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A. Bahrami; Y. Ghorbani; E. Gulcan; F. Kazemi; H. Kakaei; S. Farajzadeh
Abstract
Particle size distribution is an important parameter in flotation process, which affects the floatability and therefore the flotation kinetics. This study aims to investigate the effects of particle size distribution on flotation kinetics of bituminous coal. For this purpose, a series of batch flotation ...
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Particle size distribution is an important parameter in flotation process, which affects the floatability and therefore the flotation kinetics. This study aims to investigate the effects of particle size distribution on flotation kinetics of bituminous coal. For this purpose, a series of batch flotation experiments were conducted in rougher stage, and concentrates were collected in different time periods. Then particle size distribution for each concentrate was determined. Five flotation kinetic models were applied for the modeling of data obtained from the flotation tests using MATLAB (Matrix Laboratory) software. The relationship between flotation rate constant, maximum combustible recovery and particle size were studied. The results show that the maximum flotation combustible recovery and flotation rate are obtained with an intermediate particle size (-250 +106 μm). Results of flotation tests fitted well to all five kinetic models. It is found that the first - order model with rectangular distribution of floatability, provides the best fit to the experimental data obtained from the flotation processes among the tested models.
Full length
N. Yavari; M. Poorabdollah; L. Rajabi
Abstract
In this study, unmodified graphite and graphite modified with a silane agent were used to ameliorate the thermal conductivity coefficient and dynamical properties of unsaturated polyester resin. The effect of unmodified graphite and modified graphite addition on thermal conductivity coefficient and dynamical ...
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In this study, unmodified graphite and graphite modified with a silane agent were used to ameliorate the thermal conductivity coefficient and dynamical properties of unsaturated polyester resin. The effect of unmodified graphite and modified graphite addition on thermal conductivity coefficient and dynamical properties of unsaturated polyester resin in the graphite amounts of 0.02% and 0.3% by weight were studied using solid thermal conductivity measuring device and DMA test. The results showed that the silane modifier can help to create strong covalent bonds between graphite particles and unsaturated polyester resin network and cause changes in thermal and dynamic properties compared to unmodified graphite particles. Adding 0.3% of the weight of the unmodified graphite to the unsaturated polyester resin resulted in a 7% raise in the storage modulus in the glassy region. However, adding the same amount of graphite modified using the silane agent increased the storage module by 33% in the glassy region. Silane modifier caused better dispersion of graphite particles in the resin structure. Superior dispersion of graphite particles caused more interaction between graphite particles and resin network, which significantly increased the modulus of unsaturated polyester resin. In contrast, better dispersion of graphite particles because of the presence of silane agent increased the thermal resistance at the surface of graphite particles, which reduced the thermal conductivity coefficient compared to unmodified graphite.
Full length
M. Cheraghipoor; M. Zakeri
Abstract
Pearlescent pigments are a variety of pigments that can generate an optical pleasant appearance in the system because of the ability of easy parallel orientation of a large number of platelet-like particles. In the present work, the green pearlescent pigments based on mica (biotite) and mica-titania ...
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Pearlescent pigments are a variety of pigments that can generate an optical pleasant appearance in the system because of the ability of easy parallel orientation of a large number of platelet-like particles. In the present work, the green pearlescent pigments based on mica (biotite) and mica-titania flakes covered with a thin film of nickel oxide were prepared with novel methods via the homogeneous precipitation of nickel acetate with sodium / potassium hydroxide, and in the presence of mica (biotite), titania, ammonium molybdate or mica-titania flakes. The synthesized pigments were characterized by means of X-ray diffractometery (XRD), Thermal Gravimetric Analysis (TGA), Differential Scanning Calorimetry (DSC) and X-Ray fluorescence (XRF) analyses. By comparing the XRD pattern of synthesized pigments with the mica base pattern, it is clear that the structure of the support does not change due to the layering on these bases. As these layers are hydroxide, oxide and chloride compounds. The XRF analysis shows that the nickel compound is layered well on the mica at 8.823%. The quantity and quality of the produced pigments by methods 1 and 2 were approximately the same. Consequently, due to commercial savings, method 1 was recommended for the preparation of the metallic pearl pigments and mica was known as the best support for the production of the pearlescent pigments by the introduced methods. Furthermore, TGA/DSC curve showed that the introduced pigments were stable up to 200 ˚C. The results showed good chemical resistance and pearl luster effects for the produced pigments.
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R. Beigzadeh; R. Ozairy
Abstract
The artificial neural network (ANN) approach was applied to develop simple correlations for predicting the thermal conductivity of nitrogen-methane and carbon dioxide-methane mixtures. The genetic algorithm method was used to obtain global optimum parameters (weights and biases) of the ANNs. The methane ...
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The artificial neural network (ANN) approach was applied to develop simple correlations for predicting the thermal conductivity of nitrogen-methane and carbon dioxide-methane mixtures. The genetic algorithm method was used to obtain global optimum parameters (weights and biases) of the ANNs. The methane mole fraction, temperature, pressure, and density as effective parameters on thermal conductivity were network input variables. 171 and 180 data points related to the nitrogen-methane and carbon dioxide-methane gas mixtures, respectively, divided to test and train datasets. Simple correlations were obtained due to the small number of optimal neurons in the ANN structures. The mean relative errors of 0.206% and 0.199% for the testing dataset indicate the high accuracy and validation of the correlations. The work indicates that artificial intelligence approaches are very useful for thermal conductivity modeling in natural gases. A sensitivity analysis was performed on all input variables that indicates that the gas mixture density has the greatest impact on the thermal conductivity.
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H. Rezaei; S. Ovaysi; M. Rahimi
Abstract
The objective of the investigation was to mathematically correlate the behavior of a supersonic superheated steam flow inside a Laval nozzle, against the decision parameters. The decision parameters are the inlet temperature ranging from 374.3 K to 504.3 K and the inlet pressure from 40050.14 Pa to 133375.7 ...
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The objective of the investigation was to mathematically correlate the behavior of a supersonic superheated steam flow inside a Laval nozzle, against the decision parameters. The decision parameters are the inlet temperature ranging from 374.3 K to 504.3 K and the inlet pressure from 40050.14 Pa to 133375.7 Pa. Indeed, the outlet temperature, outlet pressure as well as the Mach number are mathematically correlated against the decision parameters. The numerical approach based on the Computational Fluid Dynamics (CFD) is selected to study the behavior of the supersonic superheated steam flow inside the nozzle. By examining the different temperature and pressure conditions of the inlet fluid, it was found that the closest distance from the starting point of condensation to the throat is at the highest pressure and lowest temperature. Conversely, the farthest distance from the starting point of condensation to the throat is at the lowest pressure and highest temperature. In addition, three mathematical correlations were developed. Due to the high accuracy of the mathematical correlations, the efficiency of the predictor models in predicting the outputs was proved.
Full length
M.H. Akbari; M. Rahimi; H.R. Karami
Abstract
Decreasing pressure losses in microtubes is an important subject, especially when increase in flow capacity is required. In the same pumping power, decreasing the pressure drops is coincides with increasing the fluid flow rate passing through a microtube. The current study aims to examine how the water ...
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Decreasing pressure losses in microtubes is an important subject, especially when increase in flow capacity is required. In the same pumping power, decreasing the pressure drops is coincides with increasing the fluid flow rate passing through a microtube. The current study aims to examine how the water pressure drop across a microtube can be affected by the addition of small concentrations of different drag-reducing polymeric agents. A kind of laminarization behaviour was found by the addition of the selected polymer to the turbulent flow. The effect of concentration of drag-reducing agent (DRA) on observed viscosity and drag values are reported. Moreover, the effects of different types of drag-reducing agents on friction factor are obtained at the best concentration in the range of examined concentrations. Under this condition amount of drag reduction percentage and increase in capacity of the flow were respectively 33% and 36%. The obtained results show that more drag reduction occurs at a higher flow rate for 20ppm of high molecular weight polyacrylamide.