability and prediction accuracy, information entropy is used to distribute the weight of the two models based on their predicting error. At last, an on-line updating strategy of the hybrid model is constructed in order to investigate the influence of the working conditions. The proposed method is tested on the diasporic-bauxite flotation process and shows high predictive accuracy and generalization capability. It lays the foundation for optimal control of the operation parameters based on mineral grade in the flotation process.

Optimizing flotation bank performance through froth depth profiling: Revisited

This communication revisits previously reported results on froth depth profiling along a rougher flotation bank. The optimization problem is reformulated as to maximize the overall bank Cu recovery subject to a lower bound constraint on the overall Cu concentrate grade. This formulation differs from that originally proposed in Maldonado et al. (2007) where the sum of the squared Cu tailing grade of each cell group was minimized for a given target bank Cu concentrate grade. A semi-empirical steady-state mathematical model of a bank of cells previously validated using industrial flotation data from Los Pelambres mine in Chile was used to simulate the process. In order to improve resolution a genetic algorithm was implemented to search for the optimal froth depth profile as opposed to the discrete dynamic programming technique originally implemented. Results show that optimal froth depth profiling resulting from solving the reformulated optimization problem produces an increase in the overall bank recovery for a given target Cu concentrate grade compared to that obtained when solving the original formulation. Moreover, the resulting optimal mass-pull profile tends to be more balance in the first cells which partially agrees with recent observations.

Hybrid model predictive control for flotation plants

Development of control strategies for large-scale processes has led to formulate novel methodologies to consider the global performance of a plant, facilitating the design, validation and evaluation of more complex control strategies. This paper describes a hybrid dynamic simulator for a flotation circuit with one production line composed by one cell and two banks in series, calibrated with industrial data. This simulator allows to represent a real plant behavior, facilitating the process of extracting input–output data. A PieceWise AutoRegresive eXogenous (PWARX) system is obtained from simulated plant by applying identification techniques for different operating conditions. A Hybrid Model Predictive Control (HMPC) methodology based on PWARX models has been developed and evaluated showing a good performance. Simulation results show that the proposed methodology is suitable for modelling the behavior of a flotation process and its control stage by minimizing the tracking error in the final tail grade.

Adsorption Selectivity of Fatty Acid Collector by Synthetic Magnetite

Selective adsorption of collectors on mineral surface can directly impact the flotation separation performance. Mineral flotation tests indicated that reverse flotation of synthetic magnetite can only bring a 2 to 4 percent increase in the concentrate grade, tailings grade remains high. The amounts of commonly used fatty acid collector, such as sodium oleate, adsorbed onto mineral surface are measured with indirect measurement to investigate adsorption selectivity of fatty acid collectors by synthetic magnetite. Results showed a higher selectivity in collector adsorption for natural magnetite, with 38.25% difference in the average adsorption rate of sodium oleate between the valuable minerals and gangue, but a less selective adsorption of fatty acid collector onto artificial magnetite, with only 1% difference in the average adsorption rate between its valuable and gangue.

On the collection of valuable minerals along rougher flotation banks

The collection of valuable minerals along rougher flotation banks was evaluated using top-of-froth measurements, which consist of sampling the froth surface. Considering non-selective froths observed in rougher flotation circuits, it was found the top-of-froth grades were similar to the bubble load grades, which allowed for a direct estimation of the collected mineral characteristics (size distribution, mineralogy, and grade). Thus, the flotation process evolution can be characterized by analyzing the collection of valuable minerals by true flotation instead of the classical mass balances approach, which strongly depends on the reliability of the tailings grade data. In addition, comparison among different valuable minerals was observed without significant sampling disturbances caused by solid entrainment.It is expected the top-of-froth measurement will be a useful tool for evaluating the effect of operating variables such as pulp conditioning, air flowrate and solids percentage on the true collection process along a flotation bank.