Iranian Journal of Chemical Engineering (IJChE)

Abstract This study simulated the production of bioethanol from mixed microalgae to the assess economic feasibility on an industrial scale. For the first time, the kinetic study of the chemical hydrolysis of mixed microalgae was carried out using the AQUASIM software. The chemical hydrolysis for the pretreatment of microalgae was carried out using H₂SO₄ (2.5%, 5%, 10% (v/v)), H₃PO₃ (2.5%, 5%, 10% (v/v)), and NaOH (1%, 2%, 4% (v/v)) at the different biomass concentrations (25 to 100 g/L) at the temperature of 121 ℃ for 70 min. Kinetic constants were calculated using experimental data and the AQUASIM software. It was found that the optimum yield of sugars, which was obtained, was about 93%. From the comparison of the values ​​of the reaction rate constant (k), it was observed that the hydrolysis rate ​​at 50 g/L by using H₂SO₄ 2.5% (v/v), is higher compared to 25, 75, and 100 g/L, and the higher reaction rate constant supports the faster hydrolysis of algal biomass. These kinetic constants were applied in simulating the process on an industrial scale using the SuperPro Designer software. Experimental and simulation results showed that 3.6 g/L of bioethanol is produced from the 9.3 g/L of glucose under optimal conditions. Also, simulation results using the SuperPro Designer software demonstrated that eliminating the algal biomass drying stage has the potential to save up to 713,000 $ in operational expenses.

Abstract Water and solid effective diffusivities and shrinkage were correlated for finite hollow cylinder-shaped apple samples during the candying operation in the osmotic solution. Experiments were conducted in the sucrose solution as an osmotic agent at different temperatures (i.e., 40, 50, and 60 °C) and at a constant concentration of 55 °Brix. The effective diffusivities of water and solid were calculated by fitting the water loss and solid uptake experimental data to Fick’s second law and fractional calculus method, considering the shrinkage of the samples during the candying process. The obtained results exhibited that the volume of the apples reduced linearly by increasing the water loss. For above conditions of the candying process, water effective diffusivities with Fick second law were determined in the range of 3.7×10−10 m2/s–8.73×10−10 m2/s, and those with fractional calculus method were in the range of 2.75×10−10 m2/s–6.98×10−10 m2/s. The results indicated that the coefficient of determination for the fractional calculus method was more than the coefficient of determination for the Fick model. The value of the empirical parameter α for the Non-Fickian diffusion model was always higher than unity, meaning that the dehydration process had a super-diffusive mechanism.

Abstract The high silica Mn-substituted MFI metallosilicate catalyst with Si/Al molar ratio of 220 and Si/Mn molar ratio of 50 was successfully synthesized by hydrothermal method. The catalyst sample was appropriately characterized by XRD, FE-SEM, EDX and BET techniques. The Mn-substituted MFI metallosilicate has not been reported as the potential catalyst for the methanol to propylene (MTP) reaction. The prepared catalyst was examined in the MTP reaction at the optimal operating conditions. Furthermore, for elucidating the flow field of the MTP fixed bed reactor, a three-dimensional (3D) reactor model was developed. A detailed reaction mechanism which was proposed for the MTP reaction over the Mn-impregnated MFI zeolite (Mn/H-ZSM-5) was properly employed. The reaction mechanism was integrated to a computational fluid dynamics (CFD) for simulating the kinetic, the energy equation and the hydrodynamics of the MTP process, simultaneously. The component distribution during proceeding of the MTP reaction was also simulated as a function of time on stream. The CFD modeling results were validated by the actual data which were obtained over the Mn-substituted MFI metallosilicate catalyst. With regard to the findings, the experimental data were in good agreement with the predicted values of the CFD modeling.

Abstract In this study a developed model has been used to evaluate the paper drying process and examine the pocket dryer conditions of a multi-cylinder fluting paper machine. The model has been developed based on the mass and energy balance relationships in which the heat of sorption and its variations with paper temperature and humidity changes have been taken into account. The applied model can be used to compute the drying parameters and analyze the pocket drying conditions. Furthermore, the effects of web tension on the heat transfer have been investigated. In the available operating range of the web tension, the overall mean heat transfer coefficient will be within 300-550 W/m2.K. The pocket air temperature was between 50 and 90 oC. The dew point temperature wasn’t close to the pocket air temperature and dew drop never happened during the dryer section. Based on the modeling result and using a novel technique, the maximum level for the exhaust air in the studied machine can be estimated to be 0.2 kg H2O/kg dry air. Result shows that increasing the exhaust humidity to the optimal level will lead to 4% reduction in the required energy and 20% rise in the heat recovery potential. Accordingly the specific heat consumption per evaporated water for the studied drying section can be reduced from 3.96 to 3.81 GJ per ton water.

Abstract Due to wide application of styrene for production of different materials, it is considered as an important product in industry. Therefore, optimizing styrene production conditions is of great importance in petrochemical industry. In this paper, styrene production reactors of Tabriz Petrochemical Complex are modeled using Artificial Neural Network (ANN) model and Adaptive Neuro Fuzzy Inference System (ANFIS). Comparison of two models revealed that the neural networks are more reliable. The process of design and evaluation of models are carried out using industrial data which show credibility of designed models. The neural networks are designed to predict the styrene output from reactors as a function of effective input parameters on the styrene production. Predictions of designed neural networks were used to study the effect of each variable, such as oxygen flow rate and steam oil ratio, on the amount of styrene produced. Also, the optimal values of effective variables for maximum production of styrene were obtained. Furthermore, in order to obtain accurate results, catalyst deactivation of styrene reactors has been modeled using Fuzzy Inference System. As a result, catalyst activity as a function of time is obtained.

Abstract This article describes kinetic modeling of the reduction of barium sulfate by methane based on experimental data obtained by thermogravimetric technique. The conversion- time data have been interpreted by using the grain model for gas-solid reactions and the effect of catalyst on the kinetic parameters has been elucidated. It was found that
zinc oxide acted as a fairly strong catalyst for the reaction, especially at higher temperatures. For example, at about 950°C the reaction rate constant was increased more than 8 times by using only 2 percent of zinc oxide. Orthogonal collocation method was used for solving coupled partial differential equations of gas-solid reaction. There is a good agreement between the experimental data and results obtained from simulation. This research offers a clean method for barium carbonate production with methane as a reducing agent, decreasing CO2 emission significantly. Also, a new process for converting sulfur dioxide to elemental sulfur by a cyclic process involving barium sulfide and barium sulfate has been proposed.