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عنوان انگلیسی مقاله:
Insight into simultaneous catalytic oxidation of benzene and toluenein air over the nano-catalyst: Experimental and modeling viaCFD-ANN hybrid method
ترجمه فارسی عنوان مقاله:
بینش به اکسیداسیون همزمان کاتالیزوری هوای بنزن و تولوئنین بر روی نانو کاتالیزور: آزمایش و مدل سازی از طریق روش ترکیبی CCD-ANN
Sciencedirect - Elsevier - Process Safety and Environmental Protection, 141 (2020) 321-332. doi:10.1016/j.psep.2020.05.035
Amin Sokhansanj, S. Majid Abdoli, Mohammad Zabihi∗
tThis study reveals the simultaneous deep oxidation of benzene and toluene over the novel supportedcobalt oxide catalyst derived from metal organic framework (MOF) over the almond shell based activatedcarbon. The performance of the fabricated catalyst was evaluated under the various operating conditionsincluding oxidation temperature, initial concentration of benzene and toluene. The maximum conver-sion of benzene and toluene were also measured to be 89.74 % and 82.37 %, respectively. The samplemorphology was studied by applying XRD, FESEM, BET and TGA analysis. The characterization tests indi-cated that the well dispersed spherical nano-supported catalyst was synthesized with size of less than40 nm. To the best of our knowledge, the computational fluid dynamics (CFD) analysis incorporated withartificial neural network (ANN) was also studied for modeling the deep catalytic oxidation over the pre-pared sample. The modeling involved with the three dimensional analysis of polluted air flow through ofa tubular micro-reactor axial inlet and outlet. The computational fluid dynamics was coded by adoptingCOMSOL Multiphysics to model the catalytic conversion of volatile organic compounds (VOCs) insidethe porous media. The kinetic modeling was also conducted by using three-layer ANN to determine thereaction rates while the reaction temperature, initial concentration of benzene and toluene were consid-ered as the input variables of network. The reaction rates were calculated by a non-linear feed-forwardnetwork with 5 neurons and log-sigmoid function in the hidden layer while the correlation coefficientwas achieved to be 0.99. The validation of CFD model was accomplished which showed the appropriatematching between the experimental data and model achievements. Therefore, the developed intelligenthybrid model (CFD-ANN) in the offered investigation can be a useful tool for studying the fluid dynamicsof VOCs oxidation over the nano-catalyst under the different operating conditions.
Keywords:OxidationMetal organic framework | Computational fluid dynamic | Neural network