European Journal of Chemistry

Neuro-Fuzzy prediction of alumina-supported cobalt vanadate catalyst behavior in the Fischer-Tropsch process



Main Article Content

Mohammad Ali Takassi
Abolfazl Gharibi Kharaji
Morteza Esfandyari
Mehdi Koolivand Salooki

Abstract

Alumina-supported cobalt vanadate multitransition-metal catalyst was prepared by impregnation method. The catalyst was characterized using X-ray diffraction, Fourier transform infrared spectroscopy, Brunauer-Emmett-Teller, X-ray fluorescence and Transmission electron microscopy. The cobalt/vanadium catalyst was employed for Fischer-Tropsch process in an autoclave reactor. The evaluation of this catalyst occurred at different temperature (423-623 K), over a pressure range of 10-50 bars with the Syngas H2/CO ratio varying from 2 to 6. The catalyst gave a high and selective conversion of syngas into methane. The degree of syngas conversion increased with increasing temperature and pressure. The adaptive Neuro-Fuzzy inference system (ANFIS) model has been applied for the training of the fuzzy system and the test set was applied to evaluate the performance of the system including moving average error (MAE), mean square error (MSE), root mean square error (RMSE) and mean absolute percentage error (MAPE). The results exposed that the predicted values from the model were in good agreement with the experimental data.

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Takassi, M. A.; Kharaji, A. G.; Esfandyari, M.; Salooki, M. K. Neuro-Fuzzy Prediction of Alumina-Supported Cobalt Vanadate Catalyst Behavior in the Fischer-Tropsch Process. Eur. J. Chem. 2013, 4, 110-116.

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Supporting Agencies

Iranian Nano Technology Initiative Council and Petroleum University of Technology
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