Nashrieh Shimi va Mohandesi Shimi Iran
Year:2012 | Volume:31 | Issue:2 (65)|Papers Count:9

N-(1, 3-Dimethylbutyl)-N'-phenyl-1, 4-phenylenediamine (Santoflex 6PPD) functions as a powerful antioxidant and antiozonant for natural and synthetic elastomeric compounds and as synthetic polymer stabilizer. Santo flex 6PPD provides protection against different forms of aging and fatigue degradation of flexible rubber components in both static and dynamic operation conditions at high temperature during storage and service operation is essential. In this research synthesis of this compound from 4-AminoDiPhenylAmine (4-ADPA) and Methyl Isobutyl Ketone (MIBK) in the presence of 5%Pt/C as catalyst with thermodynamic variables (temperature, pressure) and kinetic parameters (stirring speed, reaction time, and molar ratio) were examined with an oxidizer. At first, (4-nitrodiphenyl amine and -4-nitrosodiphenyi amine) were prepared by direct coupling of aniline and nitrobenzene under optimized molar ratio of hydrogen peroxide to moles nitrobenzene in the presence of a strong base. Then 4-ADPA was synthesized under hydrogen pressure about 200-220 psig at 80oC in the presence of 5%Pt/C as catalyst with efficiency increase about 10% and by product reduce compared to conventional methods. In the second step, 4-ADPA was reacted with Methyl Isobutyl Ketone (MIBK) under hydrogen pressure of about 800 psig and temperature of 170-175oC in the presence of 5% Pt/C catalyst Santo flex 6PPD was synthesized in 99% purity and the yield of reaction was 95% with efficiency increase about 3% in comparison with conventional methods. All of the synthesized compounds were characterized by FT-IR, 1HNMR, C.H.N and G. C. analysis.

The Degree of Deacetylation (DD) of chitosan plays a main role in its physical, chemical and biological properties. Hence, in this study, low-viscous, medium, and high (impure and improved) molecular weight chitosan were used to determine DD, using a simple and exact method, The DDs of chitosan were determined by the fourier transform infrared spectroscopy (Baseline-a and b) and linear potentiometric titration. Thie concluded results were compared using Root-Mean-Square Deviation (sRMSD) whereby an agreement between the linear potentiometric titration and fourier transform infrared spectroscopy (Baseline-a) were shown. In presented method, for purifying impurities and improving DD of the high molecular chitosan, DD was noticeably increased from 60.1 to 92.7 %. The analysis of chitosan's DD represented the raise of DD in the presence of the increase of viscosity and molecular weight of chitosan.

In this research, ZSM-5 zeolite with high ratio of Si to Al of 800 was synthesized to act as the catalyst for the conversion of Methanol to Propylene (MTP). Instead of tetra-propyl ammonium hydroxide, here, tetra-propyl ammonium bromide which is much cheaper was used as the template. The reaction was investigated in a fixed-bed flow reactor under the operating conditions of T=460oC, P= 1 atm, and WHSV=1 h-1. The obtained results with the synthesized catalysts were compared with those of a commercial catalyst. The catalysts were characterized using XRD, SEM, TPD, BET and ICP techniques. The obtained results indicated that the selectivity of methanol conversion to light olefins, including propylene is 54%. This value is significantly higher than the 40% selectivity obtained with the commercial catalyst. Aging and deactivation after 150 hours of reactor operation was less severe for the synthesized catalyst compared to the commercial catalyst.

In this paper, a steady-state model based on mass transfer for selective absorption of hydrogen sulfide gas in MethylDiEthanolAmine (MDEA) solution, in the packed absorption tower is presented. This model is able to predict the concentration and temperature profiles in gas and liquid phases for the (MDEA-H2S-CO2H2O) system. In order to predict the profile of CO2 concentration, the second-order kinetic constants of reaction between gas and MDEA solution was used. Also, among the existing kinetic data, the best one was selected. In addition, the effective parameters in obtaining these profiles and the maximum point of selectivity factor were examined in this model. In order to evaluate accuracy of proposed model, the results were compared with from a pilot plant test as well as using operating data from absorption packed tower of the gas sweetening unit of phases 4 and 5 of South Pars Gas Complex. The obtained results reveal an acceptable compatibility between experimental data and prediction of the presented model.

Although several methods have been proposed in design of multi-stream heat exchangers, but they often apply for constant physical properties. In this research, a new method is presented using the variation of physical properties with temperature as well as optimum pressure drops. Having indicated the dependency of specific heat capacity, viscosity, density and thermal conductivity on temperature variation, a set of temperature correction factors is defined for each stream. Calculating the correction factors for all streams will lead in finding an optimum DTmin in targeting stage as well as a reliable design based on effective pressure drops, which will guarantee the accuracy of results. Moreover, the optimum pressure drops are used by the optimum selection of fins for each stream in which the total annual cost of exchanger is minimized using genetic algorithm. Having applied the temperature correction factors in design of a multi-stream heat exchanger as case study, the results showed a 27.3% and 13.5% reduction in exchanger volume and total annual cost, respectively, compared to those calculated based on constant physical properties. Also, by optimization of fin types using the genetic algorithm, the results showed a 4.28% and 4.92% reduction in volume and total annual cost, respectively.

Oil production optimization is one of the main targets of reservoir management. Smart well technology gives ability of real time oil production optimization. Although this technology has many advantages; optimum adjustment or sizing of corresponding valves is its issue. In this research optimum sizing of ICDs which are passive control valves has been focused on by designing a neural network to simulate reservoir behavior and applying Particle Swarm Optimization (PSW) algorithm to find optimum port size for ICDs. Indeed; this work eliminates the need for lots of expensive and time consuming iteration through reservoir simulator. The achieved objectives of the work were oil production maximization and water production minimization.

The kinetic study of a pollutant biodegradation is considered as one of the main steps in characterization of a biofilter performance. In this research, an unidentified fungal consortium which had been previously isolated from a compost biofilter treating n-hexane and toluene vapors was used to remove n-hexane in a batch system. To specify the ability of the isolated fungi, the effect of operating temperature and pollutant concentration on the removal process were studied. The hexane concentration in liquid phase varied in the range of 5-25 mg/L and temperature altered between 25-45oC in a central composite design analysis. The optimum conditions for hexane biodegradation obtained at 36.5oC and 8.6 mg/L. The kinetic investigations at 25 and 40oC presented that Haldane, Webb and Yano models could predict the biodegradation well with R2> 0.98. The kinetic parameters of Haldane model at 40oC were Vmax=3.57 (mg/gBiomass.h), Ks=9.57 mg/L, and K1=20.48 mg/L.

In recent years biofiltration has been attended as an alternative method for the treatment of polluted air stream instead of traditional processes. Although temperature is a key factor in this process, biofiltration modeling based on the temperature effect on the reaction kinetics has been rarely considered. In this contribution, a dynamic mathematical model has been presented which takes into account the dispersion in gas phase, diffusion in biofilm, temperature effect, and potential of oxygen limitation in reaction kinetic. Model was calibrated and validated by using an experimental data in which the effect of temperature, intermittent and continuous loading on the biodegradation of n-hexane vapor was investigated Results showed that model well predicted experimental data at intermittent loading in the temperature range of 30-35oC and continuous loading in the temperature range of 35-40oC. Sensitivity analysis showed that at high inlet loads, decreasing bed temperature may change the rate limited biodegradation to the diffusion limited and a part of biofilm become inactive.

A metabolic network comprising central metabolic pathway of Pseudomonas aeruginosa under anaerobic condition was developed to confirm the model accuracy, a comparison between the model prediction and the corresponding experimental results from other works in the literature have been performed. Linear programming was used for this purpose. Objective function was specific growth rate of the microorganism. Base on the model predictions with this objective function, Entenr-Doudoroff and pentose phosphate pathway were both active for the catabolism of glucose. Moreover, the entire reactions of the tricarboxylic acid cycle were not active. Glucose was oxidized via the pentose phosphate pathway when maximization of cofactors ATP and NADPH were the objective of optimization, whereas Entner-Doudoroff was active for maximizing NADH. The model predictions showed a relative error less than 10 percent compare with the experimental results. The small error makes the model reliable for further researches.