Improving flocculation and dewatering performance of iron tailings thickeners

Arjmand, Reza; Massinaei, M.; Behnamfard, Ali

doi:10.1016/j.jwpe.2019.100873

Cited by 45 publications

(24 citation statements)

References 25 publications

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“…The advantage of this algorithm is that it uses CNN to extract regional features, and uses the features of the minimum peripheral rectangle of the candidate area and the foreground part to train CNN [5], which achieves more accurate results than the original region alone. The figure 2.4 shows the edge contour of object A extracted by the edge detection algorithm in this paper.…”

Section: Area Classificationmentioning

confidence: 99%

“…There is a lack of research on the dissolution behavior of SiO 2 and other slag in China. SiO 2 is the main component of solid iron tailings in blast furnace slag [5]. It is important to study the melting law of SiO 2 at high temperature for promoting the development of iron and steel industry in China.…”

Section: Introductionmentioning

confidence: 99%

“…There are many processing methods have been proposed for studying blast furnace slag. The bottom filtration method (OCP) was mainly used in China [5]. The Imbafa method (INBA) was mostly used in European countries and the United States [6].…”

Section: Introductionmentioning

confidence: 99%

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Notice of Retraction: Perspective and Prediction of the Rule of High Temperature Melting of SiO₂ via Visual Analysis

Zhu

et al. 2020

IEEE Access

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This paper focuses on how to perspective the melting behavior of solid iron tailings in molten blast furnace slag and take a new non-contact visual analytical method to predict its melting law. The optimized convolution neural network (CNN) is used to track the moving target in charge coupled device (CCD) camera system efficiently and accurately, and the melting behavior of SiO 2 is described by coordinate translation transformation theory. Hierarchical agglomerative clustering (HAC) and delaunay triangulation were used to extract the characteristic parameters of the melting process of SiO 2. The prediction model of the melting rate of SiO 2 at high temperature was established by least square fitting (LSF) and dimensional analysis, and compared with the actual melting rate of SiO 2 obtained by experiments. The results show that the melting characteristics of SiO 2 at high temperature are in accord with certain function rule. The performance of optimized CNN in terms of processing time and accuracy is significantly improved, and the fusion rate prediction model of SiO 2 is verified by 100% accuracy. It provides theoretical support and model basis for the improvement of slag cotton preparation technology. INDEX TERMS Melting rate, target tracking, feature extraction, dimensional analysis, best match.

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Section: Area Classificationmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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Notice of Retraction: Perspective and Prediction of the Rule of High Temperature Melting of SiO₂ via Visual Analysis

Zhu

et al. 2020

IEEE Access

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“…of the tailing slurry in both static settlement test and dynamic thickening test. In terms of static settlement test, Zhu [15] studied the relation between tailing particle size and underflow concentration and found that the higher the content of fine particles in the tailings, the lower the underflow concentration; Grangeia et al and [16] Arjmand [17] et al have found that rapid tailing sedimentation can be achieved by selecting appropriate flocculant with proper dosage and the optimal tailing slurry concentration. Chen [18] used the Altman method to study the relation between settling time and the sedimentation height of the tailing slurry under different particle size conditions; Dong [19] sampled tailings from an iron mine, then studied the relation between the unit consumption of flocculant and the settling speed of this mine's tailing slurry under different tailing slurry concentrations, and then studied the relation between the unit consumption of flocculant and the ultimate underflow concentration under different tailing slurry concentrations; Wang et al [20] found that the tailing slurry can be magnetized to improve the sedimentation performance; Liyi et al [21] found that sound waves can improve the sedimentation performance of tailings.…”

Section: Introductionmentioning

confidence: 99%

Study on the Relation between Tailing Particle Size and Tailing Slurry Underflow Concentration

Zou¹,

Liu

2022

Advances in Civil Engineering

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In order to study the effect of the physical properties of tailings on the concentration of tailing slurry underflow, the median particle size, control particle size, and density of the tailings of 9 typical mines were measured. Besides, static settlement test and dynamic thickening test of the tailing slurry of these 9 mines were separately conducted. The test results show that the underflow concentration of the tailing slurry is unrelated to the tailing density but is related to the tailing particle size. The finer the tailing particle size, the lower the underflow concentration. Through the nondimensional regression analysis, 3 relation equations were obtained: number 1 relation equation between the median particle size of tailings and the underflow concentration in the static settlement test, number 2 relation equation between the control particle size of tailings and the change in concentration in the static settlement test, number 3 relation equation between the underflow concentration in the static settlement test and the underflow concentration in the dynamic thickening test under different overflow water solid content conditions. Comparing the calculation results with the test results, it is found that the relative error between the predicted value and the test value does not exceed 6.1%, which has proved that the relation equations derived are convenient and feasible. The underflow concentration of the deep cone thickener can be predicted by merely measuring the particle size of the tailings, which means that the relation equations are highly recommended for wider use and application.

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“…Owen et al [8] showed that the rake may break the honeycomb structure of aggregates under low shear in the compression zone, and the intensity and duration of the rake action were critical factors. Many researchers [6,[9][10][11][12][13] concluded that the shear stress introduced by raking can dramatically improve the thickener performance in bed density, but it is still not enough to release an amount of water trapped in aggregates. However, at a business unit of Rio Tinto, a 2 wt.…”

Section: Introductionmentioning

confidence: 99%

Effect of Ultrasonic Frequency on Thickener Performance

Li¹,

Liu²,

Wen³

et al. 2021

Advances in Materials Science and Engineering

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Gravity thickening is an important aspect to solve numerous environmental and safety problems that were created by tailings discharging at low solid concentrations. Furthermore, in order to efficiently facilitate the separation of released water and solid sediments, a continuous thickening system with ultrasonic equipment has been used to investigate the thickening performance of copper-mine tailings under different ultrasonic frequencies (16 kHz, 20 kHz, 22 kHz, 25 kHz, and 28 kHz). After freeze-drying treatment, the underflow samples are imaged using the scanning electron microscope (SEM); then, the structure of floc or aggregates in the SEM images is quantifiably analyzed using the software of Image J. Results show that the underflow concentration increases as the ultrasonic frequency increases and decreases afterwards. A linear logarithmic function can explain the relationship between underflow concentration and run time at a certain ultrasonic. The underflow concentration is maximized at 64.47 wt. % when the ultrasonic frequency is 22 kHz. Based on the analysis on the microstructure of underflow samples, the minimum pore average size and pore average fraction are obtained when the ultrasonic frequency is 22 kHz, implying that 22 kHz is the optimum ultrasonic frequency combining the results of the underflow concentration.

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Improving flocculation and dewatering performance of iron tailings thickeners

Cited by 45 publications

References 25 publications

Notice of Retraction: Perspective and Prediction of the Rule of High Temperature Melting of SiO₂ via Visual Analysis

Notice of Retraction: Perspective and Prediction of the Rule of High Temperature Melting of SiO₂ via Visual Analysis

Study on the Relation between Tailing Particle Size and Tailing Slurry Underflow Concentration

Effect of Ultrasonic Frequency on Thickener Performance

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