a neuro-fuzzy algorithm for modeling of fischer-tropsch synthesis over a bimetallic co/ni/al2o3 catalyst

نویسندگان

paria nikparsa

department of chemistry ali akbar mirzaei

department of chemistry vahide keikhah

department of computer science hossein jistan

department of computer science

چکیده

an alumina supported co/ni catalyst was prepared by sol-gel procedure to study the catalytic behavior during fischer-tropsch synthesis in a fixed-bed reactor. the effect of co conversion (10-50%) on hydrocarbon product distribution (ch4, c5+ and c2-c4 olefin selectivities) was studied. selectivity for ch4 decreased, while those of c5+ and olefin selectivities increased with increasing co conversion. the catalysts properties were characterized at different stages using powder x-ray diffraction (xrd), brunauer-emmett-teller (bet) surface area measurements, and scanning electron microscopy (sem). a neuro-fuzzy model called locally liner model tree (lolimot) was applied to predict the catalytic behavior during fischer-tropsch reaction over the co/ni/al2o3 catalyst. the predicting system was established on co conversion values as a target based on three variables, including partial pressure of co and h2, and h2/co feed ratios as the input. to evaluate the generalization performance of the system, the k-fold cross validation was applied so that an excellent prediction was observed with mean square error (mse) which equals 7.4211e-004. finally, the extrapolation ability of lolimot was perused (beyond the training range). the obtained data from lolimot were compared with the experimental data, and the results indicated that lolimot is a worthy system modeling with high capability for data prediction, both within and beyond the training range.

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عنوان ژورنال:
physical chemistry research

جلد ۳، شماره ۱، صفحات ۷۸-۸۸

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