Modeling Selectivity of Ethylene and Propylene in the Fischer-Tropsch Synthesis with Artificial Neural Network and Response Surface Methodology

Atashi, Hossein; Gholizadeh, Jaber; Tabrizi, Farshad Farshchi; Tayebi, Jaber

doi:10.1002/slct.201600310

Cited by 5 publications

(2 citation statements)

References 25 publications

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“…Atashi et al [19] proposed a kinetic model for the hydrogenation of CO over Fe/Ce catalyst using a fixed-bed microreactor at a range of reaction conditions. The proposed Langmuir-Hinshelwood kinetic mechanism tried about 16 kinetic expressions for the consumption of CO and the interchange among adsorbed molecules of H 2 and CO.…”

Section: Introductionmentioning

confidence: 99%

Maximizing Liquid Fuel Production from Reformed Biogas by Kinetic Studies and Optimization of Fischer–Tropsch Reactions

Al-Zuhairi,

Shakor,

Hamawand

2023

Energies

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In the current work, the operating conditions for the Fischer–Tropsch process were optimized using experimental testing, kinetic modelling, simulation, and optimization. The experiments were carried out using a Ce-Co/SiO2 catalyst to examine how operating parameters affected the conversion of CO and product selectivity. A power-law kinetic model was used to represent the reaction rates in a mathematical model that was created to replicate the Fischer–Tropsch synthesis (FTS). It was decided to estimate the kinetic parameters using a genetic optimization technique. The developed model was validated for a range of operating conditions, including a temperature range of 200–240 °C, a pressure range of 5–25 bar, a H2/CO ratio of 0.5–4, and a space velocity range of 1000–5000 mL/gcat·h. The mean absolute relative error (MARE) between the experimental and predicted results was found to be 11.7%, indicating good agreement between the experimental data and the predicted results obtained by the mathematical model. Optimization was applied to maximize the production of liquid biofuels (C5+). The maximum C5+ selectivity was 91.66, achieved at an operating temperature of 200 °C, reactor total pressure of 6.29 bar, space velocity of 1529.58 mL/gcat·h, and a H2/CO feed ratio of 3.96. The practical implications of the present study are maximizing liquid biofuel production from biomass and municipal solid waste (MSW) as a renewable energy source to meet energy requirements, reducing greenhouse gas emissions, and waste management.

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Section: Introductionmentioning

confidence: 99%

Maximizing Liquid Fuel Production from Reformed Biogas by Kinetic Studies and Optimization of Fischer–Tropsch Reactions

Al-Zuhairi,

Shakor,

Hamawand

2023

Energies

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“…Network methods . Özkara‐Aydıno glu et al studied the α ‐olefin hydrocarbon selectivity of Fe/Cu/K catalysts according to process conditions .…”

Section: Introductionmentioning

confidence: 99%

Modeling Selectivity in the Fischer‐Tropsch Process with Response Surface Methodology

Atashi

Dinarvandi

2018

ChemistrySelect

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In Fischer-Tropsch synthesis, biomass and agricultural residue as a renewable and reliable resource contains carbon, hydrogen and oxygen. Fischer-Tropsch synthesis depends on the carbon structure available resources (coal, biomass, natural gas), which plays an important role in most of the primary energy supply. In this article, the effects of factors affecting the selectivity a model of Fe/Cu/K/Al catalyst for the optimization of products were investigated using statistical method. The statistical method is a relationship between the response process and the independent variable in the selectivity model. The results show, Adj R 2 and R-Sq are significant values in a model used for the optimization of products. Finally, maximizing CO + CO 2 conversion and C 5 + selectivity and minimizing CH 4 , CO, CO 2 , C 2-4 , olefin in C 2-4 selectivity were investigated under best operating conditions.

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Deactivation Model for an Industrial γ‐Alumina Supported Iron Catalyst in the Fischer Tropsch Synthesis

et al. 2019

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In this research, deactivation model of an industrial γ‐alumina‐supported iron catalyst was investigated. Experiments were carried out in a fixed‐bed micro reactor over one‐time and four‐time impregnated catalysts at a reaction temperature of 250 °C, H2/CO ratio of 1, gas hourly space velocity (GHSV) of 3000 h−1, and reaction pressure of 2 bar. Neural networks strategy was used to predict the steady‐state catalytic activity for the ultimate purpose of determining the best deactivation model. Non‐linear regression and statistical analyses showed that the second‐order generalized power‐law equation (GPLE) could adequately described the deactivation behaviors of the considered catalysts. A comparison on the model parameters indicated higher deactivation rate of the four‐time impregnated catalyst, as compared to the one‐time one.

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Modeling Selectivity of Ethylene and Propylene in the Fischer-Tropsch Synthesis with Artificial Neural Network and Response Surface Methodology

Cited by 5 publications

References 25 publications

Maximizing Liquid Fuel Production from Reformed Biogas by Kinetic Studies and Optimization of Fischer–Tropsch Reactions

Maximizing Liquid Fuel Production from Reformed Biogas by Kinetic Studies and Optimization of Fischer–Tropsch Reactions

Modeling Selectivity in the Fischer‐Tropsch Process with Response Surface Methodology

Deactivation Model for an Industrial γ‐Alumina Supported Iron Catalyst in the Fischer Tropsch Synthesis

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