Determination of the flotation characteristics of several Turkish bituminous coal seams in Zonguldak coal basin.

Ph.D. - Doctoral Progra

Hardgrove Grindability Index Estimation Using Neural Networks

In a previous study, different techniques for the estimation of coal HGI values were investigated (Özbayoğlu et.al, 2008). As continuation of that research, in this study a revised neural network methodology is used for estimating the HGI values using the same data from 163 sub-bituminous coals from Turkey. The parameter set used for estimating HGI consisted of moisture, ash, volatile matter and Rmax ratios. These 4 coal parameters were fed into different neural network topologies. The network parameters were optimized by genetic algorithms. The test results indicate that estimation rate was improved %10-15 over the previous results (Özbayoğlu et.al, 2008) by using this new parameter set and optimized neural network configurations

Comparison of Gross Calorific Value Estimation of Turkish Coals using Regression and Neural Networks Techniques

26th International Mineral Processing Congress, IMPC (2012 : New Delhi; India)Gross calorific value (GCV) of coals was estimated using artificial neural networks, linear and non- linear regression techniques. Proximate and ultimate analysis results were collected for 187 different coal samples. Different input data sets were compared, such as both proximate and ultimate analysis data, and only proximate analysis data and only ultimate analysis data. It was observed that the best results were obtained when both proximate analysis and ultimate analysis results were used for estimating the gross calorific value. When the performance of artificial neural networks and regression analysis techniques were compared, it was observed that both artificial neural networks and regression techniques were promisingly accurate in estimating gross calorific values. In general, most of the models estimated the gross calorific value within ±3% of the expected value

Türkiye'nin yüksek kükürt içerikli linyitlerinin kömür hazırlama yöntemleriyle kükürtten arındırılması

TÜBİTAK MAG Proje15.11.198

USE OF BORIC ACID AS A BINDER FOR BRIQUETTING SOME BORON MINE WASTES AND THEIR CALCINED PRODUCTS

In this study, boric acid as a binder for briquetting some boron mine wastes, such as colemanite and ulexite fines and calcined products, which do not meet the market specifications with respect to particle size, were investigated. Effects of water and binder contents, applied pressure, and curing and drying conditions on the briquette quality were evaluated in terms of mechanical strength, water-proofing characteristics and wearing resistance. The best briquettes were obtained at 62.4 MPa pressure (cured at ambient temperature for 24 h and dried at 105 C for 2 h). Only binder free briquettes of uncalcined ulexite gave satisfactory result. The briquette strength increased with an increase in the percentage of binder. The optimum binder content was found to be 5 % by weight for uncalcined ulexite and colemanite as well as calcined colemanite, but 10 To by weight for calcined ulexite. The water-proof briquettes of ulexite and calcined products of ulexite and colemanite fines could be produced. According to wearing resistance, ulexite and colemanite fines as well as calcined product of colemanite showed resistance to abrasion action during transportation and loading

The effect of synthesis and doping procedures on thermoluminescent response of lithium tetraborate

Lithium tetraborate has been a scientific focus since 1960s by the courtesy of the thermoluminescence property it possesses. Moreover, it is utilized in surface acoustic wave apparatuses, in sensor sector and in laser technology owing to its non-linear optical characteristics. For the uses in thermoluminescence dosimetry lithium tetraborate is activated by addition of a variety of metals as dopants

Flotasyonla şelitin kalsitten ayrılması

TÜBİTAK MAG-15.11.198