Kinetics of zinc sulfide concentrate direct leaching in pilot plant scale and development of semi-empirical model

The direct leaching kinetics of an iron-poor zinc sulfide concentrate in the tubular reactor was examined. All tests were carried out in the pilot plant. To allow the execution of hydrostatic pressure condition, the slurry with ferrous sulfate and sulfuric acid solution was filled into a vertical tube (9 m in height) and air was blown from the bottom of the reactor. The effects of initial acid concentration, temperature, particle size, initial zinc sulfate concentration, pulp density and the concentration of Fe on the leaching kinetics were investigated. Results of the kinetic analysis indicate that direct leaching of zinc sulfide concentrate follows shrinking core model (SCM). This process was controlled by a chemical reaction with the apparent activation energy of 49.7 kJ/mol. Furthermore, a semi-empirical equation is obtained, showing that the order of the iron, sulfuric acid and zinc sulfate concentrations and particle radius are 0.982, 0.189, ?0.097 and ?0.992, respectively. Analysis of the unreacted and reacted sulfide particles by SEM–EDS shows that insensitive agitation in the reactor causes detachment of the sulfur layer from the particles surface in lower than 60% Zn conversion and lixiviant in the face with sphalerite particles.     

Application of Compressible Volume of Fluid Model in Simulating the Impact and Solidification of Hollow Spherical ZrO<Subscript>2</Subscript> Droplet on a Surface

Applications of hollow spherical particles in thermal spraying process have been developed in recent years, accompanied by attempts in the form of experimental and numerical studies to better understand the process of impact of a hollow droplet on a surface. During such process, volume and density of the trapped gas inside droplet change. The numerical models should be able to simulate such changes and their consequent effects. The aim of this study is to numerically simulate the impact of a hollow ZrO₂ droplet on a flat surface using the volume of fluid technique for compressible flows. An open-source, finite-volume-based CFD code was used to perform the simulations, where appropriate subprograms were added to handle the studied cases. Simulation results were compared with the available experimental data. Results showed that at high impact velocities (U ₀ > 100 m/s), the compression of trapped gas inside droplet played a significant role in the impact dynamics. In such velocities, the droplet splashed explosively. Compressibility effects result in a more porous splat, compared to the corresponding incompressible model. Moreover, the compressible model predicted a higher spread factor than the incompressible model, due to planetary structure of the splat.     

Drought Monitoring Using the Multivariate Standardized Precipitation Index (MSPI)

One major characteristic of the Standardized Precipitation Index (SPI) is its flexibility to be calculated in a variety of time scales and hence being aware of different types of droughts. However, various time scales may result in confusion of the water resources’ researchers, decision makers and users in identifying and specifying drought periods in a certain region. To solve this problem in this article, a multivariate approach has been utilized having the ability to aggregate a variety of the SPI time series into a new time series called the Multivariate Standardized Precipitation Index (MSPI). The MSPI is based on the principal components analysis (PCA) of the SPI time series in a certain location. Having specified the first principal component’s (PC₁’s) scores, the MSPI would be simply attained by dividing PC₁’s values by the monthly standard deviation. In this article, MSPI’s capability in depicting the variability of the SPI time series (in five ranges of time scales, including 3–6, 6–12, 3–12, 12–24, and 24–48 months) was studied at four weather stations representing the four different climates in Iran from the driest to the wettest climates. The results showed that the PC₁ is able to justify more than 74 % of the variability for the selected sets of the SPI time scales in the studied climates. Also, it became clear that the drought and wet severity classes monitored by MSPIs matched very satisfyingly to those of the five sets of the SPI time scales. Therefore, in cases where the aggregation time scales for calculating the SPI are not previously known, this study recommends the researchers use the MSPI.     

Multi- Objective Optimal Design of on- Demand Pressurized Irrigation Networks

In the context of water as an economic good, from the use of water, one can derive a value, which can be affected by the reliability of supply. On-demand irrigation systems provide valuable water to skilled farmers who have the capacity to maximize economic value of water. In this study, simultaneous optimization of on-demand irrigation network layout and pipe sizes is considered taking into account both investment and annual energy costs. The optimization problem is formulated as a problem of searching for the upstream head value, which minimizes the total cost (investment and energy costs) of the system. The investment and annual energy costs are obtained in two separate phases. Max–Min ant system (MMAS) algorithm is used to obtain the minimum cost design considering layout and pipe diameters of the network simultaneously. Clement methodology is used to determine flow rates of pipelines at the peak period of irrigation requirements. The applicability of the proposed method is showed by re-designing a real world example from literature.     

Prediction of carbon dioxide separation from gas mixtures in petroleum industries using the Levenberg–Marquardt algorithm

In this study, two mathematical models for hydrate formation process to separate carbon dioxide by a combination of two different kinds of organic and surfactant promoters are presented. Promoters such as sodium dodecyl sulfate, sodium dodecyl benzene sulfonate, and dodecyl trimethyl ammonium chloride as surfactant promoters; also, tetrahydrofuran, cyclopentane, 1,3-dioxolane, and 2-methyl tetrahydrofuran as organic promoters have been used in recent years. The results showed that a combination of 3000 ppm of surfactant promoters and 4 wt% organic promoters had the highest separation rate of carbon dioxide and; consequently, the investigated models were based on this optimum condition. As a matter of fact, by using these simulations the hydrate formation behavior was predicted with high accuracy; moreover, conducting consuming experiments is not essential anymore. To sum up, in the present research both Vandermonde matrix model and Levenberg-Marquardt algorithm were applied to predict the hydrate formation behavior; in addition, their results were precisely considered and validated with experimental data.     

Aspen plus simulation of heavy oil gasification in a fluidized bed gasifier

Gasification is a clean technology to convert fuels to high-quality syngas in presence of a gasifying agent. In this study, an Aspen Plus model of heavy oil gasification was developed to produce the hydrogen rich syngas. Effect of some parameters such as gasification temperature and steam/fuel ratio on the hydrogen yield and was investigated. Results showed that the temperature plays a major role in the process; higher temperatures produce the higher hydrogen content. It was also found that the operation under high steam/fuel ratio can cause a significant increase in the hydrogen yield. The modeling results were compared with the experimental data available in the literature and found to be in good agreement.     

NUMERICAL SIMULATION OF FLOW OVER TWO CIRCULAR CYLINDERS IN TANDEM ARRANGEMENT

In this article,the 2-D unsteady viscous flow around two circular cylinders in a tandem arrangement is numerically simulated in order to study the characteristics of the flow in both laminar and turbulent regimes.The method applied alternatively is based on the finite volume method on a Cartesian-staggered grid.The great source term technique is employed to identify the cylinders placed in the flow field.To apply the boundary conditions,the ghost-cell technique is used.The implemented computational method is firstly validated through simulation of laminar and turbulent flows around a fixed circular cylinder.Finally,the flow around two circular cylinders in a tandem arrangement is simulated and analyzed.The flow visualization parameters,the Strouhal numbers,and drag and lift coefficients are comprehensively presented and compared for different cases in order to reveal the effect of the Reynolds number and gap spacing on the behavior of the flow.The obtained results have shown two completely distinct flow characteristics in laminar and turbulent regimes.     

First-principles study of H2 adsorption on the pristine and oxidized (8,0) carbon nanotube

The effect of oxygen, hydrogen, and (oxygen + hydrogen) molecules adsorption on the structural and electrical properties of (8,0) carbon nanotube (CNT) are investigated through density functional theory. The obtained results indicate endothermical chemisorption of O₂ on the nanotube surface with a large binding energy of about 598 meV and a significant charge transfer of about 0.43 e per molecule. It is discussed that the O₂ chemisorption creates hole carries in the (8,0) carbon nanotube and thus increases the work function of the system. In the case of hydrogen molecule, a weak physisorption on the surface of CNT (∼−5 meV) is identified. The adsorption of H₂ on CNT is also accompanied by hole doping and increment of the work function of the CNT, while the charge transfer between CNT and H₂ is negligible. The band offsets in the H₂-CNT junction are calculated to examine and describe the observed hole doping in this system. The effect of oxygenation of CNT on hydrogen adsorption is also investigated and the most favorable adsorption configuration is found and the related adsorption energy is calculated. It is argued that the oxygenation of CNT enhances the physisorption of hydrogen molecules. It is shown that hydrogen molecule adsorption on the oxidized CNT cancels hole doping and hence decreases the work function of the system.     

New Approaches for Estimation of Monthly Rainfall Based on GEP-ARCH and ANN-ARCH Hybrid Models

Accurate estimation of rainfall has an important role in the optimal water resources management, as well as hydrological and climatological studies. In the present study, two novel types of hybrid models, namely gene expression programming-autoregressive conditional heteroscedasticity (GEP-ARCH) and artificial neural networks-autoregressive conditional heteroscedasticity (ANN-ARCH) are introduced to estimate monthly rainfall time series. To fulfill this purpose, five stations with various climatic conditions were selected in Iran. The lagged monthly rainfall data was utilized to develop the different GEP and ANN scenarios. The performance of proposed hybrid models was compared to the GEP and ANN models using root mean square error (RMSE) and coefficient of determination (R²). The results show that the proposed GEP-ARCH and ANN-ARCH models give a much better performance than the GEP and ANN in all of the studied stations with various climates. Furthermore, the ANN-ARCH model generally presents better performance in comparison with the GEP-ARCH model.