Static and dynamic corrosion behavior of SnO2-doped AZS slip cast refractory in SLS glass

The corrosion behavior of a tin IV oxide-doped AZS-refractory, subject to static and dynamic corrosion testing at 1370˚C in soda-lime-silica glass, was studied considering the effect of the microstructural features on corrosion. The refractory was synthesized by slip cast methods through reaction sintering of alumina and zircon raw materials using SnO₂ as a sintering agent. SnO₂ had a considerable influence in the enhanced alumina/zircon reaction sintering and the subsequently evolved microstructures of an interlocked Zr_(1-x)Sn_(x)O₂ solid solution reinforced alumina-mullite composite. The process kinetics of the refractory corrosion followed reasonably well the predicted dependence on the square root of angular velocity under forced convection corrosion. Glass chemical corrosion and erosion of the refractory, under static and dynamic glass conditions, respectively, revealed the Zr_(1-x)Sn_(x)O₂ solid solution-rich mullite matrix as providing the most corrosion resistance and glass compatibility.     

Improving Deep Attractor Network by BGRU and GMM for Speech Separation

Deep Attractor Network (DANet) is the state-of-the-art technique in speech separation field, which uses Bidirectional Long Short-Term Memory (BLSTM), but the complexity of the DANet model is very high. In this paper, a simplified and powerful DANet model is proposed using Bidirectional Gated neural network (BGRU) instead of BLSTM. The Gaussian Mixture Model (GMM) other than the k-means was applied in DANet as a clustering algorithm to reduce the complexity and increase the learning speed and accuracy. The metrics used in this paper are Signal to Distortion Ratio (SDR), Signal to Interference Ratio (SIR), Signal to Artifact Ratio (SAR), and Perceptual Evaluation Speech Quality (PESQ) score. Two speaker mixture datasets from TIMIT corpus were prepared to evaluate the proposed model, and the system achieved 12.3 dB and 2.94 for SDR and PESQ scores respectively, which were better than the original DANet model. Other improvements were 20.7% and 17.9% in the number of parameters and time training respectively. The model was applied on mixed Arabic speech signals and the results were better than that in English.     

Room temperature oxidation of acetone by ozone over alumina-supported manganese and cobalt mixed oxides

Volatile organic compounds (VOCs) are among the major sources of air pollution. Catalytic ozonation is an efficient process for removing VOCs at lower reaction temperature compared to catalytic oxidation. In this study, a series of alumina supported single and mixed manganese and cobalt oxides catalysts were used for ozonation of acetone at room temperature. The influence of augmenting the single Mn and Co catalysts were investigated on the performance and structure of the catalyst. The manganese and cobalt single and mixed oxides catalysts of the formula Mn10%-CoX and Co10%-MnX (where X= 0, 2.5%, 5%, or 10%) were prepared. It was found that addition of Mn and Co at lower loading levels (2.5% or 5%) to single metal oxide catalysts enhanced the catalytic activity. The mixed oxides catalysts of (Mn10%-Co2.5%) and (Mn10%-Co5%) led to acetone conversion of about 84%. It is concluded that lower oxidation state of the secondary metal improves ozone decomposition and oxidation of acetone.     

Kinetics and Mechanism of Low-Grade Manganese Ore Reduction by Natural Gas

Metallurgical and Materials Transactions B - The calcination and the reduction behaviors of a low-grade manganese ore by methane was studied at 973 K to 1273 K by several techniques. The onset...     

An experimental study of the synergistic effects of BMIM.BF4, BMIM.DCA and TEACl aqueous solutions on methane hydrate formation

In this work, the effects of three ionic liquids (ILs), namely, 1-butyl-3-methylimidazolium tetrafluoroborate, 1-butyl-3-methylimidazolium dicyanamide and tetraethyl-ammonium chloride, on methane hydrate formation and dissociation kinetic parameters were studied. The kinetic parameters including the initial rate of hydrate formation, hydrate stability at atmospheric pressure and hydrate storage capacity were evaluated. The experimental measurements were performed in an initial pressure range of 3.5–7.1 MPa. It was found that both of ILs with imidazolium-based cation increase the initial methane hydrate formation rate while the IL with ammonium-based cation leads to a decrease in the initial methane hydrate formation rate. It was also interpreted from the results that all of the three studied ILs decrease methane hydrate stability at atmospheric pressure and increase methane hydrate storage capacity. Finally, both of ILs with imidazolium-based cations were found to have higher impacts on decreasing hydrate stability at atmospheric pressure and increasing the methane hydrate storage capacity than the applied IL with ammonium-based cation.     

An experimental study of the synergistic effects of BMIM-BF_4,BMIM-DCA and TEACI aqueous solutions on methane hydrate formation

In this work, the effects of three ionic liquids(ILs), namely, 1-butyl-3-methylimidazolium tetrafluoroborate, 1-butyl-3-methylimidazolium dicyanamide and tetraethyl-ammonium chloride, on methane hydrate formation and dissociation kinetic parameters were studied. The kinetic parameters including the initial rate of hydrate formation, hydrate stability at atmospheric pressure and hydrate storage capacity were evaluated. The experimental measurements were performed in an initial pressure range of 3.5-7.1 MPa. It was found that both of ILs with imidazolium-based cation increase the initial methane hydrate formation rate while the IL with ammonium-based cation leads to a decrease in the initial methane hydrate formation rate. It was also interpreted from the results that all of the three studied ILs decrease methane hydrate stability at atmospheric pressure and increase methane hydrate storage capacity. Finally, both of ILs with imidazolium-based cations were found to have higher impacts on decreasing hydrate stability at atmospheric pressure and increasing the methane hydrate storage capacity than the applied IL with ammonium-based cation.     

Energy efficiency optimization of one-way and two-way DF relaying considering circuit power

In this paper, the energy efficiency (EE) of a decode and forward (DF) relay system is studied, where two sources communicate through a half-duplex relay node in one-way and two-way relaying strategies. Both the circuitry power and the transmission power of all nodes are taken into consideration. In addition, three different coding schemes for two-way DF relaying strategy with two phases and two-way DF relaying with three phases are considered. The aim is to maximize the EE of the system for a constant spectral efficiency (SE). For this purpose, the transmission time and the transmission power of each node are optimized. Simulations are used to compare the EE–SE curve of different DF strategies with one-way and two-way amplify and forward (AF) strategies and direct transmission (DT), to find the best energy efficient strategy in different SE conditions. Analytical and simulation results demonstrate that in low SE conditions, DF relaying strategies are more energy efficient compared to that of AF strategies and DT. However, in high SE conditions, the EE of two-way AF relaying and DT strategy outperform some of the DF relaying strategies. In simulations, the impact of different circuitry power and different channel conditions on the EE–SE curves are also investigated.     

CFD and artificial neural network modeling of two-phase flow pressure drop

A large number of experiments in a 2 cm diameter and 6 m length tube were carried out in order to study the two-phase flow regimes and pressure drops in it. The two-phase flow in the experimental tube was modeled using commercial CFD code, Fluent 6.2. An Artificial Neural Network (ANN) with three inputs including gas and liquid velocities and tube slope was designed and trained to predict average pressure drop across the tube. The comparison between CFD and ANN predictions of pressure drops with experimental measurements shows that the CFD results are more accurate than the ANN evaluations for new conditions.