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Seyed Reza Shabanian,Sanaz Edrisi,Fatemeh Vahdat Khoram 한국화학공학회 2017 Korean Journal of Chemical Engineering Vol.34 No.8
Hydrogen production is one of main subjects in fuel cells. The traditional method of synthesis gas production is based on fuel reforming using catalysts. The main problem of these methods is sensitivity and fast degradation of catalysts especially when fuels with high sulfur content are used. A new technique for hydrogen production is fuelreforming using non-catalytic filtration combustion in porous media reactors. Various experimental works have been carried out to increase hydrogen production under different operating conditions such as inlet fuel velocity and equivalence ratio. First, we investigated the ability of adaptive neuro fuzzy inference system (ANFIS) for predicting the filtration combustion characteristics. Four distinct ANFIS models were developed for estimating the hydrogen yield and energy conversion efficiency for fuels of jet A and butanol. Eight different membership functions of dsigmf, gauss2mf, gaussmf, gbellmf, pimf, psigmf, trapmf and trimf were tested for training of the ANFIS networks. The results showed that the RMSE of the best developed ANFIS models for estimating of the hydrogen yield of jet fuel, hydrogen yield of butanol, conversion efficiency of jet fuel and conversion efficiency of butanol were 1.399, 1.213, 0.508 and 2.191, respectively. Moreover the R2 values of 0.998, 0.998, 0.999 and 0.999 were obtained for predicting the above mentioned variables, respectively. In the second step, a novel algorithm based on imperialist competitive algorithm (ICA) was used for optimization of hydrogen yield and energy efficiency. The maximum value of hydrogen yield and energy efficiency was 50.46% and 67.88% for jet A and 47.27% and 96.93% for butanol, respectively. The results showed that the imperialist competitive algorithm is an efficient and powerful algorithm to optimize combustion processes.
CFD Study and RSM Optimization of Acetylene Production in Partial Oxidation Process
Ghayour Maliheh Saravani,Shabanian Seyed Reza 한국화학공학회 2024 Korean Journal of Chemical Engineering Vol.41 No.3
The present study aims to increase the selectivity of C 2 H 2 in the partial oxidation process of methane, employing design of experiments (DOE) and computational fl uid dynamics (CFD). Central composite design is used to design tests, and analysis of variance is performed to evaluate the percentage of contribution of operating factors on system performance. The operating factors considered in the analysis are preheating temperature, O 2 /CH 4 ratio, and inlet velocity. The system responses are selectivity of C 2 H 2 and conversion of CH 4 . Furthermore, an optimization method using response surface methodology is utilized to determine the optimal values of operating factors that lead to the best system performance. The fi ndings indicate that increasing the preheating temperature and O 2 /CH 4 ratio boosts the selectivity of C 2 H 2 and reduces the methane conversion percentage, while increasing the inlet velocity has the opposite eff ect. The optimization method indicates that the maximum selectivity of C 2 H 2 is achieved with conversion of CH 4 of 95% under optimal conditions, namely preheating temperature of 1151.13 K, inlet velocity of 222.8 m/s, and O 2 /CH 4 ratio of 0.59.