A three dimensional CFD simulation and optimization of direct DME synthesis in a fixed bed reactor

In this study, a comprehensive three-dimensional dynamic model was developed for simulating the flow behavior and catalytic coupling reactions for direct synthesis of dimethyl ether （DME） from syngas including CO2 in a fixed bed reactor at commercial scale under both adiabatic and isothermal conditions. For this purpose, a computational fluid dynamic （CFD） simulation was carried out through which the standard κ-ε model with 10% turbulence tolerations was implemented. At first, an adiabatic fixed bed reactor was simulated and the obtained results were compared with those of an equivalent commercial slurry reactor. Then the concentration and temperature profiles along the reactor were predicted. Consequently, the optimum temperature, pressure, hydrogen to carbon monoxide ratio in the feedstock and the reactor height under different operation conditions were determined. Finally, the results obtained from this three-dimensional dynamic model under appropriate industrial boundary conditions were compared with those of others available in literature to verify the model. Next, through changing the boundary conditions, the simulation was performed for an isothermal fixed bed reactor. Furthermore, it was revealed that, under isothermal conditions, the performed equilibrium simulations were done for a single phase system. Considering the simultaneous effects of temperature and pressure, the optimum operation conditions for the isothermal and adiabatic fixed bed reactors were investigated. The results of the H2＋CO conversions indicated that, under isothermal condition, higher conversion could be achieved, in compared with that under adiabatic conditions. Then, the effects of various operating parameters, including the pressure and temperature, of the reactor on the DME production were examined. Ultimately, the CFD modeling results generated in the present work showed reasonable agreement with previously obtained data available in the literature.     

An artificial neural-network model for impact properties in X70 pipeline steels

An artificial neural-network (ANN) model has been developed for the analysis and simulation of the correlation between the mechanical properties and composition and thermomechanical treatment parameters of high strength, low alloy steels. The input parameters of the model consist of alloy compositions (C, Si, Mn, P, S, Cu, Ni, Cr, Mo, Ti, V, Nb, Ca, Al, B) and tensile test results (yield strength, ultimate tensile strength, percentage elongation). The outputs of the ANN model include impact energy (?10 °C). The model can be used to calculate the properties of low alloy steels as a function of alloy composition and thermomechanical treatment variables. The current study achieved a good performance of the ANN model, and the results are in agreement with experimental knowledge.     

Electropolymerization of thionine as a stable film along with carbon nanotube for sensitive detection of tetracycline antibiotic drug

Iranian Polymer Journal - Herein, a simple, rapid, cost-effective and sensitive poly(thionine)-based electrochemical sensor is described to determine trace amounts of tetracycline. In the present...     

Experimental characterization of a novel balsa cored sandwich structure with fiber metal laminate skins

Iranian Polymer Journal - Balsa cored sandwich structures with fiber-reinforced polymer (FRP) skins are widely used to produce lightweight, high-stiffness and cost-effective structural components...     

Modeling of Pt-Sn/γ-Al2O3 deactivation in propane dehydrogenation with oxygenated additives

A reduction in catalyst activity with time-on-stream and formation of side products are the major problems associated with catalytic propane dehydrogenation. Coke formation on the catalyst surface is the most important cause for catalyst deactivation. Experiments have indicated that the presence of very small amounts of oxygenated additives such as water can reduce the amount of coke accumulated on the catalyst surface and enhance catalyst activity. Addition of water beyond an optimum level, however, would result in a loss of activity due to sintering of catalyst. Propane dehydrogenation over a Pt-Sn/γ-Al₂O₃ catalyst in the temperature range of 575 to 620 °C was investigated in the presence of small amounts of water added to the feed. A monolayer-multilayer mechanism was used to model the coke growth kinetics. Coke deposition and catalyst sintering were considered in a catalyst deactivation model to explain the observed optimum level in the amounts of water added to the feed. The model predictions for both propane conversion and coke formation with time-on-stream were in good agreement with experimental data.     

Selecting lighting system based on workers’ cognitive performance using fuzzy best–worst method and QUALIFLEX

Cognition, Technology & Work - The present study aimed to evaluate different illumination systems in the control room of a power plant and decide on the optimal illumination system in terms of...     

Effect of Thermal Cycling on Hardness and Impact Properties of Polymer Composites Reinforced by Basalt and Carbon Fibers

The polymer-matrix composites may be significantly affected by cyclic temperature changes. This study investigates the effects of thermal cycles on hardness and impact resistance of three types of phenolic-matrix composites, that is, phenolic resin reinforced with (1) woven basalt fibers, (2) woven carbon fibers and (3) hybrid of basalt and carbon fibers. The effect of thermal cycling on hardness and impact resistance was material-dependent. While the thermal cycling rapidly decreased the hardness of composites reinforced by carbon fibers, it gradually decreased the hardness of composites reinforced by basalt fibers. Yet, the Charpy impact energy of carbon/phenolic (CFP) and basalt/carbon/phenolic (BCFP) composites was not significantly affected by thermal cycles, the Charpy impact energy of basalt/phenolic (BFP) composites shows a sharp decline with increasing thermal cycling, and reaches a plateau after a certain cycles. Based on the results, the BFP composites was significantly harder than CFP and the composites containing carbon fibers in spite of demonstration of low impact resistance at primal cycles, possessed very gradual decline in impact resistance compared to BFP composites after the thermal cycling.     

Synthesis, characterization, and biological activities of organosoluble and thermally stable xanthone-based polyamides

A series of polyamides, poly (xanthone-amide)s (PXAs) were prepared by direct polycondensation of 2,7-diaminoxanthone with various available aliphatic and aromatic dicarboxylic acids. The monomer and all the PXAs were characterized by FT-IR, ¹H NMR and ¹³C NMR. The prepared polyamides showed inherent viscosities in the range of 0.41–0.68 dL g^?1 in NMP at 25 °C. The PXAs with low crystallinity were soluble in aprotic polar solvents such as DMF, NMP, DMSO, and DMAc at room temperature. These PXAs showed low glass transition temperatures (T _g) (200–310 °C) and high thermal stability, the 10 % weight loss temperature was up to 432 °C under nitrogen. These polymers exhibited strong UV–Vis absorption maxima at 301–316 nm in NMP solutions. Their photoluminescence showed fluorescence emission maxima around 433–444 and 503–521 nm for aliphatic and aromatic polyamides, respectively. The resulting polymers were analyzed for their antioxidant activities using DPPH assay and the antibacterial activities against some bacterial strains (S. aureus, B. subtilis, E. coli and P. aeruginosa). The results revealed that the antioxidant and antibacterial activities of PXAs were more than xanthone nucleus and used standard, respectively. It showed that these polymers can be used in pharmaceutical and food industries (food packaging).     

A total fatigue life model for the prediction of the R-ratio effects on fatigue crack growth of adhesively-bonded pultruded GFRP DCB joints

A new phenomenological fatigue crack growth formulation for the modeling and the prediction of the Mode I fatigue behavior of adhesively-bonded pultruded glass fiber-reinforced polymer double cantilever beam joints under different R-ratios is introduced. The established formulation is based on the total fatigue life concept, considering however the model parameters as functions of the R-ratio by fitting the existing experimental data under two to three different R-ratios. This model can subsequently be used for the derivation of fatigue crack growth curves under any different R-ratio, thus assisting the development of methodologies for the fatigue life prediction of a joint comprising adherends with the same material under realistic loading conditions. An extensive fatigue/fracture database has been derived, containing results of 28 Mode I fatigue experiments, to assist the model development and to validate its predictions. Comparison of the model predictions and experimental results proved the model’s validity.     

Optical sensor based on 1,3-di(2-methoxyphenyl)triazene for monitoring trace amounts of mercury(II) in water samples

A new optical sensor for highly sensitive and selective determination of mercury(II) ion in aqueous solutions is developed. The mercury sensing membrane was prepared by incorporating 1,3-di(2-methoxyphenyl)triazene (MPT) as chromoionophore in the plasticized PVC membrane containing tris(2-ethylhexyl)phosphate (TEHP) as plasticizer. The proposed sensor displays a wide linear range of 9.0 × 10^?10–2.5 × 10^?7 M with a low detection limit of 2.0 × 10^?10 M in aqueous solutions at pH 4.0. This sensor has a relatively fast response time of less than 5 min. In addition to high stability and reproducibility, it shows a unique selectivity towards Hg²⁺ ion with respect to common coexisting cations. The sensor can readily be regenerated by exposure to a solution of sodium iodide (0.01 M). The proposed optode was applied to the determination of Hg²⁺ in water samples.