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Volume 59
- Volume 59 - No 4 pp. (December 2020)
- Volume 59 - No 3 pp. (September 2020)
- Volume 59 - No 2 pp. (June 2020)
- Volume 59 - No 1 pp. (March 2020)
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Volume 58
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Volume 57
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Volume 56
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Volume 55
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Volume 54
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Volume 53
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Volume 52
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Volume 51
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Volume 50
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Volume 49
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Volume 48
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Volume 47
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Volume 46
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Volume 45
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Volume 44
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Volume 43
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Volume 42
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Volume 41
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Volume 40
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Volume 39
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Volume 38
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Volume 37
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Volume 36
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Volume 35
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Volume 34
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Volume 33
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Volume 32
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Volume 31
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Volume 30
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Volume 29
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Volume 28
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Volume 27
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Volume 26
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Volume 25
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Volume 24
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Volume 23
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Volume 22
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Volume 21
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Volume 20
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Volume 19
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Volume 18
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Volume 17
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Volume 16
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Volume 15
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Volume 14
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Volume 13
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Volume 12
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Volume 11
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Volume 10
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Volume 9
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Volume 8
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Volume 7
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Volume 6
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Volume 5
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Volume 4
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Volume 3
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Volume 2
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Volume 1
- Volumes 1-60 (2021-1961)
Investigation of the Amenability of a Copper-Rich Refractory Gold Ore to Cyanide Leaching
DOI 10.30797/madencilik.843761
Deus Albert Msumange, Ersin Yener Yazıcı, Oktay Celep, Hacı Deveci
The production of gold from refractory gold ores has been increasing due to the exhaustion of free milling gold ores. The presence of cyanicides (e.g., copper minerals) and encapsulation of gold in minerals such as pyrite and arsenopyrite are common reasons for refractoriness of gold ores. In this study, the amenability of a copper-rich gold ore (108 g/t Au, 1.60% Cu) to cyanide leaching was investigated. Direct cyanide leaching of the ore showed that the gold extraction was very low by 18.4% over 24 h., indicating that the ore is highly refractory. Sulphuric acid pretreatment for the removal of acid-soluble copper was found to be not effective to achieve high gold extractions at the subsequent cyanide leaching. Leaching at high NaCN concentrations (1-8 g/L) yielded limited Au extractions of ≤47.2%. Ultra-fine grinding (UFG) (d80: 8-73 μm) as a pretreatment route followed by cyanide leaching also could provide Au recoveries of just below 54.1%. The findings showed that the ore is double-refractory and needs the employment of more effective pretreatment process(es) to achieve acceptable gold extractions (>90%) in subsequent cyanidation stage.
Investigation on Usage Possibilities of Gasification Plant Wood Waste and Sivas Kangal Lignite Coal in Dye Adsorption
DOI 10.30797/madencilik.843772
Ramazan Kırma, Musa Sarıkaya, Soner Top, Şükrü Uçkun, İrfan Timür
In this study, the usage possibilities of wood waste obtained from Gebze MDF and Particle Board Gasification Plant preliminary studies and Sivas Kangal lignite coal as absorbents were investigated. In this way, it was aimed both to evaluate the wastes and to prevent environmental pollution with materials that are cheaper and easier to obtain. The structure and surface properties of wood waste and coal samples crushed and ground to -75 μm size and used as adsorbent were investigated by XRD, SEM and BET analyses. In addition, samples have been characterized by elemental, ash, moisture, volatile matter and fixed carbon analyses. In the experiments, methylene blue (MM) with the formulation of C16H18CIN3S.xH2O was used. The effects of temperature, mixing time and concentration parameters on MM adsorption were investigated. Langmuir isotherms were created for different temperatures at optimum concentrations. As a result, it has been revealed that lignite coal and wood waste can be used as adsorbent. A 10 ppm MM for lignite coal and 3 ppm MM for wood waste were determined to be ideal concentrations for adsorption.
Usability of Control Charts to Monitor Variation of Quality Parameters in Coal-Fired Thermal Power Plants
DOI 10.30797/madencilik.845148
Ali Can Özdemir
During the production of electrical energy from coal-fired thermal power plants, calorific and unit power values are the most important indicators for evaluating the productivity of the process. These values are measured periodically, and the resulting measurements are monitored to detect root causes of variation that may occur in production process. As this application is currently performed by manual methods, the probability of obtaining incorrect results is quite high. This study aims to statistically analyze process control on the variation of quality parameters and detect root causes of unusual variations using Shewhart and cumulative sum control charts. For this purpose, the usability of these control charts was tested on AfÅŸin-Elbistan B thermal power plant. As a result, these charts identified fluctuations in the efficiency of generating electrical energy and unusual variations in the process. Furthermore, it is recommended that these control charts could be developed and applied in similar type of process.
Predicting the Modulus of Elasticity of Rock Salt Samples at Different Depths from Some Rock Properties
DOI 10.30797/madencilik.843801
Fatih Bayram, İlker Bektaşoğlu
The modulus of elasticity is used as the basic input parameter in the design and analysis of
rock engineering structure. The design and construction of underground caverns in salt domes
is important for rock engineering. It is necessary to determine the rock properties in order to
adjust the solution mining parameters applied during the design and construction of underground
caverns. In this study, the relationships between some physical, mechanical and physicochemical
properties of salt core samples taken from Tuz Gölü Basin and the modulus of elasticity were
investigated. Statistical studies were carried out to predict the modulus of elasticity from some rock properties. At the same time, prediction models for modulus of elasticity were developed based on the depth difference of salt samples. As a result, the developed statistical models are very successful in the general and depth dependent prediction of the modulus of elasticity. A predicted approach with high reliability in determining the modulus of elasticity required in the design and construction of underground caverns in Tuz Gölü Basin is provided with these statistical models.
Prediction of Blast Induced Ground Vibrations by Using Artificial Neural Networks
DOI 10.30797/madencilik.843834
Abdulkadir Karadoğan, Meriç Can Özyurt, Ülkü Kalaycı Şahinoğlu, Ümit Özer
In this study, artificial neural networks (ANN) were used as a tool for estimation of blast-induced vibrations. For this purpose, the blast shots carried out in a quarry in Istanbul were monitored and the blast-induced vibrations were recorded.
Peak Particle Velocities (PPV) and Scaled Distances (SD) of 24 events were recorded in the
first 12 shots, subjected to statistical analysis and the site-specific ground vibration propagation equation was obtained. This data set was also used to train an ANN model while SD was an input and PPV was an output; and a new model, that used to estimate blast-induced vibrations in the related field, was developed. Using the vibration propagation equation and the developed ANN model, blast-induced vibrations were estimated for 19 shots performed subsequently, and the results were compared with 37 recorded vibration data. It was seen that there was linear relationship with a high correlation between the values calculated with the equation and recorded data; and there was linear relationship with a higher correlation between outputs of ANN model and recorded data.