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Abstract
Tunnel boring machines are used for excavating a variety of soils and rocks for circular cross-section tunnels. Several published studies examined the role of rockmass in determining the cutting and advance rate of tunnel boring machines. A comprehensive review of literature was conducted to ascertain the influence of geological conditions on the performance of tunnel boring machines and revealed that different rock characteristics were used to define the tunnel boring machine performance. The progress of the tunnel boring machine was ascribed to the inherent properties of the rockmass, intact rock properties, and surrounding geological conditions. Several authors found that extreme geological conditions strongly influence the advance of the machine. The review revealed that joint spacing, angle between plane of weakness and tunnel axis, rock quality designation, and number of joint sets were the most important variables that influenced the advance rates of the tunnel boring machine. At least 12 intact rock variables were used to define tunnel boring machine performance with one to seven such variables used in combination. The compressive strength, tensile strength, and brittleness index emerged as most crucial intact properties. Rockmass classifications or indices of tunnel boring machine performance were used by different authors to predict their performance and even to define their selection methodology. Use of dynamic properties of rock/rockmass was identified as a grey area for future research by scientists.
Key words: Tunnel boring machine performance; Rock mass properties; Intact rock properties; Special conditions; Review.
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Abstract
Taking into account the existing demand for chromium concentrates, the extraction of chromium from technogenic formations of sludge storages of the tailings of chromium ore beneficiation is an important practical task. The comprehensive utilization of beneficiation sludge will increase the profitability of production and solve the environmental problems of the region. The importance of solving the problem of involving in processing tailings is connected not only with the environment but also with the need to increase the production of chromium. Modern gravity enrichment technologies make it possible to efficiently produce chromium concentrates from large and medium fractions of chromite-containing ores, while finely divided sludge is practically not extracted due to the difficulty of separating complex minerals into concentrates and waste rock. This paper presents the results of studies on the gravity processing of tailings. The technology includes the enrichment of the fine fraction -0.2+0 mm of tailings of the dressing plant of chromite-containing ores by gravity methods using a KNELSON centrifugal separator. In technology, the efficiency of the operation of gravity enrichment is provided by the preliminary activation of the fine fraction in a solution of sodium bicarbonate (NaHCO3). With gravitational enrichment, the total chromite concentrate was obtained containing 51.3% Cr2O3. The output of concentrate was 41.7%. The extraction of Cr2O3 in the concentrate was 68.1%.
Key words: Chromite-containing ore; Gravity concentration; Tailings; Concentrate.
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Abstract
The hydrometallurgical route of zinc hydroxide and synthesis of nanocrystalline ZnO is a particularly attractive method to recover oxidized lead and zinc from lead-zinc flotation tailings. In Turkey, lead-zinc complex/mixed ores along with high iron content are not suitable for conventional mineral processing methods and need hydrometallurgical treatments. Therefore, the control of iron during zinc processes is really important. In this study, hydrometallurgical process route for zinc recovery from Pb-Zn flotation tailings was investigated by considering the effects of H2SO4 concentration, leaching and roasting temperatures on the zinc dissolution considering the Eh-pH variations. The iron and zinc products were also individually examined by X-ray Diffraction (XRD), Scanning Electron Microscopy (SEM) and Atomic Force Microscopy (AFM) images in order to compare before and after leaching, precipitation and roasting steps. 83.1% Zn and 91.6% Cd leaching efficiencies were obtained from Pb-Zn flotation tailing particles with the size range of 50-110 nm from AFM image cross-sections, while lead and iron were not dissolved. Elemental sulfur started to form and produce a layer around the particles or a partially agglomerated particle in the size of 170 nm during the sulphuric acid leaching. However, majority of the particles was determined to be less than 20 microns, and AFM images showed that the size reduction between the leached and unleached particles was over 50%. Selective precipitations of iron and zinc in the form of hydroxide were performed in high recovery efficiencies of 90.1% and 99%, respectively. After the heat treatment, nanocrystalline zincite clusters of 96.6% purity were produced in the ZnO mineral form and nearly 13 nm in size. Zinc can be successfully recovered and a flotation tailings ore can be a good candidate for the production of high technology needs of nanocrystalline ZnO nanoparticles.
Key words: Pb-Zn ores; Leaching; Precipitation; Zinc oxide clusters; Zincite structure.
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Abstract
Production of sponge iron requires iron ore, coal, and dolomite. The quality of sponge iron is affected by particle size variation and moisture content of the feed materials. In the present work, image processing was used to detect both particle size and moisture variation of the feed materials on an online basis. Noise and signal irregularities in images were removed by image analysis through MATLAB. Continuous (online, every 30 minutes) images were taken over a coal bed which was moving on a conveyor belt. It was a challenge to determine the particle size distribution and surface moisture of coal online. The distribution of reflectivity of coal in the image varied according to the moisture content and particle size. It affected the intensity information of the image which was then used to predict the surface moisture content of the coal. The method is now being used successfully in a processing plant.
Key words: Image Processing; Machine Vision; Coal; Size distribution; Moisture content; Rotary Kiln.
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Abstract
The recent developments of steel and iron industries generated a huge consumption of iron ores which has attracted much attention for utilizing low-grade iron resources to satisfy this increasing demand. The present study focuses on the characterization and enrichment of the low-grade iron ores from Rouina deposit -Ain Defla-. Currently, the ore is used in the cement industry because
it is considered a low-grade iron ore. After the sampling process, a physico-chemical and mineralogical characterization was carried out and the results revealed that the sample consists of hematite, limonite and goethite as major opaque oxide minerals whereas silicates as well as clays form the gangue minerals in the sample. The average grade of FeTotal, SiO2 and Al2O3 contents in the raw material collected from the mine of the case study are 30.85%, 23.12% and 7.77% respectively. Processes involving combination of classification, washing and dry high-intensity magnetic separation were carried out to upgrade the low-grade iron ore sample to make it suitable as a marketable product. The sample was first ground and each closed size sieve fractions were subjected to washing followed by drying than dry high intensity magnetic separation and it was observed that limited upgradation is possible. As a result, it was possible to obtain a magnetic concentrate of 54.09% with a recovery degree of 89.30% and yield of 62.82% using a magnetic field intensity equal to 2.4 Tesla at the size fraction [-0.125 +0.063 mm].
Key words: Rouina; Iron ore; Sampling; Characterization; Washing; Magnetic separation.
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Abstract
Decision-makers are often being faced with imprecise and ambiguous data. In such circumstances, the use of extended Multiple-Criteria Decision-Making (MCDM) method is more appropriate than the use of other classic decision-making techniques. This paper develops an evaluation model based on the Technique for Order Performance by Similarity to Ideal Solution (TOPSIS)
to help the selection of the appropriate ore deposit for exploitation in a fuzzy environment. The applicability of the proposed model is demonstrated with a real case study involving four alternative ore deposits, seven evaluation criteria, and 3 decision-makers.
Key words: ore deposit selection, fuzzy TOPSIS, MCDM.
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